Siddharth Hariharan, et al v. Adobe Systems, Inc., et al

Filing 10

Filed (ECF) Respondents Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall and Daniel Stover answer to 23f petition. Date of service: 11/18/2013. [8867390] (BPG)

No. 13-80223
In the

United States Court Of Appeals
For the

Ninth Circuit
__________________________

IN RE HIGH-TECH EMPLOYEE ANTITRUST LITIGATION

_________________________
Petition for permission to appeal
from the United States District Court
Northern District of California
The Honorable Lucy H. Koh, Presiding
Case No. 5:11-2509-LHK
SUPPLEMENTAL EXCERPTS OF RECORD
Vols. I-VI
LIEFF CABRASER HEIMANN
& BERNSTEIN, LLP
Kelly M. Dermody
Brendan P. Glackin
Dean M. Harvey
275 Battery Street, 29th Floor
San Francisco, CA 94111-3339
Telephone: [phone]
Facsimile: 415.956.1008

JOSEPH SAVERI LAW FIRM
Joseph R. Saveri
Joshua P. Davis
Lisa J. Leebove
James G. Dallal
505 Montgomery Street, Suite 625
San Francisco, California 94111
Telephone: [phone]
Facsimile: 415.500.6803

Co-Lead Class Counsel

1141390.1

In re High-Tech Employees Antitrust Litigation
Case No. 11-2509
SUPPLEMENTAL EXCERPTS OF THE RECORD
Table of Contents
Docket Entry

Document Title

Vol.

Page

1

1

2

163

Expert Report of Edward E. Leamer, PH.D.
Reply Expert Report of Edward E. Leamer,
PH.D.
Supplemental Expert Report of Edward E.
Leamer, PH.D
Rebuttal Supplmental Expert Report of Edward
E. Leamer, PH.D

3

317

3

398

3

464

3

526

Expert Witness Report of Kevin F. Hallock
Exhibit 71 of Declaration of Anne Shaver in
Support of Motion for Class Certification
(Dept. of Justice Competitive Impact
Statement)

4

566

4

686

Opposition to Plaintiffs' Motion for Class
Certification, Case No. 12-80188
4
Order Denying Costco's 23(f) Petition
4
UNDER SEAL SUPPLEMENTAL EXCERPTS OF RECORD

715
718

PUBLIC SUPPLEMENTAL EXCERPTS OF RECORD
494
321
518-1
518-5
424-4
470-1
424-1

188-10
209
5

Transcript of Proceedings before the
Honorable Lucy H. Koh - August 8, 2013
Transcript of Proceedings before the
Honorable Lucy H. Koh - January 17, 2013

Expert Report of Edward E. Leamer, PH.D.
Reply Expert Report of Edward E. Leamer,
PH.D.
Supplemental Expert Report of Edward E.
Leamer, PH.D
Rebuttal Supplemental Expert Report of
Edward E. Leamer, PH.D

5

719

5

839

5

905

5

967

Expert Witness Report of Kevin F. Hallock

6

1009

Docket Report

6

1129

Certificate of Service

6

1

1

UNITED STATES DISTRICT COURT

2

NORTHERN DISTRICT OF CALIFORNIA

3

SAN JOSE DIVISION

4
5
6
7
8
9

IN RE: HIGH-TECH EMPLOYEE
ANTITRUST LITIGATION,
_________________________
THIS DOCUMENT RELATES TO:
ALL ACTIONS
_________________________

)
)
)
)
)
)
)
)

C-11-02509 LHK
SAN JOSE, CALIFORNIA
AUGUST 8, 2013
PAGES 1-161

10
11

TRANSCRIPT OF PROCEEDINGS
BEFORE THE HONORABLE LUCY H. KOH
UNITED STATES DISTRICT JUDGE

12
A P P E A R A N C E S:
13
FOR THE PLAINTIFFS:
14
15
16
17
18
19
20
21
22
23

JOSEPH SAVERI LAW FIRM
BY: JOSEPH SAVERI
LISA J. LEEBOVE
JAMES G. DALLAL
255 CALIFORNIA STREET, SUITE 450
SAN FRANCISCO, CALIFORNIA 94111
LIEFF, CABRASER,
HEIMANN & BERNSTEIN
BY:
KELLY M. DERMODY
BRENDAN P. GLACKIN
DEAN M. HARVEY
ANNE B. SHAVER
LISA J. CISNEROS
275 BATTERY STREET, 30TH FLOOR
SAN FRANCISCO, CALIFORNIA 94111

APPEARANCES CONTINUED ON NEXT PAGE
OFFICIAL COURT REPORTER:

LEE-ANNE SHORTRIDGE, CSR, CRR
CERTIFICATE NUMBER 9595

24
25

PROCEEDINGS RECORDED BY MECHANICAL STENOGRAPHY
TRANSCRIPT PRODUCED WITH COMPUTER

UNITED STATES COURT REPORTERS

1

2

1

APPEARANCES (CONTINUED)

2

FOR DEFENDANT
GOOGLE:

3
4

KEKER & VAN NEST
BY: ROBERT A. VAN NEST
DANIEL E. PURCELL
JUSTINA K SESSIONS
633 BATTERY STREET
SAN FRANCISCO, CALIFORNIA

94111

5
MAYER BROWN
BY: LEE H. RUBIN
TWO PALO ALTO SQUARE, SUITE 300
PALO ALTO, CALIFORNIA 94306

6
7
8

FOR DEFENDANT
APPLE:

9
10
11
12
13

O'MELVENY & MYERS
BY: GEORGE A. RILEY
MICHAEL F. TUBACH
CHRISTINA J. BROWN
TWO EMBARCADERO CENTER
28TH FLOOR
SAN FRANCISCO, CALIFORNIA

94111

FOR DEFENDANTS
ADOBE AND
INTUIT:

JONES DAY
BY: DAVID C. KIERNAN
LIN W. KAHN
CRAIG E. STEWART
555 CALIFORNIA STREET, 26TH FLOOR
SAN FRANCISCO, CALIFORNIA 94104

FOR DEFENDANT
INTEL:

BINGHAM MCCUTCHEN
BY: DONN P. PICKETT
FRANK HINMAN
SUJAL SHAH
THREE EMBARCADERO CENTER
SAN FRANCISCO, CALIFORNIA

14
15
16
17
18

94111

19
20
21

FOR DEFENDANT
PIXAR:

COVINGTON & BURLING
BY: EMILY J. HENN
333 TWIN DOLPHIN DRIVE, SUITE 700
REDWOOD SHORES, CALIFORNIA 94065

22
23
24
25

UNITED STATES COURT REPORTERS

2

3

1

SAN JOSE, CALIFORNIA

2
3
4
5
6
7

AUGUST 8, 2013
P R O C E E D I N G S

(COURT CONVENED AND THE FOLLOWING PROCEEDINGS WERE HELD:)
THE CLERK:

CALLING CASE NUMBER C-11-02509 LHK, IN

RE: HIGH-TECH EMPLOYEE ANTITRUST LITIGATION.
MR. GLACKIN:

BRENDAN GLACKIN, LEIFF, CABRASER,

HEIMANN & BERNSTEIN ON BEHALF OF THE PLAINTIFFS.

8

MS. DERMODY:

GOOD AFTERNOON, YOUR HONOR.

9

KELLY DERMODY, LEIF, CABRASER.

AND THE OTHER LEIF, CABRASER

10

PEOPLE WITH US ARE MY PARTNER, DEAN HARVEY, AND ASSOCIATES

11

ANNE SHAVER AND LISA CISNEROS.

12
13

AND ALSO IN THE COURTROOM TODAY ARE NAMED PLAINTIFFS,
BRANDON MARSHAL AND MIKE DEVINE.

14

THE COURT:

15

MR. SAVERI:

16

JOSEPH SAVERI.

17

OKAY.
GOOD AFTERNOON, YOUR HONOR.

WITH ME FROM MY OFFICE ARE LISA LEELOVE AND

JAMES DALLAL.

18

THE COURT:

OKAY.

19

MR. VAN NEST:

GOOD AFTERNOON, YOUR HONOR.

20

BOB VAN NEST FROM KEKER & VAN NEST FOR GOOGLE.

21

I'M HERE WITH

DAN PURCELL AND TINA SESSIONS.

22

ALSO, LEE RUBIN FROM MAYER BROWN.

23

AND I'VE BEEN ASKED TO SPEAK ON BEHALF OF ALL DEFENDANTS

24
25

THIS AFTERNOON.
MR. RILEY:

GOOD AFTERNOON, YOUR HONOR.

UNITED STATES COURT REPORTERS

GEORGE RILEY

3

4

1

OF O'MELVENY & MYERS FOR APPLE.

2

CHRISTINA BROWN AND MICHAEL TUBACH.

3

THE COURT:

4

MR. PICKETT:

5

OKAY.

I'M JOINED BY MY COLLEAGUES

GOOD AFTERNOON.

GOOD AFTERNOON.

DONN PICKETT.

HERE ALONG WITH FRANK HINMAN AND SUJAL SHAH FOR INTEL.

6

THE COURT:

7

MR. KIERNAN:

OKAY.

GOOD AFTERNOON.

GOOD AFTERNOON, YOUR HONOR.

8

DAVID KIERNAN OF JONES DAY ON BEHALF OF ADOBE.

9

TODAY IS LIN KAHN.

10

BECAUSE OF TRIAL ON ANOTHER MATTER.
THE COURT:

12

MR. KIERNAN:

13

THE COURT:

15

OKAY.

18

OKAY.

MR. KIERNAN AND?

I'M SORRY.

AND LIN KAHN.

OKAY.

THANK YOU.

AND THERE'S NO ONE HERE FOR LUCASFILM, PIXAR, AND

INTUIT; CORRECT?

16
17

HERE WITH ME

BOB MITTELSTAEDT COULDN'T BE HERE TODAY

11

14

I'M

MS. HENN:
BURLING.

YOUR HONOR, EMILY HENN, COVINGTON &

I'M HERE FOR THE CMC FOR PIXAR.
THE COURT:

OKAY.

WOULD YOU MIND IF WE DID THAT AT

19

THE END, OR WOULD YOU LIKE TO DO THAT AT THE BEGINNING?

20

THAT OKAY IF IT'S AT THE END?

21

MS. HENN:

22

MR. STEWART:

23
24
25

IS

YES.
YOUR HONOR, CRAIG STEWART.

I'M HERE ON

BEHALF OF INTUIT.
THE COURT:

OKAY.

ALL RIGHT.

WELL, GOOD AFTERNOON

TO EVERYONE.

UNITED STATES COURT REPORTERS

4

5

1
2
3
4

SO ACTUALLY THE FIRST QUESTION WOULD GO TO INTUIT,
LUCASFILM, AND PIXAR, AS WELL AS THE PLAINTIFFS.
WHEN DO YOU ANTICIPATE FILING YOUR MOTION FOR PRELIMINARY
APPROVAL?

5

MS. DERMODY:

WELL, YOUR HONOR, WE ARE HEAVILY IN THE

6

PROCESS OF TRYING TO DOCUMENT THAT AGREEMENT, AND WITH THE

7

ADDITION OF THE INTUIT SETTLEMENT, WE HAVE ANOTHER FAMILY TO

8

DEAL WITH IN FIGURING OUT THE BEST PROCESS.

9
10

WE'RE HOPING TO DO THAT VERY, VERY SOON.
HARD TO ACCOMPLISH THAT, YOUR HONOR.

11
12
13

WE'RE WORKING

THE COURT:

CAN WE SET A DEADLINE BY WHICH THAT WILL

BE DONE?
MR. SAVERI:

I THINK THERE ARE PROBABLY TWO THINGS WE

14

WOULD NEED TO DO:

15

APPROVAL PAPERS; AND THEN WE WOULD LIKE TO COME IN AS SOON AS

16

POSSIBLE AND HAVE THE HEARING ON PRELIMINARY APPROVAL.

17

SET A DEADLINE FOR FILING THE PRELIMINARY

THE COURT:

WELL, I HAVE SOME POSSIBLE HEARING DATES

18

FOR YOU, SO I NEED TO KNOW WHEN YOU'RE GOING TO FILE AND WE CAN

19

GO FROM THERE.

20

MS. DERMODY:

21

THE COURT:

22

MS. DERMODY:

23

THE COURT:

24
25

WHAT DO YOU HAVE, YOUR HONOR?

SO -THAT MIGHT GIVE US A TARGET.

WELL, OCTOBER 3RD, NOVEMBER 21,

DECEMBER 19, JANUARY 9, FEBRUARY 13, FEBRUARY 20.
MR. SAVERI:

YOUR HONOR, CAN THE -- IS THERE ANY WAY

UNITED STATES COURT REPORTERS

5

6

1

TO GET IN EARLIER THAN THAT FOR THE PRELIMINARY APPROVAL

2

HEARING?

3
4
5

THE COURT:

EARLIER THAN OCTOBER 3?

WHEN ARE YOU

GOING TO FILE?
MS. HENN:

YOUR HONOR, I THINK THAT WOULD BE

6

AGGRESSIVE IN LIGHT OF WHERE WE ARE AT THIS POINT IN TIME, SO I

7

THINK WE WOULD SUPPORT A DATE NO EARLIER THAN OCTOBER.

8

THE COURT:

WELL, HOW QUICKLY ARE YOU GOING TO FILE?

9

MR. SAVERI:

WELL, THE -- I DON'T -- I'M HOPING,

10

MAYBE I'M OVERLY OPTIMISTIC, THAT WE'LL HAVE THE DOCUMENTATION

11

DONE IN A COUPLE WEEKS AND WE WOULD PREPARE -- BE PREPARED TO

12

FILE SHORTLY THEREAFTER.

13
14
15

THE PRELIMINARY APPROVAL HEARING IS GOING TO BE UNOPPOSED.
THE COURT:

SO THERE HAVE BEEN NO EXCHANGES OF DRAFTS

YET OF FINAL DOCUMENTS?

16

MR. SAVERI:

17

MR. STEWART:

18

NO, WE HAVE EXCHANGED DOCUMENTS.
NOT WITH INTUIT, YOUR HONOR.

WE

HAVEN'T RECEIVED THE SETTLEMENT DOCUMENTS YET.

19

THE COURT:

20

MS. HENN:

I SEE.

WHAT ABOUT PIXAR AND LUCASFILM?

WE'VE RECEIVED ONE DOCUMENT, BUT THERE ARE

21

MANY DOCUMENTS THAT WE HAVEN'T SEEN, AND IT TOOK A WHILE TO GET

22

THE FIRST DOCUMENTS.

23
24
25

SO WE DO THINK THIS IS GOING TO TAKE SOME TIME AND
SHOULDN'T BE RUSHED.
THE COURT:

OKAY.

SO GIVE ME A DEADLINE THAT SEEMS

UNITED STATES COURT REPORTERS

6

7

1

REALISTIC FOR FILING THE MOTION, AND THEN YOU CAN PICK ANY OF

2

THESE DATES FOR THE HEARING.

3

MS. DERMODY:

IF WE'RE WORKING FROM OCTOBER 3RD, YOUR

4

HONOR, I THINK THE REAL QUESTION THEN IS HOW MUCH TIME DO YOU

5

THINK YOUR HONOR WOULD LIKE TO HAVE WITH THE PAPERS BEFORE THE

6

HEARING?

7

SO THERE WON'T BE ANY ADDITIONAL FILINGS, PRESUMABLY, AFTER THE

8

MOTION FOR PRELIMINARY APPROVAL, AND IT'S REALLY ABOUT THE

9

COURT'S CONVENIENCE.

10
11

BECAUSE AS MR. SAVERI SAID, IT WILL BE UNCONTESTED,

THE COURT:

WELL, I NEED A MINIMUM OF TWO WEEKS,

MINIMUM.

12

MS. DERMODY:

13

THE COURT:

14

MS. DERMODY:

15

YES?

SO SEPTEMBER 19?

THAT WOULD BE THE LAST POSSIBLE DATE.
I THINK THAT SOUNDS ACHIEVABLE.

SOUND RIGHT FOR YOU ALL?

16

MS. HENN:

17

YES, YOUR HONOR.

THE COURT:

I THINK SEPTEMBER 12TH WOULD BE EVEN

18

BETTER, BUT I'LL TAKE THE 19TH.

19

MS. DERMODY:

20

MR. SAVERI:

THANK YOU, YOUR HONOR.
I THINK WE'D LIKE TO GET IT DONE AS SOON

21

AS WE CAN AND GET THE MOTIONS ON FILE AND GIVE THE COURT AS

22

MUCH TIME AS WE CAN WITH THE PAPERS.

23
24
25

THE COURT:

UM-HUM.

WHY DON'T WE SAY SEPTEMBER 16TH?

IS THAT OKAY?
MS. HENN, DOES THAT GIVE YOU ENOUGH TIME, OR -- IF YOU WANT

UNITED STATES COURT REPORTERS

7

8

1

UNTIL THE 19TH, THAT'S FINE.

2

MS. HENN:

3

THE COURT:

4

THREE, RIGHT?

SEPTEMBER 19TH WOULD BE BETTER.
OKAY.

MS. HENN:

6

MS. DERMODY:

7

THE COURT:
SEPTEMBER 19TH.

9
10

YES.

MS. DERMODY:

WILL THAT BE 1:30 OR 2:00 O'CLOCK, YOUR

HONOR?

12

MS. DERMODY:

13

THE COURT:

1:30.
THANK YOU.

OKAY.

NOW, ARE THERE ANY OTHER

NEGOTIATIONS WITH OTHER REMAINING DEFENDANTS?

15

17

SO FILE THE MOTION BY

IT WILL BE HEARD ON OCTOBER THE 3RD.

THE COURT:

16

YES.

OKAY.

11

14

SO FILE YOUR -- ALL

ALL THREE?

5

8

ALL RIGHT.

MR. SAVERI:

OR NOT?

WELL, YOUR HONOR, WE WENT TO A MEDIATION

ON WHICH WE REPORTED AND THAT MEDIATION IS NOW CONCLUDED.
SO --

18

THE COURT:

19

DON'T WANT ANY DETAIL, BUT --

20

MR. SAVERI:

21
22
23

THERE'S NO FURTHER EFFORTS?

I MEAN, I

I GUESS I WANT TO BE CAREFUL ABOUT THAT.

THERE'S REALLY NOTHING ELSE THAT I CAN REPORT RIGHT NOW.
THE COURT:

OKAY.

COULD I SET JUST A SETTLEMENT

STATUS REPORT DATE FOR A WEEK FROM NOW?

24

MS. DERMODY:

25

THE COURT:

OR --

SURE, YOUR HONOR.

WHAT MAKES SENSE?

I DON'T KNOW IF THE

UNITED STATES COURT REPORTERS

8

9

1
2
3

HEARING IS GOING TO MAKE A DIFFERENCE.
MR. VAN NEST:

YOUR HONOR, THIS IS BOB VAN NEST.

I DON'T THINK ANYTHING WILL CHANGE IN A WEEK.

I THINK, AS

4

MR. SAVERI PUT IT QUITE CORRECTLY, THE MEDIATION OCCURRED, IT'S

5

OVER, AND NOTHING IS HAPPENING.

6

THE COURT:

7

MR. VAN NEST:

8
9
10
11

OKAY.
WITH RESPECT TO THE FOUR REMAINING

DEFENDANTS, NOTHING IS GOING TO CHANGE IN THE NEXT WEEK.
THE COURT:

OKAY.

WHAT ABOUT THE NEXT TWO WEEKS,

THREE WEEKS?
MR. VAN NEST:

I THINK IF YOU SET IT OUT A MONTH,

12

THEN FINE, WE'LL SUBMIT A REPORT AND PERHAPS SOMETHING WILL

13

HAPPEN IN THAT PERIOD OF TIME.

14

THAT'S FINE.

OR SET IT FOR THE 19TH AND WE'LL FILE SOMETHING ALONG WITH

15

THE OPENING PAPERS.

16

THE COURT:

OKAY.

LET ME ASK -- I MEAN, OBVIOUSLY

17

YOU MAY NOT KNOW AND YOU HAVE TO CONSULT WITH CLIENTS, BUT DO

18

YOU NEED A RULING ON THE MOTION?

19

SUMMARY JUDGMENT RULING?

20

DO YOU THINK THE PARTIES NEED FOR THE REMAINING FOUR

21

DEFENDANTS?

22
23

MR. SAVERI:

OR DO YOU THINK YOU NEED A

WHAT -- WHAT ADDITIONAL INFORMATION

YOUR HONOR, JUST SPEAKING FOR MYSELF, I

THINK WE CAN --

24

THE COURT:

25

MR. SAVERI:

UM-HUM.
-- I DON'T THINK WE NEED TO SET IT AT

UNITED STATES COURT REPORTERS

9

10

1

ANY PARTICULAR MILESTONE.

2

THE COURT:

3

UM-HUM.

MR. SAVERI:

I THINK, FROM THE PLAINTIFFS'

4

PERSPECTIVE, WE'RE READY TO TALK.

5

APPROPRIATE TO DO ANOTHER ROUND OF MEDIATION, I THINK WE'D BE

6

WILLING TO DO THAT.

7

THE COURT:

8

MR. SAVERI:

9
10

WE'RE -- IF IT WAS

UM-HUM.
TO ME I THINK IT'S IMPORTANT TO KEEP

TALKING ALL THE TIME, SO I'D LIKE TO KEEP THE COMMUNICATION
GOING.

11

SO I DON'T -- TO ANSWER YOUR QUESTION DIRECTLY, I DON'T

12

THINK WE SHOULD PUT IT OFF UNTIL SUMMARY JUDGMENT OR RULING ON

13

THE CLASS.

14
15

I MEAN, OBVIOUSLY EVERYBODY IS INTERESTED TO KNOW WHAT'S
GOING TO HAPPEN AS A RESULT OF TODAY OR --

16

THE COURT:

UM-HUM.

17

MR. SAVERI:

18

THE COURT:

19

MR. VAN NEST:

20

THE COURT:

-- DOWN THE ROAD.
UM-HUM.

LET ME HEAR FROM MR. --

MR. VAN NEST.

THANK YOU, YOUR HONOR.

OF COURSE I WAS GOING TO SAY THAT.

21

WHAT DO YOU THINK?

22

MR. VAN NEST:

23

OBVIOUSLY CLASS CERT IS A VERY

IMPORTANT MILESTONE.

24

THE COURT:

UH-HUH.

25

MR. VAN NEST:

OBVIOUSLY IF WE GO PAST THAT, SUMMARY

UNITED STATES COURT REPORTERS

10

11

1

JUDGMENT IS AN IMPORTANT MILESTONE.

2

BUT I AGREE WITH MR. SAVERI.

THERE'S NOTHING MAGIC ABOUT

3

ANY PARTICULAR TIME.

I JUST THINK IT'S UNLIKELY THAT ANYTHING

4

WILL HAPPEN BEFORE YOU RULE ON CLASS CERT.

5

THE COURT:

I SEE.

6

MR. VAN NEST:

I'M NOT SAYING ANYTHING WOULD HAPPEN

7

AFTER THAT, EITHER, BUT I DON'T THINK ANYTHING WILL HAPPEN

8

UNTIL THEN.

9

THE COURT:

10

UNTIL THERE'S AN ACTUAL RULING?

MR. VAN NEST:

A RULING OR AN INDICATION FROM YOUR

11

HONOR AS TO WHAT THE RULING WILL BE, YES.

12

ANYTHING IS LIKELY TO HAPPEN IN THAT PERIOD.

13

I DON'T THINK

ON THE OTHER HAND, IF MR. SAVERI WANTS TO TALK, THAT'S

14

FINE.

WE CAN CERTAINLY SUBMIT A REPORT ON THE 19TH.

15

WON'T TAX ANYBODY.

16

THE COURT:

17

MR. VAN NEST:

18

THE COURT:

THAT

UM-HUM.
AND THEN YOU'LL KNOW.

ALL RIGHT.

WELL, TELL ME, WITH REGARD

19

TO -- ONCE A RULING IS ISSUED, WHAT'S GOING TO HAPPEN?

20

SAY I CERTIFY A CLASS.

21

AT THAT POINT?

22

MS. DERMODY:

23

LET'S

DO YOU WANT TO HAVE ANOTHER ADR SESSION

YOUR HONOR, ACTUALLY.

24
25

THE COURT:

I THINK THAT WOULD BE VERY HELPFUL,

LET ME SEE IF THE DEFENDANTS ARE WILLING.

IS THAT SOMETHING THAT YOU'D BE WILLING TO DO AT THAT

UNITED STATES COURT REPORTERS

11

12

1
2
3

POINT?
MR. VAN NEST:
CONSIDER ADR.

4

THE COURT:

5

MR. VAN NEST:

6

UM-HUM.

THE COURT:

8

MR. VAN NEST:

10
11
12
13
14
15

AS I SAID, I THINK IT'S UNLIKELY

ANYTHING WOULD HAPPEN BEFORE YOUR RULING ON CLASS CERT.

7

9

YOUR HONOR, WE'RE ALWAYS WILLING TO

OKAY.
WE OBVIOUSLY FEEL STRONGLY ABOUT THAT

ISSUE, AS WE'RE GOING TO BE DISCUSSING IN A MOMENT.
SO I DO THINK, THOUGH, THAT ADR BEFORE THAT TIME WOULD NOT
BE PRODUCTIVE.

I DO AGREE WITH YOU THERE.

THE COURT:
CERTIFY A CLASS.

OKAY.

ALL RIGHT.

LET'S SAY I DON'T

AT THAT POINT?

MR. VAN NEST:

I THINK THE SAME THING.

THAT'S AN

IMPORTANT MILESTONE FOR ALL OF US AND --

16

THE COURT:

ALL RIGHT.

17

MR. VAN NEST:

18

THE COURT:

19

MR. VAN NEST:

20

THE COURT:

-- TALKING AFTER THAT WOULD BE --

WOULD MAKE SENSE?
-- WORTHWHILE, YES.

OKAY.

WELL, I WOULD LIKE TO, BECAUSE IT

21

SOUNDS LIKE EITHER WAY THERE'S -- EITHER WAY IT SEEMS LIKE A

22

FURTHER ADR SESSION MIGHT BE HELPFUL AFTER A RULING.

23
24
25

SO CAN I GO AHEAD AND REFER YOU NOW AND SET A LONG ENOUGH
LEAD TIME THAT YOU'RE ABLE TO MEET THAT DEADLINE?
ASSUMING -- LET'S SAY ASSUMING YOU GET A RULING, I DON'T

UNITED STATES COURT REPORTERS

12

13

1

KNOW, IN THE NEXT MONTH.

2

MR. VAN NEST:

3

THE COURT:

4
5

HOW MUCH TIME WOULD YOU NEED FOR ADR?
TO GET READY FOR ADR?

AND TO COMPLETE IT, BECAUSE I'LL SET A

DEADLINE -MS. DERMODY:

THE PROBLEM IS THE MEDIATORS'

6

SCHEDULES, YOUR HONOR.

7

THROUGH THIS, ALL OF US, COLLECTIVELY TRYING TO GET DATES.

8

THE COURT:

9

THE VERY GOOD MEDIATORS -- WE WENT

MS. DERMODY:

10
11

SURE.
AND IT WAS UNBELIEVABLE TO GET DATES

OVER A FOUR MONTH PERIOD.
SO WE MAY ALL HAVE GOOD WILL ABOUT WHEN WE COULD DO IT AND

12

HAVE AVAILABILITY.

13

BE THE SCHEDULE, WHEN THE RULING WILL COME OUT, AND WHEN YOU

14

WOULD LIKE US TO COMPLETE ADR, WE CAN CALL TODAY TO FIND OUT

15

SCHEDULES AND SEE IF WE CAN GET OURSELVES ON A CALENDAR JUST TO

16

HAVE THAT BOOKED.

17

SO THE SOONER WE KNOW WHAT YOU THINK WILL

MR. VAN NEST:

YOUR HONOR, IF YOU GAVE US 90 DAYS

18

FROM THE RULING, I THINK WE WOULD BE ABLE TO GET IN AND OUT OF

19

THE MEDIATION.

20

THE COURT:

21

MR. SAVERI:

UM-HUM.
MY CONCERN, THOUGH, YOUR HONOR, IS THAT

22

EVEN IF YOU WERE TO SAY TODAY, "I WANT YOU TO GO TO MEDIATION,"

23

GIVEN THE WAY THE MEDIATORS' CALENDARS GO AND SCHEDULING, IT

24

WOULD BE, I MEAN, 60 OR 90 DAYS BEFORE WE COULD PROBABLY GET IN

25

FRONT OF A MEDIATOR IF THE PAST IS AN INDICATOR.

UNITED STATES COURT REPORTERS

13

14

1

SO I'M A LITTLE WORRIED THAT -- IF YOUR HONOR WANTS US TO

2

GET IN AND DO IT, I THINK WE NEED TO -- IT WOULD BE USEFUL TO

3

HAVE SOME PARAMETERS.

4

I THINK A LOT OF IT DEPENDS ON WHEN YOU RULE AND THAT'S --

5

THE COURT:

UM-HUM.

WELL, I AM TARGETING GETTING AN

6

ORDER OUT BY THE END OF THIS MONTH OR EARLY SEPTEMBER AT THE

7

LATEST, BUT PREFERABLY THE END OF AUGUST.

8
9
10
11

SO UNDERSTANDING THAT'S THE CASE, I WOULD SUGGEST YOU GO
AHEAD AND JUST ASSUME ANY DAY AFTER LABOR DAY IS FAIR GAME FOR
A MEDIATION AND JUST GO AHEAD AND SCHEDULE ONE.
CAN I THEN SET YOU ON A NOVEMBER 15TH DEADLINE?

12

MR. VAN NEST:

13

MS. DERMODY:

14

MR. VAN NEST:

15

THE COURT:

SURE.
THAT MAKES SENSE, YOUR HONOR.
THAT'S FINE, YOUR HONOR.

ALL RIGHT.

SO THEN THE REMAINING

16

DEFENDANTS WILL HAVE ANOTHER PRIVATE MEDIATION SESSION TO BE

17

COMPLETED BY NOVEMBER 15TH OF 2013.

18

MR. SAVERI:

19

THE COURT:

OKAY.

YOUR HONOR -SO YOU'RE SAYING, MR. VAN NEST, THAT YOU

20

DON'T THINK THAT THERE WILL BE ANY FURTHER SETTLEMENTS ABSENT

21

ANOTHER MEDIATION SESSION?

22

MR. VAN NEST:

23

THE COURT:

24
25

THAT'S RIGHT.

SO GETTING AN INTERIM SETTLEMENT STATUS

REPORT -MR. VAN NEST:

NOT MEANINGFUL.

UNITED STATES COURT REPORTERS

14

15

1

THE COURT:

IF YOU WERE GOING TO RESOLVE THE CASE, I

2

WOULDN'T HAVE TO ISSUE THE ORDER.

3

GOING TO HAPPEN?

4
5

MS. DERMODY:

BUT YOU KNOW THAT'S NOT

YOU KNOW, YOUR HONOR, WE'LL LET YOU

KNOW IF SOMETHING ELSE --

6

MR. VAN NEST:

7

THE COURT:

8

MR. VAN NEST:

9

MR. SAVERI:

ALL RIGHT.
IF YOU SET THE DEADLINE, WE'LL

COMPLETE IT BY THEN.

10

IT'S NOT MEANINGFUL.

I WOULD HOPE, YOUR HONOR, THAT WE -- YOU

11

KNOW, WE WENT THROUGH MEDIATION SESSIONS, WE ESSENTIALLY

12

ACCOMPLISHED THE SETTLEMENTS WE DID WITH BILATERAL NEGOTIATIONS

13

BETWEEN THE PLAINTIFFS AND THE DEFENDANTS.

14
15

SO I WOULD HOPE THAT WE'D BE ABLE TO CONTINUE THAT AND NOT
JUST WAIT FOR THE MEDIATION SESSION TO TRY TO NARROW THIS.

16
17

THE COURT:

PLEASE.

MONEY --

18

MR. VAN NEST:

19

THE COURT:

20
21

I MEAN, SAVE YOURSELVES THE

ABSOLUTELY.

-- AND JUST DO IT YOURSELVES.

OKAY,

YEAH, PLEASE.
MR. SAVERI:

AND, YOUR HONOR, I GUESS THE OTHER THING

22

I WOULD SAY IS THAT FROM MY PERSPECTIVE, I THINK IT IS -- IT IS

23

USEFUL TO HAVE DECISION MAKERS TO BE PRESENT AND INVOLVED AT

24

THE MEDIATION, AND I THINK IF WE'RE GOING TO DO THIS SERIOUSLY

25

THE NEXT TIME, FROM MY PERSPECTIVE, IT WOULD BE USEFUL TO HAVE

UNITED STATES COURT REPORTERS

15

16

1

A COMMITMENT FROM ALL SIDES THAT PEOPLE WITH AUTHORITY AND

2

DECISION MAKING POWER ARE GOING TO BE ACTIVE PARTICIPANTS ON

3

THE DAY OF THE MEDIATION.

4
5
6

THE COURT:

HOW WERE THEY AVAILABLE LAST TIME?

JUST

BY PHONE, OR -MR. SAVERI:

FROM WHAT I UNDERSTAND, AND THE OTHER

7

SIDE CAN SPEAK TO THIS, THERE WERE IN-HOUSE COUNSEL REPRESENTED

8

AT THE MEDIATION, BUT THAT WAS -- THAT WAS IT.

9
10

THE COURT:

BUT THEY MUST HAVE HAD SETTLEMENT

AUTHORITY UP TO A CERTAIN NUMBER.

11

MR. SAVERI:

12

ANYTHING ABOUT THAT.

13

I DON'T KNOW ANYTHING -- I DON'T KNOW

MR. VAN NEST:

WE HAD PEOPLE THERE, YOUR HONOR, WITH

14

SETTLEMENT AUTHORITY, AND WE WILL AGAIN, AND I UNDERSTAND

15

THAT'S THE BASELINE, OF COURSE.

16

BUT AS MR. SAVERI SAYS -- AND I UNDERSTAND WHAT HE SAYS IS

17

TRUE -- SOME OF THE NEGOTIATIONS OCCURRED JUST BETWEEN THE

18

LAWYERS AND THAT'S WHAT ULTIMATELY GOT IT DONE --

19

THE COURT:

UM-HUM.

20

MR. VAN NEST:

21

THE COURT:

22

MR. VAN NEST:

23

THE COURT:

-- FOR THE ONES THAT SETTLED.

UM-HUM.
SO UNDERSTOOD.

OKAY.

ALL RIGHT.

NOW, LET ME ASK, FOR

24

ANTITRUST IMPACT, DO WE NEED TO CONSIDER NOW THE ALLEGATIONS

25

THAT YOU MADE AGAINST LUCASFILM, PIXAR, AND ADOBE -- AND

UNITED STATES COURT REPORTERS

16

17

1

INTUIT?

DO WE STILL NEED TO -- I KNOW BOTH SIDES BELIEVE THAT

2

THERE'S NO IMPACT FROM THE THREE DEFENDANTS SETTLING, BUT TELL

3

ME WHAT IS THERE, IF ANY, IMPACT ON WHETHER WE STILL LOOK AT

4

THE DEPOSITION TESTIMONY AND THE EVIDENCE OF THOSE THREE

5

COMPANIES AS PART OF THE ANALYSIS IN THIS MOTION.

6

MR. VAN NEST:

7

THE COURT:

8

MR. VAN NEST:

9

I THINK, YOUR HONOR --

WHAT DO WE DO WITH THAT?
I THINK THEY ESSENTIALLY DROP OUT.

BUT THEY'RE A SMALL PART OF THE GROUP.

I MEAN, THE THREE

10

TOGETHER EMPLOY LESS THAN 8 PERCENT OF THE EMPLOYEES IN THE

11

PROPOSED CLASS.

12

SO I THINK THE REAL FOCUS NOW IS ON THE REMAINING

13

DEFENDANTS AND THE -- AND WHATEVER AGREEMENTS THEY'RE ABLE TO

14

PROVE AS BETWEEN AND AMONG THEM.

15

BUT EITHER WAY, I THINK BOTH OF US SAID IN THE STATUS

16

CONFERENCE STATEMENTS, THE SETTLEMENTS DON'T CHANGE ANYTHING,

17

IN PART BECAUSE THE THREE SETTLING DEFENDANTS WERE A VERY SMALL

18

PART OF THIS TO BEGIN WITH.

19

CLASS MEMBERS ARE EMPLOYED BY ALL THREE COMBINED.

20

AS I SAID, LESS THAN 8 PERCENT OF

SO THE LARGEST PART OF THE CASE IS STILL BEFORE YOUR HONOR

21

AND THE CONDUCT THAT I THINK YOU'LL BE FOCUSSING ON IS THE

22

CONDUCT OF THE FOUR REMAINING DEFENDANTS, NOT THOSE THAT HAVE

23

SETTLED OUT.

24
25

THE COURT:

BUT WHY WOULDN'T THE COMMENTS OF

MR. CATMULL AND MR. LUCAS STILL BE RELEVANT TO --

UNITED STATES COURT REPORTERS

17

18

1

MR. VAN NEST:

2

THE COURT:

3

THEY MIGHT HAVE SOME --

-- THE ANTITRUST CONSPIRACY, HOW THE

AGREEMENTS WERE ENFORCED, HOW THEY WERE IMPLEMENTED?

4

MR. VAN NEST:

5

RELEVANCE, YOUR HONOR.

6

THEY MIGHT HAVE SOME LIMITED

BUT ESSENTIALLY YOU'RE LOOKING NOW -- BECAUSE THE NATURE OF

7

THE AGREEMENTS THAT THEY'VE ALLEGED ARE BILATERAL BETWEEN AND

8

AMONG INDIVIDUAL PAIRS OF DEFENDANTS, I THINK THAT EVIDENCE IS

9

GOING TO BE LARGELY RELEVANT BECAUSE THE FOCUS WILL BE ON WHAT,

10

IF ANY, IMPACT WAS THERE FROM THE BILATERAL AGREEMENTS THAT ARE

11

BEING LITIGATED NOW AS BETWEEN THE OTHER FOUR REMAINING

12

DEFENDANTS.

13
14

SO, AGAIN, I DON'T WANT TO SAY ABSOLUTELY NO RELEVANCE, BUT
VERY LIMITED.

15

THE COURT:

16

MR. SAVERI:

17

THE COURT:

OKAY.
YOUR HONOR -LET ME HEAR FROM THE PLAINTIFFS.

YOU

18

AGREE THAT YOU'RE NOT ADVOCATING AN OVERARCHING CONSPIRACY

19

ANYMORE, IT'S JUST BILATERAL AGREEMENTS AND --

20

MR. SAVERI:

NO, YOUR HONOR.

I DON'T THINK THAT THE

21

FACT THAT WE'VE -- THAT WE'VE -- NOTHING HAS REALLY CHANGED IN

22

TERMS OF OUR THEORY OF THE CASE.

23

IS GOING TO HANDLE THE SUBSTANCE OF THE ARGUMENT, BUT LET ME

24

JUST SAY THIS.

25

WE ALLEGE -- AND MR. GLACKIN

I THINK THAT THE -- AS YOU SAID, THE EVIDENCE OF THE

UNITED STATES COURT REPORTERS

18

19

1

SETTLING DEFENDANTS WITH RESPECT TO THE AGREEMENTS, THE NATURE

2

AND THE SCOPE OF THE AGREEMENTS, IS STILL GOING TO BE RELEVANT

3

IN THIS CASE.

4

AND TO THE EXTENT THAT THERE IS OTHER EVIDENCE THAT HAS TO

5

DO WITH THE BUSINESS PRACTICES OF THOSE COMPANIES THAT WE RELY

6

ON TO SHOW A CLASS-WIDE IMPACT, THE FACT THAT THOSE DEFENDANTS

7

HAVE SETTLED DOESN'T CHANGE THAT FACT.

8
9
10

REMEMBER THAT THIS REMAINS A, AN ANTITRUST CLAIM AND ALL
THE PARTICIPANTS IN THE CONSPIRACY ARE, AS A MATTER OF LAW,
JOINTLY AND SEVERALLY LIABLE.

11

AND SO TO THE EXTENT THAT WE PROVE AN UNDERSTANDING, A

12

COMMON COURSE OF CONDUCT THAT INVOLVES ALL OF THESE COMPANIES,

13

I MEAN, THAT EVIDENCE IS RELEVANT.

14

THE COURT:

WHAT IS THE BREAKDOWN OF THE, WHAT IS IT,

15

60,000 THAT YOU'RE ALLEGING ARE IN YOUR TECHNICAL EMPLOYEE

16

CLASS?

17

INCLUDING THE ONES WHO ARE NOW OUT OF THE CASE?

18

WHAT'S THE BREAKDOWN AMONGST THE VARIOUS DEFENDANTS,

MR. GLACKIN:

WOULD YOU LIKE TO KNOW THE BREAKDOWN ON

19

NUMBER OF CLASS MEMBERS OR -- WELL, I CAN TELL YOU WHERE THAT

20

INFORMATION IS IN THE RECORD ACTUALLY IF THAT WOULD BE HELPFUL.

21

THE COURT:

OKAY.

22

MR. GLACKIN:

THAT'S FINE.

IF YOU GO TO THE OCTOBER 12, 2012

23

REPORT OF DR. LEAMER AND YOU GO TO PAGE 23, WHICH IS BETWEEN

24

PARAGRAPHS 54 AND 55, THERE ARE TWO TABLES THERE THAT -- ONE OF

25

THEM IS FOR THE ALL SALARIED CLASS AND ONE OF THEM IS FOR THE

UNITED STATES COURT REPORTERS

19

20

1

TECHNICAL CLASS, WHICH IS THE SAME CLASS THAT WE'RE NOW SEEKING

2

TO CERTIFY.

3
4

THE COURT:

WHICH REPORT?

I HAVE THE MAY 10TH,

2013 --

5

MR. GLACKIN:

6

THE COURT:

7

OH, I DON'T HAVE THAT.

8

MR. GLACKIN:

9
10

-- AND JULY 12TH.

BUT IF YOU WERE TO -- I'D BE
I SHOWED THIS TO

MR. VAN NEST.
THE COURT:

12

MR. GLACKIN:

CAN YOU JUST GIVE ME THE BALLPARKS?
SURE.

WELL, BY NUMBER OF EMPLOYEES, I

CAN TELL YOU THAT ADOBE IS 3,601; APPLE IS 6,835.

14

THE COURT:

15

MR. GLACKIN:

16

THE COURT:

17

MR. GLACKIN:

18

THE COURT:

19

MR. GLACKIN:

20

THE COURT:

21

MR. GLACKIN:

22

THE COURT:

23

MR. GLACKIN:

24

THE COURT:

25

RIGHT.

HAPPY TO HAND YOU MY PAGE IF IT'S HELPFUL.

11

13

THIS IS LAST YEAR.

6,000 WHAT?
835.

OKAY.

THANK YOU.

GOOGLE IS 7,854.

OKAY.
INTEL IS 36,643.

OKAY.
INTUIT IS 3,236.

OKAY.
LUCAS IS 522; PIXAR IS 859.

ALL RIGHT.

WHAT ABOUT THE -- HOW MANY

JOBS -- WELL, I GUESS THAT'S IN THE CHART THAT YOU PROVIDED,

UNITED STATES COURT REPORTERS

20

21

1

THE VARIOUS JOB TITLES FOR EACH OF THOSE.

2

MR. VAN NEST:

3

MR. GLACKIN:

4

MR. VAN NEST:

5

THE COURT:

6

-- IS THE TOTAL.

MR. HARIHARAN -- DID I PRONOUNCE THAT CORRECTLY?
MR. GLACKIN:

8

THE COURT:

10

24 --

NOW, LET ME ASK, WITH REGARD TO

7

9

2400, YOUR HONOR --

CORRECT.

OKAY.

HE DID NOT WORK FOR A DEFENDANT

WHO IS LEFT IN THIS CASE, SO WHY SHOULD HE STILL CONTINUE TO
SERVE AS A CLASS REPRESENTATIVE?

11

MR. GLACKIN:

WELL, AS MR. SAVERI SAID, YOUR HONOR,

12

WE'RE ALLEGING A SINGLE VIOLATION OF THE SHERMAN ACT, A SINGLE

13

CONSPIRACY, COMBINATION, AGREEMENT, UNDERSTANDING IN RESTRAINT

14

OF TRADE.

15

AND EVEN -- THE EMPLOYEES WHO WERE AT THE -- THE PEOPLE WHO

16

WORKED FOR THE SETTLED COMPANIES DURING THE CLASS PERIOD STILL

17

HAVE ACTIVE CLAIMS AGAINST THE OTHER MEMBERS OF THE CONSPIRACY

18

BECAUSE, AS MR. SAVERI SAID, UNDER COPIOUS PRECEDENT, INCLUDING

19

TEXAS VERSUS RADCLIFF, WHICH IS THE SIGNATURE UNITED STATES

20

SUPREME COURT CASE ON JOINT AND SEVERAL LIABILITY, AND UNDER

21

THE SHERMAN ACT, ALL OF THE MEMBERS OF THE COMBINATION

22

CONSPIRACY UNDERSTANDING ARE LIABLE FOR ONE ANOTHER'S CONDUCT,

23

OR WRONGDOING, I SHOULD SAY.

24
25

SO MR. HARIHARAN STILL HAS AN ACTIVE CLAIM AGAINST THE
OTHER FOUR DEFENDANTS, JUST AS ALL THE OTHER NAMED CLASS

UNITED STATES COURT REPORTERS

21

22

1

REPRESENTATIVES HAVE ACTIVE CLAIMS AGAINST THOSE FOUR REMAINING

2

DEFENDANTS.

3

THE COURT:

SO YOU'RE NOT EVEN LIMITING THAT TO ANY

4

OF THE DEFENDANTS WHO HAD A SPECIFIC BILATERAL AGREEMENT WITH

5

HIS EMPLOYER, LUCASFILM?

6
7
8
9
10
11

MR. GLACKIN:

CORRECT, BECAUSE WE'RE ALLEGING A

SINGLE, A SINGLE CONSPIRACY AND RESTRAINT OF TRADE.
AND THE CLASS IS -- THE SETTLEMENT CLASS IS IDENTICAL TO
THE PROPOSED TECHNICAL CLASS.

IT INCLUDES MEMBERS OF ALL OF

THESE COMPANIES.
SO, FOR EXAMPLE, YOU KNOW, INTEL EMPLOYEES ARE MEMBERS OF

12

THE SETTLEMENT -- OF THE CLASS THAT WILL BE PROPOSED FOR THE

13

SETTLEMENT, AND THERE ARE GOING TO BE CLASS MEMBERS WHO RELEASE

14

THEIR CLAIMS AGAINST INTUIT, PIXAR, AND LUCASFILM.

15

SO WHEN WE FILE THE PAPERS, THERE WON'T BE ANY DIFFERENCE

16

BETWEEN THE CLASSES, AND THAT I THINK WE PUT FORWARD IN THE

17

UPDATE YOU REQUESTED.

18

THE COURT:

SO LET ME HEAR FROM MR. VAN NEST.

WHAT'S

19

YOUR POSITION ON WHETHER MR. HARIHARAN CAN CONTINUE TO SERVE AS

20

A CLASS REP?

21
22

MR. VAN NEST:

I THINK YOUR HONOR IS RIGHT.

HE

DOESN'T REALLY HAVE A ROLE AT THIS POINT.

23

IT'S NOTABLE THAT REALLY NONE OF THE CLASS REPS ARE FROM

24

JOB TITLES THAT MAKE UP THE VAST MAJORITY OF JOB TITLES THAT

25

ARE NOW BEING PROPOSED.

UNITED STATES COURT REPORTERS

22

23

1

THESE 2400 JOB TITLES, TWO-THIRDS OF THE CLASS WORK AT

2

INTEL.

OF THOSE, ROUGHLY HALF WORK IN SEMICONDUCTOR

3

MANUFACTURING, WHICH IS UNIQUE TO THEM.

4

THERE ARE JOB TITLES ALL OVER THE LOT THAT HAVE NOTHING TO

5

DO WITH THE JOB TITLES OF THE CLASS REPS, WHO ARE ESSENTIALLY,

6

MOST OF THEM, SOFTWARE ENGINEERS.

7

TYPICAL REPRESENTATIVES TO BEGIN WITH.

8
9
10

SO THEY DON'T REALLY HAVE

HE'S IN A UNIQUE SITUATION SINCE HE DOESN'T WORK FOR
ANYBODY THAT'S GOING TO BE IN THE CASE.
AND, OF COURSE, LUCASFILM AND PIXAR ARE KIND OF IN A

11

SEPARATE INDUSTRY, TOO.

12

FILM INDUSTRY, WHICH NOBODY ELSE PARTICIPATES IN, SO THEY ARE

13

UNIQUE.

14
15
16

HE IS UNIQUE.

THEY'RE IN THIS NORTHERN CALIFORNIA

THEY'RE NO LONGER IN THE CASE.

THEY HAVE

FOUR OTHER CLASS REPS.
FRANKLY, I DON'T THINK ANY OF THEM ARE PARTICULARLY TYPICAL

17

OF SOMETHING WHERE YOU'RE TRYING TO CERTIFY 2400 JOB TITLES,

18

BUT CERTAINLY HE'S PROBABLY AT THE BOTTOM OF THE LIST AND

19

THERE'S NO LONGER ANY REASON FOR HIM TO SERVE.

20
21

THE COURT:

DID ANY OF THE NAMED PLAINTIFFS WORK FOR

APPLE OR GOOGLE?

22

MR. GLACKIN:

23

THE COURT:

24

MR. GLACKIN:

25

THE COURT:

I BELIEVE THE ANSWER IS NO, YOUR HONOR.

OKAY.
IF I -- SORRY.

SO WHAT'S THE THEORY OF, OF THE NAMED

UNITED STATES COURT REPORTERS

23

24

1
2

PLAINTIFFS REPRESENTING EMPLOYEES AT THOSE TWO COMPANIES?
MR. GLACKIN:

WELL, THERE'S NO -- I MEAN, SAYING THAT

3

IT WAS NECESSARY TO HAVE AN EMPLOYEE FROM EACH COMPANY IN

4

THE -- AS A CLASS REPRESENTATIVE WOULD BE AKIN TO SAYING THAT

5

YOU COULD NOT CERTIFY A CLASS IN A PRICE FIXING CONSPIRACY CASE

6

UNLESS YOU HAD SOMEBODY WHO HAD BOUGHT FROM EVERY DEFENDANT.

7

AND IF YOU TOOK MR. VAN NEST'S ARGUMENT AND TRANSLATED IT

8

INTO THAT CONTEXT, WITH WHICH WE'RE ALL VERY FAMILIAR, THE

9

ARGUMENT WOULD BE THAT IF YOU BOUGHT FROM A SETTLED DEFENDANT,

10

YOU ARE NO LONGER AN APPROPRIATE CLASS REPRESENTATIVE IN A

11

GARDEN VARIETY PRICE FIXING CONSPIRACY CASE.

12

AND I CAN TELL YOU THAT HAVING -- I MEAN, I'M NOT -- I'LL

13

SIMPLY SAY I AM NOT AWARE OF THAT EVER HAPPENING.

14

AWARE OF ANYONE EVER MAKING THAT CONTENTION.

15

ANY COURT EVER COMING TO THAT CONCLUSION.

16

I'M NOT

I'M NOT AWARE OF

BECAUSE EVEN IF YOU -- I MEAN, WE HAD THIS COME UP SIMPLY

17

12 MONTHS AGO.

I MEAN, THERE WERE -- WHEN WE TRIED THE LCDS

18

CASE, WE HAD A NUMBER OF CLASS REPRESENTATIVES.

19

AGAINST TOSHIBA.

20

MAJORITY OF OUR CLASS REPRESENTATIVES DID NOT BUY FROM TOSHIBA

21

BECAUSE TOSHIBA WAS A VERY SMALL MANUFACTURER IN THAT MARKET.

22

SO IT'S TOTALLY NORMAL TO HAVE -- TO NOT HAVE COMPLETE

EVERY OTHER DEFENDANT SETTLED.

THE TRIAL WAS
BUT THE VAST

23

COVERAGE OF EVERY MEMBER OF THE CONSPIRACY IN TERMS OF

24

TRANSACTIONS, AND IT'S TOTALLY NORMAL FOR THOSE WHO BOUGHT FROM

25

SETTLED DEFENDANTS TO STAY IN THE CASE BECAUSE MR. HARIHARAN,

UNITED STATES COURT REPORTERS

24

25

1

HE'S STILL JUST IN THE SAME POSITION AS EVERY OTHER CLASS

2

MEMBER.

3

WHO HAVE NOT SETTLED.

HE STILL HAS A CLAIM AGAINST THE OTHER FOUR MEMBERS

4

MR. VAN NEST:

YOUR HONOR, THERE'S REALLY A MORE

5

FUNDAMENTAL PROBLEM THAN THIS, AND THAT IS THERE IS NO CASE

6

THAT HAS CERTIFIED A CLASS THIS BROAD AND THIS DIVERSE IN A

7

WAGE SUPPRESSION CONTEXT.

8
9

WE HAVE, AMONG THE EVIDENCE HERE -- AND I HAVE AN APPENDIX
I CAN HAND UP -- 2400 JOB TITLES, 60,000 EMPLOYEES.

10

A WIDE RANGE OF AREAS.

11

SILICON VALLEY.

12

THEY COVER

DISPARATE.

13

MORE THAN HALF OF THEM WORK OUTSIDE OF

IT IS AN ENORMOUS CLASS AND ENORMOUSLY

IF YOU LOOK AT THE JOB TITLES THAT THEY ARE CLAIMING ARE

14

LINKED TOGETHER, IT'S EVERYTHING FROM A MASK DESIGNER TO A

15

SEMICONDUCTOR MANUFACTURER TO AN ARTIST TO A SOFTWARE ENGINEER

16

TO A CHEMICAL ENGINEER.

17

PEOPLE --

18

THE COURT:

19

MR. VAN NEST:

20

THE COURT:

IT'S ENORMOUS AND NONE OF THESE

I'M SORRY TO INTERRUPT YOU.
YEAH.

BUT THE COMPANIES THEMSELVES IDENTIFIED

21

WHO THEY BELIEVE THEIR PEERS WERE FOR TALENT AND THEY DID

22

BASICALLY IDENTIFY EACH OTHER AS PEERS.

23

SPECIFIC EXHIBIT NUMBERS IF YOU WANT TO GO THERE.

24
25

I MEAN, I HAVE

BUT THEY DID DO SOME ANALYSIS OF WHO WOULD BE COMPETING FOR
THE SAME TALENT AND THEY WOULD SAY THE OTHER COMPANIES.

UNITED STATES COURT REPORTERS

25

26

1

SO I HEAR WHAT YOU'RE SAYING, YOU KNOW, THE WAFER MASK

2

DESIGNER IS DIFFERENT THAN, YOU KNOW, SOMEONE DESIGNING APPS

3

SOMEWHERE ELSE.

4

BUT EFFECTIVELY --

5

MR. VAN NEST:

NOT JUST THAT, YOUR HONOR, BUT I

6

THINK, AS YOU NOTED LAST TIME AND IN YOUR ORDER, OBVIOUSLY SOME

7

CATEGORIES OF EMPLOYEES WERE MORE IMPORTANT THAN OTHERS, OR

8

MORE -- PEOPLE WERE MORE CONCERNED ABOUT SOME CATEGORIES THAN

9

OTHERS, OBVIOUSLY.

10

AND HERE WHERE ONE OF THE COMPANIES WITH TWO-THIRDS OF THE

11

CLASS IS PRIMARILY ENGAGED IN AN AREA THAT NO OTHER DEFENDANT

12

IS ENGAGED IN -- YOU KNOW, INTEL HAS -- THERE'S ONLY A CLAIM OF

13

ONE BILATERAL AGREEMENT BETWEEN INTEL AND GOOGLE, NOT A LOT OF

14

AUDITORS.

15

AND EVEN THERE, THERE ARE SO MANY -- THIS IS WHAT YOU SAID

16

LAST TIME.

17

BIG AND SO LARGE AND SO DIVERSE THAT THERE ARE PEOPLE IN IT

18

THAT WEREN'T IMPACTED AND THAT SUFFERED NO INJURY?

19

ONE OF YOUR TWO BIG CONCERNS WAS, IS THE CLASS SO

AND OBVIOUSLY WHERE YOU HAVE MORE THAN HALF OF THE FOLKS

20

OUTSIDE OF SILICON VALLEY, SUBJECT TO DIFFERENT PAY STRUCTURE

21

ALTOGETHER, AND WHERE TWO-THIRDS OF THEM WORK FOR A COMPANY

22

THAT DOES SOMETHING UNIQUE, WE'VE GOT AN ENORMOUS PROBLEM.

23

NO OTHER CASE, NOT WEISBERG, NOT REED, NOT FLEISHMAN, NO

24

OTHER CASE HAS CERTIFIED A CLASS ANYWHERE NEAR THIS SIZE IN A

25

WAGE SUPPRESSION CASE BECAUSE THEY'RE LOOKING AT, HEY, WHAT,

UNITED STATES COURT REPORTERS

26

27

1

WHAT POSITIONS ARE COMPARABLE?

2

HOW ARE THEY GOING TO BE ABLE TO SHOW IMPACT ACROSS THE WHOLE

3

GROUP?

4

HOW MUCH HOMOGENEITY IS THERE?

IT MAKES NO LOGICAL SENSE THAT THE ABSENCE OF A CALL TO AN

5

ENGINEER IN SILICON VALLEY WOULD AFFECT A MASK DESIGNER IN

6

MASSACHUSETTS OR ARIZONA OR NEW MEXICO, AND THAT'S WHAT

7

THEY'RE -- THEY'RE HERE CLAIMING THAT THESE 2400 JOB TITLES ARE

8

ALL SOMEHOW LINKED TOGETHER.

9

INTEL, ALMOST 400 OF THEM AT GOOGLE, 350 OF THEM AT APPLE, AND

10
11
12

THERE'S 800 OF THEM ALONE AT

THEY'RE SAYING THIS IS ALL LINKED TOGETHER.
IN THE OTHER CASES WHERE THIS HAS COME UP, THE CLAIM HAS
BEEN THAT ONE --

13

THE COURT:

BUT THERE IS --

14

MR. VAN NEST:

15

THE COURT:

-- JOB TITLE --

-- EVIDENCE FOR EACH OF THE DEFENDANTS

16

THAT THEY HAD THESE JOB FAMILIES, THAT THEY HAD THESE PAY

17

RANGES THAT ARE SIMILAR TO CRIMINAL SENTENCING, YOU HAD THE

18

LOW, THE MEDIUM, AND THE HIGH.

19
20

(LAUGHTER.)
THE COURT:

AND THAT IN SOME INSTANCES, IF YOU WANTED

21

TO GO OUTSIDE THAT RANGE, YOU HAD TO GET AN EXTRA LEVEL OF

22

APPROVAL; THAT THEY WERE ALWAYS AWARE, WHEN THEY WERE BRINGING

23

A LATERAL PERSON IN, WHERE EVERYONE ELSE STOOD SO THERE

24

WOULDN'T BE AN ISSUE OF DISPARITY.

25

SO I -- LET ME ASK YOU A QUESTION.

AT THE LAST HEARING THE

UNITED STATES COURT REPORTERS

27

28

1

DEFENDANTS' COUNSEL SAID THAT -- I'LL JUST QUOTE IT -- "AND I

2

ADMIT AT THE START, WE ARE NOT SAYING THAT NOBODY WAS

3

IMPACTED."

4
5

SO LET ME ASK -- I JUST WANT TO FOLLOW-UP.
IMPACTED?

WHO WAS IMPACTED?

6

MR. VAN NEST:

7

THE COURT:

8

MR. VAN NEST:

9

THE COURT:

UM-HUM.
-- TO KNOW THAT.

WELL, HOW CAN YOU SAY THAT NO ONE WAS

IMPACTED?

12
13

WELL, I DON'T THINK THERE'S ANY WAY --

BUT WHAT WE DO KNOW --

10
11

HOW MANY WERE

MR. VAN NEST:

I'M NOT SAYING THAT NO ONE WAS

IMPACTED.

14

THE COURT:

OKAY.

15

MR. VAN NEST:

BUT FOR THE PURPOSE OF -- WHAT WE

16

UNDERSTOOD TO BE YOUR HONOR'S CONCERN WAS, CAN THE PLAINTIFF

17

SHOW, IN ORDER TO ESTABLISH CLASS-WIDE INJURY --

18

THE COURT:

LET ME ASK YOU A QUESTION.

I BELIEVE

19

THAT WAS MR. MITTELSTAEDT AT THE TIME.

20

NOT SAYING THAT NOBODY WAS IMPACTED," WHAT DID THAT MEAN?

21

MR. VAN NEST:

WHEN HE SAYS, "WE'RE

I THINK WHAT HE MEANT WAS FOR THE

22

PURPOSES OF CLASS CERT, WE'RE NOT TAKING THE POSITION THAT THEY

23

CAN'T SHOW ANY IMPACT.

24
25

THE ISSUE IS, CAN THEY SHOW IMPACT TO ALL OR NEARLY ALL OF
THE MEMBERS OF THE CLASS?

UNITED STATES COURT REPORTERS

28

29

1

I THINK THAT'S ALL MR. MITTELSTAEDT MEANT, AND THAT'S ALL I

2

MEAN, TOO.

3

PROPER, HOW MANY.

4

ANYTHING.

5

WE'RE NOT GOING TO DEBATE TODAY, I DON'T THINK IT'S
I'M NOT SURE THEY'RE GOING TO PROVE MUCH OF

THE COURT:

WELL, HOW MUCH IS REQUIRED?

IN ORDER TO

6

CERTIFY CLASS, THEY DON'T HAVE TO SHOW THAT 60,000 WAS ENOUGH.

7

40 IS USUALLY ENOUGH.

8

THE NUMBER THAT THEY'RE -- SEPARATE FROM WHETHER THEY'VE SHOWN

9

IMPACT OR NOT, WHAT IS THE MINIMUM LEVEL OF SHOWING IN TERMS OF

10

WHAT'S

PEOPLE THAT THEY NEED TO MAKE IN ORDER TO GET CERTIFIED?

11
12

SOMETIMES 20 MIGHT BE ENOUGH.

MR. VAN NEST:

THEY NEED TO SHOW THAT NEARLY ALL --

IF THEY WANT TO PROCEED AS A CLASS --

13

THE COURT:

OKAY.

14

MR. VAN NEST:

-- THEY NEED TO SHOW -- AND YOU

15

RECOGNIZED THIS AT PAGE 46 OF YOUR ORDER LAST TIME -- THEY NEED

16

TO SHOW THAT THE WAGE STRUCTURES WERE SO, SO RIGID THAT THEY

17

WOULD HAVE AFFECTED ALL OR NEARLY ALL MEMBERS OF THE CLASS.

18

THAT'S EXACTLY WHAT YOU SAID AND THAT'S EXACTLY RIGHT.

19

THESE CASES ALL SAY, IF WE'RE GOING TO PROCEED AS A CLASS,

20

YOU'VE GOT TO SHOW THAT CLASS-WIDE IMPACT, AND CLASS-WIDE MEANS

21

ALL OR NEARLY ALL.

22

NOT EVERYBODY.

NOT 60,000, CERTAINLY.

BUT IT'S -- IT'S GOT TO BE A SITUATION WHERE THEY PROVE, IN

23

ONE TRIAL, THAT VIRTUALLY ALL MEMBERS OF THE CLASS WERE

24

IMPACTED.

25

AND THEN YOU GO ON, IF THEY PREVAIL, TO TRY TO ESTABLISH

UNITED STATES COURT REPORTERS

29

30

1
2

DAMAGES.
SO WHAT WE'VE DONE HERE IS THEY'VE COME IN, AND YOU PUT

3

THEM TO IT LAST TIME, YOU SAID, "CAN YOU SHOW ME THAT THE

4

STRUCTURES FOR WAGES AT THE COMPANIES WERE SO RIGID THAT AN

5

IMPACT ON SOME PEOPLE WOULD HAVE PROPAGATED TO ALL OR NEARLY

6

ALL?"

7

AND THEY ABSOLUTELY HAVE FAILED TO DO THAT.

DR. LEAMER

8

SAYS HE CAN'T REACH THAT CONCLUSION.

HE FLAT OUT ADMITTED IN

9

DEPOSITION -- AND I HAVE THE CITATION, YOUR HONOR -- THAT "I

10

CAN'T TELL YOU THAT ADOBE'S STRUCTURE WAS SO RIGID THAT IMPACT

11

TO SOME WOULD, WOULD FLOW DOWN TO IMPACT TO OTHERS."

12

SAYS, "I DON'T BELIEVE THAT IT WOULD."

13

AND HE

NOW, YOU HAVE, FROM DR. MURPHY, YOUR HONOR, THE --

14

THE COURT:

LET ME ASK YOU A QUESTION.

15

THIS PROCEEDS ALONG INDIVIDUAL CLAIMS.

16

LET'S SAY

WORK?

17

MR. VAN NEST:

18

THE COURT:

19

MR. VAN NEST:

HOW IS THAT GOING TO

I WOULD CALL THAT A MASS ACTION.

A CLASS -NO, I WOULDN'T.

ACTUALLY, I THINK

20

THAT IS AN EASIER, MORE EFFICIENT WAY TO HANDLE THIS.

21

WE WILL

CALL THAT A MASS ACTION, NOT A CLASS ACTION.

22

IF THERE ARE PEOPLE, AND CERTAINLY THE CLASS REPS WOULD BE

23

AMONG THEM, WHO BELIEVE THEY WERE INJURED, THEY WOULD COME IN,

24

THEY WOULD PRESENT THEIR COMPLAINT, MAYBE WE'D HAVE 200 OF

25

THEM, MAYBE WE'D HAVE 300 OF THEM, BUT WHAT WE WOULD DO IS WE

UNITED STATES COURT REPORTERS

30

31

1

WOULD NEGOTIATE A REPRESENTATIVE FEW OF THOSE TO TRY THE FIRST

2

COUPLE OF CASES, OR THE FIRST CASE, AND SEE WHERE WE COME OUT

3

AND TRY TO BENCHMARK WHETHER THEY CAN ESTABLISH LIABILITY IN

4

THE FIRST PLACE, AND IF THEY CAN, WHAT ARE THE RANGES OF

5

DAMAGES.

6

NOW, REMEMBER, WE'RE TALKING --

7

THE COURT:

SO YOU'RE GOING TO HAVE BELLWETHER TRIALS

8

WHICH ARE THEN GOING TO EXTRAPOLATE THE CLASS AND SETTLE ON A

9

CLASS SIZE.

10
11

THAT'S WHAT'S GOING TO HAPPEN?

MR. VAN NEST:

HAPPENS ALL THE TIME.

AND IN THIS CASE, I'D SAY, YOUR HONOR, IT'S ABSOLUTELY

12

APPROPRIATE.

13

WHY?

14

AGREEMENTS.

15

THERE'S ONLY EVIDENCE SO FAR OF THESE BILATERAL AGREEMENTS

16

BETWEEN COMPANIES.

17
18
19

BECAUSE WHAT THEY'RE ALLEGING IS A BUNCH OF BILATERAL
THEY CAN TALK ABOUT OVERARCHING CONSPIRACY, BUT

THE COURT:

SO YOU'RE SAYING 200 BELLWETHER TRIALS

AND FROM THERE WE'LL EXTRAPOLATE TO 60,000?
MR. VAN NEST:

NO, NO, NO.

I'M SAYING IF WE HAD 200

20

PEOPLE MAKING CLAIMS -- I DON'T KNOW HOW MANY PEOPLE ACTUALLY

21

FEEL THEY HAVE A CLAIM.

22

PLAINTIFFS, WE WOULD CONDUCT A FEW, ONE, TWO, OR THREE

23

BELLWETHER TRIALS, NOT A LOT, AND THAT HAPPENS ALL THE TIME.

24
25

I'M SAYING IF WE HAVE 200 OR 300

AND HERE IT'S APPROPRIATE, YOUR HONOR, BECAUSE THEY FAILED
TO SHOW, AFTER YOU GAVE THEM A CLEAR ROADMAP, THAT THE SALARY

UNITED STATES COURT REPORTERS

31

32

1
2

STRUCTURES ARE SO RIGID -THE COURT:

SO LET ME ASK YOU, AFTER THE THREE

3

BELLWETHER TRIALS, THEN WHAT'S GOING TO HAPPEN?

4

TO ASSUME, OKAY, THIS 1,000, 2,000 GROUP OF CLASS MEMBERS HAVE

5

CLAIMS THAT ARE SOMEWHAT SIMILAR TO BELLWETHER TRIAL NUMBER TWO

6

AND SO, THEREFORE, THEIR DAMAGES SHOULD ROUGHLY APPROXIMATE --

7

MR. VAN NEST:

8

THE COURT:

9
10

YOU'RE GOING

THAT'S RIGHT.

-- WHATEVER THE FINDING WAS IN BELLWETHER

TRIAL NUMBER TWO?
MR. VAN NEST:

THAT'S WHAT TYPICALLY TAKES PLACE.

11

THAT'S WHAT'S TAKING PLACE IN A LOT OF THESE MASS TORT CASES

12

THAT ARE BEING HANDLED AROUND THE COUNTRY.

13

AFTER A COUPLE OF TRIALS, SMART TRIAL LAWYERS,

14

SOPHISTICATED COUNSEL FIGURE OUT WHAT'S HAPPENING.

15

THE CASES AND YOU GO.

16

YOU PRICE

TO ME, GIVEN THE EVIDENCE YOU HAVE, THEY ARE SWINGING FOR

17

THE FENCES WITH THIS CLASS THEY WANT, AND THEY HAVEN'T SHOWN

18

THE BASIC PREDICATE.

19
20
21

THEY NOW ADMIT THAT THE SALARY STRUCTURES ARE NOT SO RIGID
THAT IMPACT ON SOME WOULD HAVE IMPACTED ALL.
THE COURT:

ACTUALLY, I DISAGREE WITH YOU.

I THINK

22

ON THE INTERNAL EQUITY AND ON THE RIGID WAGE STRUCTURE, IT'S

23

MUCH STRONGER NOW THAN IT WAS LAST TIME AROUND.

24
25

MR. VAN NEST:

WELL, IF I COULD HAND UP WHAT I THINK

ARE THE KEY PIECES OF EVIDENCE, YOUR HONOR, AND ASK THE COURT

UNITED STATES COURT REPORTERS

32

33

1

TO TAKE A LOOK AT JUST THE VERY FIRST TAB (HANDING) -- I HAVE

2

ONE FOR THE COURT AND ONE FOR THE CLERK.

3

MR. GLACKIN:

4

MR. VAN NEST:

I HAVE ONE.
THE QUESTION YOU ASKED LAST TIME, YOUR

5

HONOR, WAS CAN YOU SHOW, WITH CLASS-WIDE EVIDENCE, THAT

6

IMPACT -- THAT THE STRUCTURE IS SO RIGID THAT IMPACT TO ONE

7

WOULD AFFECT ALL?

8

TAB 1 IS FROM DR. LEAMER'S MOST RECENT DEPOSITION.

9
10

THE COURT:

RIGHT.

AND WE'RE GOING TO GET INTO THIS.

LET ME ASK MY QUESTIONS IF YOU DON'T MIND.

11

MR. VAN NEST:

12

THE COURT:

13

MR. VAN NEST:

14

THE COURT:

15

SURE.

OKAY?
OF COURSE.

ALL RIGHT.

LET ME GO TO THE PLAINTIFFS.

WHAT EXACTLY IS YOUR THEORY OF IMPACT?

HOW ARE YOU

16

EXPLAINING HOW, IF A COLD CALL WAS MADE, HOW THE INCREASE IN

17

SALARY WOULD AFFECT MORE PEOPLE THAN JUST THE RECIPIENT OF THE

18

CALL?

19
20
21
22
23

MR. GLACKIN:

SO I THINK THAT WE WOULD SAY THAT THERE

ARE A NUMBER OF WAYS IN WHICH THIS WOULD HAVE OCCURRED.
AND OF COURSE WE'LL NEVER KNOW EXACTLY WHAT WOULD HAVE
HAPPENED BECAUSE OF THE AGREEMENTS.
BUT THE -- OUR THEORY OF IMPACT IS THAT IT'S NOT JUST ONE

24

COLD CALL THAT WOULD HAVE MOVED THE DEFENDANTS' ENTIRE

25

COMPENSATION STRUCTURE.

WE'VE NEVER ADVOCATED THAT.

UNITED STATES COURT REPORTERS

I AGREE

33

34

1

THAT'S CRAZY TO SAY THAT ONE SINGLE COLD CALL IS GOING TO MOVE

2

THE COMPENSATION STRUCTURE FOR THOUSANDS OF EMPLOYEES.

3

INSTEAD, IF YOU LOOK AT MR. CAMPBELL'S TESTIMONY, THE CEO

4

OF INTUIT WHO ALSO IS A FIGURE AT GOOGLE AND APPLE, HE EXPLAINS

5

THAT WHAT HE WAS CONCERNED ABOUT AND THE REASON HE WANTED IN ON

6

THIS WAS IT WAS THE WAVES OF COLD CALLS.

7

GOOGLE PICKING UP THE PHONE AND STARTING AT THE LETTER A ON,

8

YOU KNOW, THE LIST OF ENGINEERS AT INTUIT AND CALLING AND JUST

9

DIALING DOWN THE PHONE TREE AND CALLING EVERY SINGLE ONE OF

10
11

IT WAS SOMEBODY AT

THEM.
AND IT WAS THE DISRUPTION THAT WAS CAUSED BY THAT WAVE OF

12

CALLS, OR THOSE WAVES OF CALLS, THAT THE DEFENDANTS WERE TRYING

13

TO HEAD OFF THROUGH THESE ANTI-SOLICITATION AGREEMENTS.

14

NOW, HAD THOSE -- HAD THE AGREEMENTS NOT BEEN IN PLACE, WE

15

THINK THAT THE WORLD WOULD HAVE BEEN DIFFERENT IN A NUMBER OF

16

DIFFERENT WAYS.

17

WE THINK THAT WHEN THE WAVES OF COLD CALLS HAPPENED, THAT

18

THAT WOULD HAVE PUT UPWARD PRESSURE ON THE ENTIRE SALARY

19

STRUCTURE BECAUSE MANAGERS WOULD LET THE -- YOU KNOW, THE LOWER

20

LEVEL MANAGERS WOULD LET THE HIGHER LEVEL MANAGERS KNOW THAT

21

THE COMPANY'S EMPLOYEES WERE VULNERABLE, AND THAT WOULD HAVE

22

LED TO ADJUSTMENTS AT THE TOP OF THE SALARY STRUCTURE TO

23

IMPROVE THE SALARIES, OR THE COMPENSATION OF ALL EMPLOYEES.

24

BUT THE CEOS THEMSELVES, I MEAN, WHO ENTERED INTO THESE

25

AGREEMENTS IN THE FIRST PLACE WOULD HAVE BEEN AWARE, WOULD HAVE

UNITED STATES COURT REPORTERS

34

35

1

KNOWN THAT THEY FACED INCREASED COMPETITION FROM OTHER, FROM

2

THEIR OTHER PEER COMPANIES IN SILICON VALLEY AND WOULD HAVE --

3

AND ELSEWHERE IN NORTHERN CALIFORNIA -- AND WOULD HAVE ACTED

4

PREEMPTIVELY.

THEY AND THEIR MANAGERS WOULD HAVE ACTED

5

PREEMPTIVELY.

THEY WOULD HAVE RESPONDED TO THE THREAT OF

6

COMPETITION AS WELL BY IMPROVING THE SALARIES OF THEIR

7

EMPLOYEES, OR THE COMPENSATION OF THEIR EMPLOYEES.

8
9

SO I THINK THAT, YOU KNOW, THE INCREASE -- IF YOU LOOK AT
THE -- IF YOU LOOK AT THE COMPANIES THEMSELVES -- THE REASON

10

I'M BEING A LITTLE GENERAL IS BECAUSE EACH OF THEM MANAGED

11

THEIR COMPENSATION IN SLIGHTLY DIFFERENT WAYS.

12

DIDN'T -- THEY ALL USED THEIR OWN PROPRIETARY, YOU KNOW,

13

PAYMENT TOOL, WHICH IS -- OR WHATEVER SORT OF COMPUTER PROGRAM

14

THEIR MANAGERS WERE SUPPOSED TO LOG INTO.

15

THE COURT:

I MEAN, THEY

I GUESS I DON'T UNDERSTAND HOW THIS

16

UPWARD PRESSURE ON THE ENTIRE SALARY STRUCTURE, HOW WAS THAT

17

SUPPOSED TO HAPPEN?

18

MR. GLACKIN:

WELL, YOU -- THE EMPLOYEES -- YOU MEAN

19

FROM THE INCOMING COLD CALLS?

20

THE COURT:

21

MR. GLACKIN:

22

THE COURT:

23

YEAH.
SO THE --

WHAT'S THE CHAIN OF EVENTS THAT CAUSES

THAT TO HAPPEN?

24

MR. GLACKIN:

25

THE COURT:

YEAH.

BECAUSE I DON'T SEE IT.

UNITED STATES COURT REPORTERS

35

36

1

MR. GLACKIN:

SO THE CHAIN OF EVENTS IS THAT SOMEBODY

2

AT -- YOU KNOW, ONE OF THE 800 RECRUITERS AT GOOGLE, FOR

3

EXAMPLE, PICKS UP THE PHONE, OR MAYBE SEVERAL OF THEM PICK UP

4

THEIR PHONES AND THEY NEED TO HIRE A SOFTWARE ENGINEER, AND SO

5

THEY GET, YOU KNOW, WHATEVER PHONE LIST THEY HAVE FOR INTUIT

6

AND THEY START AT LETTER A AND THEY GO DOWN TO LETTER Z AND

7

THEY CALL ALL THOSE PEOPLE, AND MAYBE THEY GET SOME LEADS, OR

8

MAYBE THEY DON'T.

9

BUT EITHER WAY, RIGHT THERE, THE PEOPLE WHO RECEIVED THOSE

10

CALLS HAVE GAINED SOME INFORMATION ABOUT HOW THEY ARE PERHAPS

11

MORE VALUABLE THAN WHAT THEY'RE BEING PAID AT INTUIT.

12

IF THE -- IF IT GOES TO ANOTHER LEVEL WHERE THEY RECEIVE

13

JOB INTERVIEWS OR OFFERS OR IF THEY GET A NEW JOB AND LEAVE,

14

THERE'S AN ADDITIONAL AND GREATER LEVEL OF DISRUPTION THAT

15

HAPPENS TO INTUIT.

16

THE COURT:

WELL, I GUESS I -- I GUESS I DON'T SEE

17

HOW THAT'S HAPPENING.

18

RECIPIENT OF THE CALL NOW HAVING A BETTER SENSE OF HOW MUCH HE

19

OR SHE IS WORTH, BUT I GUESS I'M NOT SEEING THE RELATIONSHIP

20

BETWEEN THAT ONE PERSON'S BETTER REALIZATION OF THEIR MARKET

21

VALUE AND HOW THAT TRANSLATES TO THE ENTIRE SALARY STRUCTURE.

22

MR. GLACKIN:

I SEE WHAT YOU'RE SAYING ABOUT THE

WELL, THE POINT -- SO LET'S ASSUME THAT

23

SOMEBODY AT GOOGLE HAS PICKED UP THE PHONE AND CALLED 100

24

SOFTWARE ENGINEERS AT INTUIT, SO ALL OF A SUDDEN YOU'VE GOT 100

25

SOFTWARE ENGINEERS WHO HAVE GAINED SOME INFORMATION, AND THEN

UNITED STATES COURT REPORTERS

36

37

1

YOU MAYBE ULTIMATELY GET A SMALLER NUMBER WHO HAVE RECEIVED JOB

2

OFFERS OR HAVE BEEN INVITED IN FOR INTERVIEWS WHO ARE GOING TO

3

GET MORE INFORMATION ABOUT THEIR WORTH.

4

THOSE SOFTWARE ENGINEERS -- NOW, ONCE THEY LEARN THAT

5

THEY'RE MORE VALUABLE, THEY'RE NOT JUST GOING TO SIT THERE AND

6

SAY, "OKAY, I UNDERSTAND THAT THE GOOGLE PEOPLE WOULD REALLY

7

LOVE TO HIRE ME, BUT I'M SO HAPPY AT INTUIT, I DON'T CARE WHAT

8

INTUIT PAYS ME."

9

I MEAN, THEY'RE GOING TO AGGREGATE.

THEY'RE GOING TO TALK

10

TO THEIR MANAGER.

11

WANT MORE MONEY OR THAT THEY FEEL THEY ARE AT RISK OF BEING

12

HIRED AWAY AND THAT'S GOING TO PUT PRESSURE ON THE COMPANY.

13

THEY'RE GOING TO MAKE IT KNOWN THAT THEY

AND THE DOCUMENTS SHOW THAT THE COMPANIES ARE AWARE OF THIS

14

THREAT AND THEY TAKE IT INTO CONSIDERATION.

YOU KNOW, ONE

15

DOCUMENT I WOULD POINT TO IS -- IT WAS EXHIBIT 17, I BELIEVE,

16

TO MR. HARVEY'S ORIGINAL DECLARATION FROM 2012, WHICH IS THIS

17

DONNA MORRIS E-MAIL WHICH IS ADOBE_008692 AND IN WHICH

18

MS. MORRIS IS DESCRIBING THIS EXACT PROCESS.

19

SHE SAYS, "SALARIES ARE GETTING OUT OF WHACK, OUR

20

EMPLOYEES' SALARIES ARE MOVING APART, THERE'S NOT ENOUGH

21

COMPRESSION, WE NEED TO DO AN OUT OF CYCLE ADJUSTMENT TO DEAL

22

WITH THE COMPETITION THAT WE'RE GETTING FOR OUR COMPANIES,"

23

EXCUSE ME, "FOR OUR EMPLOYEES."

24

THE COURT:

UM-HUM.

25

MR. GLACKIN:

AND IT'S THAT KIND -- AND THIS WAS IN

UNITED STATES COURT REPORTERS

37

38

1

FEBRUARY OF 2005, MERE MONTHS BEFORE ADOBE ENTERED INTO ITS

2

COMPANY-WIDE AGREEMENT WITH MR. JOBS.

3

AND SO THIS IS EXACTLY THE KIND OF THING THAT WE SAY WOULD

4

HAVE HAPPENED A LOT MORE OFTEN HAD THESE DEFENDANTS NOT ENTERED

5

INTO THESE AGREEMENTS.

6

THE COURT:

WELL, I GUESS I'M STILL CONFUSED AS TO

7

IF -- LET'S SAY THE GOOGLE PERSON IS CALLING A THROUGH Z AT

8

INTUIT WITHIN A SPECIFIC JOB FAMILY.

9

THAT JOB FAMILY, SALARIES MIGHT GO UP AT INTUIT.

10
11

I CAN SEE WHY, WITHIN

BUT WHAT I DON'T SEE IS WHY OTHER JOB FAMILIES AT INTUIT
WOULD BE AFFECTED BY THE INCREASE.

12

MR. GLACKIN:

13

THE COURT:

OH, OKAY.

YEAH.

I UNDERSTAND.

IF THESE ARE THE DIFFERENT SILOS,

14

HOW IS THAT COMPENSATION INFORMATION SUPPOSED TO BE TRANSLATED

15

ACROSS THE DIFFERENT FAMILIES?

16

MR. GLACKIN:

17

THE COURT:

18

MR. GLACKIN:

RIGHT.

OR -THIS IS -- I THINK WHEN YOU GET TO THE

19

LEVEL OF JOB FAMILIES AND JOB TITLES, THIS IS WHERE INTERNAL

20

EQUITY AND THE WAY THAT THESE COMPANIES STRUCTURE THEIR

21

COMPENSATION SYSTEMS STARTS TO PLAY THE BIG ROLE, BECAUSE THE

22

EVIDENCE SHOWS THAT THESE -- AND THIS IS SUMMARIZED IN OUR, AT

23

LENGTH IN THE BRIEFS AND IN DR. HALLOCK'S REPORT, THAT THESE

24

COMPANIES CARE ABOUT MAINTAINING RELATIVE POSITIONING BETWEEN

25

THEIR JOB TITLES AND THEIR JOB FAMILIES.

UNITED STATES COURT REPORTERS

38

39

1

I MEAN, IT JUST MAKES SENSE, RIGHT, THAT YOU WOULD CARE

2

ABOUT HOW SOFTWARE ENGINEER 1 IS PAID RELATIVE TO SOFTWARE

3

ENGINEER 6, OR HOW A PARTICULAR FAMILY OF ENGINEERS IS PAID

4

RELATIVE TO ANOTHER FAMILY OF ENGINEERS.

5
6

IT'S NOT, I DON'T THINK, PARTICULARLY CONTROVERSIAL AT THIS
POINT ACTUALLY.

7
8

THE COURT:

BUT TELL ME ABOUT THE RADFORD DATA.

WHICH COMPANIES ARE INCLUDED IN THAT DATA?

9

MR. GLACKIN:

IT'S -- MY UNDERSTANDING IS THAT IT IS

10

A LARGE -- I MEAN, IT'S A LARGE GROUP OF COMPANIES.

11

THAN JUST THESE FIRMS, THAT'S FOR SURE.

12

IT'S MORE

AND I THINK THAT YOU CAN BE -- IF YOU'RE A SUBSCRIBER TO

13

THE RADFORD DATA AS A COMPANY, I THINK YOU CAN BE SELECTIVE

14

ABOUT THE KINDS OF COMPANIES THAT YOU WANT DATA FOR, AGGREGATE

15

DATA FOR.

16

THE COURT:

ARE THE DEFENDANTS THAT ARE IN THIS CASE

17

INCLUDED IN THE RADFORD DATA?

18

MR. GLACKIN:

19

THE COURT:

20

I BELIEVE SO.

HOW -- AND HOW IS THAT DATA ORGANIZED?

I

KNOW -- I SAW SOMEWHERE THAT IT'S JOB TITLE AND CATEGORY.

21

MR. GLACKIN:

RIGHT.

I -- MY UNDERSTANDING IS THAT

22

THERE ARE -- YOU KNOW, THERE ARE CERTAIN BENCHMARK JOB TITLES

23

THAT ARE -- WHERE MARKET AVERAGES ARE REPORTED BY RADFORD FOR

24

A --

25

THE COURT:

AND WHAT ARE THOSE?

UNITED STATES COURT REPORTERS

39

40

1
2
3
4

MR. GLACKIN:

WHAT ARE THE SPECIFIC BENCHMARK JOB

TITLES?
THE COURT:

DO THEY INCLUDE ANY THAT WOULD BE IN YOUR

ALLEGED TECHNICAL EMPLOYEE CLASS?

5

MR. GLACKIN:

6

THE COURT:

7

YES, THEY DO.

MR. GLACKIN:

WHAT -I HAVE TO CONFESS TO YOU, I DON'T KNOW

8

THEM OFF THE TOP OF MY HEAD.

9

THE COURT:

10

OKAY.

INCLUDE JOB TITLES THAT ARE IN --

11

MR. GLACKIN:

12

THE COURT:

13

MR. GLACKIN:

14

THE COURT:

15
16

BUT YOU THINK THAT THEY WOULD

YES.

-- THE TECHNICAL CLASS?
CERTAINLY.

AND WHAT DO YOU MEAN BY "BENCHMARK"?

WHY

DON'T YOU EXPLAIN THAT?
MR. GLACKIN:

SURE.

SO, I MEAN, THE WAY THAT

17

COMPANIES, IN GENERAL, USE THE RADFORD DATA IS THAT THE RADFORD

18

DATA SAYS -- THE DATA THAT THEY GET FROM RADFORD TELLS THEM

19

THAT A PARTICULAR KIND OF EMPLOYEE IN THE MARKET IS BEING PAID

20

ON AVERAGE A PARTICULAR WAGE, OR A PARTICULAR RANGE OF WAGES,

21

AND THE COMPANY DECIDES THEN, WHERE DO WE WANT TO BE RELATIVE

22

TO THE RADFORD DATA?

23

WHICH WOULD MEAN WE'RE RIGHT AT THE MEDIAN?

24

75TH PERCENTILE?

25

BE LOWER PERHAPS?

DO WE WANT TO BE IN THE 50TH PERCENTILE,
DO WE WANT TO BE

OR DO WE WANT TO BE HIGHER OR DO WE WANT TO

UNITED STATES COURT REPORTERS

40

41

1

AND THEN THEY WOULD USE THE -- THEN THEY WOULD JUST COMPUTE

2

OUT OF THE RADFORD DATA WHAT THAT BENCHMARK WOULD BE FOR THEIR

3

INTERNAL USE AND USE THAT TO SET THE SALARY STRUCTURES.

4
5

THE COURT:

GEOGRAPHY IN ADDITION TO JOB TITLE?

6
7

MR. GLACKIN:
FOR SURE.

8
9
10

IS THE RADFORD DATA BROKEN DOWN BY

I WOULD SUSPECT IT IS, BUT I DON'T KNOW

I COULD ASK.
THE COURT:

DO YOU KNOW?

DO ANY OF THE DEFENDANTS -- MR. VAN NEST,

I'M CURIOUS ABOUT THIS, YOU KNOW, BENCHMARKING

AND --

11

MR. VAN NEST:

12

THE COURT:

13

MR. VAN NEST:

YOUR HONOR --

-- THE RADFORD DATA.
YOU'VE GOT YOUR FINGER ON EXACTLY THE

14

PROBLEM, AND THE PROBLEM IS THAT YOU HAVE 2400 JOB TITLES, AND

15

YOU'RE QUITE RIGHT, IT MAKES NO SENSE THAT IF SOMEONE IN

16

SANTA CLARA THAT'S A SOFTWARE ENGINEER GETS OR DOESN'T GET A

17

CALL, A MASK DESIGNER OR A SEMICONDUCTOR PERSON IN NEW MEXICO

18

WOULD BE IMPACTED.

19

MAKE ANY SENSE.

THERE'S NO EVIDENCE OF THAT AND IT DOESN'T

20

RADFORD IS MADE UP OF THOUSANDS OF COMPANIES, AND THERE ARE

21

THOUSANDS OF JOB TITLES, AND WHAT THE DEFENDANTS HAVE TESTIFIED

22

IS THAT WHEN THEY LOOK AT A JOB TITLE, THEY'RE BENCHMARKING TO

23

A SPECIFIC JOB TITLE.

24
25

INTERNAL EQUITY IS A FACTOR THAT ONE MIGHT USE IN LOOKING
AT SIMILAR EMPLOYEES DOING A SIMILAR THING AND PERFORMING THE

UNITED STATES COURT REPORTERS

41

42

1
2

SAME WAY, SURE.
THE COURT:

BUT ISN'T THE BENCHMARK THE WAY YOU'RE

3

ABLE TO DETERMINE WHERE YOU STAND RELATIVE TO YOUR PEERS IN

4

TERMS OF COMPENSATION?

5

MR. VAN NEST:

6

JOB TITLE, TO TELL WHERE YOU FELL WITHIN THE RANGE.

7

THE COURT:

8

MR. VAN NEST:

9
10

IT WOULD ALLOW YOU, FOR A PARTICULAR

UM-HUM.
BUT, AGAIN, IT'S THOUSANDS OF

COMPANIES AND THOUSANDS OF JOB TITLES.
AND THEIR WHOLE THEORY -- YOU'VE GOT YOUR FINGER RIGHT ON

11

IT -- IS THAT EVERY ONE OF THESE 2400 JOB TITLES WOULD HAVE

12

AFFECTED EVERY OTHER ONE.

13

AND WHEN WE ASKED DR. LEAMER, "CAN YOU SHOW THAT THE

14

STRUCTURES ARE SO RIGID THAT IMPACT ON SOME WAS IMPACT ON ALL?"

15

HE NOT ONLY SAID, "NO, I DIDN'T SHOW THAT," BUT HE SAID, "I

16

DON'T BELIEVE IT'S TRUE."

17

TABS 1 AND 2 ARE THE QUOTES FROM HIS DEPOSITION, YOUR

18

HONOR, WHERE THIS WAS MADE ABUNDANTLY CLEAR THAT HE DID NOT --

19

HE WAS NOT ABLE TO CORRELATE TITLE TO TITLE; HE WAS NOT ABLE TO

20

SAY THAT A CHANGE TO SOME WOULD BE A CHANGE TO ALL; AND HE WAS

21

NOT ABLE TO SAY THAT IF YOU AFFECT THE SALARIES OF SOME PEOPLE,

22

YOU THEREFORE WILL AFFECT THE SALARIES OF SOME OR ALL BECAUSE

23

THE JOB STRUCTURE IS RIGID.

24
25

AND WE KNOW -THE COURT:

TELL ME, WHAT ARE THE RADFORD BENCHMARKS

UNITED STATES COURT REPORTERS

42

43

1

FOR JOB TITLES THAT MIGHT BE WITHIN THIS PUTATIVE TECHNICAL

2

EMPLOYEE CLASS?

IS THERE, LIKE, SOFTWARE ENGINEER?

3

MR. GLACKIN:

4

THE COURT:

5

MR. GLACKIN:

YEAH.

TECHNICAL ENGINEER?
I MEAN, I BELIEVE, FOR EXAMPLE, THAT

6

THE TESTIMONY WAS THAT AT INTEL, YOU KNOW, THEY COULD BENCHMARK

7

80 PERCENT, 75 PERCENT OF THEIR WORK FORCE DIRECTLY OFF OF

8

RADFORD JOB TITLES.

9

SO I THINK THERE -- AS MR. VAN NEST SAYS, THERE ARE

10

THOUSANDS OF COMPANIES IN THE DATA SET, THERE'S LOTS OF JOB

11

TITLES, AND IF YOU'RE INTEL OR GOOGLE OR INTUIT, YOU CAN

12

REQUEST FROM RADFORD THE BENCHMARKS THAT YOU THINK ARE RELEVANT

13

TO YOU.

14

AND I DON'T -- I DON'T KNOW THE LIST OFF THE TOP OF MY

15

HEAD, BUT THE TESTIMONY IN GENERAL WAS THAT THESE COMPANIES

16

FOUND THIS TO BE VERY USEFUL BECAUSE THERE WAS VERY -- PRETTY

17

COMPREHENSIVE COVERAGE OF THEIR WORK FORCES.

18

AND INDEED, YOU CAN SEE WHY THERE WOULD BE AN INCENTIVE TO

19

STANDARDIZE YOUR WORK FORCE AROUND THIS PARTICULAR DATA SET.

20

IT WOULD HELP YOU BE ORGANIZED.

21

THE COURT:

DID ANY OF THE FOUR REMAINING DEFENDANTS

22

BENCHMARK COMPENSATION AGAINST EACH OTHER OR AGAINST ANY OF THE

23

OTHER --

24
25

MR. VAN NEST:

THERE'S NO EVIDENCE OF THAT, YOUR

HONOR.

UNITED STATES COURT REPORTERS

43

44

1

MS. DERMODY:

YES, THERE IS.

2

MR. GLACKIN:

WELL, I DON'T -- THEY DIDN'T BENCHMARK

3

AGAINST EACH OTHER.

4

INCLUDED EACH OTHER'S DATA.

5

THINK WE'RE ARGUING THAT THEY -- THIS ISN'T -- WE'RE NOT SAYING

6

THEY CALLED EACH OTHER UP AND SET PRICE LEVELS.

7
8

MR. VAN NEST:

11

I MEAN, I -- WE'RE NOT -- I DON'T

YOUR HONOR, I DON'T THINK THAT ALL

FOUR REMAINING DEFENDANTS EVEN USED RADFORD.

9
10

THEY BENCHMARKED AGAINST RADFORD, WHICH

THERE'S NO EVIDENCE THAT ANY DEFENDANT BENCHMARKED OFF OF
IT.

THAT'S NEVER BEEN THEIR THEORY.
THEIR THEORY HAS BEEN THAT IF SOME EMPLOYEES WERE AFFECTED,

12

THERE WOULD THEN BE THIS RIPPLE THAT RIPPLES OUT, AND AS YOU

13

POINTED OUT, MAYBE THERE'S A RIPPLE TO THE FOLKS AROUND YOU IN

14

YOUR JOB, YOU KNOW, AREA.

15

BUT CERTAINLY NO EVIDENCE, EITHER ANECDOTALLY OR

16

ECONOMICALLY, OF ANYTHING GOING ANY PARTICULAR DISTANCE,

17

PARTICULARLY WHEN WE'RE TALKING ABOUT 60,000 PEOPLE.

18

OUR POINT.

19
20
21

THAT'S

SO RADFORD IS UNIVERSAL -THE COURT:

DO ANY OF THE REMAINING FOUR DEFENDANTS

USE RADFORD?

22

MR. GLACKIN:

23

THE COURT:

24

MR. GLACKIN:

25

THE COURT:

I BELIEVE THEY ALL DO.

YEAH, THAT WAS MY IMPRESSION.
YEAH.

OKAY.

SO I'M LOOKING AT A SLIDE FROM

UNITED STATES COURT REPORTERS

44

45

1

GOOGLE ENTITLED "BENCHMARKING OVERVIEW.

2

INTENDED POSITION RELATIVE TO MARKET, NON-SALES."

3

WHAT IS GOOGLE'S

AND IT TALKS ABOUT THE ELEMENT OF PAY, BASE SALARY,

4

INCENTIVE, EQUITY COMPOSITION, HOW DO WE MEASURE THE MARKET,

5

PEER COMPARATOR COMPANIES, AND IT LISTS APPLE, INTEL, INTUIT,

6

AND ADOBE, ALONG WITH OTHERS.

7
8
9

SO I READ THAT AND IT APPEARS THAT GOOGLE IS BENCHMARKING
ITS PAY AGAINST GOOGLE, INTEL, INTUIT, AND ADOBE.
AND THERE ARE SIMILAR DOCUMENTS FOR APPLE, SIMILAR

10

DOCUMENTS FOR ADOBE WHERE THEY ARE BENCHMARKING AGAINST EACH

11

OTHER.

12

SO --

13

MR. VAN NEST:

14

THE COURT:

15

MR. VAN NEST:

16

THE COURT:

17

MR. VAN NEST:

18

THE COURT:

19

DO YOU WANT TO RESPOND TO THAT?

THE POINT IS THAT RADFORD IS --

NO, THIS IS NOT RADFORD.

THIS IS A

GOOGLE DOCUMENT SAYING WE BENCHMARK -MR. VAN NEST:

21

THE COURT:

22

MR. VAN NEST:

23

THE COURT:

25

YEAH, ABSOLUTELY.

YEAH.

20

24

YOUR HONOR --

THAT'S RIGHT.

-- AGAINST OUR PEER COMPARATOR COMPANIES.
BY --

-- WHICH INCLUDE APPLE, INTEL, INTUIT,

AND ADOBE.
MR. VAN NEST:

BY JOB.

BY JOB TITLE.

UNITED STATES COURT REPORTERS

BY JOB TITLE,

45

46

1

RIGHT?

THAT'S OUR POINT.

2

THE COURT:

IT DOESN'T SAY THAT.

3

MR. VAN NEST:

4

THE COURT:

5

MR. VAN NEST:

WELL, I --

GO AHEAD.
WELL, BUT THAT'S HOW ALL THESE SURVEYS

6

AND THAT'S HOW ALL THE EVIDENCE SHAKES OUT IS THERE ARE, AS I

7

SAID, THOUSANDS OF DIFFERENT JOB CATEGORIES, AND ALL THIS DATA

8

IS ORGANIZED BY JOB CATEGORY, AND SO WHILE THE COMPANIES WANT

9

TO KNOW WHERE THEY STAND WITHIN A PARTICULAR JOB TITLE, THERE'S

10

NO EVIDENCE OF ANY RIPPLE AFFECT THAT WOULD AFFECT THE WHOLE

11

JOB STRUCTURE.

12

THAT'S MY POINT.

THE COURT:

SO THEN SHOULD THERE JUST BE A CLASS

13

CERTIFICATION FOR EACH JOB TITLE AND SAY, OKAY, SOFTWARE

14

ENGINEER, THERE'S BENCHMARKING AMONGST THESE REMAINING

15

DEFENDANTS, AMONGST EACH OTHER, AND SO FOR THAT JOB TITLE, THAT

16

WILL BE CLASS NUMBER ONE, SOFTWARE ENGINEER.

17

MR. VAN NEST:

18

THE COURT:

19

MR. VAN NEST:

20

THE COURT:

21

MR. VAN NEST:

22

THE COURT:

23

MR. VAN NEST:

THEY -- THEY --

WHY NOT?
WELL, THEY HAVEN'T --

WHY NOT?
LET ME SAY TWO THINGS.

OKAY.
THEY HAVEN'T SHOWN FOR ANY ONE TITLE

24

THAT IF SOME FOLKS IN THAT TITLE GET A BENEFIT, OR DON'T, IT'LL

25

AFFECT EVERYBODY.

THEY HAVEN'T SHOWN THAT BECAUSE WHAT

UNITED STATES COURT REPORTERS

46

47

1

DR. MURPHY SHOWS, AND WHAT THE RAW DATA SHOWS, IS THAT THERE'S

2

HUGE VARIATION YEAR TO YEAR WITHIN A TITLE.

3

IN OTHER WORDS, THE AVERAGES MOVE, BUT MANY PEOPLE WITHIN A

4

JOB TITLE MOVE CONTRA TO THE AVERAGE, SOME BY A LITTLE, SOME BY

5

A LOT.

6

IF YOU LOOK AT TAB 4, YOUR HONOR, WHICH I'VE PLACED BEFORE

7

YOU, DR. MURPHY PUTS THE RAW DATA FOR EVERY YEAR, FOR VARIOUS

8

TITLES, AND WHAT YOU SEE ARE CHARTS EXACTLY LIKE THE ONE THAT

9

YOU SEE IN TAB 4 WHERE YOU HAVE MOVEMENT UP BY A LITTLE FOR

10

SOME EMPLOYEES, MOVEMENT UP BY A LOT, MOVEMENT DOWN BY A

11

LITTLE, MOVEMENT DOWN BY A LOT.

12

THERE IS NO --

13
14

THE COURT:

AND I AM GOING TO GET TO ALL OF THE

MURPHY AND LEAMER CHARTS AND MATERIALS.

15

MR. VAN NEST:

BUT CERTAINLY -- CERTAINLY, YOUR

16

HONOR, CERTAINLY THERE IS MERIT IN SAYING YOU CAN'T CERTIFY A

17

60,000 EMPLOYEE CLASS WITH 2400 JOB TITLES WHERE THEY DON'T

18

HAVE ANY EVIDENCE OF ANY CORRELATION BETWEEN AND AMONG JOB

19

TITLES.

20

AND AS YOU POINTED OUT LAST TIME, CLEARLY THERE ARE SOME

21

CATEGORIES OF EMPLOYEES THAT FOLKS CARED ABOUT MORE THAN

22

OTHERS.

23

THE COURT:

24

MR. VAN NEST:

25

AND WHICH ONES ARE THOSE?
WELL, I THINK MOST OF THE PEOPLE IN

THE DOCUMENTS YOUR HONOR CITED LAST TIME ARE SOFTWARE ENGINEERS

UNITED STATES COURT REPORTERS

47

48

1

AND THEY TENDED TO BE PEOPLE MORE SENIOR THAN OTHERS, AND THE

2

TOP TALENT, I THINK, WAS THE QUOTE THAT YOU GAVE AND THE

3

SOFTWARE ENGINEERS MAKE UP -- AND THERE'S A WIDE RANGE OF

4

SOFTWARE ENGINEERS, TOO, SO THEY DO A WIDE VARIETY OF THINGS.

5

BUT CERTAINLY HERE WHERE WE'VE GOT TWO-THIRDS OF OUR CLASS

6

AT INTEL WITH JOBS LIKE SEMICONDUCTOR MANUFACTURER AND CHEMICAL

7

ENGINEER, ELECTRICAL ENGINEER, MASK DESIGNER, THEY HAVE NOTHING

8

TO DO WITH ANY OF THE DOCUMENTS YOUR HONOR HAS SEEN OR CITED,

9

OR ANY OF THE EVIDENCE IN THE CASE.

10

AND IF THEY HAD GONE AND SAID -- AND TAKEN YOUR ADVICE AND

11

TRIED TO FIGURE OUT WHICH OF THESE CLASSES OR TITLES CAN I SHOW

12

SOME CORRELATION WITHIN, MAYBE WE'D HAVE SOMETHING TO TALK

13

ABOUT.

14

THEY HAVEN'T DONE EVEN THAT.

THEY HAVEN'T DONE EVEN THAT

15

BECAUSE, AS TAB 4 SHOWS -- AND I'VE GOT A COUPLE OTHER TABS

16

WHEN WE GET TO THEM, YOUR HONOR -- THERE IS HUGE VARIATION

17

WITHIN EACH TITLE.

18

FOR EXAMPLE --

19

THE COURT:

SO LET ME MAKE SURE I UNDERSTAND.

20

SO THE DEFENDANTS WOULD CONCEDE THAT THERE'S BENCHMARKING

21

WITHIN A JOB TITLE, BUT YOU'RE SAYING THERE'S NO RELATIONSHIP

22

ACROSS JOB TITLES?

23

MR. VAN NEST:

24

THE COURT:

25

MR. VAN NEST:

WE'RE -- YES.

WE'RE SAYING THAT --

OKAY.
-- WHEN PEOPLE SAY, "I WANT TO BE 65

UNITED STATES COURT REPORTERS

48

49

1

PERCENT OF SOMETHING," THEY'RE LOOKING AT A SPECIFIC JOB

2

CLASSIFICATION.

3
4
5
6

THERE IS NO BENCHMARKING -THE COURT:

SO THE CLASSIFICATION CAN CERTAINLY

INCLUDE A FAMILY OF JOB TITLES, THOUGH.
MR. VAN NEST:

I THINK THEY'RE RATHER SPECIFIC IN

7

RADFORD, BUT, YOU KNOW, I DON'T WANT TO SPEAK -- RADFORD IS NOT

8

THE ONLY SURVEY OUT THERE.

9
10
11

BUT CERTAINLY, YOUR HONOR, CERTAINLY NOBODY IS LOOKING AT
RADFORD TO BENCHMARK ACROSS JOB TITLES.
AND, AGAIN, EVEN WITHIN TITLES, THE POINT THAT WE'RE MAKING

12

IS THERE IS AN ENORMOUS RANGE OF DISCRETION.

13

BANDS WHICH AFFECTED SOME OF THE BASE SALARIES, SOME OF THEM

14

WERE $100,000, $100,000 WITHIN A BAND, AND THAT'S JUST SALARY,

15

NOT BONUS OR EQUITY.

16
17
18

THESE SALARY

THAT'S WHY YOU SEE THINGS LIKE TAB 4 WHERE SOME
EMPLOYEES -THE COURT:

WE'RE GOING TO GET TO MR. MURPHY, BUT I

19

THINK WE'LL HAVE WAY MORE THAN ENOUGH STATISTICS THAN WE ALL

20

WANT BY THE END OF THE DAY.

21

MR. VAN NEST:

22

THE COURT:

23

MR. VAN NEST:

24

THE COURT:

25

I THINK --

LET ME ASK A QUESTION.
SURE.

AND THIS GOES TO MR. GLACKIN.

WHAT EVIDENCE CAN YOU CITE TO THAT THE DEFENDANTS VIEWED

UNITED STATES COURT REPORTERS

49

50

1

EACH OTHER AS PEERS FOR COMPARING COMPENSATION, FOR HAVING SOME

2

TYPE OF COMPENSATION EQUITY ACROSS COMPANIES?

3
4
5

MR. GLACKIN:

SO I'M LOOKING AT SOMETHING THAT WAS

JUST KINDLY HANDED TO ME.
DO YOU KNOW WHAT THIS IS AN EXHIBIT TO?

6

MR. HARVEY:

7

CISNEROS DECLARATION.

8

THAT'S EXHIBIT NUMBER -- THAT'S THE

MR. GLACKIN:

9

SO THIS WOULD BE AN EXHIBIT TO

MS. CISNEROS'S DECLARATION, IT'S PLAINTIFF'S 621, WHICH IS A

10

FAIRLY TYPICAL DOCUMENT.

11

OUGHT TO JUST LET MR. VAN NEST AT LEAST SEE WHAT I'M TALKING

12

ABOUT.

13

MR. VAN NEST:

14

MR. GLACKIN:

15

IT'S AN E-MAIL WHERE -- I FEEL LIKE I

THANK YOU.
IN FACT, WE CAN STAND HERE TOGETHER.

THIS IS AN E-MAIL, AN INTERNAL E-MAIL TO GOOGLE.

THE TOP

16

LINE RECIPIENT IS SHONA BROWN, WHO'S THE HEAD PERSON AT GOOGLE

17

WITH RESPECT TO H.R. AND COMPENSATION, AND IT'S A -- THERE'S A

18

SPECIFIC CALL OUT IN THE SECOND PAGE -- AND THIS IS PLAINTIFF'S

19

621, GOOGLE/HIGH-TECH --

20

EXCUSE ME, BOB.

21

MR. VAN NEST:

22

MR. GLACKIN:

SURE.
YEAH, 00336877.

23

AND, YOU KNOW, PARTWAY THROUGH THE E-MAIL, THEY ASK

24

THEMSELVES THE QUESTION, WELL, HOW DOES OUR OVERALL BUDGET

25

COMPARE TO WHO WE CONSIDER TO BE OUR PEERS?

UNITED STATES COURT REPORTERS

50

51

1
2
3
4
5
6
7
8
9
10

AND THE -- THE PEERS THAT ARE LISTED HERE ARE ADOBE,
AMAZON, APPLE, CISCO, AND INTEL.
AND THEY ASK, HOW DOES WHAT WE'RE DOING IN TERMS OF MERIT
INCREASES AND BONUS POOL THIS YEAR COMPARE TO THOSE COMPANIES?
AND I THINK THERE ARE -THE COURT:

WHAT'S THE -- WHAT'S THAT EXHIBIT NUMBER?

THAT'S THE CISNEROS DECLARATION?
MR. GLACKIN:

IT'S PLAINTIFF'S EXHIBIT 621, AND I'LL

READ THE BATES NUMBER IN CASE THAT NEEDS TO BE LOOKED AT LATER.
IT'S GOOGLE/HIGH-TECH -- 00 -- 621 TO CISNEROS, 00336877.

11

THE COURT:

0033687?

12

MR. GLACKIN:

13

THE COURT:

14

MR. GLACKIN:

6877.

OKAY.

THAT'S THE BATES NUMBER.

AND, YOU KNOW, I DEPOSED MR. SMITH, THE

15

CEO OF INTUIT, AND THERE WAS A -- YOU KNOW, THERE WAS A --

16

THERE WAS AN AWARENESS AMONG, CERTAINLY AT INTUIT, AND I

17

BELIEVE AT THESE OTHER FIRMS, OF WHAT IT MEANT TO BE SORT OF A

18

TOP RANKED FIRM AND THEY HAD A VIEW OF THEMSELVES AND A DESIRE

19

TO BE THAT, AND THE OTHER TOP RANKED FIRMS IN SILICON VALLEY

20

ARE THE DEFENDANTS, YOU KNOW, INTEL, APPLE, GOOGLE.

21

I MEAN, THESE COMPANIES ARE THE -- THEY ARE THE STABLE

22

INSTITUTIONAL, YOU KNOW, CREME DE LA CREME, TOP OF THE CROP IN

23

TERMS OF WHO YOU'D WANT TO WORK FOR, AND THERE ARE -- THERE ARE

24

MANY EXAMPLES IN THE RECORD OF THEM LOOKING AT EACH OTHER TO

25

COMPARE THEMSELVES IN TERMS OF COMPENSATION.

UNITED STATES COURT REPORTERS

51

52

1

THE COURT:

BUT HOW DOES THAT -- IT APPEARS THAT EACH

2

OF THE REMAINING DEFENDANTS HAD THESE ON-LINE TOOLS TO GET

3

INFORMATION ABOUT A SPECIFIC JOB TITLE, THE SALARY BAND AND

4

WHATNOT, AND ALSO TO SORT OF DO SOME BENCHMARKING.

5

WHERE DID -- DID YOU GET INTO, IN ANY OF THE DEPOSITIONS,

6

HOW THOSE ON-LINE TOOLS WERE CREATED, WHAT INFORMATION WAS USED

7

AND INPUTTED TO CREATE THAT SYSTEM?

8
9

MR. GLACKIN:

OR --

WELL, I THINK WE DID GET INTO THAT IN

THE DEPOSITIONS.

10

THE COURT:

OKAY.

11

MR. GLACKIN:

THE -- YOU KNOW, THE ANSWER IS THAT THE

12

H.R. DEPARTMENT WOULD INPUT THINGS LIKE RADFORD DATA, OR WHAT

13

PERCENTILE THEY WANTED TO BE AT VIS-A-VIS THE RADFORD DATA.

14

AND ANYTHING ELSE IN TERMS OF LIKE -- YOU KNOW, FOR

15

EXAMPLE, WHAT THE -- YOU SEE THIS IN THE BRIEFS.

I MEAN, WHAT

16

THE APPROPRIATE BONUS WAS FOR ONE OF FIVE PERFORMANCE RANKINGS,

17

SO THAT WOULD BE SOMETHING THAT WOULD BE DETERMINED AT THE TOP,

18

WHAT THE APPROPRIATE PERCENTAGE OR EQUITY GRANT WAS FOR A

19

PARTICULAR -- YOU KNOW, HOW YOU DID THAT IN TERMS OF YOUR

20

PERFORMANCE RANKING.

21

AND THEN IF YOU'RE THE -- AND ALL OF THAT ALSO WE SEE IN

22

THE DOCUMENTS, AND THIS IS EXPLAINED IN THE BRIEF, IS CURVED

23

OUT.

24
25

I MEAN, IT'S ALL SET RELATIVE.

SO, FOR EXAMPLE, AT INTEL, INTEL -- YOU KNOW, THERE'S A LOT
OF TALK ABOUT VARIABLE COMPENSATION, BUT INTEL WANTED TO MAKE

UNITED STATES COURT REPORTERS

52

53

1

SURE THAT 60 TO 70 PERCENT OF ITS MANAGERS, OR EXCUSE ME, OF

2

ITS EMPLOYEES WERE RATED MEDIUM, AND THEN IT WANTED TO MAKE

3

SURE THAT DIFFERENT PERCENTILES AT THE TOP AND THE BOTTOM WERE

4

RATED EXCELLENT OR, YOU KNOW, NEEDS IMPROVEMENT.

5

AND IT WAS STRUCTURED OUT ON A CURVE, JUST LIKE IT WAS AT

6

ADOBE.

ADOBE'S H.R. MANAGER TESTIFIED THAT THEY SET

7

COMPENSATION ON A BELL CURVE.

8

MORE STRUCTURED COMPENSATION SYSTEM.

9

THE COURT:

I MEAN, IT'S HARD TO IMAGINE A

WHAT ARE THE THOUSANDS OF COMPANIES THAT

10

ARE IN RADFORD?

11

NOT ALL TECH, ARE IN RADFORD?

12

WHAT OTHER TYPES OF JOBS, I'M ASSUMING IT'S

MR. GLACKIN:

NO.

RADFORD IS A HUGE COMPANY AND IT

13

SERVES ALL KINDS OF DIFFERENT CORPORATIONS IN AMERICA,

14

INCLUDING PEOPLE -- YOU KNOW, COMPANIES THAT HAVE NOTHING TO DO

15

WITH TECH.

16

AND WHAT YOU ARE -- IF YOU'RE A CLIENT OF RADFORD, YOU GIVE

17

THEM -- YOU TELL THEM WHAT YOU'RE INTERESTED IN.

18

WANT TO KNOW ABOUT THESE KINDS OF JOBS OR THESE JOB TITLES.

19

EMPLOY THESE KINDS OF PEOPLE.

20

OF WORK."

21
22
23
24
25

YOU SAY, "I
I

I EMPLOY PEOPLE WHO DO THIS KIND

AND THEN RADFORD GIVES YOU, YOU KNOW, A SELECTION OF 30 OR
50 OR 100 OR MAYBE MORE JOB TITLES.
THE COURT:

AND WHERE ARE ALL THESE COMPANIES BASED?

IS IT WORLDWIDE?
MR. GLACKIN:

WELL, THERE'S A -- I MEAN, RADFORD

UNITED STATES COURT REPORTERS

53

54

1

HAS -- I DON'T KNOW THE ANSWER TO THAT QUESTION.

2

I DON'T KNOW

IF RADFORD INCLUDES INTERNATIONAL DATA.

3

BUT I KNOW THAT RADFORD DOES HAVE A SUBSET OF TECH SECTOR

4

DATA WHICH WOULD HAVE BEEN THE SUBSET THAT THIS -- THAT THESE

5

FAMILY OF COMPANIES, OR GROUP OF COMPANIES WOULD HAVE

6

SUBSCRIBED TO, OR DID SUBSCRIBE TO.

7
8
9
10
11

THE COURT:

MR. VAN NEST, DO YOU KNOW IF RADFORD HAS

GLOBAL SALARY INFORMATION?
MR. VAN NEST:

I BELIEVE IT DOES, YOUR HONOR.

YOU CAN GET VARIOUS SLICES OF RADFORD.
BUT A MORE IMPORTANT POINT, I THINK, YOUR HONOR, IS RADFORD

12

REALLY IS NOT RELEVANT TO THEIR THEORY OF THIS CASE.

13

A PRICE FIXING CASE.

14

BUT

IT'S NOT

THAT'S NOT THE POINT.

THEIR THEORY IS THAT WHEN SOME COLD -- WHEN COLD CALLS WERE

15

PROHIBITED, SOME PEOPLE IN EACH COMPANY DIDN'T GET A CALL AND

16

DIDN'T GET INFORMATION AND, THEREFORE, THAT INFORMATION DIDN'T

17

BUBBLE UP AND, THEREFORE, THERE WAS SUPPRESSION THAT PROPAGATED

18

OUT TO EVERYBODY.

19

RADFORD HAS ABSOLUTELY NOTHING TO DO WITH THAT.

RADFORD IS

20

MARKET DATA FROM THOUSANDS OF COMPANIES THAT ALL COMPANIES LOOK

21

AT, NOT JUST THESE, BUT HEWLETT-PACKARD AND EVERYBODY HERE IN

22

THE VALLEY AND EVERYWHERE ACROSS THE UNITED STATES.

23

NOT A PART OF THEIR THEORY OF IMPACT.

24
25

RADFORD IS

AND WHAT I KEEP COMING BACK TO IS THERE IS NO CORRELATION
BETWEEN JOB TITLES, EITHER WITHIN A COMPANY OR ACROSS

UNITED STATES COURT REPORTERS

54

55

1

COMPANIES.

2

HE COULDN'T FIND CORRELATION BETWEEN JOB TITLES ACROSS

3

COMPANIES BECAUSE THERE IS NONE, AND THAT'S WHAT I KEEP COMING

4

BACK TO.

5
6

DR. LEAMER LOOKED AT ALL OF THIS AND HE CONCLUDED

IF YOU WANT TO CERTIFY SOMETHING, IT CAN'T POSSIBLY BE A
CLASS OF 2400 JOB TITLES.

7

NOW, EVEN WITHIN A FEW JOB TITLES, WE HAVE SHOWN, AND I

8

DON'T THINK THEY'RE DISPUTING IT, THAT THERE'S A WIDE VARIATION

9

IN WHAT PEOPLE ARE PAID, BECAUSE MANAGERS -- AND THERE ARE

10

12,000 OF THEM IN THESE COMPANIES THAT ARE, THAT ARE

11

DEFENDANTS -- THEY HAD ABILITY, WITHIN WIDE BANDS, TO AWARD

12

DIFFERENT SALARIES, DIFFERENT BONUSES, DIFFERENT EQUITY, AND

13

THAT'S WHY TAB 4 LOOKS LIKE IT DOES.

14
15
16
17

THE COURT:

WE'RE GOING TO GET TO THAT.

I HAVE

SPECIFIC QUESTIONS ABOUT THOSE CHARTS.
MR. VAN NEST:

OKAY.

BUT THAT'S -- MY POINT IS

THERE'S WIDE VARIATION AND FLEXIBILITY.

18

THE COURT:

I HEAR YOU.

19

MR. VAN NEST:

20

MR. GLACKIN:

NOT LOCKSTEP.
MAY I RESPOND TO ONE OF YOUR QUESTIONS

21

NOW THAT I HAVE BETTER INFORMATION, WHICH IS THE DATA THAT

22

THESE COMPANIES SUBSCRIBED TO FROM RADFORD WAS U.S., SO THESE

23

COMPANIES WERE GETTING THE TECH SECTOR SLICE OF U.S. WAGE DATA

24

THAT WAS BEING COLLECTED BY RADFORD.

25

MR. VAN NEST:

YOU CAN CUT IT THINNER THAN THAT, TOO.

UNITED STATES COURT REPORTERS

55

56

1

INSIDE SILICON VALLEY, OUTSIDE SILICON VALLEY.

2

OF INTEL'S EMPLOYEES ARE OUTSIDE SILICON VALLEY.

3

HALF OF THE PROPOSED CLASS IS OUTSIDE SILICON VALLEY.

4
5
6

OBVIOUSLY MOST
MORE THAN

SO, AGAIN, I THINK, YOUR HONOR, RADFORD, WE'RE SORT OF
BARKING UP THE WRONG TREE.
THE COURT:

IT'S NOT THEIR THEORY OF IMPACT.

WELL, IT'S A WAY THAT YOU CAN GET A

7

SPREADING OF EITHER THE SUPPRESSION OR -- I SHOULD SAY THE

8

ALLEGED SUPPRESSION OR ALLEGED SALARY INCREASE BASED ON THE

9

COLD CALLING IS IF IT SORT OF GETS INCORPORATED INTO RADFORD

10

AND THEN OTHER COMPANIES ARE BENCHMARKING OFF OF RADFORD, YOU

11

CAN SEE HOW THE EFFECTS COULD GET PROPAGATED AND SPREAD --

12

MR. GLACKIN:

13

THE COURT:

14

YES.

-- BY BENCHMARKING THROUGH THESE, IN

ADDITION TO JUST WORD OF MOUTH AND --

15

MR. VAN NEST:

THERE ARE THOUSANDS OF --

16

THE COURT:

17

MR. VAN NEST:

18

THE COURT:

19

MR. VAN NEST:

20

FEED THE RADFORD DATA.

21

THAT THESE COMPANIES, EITHER ONE OF THEM OR ALL FOUR OF THEM,

22

COULD AFFECT THE RADFORD DATA.

-- INTERNAL EQUITY.
EXCUSE ME.

GO AHEAD.
THERE ARE THOUSANDS OF COMPANIES THAT
THEY HAVEN'T EVEN ATTEMPTED TO SHOW

23

I MEAN, THERE ARE THOUSANDS -- YOU'VE GOT HEWLETT-PACKARD.

24

YOU'VE GOT -- HOW MANY COMPANIES DO WE HAVE DOWN HERE THAT ARE

25

NOT IN THE GROUP, NOT TO MENTION PEOPLE AROUND THE

UNITED STATES COURT REPORTERS

56

57

1
2
3
4

UNITED STATES, ENORMOUS TECH COMPANIES?
SO RADFORD IS NOT IMPACTED BY WHAT THESE COMPANIES DO, NOR
ARE THEY CLAIMING THAT.
WHAT THEY'RE CLAIMING IS PEOPLE IN THE COMPANIES DIDN'T

5

GET THE INFORMATION THEY WANTED AND, THEREFORE, THEIR WAGES

6

WERE SUPPRESSED AND, THEREFORE, THAT SUPPRESSION WOULD HAVE

7

PROPAGATED OUT ACROSS JOB TITLES.

8
9
10
11
12

AND THAT'S WHERE WE'RE SAYING THEY HAVE THIS COMPLETE
FAILURE OF PROOF.

THEY CAN'T SHOW THAT.

THEY'VE TRIED TO SHOW, THROUGH AVERAGING, THAT THERE'S
SOME SIMILARITY WITHIN TITLES.

THAT'S WHAT DR. LEAMER DID.

BUT AVERAGING DOES EXACTLY WHAT YOU TOLD THEM NOT TO DO

13

LAST TIME.

14

VARIATION, THAT THE STRUCTURE WAS SO RIGID THAT AN IMPACT ON

15

SOME WOULD IMPACT OTHERS."

16
17
18

YOU SAID, "TELL ME HOW YOU CAN SHOW, WITH ALL THIS

AND INSTEAD OF LOOKING AT THE KIND OF VARIATION THAT
EXISTS, HE AVERAGED IT.
AND THAT'S WHAT JUDGE ALSUP IN GPU AND WHAT JUDGE BRADY IN

19

REED -- JUDGE GRADY IN REED SAID.

20

WHETHER THERE IS IMPACT ON ALL OR NEARLY ALL, OR ON A WIDE

21

GROUP, YOU CAN'T AVERAGE, BECAUSE THE FACT THAT AN AVERAGE GOES

22

UP OR DOWN DOESN'T TELL YOU WHETHER SOME, A LOT, A FEW, OR MANY

23

WERE IMPACTED.

24
25

IF YOU'RE LOOKING TO SEE

THAT'S THE WHOLE POINT.

AND THEY DID EXACTLY WHAT JUDGE ALSUP, JUDGE GRADY, THE
WEISFELDT CASE, THE FLEISHMAN CASE, ALL THESE CASES SAY WHEN

UNITED STATES COURT REPORTERS

57

58

1

THE ISSUE IS, IS THERE A BAND OF EMPLOYEES FOR WHOM WE CAN

2

PROVE THAT ALL OR NEARLY ALL WERE IMPACTED, YOU CANNOT AVERAGE.

3

THAT IS BECAUSE -- BECAUSE THE AVERAGING TAKES AWAY THE WIDE

4

VARIATION THAT EXISTS, AND THAT'S WHY JUDGE ALSUP REFUSED TO

5

CERTIFY IN GPU.

6
7
8
9

JUDGE GRADY REFUSED TO CERTIFY -THE COURT:

WELL, HE DID CERTIFY THE CLASS IN GPU.

I AGREE THAT HE DID ALSO DENY CERTIFYING -MR. VAN NEST:

10

THE COURT:

11

MR. VAN NEST:

RIGHT.

THERE WAS A VERY --

HE DENIED IN SOME AND GRANTED IN OTHERS.
WHAT HE GRANTED WAS A VERY SMALL GROUP

12

OF PEOPLE WHO DID EVERYTHING IN A SAME WAY ON A WEBSITE AND

13

BOUGHT THE SAME PRODUCT AT THE SAME TIME.

14

THAT'S VERY DIFFERENT -- IN THE REED CASE, JUDGE GRADY

15

SAID, "I'M NOT GOING TO CERTIFY A CLASS OF EVEN 19,000 NURSES

16

THAT ALL HAVE THE SAME TITLE WHO ARE PAID ON A WAGE GRID THAT

17

DOESN'T EVEN MEASURE PERFORMANCE, JUST YEARS OF SERVICE."

18

THE COURT:

UM-HUM.

19

MR. VAN NEST:

HE SAID, "BECAUSE YOU AVERAGED, YOU'RE

20

NOT TELLING ME WHETHER OR NOT THERE IS IMPACT ON SOME, ALL, OR

21

NEARLY ALL MEMBERS OF THE CLASS."

22

AND SO HE SAID, "NO CERT.

YOU HAVE TO PROCEED BY

23

INDIVIDUAL CLAIMS OR IN A MASS ACTION," AS I MENTIONED EARLIER,

24

WHICH IS EXACTLY THE RESULT THAT SHOULD FLOW HERE, PARTICULARLY

25

WHERE YOU MADE VERY CLEAR LAST TIME THAT BASED ON THEIR

UNITED STATES COURT REPORTERS

58

59

1

THEORY --

2

THE COURT:

LET ME INTERRUPT YOU ONE SECOND.

3

MR. VAN NEST:

4

THE COURT:

YEAH.

SO THE PLAINTIFFS HAVE SUBMITTED EVIDENCE

5

THAT ADOBE USES SALARY MATRIXES, A SALARY PLANNING TOOL, AN

6

ON-LINE SALARY RANGE WEBSITE FOR MANAGERS, AND SOMETHING CALLED

7

THE OMNITURE CURRENT COST STRUCTURE.

8
9
10
11

CAN YOU GIVE US A LITTLE INFORMATION ABOUT WHAT THAT
OMNITURE CURRENT COST STRUCTURE IS?
OR MAYBE THE PLAINTIFFS KNOW.

WHOEVER KNOWS THE ANSWER TO

THIS QUESTION.

12

MR. VAN NEST:

13

THE COURT:

14

MR. VAN NEST:

15

THE COURT:

16

MR. VAN NEST:

YOUR HONOR, I CAN ANSWER GENERALLY --

OKAY.
-- THAT ALL THESE COMPANIES --

UM-HUM.
-- HAVE SOME KIND OF COMPENSATION

17

TOOLS THAT THEY USE.

18

LIKE INTEL, YOU'VE GOT TO HAVE SOME KIND OF TOOL TO HELP YOU

19

MANAGE COMPENSATION.

20

OBVIOUSLY IF YOU HAVE 100,000 EMPLOYEES

THE POINT OF ALL OF THESE --

21

THE COURT:

22

MR. VAN NEST:

23

THE COURT:

24

MR. VAN NEST:

25

AND WHY IS THAT, FOR INTERNAL EQUITY?
NO, TO MANAGE THE COMPANY.

WHY IS THAT?
IF YOU'VE GOT A HUNDRED THOUSAND

PEOPLE, SOMEBODY HAS TO KNOW WHAT THEY'RE BEING PAID.

UNITED STATES COURT REPORTERS

SOMEBODY

59

60

1

HAS TO KNOW --

2

THE COURT:

YOU DON'T NEED A TOOL FOR THAT.

YOU JUST

3

NEED A SPREADSHEET WITH THE NAME AND AMOUNT OF MONEY THEY'RE

4

MAKING.

5

WHAT IS THE OMNITURE, PLEASE?

6

MR. VAN NEST:

7

THE COURT:

8

MR. VAN NEST:

9

IT'S A COMPANY THAT ADOBE ACQUIRED.

OKAY.
OMNITURE WAS BASICALLY AN ON-LINE

ASSISTANT FOR MARKETING.

IT'S NOT REALLY SOMETHING THAT DID

10

TOO MUCH WITH COMPENSATION.

11

ON-LINE MARKETING AND THEY WERE ACQUIRED BY ADOBE SEVERAL YEARS

12

AGO.

13
14

THE MAIN POINT OF OMNITURE WAS

MY DAUGHTER USED TO WORK THERE, SO I KNOW.

BUT GETTING BACK TO MY PRINCIPAL POINT, YOUR HONOR -THE COURT:

WELL, LET ME ASK MR. GLACKIN, DO YOU HAVE

15

ANY OTHER INFORMATION ON THIS, OR IS IT NOT REALLY RELEVANT TO

16

COMPENSATION?

17
18

MR. GLACKIN:

I DON'T HAVE ANY MORE INFORMATION FOR

YOU, YOUR HONOR.

19

THE COURT:

OKAY.

20

MR. GLACKIN:

21

THE COURT:

22

MR. GLACKIN:

SORRY.

ALL RIGHT.
I'D BE HAPPY TO RESPOND TO SOME THINGS

23

THAT MR. VAN NEST HAS SAID ABOUT OTHER CASES.

24

TAKE YOUR QUESTIONS.

25

THE COURT:

I'M HAPPY TO

YOU KNOW, WE TALKED A LOT ABOUT REED AND

UNITED STATES COURT REPORTERS

60

61

1
2

GPU LAST TIME, SO I'M OKAY.
LET ME ASK THE NEXT QUESTION.

LET ME ASK MR. GLACKIN, LAST

3

TIME AROUND YOU ALL HAD ARGUED THAT THE COURT SHOULD GRANT

4

CLASS CERT IF COMMON PROOF OF THE DEFENDANTS' ANTITRUST

5

CONSPIRACY WOULD BE THE PROMINENT ISSUE AT TRIAL.

6

MR. GLACKIN:

7

THE COURT:

8

MR. GLACKIN:

9

CORRECT.

IS THAT -- IS THAT STILL YOUR POSITION?
YES, YOUR HONOR.

I MEAN, WE THINK --

WE -- OUR POSITION IS THAT CLASS CERTIFICATION COULD BE GRANTED

10

BASED SOLELY ON THE FACT -- ON THE OVERWHELMING ISSUE OF THE

11

DEFENDANTS' LIABILITY FOR THE COMMON ILLEGAL AGREEMENTS.

12

THE COURT:

BUT HOW WOULD THAT PLAY OUT?

13

MR. GLACKIN:

WELL, I MEAN, I THINK THAT THIS GETS --

14

BACKS INTO A LITTLE BIT OF THE CONVERSATION WE WERE HAVING

15

EARLIER ABOUT TREATING THIS AS A MASS TORT ACTION --

16

THE COURT:

UM-HUM.

17

MR. GLACKIN:

-- WHICH IS THAT WHETHER -- REGARDLESS

18

OF HOW THIS ACTION IS BROUGHT, THE PROOF IS GOING TO BE THE

19

SAME.

20

IF YOU -- IF MR. HARIHARAN CAME IN HERE AND TRIED TO

21

MAINTAIN AN INDIVIDUAL ACTION AGAINST THESE COMPANIES FOR THIS

22

VIOLATION, HE'D BE MAKING THE SAME ARGUMENTS AND ADVANCING THE

23

SAME PROOF ABOUT THE SEMI-RIGID JOB STRUCTURE AT THE FIRMS,

24

WHICH MEANT THAT ANY REACTION TO THIS INCREASED LEVEL OF

25

COMPETITION WAS GOING TO BE -- TO HAVE TO HAPPEN FIRM-WIDE.

UNITED STATES COURT REPORTERS

61

62

1

SO THERE'S NO -- I MEAN, THIS IS WHERE WE KIND OF GET INTO

2

THE AMGEN AREA.

3

METHODOLOGY FOR MOVING IMPACT.

4

YOU KNOW, WE ARE REQUIRED TO SHOW A PLAUSIBLE

THE COURT:

WE'VE --

WELL, THAT'S -- THAT'S FROM

5

JUDGE ILLSTON'S CASE, RIGHT, THE METHODOLOGY?

6

JUDGE ILLSTON'S CASE, SAYS PLAUSIBLE METHODOLOGY IS ENOUGH?

7

THERE ANYTHING ELSE?

8
9

MR. GLACKIN:

WHAT, OTHER THAN
IS

I'D HAVE TO GO BACK -- I COULD LOOK AT

THE LCDS CASE AND SEE WHAT SHE'S CITING THERE.

I THINK THERE

10

ARE A NUMBER OF CASES THAT HAVE USED THE PHRASEOLOGY PLAUSIBLE

11

METHODOLOGY FOR PROVING IMPACT.
THE COURT:

12
13

AREN'T PEOPLE NOW SAYING SIGNIFICANT

PROOF?

14

MR. VAN NEST:

15

MR. GLACKIN:

16

THE COURT:

UM-HUM.
NO, ABSOLUTELY NOT.

I WILL JUST TELL YOU, AS MUCH RESPECT AS

17

I HAVE FOR JUDGE ILLSTON, I WOULD FEEL RELUCTANT TO RELY ON A

18

DISTRICT COURT CASE THAT'S PRE-AMGEN, PRE-COMCAST, THAT WAS

19

AGGREGATED ON OTHER GROUNDS.

20

I DON'T KNOW.

WAS HER CLASS CERT ISSUE ACTUALLY EVEN

21

REVIEWED BY THE CIRCUIT COURT?

22

MR. GLACKIN:

23

WROTE THE OPPOSITION.

24
25

WELL, A 23(F) POSITION WAS FILED.

I

SO, YEAH, I MEAN -THE COURT:

SO WAS IT --

UNITED STATES COURT REPORTERS

62

63

1

MR. GLACKIN:

A 23(F) PETITION WENT UP AND IT WAS

2

DENIED.

THE PETITION PRESUMABLY WENT TO THE PANEL, THE MOTIONS

3

PANEL OF THE NINTH CIRCUIT.

4

THE COURT:

UH-HUH.

5

MR. GLACKIN:

AND THEY READ THE PETITION, THEY READ

6

OUR OPPOSITION, AND ABOUT 30 DAYS LATER THEY REJECTED THE

7

PETITION.

8
9
10
11

SO IF I -- IF I COULD ADDRESS THIS -THE COURT:

YOU MEAN REJECTED THE PETITION TO JUST

OVERTURN THE CLASS CERT DECISION?
MR. GLACKIN:

CORRECT.

WELL, THEY DENIED -- IT'S A

12

PETITION FOR REVIEW, AND THEN THEY COULD, I THINK IN THEORY,

13

REQUEST FURTHER BRIEFING OR THEY COULD DECIDE -- THEY COULD

14

DECIDE THE QUESTION BASED SIMPLY ON THE PETITION AND THE

15

RESPONSE, WHICH I THINK IS TOTALLY NORMAL.

16
17
18

BUT IN THE -- IN ANY EVENT, THEY DENIED THE PETITION IS
WHAT THEY DID.
THE COURT:

BUT WHY SHOULD I USE THE PLAUSIBLE

19

METHODOLOGY?

20

ENVIRONMENT WHEN ALL THE CASE LAW HAS BEEN CHANGING SO MUCH.

21

THAT SEEMS LIKE THAT'S A RISKY MOVE IN THIS

MR. GLACKIN:

WELL, I THINK THAT THE -- THE

22

SIGNIFICANT PROOF STANDARD THAT -- THE SIGNIFICANT PROOF OR THE

23

CONVINCING PROOF STANDARD THAT'S BEEN CITED BY THE

24

DEFENDANTS --

25

THE COURT:

YEAH.

UNITED STATES COURT REPORTERS

63

64

1
2
3

MR. GLACKIN:

-- IF YOU LOOK AND SEE WHERE THAT COMES

FROM, EVERY SINGLE TIME IT COMES FROM DUKES.
AND WHEN WE WERE HERE LAST TIME WE TALKED ABOUT THE FACT

4

THAT DUKES IS A CASE THAT'S ABOUT 23(A).

5

SUPREME COURT SAID THAT IF YOU ARE ARGUING THAT IT IS THE

6

ABSENCE OF A POLICY THAT HAS CAUSED HARM BY LEADING TO

7

DISCRIMINATION AGAINST A MILLION WORKERS AND THAT IS THE -- IT

8

IS THE ABSENCE OF THE POLICY THAT IS YOUR VIOLATION, AND IF

9

YOUR ONLY EVIDENCE THAT THIS IS TRULY A COMMON ISSUE IS

AND IN DUKES THE

10

STATISTICAL PROOF, IF THIS IS THE ONLY EVIDENCE OF ANY COMMON

11

ISSUE IN THE CASE UNDER RULE 23(A), THEN THAT PROOF, THEY

12

USED -- IN ONE PLACE THEY USED STRONG PROOF, IN ANOTHER PLACE

13

THEY USED CONVINCING PROOF.

14

I THINK THE NINTH CIRCUIT, IN ELLIS VERSUS COSTCO,

15

ADDRESSING THE SAME QUESTION, USED THE PHRASE SIGNIFICANT

16

PROOF.

17

SO THAT IS THE STANDARD WHEN YOU HAVE -- WHEN YOU ARE

18

ASKING WHETHER THE ONLY QUESTION UNDER 23(A) THAT COULD

19

POSSIBLY BE COMMON IS REALLY COMMON WHEN THE ONLY EVIDENCE OF

20

IT IS STATISTICAL EVIDENCE.

21

THERE IS -- WE ARE -- WE CLEAR 23(A) BY A COUNTRY MILE.

22

THIS -- WHEN IT COMES TO RULE 23(A), THIS TRULY IS A TYPICAL

23

ANTITRUST CASE WHERE THERE IS A COMMON ISSUE, AN OVERWHELMING

24

COMMON ISSUE ABOUT WHETHER OR NOT THE DEFENDANTS VIOLATED THE

25

LAW.

UNITED STATES COURT REPORTERS

64

65

1
2

AND THAT IS GOING TO BE -- THAT IS -- YOU KNOW, PERIOD,
FULL STOP.

3
4

THE COURT:

BUT YOU'RE REALLY ASKING FOR

CERTIFICATION UNDER (B)(3); RIGHT?

5

MR. GLACKIN:

CORRECT.

BUT THE POINT IS THAT THE

6

DUKES CASE IS A CASE THAT'S ABOUT RULE 23(A) AND IT'S ABOUT

7

THIS UNUSUAL CIRCUMSTANCE WHERE THE ONLY POSSIBLE -- THE ONLY

8

COMMON -- I MEAN, THIS IS THE TRIAL THAT THE SUPREME COURT WAS

9

LOOKING AT, A TRIAL WHERE AN EXPERT WITNESS TAKES THE STAND AND

10

THE ONLY EVIDENCE OF A VIOLATION THAT IS COMPANY-WIDE IS

11

STATISTICAL, AND THAT IS THE ONLY COMMON ISSUE IN THE CASE.

12

AND AT THE TIME THE COMPANY HAS -- SHOULD, IN THEORY, HAVE,

13

AS A DEFENSE AGAINST THIS CASE, THE INDIVIDUAL DECISIONS OF THE

14

MANAGERS THAT ARE ALLEGED TO BE DISCRIMINATORY.

15

SO IN THAT SITUATION, THE SUPREME COURT SAID THAT WHEN YOU

16

HAVE -- AND THIS IS WHY DUKES HAS NOT, I MEAN, HAS NOT

17

MEANINGFULLY CHANGED THE LANDSCAPE.

18

CLASS CASES IT HAS NOT HAD A MEANINGFUL EFFECT, BECAUSE IN AN

19

ANTITRUST CASE, THE COMMON ISSUE IS SOMETHING WE BLOW BY VERY

20

QUICKLY AND THEY, IN FACT, CONCEDED THAT AT THE BEGINNING OF

21

THE FIRST ARGUMENT.

CERTAINLY IN ANTITRUST

22

SO WHAT WE'RE ASKING IS WE'RE IN 23(B)(3), AND THE

23

QUESTION IS, HAVING OTHERWISE MET THE REQUIREMENTS FOR A CLASS

24

ACTION, SHOULD WE BE ALLOWED TO GO FORWARD WITH A DAMAGES CLASS

25

ACTION?

UNITED STATES COURT REPORTERS

65

66

1

AND THERE THE STANDARD IS, HAVE WE ADVANCED A PLAUSIBLE

2

METHODOLOGY FOR PROVING IMPACT?

3

THE COURT:

AND THE REASON --

BUT YOU'RE GOING TO HAVE TO GIVE ME SOME

4

AUTHORITY, OTHER THAN THE LCD ORDER, FOR PLAUSIBLE METHODOLOGY.

5

DO YOU HAVE -- IS THERE ANYTHING ELSE?

6
7

MR. GLACKIN:

WELL, I WOULD -- I WOULD RESPECTFULLY

SUBMIT THAT --

8

THE COURT:

9

MR. GLACKIN:

UH-HUH.
-- THE AMGEN CASE IS THE BEST AUTHORITY

10

FOR THIS POINT, BECAUSE WHAT THE SUPREME COURT SAYS IN AMGEN IS

11

THAT -- WHAT I THINK THE DEFENDANTS WANT YOU TO DO, WHICH IS

12

CALL A WINNER OR A LOSER ON THIS QUESTION OF WHETHER OR NOT

13

WE'VE PROVEN COMMON IMPACT, THAT IS EXACTLY WHAT THE COURT IS

14

NOT SUPPOSED TO DO.

15

THE COURT IS SUPPOSED TO SIMPLY INQUIRE WHETHER OR NOT THE

16

ISSUE IS COMMON.

17

RISE OR FALL ON COMMON PROOF, THEN IT'S APPROPRIATE TO CERTIFY

18

A CLASS ACTION.

19
20
21

AND IF THE ISSUE IS COMMON, IF IT'S GOING TO

AND IT'S NOT APPROPRIATE FOR THE COURT TO WEIGH THE
INFERENCES THAT ARE BEING OFFERED BY THE PARTIES.
THE COURT:

LET ME ASK YOU TO COMMENT ON

22

MR. VAN NEST'S SUGGESTION ABOUT THE MASS TORT BELLWETHER MODEL.

23

HOW WOULD THAT -- I GUESS I'M JUST NOT CLEAR.

24

SAYING, OBVIOUSLY THIS IS YOUR DEFAULT, DEFAULT, DEFAULT,

25

DEFAULT POSITION, JUST CERTIFY A CLASS ON ANTITRUST LIABILITY,

UNITED STATES COURT REPORTERS

IF YOU'RE

66

67

1

HOW WOULD THAT PLAY OUT?

2

TRIALS ON INDIVIDUAL IMPACT AND DAMAGES?

3

MR. GLACKIN:

WE'RE GOING TO HAVE, WHAT, INDIVIDUAL
OR WHAT?

WELL, THIS IS -- I MEAN, THIS IS

4

EXACTLY WHY IT WOULD BE, I THINK, THE WRONG -- BECAUSE, OKAY,

5

TO TELL YOU HOW IT WOULD PLAY OUT --

6

THE COURT:

7

MR. GLACKIN:

8
9
10

YEAH.
-- IN THE HYPOTHETICAL SCENARIO WHERE

THAT HAPPENED -THE COURT:

UM-HUM.

MR. GLACKIN:

-- WE WOULD HAVE THE TRIAL ON

11

LIABILITY, THAT WOULD HAPPEN.

12

GUESS WE WOULD BRING IN THE EMPLOYEES OF THESE COMPANIES ONE AT

13

A TIME TO PROVE IMPACT.

14

AND THEN WE WOULD BRING -- I

BUT IN EVERY SINGLE CASE, THE PROOF OF IMPACT WOULD BE THE

15

OPINION THAT THIS CONDUCT, THAT THIS CONDUCT AFFECTED THE PAY

16

STRUCTURE OF THE ENTIRE COMPANY.

17

AND I DON'T -- YOU KNOW, WE'RE NOT ASKING FOR THAT KIND OF

18

A CLASS TO BE CERTIFIED.

19

THAT WAY, FRANKLY.

20

I SEE NO WAY TO PROSECUTE THE CASE

IT MAKES ABSOLUTELY NO SENSE.

THE COURT:

ALL RIGHT.

SO IF I'M NOT GOING TO -- SO

21

THEN YOU WOULDN'T WANT A CLASS CERTIFIED JUST BASED ON

22

ANTITRUST LIABILITY?

23

MR. GLACKIN:

NO, BECAUSE I CAN'T -- I REALLY CAN'T

24

SEE A PLAN AFTER THAT THAT WOULD MAKE ANY SENSE, JUST LIKE I

25

CAN'T SEE HOW A MASS TORT PLAN WOULD MAKE ANY SENSE, BECAUSE

UNITED STATES COURT REPORTERS

67

68

1

THE WHOLE POINT HERE THAT WE ESTABLISHED WITH MR. MITTELSTAEDT

2

AT THE FIRST HEARING IS THAT WE'RE NEVER GOING TO KNOW WHO

3

WOULD HAVE GOTTEN THE COLD CALLS.

4

WHICH SPECIFIC JOB TITLES WOULD HAVE GOTTEN THE WAVES OF -- THE

5

COLD CALLS FROM THE 800 GOOGLE RECRUITERS.

6

BECAUSE IT DIDN'T HAPPEN.

7

THE IMPACT FROM THE COLD CALL THAT DIDN'T HAPPEN BECAUSE WE

8

DON'T KNOW WHERE THAT COLD CALL WENT.

9

WE'RE NEVER GOING TO KNOW

WE'LL NEVER KNOW

SO WE CAN NEVER TRACE OUT, YOU KNOW,

AND THAT'S WHY THE DEFENDANTS WANT THIS STANDARD.

IF THE

10

STANDARD IS WE HAVE TO SHOW -- THAT WE HAVE TO PROVE THAT A

11

COLD CALL HAPPENED, WOULD HAVE HAPPENED TO A SPECIFIC PERSON

12

AND SHOW THE PROPAGATION OUTWARD FROM THAT COLD CALL, I MEAN,

13

WE CAN'T WIN.

14

THAT STANDARD IS SO FAVORABLE TO THEM.

15

I MEAN, WE MIGHT AS WELL GO HOME, AND THAT'S WHY

THE COURT:

WELL, LAST TIME WHEN WE HAD SEVEN

16

DEFENDANTS, THE PARTIES PREDICTED THAT THE TRIAL WOULD BE 17

17

DAYS.

18

INTUIT?

19

WHAT IS IT NOW THAT IT'S MINUS LUCASFILM, PIXAR, AND

MR. GLACKIN:

I'M THINKING.

I MEAN, I WOULD IMAGINE

20

THAT THE PLAINTIFFS' CASE PROBABLY COULD BE PUT ON IN SOMETHING

21

LIKE SIX OR SEVEN TRIAL DAYS, MAYBE EIGHT OR NINE.

22

KNOW.

I DON'T

I'M A LITTLE HESITANT.

23

I WOULD IMAGINE THAT THE REDUCTION IN THE NUMBER OF

24

DEFENDANTS WOULD MEAN THAT YOU WOULD HAVE, YOU KNOW, FEWER

25

DEFENDANTS WHO WANTED TO PUT ONE OR TWO CORPORATE

UNITED STATES COURT REPORTERS

68

69

1

REPRESENTATIVES ON THE STAND TO SAY EITHER THAT THEY DIDN'T DO

2

ANYTHING WRONG OR THE AGREEMENTS NEVER WOULD HAVE HAD THIS

3

IMPACT.

4

SO I WOULD SUSPECT THAT ON THE DEFENSE SIDE, THE BACK END

5

WOULD GET LOWER.

6

MATTER WHAT.

7

I THINK OUR CASE IS KIND OF THE SAME NO

THE COURT:

WHAT ABOUT FOR THE DEFENDANTS?

8

THE NEW ESTIMATED TRIAL LENGTH?

9

MR. VAN NEST:

WHAT IS

10
11

I HAVEN'T THOUGHT THAT THROUGH

CAREFULLY ENOUGH, YOUR HONOR.
BUT I WOULD SAY, I THINK IT DOES MATTER.

IF THE EVIDENCE

12

FOR LUCASFILM AND PIXAR AND INTUIT IS OUT, WHICH I THINK IT

13

SHOULD BE, THEN ARGUABLY WE COULD DO IT IN LESS TIME.

14

THAT'S CLEARLY RIGHT.

15

I THINK

AND IF -- IF THEY'RE SAYING THEY WANT TO PROVE JUST EXACTLY

16

WHAT THEY STARTED OFF WITH, THEN I DON'T THINK THE TIME

17

SHRINKS.

18

BUT IN MY VIEW, THE EVIDENCE AFFECTING THOSE COMPANIES IS

19

DIFFERENT AND NOT REALLY RELATED ANYMORE AND IT WOULD BE A

20

LITTLE SHORTER.

21

I --

22

THE COURT:

23

MR. VAN NEST:

24

THE COURT:

25

LET ME -OH, SORRY.

LET ME HEAR FROM MR. GLACKIN.

YOUR -- TELL ME HOW YOUR CASE AT TRIAL WOULD LOOK.

UNITED STATES COURT REPORTERS

FOR
HOW WOULD

69

70

1

IT BREAK DOWN BETWEEN LIABILITY VERSUS IMPACT VERSUS DAMAGES?

2

MR. GLACKIN:

WELL, I CAN TELL YOU THAT, HAVING DONE

3

ONE OF THESE CASES, THAT THE IMPACT AND DAMAGES PART OF THE

4

CASE IS NOT GOING TO TAKE A LOT OF TIME.

5

SPEND A LOT OF TIME ON THOSE ISSUES AT CLASS CERTIFICATION, BUT

6

AT TRIAL, THE DIRECT EXPERT TESTIMONY ON THOSE POINTS WILL BE

7

OVER IN TWO TO THREE HOURS I WOULD SUSPECT ON IMPACT AND

8

DAMAGES.

9

I MEAN, WE -- WE

AND THEN I WOULD SUSPECT THAT THE DEFENDANTS ARE GOING TO

10

HAVE AT LEAST ONE OR POSSIBLY TWO ECONOMETRICIANS WHO WILL COME

11

IN AND SAY THAT OUR ECONOMETRICIAN IS WRONG.

12

YOU KNOW, THIS CASE -- I SUPPOSE I MIGHT HAVE TO EXPAND

13

THAT ESTIMATE A BIT IF WE'RE GOING TO HAVE EXPERT TESTIMONY --

14

IF WE'RE BUILDING INTO THAT CATEGORY EXPERT TESTIMONY ABOUT

15

THESE COMPANIES' COMPENSATION STRUCTURES.

16

BUT, AGAIN, IT'S NOT A BIG PART OF THE CASE.

MOST OF THE

17

CASE WILL BE ABOUT THE AGREEMENTS AND THE, THE SUBJECTIVE

18

INTENT OF THE PEOPLE WHO REACHED THEM.

19
20
21
22
23

BY THE WAY, I HAVE -MR. VAN NEST:

I HAVE A DIFFERENT VIEW, OBVIOUSLY,

YOUR HONOR, ON A NUMBER OF THESE POINTS.
MR. GLACKIN:

I HAVE A PLAUSIBLE METHODOLOGY CASE FOR

YOU, YOUR HONOR.

24

THE COURT:

ALL RIGHT.

25

MR. GLACKIN:

WHAT'S THAT?

I'D OFFER YOU THE GPUS DECISION, WHICH

UNITED STATES COURT REPORTERS

70

71

1

WE QUOTED IN OUR BRIEF, AND I WOULD ACTUALLY OFFER THE PASSAGE

2

THAT WE QUOTED, I THINK IN OUR REPLY BRIEF, WHICH SAYS --

3

THE COURT:

YOU KNOW, I FEEL SOMEWHAT HESITANT ON

4

RELYING ON ANY DISTRICT COURT CASE THAT WAS BEFORE THE SUPREME

5

COURT CASES.

6

BECAUSE THEY MAY ADDRESS ISSUES THAT ARE MORE ON POINT.

7
8

I MEAN, OBVIOUSLY THEY'RE -- WE MAY HAVE TO JUST

BUT ANYWAY, GO AHEAD.

SO YOU WANTED GPU, JUDGE ALSUP'S

DECISION.

9

MR. GLACKIN:

JUDGE ALSUP'S DECISION, WHICH IS THE

10

AUTHORITY THAT THE DEFENDANTS HAVE -- I MEAN, WE BLOCK QUOTED

11

THIS IN OUR BRIEF.

12

PLAINTIFFS DID IN THAT CASE WASN'T ENOUGH, HE WAS CAREFUL TO

13

QUALIFY IT BY SAYING, "THIS ORDER AGREES THAT SUCH METHODS WERE

14

PLAUSIBLY RELIABLE, SHOULD BE ALLOWED AS A MEANS OF COMMON

15

PROOF.

16

FREE PASS IN MANY INDUSTRIES."

17

WHEN HE -- WHEN HE RULED THAT WHAT THE

TO RULE OTHERWISE WOULD ALLOW ANTITRUST VIOLATORS A

THE COURT:

ALL RIGHT.

LET ME ASK MY QUESTION.

LET

18

ME ASK MR. VAN NEST, AND I THINK WE'RE GETTING -- WE'VE BEEN

19

GOING ALMOST AN HOUR AND A HALF.

20
21
22
23

(DISCUSSION OFF THE RECORD BETWEEN THE COURT AND THE COURT
REPORTER.)
THE COURT:

LET'S GO A LITTLE BIT MORE AND THEN WE'LL

HAVE TO TAKE A BREAK.

24

LET ME ASK MR. VAN NEST, IT SEEMS -- IT SEEMS LIKE THE

25

DEFENDANTS ARE ARGUING THAT IT'S NOT ENOUGH THAT THERE ARE

UNITED STATES COURT REPORTERS

71

72

1

COMMON QUESTIONS, BUT THAT THE RESULT HAS TO BE THE SAME FOR

2

ALL 60,000 CLASS MEMBERS.

3
4

DO YOU WANT TO COMMENT ON THE WHOLE SORT OF COMMON QUESTION
VERSUS COMMON ANSWERS --

5

MR. VAN NEST:

6

THE COURT:

7

-- ISSUE AND WHAT'S REQUIRED BY THE CASE

LAW --

8

MR. VAN NEST:

9

THE COURT:

10
11

SURE.

YEAH.

-- CURRENTLY?

MR. VAN NEST:

ABSOLUTELY, YOUR HONOR.

THAT'S NOT WHAT WE'RE ARGUING.

WE'RE ARGUING -- WE'RE

12

FOLLOWING UP ON WHAT YOU SAID LAST TIME, WHICH IS THAT IF YOU

13

WANT TO PROCEED AS A CLASS, A (B)(3) CLASS WHERE PEOPLE ARE

14

GOING TO GET DAMAGES, AND YOU WANT TO DO IT IN ONE BIG TRIAL,

15

YOU HAVE TO SHOW THAT ALL OR NEARLY ALL OF THE CLASS MEMBERS

16

WERE IMPACTED, BECAUSE IMPACT IS AN ELEMENT OF LIABILITY.

17

THAT'S THE WHOLE POINT.

18

IMPACTED IS NECESSARY TO ESTABLISH LIABILITY.

19

IN AN ANTITRUST CASE, WHETHER THEY'RE

SO IF WE'RE GOING TO DO IT FOR A CLASS, THE RULE IS -- AND

20

THIS IS WHAT JUDGE ALSUP SAID IN GPU AND JUDGE GRADY SAID IN

21

REED -- YOU HAVE TO SHOW THAT ALL OR NEARLY ALL MEMBERS OF THE

22

CLASS WERE IMPACTED.

23
24
25

AND YOU SAID THAT LAST TIME, TOO.

THAT'S THE ASSIGNMENT

YOU GAVE US.
NOW, IN ORDER TO SHOW THAT, YOU'RE QUITE RIGHT, THERE'S

UNITED STATES COURT REPORTERS

72

73

1

NO -- NO LONGER IS A PLAUSIBLE THEORY ENOUGH.

2

THAT, DUKES CHANGED THAT, AND ELLIS IN THE NINTH CIRCUIT

3

CHANGED THAT.

4

COMCAST CHANGED

AND YOU SAID -- YOU GOT IT RIGHT AT PAGE 16 OF YOUR ORDER

5

WHERE YOU SUMMARIZE ALL OF THIS.

6

RELY ON PLAUSIBLE THEORIES.

7

THOROUGH REVIEW OF THEIR THEORY AND YOU HAVE TO DO A RIGOROUS

8

EVALUATION AND ANALYSIS TO SEE IF THIS IS REALLY PERSUASIVE."

9

AND WHAT YOU SAID LAST TIME WAS, "IF YOU GUYS WANT TO

YOU SAID, "I'M NOT GOING TO

I THINK YOU HAVE TO CONDUCT A

10

CERTIFY A CLASS, YOU HAVE TO SATISFY TWO REQUIREMENTS.

11

HAVE TO SHOW THAT THE COMP STRUCTURES WERE SO RIGID THAT IMPACT

12

ON SOME WOULD AFFECT EVERYBODY, OR NEARLY EVERYBODY; AND YOU

13

HAVE TO SHOW THAT YOUR CLASS IS NARROWLY DRAWN SO THERE AREN'T

14

A WHOLE LOT OF PEOPLE IN IT THAT WEREN'T IMPACTED AT ALL AND

15

WEREN'T INJURED AND DAMAGED," AND THEY FLUNKED ON BOTH OF THOSE

16

UNDER ANY STANDARD.

17
18
19

YOU

REMEMBER, UNDER THE STANDARD THAT JUDGE ALSUP APPLIED IN
GPU, HE DENIED CERT EVEN THERE.
THEY FAILED TO SHOW THAT THE SALARY STRUCTURES ARE SO RIGID

20

THAT WHATEVER HAPPENED WHEN PEOPLE DIDN'T GET CALLS WOULD

21

PROPAGATE.

22

AND AS I POINTED OUT, TAB 1 AND TAB 2, DR. LEAMER ADMITS

23

THAT HE CAN'T MAKE THAT SHOWING AND HE DOESN'T THINK IT'S TRUE.

24
25

SO IF THAT'S THE CASE, NOW WE'RE LOOKING AT, OKAY, WHAT DO
WE HAVE?

DO WE HAVE SOME TITLES THAT -- WHERE WE CAN SHOW

UNITED STATES COURT REPORTERS

73

74

1
2

PROPAGATION EVEN WITHIN A TITLE?
AND THE ANSWER TO THAT IS THE MURPHY EXHIBITS SHOWING LOTS

3

OF VARIATION IN THE SAME JOB TITLE YEAR IN AND YEAR OUT AT

4

EVERY ONE OF THE DEFENDANTS.

5

SO THERE ISN'T A RIGID WAGE STRUCTURE, AND --

6
7

THE COURT:

WEREN'T EVEN REALLY CHALLENGING LIABILITY, SO --

8
9

YOU KNOW, LAST TIME AROUND YOU ALL

MR. VAN NEST:

WELL, BUT -- NO, WE WERE CHALLENGING

THE SAME THING.

10

THE COURT:

BUT --

11

MR. VAN NEST:

12

THE COURT:

13

CONCEDED LIABILITY LAST TIME.

WELL, I MEAN, NO.

14

MR. VAN NEST:

15

THE COURT:

16

NO, NO.

NO.

YOU BASICALLY SORT OF

WHAT WAS --

SO I'M CURIOUS, NOW YOU'RE SAYING, "OH,

LET'S GO BACK" --

17

MR. VAN NEST:

18

THE COURT:

19

IMPACT IS --

NO.

-- "AND LIABILITY AND IMPACT IS PART OF

LIABILITY," BUT YOU ESSENTIALLY CONCEDED THAT POINT LAST TIME.

20

MR. VAN NEST:

NO, NO.

WHAT WAS SAID LAST TIME, YOUR

21

HONOR, IS -- YOU JUST INVITED THEM, DO THEY WANT TO HAVE A

22

CLASS CERTIFIED OVER WHETHER THERE WAS A CONSPIRACY TO IMPACT

23

WAGES, ET CETERA, ET CETERA.

24
25

AND THEY DON'T WANT THAT.
KAHUNA.

THEY WANT -- THEY WANT THE WHOLE

THEY WANT EVERYTHING IN ONE TRIAL.

UNITED STATES COURT REPORTERS

74

75

1

FAIR ENOUGH.

FAIR ENOUGH.

2

IF THEY WANT -- WHAT WE SAID LAST TIME WAS WE'RE NOT

3

CHALLENGING THAT PROOF OF THE CONSPIRACY IS NOT COMMON.

4

COMMON.

THAT'S

WE SAID THAT'S A COMMON ISSUE.

5

BUT THAT DOES NOT ENTITLE YOU TO CERTIFICATION BECAUSE YOU

6

HAVE TO SHOW THAT COMMON ISSUES PREDOMINATE, AND THE BIG ISSUE

7

FOR THEM IS GOING TO BE -- AND BELIEVE ME, IT'S NOT A COUPLE

8

HOURS -- THE HUGE ISSUE IN THIS CASE IS GOING TO BE, GIVEN THE

9

NATURE OF WHAT THEY'RE ALLEGING, CAN THEY SHOW IMPACT TO ALL OR

10

NEARLY ALL MEMBERS OF THE CLASS?

11

THAT'S GOING TO REQUIRE TESTIMONY FROM THE H.R. PEOPLE AT

12

EVERY SINGLE DEFENDANT.

13

EXPERTS ABOUT WHAT THE DEFENDANTS' PAY STRUCTURES AND PRACTICES

14

WERE.

15

WHAT THEY DID AND WHY.

16

EXPERTS UP TO TALK ABOUT THE BIG PICTURE.

17

IT'S GOING TO REQUIRE TESTIMONY FROM

THERE'S GOING TO BE TESTIMONY FROM EACH COMPANY ABOUT
IT'S NOT JUST PUTTING A COUPLE OF

THE JURY WOULD HAVE TO KNOW, BECAUSE YOU'RE TALKING ABOUT

18

THIS MANY EMPLOYEES, HOW DO THESE COMPANIES MANAGE H.R.?

19

DID THEY LOOK AT?

20

WHAT

HOW MUCH VARIATION WAS THERE?

WE WILL PROBABLY BE CALLING MANAGERS TO SAY, "I WOULD

21

NEVER RAISE THE SALARY OF EVERYBODY IN MY UNIT BECAUSE I'VE GOT

22

TO PROTECT MY TOP PERFORMER.

23

WOULD BE CRAZY."

I'D RUN OUT OF BUDGET.

THAT

24

AND THERE'S NO EVIDENCE THAT ANYBODY EVER DID THAT.

25

ALL THE EVIDENCE IS THAT IF YOU HAVE SOMEBODY THAT'S A

UNITED STATES COURT REPORTERS

75

76

1

HIGH PERFORMER YOU HAVE TO PROTECT, THEY GET A BIG SALARY

2

SPIKE, JUST LIKE TAB 4 AND TAB 5 SHOW.

3

AND SO THE BIG ISSUE THAT WE UNDERSTOOD FROM YOUR HONOR'S

4

ORDER, ONE OF THE BIG ISSUES THAT WAS LEFT OVER WAS, CAN THEY

5

SHOW IMPACT ON A CLASS-WIDE BASIS?

6

THAT'S WHY, IN MY VIEW, A --

7

THE COURT:

SO DO YOU BELIEVE THAT THE TEST RIGHT NOW

8

IS JUST WHETHER COMMON QUESTIONS PREDOMINATE FOR A 23(B)(3)

9

CLASS --

10

MR. VAN NEST:

11

THE COURT:

12

MR. GLACKIN:

13

THE COURT:

14

MR. VAN NEST:

15

THE COURT:

16

MR. VAN NEST:

YOU HAVE --

-- TO BE CERTIFIED?
ARE YOU POSITING THAT TO ME OR TO HIM?

TO MR. VAN NEST.
FOR A (B)(3) CLASS --

YES.
-- YOU HAVE TO SHOW THAT COMMON

17

QUESTIONS PREDOMINATE AND THAT THERE IS, THAT THERE IS A THEORY

18

THAT PASSES A RIGOROUS ANALYSIS BASED ON RELIABLE EVIDENCE THAT

19

THERE WAS IMPACT TO ALL OR NEARLY ALL MEMBERS OF THE CLASS.

20
21

IF YOU DON'T HAVE THAT, THEN YOU CAN PROCEED WITH
BELLWETHER TRIALS, CERTAINLY, AND WITH A BELLWETHER TRIAL --

22

THE COURT:

AND YOU'RE RELYING, FOR THAT SECOND HALF,

23

SEPARATE FROM WHETHER COMMON QUESTIONS PREDOMINATE, JUST ON MY

24

ORDER?

25

THAT'S WHAT YOU'RE BASING IT ON?
MR. VAN NEST:

I'M RELYING PRIMARILY ON YOUR ORDER.

UNITED STATES COURT REPORTERS

76

77

1
2

BUT THAT'S WHAT JUDGE ALSUP AND JUDGE GRADY, ALL THESE
CASES -- THE WHOLE POINT --

3
4

THE COURT:

WHAT ARE YOU RELYING ON FOR YOUR

SECOND -- ARTICULATE THE SECOND HALF --

5

MR. VAN NEST:

6

THE COURT:

7
8
9

THE SECOND HALF --

-- OF WHAT YOU BELIEVE THE STANDARD TO

BE.
MR. VAN NEST:

I BELIEVE THE STANDARD IS THAT THE

PLAINTIFFS HAVE TO SHOW THAT THEY CAN PROVE, BY COMMON

10

EVIDENCE, THAT THERE WAS CLASS-WIDE IMPACT, AND I'LL CITE

11

COMCAST FOR THAT, I'LL CITE AMCHEM FOR THAT, I'LL CITE REED FOR

12

THAT, I'LL CITE GPU FOR THAT.

13

ALL THESE CASES SAY THAT YOU HAVE TO BE ABLE TO PROVE, FOR

14

A (B)(3) CLASS -- WHICH IS A HIGHER STANDARD, BY THE WAY, THAN

15

JUST A 23(A) -- YOU HAVE TO PROVE THAT THERE WAS IMPACT,

16

CLASS-WIDE IMPACT AS PART OF YOUR ANTITRUST CLAIM.

17
18
19

AND THEY DIDN'T DISAGREE WITH THAT.
THE COURT:

SO YOUR STANDARD IS COMMON EVIDENCE TO

PROVE CLASS-WIDE IMPACT?

20

MR. VAN NEST:

21

THE COURT:

22
23

RIGHT.

OKAY.

BECAUSE YOU HAD OTHER EXTRA

ADVERBS AND ADJECTIVES IN THERE EARLIER.
MR. VAN NEST:

WELL, I'M -- WHAT YOU -- THE WAY YOU

24

DESCRIBED IT IN THE ORDER, YOU DESCRIBED IT AS PROVING THAT

25

THERE WAS IMPACT TO ALL OR NEARLY ALL MEMBERS OF THE CLASS.

UNITED STATES COURT REPORTERS

77

78

1

THAT'S WHAT YOU SAID IN YOUR ORDER.

2

AND I WOULD AGREE WITH THAT.

THAT'S WHAT THESE CASES ALL

3

REQUIRE WHEN THEY SAY YOU HAVE TO HAVE PROOF OF CLASS-WIDE

4

IMPACT.

5

AND YOU CAN SEE -- PAGE 43 OF YOUR ORDER IS WHAT I'M

6

DRAWING ON.

7

THE STANDARD YOU SET UP AND THAT'S THE STANDARD THAT APPLIES.

8
9

PAGE 36 TO THE SAME EFFECT.

AND THEY HAVEN'T MET IT.

THAT'S WHAT -- THAT'S

THEY HAVEN'T MET IT BECAUSE

DR. LEAMER ADMITS THAT HE CAN'T SAY THAT THE SALARY STRUCTURES

10

WERE SO RIGID THAT CHANGES TO SOME WOULD HAVE TRANSLATED INTO

11

CHANGES FOR ALL.

12

AND THE RAW DATA THAT WE'VE PRESENTED AND THAT DR. MURPHY

13

ANALYZED PROVES IT AGAIN, NAMELY, THERE'S HUGE VARIATION AND

14

FLEXIBILITY IN PAY AND IT'S BASED ON INDIVIDUAL FACTORS.

15

AND WHAT DR. SHAW DID, OUR ECONOMIST FROM STANFORD -- SHE

16

HAS BEEN IN SILICON VALLEY FOR THE PAST 20 YEARS TALKING TO

17

H.R. PEOPLE, AND SHE SAYS THE DATA THAT COMES OUT OF THESE

18

COMPANIES IS CONSISTENT WITH THE PREVAILING PRINCIPLE IN

19

SILICON VALLEY, PAY FOR PERFORMANCE.

PAY FOR PERFORMANCE.

20

THESE ARE ENTREPRENEURIAL COMPANIES.

THEY ARE CUTTING EDGE.

21

THEY ARE NOT LOCKSTEP.

22

KNOW, GOVERNED BY COLLECTIVE BARGAINING AGREEMENTS WHERE

23

EVERYTHING IS IN SOME KIND OF A SCHEDULE.

24

PERFORMANCE, AND THE DATA PROVES THAT.

25

THEY ARE NOT LABOR.

THEY ARE NOT, YOU

IT'S PAY FOR

AND GIVEN THAT THAT'S THE CASE, WE'RE BETTER OFF TRYING A

UNITED STATES COURT REPORTERS

78

79

1

HANDFUL -- AND I MEAN A HANDFUL -- OF CASES WHERE AN INDIVIDUAL

2

PLAINTIFF COMES IN AND SAYS, "I WAS AT COMPANY A AND COMPANY A

3

HAD AN AGREEMENT WITH COMPANY B AND I AND MANY OTHERS WERE

4

PRIME PERFORMING CANDIDATES THAT WOULD HAVE GOTTEN COLD CALLS

5

AND HERE'S HOW I WAS INJURED.

6

PAY WOULD HAVE GONE UP," AND SO ON AND SO FORTH.

I WOULD HAVE GOTTEN A CALL, MY

7

THAT'S GOING TO BE A BETTER WAY TO RESOLVE THIS CASE THAN

8

SOME TRIAL, WHICH THEY HAVEN'T ESTABLISHED A BASIS FOR, WHERE

9

THEY TRY TO PROVE CLASS-WIDE IMPACT ACROSS THE WHOLE CLASS WITH

10
11
12

COMMON EVIDENCE.
AND YOUR HONOR, IT'S -THE COURT:

YOU KNOW, I'M LOOKING AT THE DEFENDANTS'

13

ADMINISTRATIVE MOTION TO CONSIDER WHETHER CASES SHOULD BE

14

RELATED FILED ON JULY 19TH OF 2011, AND THE DEFENDANTS IN THIS

15

CASE BASICALLY SAID, "THESE CASES INVOLVE THE SAME ALLEGED

16

CLASS, SAME FACTUAL ALLEGATIONS, SAME CLAIMS FOR RELIEF.

17

BECAUSE THE CASES INVOLVE SUBSTANTIALLY THE SAME PARTIES,

18

EVENTS, AND ALLEGATIONS, AND BECAUSE IT APPEARS LIKELY THAT

19

THERE WILL BE AN UNDULY BURDENSOME DUPLICATION OF LABOR AND

20

EXPENSE OR CONFLICTING RESULTS IF THEY ARE HEARD BEFORE

21

DIFFERENT JUDGES, DEFENDANTS BELIEVE THEY ARE RELATED WITHIN

22

THE MEANING OF THE RELATED CASE."

23

MR. VAN NEST:

24

THE COURT:

25

I'LL STAND BY EVERY WORD OF THAT.

THERE WAS A TIME WHERE YOU ALL WANTED ALL

THIS CONSOLIDATED BECAUSE YOU CONCEDED THAT, FOR PURPOSES OF

UNITED STATES COURT REPORTERS

79

80

1

ADMINISTRATION, IT MADE MUCH MORE SENSE --

2

MR. VAN NEST:

3

THE COURT:

4

MR. VAN NEST:

5

IT DOES.

-- TO HAVE THESE TOGETHER.
ABSOLUTELY.

AND I'M NOT SAYING

ANYTHING DIFFERENT TODAY, YOUR HONOR.

6

THE COURT:

UM-HUM.

7

MR. VAN NEST:

THERE'S NO -- WE WOULDN'T WANT FIVE

8

JUDGES DECIDING THE ISSUE THAT YOUR HONOR IS EVALUATING NOW,

9

AND WE WOULDN'T WANT FIVE JUDGES HANDLING THE CASE, NO MATTER

10

HOW WE DID IT, BECAUSE AS WE SAID LAST TIME, IF THEY'RE GOING

11

TO PROVE A CONSPIRACY, THAT EVIDENCE IS COMMON TO EVERYONE.

12

RIGHT?

13

OF THIS WHERE YOU HAVE TO SHOW THAT SOMEBODY CONSPIRED TO DO

14

SOMETHING, THAT IS COMMON AND THEY INTEND TO PROVE THAT IN A

15

COMMON WAY.

16

THAT'S WHAT WE'RE SAYING IS THAT THE PROOF OF PART ONE

WE GET THAT.

NOW, YOU OFFERED THEM CERTIFICATION ON THAT AND THEY DON'T

17

WANT IT.

18

THEY WANT TO PUT 60,000 PEOPLE IN A CLASS AND START THROWING

19

SOME HUGE NUMBERS AROUND, WHICH IS WHAT THEY'RE DOING.

20
21

THEY DON'T WANT THAT BECAUSE

AND WHAT WE'RE SAYING IS YOU HAVEN'T ESTABLISHED THE
PREDICATE FOR THAT BECAUSE YOU HAVEN'T --

22
23

THEY DON'T WANT THAT.

THE COURT:

OKAY.

LET ME INTERRUPT YOU ONE SECOND,

PLEASE.

24

MR. VAN NEST:

25

THE COURT:

SURE.

LET ME ASK MR. GLACKIN --

UNITED STATES COURT REPORTERS

80

81

1

MR. GLACKIN:

I HAVE A FEW WORDS ABOUT THE LEGAL

2

STANDARD I THINK YOU'RE MULLING OVER, IF I COULD RESPOND TO

3

THAT BRIEFLY.

4

THE COURT:

GO AHEAD, PLEASE.

5

MR. GLACKIN:

SO FIRST I'D OFFER YOU ANOTHER DISTRICT

6

COURT CASE, WHICH IS PRE-AMGEN, OF COURSE, BUT I BELIEVE IT'S

7

POST-DUKES --

8

THE COURT:

OKAY.

9

MR. GLACKIN:

-- WHICH IS THE IN RE: RAIL FREIGHT

10

DECISION OUT OF THE DISTRICT OF COLUMBIA, WHICH IS 2012 WL,

11

WEST LAW, 2870207 AT STAR 60.

12

THE COURT:

13

MR. GLACKIN:

14

THE COURT:

15

MR. GLACKIN:

2870207?
2870207, CORRECT.

OKAY.
AND I THINK THE URETHANES CASE THAT WE

16

CITED IN OUR MOST RECENT BRIEF, WHICH WAS A CASE IN WHICH THE

17

COURT, AFTER TRIAL, CONSIDERED A REQUEST TO DECERTIFY A CLASS

18

POST-COMCAST AND AMGEN -- I ALWAYS MIX UP AMCHEM AND AMGEN --

19

POST-AMGEN AND COMCAST WOULD ALSO BE INSTRUCTIVE, AND IT WOULD

20

SEE -- YOU WOULD SEE A DISTRICT COURT IN AN ANTITRUST CASE

21

APPLYING THOSE NEW CASES AND DENYING A MOTION TO DECERTIFY A

22

CLASS.

23

THE COURT:

24

MR. GLACKIN:

25

WHICH CASE IS THAT?
THAT IS -- IT'S IN OUR MOST RECENT

REPLY BRIEF, IN RE: URETHANE ANTITRUST LITIGATION, 2013 U.S.

UNITED STATES COURT REPORTERS

81

82

1
2

DIST LEXIS, IT'S THE LEXIS CITE, 69784.
AND IF I COULD SAY JUST ONE MORE THING?

I MEAN, WHAT I

3

UNDERSTAND YOUR HONOR TO BE GRAPPLING WITH A LITTLE BIT HERE IS

4

THE STRONG PROOF, CONVINCING PROOF VERSUS A COMMON QUESTION IS

5

ENOUGH REGARDLESS OF WHETHER OR NOT THE ANSWER TO THE COMMON

6

QUESTION IS YES OR NO.

7

THE COURT:

8

MR. GLACKIN:

9

UM-HUM.
AND WHAT I WOULD POINT OUT IS THAT IF

DUKES WAS ABOUT THE 23(B)(3) STANDARD, YOU COULD NOT RECONCILE

10

IT WITH AMGEN.

11

THE PLAINTIFFS HAVE TO DO, AND THE REASON IS THAT DUKES IS A

12

CASE ABOUT -- IN THE CIRCUMSTANCES I DESCRIBED, WHICH I WON'T

13

REPEAT, AND AMGEN IS A CASE THAT'S ACTUALLY ABOUT RULE

14

23(B)(3).

15

THE CASES SAY VERY DIFFERENT THINGS ABOUT WHAT

SO I THINK THAT, YOU KNOW, THE LIGHT HERE IN TERMS OF WHAT

16

SHOULD BE FOLLOWED IN DECIDING WHETHER OR NOT WE'VE MET THE

17

STANDARD OF RULE 23(B)(3), WHICH IS PREDOMINANCE OF COMMON

18

QUESTIONS, IS AMGEN.

19

DUKES.

IT'S CLEARLY AMGEN AND IT'S CLEARLY NOT

20

SO, YOU KNOW, I THINK THAT -- I WOULD JUST POINT OUT THAT

21

IF THE DEFENDANTS ARE RIGHT AND DUKES IS A 23(B)(3) CASE, THE

22

SUPREME COURT IN AMGEN WOULD HAVE HAD TO OVERTURN IT BECAUSE

23

YOU CAN'T RECONCILE THOSE TWO STANDARDS.

24
25

THE COURT:

LET ME ASK, YOU KNOW, THE CASES -- THE

AMOUNT OF DOCUMENTARY EVIDENCE IN THIS CASE IS SIGNIFICANTLY

UNITED STATES COURT REPORTERS

82

83

1

GREATER, I THINK, THAN PRETTY MUCH ANY OF THE OTHER CASES.

2

KNOW, FOR EXAMPLE, IN DUKES THEY HAD SOME ANECDOTAL EVIDENCE OF

3

DISCRIMINATION FROM, WHAT, 200 -- 120 WOMEN.

4

STATISTICAL EVIDENCE AND THEN THEY HAD A SOCIOLOGIST TALK ABOUT

5

WAL-MART CULTURE.

6

THEY HAD

WE DON'T HAVE THAT SITUATION.

7

MR. GLACKIN:

8

THE COURT:

9

YOU

CORRECT.

WE HAVE A POLICY, A SPECIFIC CONTRACTUAL

POLICY AMONGST THE DEFENDANTS.

10

MR. GLACKIN:

11

THE COURT:

CORRECT.

WE'RE JUST NOT -- IF YOU LOOK AT THE

12

OTHER CASES, THEY JUST DON'T HAVE THIS LEVEL OF DOCUMENTARY

13

EVIDENCE.

14

MR. GLACKIN:

15

THE COURT:

I MEAN, IF --

SO WHAT IS THE SIGNIFICANCE OF THE

16

STATISTICAL EVIDENCE?

17

THIS MUCH DOCUMENTARY EVIDENCE?

18

MR. GLACKIN:

19
20

HOW IMPORTANT IS IT IN A CASE THAT HAS

WELL, I THINK THAT IT IS OF MUCH LESS

IMPORTANCE.
AND, YOU KNOW, AS AN EXERCISE, BECAUSE I WAS INTERESTED,

21

BEFORE WE CAME DOWN HERE I ASKED MY PARTNER, MR. HARVEY, TO

22

PULL THE EXPERT REPORTS IN GPUS, BECAUSE I WAS CURIOUS TO SEE

23

EXACTLY WHAT HAD HAPPENED BECAUSE JUDGE ALSUP'S OPINION IS A

24

LITTLE AMBIGUOUS.

25

THE DEFENDANTS CAN PULL THEM OFF OF ECF, AND YOU CAN DOWNLOAD

AND WE'D BE HAPPY TO SUPPLY THEM TO YOU, AND

UNITED STATES COURT REPORTERS

83

84

1
2

THEM FROM ECF, TOO.
AND WHAT DR. TEECE HAS IN THAT CASE IS HE HAS A CORRELATION

3

ANALYSIS WHERE HE'S MASHED TOGETHER -- HE'S CALCULATED THREE

4

CORRELATIONS.

5

OF THE ACTION INTO THREE GROUPS AND SHOW THAT THEY CORRELATE.

6
7
8
9

HE'S MASHED TOGETHER ALL THE PRODUCTS IN TERMS

HE'S GOT NO DOCUMENTARY EVIDENCE SHOWING THAT THERE WAS ANY
STRUCTURE TO HOW THESE TRANSACTIONS WERE PRICED, NONE AT ALL.
THIS IS -- THIS IS A CASE WHERE, IF I WERE GOING TO
ANALOGIZE IT TO A PRICE FIXING CASE, WE HAVE THE AGREEMENT AND

10

THEN, ON THE QUESTION OF IMPACT -- I MEAN, THIS -- AND LET ME

11

BACK UP AND SAY THIS ISSUE COMES UP BECAUSE IN THE MODERN

12

CORPORATE WORLD IN THESE PRICE FIXING CASES THERE ARE -- YOU

13

KNOW, INEVITABLY THERE ARE THOUSANDS OF DIFFERENT PRODUCTS THAT

14

ARE INVOLVED BECAUSE THERE ARE HUNDREDS OF DIFFERENT GRADES OF

15

WHATEVER CHEMICAL IT IS, OR THERE MIGHT BE -- I THINK IN THE

16

LCDS CASE, THERE WERE -- AT ANY GIVEN TIME THERE WERE HUNDREDS,

17

IF NOT THOUSANDS, OF DIFFERENT MODELS OF TFTL SCREENS, TFT LCD

18

SCREENS, EACH OF WHICH WAS JUST A LITTLE BIT DIFFERENT IN THE

19

SENSE THAT THE SCREW WAS IN A DIFFERENT PLACE.

20

THE COURT:

BUT YOU DON'T HAVE ANY CASE LAW THAT

21

REALLY SAYS THERE'S A SLIDING SCALE OF IMPORTANCE OF

22

STATISTICAL EVIDENCE BASED ON OTHER FORMS OF EVIDENCE, DO YOU?

23
24
25

MR. GLACKIN:

I'M NOT AWARE OF A CASE THAT PUTS IT

EXACTLY THAT WAY.
THE COURT:

UM-HUM.

UNITED STATES COURT REPORTERS

84

85

1

MR. GLACKIN:

BUT I WOULD OFFER THAT IF YOU HAD A

2

PRICE FIXING CASE, LIKE GPUS WHERE ALL YOU HAVE IS THREE

3

CORRELATIONS, YOU'RE LOOKING AT ONE THING.

4

THE COURT:

5

MR. GLACKIN:

YEAH.
IF YOU HAD A PRICE FIXING CASE WHERE

6

THE DEFENDANTS NOT ONLY DID THE VIOLATION, BUT THEN THEY ALL

7

CAME IN AND ADMITTED THAT THE THOUSANDS OF DIFFERENT PRODUCTS

8

WERE ALL PRICED OFF OF A BELL CURVE, THEN I THINK YOU WOULD BE

9

A LONG WAY TOWARDS PROVING THAT THE UNLAWFUL AGREEMENT THAT

10

AFFECTED THE PRICE OF SOME OF THESE THINGS HAD AN AFFECT ON ALL

11

OF THEM.

12

IT WOULD BE ALMOST AKIN TO SETTING, YOU KNOW, A PRICE

13

FIXING CONSPIRACY WHERE TARGETS WERE SET FOR BENCHMARK PRICES.

14

IF YOU COULD SHOW THEN THAT ALL THE PRICES WERE SET OFF A BELL

15

CURVE BECAUSE THAT'S JUST HOW THE DEFENDANTS DID BUSINESS, I'M

16

NOT ACTUALLY SURE -- I ACTUALLY THINK THAT TO SHOW IMPACT, YOU

17

WOULDN'T NEED TO DO ANYTHING ELSE.

18
19
20

YOU MIGHT NEED TO DO SOMETHING ELSE TO PROVE DAMAGES, WHICH
IS A WHOLE DIFFERENT ISSUE.
BUT TO SHOW IMPACT, IF YOU SHOWED, IN A PRICE FIXING CASE,

21

AN AGREEMENT TO FIX THE TARGET PRICE OF A HIGH VOLUME PRODUCT

22

AND THE DEFENDANTS CAME IN AND ADMITTED THAT THE PRICES OF THE

23

OTHER PRODUCTS WERE SET ON A BELL CURVE OFF THE HIGH VOLUME

24

PRODUCT, IN MY OPINION YOU'VE PROVEN IMPACT RIGHT THEN AND

25

THERE, OR YOU'VE CERTAINLY, IN THE ABSENCE OF ANY CONTRARY

UNITED STATES COURT REPORTERS

85

86

1

EVIDENCE, MET YOUR BURDEN OF PRODUCTION.

2

THE COURT:

LET'S GO TO AND START THE QUESTIONS ON --

3

I WAS SAVING THE BEST FOR LAST -- ALL THE STATISTICAL QUESTIONS

4

FOR THE END.

5

LET'S --

6

MR. VAN NEST:

7

THE COURT:

CAN I --

OH, I'M SORRY.

IT'S ACTUALLY 3:30.

8

MAYBE WE SHOULD -- DO YOU WANT TO JUST DO A QUICK -- TWO

9

MINUTES, PLEASE.

10
11

MR. VAN NEST:
HONOR --

12

THE COURT:

13

MR. VAN NEST:

14

THE COURT:

15

IN A MINUTE --

17

MR. GLACKIN:

18

THE COURT:
MINUTE.

I CAN'T DO MUCH IN A MINUTE.
OH, YES, YOU CAN.

LET'S GO AHEAD -- I'LL GIVE YOU HALF A

GO FOR IT.

(LAUGHTER.)

21

MR. VAN NEST:

22

THE COURT:

23

WELL, MAYBE WE

SHOULD TAKE A BREAK.
MR. VAN NEST:

20

-- FOR LEE-ANNE.

-- LET'S TAKE A BREAK.

16

19

I'LL DO WHATEVER YOU WANT, YOUR

I CAN DO EVEN MORE IN HALF A MINUTE.

I'M FEELING GENEROUS.

(LAUGHTER.)

24

MR. GLACKIN:

25

THE COURT:

NO IMPACT.

GO AHEAD.

UNITED STATES COURT REPORTERS

86

87

1

MR. VAN NEST:

THE BIG PICTURE, YOUR HONOR, IS THAT

2

IF YOU LOOK AT ALL OF THE STATISTICS, WHAT YOU SEE IS THE

3

OPPOSITE OF A RIGID WAGE STRUCTURE.

4

IS BASED ON PAYING INDIVIDUAL PEOPLE ON A LOT OF DIFFERENT

5

FACTORS BASED ON THEIR PERFORMANCE WHERE THERE IS ENORMOUS

6

VARIABILITY, YEAR TO YEAR, WITHIN THE SAME JOB TITLES

7

EMPLOYEE-TO-EMPLOYEE.

8

VERY DISCRETIONARY.

9

YOU SEE A STRUCTURE WHICH

THERE IS NO PATTERN.

IT IS -- IT IS

THAT IS THE OPPOSITE OF WHAT WOULD BE REQUIRED BASED ON

10

THEIR THEORY, THAT CALLS NOT MADE WOULD HAVE RESONATED THROUGH

11

THE WHOLE CLASS.

12

AND SO WHEN WE GET TO TALKING IN DETAIL -- AND I'VE ONLY

13

GOT A FEW PAGES OF THEM TO SHOW YOUR HONOR, JUST THE

14

HIGHLIGHTS -- YOU WILL SEE THAT WHETHER YOU LOOK AT IT WITHIN A

15

CLASS -- EXCUSE ME -- WITHIN A TITLE OR ACROSS TITLES OR ACROSS

16

COMPANIES, THERE IS NO RIGID STRUCTURE THAT COULD SUPPORT THE

17

THEORY THAT THEY ARE ADVANCING.

18

AND I WOULD SAY WITH RESPECT TO YOUR HONOR'S QUESTION ON

19

DOCUMENTARY EVIDENCE, THERE ISN'T ANY DOCUMENTARY EVIDENCE OF

20

IMPACT.

21

THAT'S THE IMPORTANT THING.

IN A LOT OF THESE CASES THERE ARE -- THERE'S ACTUAL

22

AGREEMENT BY THE DEFENDANTS THAT THERE WAS A DO NOT HIRE

23

AGREEMENT IN PLACE, OR SOME SUCH THING.

24

CASE WHERE THERE THE COURT FAILED TO CERTIFY A MUCH SMALLER

25

CLASS, EVEN THOUGH LIABILITY WAS VIRTUALLY ADMITTED, BECAUSE

THAT WAS THE WEISFELDT

UNITED STATES COURT REPORTERS

87

88

1

THE COURT SAID "YOU HAVEN'T PROVEN THAT THERE WAS IMPACT TO THE

2

CLASS ON A CLASS-WIDE BASIS."

3

AND THE SAME IS TRUE HERE.

ALL THE EVIDENCE YOUR HONOR IS

4

CITING, AND WE DON'T NEED TO DEBATE IT TODAY, ALL THAT GOES TO

5

WHETHER OR NOT THERE WERE AGREEMENTS, WHAT THE INTENT OF THEM

6

WAS, HOW WIDESPREAD THEY WERE, AND SO ON.

7

NONE OF IT GOES TO IMPACT.

THERE AREN'T DOCUMENTS THAT

8

SHOW OR ANY DISCUSSION THAT SHOWS ANYBODY WAS IMPACTED.

9

WHAT'S LACKING.

10
11

THAT'S WHY THIS CASE IS GOING TO TURN ON STATISTICS AND
STATISTICAL PROOF, AND THAT'S WHY --

12
13

THAT'S

THE COURT:

BUT YOU'RE ASKING THEM TO PROVE A

NEGATIVE.

14

MR. GLACKIN:

15

MR. VAN NEST:

16

THE COURT:

THIS IS THE PROBLEM -NO.

BECAUSE THEY HAD THE AGREEMENT, BECAUSE

17

THERE WAS NO COLD CALLING, BECAUSE PEOPLE COULD NOT SOLICIT

18

EACH OTHER'S EMPLOYEES.

19

MR. VAN NEST:

20

THE COURT:

21

MR. VAN NEST:

I'M NOT, YOUR HONOR.

WHAT'S THE -THEY SAID THEY COULD PROVE IT BECAUSE

22

THEIR WHOLE CASE THEORY WAS "WE'RE GOING TO SHOW THAT THERE'S A

23

RIGID JOB PAY STRUCTURE AT ALL OF THE DEFENDANTS, SO THAT IF WE

24

CAN SHOW THAT COLD CALLS WEREN'T MADE AND PEOPLE DIDN'T GET

25

INFORMATION, THAT THAT IMPACT ON THAT EMPLOYEE, OR THAT GROUP

UNITED STATES COURT REPORTERS

88

89

1
2

OF EMPLOYEES, WOULD RESONATE THROUGH THE WHOLE FIRM."
THAT WAS THE PROMISE THEY MADE.

3

ARGUED ON THE MOTION TO DISMISS.

4

THAT WAS THE THEORY THEY

ARGUED LAST TIME.

5
6
7
8

AND YOU SAID, "FINE.
IMPACT, PROVE IT.

LET'S SEE WHAT THE NUMBERS SHOW."

DR. LEAMER ADMITS THAT HE CAN'T SHOW IT.
THE COURT:

LET'S SAVE THAT FOR AFTER THE BREAK.

MR. VAN NEST:

12

THE COURT:
UNTIL 3:45.

OKAY?

15

THE COURT:

THE COURT:

22

THANK YOU, YOUR HONOR.

THANK YOU ALL VERY MUCH.

OKAY.

LET'S GO TO DR. LEAMER'S OPENING

EXPERT REPORT.

19

21

LET'S TAKE A BREAK

(RECESS FROM 3:34 P.M. UNTIL 3:58 P.M.)

17

20

ALL RIGHT.

THANK YOU.

MR. VAN NEST:

18

VERY GOOD.

OKAY?

14

16

WE

ARE GOING TO GET INTO THE WEEDS ON THE STATS.

11

13

IF THAT'S YOUR THEORY OF COMMON

THEY'VE COME BACK AND THEY'VE FAILED TO PROVE IT, AND

9
10

THAT WAS THE THEORY THEY

MR. GLACKIN:

YOU MEAN THE ONE DATED MAY 10TH, OF

COURSE?
THE COURT:

YES, THE ONE DATED IN MAY.

WHY DON'T YOU EXPLAIN -- LET'S START WITH EXHIBIT 2.

WHY

23

DON'T YOU JUST EXPLAIN WHAT HIS CORRELATION ANALYSIS THEORY IS.

24

WHAT DO THESE DIFFERENT THINGS REPRESENT?

25

MR. GLACKIN:

SURE.

UNITED STATES COURT REPORTERS

89

90

1

THE COURT:

START WITH EXHIBIT 2, APPLE.

2

MR. GLACKIN:

EXHIBIT 2, APPLE.

IS THERE A REASON

3

YOU DON'T WANT TO START WITH EXHIBIT 1, ADOBE?

4

EXACTLY THE SAME IN TERMS OF WHAT'S THERE AND THE ADOBE ONE HAS

5

SOME HIGHLIGHTING ON IT THAT MIGHT BE HELPFUL.

6

THE COURT:

7

MR. GLACKIN:

8
9

BECAUSE THEY'RE

THAT'S FINE.
WE CAN START WITH APPLE.

IT'S THE SAME

CHARTS EITHER WAY.
EXHIBIT 1 IS THE OUTPUT OF THE REGRESSION ANALYSIS FOR

10

ADOBE; AND THEN EXHIBIT 2 IS THE OUTPUT OF THE REGRESSION

11

ANALYSIS FOR EVERY OTHER COMPANY.

12
13

THE COURT:

WHY DOES IT LOOK DIFFERENT THAN THE APPLE

ONE?

14

MR. GLACKIN:

15

THE COURT:

16

SO WE CAN START --

YOU MEAN WHY IS THERE HIGHLIGHTING?

NO.

IF YOU LOOK UNDER SECTION 1, THE

CATEGORIES ARE DIFFERENT.

17

MR. GLACKIN:

I THINK -- SO PROBABLY -- WHAT'S

18

DIFFERENT IS THE -- SECTION 1 IS ALL JUST A REPORT OF THE

19

CHARACTERISTICS OF THE TITLE IN TERMS OF HOW MANY EMPLOYEES ARE

20

THERE AND WHAT THE HIRING RATE IS FOR EMPLOYEES IN THAT TITLE.

21

I THINK THAT SOME OF THAT INFORMATION WAS OMITTED FROM

22

EXHIBIT 2 BECAUSE IT'S NOT THAT IMPORTANT AND IT ALLOWED THERE

23

TO BE MORE SPACE BETWEEN THE COEFFICIENTS ON THE REGRESSION

24

OUTPUTS, WHICH ARE ALL THE SAME -- I MEAN, ALL THE SAME

25

COLUMNS.

I THINK THAT WAS THE ONLY REASON THAT WAS OMITTED.

UNITED STATES COURT REPORTERS

90

91

1
2
3

BUT I COULD WALK THROUGH EITHER ONE AND EXPLAIN WHAT THEY
MEAN.
SO IN OTHER WORDS, THE ONLY -- THE DIFFERENT -- THE

4

REASON -- IF YOU LOOK AT SECTION 1 OF ADOBE AND COMPARE IT TO

5

SECTION 1 OF APPLE, THEY BOTH SHOW THE YEARS OF DATA FOR THE

6

TITLE, AND WHAT THAT MEANS IS -- THAT'S THE NUMBER OF YEARS FOR

7

WHICH WE HAVE DATA FOR THAT JOB TITLE BECAUSE THAT'S A RELEVANT

8

THING TO KNOW.

9

AND THEN THE NEXT COLUMN IS TOTAL EMPLOYEE YEARS, WHICH

10

TELLS YOU THE NEXT THING YOU NEED TO KNOW, WHICH IS HOW MANY --

11

WHAT'S THE WEIGHT OF THAT JOB TITLE WITHIN THE DATA?

12

HAVE THE NUMBER OF YEARS.

13
14
15

SO YOU

AND THEN YOU HAVE THE NUMBER OF YEARS WORKED BY EMPLOYEES
IN THAT JOB TITLE, WHICH IS A RELEVANT THING TO KNOW.
THEN THE OTHER COLUMNS IN THE ADOBE CHART ARE ABOUT THE --

16

THEY'RE SORT OF OTHER WAYS OF -- OTHER DESCRIPTIONS OF THE

17

CHARACTERISTICS OF THE NUMBER OF EMPLOYEES IN THAT TITLE.

18
19
20
21
22

SO AV EMP IS THE AVERAGE NUMBER OF EMPLOYEES IN THAT TITLE
AT ANY GIVEN TIME.
D-LOG AVERAGE IS THE RATE OF CHANGE OF THE NUMBER OF
EMPLOYEES IN THE TITLE.
SO, FOR EXAMPLE, IF YOU -- LOOKING AT THE VERY TOP ONE

23

WHERE IT SAYS D-LOG AVERAGE IS .27, THAT MEANS THAT ON AVERAGE,

24

THAT TITLE WAS INCREASING BY 27 PERCENT PER YEAR.

25

AND THEN D-LOG STANDARD DEVIATION IS THE STANDARD DEVIATION

UNITED STATES COURT REPORTERS

91

92

1

OF THE RATE OF CHANGE, AND THE BIGGER THAT NUMBER IS, THE MORE

2

FLUCTUATION THERE WAS AROUND THE CHANGE OF HEAD COUNT IN ANY

3

GIVEN YEAR.

4

SO IN OTHER WORDS, IF THE STANDARD DEVIATION WAS 0, THAT

5

WOULD, I THINK, IMPLY THAT THERE WAS A STATIC 27 PERCENT

6

INCREASE IN HEAD COUNT EVERY YEAR.

7

WITH A STANDARD DEVIATION --

8

THE COURT:

9

MR. GLACKIN:

10

AND WHERE DO YOU GET THAT 27 PERCENT?

ADOBE EXHIBIT 1.

11

THE COURT:

12

MR. GLACKIN:

13

IT'S .018 AND THEN IT'S MINUS .027.

THE COURT:

OH, YOU'RE LOOKING AT THE FIRST PAGE OF

IT.

16

MR. GLACKIN:

17

THE COURT:

18

MR. GLACKIN:

19
20

WHAT I'M LOOKING AT IS EXHIBIT 1, WHICH

IS ADOBE.

14
15

THAT'S D-LOG AVERAGE .27 ON THE

YEAH.

OKAY.

I SEE.

YOU SEE THE .27, THE VERY TOP ENTRY.

SO THE .34 TELLS YOU THAT IT WASN'T .27 EVERY YEAR.
THE HEAD COUNT -- HOW THE HEAD COUNT MOVED IS NOT SUPER

21

IMPORTANT TO THE ANALYSIS AND THAT'S WHY IT WAS OMITTED FROM

22

THE LARGER REPORT OF REGRESSION RESULTS IN EXHIBIT 2.

23

WHAT YOU REALLY NEED TO KNOW TO UNDERSTAND -- TO INTERPRET

24

THOSE RESULTS, I THINK, IS THE NUMBER OF EMPLOYEE YEARS AND THE

25

NUMBER OF YEARS OF DATA WE HAVE.

THOSE ARE THE MOST IMPORTANT

UNITED STATES COURT REPORTERS

92

93

1

THINGS TO KNOW.

2

THE COURT:

OKAY.

3

MR. GLACKIN:

WHAT DOES THE T-STAT SHOW?

SO A T-STAT IS A MEASURE OF STATISTICAL

4

SIGNIFICANCE, AND A -- THE BEST WAY TO INTERPRET THEM IS THAT A

5

T-STAT OF 2.0 OR GREATER MEANS THAT THE COEFFICIENT IS

6

STATISTICALLY SIGNIFICANT TO CONVENTIONAL CONFIDENCE LEVELS,

7

WHICH I THINK IN THIS CASE WOULD BE 95 PERCENT LEVELS, OR 5

8

PERCENT LEVELS.

9

THE COURT:

SO WHAT IS HIS THEORY?

HIS THEORY IS

10

THAT IF HE CAN SHOW THAT THE AVERAGE COMPENSATION FOR A SINGLE

11

JOB TITLE, THAT THE CHANGES IN THAT COMPENSATION ARE CORRELATED

12

TO CHANGES IN THE AVERAGE COMPENSATION FOR THE ENTIRE TECHNICAL

13

CLASS, THAT THAT MEANS THEY'RE RISING AND FALLING TOGETHER?

14

THAT THE THEORY?

15

IS

OR WHAT IS IT?

MR. GLACKIN:

SO IF YOU'LL INDULGE ME, IT MIGHT HELP

16

TO GO BACK TO THE BEGINNING A LITTLE BIT, WHICH IS TO GO BACK

17

TO THE COMMON FACTORS ANALYSIS FROM THE VERY FIRST REPORT.

18

AND THE REASON IT'S IMPORTANT TO GO BACK THERE IS THAT THE

19

DEFENDANTS' MAIN ATTACK ON THIS ANALYSIS HAS BEEN TO SAY THAT

20

DR. LEAMER IGNORED INDIVIDUAL LEVEL DATA AND DIDN'T TAKE INTO

21

ACCOUNT INDIVIDUAL VARIATION WITHIN JOB TITLE AND HOW IMPORTANT

22

THAT IS.

23

AND IT'S ABSOLUTELY NOT TRUE.

THE VERY FIRST THING THAT

24

DR. LEAMER DID WAS TO ESTABLISH WHAT -- TO WHAT EXTENT COMMON

25

FACTORS LIKE JOB TITLE, AGE, AND COMPANY EXPLAIN THE

UNITED STATES COURT REPORTERS

93

94

1
2
3

COMPENSATION OF INDIVIDUAL EMPLOYEES.
AND THIS IS AT THE AREA OF, LIKE, PARAGRAPH 129 IN HIS VERY
FIRST REPORT OF OCTOBER 1ST OF 2012.

4

THE COURT:

BUT THAT DOESN'T EXPLAIN WHY HE DIDN'T

5

TAKE INDIVIDUAL COMPENSATION HERE, WHY HE AVERAGED IT BY JOB

6

TITLE.

7

MR. GLACKIN:

WELL, IT DOES ACTUALLY, BECAUSE WHAT

8

THE -- WHAT THE COMMON FACTORS ANALYSIS SHOWED IS THAT -- AND

9

EVERYBODY AGREES ABOUT THIS AT THIS POINT -- IS THAT THESE

10

COMMON FACTORS EXPLAIN 90-PLUS PERCENT OF AN EMPLOYEE'S

11

COMPENSATION, WHICH IS -- WHICH MEANS THAT IF YOU KNOW THE

12

COMPANY, JOB TITLE, AGE, AND GENDER, I THINK, ARE THE FACTORS

13

OF ANY MEMBER OF THE CLASS, YOU CAN CALCULATE, ON AVERAGE,

14

THEIR COMPENSATION, 94 PERCENT OF THEIR COMPENSATION, OR YOU

15

CAN EXPLAIN 90-PLUS PERCENT OF THEIR COMPENSATION.

16

EXCUSE ME.

AND EVERYONE AGREES THAT THAT RESULT IS MAINLY DRIVEN BY

17

TITLE, THAT IT'S ACTUALLY THE TITLE THAT DRIVES 90 PERCENT OF

18

THAT RESULT, EVEN ACCORDING TO DR. MURPHY.

19

SO -- AND OF COURSE WE EXPECT THAT, RIGHT?

IF WE HAD A

20

CASE WHERE MOST OF THE EMPLOYEES' COMPENSATION WAS EXPLAINED BY

21

THEIR GENDER, THIS WOULD BE A TITLE 7 LAWSUIT, RIGHT?

22

NOT HOW COMPANIES PAY PEOPLE.

23

THEIR GENDER, OR THEY TRY NOT TO.

24

THEIR AGE TO THE EXTENT IT'S A PROXY FOR TENURE.

25

THAT'S

THEY DON'T PAY THEM ACCORDING TO
AND THEY DO PAY ACCORDING TO

BUT JOB TITLE, EVERYONE AGREES, DRIVES 90 PERCENT PLUS OF

UNITED STATES COURT REPORTERS

94

95

1

THE COMPENSATION OF EVERY MEMBER OF THE CLASS, AND DR. MURPHY

2

AGREED WITH THIS.

3

DEPOSITION.

4

HE AGREED TO IT UNDER OATH AT HIS

SO THE VERY FIRST THING DR. LEAMER DID IS ESTABLISH THAT

5

THESE EMPLOYEES ARE EMBEDDED IN A SYSTEM THAT PAYS THEM BASED

6

ON THEIR JOB TITLE.

7

AND ALL OF THE VARIATION THE DEFENDANTS ARE TALKING ABOUT

8

IN TOTAL COMPENSATION -- BY THE WAY, THAT COMMON FACTORS

9

ANALYSIS IS A TOTAL COMP ANALYSIS.

10
11

IT'S NOT AN ANALYSIS ONLY

OF BASE SALARY.
ALL THE VARIATION THAT THE DEFENDANTS ARE SAYING IS SO

12

IMPORTANT IS IN THAT TOP AREA.

13

AREA.

14

BELOW IS DETERMINED BY COMPANY, TENURE, GENDER, AND JOB TITLE,

15

AND 90 PERCENT OF THAT IS DETERMINED BY JOB TITLE.

16

IT'S IN THAT 90 TO 100 PERCENT

THAT'S WHERE ALL THE VARIATION IS HAPPENING.

90 AND

NOW, THAT DOESN'T EVEN MEAN, BY THE WAY, THAT THE VARIATION

17

PART IS ALL DISCRETIONARY BECAUSE THERE'S OTHER FACTORS WE

18

DON'T KNOW, LIKE PEOPLE'S EDUCATION, WHICH IS NOT IN THE DATA

19

SET, THAT PROBABLY WOULD EXPLAIN EVEN MORE APPROACHING UP TO

20

THAT 100 PERCENT LEVEL.

21
22

SO THE BOTTOM LINE IS, AND THE REASON I'M -THE COURT:

SO FROM WHAT I HEAR, WHAT YOU'RE SAYING

23

IS BECAUSE HE FELT THAT THE INDIVIDUAL VARIATIONS WOULD BE

24

MINOR AND WOULD BE EXPLAINABLE BY GENDER, JOB TITLE, AND

25

WHATEVER, HE DIDN'T FEEL LIKE HE NEEDED TO INCORPORATE

UNITED STATES COURT REPORTERS

95

96

1

INDIVIDUAL AVERAGES IN THIS CORRELATION ANALYSIS, THAT HE

2

THOUGHT HE COULD JUST AVERAGE IT ACROSS THE WHOLE JOB TITLE?

3

IS THAT WHAT YOU'RE -- LIKE WHAT IS THE BOTTOM LINE OF WHAT

4

YOU'RE SAYING?

5

MR. GLACKIN:

THAT IS ALMOST RIGHT, EXCEPT I'D SAY

6

IT'S EVEN A LITTLE STRONGER.

7

THE COURT:

8

MR. GLACKIN:

9

UM-HUM.
ONCE YOU KNOW THAT 90 PERCENT OF HOW

THE EMPLOYEES ARE PAID IS BASICALLY BASED ON THEIR JOB TITLE,

10

THEN THE QUESTION IS, IS THERE -- AND THIS IS THE QUESTION THAT

11

WE UNDERSTOOD, THE LINK THAT WE UNDERSTOOD THE COURT TO HAVE

12

FOUND MISSING, WHAT IS IT THAT -- IS THERE SOMETHING HOLDING

13

THOSE JOB TITLES TOGETHER?

14

REAL WORLD THE JOB TITLES GO LIKE THIS (INDICATING), AND I AM

15

MOVING MY ARMS UP AND DOWN, OR IS THE TRUTH THAT IN THE REAL

16

WORLD THE JOB TITLES MOVE TOGETHER AND ARE CORRELATED?

RIGHT?

IS THE TRUTH THAT IN THE

17

BECAUSE IF YOU SHOW THAT 90 PERCENT OF THE EMPLOYEE TOTAL

18

COMPENSATION IS DRIVEN BY THEIR JOB TITLE AND YOU SHOW THAT THE

19

JOB TITLES ARE CORRELATED, THEN YOU HAVE SHOWN THAT THERE IS A

20

PAY STRUCTURE IN PLACE THAT WILL TEND TO HAVE -- THAT WILL TEND

21

TO SPREAD THE EFFECTS OF THESE AGREEMENTS EXACTLY THE WAY THAT

22

DR. LEAMER POSITED THEY WOULD AS A MATTER OF ECONOMIC THEORY.

23
24
25

AND THAT IS EXACTLY WHAT WE HAVE SHOWN.
THE COURT:

WHAT -- YOU KNOW, IN TAB 3 OF WHAT

MR. VAN NEST GAVE ME, I GUESS THAT'S PROBABLY FROM THE

UNITED STATES COURT REPORTERS

96

97

1

SUPPLEMENTAL REPORT, HE SAYS HE'S WORKING WITH TITLE AVERAGES

2

BECAUSE INDIVIDUAL DATA IS LIKELY TO BE DOMINATED BY FORCES

3

THAT OPERATE AT THE INDIVIDUAL LEVEL.

4
5

WHAT IS THAT?

SO THOSE ARE THE FACTORS THAT YOU'RE TALKING

ABOUT RIGHT NOW?

6

MR. GLACKIN:

7

THE COURT:

8
9
10
11

WELL, THE --

OR WHAT?

WHAT'S BEING REFERRED TO HERE?

SIMILARLY WHEN HE SAYS IN HIS REPLY REPORT THAT AVERAGING
ACROSS THE INDIVIDUALS AND ANY TITLE CAN REDUCE THE INDIVIDUAL
IDIOSYNCRATIC EFFECTS, WHAT'S HE REFERRING TO?
MR. GLACKIN:

WELL, WHAT HE'S REFERRING TO IS THAT IF

12

YOU -- AND THIS IS THE SAME THING THAT DR. MURPHY, THE SAME

13

EXPLANATION DR. MURPHY GAVE FOR USING THE ACS DATA SET --

14

EXCUSE ME -- AVERAGING, AGGREGATING AND AVERAGING THE DATA IN

15

THE ACS DATA SET, WHICH IS IF YOU WANT TO DETECT WHETHER OR NOT

16

THERE IS A STRUCTURE IN WHICH THESE JOB TITLES ARE EMBEDDED,

17

YOU HAVE TO LOOK AT THE AVERAGES, THE AVERAGE COMPENSATION

18

WITHIN THE JOB TITLE.

19
20
21
22

AND WE'VE ESTABLISHED THAT THAT'S THE APPROPRIATE LEVEL OF
AGGREGATION IN A NUMBER OF WAYS.
FIRST OF ALL, WE'VE SHOWN THAT 90 PERCENT OF THE EMPLOYEES'
COMPENSATION IS DRIVEN BY JOB TITLE.

23

SECOND OF ALL --

24

THE COURT:

25

MR. VAN NEST:

DO YOU AGREE WITH THAT?
I THINK -- I DON'T KNOW IF IT'S 90

UNITED STATES COURT REPORTERS

97

98

1

PERCENT, YOUR HONOR.

I DISAGREE WITH THE SIGNIFICANCE OF IT,

2

BUT I THINK THAT JOB TITLE DOES EXPLAIN A LOT OF COMPENSATION.

3

BUT THE JOB TITLE RANGES ARE HUGE AND THEY INCLUDE SALARY,

4

BONUS, AND EQUITY, WHICH IS WHY DR. LEAMER HAD TO AVERAGE TO

5

GET EVEN THE RESULTS HE DID.

6

THE INDIVIDUAL FORCES HE'S TALKING ABOUT THAT DOMINATE ARE

7

THINGS LIKE HOW WELL DID THE INDIVIDUAL PERFORM?

8

REALLY IMPORTANT UNIT?

9

COMPANY DOING THAT YEAR?

10
11

WAS HE IN A

HOW -- YOU KNOW, HOW WELL IS THE
FOUR FACTORS THAT APPLY TO THE

INDIVIDUAL.
AND THOSE DOMINATE, AND THEY DOMINATE BECAUSE IN

12

SILICON VALLEY, PEOPLE ARE PAID BASED ON PERFORMANCE AND THERE

13

IS NO WRITTEN -- YOU KNOW, THERE'S NO RIGID STRUCTURE.

14

THE BANDS ARE --

15
16

THE COURT:

SOME OF

BUT CAN YOU CONTROL FOR PERFORMANCE AND

STILL HAVE THE COMPENSATION MOVING TOGETHER?

17

MR. VAN NEST:

18

THE COURT:

19

MR. VAN NEST:

COULD YOU?

YEAH.
I'M NOT SURE, BECAUSE CERTAINLY THE

20

RAW DATA HERE SHOWS THAT THE COMPENSATION NEVER MOVES TOGETHER

21

FOR ANY TITLE FOR ANY OF THESE COMPANIES.

22

GET TO IN MY DATA, YOU KNOW, THE RAW DATA IN A MINUTE.

23

THAT'S WHAT WE'LL

AND WHAT HE'S SAYING HERE, DR. LEAMER, IS "IF I HAD TO LOOK

24

AT INDIVIDUAL DATA, IT WOULD BE DOMINATED BY INDIVIDUAL

25

FACTORS."

UNITED STATES COURT REPORTERS

98

99

1

AND THIS IS WHAT GRADY AND ALSUP BOTH SAID, TOO, IS THAT --

2
3

THE COURT:

FACTORS, THE IDIOSYNCRATIC EFFECTS?

4
5

BUT WHAT DID HE DEFINE AS THE INDIVIDUAL

MR. VAN NEST:

THE COURT:

7

MR. GLACKIN:

9
10

THINGS THAT OPERATE ON THE INDIVIDUAL

LEVEL, LIKE PERFORMANCE OF THE INDIVIDUAL.

6

8

WHAT WAS HE REFERRING TO?

DO YOU AGREE WITH THAT, MR. GLACKIN?
NO, I DON'T AGREE THAT THAT'S THE ONLY

FACTOR.
THE COURT:

BUT YOU AGREE THAT IT IS, THE PAID FOR

PERFORMANCE?

11

MR. GLACKIN:

12

THE COURT:

13

MR. GLACKIN:

YES.

OKAY.

I AGREE -WHAT ELSE?

WHAT ELSE?

ANOTHER FACTOR WOULD BE EDUCATION,

14

WHICH WE DON'T HAVE -- WHICH WE CAN'T USE AS A VARIABLE BECAUSE

15

IT WASN'T CONSISTENTLY RECORDED IN THE DATA, AND WE WOULD HAVE

16

LOVED TO DO THAT BECAUSE I THINK THEN WE WOULD BE ABLE TO

17

EXPLAIN EVEN MORE.

18

BUT THAT'S ONE.

AND THEN ANOTHER IMPORTANT ONE IS TENURE, OR WE'VE INCLUDED

19

THE VARIABLE OF AGE, BUT THE FACTOR IS TENURE.

20

LONGER IN THE COMPANY ARE GOING TO -- AND MORE EXPERIENCED ARE

21

GOING TO GET PAID MORE THAN PEOPLE WHO ARE NEW, AND THAT'S JUST

22

A FACT OF LIFE.

23

PEOPLE WHO ARE

AND SO IF YOU'RE TRYING TO ESTABLISH, OR DETERMINE I SHOULD

24

SAY, WHETHER OR NOT THERE'S A STRUCTURE HOLDING TOGETHER THESE

25

JOB TITLES, IT'S APPROPRIATE TO AVERAGE THE INDIVIDUAL DATA TO

UNITED STATES COURT REPORTERS

99

100

1
2

REDUCE THE EFFECT OF THOSE FACTORS.
AND THIS IS EXACTLY THE SAME APPROACH THAT DR. MURPHY TOOK

3

WITH RESPECT TO THE ACS DATA SET, AND HE EXPLAINED IT IN

4

EXACTLY THE SAME WORDS ACTUALLY.

5

MR. VAN NEST:

6

THE COURT:

SO --

WELL, DOES -- WOULD DR. LEAMER AGREE THAT

7

THERE ARE SUBSTANTIAL VARIATIONS IN COMPENSATION WITHIN A JOB

8

TITLE?

9

MR. GLACKIN:

I THINK HE'D CERTAINLY AGREE THAT

10

SOMETIMES THERE ARE, THAT THERE COULD BE.

11

THINK WE'RE RULING THAT OUT AS A POSSIBILITY.

12

IT DEPENDS WHAT YOU MEAN BY "SUBSTANTIAL."

13
14
15

I MEAN, I DON'T
I MEAN, I THINK

BUT THE -- YOU KNOW, LOOK, THE DIFFERENCES IN PAY LEVEL, I
MEAN, THEY ARE WHAT THEY ARE.
AND, YOU KNOW, THE DEFENDANTS HAVE NOT DONE AN

16

EMPLOYEE-BY-EMPLOYEE CORRELATION ANALYSIS TO SHOW THAT THE PAY

17

OF THE EMPLOYEES IS NOT CORRELATED TOGETHER.

18

TO DO THAT, YOU WOULD HAVE TO CREATE A MATRIX THAT WAS

19

60,000 -- OR FOR THE BIGGEST EMPLOYER, INTEL, YOU'D HAVE TO

20

CREATE A MATRIX THAT WAS 36,000 BY 36,000 ACROSS.

21

BUT IF YOU DID THAT, THE COMMON FACTORS ANALYSIS TELLS YOU

22

WHAT YOU WOULD SEE, WHICH IS THAT EMPLOYEES IN THE SAME JOB

23

TITLE, YOU KNOW, DO TEND TO HANG TOGETHER BECAUSE THEIR

24

COMPENSATION IS PRINCIPALLY DRIVEN BY JOB TITLE.

25

UNDISPUTED FACT AT THIS POINT, AS I UNDERSTAND IT, THAT JOB

UNITED STATES COURT REPORTERS

IT'S JUST AN

100

101

1

TITLE IS THE MAJOR DETERMINING FACTOR IN COMPENSATION.

2

HENCE THE INQUIRY THAT WE TURNED TO, WHICH IS, DOES THIS

3

STRUCTURE EXIST?

4

AND SO

AND WE UNDERSTOOD THE CRITICISMS OF THE DEFENDANTS LAST

5

TIME TO BE THAT WE HAD NOT SHOWN THAT THIS CORRELATION HELD

6

OVER TIME, AND WE HAD NOT SHOWN THAT THE -- WE HAD NOT SHOWN

7

COMPREHENSIVELY THE CORRELATION OF THE JOB TITLES BECAUSE THE

8

CO-MOVEMENT CHARTS WERE SELECTIVE.

9
10
11

SO WE SET ABOUT TO ANSWER THOSE CRITICISMS, IN ADDITIONAL
TO THE OVERBREADTH CONCERN I WOULD SAY.
MR. VAN NEST:

SO, YOUR HONOR, IT IS -- IT IS

12

DEFINITELY AGREED BY EVERYONE THAT PERFORMANCE IS A HUGE

13

FACTOR; AND IT IS NOT AGREED, CERTAINLY NOT BY US, AND I DON'T

14

THINK DR. LEAMER DISPUTES THIS, THAT THERE IS ENORMOUS

15

VARIATION IN PAY WITHIN EACH JOB TITLE.

16

THAT'S WHAT WE'RE SHOWING IN TABS 4 AND 5.

IT'S NOT THAT

17

COMPLICATED, EITHER.

WHAT WE SHOW HERE IN TAB 4 IS -- AND THIS

18

IS IN DR. MURPHY, EXHIBIT 1 -- THAT IF YOU PICK A TITLE, LIKE

19

ARCHITECT AT INTUIT, AND YOU PLOT THE PEOPLE IN THAT CATEGORY,

20

RIGHT THERE ON TAB 4 --

21

THE COURT:

22

MR. VAN NEST:

23

THE COURT:

24
25

WELL, LET ME ASK YOU A QUESTION.
-- YOU SEE HUGE VARIATION UP AND DOWN.

I HEAR THAT.

BUT YOU ALSO SEE THAT WITH GOOGLE AFTER THE BIG BANG WHERE
THEY GAVE ACROSS THE BOARD 10 PERCENT INCREASE TO ALL EMPLOYEES

UNITED STATES COURT REPORTERS

101

102

1

AND YOU STILL SEE THAT LEVEL OF VARIATION.

2

MR. VAN NEST:

3

THE COURT:

4

MR. VAN NEST:

5

THE COURT:

THAT'S RIGHT.

SO LET ME ASK -THERE'S AN EXPLANATION FOR THAT, TOO.

-- WHY IS THAT?

WHY ARE SOME PEOPLE'S

6

SALARIES GOING DOWN WHEN THE ENTIRE WORK FORCE IS GETTING A 10

7

PERCENT SALARY INCREASE?

8

MR. VAN NEST:

THEY DIDN'T GET A 10 PERCENT SALARY

9

INCREASE WITH BIG BANG, YOUR HONOR.

SO WHAT THEY GOT WAS A

10

CHANGE IN THE FORM OF COMPENSATION.

PEOPLE GOT A BUMP IN THEIR

11

BASE PAY, BUT NOT NECESSARILY IN THEIR TOTAL COMP.

12
13
14

NOT EVERYBODY GOT AN INCREASE, BY THE WAY, AS DR. LEAMER'S
TABLE SHOWS.
WHAT HAPPENED WITH BIG BANG, BY THE WAY, IS NOT AN EXAMPLE

15

OF RIPPLE.

16

CHANGE A FEW, THEN EVERYBODY GETS CHANGED BECAUSE THE JOB

17

STRUCTURES ARE RIGID.

18

IT'S NOT AN EXAMPLE OF RIPPLE.

RIPPLE -- OR EXCUSE ME.

RIPPLE IS IF I

BIG BANG WAS A VERY UNIQUE, AS

19

DR. LEAMER PUT IT, SPECIFIC RESPONSE TO ONE SET OF FACTS, WHICH

20

WAS ENORMOUS HIRING BY FACEBOOK OF GOOGLE EMPLOYEES, AND IT IS

21

AN EXTERNAL FACTOR.

22

EVERYTHING.

IT'S A COMPANY-WIDE DECISION TO MOVE

23

IT'S NOT AN EXAMPLE OF DR. LEAMER'S THEORY.

24

IN BIG BANG, BY THE WAY, TOTAL COMP DID NOT GO UP ANY MORE

25

THAT YEAR THAN IN ANY OTHER YEAR AT GOOGLE, BECAUSE WHAT THEY

UNITED STATES COURT REPORTERS

102

103

1

DID WAS THEY SAID, "WE'RE GOING TO PAY MORE IN BASE PAY, BUT

2

NOT AS MUCH IN BONUS AND EQUITY."

3

IT WAS A CHANGE IN THE MIX.

GOOGLE EMPLOYEES WERE

4

OBJECTING TO A MIX OF PAY IN WHICH EQUITY WAS HEAVILY WEIGHED

5

BECAUSE THEY DIDN'T VALUE EQUITY AS HIGH, AS HIGHLY, AND SO

6

IT -- IT WAS A SHIFT IN THE FORM OF PAYMENT, NOT NECESSARILY

7

THE TOTAL.

8
9

AND AS YOU LOOK AT CHARTS LIKE THE CHART I'M SHOWING HERE
IN TAB 4, YOUR HONOR, THE KEY POINT IS THAT PAY IS MOVING IN

10

EACH YEAR FOR SOME EMPLOYEES WITHIN THE SAME TITLE UP A LITTLE,

11

SOME DOWN A LITTLE, SOME UP A LOT, A FEW DOWN A LOT.

12

AND IF YOU LOOK AT HOW PEOPLE MOVED AGAINST THE AVERAGE, IN

13

MANY OF THESE YEARS, MORE THAN HALF THE PEOPLE IN A GIVEN TITLE

14

MOVE IN A DIFFERENT DIRECTION THAN THE AVERAGE.

15

AND WHAT WE'RE SAYING NOW --

16

THE COURT:

17

MR. VAN NEST:

18

THE COURT:

19
20
21

OKAY.

I'M SORRY.

LET ME INTERRUPT YOU.

YES.

MY QUESTION WAS HOW TO EXPLAIN THE SALARY

FALLS DURING THE BIG BANG YEAR.
SO LET ME ASK THAT TO MR. GLACKIN.
MR. GLACKIN:

SURE.

I MEAN, I -- SO THE -- WE'VE

22

NEVER DISPUTED -- WE'VE NEVER SAID THAT THE PLAINTIFF -- THAT

23

THE DEFENDANTS PAY ALL THEIR EMPLOYEES THE SAME OR THAT THEY

24

PAY THEM IN LOCKSTEP.

25

VARIATION.

WE NEVER SAID THAT, THAT THERE'S NO

THERE IS ABSOLUTELY VARIATION IN HOW THEY PAY THEIR

UNITED STATES COURT REPORTERS

103

104

1
2

EMPLOYEES.
BUT THE POINT I THINK -- I KNOW THE CHART YOU'RE THINKING

3

OF IN DR. LEAMER'S REPLY REPORT.

WHAT YOU LEARN FROM THAT --

4

SO YOU WANT -- THE ANSWER TO YOUR QUESTION IS WHY WOULD

5

SOMEBODY'S TOTAL COMP GO DOWN?

6

2010, THEY WERE -- PERHAPS THEY GOT A HIGHER, A HIGHER AMOUNT

7

OF TOTAL COMP BECAUSE THEY HAD A GOOD YEAR OR THEY GOT A BONUS.

8

I MEAN, THERE CERTAINLY CAN BE VARIABILITY IN PAY, AND SO IT

9

MIGHT BE THAT WHATEVER THEY GOT IN 2010, DESPITE THE BIG BANG,

THE ANSWER MIGHT BE THAT IN

10

EXCEEDED WHAT THEY GOT IN 2011, BUT THEIR BASE SALARY, FROM

11

WHICH A LOT OF OTHER THINGS FLOW AT THESE COMPANIES, WAS

12

INCREASED BY 10 PERCENT IN 2011.

13

AND THAT'S -- THE POINT OF THAT CHART IS TO ILLUSTRATE WHY

14

IT IS MISLEADING TO LOOK AT THE INDIVIDUAL LEVEL DATA, BECAUSE

15

I COMPLETELY DISAGREE WITH MR. VAN NEST.

16

KIND OF PREEMPTIVE RESPONSE THAT IT IS OUR POSITION WOULD HAVE

17

OCCURRED HAD THESE AGREEMENTS NOT BEEN ENTERED INTO.

18

NOT HAVE BEEN 10 PERCENT EVERY YEAR, BUT IT WAS THESE KINDS OF

19

PREEMPTIVE RESPONSES THAT WE SAY WERE PRECLUDED BY THE

20

AGREEMENTS.

21

AND LET ME SAY ONE OTHER THING.

THIS IS EXACTLY THE

IT MIGHT

I MEAN, WHEN MR. VAN NEST

22

SAYS THAT GOOGLE JUST SORT OF WASHED IT ALL OUT AND DIDN'T GIVE

23

THEIR EMPLOYEES ANY MONEY, GOOGLE TESTIFIED IN THIS CASE, AND I

24

WOULD HAVE TO GET THE CITE OUT OF THE BRIEFS, THAT THE BIG BANG

25

COST THEM $500 MILLION.

SO SOMEHOW NOTWITHSTANDING THAT THEY

UNITED STATES COURT REPORTERS

104

105

1

SMOOTHED EVERYTHING OUT AND IT DIDN'T REALLY HAVE ANY IMPACT,

2

IT COST THEM $500 MILLION.

3
4
5

SO I JUST DON'T AGREE WITH THAT AS A FACTUAL ASSERTION THAT
THIS WAS A NON-EVENT FOR THE EMPLOYEES OF GOOGLE.
THE COURT:

SO LET ME ASK, WHAT IS YOUR BEST EVIDENCE

6

THAT COMPENSATION FOR EMPLOYEES MOVES TOGETHER WITHIN THE SAME

7

JOB TITLE?

WHAT'S THE BEST EVIDENCE THAT YOU HAVE ON THAT?

8

MR. GLACKIN:

9

THE COURT:

10

THE BEST -- WITHIN THE JOB TITLE --

UM-HUM.

MR. GLACKIN:

-- THE BEST ANALYSIS WE HAVE IS THE

11

COMMON FACTORS ANALYSIS WHICH SHOWS THAT IT IS THE TITLE ITSELF

12

THAT DETERMINES 90 PERCENT, APPROXIMATELY, OF THE INDIVIDUAL

13

EMPLOYEE'S SALARY.

14

AND I JUST WANT TO STRESS AGAIN, THAT ANALYSIS WAS RUN ON

15

AN EMPLOYEE-BY-EMPLOYEE BASIS.

16

WE ASKED, WHAT PERCENT OF EACH EMPLOYEE'S COMPENSATION CAN YOU

17

EXPLAIN WITH THESE COMMON FACTORS?

18

KNOW, APPROXIMATELY 90 PERCENT IS EXPLAINED BY JOB TITLE.

19

IT WAS NOT AVERAGED.

IT WAS --

AND THE ANSWER IS, YOU

AND THAT IS THE EVIDENCE -- IT IS THAT EVIDENCE, PLUS THE

20

HUGE DOCUMENTARY RECORD, THAT THE DEFENDANTS OPERATE A

21

TITLE-BASED PAY SYSTEM.

22

SERIOUS DISPUTE AT THIS POINT THAT THE DEFENDANTS OPERATE A

23

TITLE-BASED -- THAT EACH OF THEM OPERATES A TITLE-BASED

24

COMPENSATION SYSTEM.

25

AGAIN, I CAN'T IMAGINE THAT THERE IS

THE -- IT IS THOSE TWO FACTS THAT TELL US THAT JOB TITLE IS

UNITED STATES COURT REPORTERS

105

106

1

THE RIGHT PLACE TO LOOK FOR THE EXISTENCE OF A STRUCTURE AND

2

THE RIGHT PLACE TO ASK THE QUESTION OF WHETHER OR NOT

3

COMPENSATION IS MOVING TOGETHER.

4

THE COURT:

BUT YOU WOULD CONCEDE THAT AVERAGING IT

5

BY TITLE, AS DR. LEAMER DID, DOES MASK SOME OF THE INDIVIDUAL

6

VARIATIONS --

7

MR. GLACKIN:

8

THE COURT:

9

MR. GLACKIN:

THAT'S THE POINT --

-- THAT WOULD HAPPEN WITHIN A TITLE?
I ABSOLUTELY AGREE.

I CONCEDE THAT AND

10

I AGREE WITH IT.

11

MATTER OF GOOD STATISTICS, FOR THE VERY REASONS GIVEN BY

12

DR. MURPHY WHEN HE EXPLAINED DOING THIS WITH RESPECT TO THE ACS

13

DATA.

14

AND IN FACT, IT IS NECESSARY TO DO IT, AS A

LET ME -- AGAIN, TO TALK ABOUT AVERAGING AND GPUS FOR A

15

MINUTE, GPUS DOES NOT STAND FOR THE PROPOSITION THAT ONE MAY

16

NEVER AVERAGE.

17

AVERAGING IS FUNDAMENTAL TO MOST STATISTICAL INQUIRIES.

18

YOU HAVE TO AVERAGE TO DO CORRELATION ANALYSIS.

AND DR. MURPHY TESTIFIED THAT HE AVERAGES DATA ALL THE

19

TIME.

HE SAID SOMETIMES HE DOESN'T, SOMETIMES HE DOESN'T USE

20

AGGREGATE OR AVERAGE DATA, BUT A LOT OF TIMES HE DOES.

21

CONCEDED, AVERAGING IS A BASIC, USEFUL STOOL IN STATISTICS.

AND HE

22

WHAT HAPPENED IN GPUS, AS I SAID, AND YOU CAN PULL THE

23

REPORTS OFF ECF, DR. TEECE, I THINK, DID THREE CORRELATION

24

ANALYSES.

25

PURCHASERS OF THE LITTLE -- ALL THE LITTLE GUYS AND ALL THE BIG

HE ASKED WHETHER YOU COULD CORRELATE ALL THE

UNITED STATES COURT REPORTERS

106

107

1

GUYS AND WHETHER THOSE THINGS MOVED TOGETHER IN TIME, AND HE

2

MASHED TOGETHER ALL THE PRODUCTS, ALL OF THE DISTRIBUTION

3

CHANNELS, ALL OF THE DIFFERENT OEMS INTO BIG BLOCKS.

4
5
6

WE HAVE -- YOU CAN SEE HIS REPORT OF THE CORRELATION
RESULTS.

IT'S A SINGLE TABLE WITH THREE ROWS.

WE HAVE DONE -- WE HAVE DONE THE CORRELATION ANALYSIS ON

7

THE 2400 JOB TITLES.

8

ENOUGH DATA.

9
10

WE HAVE -- WHERE POSSIBLE, WHERE WE HAVE

WE HAVEN'T DONE IT FOR ALL 2400, TO BE CLEAR.

WE HAVE EXPANDED THIS ANALYSIS TO INCLUDE ALL 2400 TITLES
IN AN ATTEMPT --

11

THE COURT:

EVERYONE KEEPS SAYING 2400 AND I THOUGHT

12

THE ORIGINAL NUMBER WAS A LITTLE HIGHER THAN THAT.

13

DIFFERENCE BECAUSE INTUIT, LUCASFILM, AND PIXAR ARE GONE?

14

MR. GLACKIN:

15

DIFFERENCE.

16

2350-ISH.

17
18

BUT I DON'T HAVE -I THOUGHT IT WAS 2536 IS WHAT I READ FROM

ONE OF THE EARLIER -- IT'S 2400 NOW?
MR. GLACKIN:

I THINK WE'RE USING THAT NUMBER

LOOSELY.

21

THE COURT:

22

MR. GLACKIN:

23

THE COURT:

24

MR. VAN NEST:

25

NO, I DON'T THINK THAT MAKES ANY

AND I THINK -- I WANT TO SAY THE NUMBER IS

THE COURT:

19
20

IS THE

OKAY.
I WOULD GO WITH WHAT'S WRITTEN DOWN.

OKAY.
2400 IS, IF NOT THE PRECISE NUMBER,

YOUR HONOR, VERY CLOSE.

UNITED STATES COURT REPORTERS

107

108

1

THE COURT:

2

MR. VAN NEST:

3

VERY CLOSE.

MR. GLACKIN:

5

THE COURT:

8

THE COURT:

9

MR. VAN NEST:
THE COURT:

11

MR. VAN NEST:

AND THAT'S IN YOUR --

WE HAVE IT BEHIND TAB 6, YOUR HONOR.

BEHIND TAB 6.
AND IF YOU'D LIKE ME TO EXPLAIN THAT,

I CAN.

13

THE COURT:

LET ME ASK, HOW DO THE PLAINTIFFS RESPOND

TO THIS?

15

MR. GLACKIN:

16

THE COURT:

SURE.

SO --

DOESN'T THIS UNDERMINE YOUR CORRELATION

THEORY?

18

MR. GLACKIN:

19

THE COURT:

20

MR. GLACKIN:

21

WHICH ONE, YOUR HONOR?

EXHIBITS 7 AND 8.

10

17

LET'S GO TO THE MURPHY EXHIBITS 7

AND 8.
MR. VAN NEST:

14

YEAH, THERE'S A LOT OF TITLES.

OKAY.

7

12

AND THERE'S NO DISPUTE ABOUT

THAT.

4

6

RIGHT.

NOT AT ALL.

WHY NOT?
THERE'S TWO REASONS THAT THESE CHARTS

ARE MISLEADING.

22

YOU HAVE TO REMEMBER THAT THE THING WE'RE ASKING IS, IS

23

THERE A RELATIONSHIP BETWEEN THE TITLES OVER TIME, OR IS THERE

24

A RELATIONSHIP BETWEEN THE TITLES AND AVERAGE -- TECHNICALLY

25

WHAT WE'VE MEASURED IS A RELATIONSHIP BETWEEN THE TITLES AND

UNITED STATES COURT REPORTERS

108

109

1

ALL THE OTHER TITLES AT THE SAME COMPANY.

2

RELATIONSHIP THERE, A POSITIVE RELATIONSHIP OVER TIME?

3
4

IS THERE A

THE QUESTION ISN'T, DO THEY ALL MOVE TOGETHER AT EXACTLY
THE SAME TIME?

5

THE QUESTION IS, IS THAT RELATION POSITIVE OVER TIME?

6

AND SO THAT PROPOSITION THAT THE RELATIONSHIP IS POSITIVE

7

OVER TIME IS COMPLETELY CONSISTENT WITH THERE SOMETIMES BEING

8

VARIATION AND WITH THEM SOMETIMES GOING IN DIFFERENT

9

DIRECTIONS.

10

BUT WHAT IT TELLS YOU IS, AND THIS WAS EXACTLY THE

11

QUESTION THAT WE UNDERSTOOD TO HAVE BEEN POSED, WHAT IT TELLS

12

YOU IS THAT OVER TIME, THE RELATIONSHIP IS POSITIVE AND THAT

13

THEY WILL TEND -- THEY ARE MOVING IN THE SAME DIRECTION

14

TOGETHER.

15

THE REASON THAT -- SO THAT'S WHY IT'S MISLEADING WITH

16

RESPECT TO THE FIRST CHART TO FOCUS ON -- I MEAN, CERTAINLY

17

THERE IS VARIATION.

18

CHART AND SIMPLY SAY, OH, YOU KNOW, THEY DIDN'T ALL MOVE THE

19

SAME WAY AT THE SAME TIME, HENCE, THERE'S NO STRUCTURE, BECAUSE

20

OVER TIME THERE IS A STRUCTURE.

21

BUT IT'S MISLEADING TO LOOK AT THE FIRST

WITH RESPECT TO THE SECOND CHART, WHAT'S COMPLETELY

22

MISLEADING ABOUT THAT CHART IS THAT THOSE, THOSE DOTS ARE NOT

23

NECESSARILY THE SAME, IN THE SAME POSITION EVERY YEAR.

24

WHAT YOU'RE SEEING HERE IS -- WHAT THERE ARE -- WHAT THIS IS

25

SHOWING IS THAT IN 2002, ALL OF THE -- FOR EXAMPLE, AT ADOBE

UNITED STATES COURT REPORTERS

I MEAN,

109

110

1

THE JOB TOTAL AVERAGE COMPENSATION WENT DOWN AND IT WENT DOWN

2

BY DIFFERENT AMOUNTS FOR DIFFERENT TITLES, AND THEN YOU SEE THE

3

NEXT YEAR IT WENT UP FOR MOST TITLES, AND FOR SOME TITLES IT

4

WENT DOWN.

5
6

BUT IT DOESN'T -- AND THEN YOU SEE THAT IT'S -- ACTUALLY
YOU CAN SEE A PATTERN THERE BEING REPEATED OVER TIME.

7

BUT THE BOTTOM DOT IS NOT ALWAYS THE BOTTOM DOT, RIGHT?

8

SO IT'S TOTALLY FINE.

9

YEAR, THERE MAY BE A DIVERGENCE.

10
11

I MEAN, WE AGREE THAT IN ANY GIVEN
THERE MAY BE VARIABILITY.

BUT WHAT THE STATISTICAL ANALYSIS TELLS US IS THAT OVER
TIME, THAT VARIABILITY IS TIED TO A POSITIVE STRUCTURE.

12

THE COURT:

MR. VAN NEST.

13

MR. VAN NEST:

YOUR HONOR, YOU'VE HIT IT RIGHT ON THE

14

HEAD.

15

WITHIN A TITLE, THAT WAS TAB 4 AND 5, AND IT'S CONCEDED NOW

16

THAT THE AVERAGING MASKS THAT.

17

THIS -- WE WERE TALKING A MINUTE AGO ABOUT VARIATION

THIS ASKS A DIFFERENT QUESTION.

THIS IS BETWEEN TITLES.

18

CAN THEY SHOW THAT THERE'S A RIGID JOB STRUCTURE SO THAT THE

19

TITLES ARE CORRELATED BETWEEN THEMSELVES?

20

THE TOP OF THE PAGE, IN MY TAB, IS WHAT DR. LEAMER SAYS IS

21

HIS BEST CASE.

22

TITLES AT ADOBE, HE'S CHERRY PICKED SIX OF THEM, HE'S SHOWN THE

23

GRAPH AND HE SAYS THIS IS A GREAT CORRELATION BETWEEN TITLES.

24
25

THAT'S HIS BEST CORRELATION.

HE'S TAKEN SOME

ALL MURPHY DID WAS, AT THE BOTTOM OF THE PAGE, IS HE
EXPANDED THE NUMBER OF TITLES WITHIN EACH COMPANY YOU LOOK AT.

UNITED STATES COURT REPORTERS

110

111

1

HE LOOKED AT THE 50 MOST POPULATED, THE TITLES WITH THE MOST

2

EMPLOYEES, AND HE'S PLOTTING, YEAR TO YEAR, WHETHER THAT TITLE

3

MOVED UP OR MOVED DOWN.

4
5

AND AS YOUR HONOR CAN SEE, AND THIS HAS BEEN DEMONSTRATED
OVER AND OVER AGAIN, THERE'S HUGE VARIATION.

6

EACH COMPANY, YEAR BY YEAR, SOME TITLES MOVE UP A LITTLE,

7

SOME MOVE UP A LOT, SOME MOVE DOWN A LITTLE, SOME MOVE DOWN A

8

LOT.

9
10

AND IT'S NOT THE SAME TITLES.
OF ANY OF THIS.

11

THERE IS NO FIXED PATTERN

THERE IS ENORMOUS VARIABILITY.

AND WHAT EXHIBIT 7 AND EXHIBIT 8 ARE SHOWING RIGHT ON THE

12

HEAD IS THE SECOND PART OF THE EQUATION.

13

VARIATION WITHIN A TITLE.

14

TITLES BECAUSE IT SHOWS THAT WHEN YOU LOOK AT MORE THAN A FEW

15

AND YOU EXPAND IT TO THE TOP 50 FOR EACH COMPANY, YOU SEE,

16

OBVIOUSLY ON THE PAGE, AN ENORMOUS VARIATION UP AND DOWN OF

17

DIFFERENT TITLES YEAR AFTER YEAR AFTER YEAR, WHICH PROVES OUR

18

POINT THAT THERE ISN'T ANY SORT OF A RIGID JOB STRUCTURE WHERE

19

PEOPLE MOVE -- WHERE EVERYTHING -- WHERE A CHANGE IN SOME WOULD

20

AFFECT IN A CHANGE IN ALL, OR A CHANGE IN SOME WOULD PROPAGATE

21

OUT.

22

WE'VE SHOWN HUGE

THIS SHOWS HUGE VARIATION ACROSS

AND THINK ABOUT IT LOGICALLY.

WHY IN THE WORLD WOULD THE

23

FACT THAT A SOFTWARE ENGINEER HERE IN SILICON VALLEY WHO DIDN'T

24

GET A CALL, WHY WOULD THAT AFFECT A MASK DESIGNER IN

25

NEW MEXICO?

WHY WOULD THAT AFFECT A SEMICONDUCTOR

UNITED STATES COURT REPORTERS

111

112

1

MANUFACTURING PERSON IN ARIZONA?

2

CONSTRUCTION MANAGER, AN ARTIST, A CHEMICAL ENGINEER, AN

3

ELECTRICAL ENGINEER?

4

PROBLEM AND 60,000 EMPLOYEES.

5

WHY WOULD THAT AFFECT A

THAT'S THE POINT OF THIS 2400 TITLE

IT'S UNPRECEDENTED FOR A REASON.

NO COURT ANYWHERE HAS

6

EVER FOUND, IN A CASE LIKE THIS, THAT YOU CAN CERTIFY AND

7

EXPECT TO PROVE COMMON IMPACT OVER A GROUP THIS DISPARATE.

8
9

AND THIS TAB 6, EXHIBIT 7 FROM MURPHY, PROVES THAT THERE
IS NO RIGID PAY STRUCTURE, RIGHT?

IT IS A STRUCTURE BASED ON

10

PAYING FOR PERFORMANCE WHERE TITLES MOVE IN DIFFERENT

11

DIRECTIONS EACH YEAR AND WHERE INDIVIDUAL EMPLOYEES MOVE IN

12

DIFFERENT DIRECTIONS EACH YEAR.

13

AND THE ONLY WAY LEAMER CAN GET ANYWHERE CLOSE TO WHAT HE

14

GOT IS BY AVERAGING.

15

INDIVIDUAL EMPLOYEE PAY WITHIN A TITLE.

16

BASED ON AVERAGES.

17

HE AVERAGED EVERYTHING.

HE AVERAGED

HIS REGRESSIONS ARE

HIS CORRELATIONS ARE BASED ON AVERAGES.

AND WHAT THE CASE LAW SAYS REPEATEDLY IS NOT THAT YOU CAN

18

NEVER AVERAGE.

19

IN ECONOMIC ANALYSIS.

20

THAT'S NOT WHAT WE'RE SAYING.

YOU CAN AVERAGE

BUT WHEN THE QUESTION IS WHETHER YOU CAN PROVE COMMON

21

IMPACT WHEN WHAT'S INVOLVED ARE LOTS OF INDIVIDUAL PEOPLE AND

22

DECISIONS, AVERAGING THEM TELLS YOU NOTHING BECAUSE THE FACT

23

THAT AN AVERAGE GOES UP OR DOWN DOESN'T TELL YOU WHETHER ALL OR

24

NEARLY ALL PEOPLE WERE AFFECTED.

25

SO OUR POINT WITH TABS 4, 5, 6, AND 7 IS THEY FLUNKED THE

UNITED STATES COURT REPORTERS

112

113

1

BASIC TEST THAT YOU GAVE THEM AND NOW THEY'RE WALKING AWAY FROM

2

IT, AND THEY FLUNKED IT SO BAD THAT DR. LEAMER HAS TO ADMIT,

3

WHICH IS IN TAB 1 -- WE ASKED HIM POINT BLANK, "DO YOUR

4

RESULTS, YOUR CORRELATION, YOUR REGRESSION, EVERYTHING YOU DID,

5

DO THEY ENABLE YOU TO CONCLUDE THAT ADOBE'S COMP STRUCTURE WAS

6

SO RIGID THAT RAISES FOR ONE OR A FEW WOULD HAVE NECESSARILY

7

PROPAGATED INTO RAISES FOR ALL?"

8

"NO.

9

AND HE CAN'T CONCLUDE IT BECAUSE THE DATA DOESN'T SUPPORT

10

THE COURT:

LET ME ASK MR. GLACKIN, WHAT IS YOUR BEST

EVIDENCE THAT COMPENSATION MOVES TOGETHER ACROSS JOB TITLES?

13
14

MR. GLACKIN:

WELL, THERE'S -- I -- WHAT'S MY BEST

EVIDENCE?

15

THE COURT:

16

MR. GLACKIN:

17

I DIDN'T CONCLUDE THAT."

IT.

11
12

I CAN'T CONCLUDE THAT.

YES.
I HESITATE BECAUSE I FEEL THE RECORD IS

SO RICH AND I'M NOT SURE I CAN ACTUALLY PICK A WINNER.

18

THE COURT:

UM-HUM.

19

MR. GLACKIN:

YOU KNOW, THERE'S THIS -- THERE'S THE

20

RICH DOCUMENTARY RECORD THAT SHOWS THAT THE DEFENDANTS

21

MODULATED THEIR ENTIRE PAY SYSTEMS AT THE JOB TITLE LEVEL AND

22

THAT THEY SET COMPENSATION ON A BELL CURVE IN A NUMBER OF

23

INSTANCES.

24
25

BUT IN ADDITION TO THAT, YOU KNOW -- AND AGAIN I HESITATE
BECAUSE WE TOOK THE CRITICISMS VERY SERIOUSLY AND WE DIDN'T

UNITED STATES COURT REPORTERS

113

114

1

JUST DO ONE ADDITIONAL STATISTICAL ANALYSIS.

WE LOOKED AT THIS

2

FROM FOUR DIFFERENT -- I SHOULD SAY DR. LEAMER STATISTICALLY

3

LOOKED AT IT FROM FOUR DIFFERENT DIRECTIONS.

4

ON THE LEVEL OF CONTEMPORANEOUS CORRELATIONS, WHETHER OR NOT

5

THERE'S A SIMPLE CORRELATION, HE LOOKED AT THAT AT THE JOB

6

TITLE LEVEL, AND HE LOOKED AT IT AT THE ENTIRE COMPANY LEVEL BY

7

COMBINING SMALL TITLES INTO GROUPS.

HE LOOKED AT IT

8

THEN HE RAN A MULTIPLE REGRESSION ANALYSIS WHICH ALLOWED

9

THE STRUCTURAL VARIABLES TO COMPETE WITH THE EXTERNAL VARIABLES

10

THAT THE DEFENDANTS SAY ARE SO IMPORTANT, AND THE EXTERNAL

11

VARIABLES LOST.

12

COEFFICIENTS, THE EXTERNAL MARKET FORCE VARIABLES HAD VERY LOW

13

COEFFICIENTS, WHICH CONFIRMS AGAIN WHAT WE KNEW FROM THE COMMON

14

FACTORS ANALYSIS, WHICH IS THAT THE MAJORITY OF WHAT THE

15

EMPLOYEES ARE PAID IS DETERMINED BY JOB TITLE.

16

THE STRUCTURAL VARIABLES HAD VERY HIGH

SO HAVING DONE THAT ANALYSIS, IT REALLY IS -- YOU KNOW,

17

HAVING BEEN CRITICIZED FOR ONLY DISPLAYING CHARTS AND NOT

18

LOOKING AT EVERY TITLE IN THE COMPANY, WE HAVE NOW DONE THE

19

ANALYSIS OF LOOKING AT EVERY TITLE IN THE COMPANY, IN THE

20

COMPANIES.

21

THE COMPANIES, AND NOW THE DEFENDANTS ARE CHERRY PICKING THEIR

22

OWN CHARTS AND SAYING IF YOU LOOK AT THESE CHARTS, YOU SEE

23

THINGS MOVING IN A LOT OF DIFFERENT DIRECTIONS, WHICH WAS

24

EXACTLY WHAT WE WERE TAKEN TO TASK FOR THE FIRST TIME AROUND.

25

WE HAVE DONE MULTIPLE ANALYSES OF EVERY TITLE IN

THEY HAVEN'T OFFERED A SINGLE -- DR. MURPHY HAS NOT OFFERED

UNITED STATES COURT REPORTERS

114

115

1

A SINGLE LEGITIMATE CRITICISM OF THE MULTIPLE REGRESSION

2

ANALYSIS THAT DR. LEAMER HAS DONE.

3

IT IS, FRANKLY, AMAZING TO ME, AFTER THE YEARS THAT I HAVE

4

DONE THIS, THAT WE DO NOT SEE FROM DR. MURPHY A COMPETING

5

REGRESSION IN WHICH HE HAS ADDED A VARIABLE AND BLOWN THIS

6

REGRESSION UP.

7

THE OPENING REPORT.

8

THE FIRST THING THEY DO IS ADD THE S&P 500 TOTAL RETURN INDEX

9

AND SHOW THAT IT BLOWS UP WHATEVER THE PLAINTIFFS' EXPERT IS

10
11

THAT'S EXACTLY WHAT HE DID NUMEROUS TIMES IN
IT IS A STANDARD DEFENSE TACTIC.

IT IS --

TRYING TO DO.
THERE IS NOT ONE SINGLE EXAMPLE OF THAT KIND OF ATTACK IN

12

HERE, AND IT IS BECAUSE THE REGRESSION IS TELLING THE TRUTH.

13

IT'S BECAUSE THE REGRESSION IS RIGHT, THAT THERE IS THIS

14

RELATIONSHIP BETWEEN THE TITLES OVER TIME, NOT THAT THEY HAVE

15

TO MOVE IN LOCKSTEP EVERY YEAR, BUT THERE IS A STRUCTURE THAT

16

BINDS THESE TITLES TOGETHER OVER TIME.

17

IT'S WHAT THE DEFENDANTS' EMPLOYEES SAY, THEIR H.R.

18

EMPLOYEES SAY, IT'S WHAT THE CEOS SAY, IT'S WHAT THE PEOPLE WHO

19

ENTERED INTO THESE AGREEMENTS SAY, AND IT'S WHAT THE DATA SAYS,

20

AND THEY HAVE NOT EVER ATTACKED THAT ANALYSIS.

21

THEIR ONLY RESORT IS TO GO BACK TO THE INDIVIDUAL LEVEL AND

22

SHOW THINGS MOVING IN A LOT OF DIFFERENT DIRECTIONS AND ACCUSE

23

US OF AVERAGING.

24
25

THE COURT:
DR. MURPHY'S REPORT.

SO LET ME GO TO PARAGRAPH 22 OF
IT'S ON PAGE 8.

WHY IS THE CORRELATION

UNITED STATES COURT REPORTERS

115

116

1

NOT RELEVANT?

2

WHAT IS THE BENEFIT --

MR. VAN NEST:

WHAT HE'S SAYING, YOUR HONOR -- AND

3

OBVIOUSLY DR. MURPHY IS HERE IF YOU WANT TO HEAR FROM HIM, AND

4

HE CAN PROBABLY EXPLAIN THIS BETTER THAN I CAN -- BUT THE

5

FUNDAMENTAL POINT IS THAT CORRELATION OF -- THIS CORRELATION

6

STUDY OR TEST IS MEANINGLESS.

7

ALL HE'S SAYING -- ALL LEAMER IS SAYING ON THE CORRELATION

8

IS IF I TAKE THE AVERAGE OF A JOB TITLE AND COMPARE IT TO THE

9

AVERAGE PAY OF CLASS MEMBERS AT THAT COMPANY, I SEE A

10
11

CORRELATION.
WELL, OBVIOUSLY BOTH THE TITLES AT THE COMPANY AND ALL THE

12

EMPLOYEES IN THE TECH GROUP AT THE COMPANY, THEY'RE ALL SUBJECT

13

TO THE SAME EXACT EXTERNAL FACTORS, HOW WELL DID THE COMPANY DO

14

THAT YEAR, HOW WELL IS THE ECONOMY DOING, WHAT'S THE JOB

15

MARKET --

16

THE COURT:

17

MR. VAN NEST:

18

THE COURT:

19
20

BUT WHAT'S THE BENEFIT OF -THERE ISN'T.

-- MEASURING THE DEVIATION?

WHAT'S THAT

BENEFIT?
MR. VAN NEST:

THERE'S NO -- THERE'S NO BENEFIT IN

21

DETERMINING WHETHER THERE'S A RIGID JOB STRUCTURE.

22

CORRELATION DOESN'T TELL YOU THAT.

23

THE

THAT'S WHY DR. LEAMER SAYS "I CAN'T TELL YOU THAT CHANGES

24

TO SOME EMPLOYEES WOULD PROPAGATE."

THERE'S NO -- WHAT

25

DR. MURPHY IS SAYING IS CORRELATION, IN THIS CONTEXT WHERE

UNITED STATES COURT REPORTERS

116

117

1

YOU'RE COMPARING A TITLE TO THE REST OF THE EMPLOYEES AT THE

2

COMPANY, THAT WILL MOVE TOGETHER WHETHER THE STRUCTURE IS RIGID

3

OR NOT BECAUSE THEY'RE ALL SUBJECT TO THE SAME SET OF FACTORS.

4

AND WHEN YOU LOOK AT EXHIBIT 8, OR FIGURE 8 AND FIGURE 7,

5

HE TESTED THE THEORY.

6

50 TITLES?

7

PATTERN?

8

10

DO THEY ALL SEEM TO -- IS THERE A TIGHT, RIGID

ABSOLUTELY NOT.

9

WHAT HAPPENS WHEN YOU LOOK AT THESE TOP

THE COURT:

THERE'S HUGE VARIATION.
WHY ISN'T ALL THIS MERITS ANALYSIS FOR

LATER?

11

MR. VAN NEST:

BECAUSE COMCAST AND ELLIS TELL US THAT

12

THE STANDARD FOR ESTABLISHING CERTIFIABILITY IN (B)(3) IS

13

EXTREMELY HIGH.

14

YOU ASKED EARLIER ABOUT CASE LAW.

COMCAST CITES DUKES AND

15

IT SAYS DUKES APPLIES WITH EVEN MORE FORCE IN (B)(3), AND IF

16

YOU WANT TO CERTIFY A CLASS OF 60,000 PEOPLE WITH 2400 --

17

THE COURT:

18

EVIDENCE.

19

OKAY.

BUT DUKES HAD NO DOCUMENTARY

DUKES HAD A SOCIOLOGIST TALKING ABOUT WAL-MART

CULTURE.

20

MR. VAN NEST:

21

THE COURT:

22

IT HAD 120 ANECDOTES FROM WOMEN

EMPLOYEES.

23

MR. VAN NEST:

24

THE COURT:

25

WELL, LOOK AT --

LOOK AT ELLIS.

THEY HAD STATISTICS.

THEY DID NOT HAVE

THE WEALTH OF DOCUMENTARY EVIDENCE THAT EXISTS HERE.

UNITED STATES COURT REPORTERS

117

118

1

MR. VAN NEST:

2

THE COURT:

3

MR. VAN NEST:

BUT -- BUT AGAIN, YOUR HONOR --

YEAH.
I DON'T WANT TO DISPUTE THAT THERE'S

4

DOCUMENTARY EVIDENCE THAT PEOPLE WERE TALKING ABOUT AGREEMENTS.

5

BUT THERE'S NO DOCUMENTARY EVIDENCE OF ANY COMMON IMPACT

6

ACROSS THE CLASS.

7

ANY IMPACT.

8
9
10
11
12

THERE'S NO EVIDENCE IN DOCUMENTS OF REALLY

THERE MAY BE EVIDENCE OF INTENT.
PEOPLE TALKING TOGETHER, OF COURSE.
TIME.

THERE MAY BE EVIDENCE OF
WE'VE REVIEWED THAT LAST

THAT EVIDENCE IS COMMON.

THE POINT HERE IS THAT IF YOU HAVE TO SHOW, AS COMCAST
REQUIRES AND ELLIS --

13

THE COURT:

ANYWAY, OKAY.

14

MR. VAN NEST:

15

THE COURT:

SO --

LET ME GIVE MR. GLACKIN AN OPPORTUNITY TO

16

RESPOND TO THIS ISSUE ABOUT IS IT BETTER TO MEASURE DEVIATION

17

VERSUS THE CORRELATION?

18

MR. GLACKIN:

19

THE COURT:

20

IT'S PARAGRAPH 22.

MR. GLACKIN:

22

THE COURT:

23

MR. GLACKIN:

25

IT'S ON PAGE 8 OF

DR. MURPHY'S --

21

24

CAN YOU POINT ME TO EXACTLY --

WELL --

-- JUNE 2013 REPORT.
OKAY, YEAH, I UNDERSTAND.

I MEAN, THIS IS -- YOU KNOW, SO THIS IS THE HEART OF DR.,
OF DR. MURPHY'S CRITICISM, SO TO SPEAK, IS HE'S SAYING

UNITED STATES COURT REPORTERS

118

119

1
2

DEVIATION REALLY MATTERS.
AND WHAT IS HIS EXPLANATION FOR WHY DEVIATION REALLY

3

MATTERS?

YOU MIGHT HAVE LOOKED LONG AND HARD FOR IT.

4

I THINK

SOMEWHERE IN HIS REPORT HE SAYS BASIC ECONOMICS.

5

AND WHAT HE EXPLAINED AT HIS DEPOSITION IS THAT THE REASON

6

DEVIATION MATTERS IS THAT IT SHOWS THAT IT IS POSSIBLE FOR THE

7

DEFENDANTS TO PAY THEIR EMPLOYEES DIFFERENTLY.

8

SHOWS.

9

THAT IS WHAT IT

AND IF IT IS POSSIBLE FOR DEFENDANTS TO PAY THEIR EMPLOYEES

10

DIFFERENTLY, THEN THEY WILL TRY TO PAY THEM AS LITTLE AS

11

POSSIBLE, EVEN IN RESPONSE TO COMPETITION.

12
13
14

THAT IS WHAT I UNDERSTAND TO BE HIS, THE THEORY BEHIND HIS
ECONOMICS.
AND I -- MY RESPONSE TO THAT IS WE ARE WAY BEYOND BASIC

15

ECONOMICS.

16

SITUATION WHERE EVERY COMPANY FACES OFF AGAINST ITS INDIVIDUAL

17

EMPLOYEES IN ONE-ON-ONE NEGOTIATIONS AND JUST DOES A SIMPLE

18

COST MINIMIZATION FORMULA.

19

WE ARE WAY BEYOND TALKING REASONABLY ABOUT A

IT IS UNDISPUTED BY ANY OF THE EXPERTS AT THIS POINT THAT

20

THESE COMPANIES USE PAY STRUCTURES, THAT INFORMATION ECONOMICS

21

AND THE PRINCIPLES OF INTERNAL EQUITY ARE IMPORTANT FACTORS IN

22

HOW THESE COMPANIES PAY THEIR EMPLOYEES.

23

SO WHAT DR. MURPHY IS DOING IS SIMPLY SAYING, "WELL, IF I

24

LIVED IN A WORLD WHERE NONE OF THOSE THINGS MATTERED AND THE

25

WAY GOOGLE PAID ITS EMPLOYEES WAS TO SIT DOWN ACROSS THE TABLE

UNITED STATES COURT REPORTERS

119

120

1

FROM THEM AND NEGOTIATE A SALARY AND THERE WAS NOTHING ELSE

2

THAT MATTERED TO THAT CALCULUS, THEN GOOGLE WOULD HAVE AN

3

INCENTIVE TO PAY THAT EMPLOYEE AS LITTLE AS POSSIBLE."

4

JUST AN IRRELEVANT HYPOTHETICAL.

5

MR. VAN NEST:

6

THE COURT:

7

IT'S

IF I MAY --

WHAT ABOUT WHAT IS MR. VAN NEST'S TAB 5?

I HAD SOME QUESTIONS ABOUT THESE CHARTS.

8

THE FIRST QUESTION IS, IN FOOTNOTE 10, DR. MURPHY SAYS,

9

"I'M INCLUDING PEOPLE WHO GOT PROMOTIONS AND WHO BASICALLY LEFT

10

ONE JOB TITLE AND MOVED TO ANOTHER ONE."

11

BE INCLUDED HERE?

12

VARIATION AS WELL IF YOU'RE TRACKING OVER TIME PEOPLE WHO ARE

13

IN MULTIPLE JOB TITLES.

14

VARIATION.

15

SHOULD THOSE PEOPLE

BECAUSE THAT COULD EXPLAIN A LOT OF THE

MR. VAN NEST:

THAT COULD EXPLAIN SOME OF THE

I THINK -- IT COULD.

16

BUT THIS VARIATION IS ENORMOUS, YOUR HONOR, AS YOU CAN SEE.

17

ALL WE'RE DOING HERE IS LOOKING AT EMPLOYEES WITHIN EACH OF

18

THESE JOB TITLES IN A PARTICULAR YEAR.

19

YEAR.

20
21
22

THIS ISN'T OVER TIME.

SO THIS IS JUST ONE

THIS IS IN 2007.

SO YOU CAN SEE -THE COURT:

RIGHT.

BUT I GUESS I'M -- BUT HE SAYS IN

THE FOOTNOTE THAT HE INCLUDED PEOPLE THAT CHANGED JOBS.

23

MR. VAN NEST:

24

THE COURT:

25

MR. VAN NEST:

HE DID.

SO -SO THERE WOULD BE SOME PEOPLE --

UNITED STATES COURT REPORTERS

120

121

1

THE COURT:

SO THERE'S GOING TO BE -- SO THERE'S ONE

2

TITLE LISTED ON TOP OF EACH CHART, BUT THAT'S OBVIOUSLY

3

INCORRECT BECAUSE SOME OF THESE PEOPLE HAD DIFFERENT JOB

4

TITLES.

5

MR. VAN NEST:

BUT TAKE A LOOK, THOUGH, YOUR HONOR.

6

IF THIS WERE CLOSE, THEN MAYBE WE WOULD BE -- MAYBE WE WOULD BE

7

LOOKING MORE CAREFULLY AT THAT FOOTNOTE.

8
9
10

BUT TAKE A LOOK.

FOR EACH ONE OF THESE COMPANIES, THERE IS

NOT ONLY A HUGE RANGE BETWEEN WHETHER YOU GO UP IN PAY OR GO
DOWN --

11

THE COURT:

UM-HUM.

12

MR. VAN NEST:

-- BUT THERE'S ALSO A HUGE RANGE IN

13

HOW MUCH.

14

A YEAR OR DOWN AS MUCH AS 60 PERCENT, AND THAT'S TRUE FOR

15

APPLE, IT'S TRUE FOR GOOGLE, IT SLIGHTLY LESS TRUE FOR INTUIT.

16
17

SOME OF THESE PEOPLE GO UP AS MUCH AS 75 PERCENT IN

THE COURT:

BUT THAT COULD BE EXPLAINED BY YOU

GETTING A NEW JOB.

18

MR. GLACKIN:

19

THE COURT:

20

MR. GLACKIN:

21

THE QUESTION I HAD ALSO --

THE COURT:

23

MR. GLACKIN:

25

DO YOU STILL WANT ME TO RESPOND TO THIS

OR NOT?

22

24

YES.

GO AHEAD.
I DON'T THINK WE TAKE SERIOUS ISSUE

WITH IT ONE WAY OR ANOTHER.
I WILL SAY THAT I THINK THE ANSWER TO THE QUESTION DEPENDS

UNITED STATES COURT REPORTERS

121

122

1

ON -- THE ANSWER TO THAT QUESTION DEPENDS ON WHAT THE RELEVANT

2

QUESTION IS.

3

TOGETHER JOB TITLES, PROBABLY YOU SHOULD EXCLUDE THE PEOPLE WHO

4

CHANGED JOB TITLES.

5
6
7
8
9

IF THE QUESTION IS, IS THERE A STRUCTURE HOLDING

IF THE QUESTION IS, DID THE DEFENDANTS PAY THEIR EMPLOYEES
DIFFERENTLY, THEN MAYBE YOU SHOULD INCLUDE THEM.
MR. VAN NEST:
THE POINT?

AND ISN'T THAT THE POINT?

ISN'T THAT

PROMOTION IS ANOTHER WAY TO RESPOND, YOUR HONOR.

MR. GLACKIN:

WELL --

10

MR. VAN NEST:

11

DIFFERENTIATE BETWEEN EMPLOYEES.

12

MR. GLACKIN:

13

PROMOTION IS ANOTHER WAY TO

MR. VAN NEST:

THAT'S OUR WHOLE POINT --

I RESPECTFULLY -- SORRY.
-- IS THAT WHEN YOU MOVE SOMEONE UP,

14

IT'S ANOTHER TOOL TO DIFFERENTIATE BETWEEN INDIVIDUALS, WHICH

15

IS WHAT -- A TOOL IS SALARY, A TOOL IS BONUS, A TOOL IS EQUITY,

16

AND A TOOL IS PROMOTION.

17

THE COURT:

THE DOCUMENTARY EVIDENCE DOES SUPPORT

18

THAT PROMOTION WAS ONE WAY THAT MANAGERS DEALT WITH HOW TO

19

COMPENSATE THE TOP PERFORMERS.

20

MR. GLACKIN:

21

MR. VAN NEST:

22
23

INDIVIDUALS.

SURE.
AND THAT'S INDIVIDUALS.

THAT'S OUR POINT.

THAT'S

THAT'S AN INDIVIDUAL THING.

AND OUR WHOLE PITCH HERE, AND THE DATA SUPPORT IT, MURPHY'S

24

DATA AND SHAW'S DATA ALL SUPPORT THIS, IS THAT PEOPLE ARE

25

MAKING WIDE DISTINCTIONS IN VARIATIONS AMONG EMPLOYEES WITHIN

UNITED STATES COURT REPORTERS

122

123

1

THE CLASS.

2

THE COURT:

3

MR. VAN NEST:

4
5

UM-HUM.
AND THERE ARE WIDE VARIATIONS BETWEEN

THE TITLES, WITHIN THE TITLES AND BETWEEN THE TITLES.
THERE ISN'T THIS SORT OF RIGID JOB STRUCTURE THAT THEY SAID

6

THEY WOULD PROVE IN ORDER TO SHOW THAT CHANGES TO SOME WOULD

7

PROPAGATE OUT.

8
9

THE COURT:

LET ME ASK -- AND I'M GOING TO GIVE YOU A

CHANCE TO RESPOND.

10

MR. GLACKIN:

11

THE COURT:

OKAY.

THANK YOU.

LAST TIME I GAVE DR. LEAMER A HARD TIME

12

FOR CHERRY PICKING JOB TITLES OUT OF GOOGLE AND APPLE AND

13

NOBODY ELSE.

14

AND THERE CERTAINLY SEEMS TO BE SOME CHERRY PICKING HERE,

15

BECAUSE FOR LUCASFILM, WE'RE COMPARING ARTIST 2 AND SENIOR

16

ARTIST 1 AND SOFTWARE ENGINEER, BUT THEN YOU GO SOMEWHERE ELSE

17

AND WE'RE COMPARING SOMETHING TOTALLY DIFFERENT.

18

WAS AN ANALYSIS DONE FOR ALL THE DIFFERENT JOB TITLES AND

19

THEN YOU JUST PICKED THE TOP THREE FOR EACH COMPANY THAT HAD

20

THE MOST VARIATION?

21
22
23
24
25

OR WHAT -- IT'S NOT CONSISTENT ACROSS.

MR. VAN NEST:

I THINK THAT DR. MURPHY WOULD HAVE TO

ANSWER THAT.
MR. GLACKIN:

I CAN TELL YOU WHAT HE SAID AT HIS

DEPOSITION IF YOU WANT.
THE COURT:

WHAT DID HE SAY?

UNITED STATES COURT REPORTERS

123

124

1

MR. GLACKIN:

WHAT HE SAID IS HE RAN IT BACK AT THE

2

RANCH, SO TO SPEAK, FOR EVERYTHING.

3

WAS IN THE MIDDLE OF THE CLASS PERIOD, AND HE PICKED -- I

4

THINK -- THE PROBLEM IS THAT -- I THINK IF YOU LOOK IN THE

5

REPORT, HIS REPORT, IT MAY SAY THAT THESE WERE THE MOST

6

POPULATED JOB TITLES AT THESE FIRMS.

7

BECAUSE IT'S TAKEN OUT OF THE REPORT, BUT I KNOW THAT WITH

8

RESPECT TO AT LEAST SOME OF THESE CHARTS, THAT WAS HOW HE

9

EXPLAINED HIS SELECTION OF THE JOB TITLES, WHICH IS FINE.

10

THE COURT:

ALL RIGHT.

HE PICKED 2007 BECAUSE IT

I'M NOT -- I CAN'T TELL

DO YOU WANT TO RESPOND TO

11

THIS, TO THESE CHARTS?

12

WITHIN A YEAR, WITHIN A SINGLE JOB TITLE.

13
14

MR. VAN NEST:
TITLE, EVERY TITLE.

THEY CERTAINLY SHOW A LOT OF VARIATION

AND APPENDIX B, YOUR HONOR, IS EVERY

APPENDIX B TO MURPHY, EVERY TITLE.

15

MR. GLACKIN:

16

THE COURT:

17

MR. GLACKIN:

SO THIS IS MY RESPONSE TO THAT.

UM-HUM.
TO ACCEPT THE DEFENDANTS' POSITION, YOU

18

HAVE TO ACCEPT THAT THE EXISTENCE OF VARIATION IN PAY DISPROVES

19

THE EXISTENCE OF A JOB STRUCTURE THAT HOLDS TOGETHER BASED ON

20

INTERNAL EQUITY.

21

AND DR. MURPHY, AT HIS DEPOSITION, WISELY CONCEDED THAT

22

THERE IS NO INCONSISTENCY BETWEEN THOSE TWO THINGS.

23

PAY YOUR EMPLOYEES DIFFERENTLY IN THAT TOP -- YOU KNOW, AT THAT

24

TOP LEVEL IN TERMS OF THE TOP OF THEIR COMPENSATION, BUT STILL

25

HOLD THEM ALL TOGETHER IN A JOB TITLE STRUCTURE.

UNITED STATES COURT REPORTERS

YOU CAN

124

125

1

AND THIS WAS -- I MEAN, THIS IS THE QUOTE THAT WE SET OFF

2

FROM HIM.

3

IT'S INCONSISTENT THAT -- ARE YOU SAYING THAT IT'S INCONSISTENT

4

TO HAVE WIDE VARIATION IN PAY AND A STRUCTURE THAT HOLDS

5

TOGETHER ON INTERNAL EQUITY?" HE SAID, "NO, THEY'RE NOT

6

INCONSISTENT."

7

WHEN I ASKED HIM AT HIS DEPOSITION, "ARE YOU SAYING

AND WE DRILLED DOWN ON IT AND HE SAID, "YEAH," HE SAID, "I

8

CAN'T TELL YOU THAT THE EXISTENCE OF WIDE VARIATION DISPROVES A

9

JOB STRUCTURE THAT RESPECTS INTERNAL EQUITY.

10
11
12
13

I CAN'T TELL YOU

IT DISPROVES IT."
AND THIS IS WHEN HE SAID THERE'S NO ABSOLUTES IN STATISTICS
AND IF YOU WANT ABSOLUTES, YOU HAVE TO TALK TO GOD.
BUT PUTTING ALL THAT ASIDE, THE DEFENDANTS' BRIEF IS SIMPLY

14

NOT CONSISTENT WITH COMMON SENSE.

THERE'S NO REASON THAT YOU

15

CAN'T HAVE A STRUCTURE THAT IS HOLDING TOGETHER 90 PERCENT OF

16

THE COMPENSATION WHILE, AT THE SAME TIME, THERE IS VARIATION

17

OVER ON TOP OF THAT TO REFLECT THE FACT THAT PEOPLE ARE OLDER,

18

OR YOUNGER, OR OF DIFFERENT GENDERS, UNFORTUNATELY, OR HAVE

19

PERFORMED BETTER IN A GIVEN YEAR.

20

THERE'S NOTHING INCONSISTENT BETWEEN THOSE TWO THINGS,

21

WHICH IS WHY WE HAVEN'T EVER SAID THERE'S NO VARIATION BETWEEN

22

THE DEFENDANTS' PAYMENT.

23

THE COURT:

I GUESS I'M NOT CLEAR.

ARE YOU SAYING

24

FOR THE VAST MAJORITY OF PEOPLE, THEIR COMPENSATION WILL MOVE

25

TOGETHER WITHIN JOB TITLE, BUT THEN THERE'S GOING TO BE THE TOP

UNITED STATES COURT REPORTERS

125

126

1

AND THE BOTTOM, THE TOP PERFORMERS, FOR EXAMPLE, AND PEOPLE WHO

2

MAY, FOR WHATEVER REASONS, NOT BE VALUED AS HIGHLY, BUT THOSE

3

WILL VARY THE MOST, BUT THE VAST MAJORITY IN THE MIDDLE IS

4

GOING TO MOVE --

5

MR. GLACKIN:

6

THE COURT:

7

MR. GLACKIN:

NO, NO, NO.

I'M JUST NOT CLEAR ON WHAT YOU'RE SAYING.
WHAT I'M SAYING IS IF YOU LOOK AT ANY

8

INDIVIDUAL EMPLOYEE'S COMPENSATION, HIGH PERFORMER OR LOW

9

PERFORMER, ABOUT 90 PERCENT OF IT IS EXPLAINED BY THEIR JOB

10

TITLE, WHICH MAKES PERFECT SENSE, YOU KNOW, WHEN YOU LOOK AT

11

THE FACT THAT THE DEFENDANTS TRACK ALL THEIR EMPLOYEES IN THE

12

SALARY RANGES THAT ARE NOT INFINITE ON THE TOP OR BOTTOM END.

13

SO WHATEVER EMPLOYEE YOU LOOK AT, HIGH OR LOW, GOOD YEAR,

14

BAD YEAR, MOST OF THEIR COMPENSATION IS EXPLAINED BY THEIR JOB

15

TITLE.

16

I MEAN, AND THAT IS WHY -- THAT IS ONE OF MANY REASONS THAT

17

THE JOB TITLE IS THE RIGHT PLACE TO LOOK FOR A STRUCTURE TO THE

18

DEFENDANTS' COMPENSATION AS A MATTER OF STATISTICS, IN ADDITION

19

TO THE RICH RECORD THAT TELLS US THAT THAT'S THE RIGHT PLACE TO

20

LOOK.

21
22
23

THE COURT:

CAN WE GO TO DR. LEAMER'S REPLY REPORT,

PARAGRAPH 35?
MR. VAN NEST:

YOUR HONOR, CAN I JUST RESPOND VERY

24

QUICKLY TO WHAT HE JUST SAID?

25

THE COURT:

YES.

UNITED STATES COURT REPORTERS

126

127

1

MR. VAN NEST:

THE POINT IS WHERE THE JOB TITLE

2

SHOWS -- HAS AN ENORMOUS RANGE OF COMPENSATION WITHIN IT BASED

3

ON SALARY, EQUITY, AND BONUS, WHAT HE SAID MAKES ABSOLUTELY NO

4

DIFFERENCE, AND THAT'S WHY YOU HAVE THE RESULTS THAT YOU HAVE

5

WHEN YOU LOOK AT THE RAW DATA.

6
7

THE EMPLOYEES' PAY IS WIDELY VARIED YEAR TO YEAR, AND THE
TITLES VARY WIDELY YEAR TO YEAR.

8

THE COURT:

9

MR. VAN NEST:

10

THE COURT:

BUT IT'S -BECAUSE THERE'S SO MUCH DISCUSSION --

BUT IT'S NOT CONSISTENT WITH THE

11

DOCUMENTARY EVIDENCE THAT SAYS HERE ARE THE RANGES, AND IF YOU

12

WANT TO GO ABOVE THIS LEVEL, YOU NEED TO GET ONE ADDITIONAL

13

LEVEL OF APPROVAL, OR THAT --

14
15

MR. VAN NEST:
HONOR.

16

THE COURT:

17

MR. VAN NEST:

18

IT IS CONSISTENT -- EXCUSE ME, YOUR

GO AHEAD.
I APOLOGIZE.

IT'S CONSISTENT WITH THE LEVEL -- YOU CAN LOOK AT

19

DR. HALLOCK'S FIGURE 7.

20

$50,000.

21

JUST SALARY, NOT INCLUDING BONUS AND EQUITY.

22
23
24
25

SOME OF THE RANGES ARE $100,000,

THAT'S THE RANGE OF SOME OF THESE JOB TITLES.

THAT'S

THE REASON THAT YOU HAVE SOMETHING LIKE TABS 4, 5, AND 6 IS
THAT THERE IS AN ENORMOUS RANGE WITHIN EACH JOB TITLE.
NO ONE IS DENYING THAT THE DEFENDANTS HAVE STRUCTURES AND
THAT THEY PAY PEOPLE WITHIN JOB TITLES.

UNITED STATES COURT REPORTERS

127

128

1

BUT JOB TITLES, LIKE EVERYTHING ELSE, ARE BASED ON

2

PERFORMANCE, AND WHEN YOU PERFORM OUT OF ONE, YOU MOVE INTO

3

ANOTHER.

4

AND EVEN WITHIN A JOB TITLE, AS YOU CAN SEE IN TAB 4,

5

THERE'S MOVEMENT EVERY YEAR, UP AND DOWN.

6

LOT, THERE'S MOVEMENT A LITTLE, AND THAT'S WHY THERE'S SO MUCH

7

VARIABILITY.

8

CONCLUDE IMPACT TO SOME WOULD TRANSLATE TO IMPACT FOR OTHERS.

9

SOME OF THESE BANDS, JUST BASED ON BASE SALARY, ARE 50 TO

10
11

$100,000.

THERE'S MOVEMENT A

THAT'S WHY DR. LEAMER CAN'T SAY THAT HE CAN

THAT DOESN'T COUNT EQUITY.
THE COURT:

WELL, THERE'S CERTAINLY A LOT OF

12

DOCUMENTARY EVIDENCE THAT SAYS WHAT THE SPECIFIC BAND IS FOR

13

EACH JOB TITLE FOR ALL OF THE DIFFERENT DEFENDANTS.

14

MR. VAN NEST:

15

THE COURT:

16
17
18
19
20

SO ANYWAY.

MR. GLACKIN:

THIS IS THE REBUTTAL, SUPPLEMENTAL

EXPERT REPORT?
THE COURT:

I'M SORRY, NO.

THIS IS HIS ORIGINAL.

LET'S GO TO THE MULTIPLE REGRESSION ANALYSIS.
MR. GLACKIN:

22

MR. VAN NEST:

23

THE COURT:

25

LET ME GO TO, PLEASE,

PARAGRAPH 35.

21

24

TRUE.

SURE.
I'VE GOT IT, TINA.

THIS IS WHERE HE WAS COMPARING THE

INTERNAL VERSUS THE EXTERNAL FACTORS.
MR. GLACKIN:

RIGHT.

UNITED STATES COURT REPORTERS

128

129

1

THE COURT:

SO DO WE HAVE TO COMPARE THE MAGNITUDE OF

2

THE COEFFICIENTS FOR THE INTERNAL FACTORS RELATIVE TO THE

3

COEFFICIENTS FOR THE EXTERNAL FACTORS?

4

MR. GLACKIN:

WELL, SO I DON'T THINK IT'S NECESSARY.

5

I THINK, YOU KNOW, THE WAY THAT THIS -- THE WAY THAT THIS

6

REGRESSION WORKS IS THAT IF THE DEFENDANTS WERE RIGHT THAT

7

EVERYBODY'S PAY IS COMPLETELY DETERMINED BY EXTERNAL FACTORS,

8

SUCH AS FIRM REVENUE OR PERFORMANCE OF THE FIRM OR THINGS GOING

9

ON IN THE GENERAL TECH JOB MARKET, IF YOU INCLUDE THOSE FACTORS

10

AND THEN YOU ALSO INCLUDE THE SHARING VARIABLES AND YOU RUN THE

11

REGRESSION AND THE SHARING VARIABLES STAY POSITIVE, IF THEY

12

DON'T ALL JUST GO AWAY, THEN YOU'VE STILL DETECTED THE

13

EXISTENCE OF A STRUCTURE.

14

BUT I DO THINK IT IS WORTH NOTING HERE THAT IN MANY CASES,

15

I BELIEVE IN -- I BELIEVE, OVERALL, THAT THE SHARING VARIABLES

16

DID BETTER AND PERFORMED BETTER IN DR. LEAMER'S OPINION THAN

17

THE EXTERNAL FACTOR VARIABLES.

18
19

SO I DON'T THINK THAT, YOU KNOW, STRICTLY SPEAKING YOU HAVE
TO COMPARE THE MAGNITUDE.

20

IF THE ONLY THING THAT MATTERED WAS THE EXTERNAL FACTORS,

21

WHEN YOU RAN THE REGRESSION YOU WOULD GET BACK BIG RESULTS ON

22

THE EXTERNAL FACTORS AND YOU WOULD GET BACK ZERO ON THE SHARING

23

VARIABLES BECAUSE THE EXTERNAL FACTORS ARE ACCOUNTING FOR

24

EVERYTHING.

25

THE COURT:

DO THE DEFENDANTS AGREE THAT THE

UNITED STATES COURT REPORTERS

129

130

1

MAGNITUDE OF THE SHARING EFFECT VARIABLES IS LARGER THAN THE

2

EXTERNAL ONES?

3

MR. VAN NEST:

NO, YOUR HONOR.

4

THEY'RE NOT SIGNIFICANT.

5

WE -- OUR POINT --

THEY'RE NOT SIGNIFICANT AT ALL,

NUMBER ONE.

6

AND NUMBER TWO, AGAIN, WHAT DR. MURPHY SAYS ABOUT THIS

7

REGRESSION IS YOU WOULD EXPECT THE SAME RESULT WHETHER YOU HAD

8

A RIGID STRUCTURE OR A NON-RIGID STRUCTURE, BECAUSE IF WHAT

9

YOU'RE COMPARING IS A TITLE WITHIN ONE COMPANY TO THE SALARIES

10

AVERAGED OF ALL TECHNICAL EMPLOYEES IN THAT COMPANY, THERE'S

11

ALWAYS GOING TO BE SOME CORRELATION BECAUSE THEY'RE ALL SUBJECT

12

TO THE SAME EXTERNAL FACTORS, COMPANY PERFORMANCE, ECONOMY.

13

SO THEY'RE -- THESE ARE NOT SIGNIFICANT, AND WE SHOW THIS

14

IN FIGURE 8 OF -- YOU CAN SEE IT IN FIGURE 8 OF DR. LEAMER'S

15

REPORT.

16

SIGNIFICANT.

17

HE'S SAYING A LARGE NUMBER, ADOBE, 75 PERCENT, NOT

APPLE, 62 PERCENT, NOT SIGNIFICANT.

18

MR. GLACKIN:

19

MR. VAN NEST:

I -GOOGLE, 69 PERCENT, NOT SIGNIFICANT.

20

I MEAN, THEY'RE NOT -- AND BOTTOM LINE, WHAT I HAVE AT

21

TAB 8 IS LEAMER'S ADMISSION THAT AFTER ALL OF THE REGRESSIONS

22

HE DID, HE CANNOT TESTIFY THAT THERE'S ANYTHING THAT WOULD SHOW

23

CHANGES IN WAGES BEING TRANSLATED ACROSS THE FIRM.

24
25

THAT'S WHAT -- THAT'S THE POINT.
TO SHOW.

THAT'S WHAT HE'S TRYING

THAT'S WHAT YOU CHALLENGED HIM ON LAST TIME IS CAN

UNITED STATES COURT REPORTERS

130

131

1

YOU SHOW, TITLE TO TITLE, THAT ONE TITLE CAUSES ANOTHER TITLE

2

TO MOVE?

3

ANOTHER TITLE TO MOVE?

OR THAT A CHANGE IN PAY IN ONE TITLE WOULD CAUSE

4

THE POINT ISN'T, DO WE HAVE A STRUCTURE?

5

IT'S, IS THE STRUCTURE RIGID OR IS IT FLEXIBLE?

6

AND WHAT DR. LEAMER ADMITTED IN HIS DEPOSITION AT PAGES

7

658 TO 660 WAS THAT EVEN THE COEFFICIENTS THAT HE SHOWS DO NOT

8

DEMONSTRATE THAT A CHANGE IN WAGES WOULD BE TRANSLATED ACROSS

9

THE FIRM.

10

SAME THING IN TAB 9.

WE ASKED HIM AGAIN, "BASED ON

11

EVERYTHING YOU DID, CAN YOU TELL US THAT WHEN A COMPANY CHANGES

12

THE PAY OF SOME PEOPLE, IT PROPAGATES TO EVERYONE ELSE?"

13

"NO, I CAN'T DO THAT.

14

THE QUESTION ISN'T, DO WE HAVE A STRUCTURE?

15

EVERY COMPANY

HAS TO HAVE SOME STRUCTURE FOR PAYING 50 TO 100,000 PEOPLE.

16
17

AND THAT'S NOT MY VIEW."

THE QUESTION IS, IS THE STRUCTURE RIGID AND DOES A CHANGE
IN ONE TITLE CAUSE A CHANGE IN ANOTHER TITLE?

18

AND ALL THE EVIDENCE IS TO THE SAME EFFECT, NO.

19

THE COURT:

HAS DR. MURPHY DONE ANY STUDIES OR ANY

20

QUANTITATIVE ANALYSIS SHOWING WHAT THE RELATIONSHIP MAY BE

21

BETWEEN SAN JOSE EMPLOYMENT RATES AND THE AVERAGE COMPENSATION

22

FOR A TECHNICAL CLASS MEMBER?

23

MR. VAN NEST:

24

NOT.

HE'S HERE.

25

I'M NOT SURE WHETHER HE'S DONE THAT OR

I'M NOT SURE WHETHER HE'S DONE THAT ANALYSIS

OR NOT.

UNITED STATES COURT REPORTERS

131

132

1

MR. GLACKIN:

2

THE COURT:

3

MR. GLACKIN:

IT'S CERTAINLY NOT IN HIS REPORT.

UM-HUM.
I MEAN, LIKE, IF DR. MURPHY HAD A

4

BETTER VARIABLE, RIGHT, IF SAN JOSE METRO AREA EMPLOYMENT WAS

5

THE WRONG VARIABLE, HE CERTAINLY HAD THE OPPORTUNITY TO TAKE

6

THE SAME REGRESSION AND PUT A DIFFERENT VARIABLE IN IT.

7

MR. VAN NEST:

8

MR. GLACKIN:

9

MR. VAN NEST:

10
11
12
13
14
15

MR. GLACKIN:

HIS POINT ISN'T THAT THERE'S --

EXCUSE ME.

I WASN'T FINISHED.

I'M SORRY.
I WAS ANSWERING THE JUDGE'S, WHAT I

UNDERSTOOD THE COURT'S QUESTION TO BE.
HE DID NOT DO THAT.

HE DID NOT RE-RUN THIS REGRESSION WITH

A, QUOTE UNQUOTE, BETTER VARIABLE.
INSTEAD HE WENT TO OTHER DATA SETS, LIKE THE WEATHER, AND
TRIED TO SHOW THAT HE CAN GET --

16

THE COURT:

17

MR. GLACKIN:

18

NO.

I WAS NOT PERSUADED.
-- SIMILAR RESULTS.

AND AGAIN, THE ABSENCE OF THAT, THE ABSENCE -- I MEAN, YOU

19

REMEMBER HE TESTIFIED AT HIS DEPOSITION THE FIRST TIME AROUND

20

THAT ADDING THE S&P 500 TOTAL RETURN INDEX IS SOMETHING HE

21

ALWAYS DOES TO TEST THE SENSITIVITY OF A REGRESSION AND WE HAD

22

TO, YOU KNOW, SLOG THROUGH MULTIPLE DIFFERENT REPORTS OF

23

REGRESSION RESULTS USING THINGS LIKE THE S&P 500 TOTAL RETURN

24

INDEX AND GIVING US CRAZY ANSWERS.

25

RESPECT.

HE HASN'T DONE THAT IN ANY

UNITED STATES COURT REPORTERS

132

133

1

THE BEST HE CAN DO IS SAY THAT IF YOU HYPOTHESIZE THAT WE

2

HAVE FAILED TO ACCOUNT FOR HALF OF THE RELEVANT FACTORS, THEN

3

THE ANSWER WOULD BE DIFFERENT.

4

WELL, I AGREE.

5

BE A DIFFERENT ANSWER.

6
7

BUT HE HAS NOT DONE THE STANDARD THING THAT, FRANKLY, I
THINK IT SPEAKS VOLUMES THAT HE DID NOT DO.

8
9

IF YOU HYPOTHESIZE THAT, THEN THERE MIGHT

MR. VAN NEST:

YOUR HONOR, THE REASON YOU WOULDN'T DO

IT IS THAT OBVIOUSLY IF WHAT YOU'RE TRYING TO COMPARE IS PAY

10

WITHIN ONE TITLE ON AN AVERAGE TO PAY WITHIN ALL TECHNICAL

11

EMPLOYEES IN A COMPANY, A REGRESSION DOESN'T ANSWER THE

12

QUESTION BECAUSE THEY WILL ALWAYS BE RELATED.

13

BE RELATED BECAUSE THEY'RE ALL SUBJECT TO THE SAME EXTERNAL SET

14

OF FACTORS.

15

THEY WILL ALWAYS

WHAT THEY FAILED TO SHOW WAS THAT A CHANGE IN ONE TITLE

16

WOULD CAUSE A CHANGE IN ANOTHER.

17

IN FACT, HE SAYS, "I DON'T THINK IT'S TRUE."

18

DR. LEAMER DOESN'T SAY THAT.

AND THAT IS GAME OVER BECAUSE THE WHOLE POINT IS NOT THAT

19

YOU HAVE A STRUCTURE, NOT THAT YOU PAY PEOPLE ACCORDING TO

20

TITLE.

21
22
23

WE DO THAT.

BUT IS IT RIGID SO THAT EITHER WITHIN A TITLE OR ACROSS
TITLES, A CHANGE IN ONE WOULD PROPAGATE OUT?
THERE'S NO DATA TO SUPPORT THAT.

24

THE COURT:

SO WHAT -- I'M SORRY TO INTERRUPT YOU.

25

MR. VAN NEST:

I'M SORRY.

UNITED STATES COURT REPORTERS

133

134

1

THE COURT:

2

IT THE DOCUMENTARY EVIDENCE?

3

WHAT IS YOUR EVIDENCE OF CAUSATION?

MR. GLACKIN:

IS

WHAT DO YOU HAVE ON CAUSATION?

INSOFAR AS THAT IS DIFFERENT FROM

4

IMPACT?

I GUESS -- I MEAN, I THINK OF -- I THINK ANTITRUST

5

IMPACT AND CAUSATION ARE -- PEOPLE FREQUENTLY COMPARE ANTITRUST

6

IMPACT TO THE CONCEPT OF PROXIMATE CAUSATION IN GENERAL TORT,

7

SO I THINK THAT IT IS THE SAME EVIDENCE.

8
9

THE COURT:
THE CAUSATION?

AND WHAT IS IT?

LET'S SAY I ACCEPT THAT THERE'S A CORRELATION.

10

MR. GLACKIN:

11

THE COURT:

12

MR. GLACKIN:

13

WHAT IS IT THAT SHOWS

OKAY.

WHAT'S THE CAUSATION?
WELL, THE EVIDENCE -- AGAIN, IT HELPS

TO BACK UP A LITTLE BIT TO WHERE, TO WHERE WE STARTED.

14

THE COURT:

UM-HUM.

15

MR. GLACKIN:

WHAT I UNDERSTOOD THE INQUIRY TO BE IS,

16

YOU KNOW, WE HAD DONE THE WORK TO SHOW THAT PEOPLE'S PAY AT

17

THESE COMPANIES, CLASS MEMBERS' PAY IS MAINLY DRIVEN BY JOB

18

TITLE.

19

AND WE HAD DONE THE WORK TO SHOW THAT THE -- TO AT LEAST

20

OFFER PROOF THAT THE AGREEMENTS HAD A BROAD AND GENERALIZED

21

EFFECT, WHICH WAS THE ADMISSIONS OF THE CEOS, THE DOCUMENTS,

22

THE NATURE OF THE AGREEMENTS THEMSELVES, AND THE REGRESSION

23

ANALYSIS.

24
25

THEY ALL SHOWED THAT THE INTENT AND THE ACTUAL EFFECT OF
THESE AGREEMENTS -- I MEAN, THIS IS PROOF -- I UNDERSTAND THAT

UNITED STATES COURT REPORTERS

134

135

1

THE DEFENDANTS WILL DISPUTE IT AT TRIAL -- BUT IT IS PROOF THAT

2

THESE AGREEMENTS HAD AN EFFECT BEYOND ONE WORKER.

3

THE THING THAT I UNDERSTOOD TO BE MISSING FROM THE COURT'S

4

PERSPECTIVE WAS SOME OF THE INFERENTIAL LINKS ALONG THE WAY,

5

AND SO WHAT WE HAVE DONE IS TO SHOW -- AND MAINLY ABOUT WHETHER

6

OR NOT THERE IS ACTUALLY A TITLE STRUCTURE THAT IS RESPECT --

7

THAT RESPECTS INTERNAL EQUITY AND THAT APPLIES THROUGHOUT THE

8

FIRM.

9
10

THAT'S THE QUESTION THAT WE UNDERSTOOD TO BE POSED.

AND WE HAVE, I THINK, ANSWERED IT.
SO I WOULD SAY THAT IT IS -- IT IS ALL THAT EVIDENCE.

WHAT

11

IS THE EVIDENCE OF CAUSATION?

IT IS THE EVIDENCE THAT THEY PAY

12

ACCORDING TO TITLE?

13

EFFECT, INCLUDING THE EVIDENCE -- ADMISSIONS BY THE CEOS THAT

14

THEY HAVE A PAY STRUCTURE AND THAT THE GOAL OF THE AGREEMENTS

15

WAS TO PROTECT THE PAY STRUCTURE?

IT IS THE EVIDENCE OF BROAD AND GENERAL

16

AND THEN IT IS ALL THE INFERENTIAL LINKS IN BETWEEN THAT

17

SHOW THAT HAD PREEMPTIVE MEASURES BEEN TAKEN BY THESE COMPANIES

18

TO RESPOND TO INCREASED COMPETITION, THAT THESE PREEMPTIVE

19

MEASURES WOULD HAVE APPLIED ACROSS THE FIRM.

20

AND TO RESPOND TO ONE THING THAT MR. VAN NEST SAID, I

21

BELIEVE, IF HE'S STILL REFERRING TO TAB 8 OF DR. LEAMER'S

22

TESTIMONY, HE'S OVERSTATING IT.

23

I DON'T THINK DR. LEAMER WAS EVER ASKED, NOR DID HE EVER

24

TESTIFY, ABOUT WHETHER MOVING A TITLE'S COMPENSATION WOULD

25

AFFECT THE REST OF THE FIRM.

UNITED STATES COURT REPORTERS

135

136

1

THE DOCUMENTARY EVIDENCE, I THINK, SHOWS THAT AT SOME OF

2

THESE FIRMS IT WOULD HAVE, BECAUSE THEY -- BECAUSE THEY SET ALL

3

THEIR TITLES AS A PERCENTILE OFF OF RADFORD, AND SO THE WAY

4

THAT THEY WOULD MOVE THE TITLES IS TO CHANGE THE PERCENTILE

5

THAT THEY WERE PEGGING OFF OF RADFORD.

6

WHAT DR. LEAMER WAS ASKED OVER AND OVER AGAIN IS, "ARE YOU

7

SAYING THAT IF ONLY A FEW PEOPLE'S PAY CHANGED, THAT IT WOULD

8

AFFECT THE WHOLE FIRM?"

9

AND THAT IS NOT OUR THEORY OF THE CASE AND THAT IS NOT HIS

10
11
12
13

AND HE'S NEVER OFFERED THAT OPINION

OPINION.
THE COURT:

BUT WHAT'S YOUR EVIDENCE OF CAUSATION

ACROSS JOB TITLES?
MR. GLACKIN:

WELL, AGAIN, THE EVIDENCE OF CAUSATION

14

IS THE EVIDENCE THAT THESE, THAT THESE FIRMS RESPECT THE

15

PRINCIPLE OF INTERNAL EQUITY AND THAT THE TITLES ARE HELD

16

TOGETHER IN A STRUCTURE, IN PART TO PRESERVE INTERNAL EQUITY.

17
18
19

THE COURT:

BUT ISN'T INTERNAL EQUITY ALL WITHIN THE

JOB TITLE?
MR. GLACKIN:

NO, IT'S NOT.

INTERNAL EQUITY OPERATES

20

AT DIFFERENT -- AT EVERY LEVEL OF THE COMPANY.

21

MAINTAINING A RELATIVE DISTANCE BETWEEN THE JOB TITLES IS JUST

22

AS IMPORTANT AS MAINTAINING THE RIGHT DISTANCE BETWEEN THE

23

EMPLOYEES WITHIN THE JOB TITLE.

24
25

I MEAN, THE --

SO INTERNAL EQUITY IS A CONCEPT THAT APPLIES UP AND DOWN
THE FIRM AT EVERY LEVEL OF AGGREGATION.

UNITED STATES COURT REPORTERS

136

137

1

THE COURT:

OKAY.

BUT WHAT IS YOUR EVIDENCE OF

2

CAUSATION ACROSS THE JOB TITLES?

3

IS A CORRELATION.

4

EVIDENCE BE?

5

LET'S SAY I ASSUME THAT THERE

WHAT WOULD -- WHAT WOULD YOUR CAUSATION

MR. GLACKIN:

WELL, THE CAUSATION EVIDENCE, IN

6

ADDITION TO THE CORRELATION, IS THE CONDUCT REGRESSION WHICH IS

7

EVIDENCE OF BROAD AND GENERALIZED -- IN ADDITION TO BEING AN

8

ESTIMATE OF DAMAGES, IT IS EVIDENCE OF BROAD AND GENERALIZED

9

HARM.

10

AND SO THE COMBINATIONS -- AGAIN, I DON'T WANT TO JUST KEEP

11

SAYING THE DOCUMENTS AND THE CEOS OVER AND OVER AGAIN.

12

KNOW ABOUT THAT STUFF.

13

CAUSATION.

14

YOU

I WOULD SAY THAT'S ALSO EVIDENCE OF

BUT WHEN YOU TAKE THE CONDUCT -- STATISTICALLY WHEN YOU

15

TAKE THE CONDUCT REGRESSION AND YOU ADD IT THE CORRELATION

16

ANALYSIS, YOU CONCLUDE THAT THE BROAD AND GENERAL HARM WOULD

17

HAVE BEEN FELT THROUGHOUT THE COMPANY AND NOT CONCENTRATED AT

18

HALF THE TITLES, FOR EXAMPLE.

19

UNDERSTOOD.

20

THE COURT:

THAT WAS THE INQUIRY THAT WE

DO YOU THINK THAT THE CORRELATION

21

ANALYSIS AND THE REGRESSION ANALYSIS PROVES THE CAUSATION, OR

22

NOT?

23

MR. GLACKIN:

SO I THINK THAT THE CONDUCT REGRESSION,

24

WHICH IS ALSO THE ESTIMATE OF DAMAGES, WHEN ADDED TO THE OTHER

25

STATISTICAL EVIDENCE PROVES CAUSATION, WHICH I UNDERSTAND TO BE

UNITED STATES COURT REPORTERS

137

138

1

THE SAME THING AS ANTITRUST IMPACT.

2
3

THE COURT:

THE CONDUCT REGRESSION AND WITH WHAT

OTHER STATISTICAL EVIDENCE?

4

MR. GLACKIN:

WITH THE EVIDENCE THAT ALL THE TITLES

5

AT THESE FIRMS HAVE A POSITIVE SHARING RELATIONSHIP WITH ONE

6

ANOTHER, BOTH CONTEMPORANEOUSLY AND OVER TIME.

7

EVIDENCE THAT THE EFFECT OF THESE AGREEMENTS WOULD HAVE BEEN

8

CLASS-WIDE.

9
10

THE COURT:

THAT IS

EVIDENCE THAT ALL TITLES HAVE POSITIVE

SHARING RELATIONSHIPS OVER TIME?

11

MR. GLACKIN:

AND I WANT TO BE -- I SHOULD BE

12

CAREFUL.

13

THAT HAVE NEGATIVE RELATIONSHIPS, BUT HE ALSO -- HE EXPLORED

14

THOSE TITLES, EXPLAINED WHY IT'S NOT SURPRISING TO FIND SOME

15

THAT HAVE NEGATIVE RELATIONSHIPS, AND EXPLAINED THAT HIS

16

OVERALL OPINION IS THAT THOSE TITLES ARE HELD TOGETHER THAT

17

WAY, AS IS DR. HALLOCK'S OPINION BASED ON THE EVIDENTIARY

18

RECORD.

19

I MEAN, DR. LEAMER NOTED THAT THERE ARE A FEW TITLES

THE COURT:

SO WHAT IS THE -- SO FOR THE COEFFICIENT,

20

YOUR CASE IS PROVEN IF THE NUMBER IS CLOSEST TO 1?

21

RIGHT?

22

STATISTICALLY SIGNIFICANT?

23

IS THAT

AND FOR THE T-STAT, WHAT NUMBER IS IT TO BE

MR. GLACKIN:

SO FOR -- OKAY.

SO LET ME TAKE THE

24

SECOND THING FIRST BECAUSE IT RELATES TO SOMETHING THAT

25

MR. VAN NEST WAS TALKING ABOUT BEFORE.

UNITED STATES COURT REPORTERS

138

139

1

HE CALLED THE COURT'S ATTENTION TO NOT SIGNIFICANT, TO THE

2

NOT SIGNIFICANT COLUMN IN THE REGRESSION ANALYSIS, SO THAT

3

MEANS THAT THOSE RESULTS DON'T MEET STATISTICAL SIGNIFICANCE AT

4

CONVENTIONAL LEVELS.

5
6

A T-STAT OF 2 OR MORE IS STATISTICAL SIGNIFICANCE AT
CONVENTIONAL LEVELS.

7

HOWEVER, THE FACT THAT WE DON'T -- THE POINT ISN'T THAT --

8

IT'S NOT NECESSARY TO DR. LEAMER'S OPINION THAT ALL THE

9

COEFFICIENTS BE POSITIVE, ALTHOUGH THE VAST MAJORITY ARE; NOR

10

IS IT NECESSARY TO HIS OPINION THAT THEY ALL BE STATISTICALLY

11

SIGNIFICANT.

12

WHAT THE TOTAL PICTURE OF VAST, VASTLY POSITIVE

13

COEFFICIENTS AND VASTLY STATISTICALLY SIGNIFICANT COEFFICIENTS

14

WHERE YOU HAVE 11 YEARS OF DATA TELLS HIM THAT THIS STRUCTURE

15

DOES EXIST.

16

AND I'LL JUST POINT OUT THAT IT'S, AGAIN, IT'S SORT OF --

17

IT'S SORT OF ESTABLISHED AGREEMENT IN THIS CASE AT THIS POINT

18

THAT STATISTICAL SIGNIFICANCE IS NOT NECESSARY TO THE

19

RELIABILITY OF AN ECONOMETRIC OPINION.

20

DR. MURPHY THE FIRST TIME AROUND.

21

OF BEHIND US ON THE ISSUE.

22

ZONE IN ON THAT COLUMN.

23

THE COURT:

24

MR. GLACKIN:

25

THAT WAS AGREED TO BY

I THINK, AGAIN, THAT'S SORT

SO I DON'T THINK IT'S HELPFUL TO

WHAT'S THE CHANGE CORRELATION?
COULD YOU TELL ME WHAT YOU'RE LOOKING

AT?

UNITED STATES COURT REPORTERS

139

140

1

THE COURT:

I'M LOOKING AT EXHIBIT 2 --

2

MR. GLACKIN:

3

THE COURT:

4

MR. GLACKIN:

SURE.

-- OF THE OPENING REPORT.
OKAY.

SO, YOU KNOW, IF IT WOULD BE

5

HELPFUL, I WOULD BE HAPPY TO JUST GO ACROSS THE COLUMNS, OR I

6

CAN JUST FOCUS ON --

7

THE COURT:

8

MR. GLACKIN:

9

THAT'S FINE.
-- CHANGE CORRELATION.

SO LEVEL CORRELATION IS THE DEGREE TO WHICH THE

10

COMPENSATION LEVELS ARE CORRELATED, SO IF THE AVERAGE

11

COMPENSATION IS A HUNDRED GRAND FOR ONE TITLE, THE QUESTION IS,

12

HOW IS THAT LEVEL CORRELATED TO THE AVERAGES AT ANY GIVEN POINT

13

IN TIME?

14
15
16

CHANGE COMPENSATION IS THE RATE OF -- TO WHAT DEGREE ARE
THE RATES OF CHANGE CORRELATED?
SO WHEN THE -- WHEN THE OTHER COMPENSATION AT THE COMPANY

17

GOES UP BY X PERCENT, 5 PERCENT, WHAT HAPPENS -- HOW MUCH DOES

18

THE COMPENSATION FOR THAT TITLE CHANGE?

19

CHANGE?

20

WHAT PERCENT DOES IT

AND THEN THE REGRESSION COEFFICIENTS ARE -- THE

21

CONTEMPORANEOUS COEFFICIENT IS -- BASICALLY IT SAYS HOW MUCH

22

EXPLANATORY POWER IS IN THE -- IS WHAT'S HAPPENING AT THE SAME

23

TIME WITH COMPENSATION TO THE REST OF THE CLASS?

24

FACTOR IS THAT IN THE PAY OF THE TITLE?

25

HOW MUCH OF A

THE LAGGED COEFFICIENT, OR VARIABLE, ASKS HOW --

UNITED STATES COURT REPORTERS

140

141

1

THE COURT:

2

ADOBE'S JOB TITLES?

3

WHY DON'T YOU HAVE DATA FOR MOST OF
WHY IS IT BLANK?

MR. GLACKIN:

BECAUSE -- SO YOU'RE TALKING -- SO THE

4

DATA FOR ADOBE TITLES IS BROKEN DOWN BY -- ALL THE DATA IN

5

THESE EXHIBITS IS BROKEN DOWN BY THE NUMBER OF YEARS FOR WHICH

6

WE HAVE DATA FOR A TITLE.

7

FOR EXAMPLE, WE HAVE 11 YEARS OF DATA.

8

TITLES ARE IN EXISTENCE FOR ALL 11 YEARS.

9

SOME OF THESE

TO WORK WITH.

10
11
12
13
14

THAT'S A LOT OF DATA

SOME OF THESE TITLES ARE IN EXISTENCE FOR TWO OR THREE
YEARS.

THAT'S NOT ENOUGH DATA TO WORK WITH.

SOME OF THESE TITLES ARE IN EXISTENCE FOR SIX, SEVEN, OR
EIGHT YEARS.
THE REASON THAT YOU SEE BLANKS ON -- I THINK THE PAGE

15

YOU'RE LOOKING AT FOR ADOBE IS YOU'LL SEE THOSE ARE ALL TITLES

16

FOR WHICH WE ONLY HAVE SIX YEARS OF DATA.

17

TO DO THE CORRELATION ANALYSIS, BUT IT IS NOT ENOUGH DATA TO DO

18

THE REGRESSION ANALYSIS, BECAUSE THE REGRESSION ANALYSIS HAS

19

FOUR VARIABLES, AND WITH SIX -- AND ONE OF THOSE VARIABLES IS A

20

RATE OF CHANGE, AND WITH SIX -- I'M GOING TO TRY TO GET THIS

21

RIGHT -- WITH ONLY SIX YEARS OF DATA AND ONE OF YOUR VARIABLES

22

BEING A CHANGE VARIABLE, YOU ONLY HAVE 5 DEGREES OF FREEDOM,

23

WHICH IS NOT ENOUGH DATA.

24

KIND OF SENSIBLE ANSWER ABOUT FOUR EXPLANATORY VARIABLES AND

25

ONE DEPENDENT VARIABLE, WHICH IS FIVE VARIABLES TOTAL.

THAT IS ENOUGH DATA

IT'S NOT ENOUGH FREEDOM TO GET ANY

UNITED STATES COURT REPORTERS

141

142

1
2

THE COURT:

WHY DON'T YOU CONTINUE WITH THE

CONTEMPORARY AND THE LAGGED VARIABLE?

3

MR. GLACKIN:

SURE.

SO THE CONTEMPORARY VARIABLE

4

REFLECTS HOW MUCH, HOW MUCH THE JOB TITLE'S COMPENSATION IS

5

EXPLAINED BY WHAT'S HAPPENING AT THE REST OF THE COMPANY.

6

THE LAGGED VARIABLE ASKS HOW MUCH OF THE JOB TITLE'S

7

COMPENSATION, IN THE REGRESSION, IS EXPLAINED BY THE DIFFERENCE

8

BETWEEN THE JOB TITLE AND THE REST OF THE CLASS, THE REST OF

9

THE COMPANY IN THE PRIOR YEAR.

10

SO IN OTHER WORDS, IF THERE WAS A BIG DIFFERENCE, DO WE

11

SEE A CONVERGENCE IN THE SECOND YEAR, OR VICE-VERSA?

12

IT TO BE EITHER ONE.

13

IT ALLOWS

AND SO THAT IS TO ACCOUNT FOR THE POSSIBILITY THAT

14

SOMETIMES THE EFFECT OF THE INTERNAL EQUITY ON THE STRUCTURE

15

WILL BE FELT IN A SUBSEQUENT YEAR.

16

AND THEN THE OTHER TWO VARIABLES ARE THE EXTERNAL FACTOR

17

VARIABLES.

18

FIRM PERFORMANCE, YOU KNOW, THE COMPANY HAS A GOOD YEAR, SO

19

EVERYONE GETS PAID MORE; AND -- OR THAT TITLE GETS PAID MORE;

20

AND THE SJ EMP IS SAN JOSE EMPLOYMENT, SO THAT ACCOUNTS FOR THE

21

TECH SECTOR IS HOT, JOBS ARE SCARCE, PAY GOES UP.

22

REVENUE IS THE FIRM'S REVENUE, WHICH ACCOUNTS FOR

AND WHAT YOU SEE WHEN YOU LOOK AT THESE IS A LOT OF MOSTLY

23

GOOD SIZED AND POSITIVE COEFFICIENTS ON THE INTERNAL SHARING

24

VARIABLES.

25

THEY'RE NOT ALWAYS POSITIVE AND THEY'RE NOT ALWAYS LARGE.

UNITED STATES COURT REPORTERS

142

143

1

BUT THEY CERTAINLY DON'T GO AWAY WHEN YOU ACCOUNT FOR THE

2

EXTERNAL FACTORS, WHICH IS WHAT WOULD HAPPEN IF THE DEFENDANTS'

3

THEORY OF THE CASE WERE CORRECT.

4

THE COURT:

WHAT ABOUT THE NET EFFECT?

5

MR. GLACKIN:

6

THE COURT:

7

MR. GLACKIN:

OH, SO --

UM-HUM.
-- ALL THE NET -- SO T STATUS IS

8

T-STAT, AND THE NET EFFECT IS IF YOU ADD THE CONTEMPORANEOUS

9

AND THE LAGGED VARIABLES TOGETHER, THAT'S THE ANSWER.

10

SO FOR -- IF YOU'RE LOOKING AT EXHIBIT 2, APPLE, YOU SEE

11

THAT FOR THE FIRST ONE, INFORMATION SYSTEMS MANAGER 2, THE

12

CONTEMP IS .8, THE LAGGED IS .04, IF YOU ADD THEM TOGETHER, YOU

13

GET .84.

14

THE COURT:

AND WHAT IS THE OBS IN SECTION 6?

15

MR. GLACKIN:

THAT IS THE R SQUARED.

SO THAT IS

16

THE -- THAT IS JUST A -- THAT IS A STANDARD ECONOMIC, OR

17

STATISTICAL MEASURE OF WHAT'S CALLED GOODNESS OF FIT TO THE

18

DATA.

19

VARIABLE IS BEING EXPLAINED BY THE EXPLANATORY VARIABLES.

20

IT TELLS YOU SOMETHING ABOUT HOW MUCH OF THE DEPENDENT

I'M SURE SOMEONE COULD PROBABLY EXPLAIN IT TECHNICALLY

21

BETTER THAN THAT, BUT I THINK EVERYONE AGREES THAT THAT'S

22

GENERALLY WHAT IT IS.

23

THE COURT:

LET ME ASK BOTH SIDES, HOW DO YOU EXPLAIN

24

WHY THE TWO EXPERTS CAME OUT WITH CONFLICTING ANALYSIS OF THE

25

ACS DATA?

DID THEY DO IT IN DIFFERENT WAYS?

UNITED STATES COURT REPORTERS

DID THEY LOOK AT

143

144

1
2

SOMETHING DIFFERENTLY?
MR. GLACKIN:

WELL, I DON'T THINK THAT THEIR

3

ANALYSIS -- HOW DID THEY COME OUT WITH CONFLICTING ANALYSIS OF

4

THE ACS DATA?

5

THIS IS THE STATE OF PLAY WITH THE ACS DATA.

WHAT

6

DR. MURPHY DID IS HE TOOK ALL OF THE SURVEY DATA FROM ALL OF

7

THESE DIFFERENT JOBS ACROSS THE UNITED STATES AND HE PLUGGED IT

8

INTO A REGRESSION ANALYSIS AND HE SAID, "SEE, I CAN GET

9

POSITIVE RESULTS ON THE SHARING VARIABLES, SO THAT MEANS THAT

10
11

WHAT DR. LEAMER DID IS INVALID."
WHAT DR. LEAMER HAS POINTED OUT IN HIS REBUTTAL REPORT, HIS

12

REPLY OR REBUTTAL REPORT, IS THAT THAT DATA SET IS COMPLETELY

13

UNSUITED TO THIS PURPOSE BECAUSE OF THIS HUGE METHODOLOGICAL

14

FLAW WITH THE WAY THE DATA IS GATHERED.

15

WHAT THE -- WHEN THE SURVEY IS ADMINISTERED TO THE OCCUPANT

16

OF THE HOUSE, A SINGLE PERSON FROM THE HOUSE ANSWERS ON BEHALF

17

OF EVERYBODY IN THE HOUSE AND SAYS THE LOT -- "IN THE LAST 365

18

DAYS, WE HAVE EARNED X AMOUNT OF MONEY," AND THAT SURVEY IS

19

ADMINISTERED EVERY MONTH.

20

SO IN EVERY MONTH, OTHER THAN DECEMBER, YOU'RE GETTING

21

ANSWERS FOR BOTH THE PRIOR YEAR AND -- YOU'RE GETTING AN AMOUNT

22

OF MONEY THAT INCLUDES MONEY FROM THE PRIOR YEAR AND MONEY FROM

23

THE CURRENT YEAR.

24

SO IF THE SURVEY IS ADMINISTERED IN JUNE, HE TELLS YOU, "I

25

EARNED 80 GRAND THIS YEAR," BUT YOU DON'T KNOW WHAT OF THAT 80

UNITED STATES COURT REPORTERS

144

145

1

GRAND WAS EARNED IN 2013 VERSUS WHAT OF THAT 80 GRAND WAS

2

EARNED IN 2012.

3
4

YOU HAVE NO IDEA.

SO THEN DR. MURPHY TAKES THIS DATA SET AND HE USES -- HE
APPLIES TO IT CALENDAR YEAR VARIABLES AND GETS THESE RESULTS.

5

AND, YOU KNOW, I DON'T KNOW WHAT, WHAT OTHER ANALYSIS HE

6

DID, BUT THIS ONE IS COMPLETELY INAPPROPRIATE AND IT IS SUBJECT

7

TO A HUGE METHODOLOGICAL FLAW AND THAT'S WHY IT'S NOT RELIABLE.

8

AND THEN AS DR. LEAMER POINTS OUT, THERE -- IF YOU -- IF

9

YOU ASK YOURSELF HOW WELL THESE TITLES ARE CORRELATED WITH ONE

10

ANOTHER IN THE ACS DATA SET, WHAT YOU SEE IS -- AND THIS IS IN

11

HIS REBUTTAL REPORT -- THAT IN THE ACS DATA -- SO THERE ARE --

12

THERE IS ACTUALLY THE KIND OF CORRELATIONS YOU MIGHT EXPECT TO

13

SEE.

14

NEGATIVE CORRELATIONS, AND THEY FALL ROUGHLY EVENLY AROUND 0.

15

THERE ARE SOME POSITIVE CORRELATIONS, THERE ARE SOME

IN THE DEFENDANTS' DATA, THE CORRELATIONS ARE ALMOST ALL

16

POSITIVE, AND MOST OF THEM ARE UP AROUND .8 OR .9, AND THAT

17

JUST SHOWS THAT THE ACS DATA IS COMPLETELY UNCOMPARABLE TO THE

18

DEFENDANTS' DATA AND ANALYZING IT IS A POINTLESS EXERCISE UNDER

19

THESE CIRCUMSTANCES.

20
21

THE COURT:
ACS DATA.

22
23

LET ME LET MR. VAN NEST RESPOND TO THE

MR. VAN NEST:

AND I WANT TO GO BEYOND THAT A LITTLE

BIT.

24

BUT THE ACS DATA JUST PROVES THE BASIC POINT THAT

25

DR. MURPHY IS MAKING, THAT THESE REGRESSIONS DON'T MEAN A

UNITED STATES COURT REPORTERS

145

146

1

THING, AND EVEN LEAMER SAYS THESE ARE LIMITED EXERCISES.

2

LEAMER SAYS THESE DON'T SHOW CAUSATION.

3

OF HIS DEPO AND, REPEATEDLY, THESE DO NOT SHOW CAUSATION.

4

THEY ARE IS CORRELATION.

5

THE COURT:

6

MR. VAN NEST:

HE SAYS IT AT PAGE 525
ALL

UM-HUM.
AND THE ACS DATA SHOWS THAT IF WHAT

7

YOU'RE COMPARING IS A TITLE WITHIN A COMPANY TO EVERYBODY IN

8

THE COMPANY, GETTING A POSITIVE CORRELATION DOESN'T TELL YOU

9

WHETHER YOU HAVE A RIGID OR A NON-RIGID STRUCTURE BECAUSE THOSE

10

THINGS WILL TEND TO BE CORRELATED NO MATTER WHAT --

11

THE COURT:

12

MR. VAN NEST:

13

SAME EXTERNAL FACTORS.

14
15

UM-HUM.
-- BECAUSE THEY ARE ALL SUBJECT TO THE

LET ME MAKE ANOTHER POINT ABOUT THIS, YOUR HONOR.
THE COURT:

WHY DO YOU THINK THAT DR. MURPHY GOT THE

16

HIGH, THESE HIGH COEFFICIENTS AND DR. LEAMER GOT THE LOW ONES

17

WITH THE SAME DATA?

18

MR. VAN NEST:

19

DID WITH THE ACS DATA.

20

I DON'T KNOW EXACTLY WHAT DR. LEAMER

ALL I KNOW IS THAT DR. MURPHY TRIED TO REPLICATE EXACTLY

21

WHAT LEAMER HAD DONE WITH THE COMPANY DATA.

22

LIKE LEAMER DID, SO HE WENT ABOUT IT THE SAME WAY LEAMER DID,

23

GOT THE SAME HIGH CORRELATIONS.

24
25

HE USED AVERAGES

AND JUST AN EXAMPLE OF THIS, YOUR HONOR -THE COURT:

EVEN HIGHER.

UNITED STATES COURT REPORTERS

146

147

1
2

MR. VAN NEST:

CORRELATIONS HE JUST TOLD YOU ABOUT FROM ADOBE --

3

THE COURT:

4

MR. VAN NEST:

5

IF YOU LOOK -- IF YOU LOOK AT THE

UM-HUM.
-- YOU WILL SEE THE THIRD TITLE DOWN

IS A PRINCIPAL SCIENTIST 6.

6

THE COURT:

UM-HUM.

7

MR. VAN NEST:

THE CORRELATIONS ARE HIGH, AND YET, IF

8

YOU LOOK AT THE RAW DATA FOR THAT ADOBE PRINCIPAL SCIENTIST 6,

9

BEHIND TAB 4 YOU'LL SEE THERE IS ENORMOUS VARIATION, ENORMOUS

10

VARIATION WITHIN THAT TITLE WITHIN THE PEOPLE EMPLOYED THERE.

11

AND SO THAT'S WHY MURPHY SAYS THIS REGRESSION AND

12

CORRELATION MEAN NOTHING.

13

YOU'VE TAKEN THE VARIATION OUT.

14

WHEN YOU AVERAGE TO START WITH,

BUT IF YOU COMPARE WHAT HE'S SHOWING AS CORRELATION, HE'S

15

GOT A .86, HE'S GOT A .89 AND .79 ON HIS LEVEL AND CHANGE

16

CORRELATIONS FOR THIS PRINCIPAL SCIENTIST 6.

17

IF YOU LOOK AT THE RAW DATA BEHIND TAB 4, THERE IS AN

18

ENORMOUS AMOUNT OF VARIATION, PROVING OUR POINT THAT THESE

19

REGRESSIONS TELL YOU NOTHING.

20

AND THEY ARE SET UP TO SHOW SOMETHING THAT DOESN'T ANSWER THE

21

RIGHT QUESTION.

22
23
24
25

THEY ARE SET UP USING AVERAGES

THE RIGHT QUESTION IS, DOES A CHANGE IN ONE TITLE CAUSE A
CHANGE IN OTHER TITLES?
HE HASN'T POINTED YOU TO ANY STATISTICAL EVIDENCE TO PROVE
THAT.

THERE IS NO DOCUMENTARY EVIDENCE TO PROVE THAT.

UNITED STATES COURT REPORTERS

147

148

1

THE FACT THAT WE HAVE A STRUCTURE MEANS NOTHING WHEN THOSE

2

STRUCTURES HAVE 50 TO $100,000 OF RANGE WITHIN A BAND.

3

AND IF YOU LOOK AT MURPHY 7 AND MURPHY 8, THERE IS

4

ABSOLUTELY NO WAY TO CONCLUDE, OTHER THAN WITH RESPECT TO THESE

5

TITLES --

6
7

THE COURT:

WHAT EXHIBIT NUMBER HAS THE $100,000

RANGE?

8

MR. VAN NEST:

9

THE COURT:

10

EXCUSE ME?

WHAT EXHIBIT NUMBER?

MR. VAN NEST:

IT'S EXHIBIT 7 IN HALLOCK.

IT'S

11

EXHIBIT 7 IN HALLOCK, AND HE'S SHOWING AN EXAMPLE THERE OF

12

SALARY RANGES AT GOOGLE.

13

COMPANIES.

14

GOT -- IT'S FROM HIS MAY 10TH REPORT.

15

AT GOOGLE AND YOU CAN SEE THAT --

AND THAT'S JUST, YOU KNOW, ONE OF THE

BUT IT'S FIGURE 7 FROM HALLOCK'S REPORT.

16

THE COURT:

17

MR. VAN NEST:

HE'S

HE'S SHOWING A JOB GRADE

UM-HUM.
-- AT THE HIGH END, IT'S MORE THAN

18

100, AND THEN YOU'VE GOT ANOTHER ONE THAT'S ALMOST A HUNDRED,

19

IT'S 90, ANOTHER ONE THAT'S 70.

20
21

I MEAN -- AND THIS IS JUST SALARY, YOUR HONOR, BASE.

THIS

DOESN'T INCLUDE EQUITY.

22

THE COURT:

UM-HUM.

23

MR. VAN NEST:

24

THE COURT:

25

MR. VAN NEST:

IT DOESN'T INCLUDE BONUS.

UM-HUM.
AND SO YOU WOULD EXPECT TO SEE THESE

UNITED STATES COURT REPORTERS

148

149

1

WIDE VARIATIONS WITHIN A TITLE --

2

THE COURT:

3

MR. VAN NEST:

4

UM-HUM.
-- AND WIDE VARIATIONS BETWEEN AND

AMONG TITLES.

5

THE COURT:

UM-HUM.

6

MR. VAN NEST:

AND I GUESS -- WHEN YOU HAVE LEAMER

7

ADMITTING THAT HE CAN'T SHOW CAUSATION AND YOU HAVE HIM

8

CONCEDING THAT HE CAN'T SAY THE STRUCTURE IS SO RIGID THAT

9

THERE WOULD BE PROPAGATION, ADD THAT TO APPENDIX E, WHICH IS

10

TAB 11 IN WHAT I HANDED UP, YOUR HONOR.

11

OF 2400 JOB TITLES THAT THEY'RE TRYING TO STAND HERE AND TELL

12

YOU ARE ALL MOVING TOGETHER AND ALL CAUSE ONE TO THE OTHER.

13
14

IT'S LUDICROUS.

APPENDIX E IS THE LIST

YOU CAN GO TO ANY PAGE OF THIS AND SEE AN

ENORMOUS AMOUNT OF VARIATION ON ALL THESE COMPANIES.

15

INTEL, 800 TITLES.

16

APPLE, 350 TITLES.

17

GOOGLE, 300 TITLES.

18

AND JUST LOOK AT THE RANGE.

PICK UP THE FIRST PAGE OF

19

INTEL:

20

ENGINEERING MANAGER; YOU'VE GOT A CHEMICAL ENGINEER; A CIRCUIT

21

DESIGN ENGINEER; CONSTRUCTION PROJECT MANAGER; CONSULTING

22

ENGINEERING MANAGER; FAILURE ANALYSIS ENGINEER.

23

ON AND ON AND ON.

24
25

ASSEMBLY TD PROCESSOR AND INTEGRATOR; YOU'VE GOT A CAD

IT GOES ON AND

AND WITH 2400 OF THESE, THE IDEA THAT THEY -- THAT THERE'S
SOME, QUOTE, LINKAGE WITHIN COMPANIES IS ABSOLUTELY CRAZY.

UNITED STATES COURT REPORTERS

149

150

1

AND THAT'S WHY THERE ISN'T ANY STATISTICAL EVIDENCE.

2

IS NONE.

THE STATISTICAL EVIDENCE POINTS THE OTHER WAY.

3

THERE

VARIATION, WIDE DISCRETION, BIG DIFFERENCES YEAR TO YEAR.

4

MR. GLACKIN:

5

MR. VAN NEST:

HUGE

I -AND SO WHAT THEY'RE ASKING YOU TO

6

DO -- THIS IS A SWING FOR THE FENCES TYPE PLAY.

7

A FACTOR OF THREE THAN ANY SIMILAR CASE THAT'S -- WHERE IT'S

8

EVEN BEEN REQUESTED.

9

IT'S BIGGER BY

AND IN REED AND THE OTHER CASES THAT WE CITED, YOUR HONOR,

10

WEISFELDT AND FLEISHMAN, MUCH SMALLER CLASSES WITH SINGLE JOB

11

TITLES WERE NOT CERTIFIED.

12

THE COURT:

13

MR. VAN NEST:

UM-HUM.
AND THAT'S BEFORE COMCAST SAID YOU

14

HAVE TO MAKE A RIGOROUS ANALYSIS OF THE DATA AND SEE HOW

15

RELIABLE AND PERSUASIVE IT IS IF WHAT THEY WANT IS SOMETHING

16

THIS BIG WHERE THEY'RE GOING TO PROVE IN ONE TRIAL ALL OF THIS,

17

ALL THIS STUFF.

18

NOW, YOU OFFERED THEM SOMETHING LESS AND THEY DON'T WANT

19

IT, AND THAT SOMETHING LESS WAS, LET'S TRY THE CONSPIRACY ISSUE

20

FIRST.

21

THEY'VE GOT TO PROVE IMPACT ACROSS THE CLASS AND THEY

22

HAVEN'T DONE IT.

23

DOCUMENTS THAT REFLECT THAT.

24
25

THE DATA DON'T REFLECT IT.

THERE ARE NO

AND SO WE NEED TO THINK ABOUT ANOTHER WAY TO RESOLVE THIS
CASE, AND I THINK COMING BACK TO THE IDEA OF LETTING PEOPLE, IN

UNITED STATES COURT REPORTERS

150

151

1

EFFECT, OPT INTO A MASS ACTION WHERE WE CAN ACTUALLY MANAGE HOW

2

IT GETS TRIED AND WHAT PORTIONS OF IT GET TRIED AND HOW WE CAN

3

SET OURSELVES UP TO RESOLVE THIS IS A LOT BETTER THAN THIS HAIL

4

MARY WHERE THEY WANT 60,000 PEOPLE IN A CLASS WITH 2400 TITLES.

5

IT'S JUST GOING TO BE A MESS AND WE'RE BETTER OFF SAYING NO

6

NOW.

7

SAY NO AND FIGURE OUT ANOTHER BETTER WAY TO DO THIS, WHICH, AS

8

I SAY, IS HOW WE'RE TRYING THESE TORT CASES AROUND CALIFORNIA

9

AND THE UNITED STATES NOW MORE AND MORE.

10

BECAUSE THEY DIDN'T TAKE YOUR MORE LIMITED OFFER, LET'S

WITH THESE STANDARDS BEING IMPOSED FROM COMCAST AND ELLIS

11

AND AMGEN AND ALL THIS, WHAT COURTS ARE DOING IS REFUSING TO

12

CERTIFY AND FINDING A BETTER WAY, USUALLY A MASS APPROACH WHERE

13

PEOPLE MAKE THEIR CLAIMS AND WE TRY, IN A BELLWETHER TRIAL, A

14

SERIES OF THOSE.

15

THAT'S THE WAY THIS CASE SHOULD BE RESOLVED.

16

FAIRER TO THE DEFENDANTS.

17

THAT'S A LOT

WE'LL GET A BETTER RESULT.

18

THIS CLASS CAN'T STAND UP.

19
20

IT'S A LOT BETTER ACROSS THE BOARD.

THE COURT:

ALL RIGHT.

LET ME INTERRUPT YOU ONE

SECOND.

21

MR. VAN NEST:

22

THE COURT:

YEAH.

LET ME ASK MR. GLACKIN, LAST TIME YOU HAD

23

MENTIONED THAT YOU MIGHT BE INTRODUCING THE STATISTICAL

24

EVIDENCE FOR FALSIFICATION PURPOSES.

25

ARE YOU DOING THAT NOW, OR THAT'S NOT REALLY AN ISSUE

UNITED STATES COURT REPORTERS

151

152

1

ANYMORE?

2
3

MR. GLACKIN:

I DON'T THINK THAT THAT'S A VERY

IMPORTANT ISSUE.

4

THE COURT:

OKAY.

5

MR. GLACKIN:

6

THE COURT:

CAN I RESPOND TO SOME OF THAT?

WELL, I'M GOING TO -- I'D LIKE TO WRAP

7

UP, AND I ALSO WANT TO HAVE A LITTLE BIT OF A CMC, BUT I WANT

8

TO FINISH IN THE NEXT TEN, NO LATER THAN THE NEXT TEN MINUTES.

9

SO --

10

MR. VAN NEST:

11

THE COURT:

12

YES, I KNOW.

YOU HAVE A FLIGHT TO CATCH,

RIGHT?

13

MR. VAN NEST:

14

THE COURT:

15

MR. VAN NEST:

16

THE COURT:

17

MR. GLACKIN:

18

ME, TOO, YOUR HONOR.

I DO.

OKAY.

IS IT OKAY IF WE GO TO 5:30?

SURE.

OKAY.
THERE'S JUST A COUPLE OF POINTS IN THAT

THAT I THINK I CAN RESPOND TO RATHER BRIEFLY IF IT'S ALL RIGHT.

19

THE COURT:

OKAY.

20

MR. GLACKIN:

VERY QUICK.

SO FIRST OF ALL, THE RIGOROUS ANALYSIS

21

STANDARD IS NOT NEARLY -- IT'S BEEN AROUND FOR 30 YEARS.

22

DUKES, COMCAST, AMGEN, NONE OF THOSE CASES CHANGE IT.

23

BEEN AROUND FOREVER.

IT'S

IT'S BEEN AROUND SINCE EISEN.

24

SECOND OF ALL, THIS IS NOT A BIG CLASS.

25

PARTICULARLY LARGE OR COMPLICATED CLASS ACTION.

UNITED STATES COURT REPORTERS

THIS IS NOT A
I MEAN, WE

152

153

1

REGULARLY CERTIFY, IN ANTITRUST CASES, CLASS ACTIONS WITH

2

THOUSANDS OF PRODUCTS, THOUSANDS OF PURCHASERS.

3

IT IS THE REASON -- THE FACT THAT CLASS RELIEF --

4

THE COURT:

IT IS THE --

CAN I -- LET ME INTERRUPT YOU AND ASK A

5

QUESTION.

6

THE SMALLER 150,000 MEMBER WAL-MART CLASS, AND ONE OF HIS

7

COMMENTS IN HIS CONCLUSION WAS, "LOOK, IT'S KIND OF ARBITRARY

8

HOW YOU CHOSE TO NARROW THIS.

9

REGIONS YOU CHOSE ARE REALLY NOT ANY DIFFERENT THAN ANY OTHER

10
11

YOU KNOW, JUDGE BREYER RECENTLY DENIED CLASS CERT TO

YOU KNOW, THE GEOGRAPHICAL

REGIONS WHERE WAL-MART OPERATES."
WHAT -- HOW WOULD YOU RESPOND TO -- YOU KNOW, WHAT

12

JUSTIFIES THIS TECHNICAL CLASS?

13

BLAME FOR THIS, BUT WHAT JUSTIFIES THIS VERSUS THE ALL EMPLOYEE

14

CLASS?

15
16

OR WHAT -- YOU KNOW, WHAT -MR. GLACKIN:

THE COURT:

18

MR. GLACKIN:

20
21
22

SO THE -- THE SUBSEQUENT DISCOVERY THAT

WE'VE TAKEN SINCE THE HEARING --

17

19

AND MAYBE I'M PARTIALLY TO

UH-HUH.
-- HAS CONFIRMED THAT THESE AGREEMENTS

WERE PARTICULARLY TARGETED AT HIGH TECH WORKERS.
THE -- SO THERE'S A LITTLE BIT MORE EVIDENCE ABOUT THAT IN
THE RECORD NOW THAT WE ALSO CITED.
BUT THE SELECTION OF THIS GROUP OF PEOPLE WAS NOT AT ALL

23

ARBITRARY.

I MEAN, THE DEFENDANTS THEMSELVES, SEVERAL OF

24

THEM -- AND THIS IS ALL IN APPENDIX B TO DR. LEAMER'S FIRST

25

REPORT -- SEVERAL OF THESE DEFENDANTS SEGMENT THEIR EMPLOYEES

UNITED STATES COURT REPORTERS

153

154

1

INTO TECH AND NON-TECH.

2

EMPLOYEE AND EVERY JOB TITLE THAT IT CONSIDERS TO BE TECHNICAL,

3

SO WE INCLUDED THOSE.

4
5
6

GOOGLE PUTS A "T" NEXT TO EVERY

WE EXCLUDED THE OTHER ONES.

YOU KNOW, THIS IS A DIFFERENTIATION THAT'S BEING DRIVEN BY
THE DEFENDANTS' OWN APPROACH TO THEIR EMPLOYEES.
AND THEN IN ADDITION TO THAT, WE'VE ASKED DR. HALLOCK, WHO

7

IS A LEADING EXPERT ON COMPANY PAY SYSTEMS AND HOW COMPANIES

8

ORGANIZE AND COMPENSATE THEIR EMPLOYEES, HE'S REVIEWED THE

9

TECHNICAL CLASS AND HE'S OFFERED THE OPINION THAT, FIRST OF

10

ALL, IT'S A SENSIBLE COLLECTION THAT IS CONSISTENT WITH THE WAY

11

THAT COMPANIES ORGANIZE THEIR JOB FAMILIES TO REFLECT

12

PARTICULAR FUNCTIONS WITHIN THE FIRM, AND HE'S ALSO OFFERED THE

13

OPINION THAT HARM LIKELY WOULD HAVE BEEN CONCENTRATED ON THE

14

TECHNICAL CLASS GIVEN THE NATURE OF THE AGREEMENTS.

15

SO IT WAS NOT AN ARBITRARY DECISION AT ALL.

16

THE COURT:

ALL RIGHT.

LET ME DO A LITTLE

17

HOUSEKEEPING AND THEN I'M GOING TO GIVE YOU THE LAST COUPLE

18

MINUTES TO WRAP UP TO SAY WHATEVER, HOWEVER YOU WISH TO CLOSE.

19

LET'S HAVE THE FURTHER CMC ON OCTOBER 3RD, WHICH IS WHEN

20

WE'RE GETTING TOGETHER ANYWAY FOR THE PRELIMINARY APPROVAL.

21

DOES THAT SOUND OKAY?

22

MR. VAN NEST:

23

THE COURT:

THAT'S FINE, YOUR HONOR.

ALL RIGHT.

I WOULD -- IN LIGHT OF THE

24

THREE DEFENDANTS SETTLING, I'D LIKE TO REDUCE SOME OF THE PAGE

25

LIMITS THAT I HAD PREVIOUSLY SET FOR PRETRIAL DOCUMENTS.

UNITED STATES COURT REPORTERS

154

155

1
2

MR. VAN NEST:

COULD I JUST BRIEFLY MAKE A PLEA THAT

YOU NOT DO THAT, YOUR HONOR?

3

WE'RE HAVING -- WE HAVE -- IT'S STILL FOUR DEFENDANTS.

4

EACH HAVE ISSUES THAT WE NEED TO PRESS.

5

WE

SAME.

6

WE'RE NOT ALL THE

AND HONESTLY, IF THEIR POSITION IS THAT ALL THE SAME

7

EVIDENCE AND STUFF IS RELEVANT, IT SHOULDN'T CHANGE THE PAGE

8

LIMITS.

9
10
11

I WOULD JUST LEAVE IT AT THAT, YOUR HONOR, AND ASK YOU
PLEASE NOT TO DO THAT.
THE COURT:

IT'S ALREADY REALLY TIGHT.
WELL, THIS IS WHAT I'LL DO.

LET'S TALK

12

ABOUT THIS -- SINCE IT'S A LATE HOUR NOW, LET'S TALK ABOUT THIS

13

ON OCTOBER 3RD SINCE WE HAVE TIME.

14

GOING TO RUN UNTIL, I THINK, FEBRUARY.

15

MR. VAN NEST:

16

THE COURT:

NONE OF THOSE DEADLINES ARE

GOOD TO GO.

OR JANUARY.

BUT IF YOU WOULD AT LEAST

17

TALK ABOUT MAYBE YOU COULD SHAVE SOME OFF HERE AND THERE.

I

18

MEAN, THESE LIMITS WERE SET ASSUMING ALL SEVEN DEFENDANTS WOULD

19

BE PARTICIPATING.

20

SOME LIMITS AND THEN PUT YOUR PROPOSAL IN THE JOINT CASE

21

MANAGEMENT STATEMENT.

SO IF YOU WOULD PLEASE AT LEAST CONSIDER

22

MR. VAN NEST:

23

THE COURT:

CERTAINLY WE WILL.

ALL RIGHT.

SO -- WELL, I WAS GOING TO

24

MAKE SOME PAGE REDUCTIONS, BUT IF YOU WANT ME TO HOLD OFF ON

25

THAT, THEN I DON'T THINK THAT --

UNITED STATES COURT REPORTERS

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156

1

MR. VAN NEST:

2

THE COURT:

3

-- THERE'S ANYTHING MORE WE NEED TO DO ON

THE CMC.

4

MR. VAN NEST:

5

MR. SAVERI:

6

PLEASE.

THANK YOU.

I THINK THAT'S FINE.

WE'LL WORK IT

OUT --

7

MR. VAN NEST:

8

MR. SAVERI:

9

THE COURT:

WE'LL WORK IT OUT.

-- AFTER MR. VAN NEST'S SOJOURN.
I WOULD APPRECIATE ANY SHAVING.

10

MR. SAVERI:

YOU GOT IT.

11

MR. VAN NEST:

12

THE COURT:

WE KNOW THAT, YOUR HONOR.

OKAY.

AND ALSO IF YOU WOULD GIVE ME A

13

NEW TRIAL ESTIMATE AS WELL, YOU KNOW, DEPENDING ON WHO IS LEFT

14

TO TRY THE CASE, WHETHER THAT WOULD ACTUALLY CHANGE THE LENGTH

15

OF THE TRIAL.

16
17
18
19

MR. SAVERI:

SO WE HAVE 17 DAYS.

YOU WANT TO SEE IF

WE CAN TRIM THAT BACK?
THE COURT:

YEAH.

I JUST WANT TO KNOW, IS THERE A

NEW ESTIMATE NOW THAT THERE ARE THREE FEWER DEFENDANTS?

20

MR. SAVERI:

21

THE COURT:

OH, OKAY.
OKAY.

WHY DON'T -- WE'LL KEEP EVERYTHING

22

AS IS, BUT IF YOU WOULD PLEASE MEET AND CONFER AND MAKE SOME

23

PROPOSALS.

24

MR. VAN NEST:

25

THE COURT:

WE'LL DO THAT.

OKAY.

LET ME GIVE THE LAST, REALLY, TWO

UNITED STATES COURT REPORTERS

156

157

1

MINUTES, BECAUSE POOR MS. SHORTRIDGE IS PROBABLY GOING TO LOSE

2

HER ARMS IN A MINUTE, JUST THE LAST TWO MINUTES OF YOUR

3

STRONGEST WHATEVER YOU WANT TO SAY ON IMPACT OR WHY THIS SHOULD

4

BE CERTIFIED OR --

5
6
7

MR. GLACKIN:

WELL, THERE'S ONE, ONE POINT I WANTED

TO MAKE.
MR. VAN NEST SAID THAT DR. LEAMER ADMITTED NOTHING HE DOES

8

CAN SHOW CAUSALITY AND HE CITED TO 525 OF THE DEPOSITION OF

9

DR. LEAMER.

10

I WENT IMMEDIATELY TO THE EXCERPTS THAT WE HAVE THAT WERE

11

SUBMITTED BY THE DEFENDANTS.

12

CAN'T CONFIRM THAT HE DID SAY THAT.

13

BUT I WAS AT HIS DEPOSITION.

14
15

I DIDN'T SEE THAT PAGE, SO I

I DON'T REMEMBER HIM EVER

SAYING THAT.
AND HE EXPRESSLY SAYS IN HIS FINAL REPORT THAT THE KIND OF

16

REGRESSION ANALYSIS HE'S DONE, WHICH INCLUDES TEMPORAL ORDERING

17

AND ALSO INCLUDES ACCOUNTING FOR THE EXTERNAL FACTORS THAT THE

18

DEFENDANTS HAVE CLAIMED ARE IMPORTANT, CAN SUPPORT AN INFERENCE

19

OF CAUSALITY.

20

SO, YOU KNOW, WE HAVE -- I'M ONLY GOING TO -- YOU'VE HEARD

21

A LOT OF ARGUMENT TODAY.

22

I'M NOT GOING TO WALK THROUGH IT ALL

AGAIN.

23

ALL I WILL SAY IS THAT, YOU KNOW, WE SORT OF UNDERSTOOD

24

THERE TO BE A SPECIFIC ISSUE, A DEFICIENCY THAT HAD BEEN RAISED

25

WITH RESPECT TO THE EVIDENCE THAT WE HAD SUBMITTED.

UNITED STATES COURT REPORTERS

WE HADN'T

157

158

1

SHOWN MOVEMENT OVER TIME, WE HADN'T EXPANDED THE ANALYSIS TO

2

THE ENTIRE STRUCTURE, AND WE HADN'T ACCOUNTED FOR EXTERNAL

3

FACTORS.

4

WE'VE NOW DONE ALL THREE OF THOSE THINGS.

WE HAVE

5

COMPLETED ALL THE INFERENTIAL LINKS THAT THE DEFENDANTS

6

COMPLAINED ABOUT LAST TIME, AND THAT'S WHY, INSTEAD OF SAYING

7

WE HAVEN'T, THEY'RE JUST FOCUSSING BACK ON THIS QUESTION OF

8

INDIVIDUAL VARIATION AND SAYING THAT IT MATTERS.

9

BUT IN THE TEXT OF HIS DEPOSITION THAT WE BLOCK QUOTED IN

10

OUR REPLY BRIEF, DR. MURPHY ADMITS THAT IT DOESN'T MATTER, THAT

11

WIDE VARIATION IN INDIVIDUAL PAY IS NOT INCONSISTENT WITH A JOB

12

TITLE STRUCTURE HELD TOGETHER BY INTERNAL EQUITY.

13

AND SO WHAT THAT TELLS YOU IS WE HAVE -- WE HAVE NOT JUST

14

GIVEN THE COURT A PLAUSIBLE METHODOLOGY.

15

GIVEN THE COURT, I THINK, SIGNIFICANT PROOF OF ANTITRUST

16

IMPACT, FAR MORE SIGNIFICANT PROOF THAN I HAVE SEEN IN AN

17

ANTITRUST CLASS CASE.

18
19

AT THIS POINT WE HAVE

SO I RESPECTFULLY SUBMIT WE'VE MORE THAN CLEARED THE HURDLE
ON THAT ONE.

20

MR. VAN NEST:

SO, YOUR HONOR, I'LL STICK WITH THE

21

KEY POINTS IN THE TABS I HANDED UP.

22

STORY.

23

I THINK THEY TELL THE

AND LET ME TELL IT JUST FROM THE VERY HIGHEST POINT.

THERE

24

ARE THREE REASONS WHY THEY FAIL THE TEST THAT COMCAST SETS OUT.

25

COMCAST SAYS RIGOROUS ANALYSIS, YOU'VE GOT TO PROVE CLASS-WIDE

UNITED STATES COURT REPORTERS

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159

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INJURY, WHICH YOU'VE INTERPRETED, I THINK CORRECTLY SO, AS ALL

2

OR NEARLY ALL PEOPLE.

3

ONE.

LEAMER AVERAGED AND THE CASE LAW UNIFORMLY REJECTS

4

THAT.

5

UNIFORMLY REJECTED THAT AVERAGING CAN ALLOW YOU TO SHOW

6

CLASS-WIDE IMPACT.

7

GPU REJECTED IT, REED REJECTED IT, AND IT'S BEEN

IT CAN'T, BECAUSE THE WAY THE AVERAGE MOVES DOESN'T TELL

8

YOU ANYTHING ABOUT HOW MANY PEOPLE WERE IMPACTED.

9

ONE.

10

POINT TWO.

THAT'S POINT

THE RAW DATA THAT WE LOOKED AT IN TABS 4, 5, 6,

11

AND 7 SHOWS TWO THINGS CLEARLY AS A BELL.

12

ENORMOUS VARIATION WITHIN EACH JOB TITLE BECAUSE THE BANDS ARE

13

BROAD, BECAUSE THERE IS SALARY, BONUS AND EQUITY ALL IN PLAY,

14

AND FOR ALL THESE TITLES, AND MURPHY LOOKED AT EVERY ONE, THERE

15

IS A WIDE RANGE OF VARIATION WITHIN THE TITLE.

16

ONE, THERE IS

AND POINT TWO, THERE IS NO SHOWING THAT MOVING ONE TITLE

17

CAUSES ANY OTHER TITLE TO MOVE.

18

AND MURPHY 8.

19

TITLES.

20

THAT'S THE POINT OF MURPHY 7

THERE IS ENORMOUS VARIATION BETWEEN AND AMONG

AND THE THIRD POINT IS THEY SIMPLY HAVEN'T SHOWN THIS

21

RIPPLE EFFECT OR HOW THE HECK IT WOULD WORK.

22

WHAT DO YOU HAVE TO SHOW CAUSATION?

23

IS YOUR THEORY OF PROPAGATION?

24
25

WE KEEP ASKING,

WHAT DO YOU HAVE -- WHAT

THEY DON'T REALLY HAVE A THEORY OF PROPAGATION BECAUSE
THERE'S NO EVIDENCE OF IT, THERE'S NO ANECDOTES OF IT EITHER

UNITED STATES COURT REPORTERS

159

160

1

BEFORE, DURING, OR AFTER THE CLASS PERIOD.

2

THIS RIPPLE THEORY IS A MADE UP THEORY THAT THE EVIDENCE

3

WILL NOT SUPPORT, AND WITHOUT THAT, WITHOUT THAT, THEY CAN'T

4

SHOW CLASS-WIDE INJURY.

5

MY FINAL POINT, YOUR HONOR, IS JUST APPENDIX B.

6

TITLES, 60,000 CLASS MEMBERS.

7

AMONG ALL THE CLASSES IN THE UNITED STATES.

8

2400

AN ENORMOUS CLASS FOR ANY WAGE SUPPRESSION CASE.

9

IT'S NOT THAT THAT'S A BIG CLASS
IT'S THAT THAT'S

REED SAID 19,000, TOO MANY.

10

FLEISHMAN, EVEN LESS THAN THAT, TOO MANY.

11

WEISFELDT, LESS THAN THAT, TOO MANY.

12

AND THE REASON IS THAT WHEN YOU HAVE THIS MUCH DISPARITY

13

AND DIFFERENCE BETWEEN AND AMONG THESE TYPES OF JOBS, THERE IS

14

NO WAY TO SHOW THAT IMPACT ON SOME OF THEM WOULD HAVE IMPACTED

15

ALL OR NEARLY EVERYONE, ESPECIALLY WHEN THEY'RE SWINGING FOR

16

THE FENCE WITH A 2400 TITLE PROPOSED CLASS.

17

IT IS UNWORKABLE.

IT IS UNPRECEDENTED.

THEY CAN'T POINT

18

TO A SINGLE CASE WHERE ANYTHING EVEN APPROACHING THIS WAS

19

CERTIFIED, NOT ONE.

20
21
22

THEY HAVEN'T CITED ONE.

THERE ISN'T ONE BECAUSE THE CASES THAT ARE ANYWHERE NEAR
THIS ARE ALL CASES DENYING CLASS CERT.
AND THAT'S WHY WE EMPHASIZE REED, WEISFELDT, FLEISHMAN AND

23

THE LIKE.

24

DOESN'T TELL YOU ANYTHING, AND YOU CAN'T RUN A CLASS ACTION IN

25

THIS WAY.

THEY ALL RECOGNIZE WHAT WE RECOGNIZE, THAT AVERAGING

UNITED STATES COURT REPORTERS

160

161

1
2
3

LET'S SAY NO AND GET ON TO A MORE REASONABLE WAY OF DOING
THIS AND FIGURE OUT A BETTER WAY TO RESOLVE THESE CLAIMS.
THANKS FOR YOUR ATTENTION, YOUR HONOR.

4
5

THE COURT:
MUCH.

ALL RIGHT.

I REALLY APPRECIATE IT.

6

MR. GLACKIN:

7

MR. VAN NEST:

8

WELL, THANK YOU ALL VERY
THANKS FOR YOUR PATIENCE TODAY.

THANK YOU, YOUR HONOR.
THANK YOU, YOUR HONOR.

(THE PROCEEDINGS IN THIS MATTER WERE CONCLUDED.)

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UNITED STATES COURT REPORTERS

161

1
2
CERTIFICATE OF REPORTER

3
4
5
6
7

I, THE UNDERSIGNED OFFICIAL COURT REPORTER OF THE UNITED

8

STATES DISTRICT COURT FOR THE NORTHERN DISTRICT OF CALIFORNIA,

9

280 SOUTH FIRST STREET, SAN JOSE, CALIFORNIA, DO HEREBY

10
11

CERTIFY:
THAT THE FOREGOING TRANSCRIPT, CERTIFICATE INCLUSIVE, IS

12

A CORRECT TRANSCRIPT FROM THE RECORD OF PROCEEDINGS IN THE

13

ABOVE-ENTITLED MATTER.

14
15

17

_______________________________
LEE-ANNE SHORTRIDGE, CSR, CRR
CERTIFICATE NUMBER 9595

18

DATED:

16

AUGUST 19, 2013

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25

UNITED STATES COURT REPORTERS

162

1

1

UNITED STATES DISTRICT COURT

2

NORTHERN DISTRICT OF CALIFORNIA

3

SAN JOSE DIVISION

4
5
6

IN RE: HIGH-TECH EMPLOYEE
ANTITRUST LITIGATION,

7
8

_________________________

9

THIS DOCUMENT RELATES TO:
ALL ACTIONS
_________________________

10

)
)
)
)
)
)
)
)
)
)

C-11-02509 LHK
SAN JOSE, CALIFORNIA
JANUARY 17, 2013
PAGES 1-153

11
12
13

TRANSCRIPT OF PROCEEDINGS
BEFORE THE HONORABLE LUCY H. KOH
UNITED STATES DISTRICT JUDGE

14
15

A P P E A R A N C E S:

16

FOR THE PLAINTIFFS:

17
18

JOSEPH SAVERI LAW FIRM
BY: JOSEPH SAVERI
LISA J. LEEBOVE
JAMES G. DALLAL
255 CALIFORNIA STREET, SUITE 450
SAN FRANCISCO, CALIFORNIA 94111

19
20
21
22
23
24
25

LIEFF, CABRASER,
HEIMANN & BERNSTEIN
BY:
KELLY M. DERMODY
BRENDAN P. GLACKIN
DEAN M. HARVEY
ANNE B. SHAVER
275 BATTERY STREET, 30TH FLOOR
SAN FRANCISCO, CALIFORNIA 94111
APPEARANCES CONTINUED ON NEXT PAGE
OFFICIAL COURT REPORTER:

LEE-ANNE SHORTRIDGE, CSR, CRR
CERTIFICATE NUMBER 9595

UNITED STATES COURT REPORTERS

163

2

1
2

APPEARANCES (CONTINUED)

3
4

FOR DEFENDANT
APPLE:

5
6
7
8

FOR DEFENDANT
LUCASFILM:

9

O'MELVENY & MYERS
BY: GEORGE A. RILEY
MICHAEL F. TUBACH
CHRISTINA J. BROWN
TWO EMBARCADERO CENTER
28TH FLOOR
SAN FRANCISCO, CALIFORNIA

94111

KEKER & VAN NEST
BY: DANIEL PURCELL
633 BATTERY STREET
SAN FRANCISCO, CALIFORNIA

94111

10
11

FOR DEFENDANT
GOOGLE:

MAYER BROWN
BY: LEE H. RUBIN
DONALD M. FALK
ANNE SELIN
TWO PALO ALTO SQUARE, SUITE 300
PALO ALTO, CALIFORNIA 94306

FOR DEFENDANTS
ADOBE AND INTUIT:

JONES DAY
BY: ROBERT A. MITTELSTAEDT
CRAIG E. STEWART
DAVID C. KIERNAN
LYNN WONG
555 CALIFORNIA STREET
26TH FLOOR
SAN FRANCISCO, CALIFORNIA 94104

FOR DEFENDANT
INTEL:

BINGHAM MCCUTCHEN
BY: FRANK M. HINMAN
DONN P. PICKETT
SUJAL SAHW
1117 S. CALIFORNIA AVENUE
PALO ALTO, CALIFORNIA 94304

FOR DEFENDANT
PIXAR:

COVINGTON & BURLING
BY: EMILY J. HENN
DEBORAH A. GARZA
333 TWIN DOLPHIN DRIVE, SUITE 700
REDWOOD SHORES, CALIFORNIA 94065

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13
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UNITED STATES COURT REPORTERS

164

3

1

SAN JOSE, CALIFORNIA

2
3

JANUARY 17, 2013
P R O C E E D I N G S

(COURT CONVENED AND THE FOLLOWING PROCEEDINGS WERE HELD:)

4

THE COURT:

GOOD AFTERNOON AND WELCOME.

5

THE CLERK:

YOU MAY BE SEATED.

6

CALLING CASE NUMBER C-11-02509 LHK, IN RE: HIGH-TECH

7

EMPLOYEE ANTITRUST LITIGATION.

8

THE COURT:

9
10

WOULD YOU LIKE TO STATE YOUR

APPEARANCES?
MR. GLACKIN:

BRENDAN GLACKIN, LEIFF, CABRASER,

11

HEIMANN & BERNSTEIN.

12

MR. HARVEY, AND MS. SHAVER.

13
14
15

I'M WITH MY COLLEAGUES MS. DERMODY,

ALSO JOINING US IN THE COURTROOM IS PLAINTIFF
MICHAEL DIVINE SEATED IN THE FRONT ROW.
MR. SAVERI:

GOOD AFTERNOON, JUDGE KOH.

16

JOSEPH SAVERI, JOSEPH SAVERI LAW FIRM IN SAN FRANCISCO, AND

17

JAMES DALLAL AND LISA LEELOVE.

18

THE COURT:

19

MR. MITTELSTAEDT:

OKAY.

GOOD AFTERNOON.
AND YOUR HONOR, FOR DEFENDANTS,

20

BOB MITTELSTAEDT OF JONES DAY FOR ADOBE AND INTUIT, AND WITH ME

21

ARE LYNN WONG, DAVID KIERNAN, AND CRAIG STEWART.

22

THE COURT:

SO NOT EVERYONE IS ON THIS LIST.

23

THE CLERK:

I WAS TOLD THEY WERE.

24

THE COURT:

YOU SAID LYNN WONG AND GREG STEWART?

25

OKAY.

OR

CRAIG STEWART?

UNITED STATES COURT REPORTERS

165

4

1

MR. MITTELSTAEDT:

2

THE COURT:

3

MR. PURCELL:

4

CRAIG STEWART.

CRAIG STEWART.

OKAY, THANK YOU.

GOOD AFTERNOON, YOUR HONOR.

DAN PURCELL OF KEKER & VAN NEST FOR LUCASFILM.

5

THE COURT:

OKAY.

GOOD AFTERNOON.

6

MR. PICKETT:

7

DONN PICKETT OF BINGHAM MCCUTCHEN.

8

INTEL, ALONG WITH FRANK HINMAN AND SUJAL SHAW.

GOOD AFTERNOON, YOUR HONOR.

I'M

I'M HERE ON BEHALF OF

9

THE COURT:

OKAY.

GOOD AFTERNOON.

10

MR. RUBIN:

GOOD AFTERNOON, YOUR HONOR.

LEE RUBIN

11

FROM MAYER BROWN.

WITH ME TODAY IS MY PARTNER, DON FALK FROM

12

MAYER BROWN, AND ANNE SELIN, AND ANNE SELIN IS PROBABLY NOT ON

13

THE LIST.

14

THE COURT:

OKAY.

AND THE LAST NAME IS SPELLED?

15

MR. RUBIN:

SELIN, S-E-L-I-N.

16

THE COURT:

S-E-L-I-N.

17

MR. RUBIN:

THANK YOU.

18

MS. HENN:

OKAY, THANK YOU.

GOOD AFTERNOON, YOUR HONOR.

EMILY HENN,

19

AND MY COLLEAGUE DEBORAH GARZA, OF COVINGTON & BURLING ON

20

BEHALF OF PIXAR.

21

THE COURT:

OKAY.

GOOD AFTERNOON.

22

MR. RILEY:

GOOD AFTERNOON, YOUR HONOR.

23

GEORGE RILEY OF O'MELVENY & MYERS.

24

MICHAEL TUBACH, AND MY OTHER COLLEAGUE, CHRISTINA BROWN.

25

THE COURT:

OKAY.

I'M JOINED BY MY COLLEAGUE,

GOOD AFTERNOON.

UNITED STATES COURT REPORTERS

SO HAS EVERYONE

166

5

1

STATED THEIR APPEARANCES?

2

OKAY.

3

THE CMC SECOND.

4
5
6

OKAY.

ALL RIGHT.

THANK YOU.

LET'S HANDLE THE CLASS CERT MOTION FIRST AND THEN
AND WHY DON'T WE START WITH THE PLAINTIFFS?

WELL, ACTUALLY, I'M SORRY, LET MET START WITH THE
DEFENDANTS FIRST.
I JUST WANT TO NARROW THE SCOPE OF WHAT'S AT ISSUE TODAY.

7

I DIDN'T SEE IN YOUR OPPOSITION REALLY ANYTHING CHALLENGING

8

OTHER THAN -- ANY CLASS CERTIFICATION REQUIREMENT OTHER THAN

9

PREDOMINANCE.

IS THAT CORRECT?

10

MR. MITTELSTAEDT:

PREDOMINANCE AND SUPERIORITY.

11

THE COURT:

SO ARE YOU CONCEDING NUMEROSITY

OKAY.

12

AND ALL THE OTHER RULE 23 REQUIREMENTS?

13

MR. MITTELSTAEDT:

FOR PURPOSES OF THIS MOTION, YES.

14

THE COURT:

SO IT'S ONLY PREDOMINANCE AND

15

SUPERIORITY.

16

HAVE TO COVER.

17

OKAY.

18

OKAY.

OKAY.

THANK YOU.

THAT HELPS US NARROW WHAT WE

LET ME GO, PLEASE, TO THE PLAINTIFFS, AND I FIRST

JUST WANT TO MAKE SURE THAT I UNDERSTAND WHAT YOUR THEORY IS.

19

MR. GLACKIN:

20

THE COURT:

OKAY.

SO IF YOU COULD, PLEASE, THERE ARE

21

CERTAIN FIGURES THAT I'D LIKE YOU TO PLEASE EXPLAIN OR

22

ELABORATE IN DR. LEAMER'S REPORT IN SUPPORT OF THE MOTION.

23

MR. GLACKIN:

24

THE COURT:

25

SURE.

SO LET ME SEE IF I UNDERSTAND THE

INTERNAL EQUITY THEORY THAT YOU ARE ALLEGING.

UNITED STATES COURT REPORTERS

167

6

1

IS IT YOUR ASSERTION THAT ALL OF THE COMPENSATIONS FOR ALL

2

OF THE WORKERS ARE SOMEHOW LINKED, SO IF THERE'S ANY CHANGE IN

3

ONE, IT SHOULD HAVE SOME TYPE OF TRICKLE DOWN OR SOME SHADOWING

4

EFFECT ON THE OTHER EMPLOYEES OF THE SAME COMPANY?

5

RIGHT?

6
7
8

MR. GLACKIN:

IS THAT

YEAH, I WOULD SAY THAT'S BASICALLY

CORRECT, YOUR HONOR.
WE -- DR. LEAMER, TO BEGIN SPEAKING ABOUT THEORY, HE

9

PROPOSES THAT IF THE -- THAT GIVEN THE RECOGNIZED THEORY OF

10

INTERNAL EQUITY, THAT GAINS TO PART OF A WORK FORCE WILL BE

11

SHARED WITH OTHER MEMBERS OF THE SAME WORK FORCE.

12

WOULD PUT IT.

13

THAT'S HOW I

IT'S A SHARING OF GAINS.

SO IT'S NOT -- YOU KNOW, ANOTHER KIND OF SHARING, OR OF

14

LINKING THAT YOU COULD TALK ABOUT IN AN ECONOMICS MATTER WOULD

15

BE, FOR EXAMPLE, A SUPPLY AND DEMAND SIDE SUBSTITUTION.

16

COULD SAY, FOR EXAMPLE, THE PRICE OF A AND THE PRICE OF B ARE

17

LINKED BECAUSE IF YOU MODIFY THE PRICE OF A, OR THE SUPPLY OF

18

A, SUPPLY AND DEMAND SIDE SUBSTITUTION FORCES ARE GOING TO DO

19

SOMETHING TO THE PRICE OF B AS A MATTER OF SUPPLY AND DEMAND.

20

THE COURT:

21

MR. GLACKIN:

YOU

SO LET ME ASK YOU -THAT'S ONE KIND OF LINK.

22

DIFFERENT KIND OF LINKING.

23

THAT'S A

LINKING.

24
25

THE COURT:

THAT'S WHAT I THINK OF MORE AS

AND I'M SORRY TO INTERRUPT YOU.

I CAN

UNDERSTAND THE SHARING OF GAINS IN TERMS OF EXAMPLES THAT ARE

UNITED STATES COURT REPORTERS

168

7

1

BRIEFED, LIKE A PIXAR MOVIE DOES VERY WELL SO EVERYONE GETS,

2

ACROSS THE BOARD, RECEPTION TO PRESIDENTS GET A SORT OF BONUS

3

IN THAT YEAR.

4

BUT THIS IS A SHARING OF PAIN AND NOT A SHARING OF GAIN.

5

SO WHAT SAYS THAT IF THERE'S A SUPPRESSION OF GAIN IN ONE SORT

6

OF JOB FIELD THAT THAT WOULD NECESSARILY RESULT -- AND I GUESS

7

I'M HAVING A DIFFICULTY VISUALIZING WHY THE CATEGORY OF SOU

8

CHEFS' SALARIES WOULD NECESSARILY IMPACT THE CATEGORY OF

9

ADMINISTRATIVE ASSISTANTS THAT WOULD NECESSARILY IMPACT THE

10
11

CATEGORY OF AN ANIMATOR VERSUS A SOFTWARE ENGINEER.
DO YOU SEE WHAT I'M SAYING?

WHY CAN'T THOSE BE ON

12

SEPARATE TRACKS?

13

ALREADY ORGANIZED BY FAMILIES ANYWAY.

14

TO ACTUALLY BE INTERLINKED?

15

GROUND?

16

I KNOW THAT YOU HAVE SOME DATA THAT THEY'RE

MR. GLACKIN:

WHY DO THE FAMILIES HAVE

CAN'T THEY ALL JUST BE ON SEPARATE

WELL, SO THE -- THE ANSWER I WOULD

17

GIVE TO THAT IS THAT, FIRST OF ALL, WE ARE NOT TALKING ABOUT A

18

SHARING -- WE'RE TALKING ABOUT A SHARING OF PAIN IN THE SENSE

19

OF A SHARING OF TALKING ABOUT DAMAGES, BUT WE ACTUALLY ARE

20

REALLY TALKING ABOUT A SHARING OF GAIN BECAUSE WE'RE TALKING

21

ABOUT WHAT WOULD HAVE HAPPENED IN THE WORLD THAT DOESN'T EXIST,

22

WHICH IS THE WORLD WHERE THESE AGREEMENTS WERE NEVER REACHED.

23

AND WE'RE SAYING THAT IN THAT WORLD, THERE WOULD HAVE BEEN

24

COMPETITIVE GAINS THAT WOULD HAVE, IN SOME RESPECTS, BEEN

25

FOCUSSED ON INDIVIDUALS OR GROUPS OF EMPLOYEES, BUT THAT THE

UNITED STATES COURT REPORTERS

169

8

1

EFFECT OF THOSE GAINS WOULD HAVE BEEN WIDELY FELT ACROSS THE

2

WORK FORCES.

3

AND THERE'S -- YOU KNOW, I HEAR WHAT YOU'RE SAYING ABOUT,

4

OH, IT SORT OF DOESN'T -- IT'S SURPRISING THAT THE -- THAT WE

5

WOULD INCLUDE THE SOU CHEF, FOR EXAMPLE.

6

EXPLANATION FOR THAT?

WHAT'S THE

7

AND I WOULD -- I GUESS I WOULD SAY THAT THE INTERNAL

8

EQUITY FRAMEWORK POSTULATES THAT THIS FEELING OF FAIRNESS WHICH

9

DRIVES A COMPANY'S NEED TO SHARE GAINS LIKE THIS CAN APPLY

10

COMPANY-WIDE.

11

APPLY WITH DIFFERENT STRENGTHS, CERTAINLY IN DIFFERENT

12

CONTEXTS.

13
14

IT CAN APPLY IN MANY DIFFERENT WAYS AND IT CAN

BUT THERE IS A COMPANY-WIDE SENSE OF FAIRNESS THAT SAYS
THAT, UNDER CERTAIN CIRCUMSTANCES, THE GAINS SHOULD BE SHARED.

15

AND PRACTICALLY SPEAKING, AND THIS IS ACTUALLY DISCUSSED,

16

I BELIEVE, IN THE AKER -- I BELIEVE WE CITED GEORGE AKERLOF'S

17

ARTICLE, THE FAIR WAGE HYPOTHESIS.

18

THE THINGS THAT HE STUDIES THERE, OR DISCUSSES, IS RESEARCH ON

19

SHARING OF GAINS BETWEEN EMPLOYEES WITH VASTLY DIFFERENT SKILL

20

SETS.

HE SAYS -- I MEAN, ONE OF

SO THAT'S THE -- THAT'S THE THEORY.

21

AND THEN THE FACT OF HOW COMPENSATION WAS SET AT THESE

22

COMPANIES ALSO IS CONSISTENT AND IN LINE WITH THE PREDICTION

23

THAT AT LEAST SOME LEVEL OF THESE GAINS WOULD BE SHARED

24

COMPANY-WIDE, AND THAT FACT IS THAT THEY ALL USE ADMINISTRATIVE

25

PAY SYSTEMS, THEY SET COMPANY-WIDE COMPENSATION BUDGETS, THEY

UNITED STATES COURT REPORTERS

170

9

1

SET COMPANY-WIDE RAISE BUDGETS.

2

THAT THEY MAKE IN THEIR DECLARATIONS AND IN THEIR PAPERS.

3

THIS IS ACTUALLY AN ARGUMENT

AND THERE'S -- IT'S -- IF THE COMPANY COMPENSATION BUDGET

4

GOES UP BECAUSE MANAGERS ARE COMPLAINING THAT THEY NEED MORE

5

MONEY TO SATISFY THEIR EMPLOYEES OR BECAUSE THE CEO IS

6

CONCERNED ABOUT COMPETITION HE'S FACING FROM ONE OF THESE OTHER

7

COMPANIES WITH WHICH, IN THE REAL WORLD, HE HAD AN AGREEMENT SO

8

HE WASN'T CONCERNED ABOUT THAT, THAT COULD MOVE THE WHOLE PAY

9

STRUCTURE.

IT COULD MOVE SALARY BANDS.

IT COULD INFLUENCE

10

COMPANIES' DECISIONS ABOUT WHERE TO SET MINIMUM AND MAXIMUM

11

SALARIES FOR JOB TITLES.

12

DECISIONS ABOUT --

13

THE COURT:

IT WOULD INFLUENCE COMPANIES'

AND I'M SORRY TO INTERRUPT YOU.

I CAN

14

UNDERSTAND HOW WITHIN THE SAME JOB FAMILY CO-WORKERS MIGHT TALK

15

AND FIND OUT, "WHAT ARE YOU MAKING?

16

WHAT OFFER DID YOU GET?"

BUT WHAT IS THE EVIDENCE THAT THE SOU CHEF IS TALKING TO

17

THE ANIMATOR IS TALKING TO SOME OTHER, YOU KNOW, CO-WORKER FROM

18

A COMPLETELY DIFFERENT JOB FAMILY AND THAT THERE'S SORT OF THIS

19

EQUITY CONCERN --

20

MR. GLACKIN:

21

THE COURT:

22

MR. GLACKIN:

UM-HUM.

-- ACROSS JOB FAMILIES?
SO I DON'T THINK THERE'S EVIDENCE -- I

23

MEAN, TO ANSWER YOUR QUESTION DIRECTLY, I DON'T THINK THERE'S

24

EVIDENCE THAT THE SOU CHEF IS TALKING TO THE CEO'S A.A., FOR

25

EXAMPLE.

UNITED STATES COURT REPORTERS

171

10

1

THE COURT:

UM-HUM.

2

MR. GLACKIN:

I THINK THAT WHAT WE'VE -- WHAT WE'VE

3

POSTULATED AND WE WOULD SAY WHAT WE'VE DEMONSTRATED IS THAT

4

THIS INFORMATION -- THERE'S AN INFORMATION NETWORK THAT

5

CONNECTS THESE EMPLOYEES.

6

RECEIVES THE INFORMATION TO TALK TO PEOPLE IN OTHER JOB

7

FAMILIES.

8
9

IT DOESN'T REQUIRE THE EMPLOYEE WHO

THE INFORMATION COMES INTO THE NETWORK AND IT IS -- IT IS
SPREAD AND THE FORCE OF -- AND THE FORCE OF INTERNAL EQUITY

10

CAUSES THE COMPETITIVE EFFECT TO BE SHARED TO SOME LEVEL ACROSS

11

THE ENTIRE WORK FORCE, OR IT CAN.

12

AND A CONCRETE EXAMPLE OF THIS IS THE GOOGLE PAY RAISE IN

13

RESPONSE TO AGGRESSIVE RECRUITING BY FACEBOOK.

14

WAS A -- THAT WAS -- THAT'S AN EXAMPLE OF AGGRESSIVE RECRUITING

15

BY A SINGLE COMPANY THAT MOVED AN ENTIRE PAY STRUCTURE BY 10

16

PERCENT FROM SOU CHEFS TO SECRETARIES.

17

I MEAN, THAT

SO THIS IS NOT -- I MEAN, WE BELIEVE THAT -- I MEAN, THIS

18

IS SOUND ECONOMIC THEORY AND I DON'T THINK THERE'S A DISPUTE

19

ABOUT THAT AT THIS POINT.

20

THERE'S ALSO NOT REALLY A DISPUTE THAT THESE DEFENDANTS

21

USE ADMINISTRATIVE PAY STRUCTURES AND THAT THEY SET THEIR

22

COMPENSATION THE WAY EVERY OTHER MAJOR COMPANY IN THE WORLD

23

SETS IT.

24
25

AND THEN WE ALSO HAVE DOCUMENTARY EVIDENCE THAT
DIRECTLY -- AND THERE'S A FEW INSTANCES OF THIS THAT WE CITED

UNITED STATES COURT REPORTERS

172

11

1

IN THE BRIEF -- THAT DIRECTLY LINKS COMPETITION, AGGRESSIVE

2

COMPETITION BY A SINGLE FIRM TO EITHER CONCERN ABOUT THE PAY

3

STRUCTURE MOVING IN THE CASE OF SOME OF THE PIXAR E-MAILS WE'VE

4

CITED, OR TO AN ACTUAL ENORMOUS, $500 MILLION MOVEMENT OF THE

5

PAY STRUCTURE, WHICH IS WHAT GOOGLE DID.

6

THE COURT:

LET ME ASK YOU, SINCE WE'RE

7

UNFORTUNATELY LIMITED IN TERMS OF DOCUMENTARY EVIDENCE, WHAT

8

EVIDENCE IS THERE ABOUT WHAT TYPE OF EMPLOYEES OR WHAT TYPE OF

9

JOB FAMILIES RECEIVE COLD CALLS GENERALLY?

10

MR. GLACKIN:

WELL, THAT IS AN EXCELLENT QUESTION,

11

AND AS -- I MEAN, DR. LEAMER SAID, I WOULD COUNT NO FEWER THAN

12

20 TIMES IN HIS DEPOSITION, THAT HE WOULD HAVE LOVED TO HAVE

13

HAD RELIABLE DATA ABOUT THE COLD CALLING, AND THE PROBLEM IS IT

14

JUST DIDN'T EXIST.

15

HAVE.

16
17
18

I MEAN, WE CAN ONLY WORK WITH THE DATA WE

I'M ALMOST TEMPTED TO QUOTE DEFENSE SECRETARY ROSENFELD,
YOU GO TO WAR WITH THE DATA THAT YOU HAVE.
AND THE DEFENDANTS DON'T DISPUTE THAT.

THERE'S NO

19

ANALYSIS OF THE COLD CALLING DATA BY DR. MURPHY EITHER.

20

WHY HE'S, WE WOULD SAY WRONGLY, BUT HE'S USING THIS PROXY

21

APPROACH BASED ON INTER-DEFENDANT HIRING, WHICH IS EVIDENCE

22

THAT WE DEVELOPED USING UNIQUE EMPLOYEE IDENTIFIERS.

23

THAT'S

BUT THERE'S NO -- THERE IS NO EVIDENCE IN THIS CASE ABOUT

24

HOW THAT COLD CALLING -- THERE'S NO RELIABLE EVIDENCE, I SHOULD

25

SAY, NO RELIABLE STATISTICAL EVIDENCE ABOUT HOW THAT COLD

UNITED STATES COURT REPORTERS

173

12

1
2

CALLING WAS CONCENTRATED, IF AT ALL, TO DIFFERENT EMPLOYEES.
I MEAN, I WILL SAY, YOU MENTIONED SOU CHEF.

THERE IS A

3

DOCUMENT IN THIS CASE THAT, YOU KNOW, DISCUSSES BEING CONCERNED

4

ABOUT LOSING A SOU CHEF.

5

THE COURT:

YEAH.

6

MR. GLACKIN:

SO DEFINITELY THERE'S NO DOUBT THAT

7

SOU CHEFS WERE WITHIN THE SCOPE OF THESE AGREEMENTS, SO I JUST

8

WANTED TO MENTION THAT IN CASE IT HAD SLIPPED YOUR MIND.

9
10
11

THE COURT:

NO.

THAT'S WHAT PROMPTED THE QUESTION

ACTUALLY.
SO LET ME ASK, I COMPLETELY AGREE WITH YOU THAT THE

12

AGREEMENTS ARE EXPLICITLY NOT RESTRICTED BY JOB FAMILY,

13

GEOGRAPHY, THEY'RE NOT LIMITED BY ANYTHING.

14

EMPLOYEE CANNOT BE COLD CALLED, COUNTER-OFFERED, OR HIRED

15

WITHOUT GETTING CONSENT OF THE CURRENT EMPLOYER.

16

THEY APPLY TO ANY

BUT DOESN'T IT SEEM THAT, OVERALL, THE PRIMARY CONCERN OF

17

THESE CEO'S WAS THE TOP TALENT, AND SPECIFICALLY THE TOP

18

TECHNICAL TALENT?

19

LIKE THEY WERE OKAY ABOUT THE ADMINISTRATIVE ASSISTANT

20

FROM PIXAR.

21

REALLY DON'T WANT THE TOP TECHNICAL TALENT LEAVING.

22

THEY'RE OKAY REALLY ABOUT THE SOU CHEF.

MR. GLACKIN:

BUT THEY

I MEAN, I WOULD -- SO FIRST OF ALL, I

23

WOULD HASTEN TO ADD THAT WE HAVEN'T ACTUALLY DEPOSED ANY OF THE

24

CEO'S YET, SO THE DISCOVERY RECORD IS STILL OPEN ON WHAT THEY

25

THINK.

UNITED STATES COURT REPORTERS

174

13

1

I WOULD SAY THAT THERE IS CERTAINLY SOME EVIDENCE IN THE

2

RECORD, AND WE CITED IT I BELIEVE ON THE LAST PAGE, OR LAST TWO

3

PAGES OF OUR OPENING BRIEF, WHICH IS WHERE WE ALSO DISCUSSED --

4

WE EXPLAINED WHY WE PROPOSED A POSSIBLE ALTERNATIVE CLASS.

5

THERE IS SOME EVIDENCE OF THEM BEING CONCERNED ABOUT THAT;

6

THERE'S ALSO EVIDENCE OF THEM BEING CONCERNED ABOUT THE ENTIRE

7

PAY STRUCTURE; AND THEN THERE IS ALSO EVIDENCE OF THEM BEING

8

CONCERNED ABOUT THE SOU CHEF, I MEAN, FIGURATIVELY SPEAKING.

9
10
11
12
13
14
15

SO I WOULD AGREE THAT THERE IS SOME EVIDENCE OF THE KIND
THAT YOU DESCRIBE.
BUT I WOULD ALSO AGREE -- SAY THAT THERE'S EVIDENCE THAT
THEY WERE CONCERNED ABOUT OTHER THINGS.
THE COURT:

OKAY.

THANK YOU.

LET ME GO TO THE

DEFENDANTS.
WHY DIDN'T YOUR CLIENTS RESTRICT THESE AGREEMENTS TO

16

SPECIFIC TYPES OF EMPLOYEES?

AND THERE'S CERTAINLY DOCUMENTARY

17

EVIDENCE WHERE -- I CAN'T RECALL WHO THE COMPANY WAS -- BUT I

18

KNOW STEVE JOBS WAS INVOLVED WHERE THEY TRIED TO NARROW THE

19

CLASS OF EMPLOYEES WHO COULDN'T BE SOLICITED, OR I SHOULD SAY

20

CLASS EMPLOYEES, AND THE AGREEMENT WAS, NO, JUST ANY EMPLOYEE.

21

DON'T CONTACT THEM.

22

SO YOU TELL ME, WHY SHOULD THERE BE ANY FURTHER

23

RESTRICTION WHEN THE AGREEMENT IS PRETTY EXPLICIT THAT IT

24

APPLIES TO ANY EMPLOYEE, AND THERE'S CERTAINLY E-MAILS WITH

25

STEVE JOBS AND OTHER CEO'S NOT LIMITING IT TO ANY PARTICULAR

UNITED STATES COURT REPORTERS

175

14

1

TYPE OF EMPLOYEE.

2

MR. MITTELSTAEDT:

I THINK, YOUR HONOR, THE ISSUE IS

3

WHO WAS IMPACTED.

4

IMPACTED, WHO WOULD HAVE RECEIVED A RAISE, WHO WOULD HAVE GONE

5

TO ANOTHER JOB IF THEY HAD RECEIVED A CALL.

6

NOT JUST WHO DIDN'T GET A CALL, BUT WHO WAS

IN THE CASES THAT WE'VE CITED, REED, WEISFELD, MPT, AND

7

JOHNSON, THE AGREEMENTS THERE WERE BROAD RANGING.

SOME OF

8

THOSE CASES INVOLVED JUST NURSES, AND IN REED, FOR EXAMPLE, THE

9

COURT SAID THE QUESTION IS, IS THERE IMPACT ON THE NURSES

10

ACROSS THE BOARD AND DOES THE PLAINTIFF HAVE A METHOD OF

11

PROVING IMPACT ACROSS THE BOARD?

12

AND WHAT THE COURT FOUND IN REED, LIKE THE OTHER CASES, IS

13

THAT IF THE PLAINTIFFS HAVE TO GO PERSON BY PERSON, DEPARTMENT

14

BY DEPARTMENT, COMPANY BY COMPANY, TO DETERMINE WHO WAS

15

IMPACTED, NOT JUST WHO WAS WITHIN THE SCOPE OF WHETHER IT'S A

16

NO HIRING --

17

THE COURT:

SO YOU CONCEDE THAT ALL EMPLOYEES WERE

18

IN THE SCOPE.

19

DEFINE THE CATEGORY OF EMPLOYEES THAT WERE ACTUALLY DAMAGED?

20

YOUR POSITION IS JUST THAT ONLY WHAT -- CAN YOU

MR. MITTELSTAEDT:

21

CERTAINLY.

22

IT'S NOT WHAT CATEGORIES.

23

I'M MAKING THE LATTER POINT,

AND IT'S, IN MY VIEW -- AND I'LL GET INTO THIS -IT'S INDIVIDUAL BY INDIVIDUAL.

BUT ON THE FIRST POINT, THESE AGREEMENTS, TO THE EXTENT

24

THEY WERE ACTUAL AGREEMENTS, DIFFERED FROM COMPANY TO COMPANY

25

TO COMPANY, BOTH AS TO THE TERMS AND WHO THEY COVERED, SO I

UNITED STATES COURT REPORTERS

176

15

1

CAN'T MAKE ANY BROAD GENERALIZATION ABOUT ALL OF THEM COVERED

2

EVERYBODY OR NONE OF THEM COVERED EVERYBODY.

3

TO BE TAKEN ONE BY ONE.

4

THEY REALLY NEED

BUT --

5

THE COURT:

SO TELL ME, WHAT ARE THE CHARACTERISTICS

6

OF THE INDIVIDUALS THAT THE DEFENDANTS WOULD CONCEDE WERE

7

DAMAGED?

8
9
10
11

MR. MITTELSTAEDT:

WELL, NONE OF THE NAMED

PLAINTIFFS FIT THIS CATEGORY.
BUT YOUR HONOR SAID, IN APRIL, AFTER READING THE
COMPLAINT, AFTER SEEING THE PLAINTIFFS' THEORY --

12

THE COURT:

I DON'T WANT TO HEAR WHAT I SAID.

I

13

WANT TO HEAR YOUR POSITION.

14

THE CHARACTERISTICS OF INDIVIDUALS THAT THE DEFENDANTS CONCEDE

15

WERE DAMAGED?

16

WHAT ARE -- HOW WOULD YOU DESCRIBE

I DON'T WANT TO HEAR WHAT I SAID.

MR. MITTELSTAEDT:

OKAY.

IT WOULD BE SOMEBODY WHO

17

WOULD HAVE RECEIVED A COLD CALL BUT FOR THE AGREEMENTS; WOULD

18

HAVE TAKEN THAT COLD CALL, TAKEN IT FAR ENOUGH DOWN THE ROAD TO

19

GET SOME SALARY INFORMATION; AND THEN WENT INTO HIS OR HER BOSS

20

AND SAID, "I'VE GOT AN OFFER FROM ANOTHER COMPANY AT A HIGHER

21

WAGE.

WILL YOU NEGOTIATE AND GIVE ME A RAISE?"

22

AND THEN IF THAT -- IF THE MANAGER SAYS, "NO, ACTUALLY, I

23

DON'T WANT TO GIVE YOU A RAISE," THEN THAT PERSON HAS TO DECIDE

24

WHETHER THEY WOULD TAKE THE JOB AT THE COMPETING COMPANY.

25

IF THAT PERSON COULD SHOW THAT THEY WOULD HAVE RECEIVED A

UNITED STATES COURT REPORTERS

177

16

1

CALL, IT WOULD HAVE LED TO A RAISE, THEN THEY COULD SAY THAT

2

THEY WERE DAMAGED BY AN AGREEMENT THAT KEPT THEM FROM GETTING

3

THE CALL.

4
5
6

THE COURT:

AND THE DEFENDANTS CONCEDE THAT THERE

ARE INDIVIDUALS LIKE THAT AT ALL OF YOUR CLIENTS' COMPANIES?
MR. MITTELSTAEDT:

7

BEEN IDENTIFIED.

8

WELL, I DON'T THINK ANYBODY HAS

THAT CATEGORY.

9
10
11

I KNOW THE NAMED PLAINTIFFS DON'T FIT INTO

MR. DIVINE, FOR EXAMPLE, HE HELD SOME -THE COURT:

AND I'VE READ ABOUT THE NAMED

PLAINTIFFS, SO LET'S NOT GO THERE.

12

MR. MITTELSTAEDT:

13

THE COURT:

OKAY.

LET ME ASK -- THERE IS NINTH CIRCUIT

14

CASE LAW THAT SAYS DAMAGE CALCULATIONS SHOULD NOT DEFEAT CLASS

15

CERTIFICATION, BUT IT SEEMS LIKE THAT'S THE CRUX OF YOUR

16

OPPOSITION IS THAT YOU'RE SAYING THAT THE PLAINTIFFS NEED TO

17

SHOW INDIVIDUALIZED INJURY AND THEY CAN'T DO THAT, AND THEY

18

CAN'T DO A DAMAGES CALCULATION, THEREFORE, THEY CAN'T GET A

19

CLASS CERTIFIED.

20
21
22

DO YOU WANT TO RESPOND TO THAT?

I'M THINKING OF YOKOYAMA.

GO AHEAD, PLEASE.
MR. MITTELSTAEDT:

TO STATE AN ANTITRUST TRUST CAUSE

23

OF ACTION, THE PLAINTIFF NEEDS TO SHOW THAT THERE WAS A

24

VIOLATION, AND THAT'S WHAT THEY USE THEIR AGREEMENT -- THE

25

AGREEMENTS FOR.

UNITED STATES COURT REPORTERS

178

17

1

THE COURT:

AND LET ME ASK YOU, DO YOU FIGHT -- DO

2

YOU CONTEST THAT PRONG OF THE ANALYSIS?

3

MR. MITTELSTAEDT:

4

NOT FOR PURPOSES OF THIS

MOTION --

5

THE COURT:

OKAY.

6

MR. MITTELSTAEDT:

-- EXCEPT TO SAY THIS, YOUR

7

HONOR:

8

THAT THE D.O.J. DID NOT ALLEGE, YOU KNOW, THAT LOOKS LIKE IT'S

9

A COMMON ISSUE.

10

WHEN THEY ALLEGE AN OVERARCHING AGREEMENT, SOMETHING

WHEN THEY GET INTO, YOU KNOW, AN AGREEMENT BY ADOBE WITH

11

APPLE, THAT IS A DIFFERENT ANALYSIS, A DIFFERENT INQUIRY AT

12

TRIAL, IF YOU WILL, THAN WHETHER THERE WAS AN AGREEMENT BETWEEN

13

PIXAR AND LUCASFILM.

14
15

AND SO, YOU KNOW, WHEN YOU LOOK AT JUST AN INDIVIDUAL -THE COURT:

BUT I DIDN'T SEE THAT IN YOUR

16

OPPOSITION.

I DIDN'T SEE YOU MAKING THAT ARGUMENT.

17

POINT ME TO -- I DIDN'T SEE YOU CHALLENGING THAT THERE WAS AN

18

ANTITRUST TRUST VIOLATION IN YOUR OPPOSITION.

19

MR. MITTELSTAEDT:

20

THE COURT:

21
22

CAN YOU

AND THAT --

IF YOU DID, CAN YOU POINT ME TO IT?

THAT'LL JUST HELP US WITH GETTING THE ORDER DRAFTED.
MR. MITTELSTAEDT:

NO.

AND, YOUR HONOR, THAT --

23

THAT'S BECAUSE THEY ARE ALLEGING THE OVERARCHING CONSPIRACY AND

24

YOUR HONOR LET THAT GO ON THE MOTION TO DISMISS.

25

THE COURT:

UM-HUM.

UNITED STATES COURT REPORTERS

179

18

1

MR. MITTELSTAEDT:

2

THE COURT:

BUT AFTER --

SO THAT'S NOT BEING CHALLENGED?

THE

3

FACT OF THE ANTITRUST VIOLATION IS NOT BEING CHALLENGED FOR

4

PURPOSES OF THIS CLASS CERT MOTION?

5

MR. MITTELSTAEDT:

WELL, THE -- THE WAY I WOULD

6

PHRASE IT IS, ARE WE CONTESTING THAT THAT'S AN INDIVIDUAL ISSUE

7

OR A COMMON ISSUE?

AND I'M -- I THINK THAT'S A COMMON ISSUE.

8

THE COURT:

OKAY.

9

MR. MITTELSTAEDT:

BUT THE SECOND ELEMENT OF AN

10

ANTITRUST LIABILITY CLAIM IS THAT THE PLAINTIFF SHOWS IMPACT ON

11

HIM OR HER OF THE VIOLATION, AND SO THAT'S BEFORE YOU GET TO

12

DAMAGES, THE AMOUNT OF DAMAGES.

13

THEY HAVE TO SHOW AN IMPACT.

AND IN REED, AGAIN -- AND REED -- YOU KNOW, IF THERE'S A

14

SINGLE CASE THAT'S THE MOST IMPORTANT HERE, YOUR HONOR, I THINK

15

IT IS THE REED CASE.

16

AND IN THE REED CASE, THE COURT IS QUOTING FROM THE THIRD

17

CIRCUIT IN HYDROGEN PEROXIDE, AND IT SAYS, "IN ANTITRUST CASES,

18

IMPACT OFTEN IS CRITICALLY IMPORTANT FOR PURPOSES OF EVALUATING

19

THE PREDOMINANCE REQUIREMENT BECAUSE IT'S AN ELEMENT OF THE

20

CLAIM THAT MAY CALL FOR INDIVIDUAL AS OPPOSED TO COMMON PROOF."

21

AND SO WHAT WE'RE SAYING IS THAT THE ONLY WAY FOR THE

22

PLAINTIFFS TO SHOW IMPACT, NAMELY, THAT SOMEBODY WAS INJURED IN

23

HIS OR HER PROPERTY OR BUSINESS -- AND THAT'S, THAT'S WHAT THEY

24

NEED TO SHOW UNDER AN ANTITRUST VIOLATION -- IN ORDER TO SHOW

25

THAT, THEY HAVE TO GO INDIVIDUAL BY INDIVIDUAL.

UNITED STATES COURT REPORTERS

180

19

1

THEY HAVE TO SHOW, YOU KNOW, WHO WOULD HAVE RECEIVED THE

2

COLD CALL, WHAT IT WOULD HAVE LED TO.

3

WOULD HAVE LED TO A PAY RAISE, EITHER AT THAT COMPANY OR AT

4

ANOTHER COMPANY.

5

AND THAT IS WHERE ALL THESE CASES HAVE SAID THAT'S AN

6

INDIVIDUAL QUESTION.

7

THE COURT:

8
9
10

THEY HAVE TO SHOW IT

WOULD THERE HAVE BEEN AN IMPACT?
I'M SORRY TO INTERRUPT YOU.

WHAT IS THE DEFENDANTS' POSITION AS TO WHAT TYPES OF
EMPLOYEES OR MAYBE JOB FAMILIES WOULD BE SUBJECT TO A COLD
CALL?

OR DO YOU HAVE A POSITION?

11

MR. MITTELSTAEDT:

WELL, NOT REALLY.

THAT'S WHAT I

12

SAID BEFORE, THAT ALL OF THE -- EACH OF THESE AGREEMENTS WAS

13

DIFFERENT.

14

THE COURT:

UM-HUM.

15

MR. MITTELSTAEDT:

EACH COMPANY WAS IN A DIFFERENT

16

POSITION.

17

EMPLOYEES.

18

SO I DON'T THINK IT CAN BE GENERALIZED.

19
20
21

SOME COMPANIES WERE LOOKING FOR A CERTAIN TYPE OF
OTHERS WERE LOOKING FOR OTHER TYPES OF EMPLOYEES.

BUT TO ME, YOUR HONOR, THE IMPORTANT POINT ISN'T THE SCOPE
OF THE AGREEMENTS.

IT'S WHO THEY CAN SHOW WAS IMPACTED.

AND, YOU KNOW, THEY HAVE -- AND WE DON'T THINK THEY HAVE

22

COME UP WITH A METHOD TO SHOW, BY COMMON EVIDENCE ACROSS THE

23

BOARD, WHO WAS INJURED.

24
25

AND SO IF I CAN BE PERMITTED TO JUST SAY ONE THING THAT
YOUR HONOR HAD SAID, BECAUSE IT'S -- I THINK IT GOES TO THE

UNITED STATES COURT REPORTERS

181

20

1

HEART OF THIS.

2

AT THE START OF THIS CASE, YOUR HONOR TURNED TO THE

3

PLAINTIFFS AND SAID, YOU KNOW, THE CLASS OF EVERYBODY IS JUST

4

INTUITIVELY TOO BROAD.

5

AND YOUR HONOR SAID, "YOU NEED TO FIGURE OUT WHO WAS

6

IMPACTED, NOT WHO WAS IN THE SCOPE OF THE AGREEMENTS, BUT WHO

7

WAS IMPACTED."

8

AND THE PLAINTIFF SAID, IN APRIL, THAT THAT'S WHY THEY

9

NEEDED THE DATA, AND THEY SAY, "IT'S ONE OF THE QUESTIONS WE'RE

10

ASKING OUR ECONOMIST.

11

EMBEDDED IN OUR REQUEST FOR DATA."

12

IT'S ONE OF THE QUESTIONS THAT IS

AND THEN IN JUNE WHEN THEY CAME BACK AND ASKED FOR MORE

13

TIME TO ANALYZE THE DATA, THEY SAID -- AND THIS IS AT PAGE 21

14

OF THE JUNE TRANSCRIPT -- "ONE OF THE THINGS WE NEED TO DO WITH

15

THE DATA IS TO LOOK AT IT AND SEE WHAT IMPACT.

16

THE DATA TO HELP ADDRESS THE VERY SPECIFIC QUESTION YOU'RE

17

ASKING, WHICH IS, WHAT'S THE CLASS IN THIS CASE?"

18

WE NEED TO GET

THEY SAID, "WE DIDN'T HAVE ACCESS TO DATA AT THE START,

19

THEY DIDN'T HAVE ACCESS AT THE START, WE NEED THAT DATA TO HELP

20

ANSWER THAT QUESTION.

21

CERTIFICATION THAT'S GOING TO BE AS SPECIFIC AS WE CAN BASED ON

22

WHAT THE DATA SHOWS."

WE'RE GOING TO MAKE A MOTION FOR CLASS

23

AND SO WE'VE GIVEN THEM 12 YEARS OF COMPENSATION DATA AND

24

IF THERE WERE ANYTHING TO THE CLAIM THAT WHEN -- AND FOUR OF IT

25

WAS BEFORE THE -- OR, YEAH, FOUR YEARS WAS BEFORE THE ALLEGED

UNITED STATES COURT REPORTERS

182

21

1

VIOLATION PERIOD.

2

IF THERE WERE ANYTHING TO THEIR CLAIM THAT PEOPLE WOULD

3

GET COLD CALLS, THAT THE COLD CALLS WOULD LEAD TO A RAISE FOR

4

THAT PERSON AND THEN IT WOULD LEAD TO A RAISE FOR SOMEBODY

5

ELSE, EVEN WITHIN THE SAME DEPARTMENT, THERE WOULD BE AMPLE

6

EVIDENCE OF THAT IN THE DATA.

7

IT WOULD -- YOU KNOW, IF ALL THESE COMPANIES HAD THIS

8

INTERNAL EQUITY SYSTEM WHICH MEANT THAT A RAISE FOR ONE IS A

9

RAISE FOR EVERYBODY --

10

THE COURT:

OKAY.

I'M SORRY.

I'M GOING TO

11

INTERRUPT YOU, BECAUSE UNFORTUNATELY I HAVE A LONG LIST OF

12

TOPICS THAT I WANT TO COVER WITH YOU ALL.

13

MR. MITTELSTAEDT:

SURE.

14

THE COURT:

THANK YOU.

15
16
17

OKAY.

OKAY.

LET ME GO BACK TO THE PLAINTIFFS, AND WE'RE KIND OF

STUCK ON COLD CALLING FOR A LITTLE WHILE.
I GUESS I'M STILL BACK TO THE SAME ISSUE OF WHETHER THERE

18

SHOULD BE REFINEMENT OF THE CLASS, AND I GUESS THE QUESTION IS,

19

FIRST, WHETHER THERE SHOULD BE SOME NARROWING OF THE MARKET BY

20

EITHER GEOGRAPHY OR BY TYPE OF WORK.

21

QUESTION FIRST?

22

MR. GLACKIN:

SURE.

WOULD YOU ADDRESS THAT

THAT'S TWO QUESTIONS.

23

IN TERMS OF GEOGRAPHY, THAT'S AN ISSUE THAT WE HAVE NOT

24

STUDIED AND THAT HAS NOT BEEN SUGGESTED BY THE DEFENDANTS AS

25

PROPER, SO AS I'M STANDING HERE, I DON'T HAVE AN OPINION AS TO

UNITED STATES COURT REPORTERS

183

22

1
2

WHETHER OR NOT THAT WOULD BE SENSIBLE.
I'M NOT AWARE OF ANY EVIDENCE THAT HOW THE DEFENDANTS' PAY

3

STRUCTURE OPERATED WAS SORT OF EXISTENTIALLY DIFFERENT

4

DEPENDING ON WHERE A WORKER WAS LOCATED.

5

HAVE PAID PEOPLE DIFFERENTLY BASED ON WHERE THEY WORK, I MEAN,

6

DIFFERENT ACTUAL AMOUNTS OF MONEY.

7

CERTAINLY THEY MAY

BUT ALL OF THAT WOULD BE ACCOUNTED FOR IN THE DATA

8

ANALYSIS THAT WE'VE DONE.

9

SAY IT'S INCLUDED IN THAT INDIVIDUAL EMPLOYEE COMPENSATION

10
11

OR IT WOULD BE INCLUDED -- I SHOULD

NUMBER.
IN TERMS OF TYPE OF WORK, WE TOOK THE -- WE TOOK THE ISSUE

12

SERIOUSLY, YOUR HONOR, AND THAT'S WHY WE OFFERED THIS, WHAT

13

WE -- THE REASON WE OFFERED AN ALTERNATIVE CLASS THAT WE CALL

14

THE TECHNICAL CLASS IS BECAUSE WE WANTED TO DEMONSTRATE THAT IF

15

THERE WAS A CONCERN ABOUT COHESIVENESS, IF YOU WILL, FOR WANT

16

OF A BETTER TERM, THAT WE COULD MEET THAT CONCERN BY SIMPLY

17

LOOKING AT THE JOB TITLES OF -- USED BY THE DEFENDANTS AND

18

CALLING OUT PEOPLE WHO ARE WORKING IN SOFTWARE, TECHNICAL, AND

19

CREATIVE POSITIONS BASED ON A REVIEW OF THE JOB TITLES.

20
21
22

WE THINK THAT, AS I SAID, THAT THE IMPACT WAS BROADER THAN
THAT.
BUT IF YOUR HONOR HAD WHAT I WOULD CHARACTERIZE AS SORT OF

23

A COHESION CONCERN, THAT WE WOULD -- THAT'S -- THAT WE WOULD

24

PROPOSE IS THE BEST WAY TO ADDRESS IT.

25

OTHER IDEAS, BUT THAT WAS OUR IDEA.

I'M OPEN TO HEARING

UNITED STATES COURT REPORTERS

184

23

1

AND THEN IN TERMS OF -- JUST IN TERMS OF THE DATA AND ALL

2

THE THINGS THAT WERE SAID, WE REALLY WANTED THE COLD CALLING

3

DATA.

4

AND IT JUST DOESN'T EXIST AND THAT IS -- THAT IS SOMETHING WE

5

WERE AFTER AND WE DON'T HAVE IT.

6

ANSWER THE QUESTION OF HOW COLD CALLING WOULD HAVE BEEN

7

FOCUSSED.

8
9

WE REALLY WANTED RELIABLE DATA ABOUT THE COLD CALLING

SO THAT IS WHY WE CAN'T

BUT JUST TO GET BACK TO THE -THE COURT:

IS THERE DEFINITE -- LET'S TALK ABOUT

10

YOUR TECHNICAL ALTERNATIVE CLASS.

11

INTERCHANGEABILITY THERE, LIKE WOULD INTUIT NEED AN ANIMATOR?

12

LIKE HOW --

13

MR. GLACKIN:

NO.

IS THERE DEFINITE

THERE'S -- I MEAN, I THINK -- AND

14

DR. LEAMER TESTIFIED TO THIS AT HIS DEPOSITION.

15

THESE -- THERE ARE MULTIPLE DIFFERENT -- IF YOU WERE GOING TO

16

DO A MARKET-WIDE ANALYSIS, THERE ARE MULTIPLE DIFFERENT MARKETS

17

AT ISSUE HERE.

18

THE COURT:

19

MR. GLACKIN:

I MEAN,

UM-HUM.
AND, NO, I WOULD NEVER SAY THAT

20

EVERYONE IN THE TECHNICAL CLASS IS INTERCHANGEABLE, JUST AS I

21

WOULD NEVER SAY THAT EVERYBODY IN THE LARGER CLASS IS

22

INTERCHANGEABLE FROM A MARKET ANALYSIS STANDPOINT.

23

BUT, AGAIN, OUR WHOLE -- OUR WHOLE -- THE WHOLE THRUST OF

24

DR. LEAMER'S ANALYSIS HERE, AND ACROSS 130 PAGES, IS THAT A

25

TRADITIONAL MARKET ANALYSIS OF THIS CONDUCT IS THE WRONG WAY TO

UNITED STATES COURT REPORTERS

185

24

1

LOOK AT A LABOR MARKET.

2

MARKET AND A RESTRICTION ON COMPETITIVE INFORMATION IN A LABOR

3

MARKET.

4

IT JUST DOESN'T APPLY TO A LABOR

AND THERE'S -- I MEAN, I'M NOT GOING TO RECAPITULATE

5

EVERYTHING HE SAID, BUT THAT'S THE WHOLE POINT IS THAT THAT

6

INTERCHANGEABILITY QUESTION REALLY GOES TO A TROPE THAT IS NOT

7

APPLICABLE HERE.

8
9

THE COURT:
CONSPIRACY THEN?

SO DOES THAT UNDERMINE THE OVERARCHING

DOES THAT RE-ENFORCE THAT THE BILATERAL

10

AGREEMENTS WERE REALLY REFLECTING THE RELEVANT MARKET FOR

11

EMPLOYEES, LIKE THE TWO COMPANIES THAT WOULD ACTUALLY COMPETE

12

FOR THE SAME WORKERS ENTERED INTO A BILATERAL AGREEMENT AND

13

THERE WOULDN'T KIND OF BE THE SORT OF OVERARCHING, YOU KNOW,

14

INTUIT NEEDS A PIXAR PERSON AND SORT OF ALL THAT, THE CROSS

15

DEMAND THAT WE HAD TALKED ABOUT --

16

MR. GLACKIN:

17

THE COURT:

18

MR. GLACKIN:

19

YEAH.

-- ON THE MOTION TO DISMISS?
I MEAN, I THINK THAT THERE'S -- I

MEAN, THERE'S A FEW THINGS TO UNPACK THERE.

20

I MEAN, TO THE EXTENT THAT WE'RE TALKING ABOUT, AS A

21

QUESTION OF LAW, WHETHER -- OR AS A QUESTION, I SHOULD SAY, OF

22

ANTITRUST VIOLATION AND WHETHER THERE WAS A SINGLE CONSPIRACY

23

OR MORE THAN ONE CONSPIRACY, AS TO THAT QUESTION I WOULD SAY

24

THAT, AGAIN, WE HAVE YET TO DEPOSE ANY OF THE PEOPLE WHO WERE

25

THE ARCHITECTS OF THIS CONSPIRACY.

UNITED STATES COURT REPORTERS

186

25

1
2

THE COURT:

WHEN ARE THOSE DEPOSITIONS GOING

FORWARD?

3

MR. GLACKIN:

THEY'RE SET ACTUALLY TO START NEXT

4

WEEK, AND WE ARE GOING TO HAVE TO GET DONE BEFORE THE END OF

5

DISCOVERY, WHICH IS, I BELIEVE, TOWARDS THE END OF MARCH.

6

THEY'RE HAPPENING.

7
8
9

I DON'T KNOW WHAT THEY'RE GOING TO SAY.

SO

I DON'T KNOW THAT

THEY'RE GOING TO ADMIT THAT THERE WAS A SINGLE CONSPIRACY.
BUT THAT'S -- THAT'S AN ISSUE THAT THEY'RE NOT CONTESTING

10

AND I SUSPECT THAT -- FOR THE PURPOSES OF THIS MOTION, AND I

11

SUSPECT THAT PART OF THAT MAY BE THAT WE CAN VERY EASILY SAY

12

THAT DISCOVERY IS COMPLETELY OPEN ON THIS POINT.

13

THE COURT:

WHY WEREN'T THOSE SCHEDULED -- I THINK

14

IT'S VERY CONVENIENT THAT THEY WERE NOT SCHEDULED UNTIL AFTER

15

THE HEARING ON CLASS CERT.

16

MR. GLACKIN:

WELL, WE'VE BEEN -- I DON'T KNOW WHAT

17

TO SAY EXCEPT TO SAY WE'VE BEEN PRESSING FOR THEM AND WE WOULD

18

HAVE LIKED TO HAVE TAKEN SOME OF THEM FASTER AND WE REQUESTED

19

SOME OF THEM BEFORE THE HEARING.

20

THE COURT:

BUT THAT IS WHERE WE ARE.

WELL, WHEN WE GO THROUGH THE CMC, I WANT

21

YOU TO GIVE ME ALL OF THE DATES AND THOSE DATES ARE GOING TO

22

STICK.

23

MR. GLACKIN:

24

THE COURT:

25

ALL RIGHT.

OKAY.

OKAY?

LET ME ASK WITH REGARD TO YOUR ALTERNATIVE

UNITED STATES COURT REPORTERS

187

26

1

CLASS, DO WE KNOW -- AND WE PROBABLY DON'T BECAUSE THERE'S NO

2

COLD CALLING DATA -- WHETHER THE INDIVIDUALS IN THAT CATEGORY,

3

OR THAT CLASS, WOULD HAVE RECEIVED COLD CALLS OR WOULD HAVE

4

BEEN LIKELY SUBJECT TO COLD CALLS?

5

MR. GLACKIN:

WELL, I THINK THAT -- I MEAN, HOW CAN

6

I PUT THIS?

7

LARGE, AND SO THEIR TECHNOLOGY TALENT IS A BIG PART OF THEIR

8

WORK FORCE UNLIKE, SAY, BURGER KING.

9

THEM.

10
11

SO THE DEFENDANTS ARE TECHNOLOGY COMPANIES, BY AND

COLD CALLING MATTERED TO

THEY HAD LARGE STAFFS OF PEOPLE WHO MADE A LOT OF COLD

CALLS TO TRY TO FILL OPEN POSITIONS.
SO I FEEL -- IT WAS -- I WOULD SAY IT WAS A SIGNIFICANT

12

RECRUITING CHANNEL FOR THEM, FOR EACH OF THEM, OR AT LEAST NOT

13

A NEGLIGIBLE ONE.

14

BUT BEYOND THAT, WE'RE NOT IN A POSITION TO SAY THAT

15

MEMBERS OF ONE -- MEMBERS OF ONE EMPLOYEE GROUP OR ONE, YOU

16

KNOW, OF THE SMALLER CLASS ARE MORE LIKELY TO HAVE RECEIVED

17

COLD CALLS THAN MEMBERS OF THE -- THAN CLASS MEMBERS NOT IN

18

THAT SMALLER CLASS.

19

WAY OR THE OTHER, NOT BASED ON EVIDENCE.

20

SPECULATE, BUT NOT BASED ON EVIDENCE.

21

THE COURT:

WE'RE NOT IN A POSITION TO SAY THAT ONE
I MEAN, WE COULD

LET ME ASK ABOUT YOUR NAMED PLAINTIFFS.

22

THEY'RE ALL SOFTWARE ENGINEERS, OR THEY WERE.

23

THEM ARE DOING DIFFERENT OCCUPATIONS RIGHT NOW.

24

MR. GLACKIN:

25

THE COURT:

I KNOW SOME OF

CORRECT.

HOW WERE THEY TYPICAL?

UNITED STATES COURT REPORTERS

AND I'M

188

27

1

UNDERSTANDING THAT THE DEFENDANTS ARE NOT CHALLENGING

2

TYPICALITY HERE, BUT HOW ARE THEY TYPICAL OF THE SOU CHEFS AND

3

ADMINISTRATIVE ASSISTANTS AND THE OTHER TYPES OF EMPLOYEES?

4

MR. GLACKIN:

WELL, IN AN ANTITRUST CASE, TYPICALITY

5

IS -- YOU KNOW, ORDINARILY THE MOST TYPICAL THING ABOUT THE

6

CLASS REPRESENTATIVE IS THAT THEY HAVE THE ISSUE THAT'S COMMON

7

TO THE WHOLE CLASS, WHICH IS THE VIOLATION.

8

AND USUALLY WHEN YOU LOOK AT -- WHEN YOU ASK ABOUT

9

TYPICALITY IN AN ANTITRUST CASE, YOU MIGHT BE ASKING YOURSELF

10

IF IT'S POSSIBLE TO -- IF THERE'S SOME SORT OF FUNDAMENTAL

11

CONFLICT BETWEEN THIS PERSON AND OTHER MEMBERS OF THE CLASS

12

THAT MAKES THEIR CLAIM SO UNUSUAL THAT THEY'RE GOING TO BE A

13

BAD CLASS REPRESENTATIVE.

14

ADEQUACY.

I MEAN, IT'S A RELATED CONCEPT TO

15

AND I DON'T THINK THERE'S ANYTHING ABOUT OUR PROPOSED

16

CLASS REPRESENTATIVES, ABOUT THE PLAINTIFFS HERE, THAT SUGGESTS

17

THAT THERE -- THAT SUCH A CONFLICT EXISTS, THAT THE CLASS WOULD

18

BE DISADVANTAGED BECAUSE THEIR CLAIM IS A LOT DIFFERENT THAN

19

THE CLASS -- THAN THE CLAIM OF SOMEBODY ELSE IN THE CLASS.

20

THINK THEY'RE COMPLETELY, FOR PURPOSES OF THIS MOTION,

21

COMPLETELY TYPICAL.

22

THE COURT:

I

AND YOU'RE SAYING THAT BECAUSE YOU

23

BELIEVE THEIR INJURY IS THE SAME BASED ON THE VIOLATION OF

24

SUPPRESSED COMPENSATION?

25

MR. GLACKIN:

CORRECT.

THEY HAVE THE SAME -- THEY

UNITED STATES COURT REPORTERS

189

28

1

SHARE IN COMMON THE TWO THINGS THAT REALLY MATTER.

2

EMPLOYED BY THE DEFENDANTS, BY DEFENDANTS; AND THE DEFENDANT

3

THAT EMPLOYED THEM WAS A PARTY TO AN UNLAWFUL AGREEMENT OR

4

AGREEMENTS.

5

THE COURT:

THEY WERE

THE PLAINTIFFS RELY, IT APPEARS, HEAVILY

6

ON JUDGE ILLSTON'S DECISION ABOUT THE CLASS CERT ANALYSIS

7

REALLY JUST BEING ON THE METHOD FOR FIGURING OUT WHETHER

8

THERE'S CLASS-WIDE IMPACT VERSUS ACTUALLY LOOKING AT THE MERITS

9

OF WHETHER THERE HAS, IN FACT, BEEN CLASS-WIDE IMPACT.

10

MR. GLACKIN:

11

THE COURT:

CORRECT.

TELL ME WHY, AFTER DUKES V. WAL-MART, I

12

SHOULD FOLLOW JUDGE ILLSTON, WHO I ADMIRE A LOT AND RESPECT A

13

LOT, BUT WHY, AFTER DUKES, SHOULD I DO THAT?

14
15
16

MR. GLACKIN:

OH, SURE.

SO -- EXCUSE ME -- I DON'T

THINK THAT DUKES HAS HAD ANY EFFECT ON THIS ANALYSIS AT ALL.
DUKES IS A CASE THAT'S ABOUT 23(A) -- THIS IS A 23(B)(2)

17

CLASS, NOT A (B)(3) DAMAGES CLASS -- AND IT WAS A CASE ABOUT

18

COMMONALITY.

19

AND THE CASE -- THE ISSUE BEFORE THE SUPREME COURT IN

20

DUKES WAS IF THE ONLY COMMON ISSUE THE PLAINTIFFS HAVE IS THE

21

LACK OF A POLICY AND THE DISCRIMINATORY EFFECT THAT THEY SAY

22

THAT LACK OF A POLICY HAD, THAT THEY CAN PROVE THROUGH

23

STATISTICAL EVIDENCE, IF THAT IS THE ONLY COMMON ISSUE, THE

24

ONLY THING HOLDING THIS CLASS TOGETHER, THEN WE -- YOU BETTER

25

BE REALLY CONVINCING IS HOW I WOULD FRAME IT, AND THE COURT IS

UNITED STATES COURT REPORTERS

190

29

1

REQUIRED TO MAKE -- I BELIEVE THE SUPREME COURT -- THE

2

DEFENDANTS USED THE PHRASE "CONVINCING PROOF" IN THEIR PAPERS.

3

I SEEM TO RECALL THE PHRASE AS "SIGNIFICANT PROOF."

4

PHRASES ARE USED IN THE OPINION.

5

MAYBE BOTH

BUT IF YOU'RE IN THAT SITUATION WHERE THE ONLY EVIDENCE OF

6

A COMMON ISSUE IS THE STATISTICAL ANALYSIS SHOWING DISPARATE

7

IMPACT, THEN YOU ARE REQUIRED TO HAVE -- TO MAKE A SHOWING THE

8

SUPREME COURT CALLS CONVINCING PROOF.

9

IN AN ANTITRUST CASE, A SECTION 1 ANTITRUST CASE IS

10

FUNDAMENTALLY DIFFERENT.

11

SAYS THAT THE VIOLATION IS THE GLUE, THAT THAT IS THE COMMON

12

ISSUE.

13

I MEAN, THE LAW GOING BACK 50 YEARS

THAT'S WHY, IN ANTITRUST CASES, YOU SPEND ABOUT 30 SECONDS

14

IN THE BRIEFING TALKING ABOUT 23(A) IF IT'S A SECTION 1

15

AGREEMENTS CASE BECAUSE THERE'S JUST NO DOUBT THAT THE

16

VIOLATION IS COMMON, THAT YOU'VE MET THAT REQUIREMENT OF 23(A).

17

YOU HAVE A PRETTY IMPORTANT COMMON ISSUE THAT IS THE GLUE THAT

18

MAKES THE CLASS COHESIVE.

19
20
21

IT IS COMMON TO EVERY CLASS MEMBER.

SO THEN YOU GO TO THE 23 (B)(3) ANALYSIS, WHICH IS NOT THE
SUBJECT OF DUKES.

THERE WAS NO 23 (B)(3) CLASS IN DUKES.

AND THERE, AGAIN, THE LAW GOING BACK TIME IMMEMORIAL IS

22

PRETTY CLEAR THAT THE VIOLATION ITSELF, PUTTING ALL ELSE ASIDE,

23

CAN BE A REASON TO CERTIFY A CLASS.

24

JUST BASED ON THE VIOLATION AND HAVE -- EVEN IF THERE ARE

25

INDIVIDUALIZED ISSUES, IF YOU MEET THE OTHER REQUIREMENTS THAT

YOU CAN CERTIFY A CLASS

UNITED STATES COURT REPORTERS

191

30

1
2

CLASS RELIEF IS STILL SUPERIOR.
SO I WOULD SAY THAT WHEN YOU GET TO -- IN AN ANTITRUST

3

CASE, BY THE TIME YOU GET TO THE CONVERSATION WE'RE HAVING NOW

4

ABOUT IMPACT, THERE'S A PRETTY BIG THUMB ON THE SCALE IN FAVOR

5

OF CLASS CERTIFICATION, AND THAT IS A LOGICAL RESULT OF THE

6

NATURE OF THE CASE UNDER RULE 23.

7

SO BACK TO JUDGE ILLSTON.

I MEAN, THE REASON THAT WE

8

CITED THAT CASE SO MUCH, BESIDES FAMILIARITY WITH IT, IS

9

THAT -- I MEAN, THERE ARE MANY GOOD CLASS CERTIFICATION

10

DECISIONS IN THE NORTHERN DISTRICT THAT WE'VE CITED AND I WOULD

11

SAY THAT ALL OF THOSE JUDGES DID A FINE JOB.

12

BUT I FELT -- WE BELIEVE THAT JUDGE ILLSTON'S OPINION

13

THERE IS PARTICULARLY COMPREHENSIVE AND THAT THE ISSUES THAT

14

ONE -- THAT -- THE ANALYSIS THAT THE COURT SHOULD GO THROUGH

15

AND THE ISSUES THAT ARE COMMONLY RAISED IN THESE CASES ARE --

16

WERE VERY WELL VENTILATED THERE AND CONSIDERED BY HER.

17

AND SO WE THINK IT'S AN EXCELLENT, AN EXCELLENT ROAD MAP,

18

IF YOU WILL, OF WHAT THE COURT IS SUPPOSED TO DO HERE, WHICH IS

19

LOOK AT EVERY ISSUE AND SAY, IS IT INDIVIDUAL OR IS IT COMMON?

20

PUT THE COMMON ISSUES ON ONE SIDE OF THE LEDGER, PUT THE

21

INDIVIDUAL ISSUES ON THE OTHER SIDE OF THE LEDGER, IF ANY, AND

22

THEN MAKE A JUDGMENT AS TO WHETHER OR NOT THE INDIVIDUAL ISSUES

23

PREDOMINATE.

24
25

THE COURT:

CAN YOU WALK ME THROUGH -- THIS IS IN

DR. LEAMER'S EXPERT REPORT IN SUPPORT OF THE MOTION -- WALK ME

UNITED STATES COURT REPORTERS

192

31

1

THROUGH FIGURES 13 THROUGH 22 AND WHAT EXACTLY THEY SHOW AND

2

WHAT THEY REPRESENT.

THAT WOULD JUST BE HELPFUL --

3

MR. GLACKIN:

4

THE COURT:

CERTAINLY, YOUR HONOR.

-- TO KNOW WHETHER THESE ARE JUST

5

HYPOTHETICALS, ARE THESE ACTUAL DATA THAT'S BEEN AGGREGATED AND

6

THEN AVERAGED?

7
8

OR WHAT -- WHAT THESE ARE.

MR. GLACKIN:

YOU COULD GUIDE ME ALONG IF YOU TOLD

ME WHAT PAGE FIGURE 13 IS ON.

9

THE COURT:

SURE.

10

MR. GLACKIN:

11

THE COURT:

PAGE 57.

PAGE 57.

OR IF YOU WANT TO START WITH 15, WHICH

12

IS ON PAGE 59, OR 20, WHICH IS ON PAGE 66.

13

HOWEVER YOU FIND IT EASIER TO EXPLAIN WHAT THEY REPRESENT.

14
15

MR. GLACKIN:

I MEAN, IT --

SURE, AND I THINK THIS IS AN EXCELLENT

THING TO DO.

16

THE COURT:

OKAY.

17

MR. GLACKIN:

SO LET'S ACTUALLY GO BACK TO 12 AND

18

13, BECAUSE THE SIGNIFICANCE OF WHAT COMES OUT OF 15 AND 16

19

DEPENDS ON UNDERSTANDING 12, 13, AND 14.

20

THE COURT:

OKAY.

21

MR. GLACKIN:

SO 12, 13, AND 14 ARE -- EXCUSE ME,

22

AND ACTUALLY GOING BACK TO 11 I WOULD SAY -- ARE -- REPRESENT

23

THE RESULTS OF THE CORRELATION ANALYSIS.

24
25

AND THIS, JUST TO BE COMPLETELY CLEAR, IS NOT AN AVERAGED
EXERCISE.

THIS IS AN EXERCISE THAT'S PERFORMED ON THE ENTIRE

UNITED STATES COURT REPORTERS

193

32

1

DATA SET, AND THE QUESTION THAT DR. LEAMER IS ASKING IS, TO

2

WHAT EXTENT DO A SET OF COMMON OBJECTIVE FACTORS THAT WE CAN

3

IDENTIFY IN THE DATA EXPLAIN THE COMPENSATION OF CLASS MEMBERS?

4

AND THE REASON WE ASKED THE QUESTION IS, IF THE

5

COMPENSATION OF CLASS MEMBERS IS NOT WELL EXPLAINED BY COMMON

6

OBJECTIVE FACTORS, THEN WE WOULD HAVE A REASON TO BELIEVE THAT

7

OUR HYPOTHESIS OF A PAY STRUCTURE IS FALSE.

8
9

SO HE ASKED THE QUESTION, AND YOU SEE ON 11 YOU HAVE, I
WOULD SAY, THE SORT OF HIGH LEVEL RESULTS.

AND THE R SQUARE

10

NUMBER, AND I'M -- I BELIEVE -- I HOPE I'M GOING TO GET THIS

11

RIGHT -- IT SAYS THIS IS THE PERCENTAGE OF -- THIS IS AN

12

AVERAGE.

13

IS EXPLAINED FOR THAT YEAR AT THESE DEFENDANT FIRMS BY THESE

14

COMMON OBJECTIVE FACTORS.

15

THIS IS THE AVERAGE PERCENTAGE OF COMPENSATION THAT

THE COURT:

SO DR. LEAMER TOOK ALL OF THE DATA FOR

16

ALL EMPLOYEES OF ALL DEFENDANTS AND THEN DID AN ANALYSIS TO

17

DETERMINE HOW MUCH OF THE PAY DIFFERENTIAL IS DETERMINED BY

18

AGE, FOR EXAMPLE, OR BY TENURE AT THE COMPANY.

19

MR. GLACKIN:

IS THAT RIGHT?

EXACTLY, HOW MUCH OF IT IS DETERMINED

20

BY THESE SIX FACTORS TOGETHER, AND ALSO HOW MUCH OF IT IS

21

DETERMINED BY THEM INDIVIDUALLY, CORRECT.

22

AND WHAT WE FIND IS, UNSURPRISINGLY -- AND DR. MURPHY, I

23

THINK, FOUND THIS, TOO -- IS THAT JOB TITLE IS FAR AND AWAY THE

24

MOST IMPORTANT FACTOR, WHICH IS TOTALLY UNSURPRISING AT

25

COMPANIES THAT PAY PEOPLE WITHIN SALARY RANGES ACCORDING TO JOB

UNITED STATES COURT REPORTERS

194

33

1
2
3
4

TITLES, WHICH IS WHAT WE HAVE REASON TO BELIEVE HAPPENED HERE.
SO THAT'S -- THAT'S WHAT 12 -- THAT'S WHAT 11, 12, 13, AND
14 ARE ABOUT.
AND THEN IF YOU LOOK AT 14 --

5

THE COURT:

NOW, TITLE INDICATORS, IT JUST SAYS YES.

6

IT DOESN'T SAY HOW MUCH OF A DIFFERENTIAL IT MADE IN TERMS OF

7

COMPENSATION.

8
9
10
11

MR. GLACKIN:

YES.

I THINK WHAT THAT -- EXCUSE ME.

I MIGHT ACTUALLY BE -- IT'S POSSIBLE THAT I'M MISINTERPRETING
THAT COLUMN ESTIMATE.
BUT WHAT TITLE -- WHAT I READ TITLE INDICATORS THERE TO

12

MEAN IS THAT TITLE INDICATORS ARE INCLUDED IN THE ANALYSIS,

13

WHICH IS TRUE.

14

THE COURT:

OKAY.

SO THEN THIS IS JUST LOOKING AT

15

THE DIFFERENCE THAT AGE, TENURE AT THE COMPANY, AND GENDER

16

MAKE?

IT'S ONLY LOOKING AT THOSE THREE VARIABLES?

17

MR. MITTELSTAEDT:

18

MR. GLACKIN:

19

JOB TITLE, AND WHAT COMPANY IT IS.

20

THE COURT:

21

MR. GLACKIN:

22

THE COURT:

YEAH.

RIGHT.

AGE, TENURE, GENDER, LOCATION,

THAT'S WHAT EMPLOYER INDICATORS MEANS?
I BELIEVE SO.

WHAT COMPANY IT IS?

I GUESS I'M JUST

23

NOT CLEAR ON WHY IT DOESN'T SHOW WHAT DIFFERENCE THE TITLE

24

INDICATOR MAKES.

25

GO ON.

IT JUST SAYS YES.

BUT THAT'S FINE.

UNITED STATES COURT REPORTERS

WE CAN

195

34

1

MR. GLACKIN:

SO -- AND THEN IF YOU LOOK -- AND THEN

2

ON 12, THIS INFORMATION IN FIGURE 12 IS DISAGGREGATED BY

3

DEFENDANT, RIGHT?

4

THE PERCENTAGE OF EMPLOYEE COMPENSATION THAT IS EXPLAINED BY

5

THESE COMMON OBJECTIVE FACTORS IN ANY GIVEN YEAR FOR ANY GIVEN

6

DEFENDANT.

7

SO YOU CAN SEE THE -- THIS FIGURE 12 SHOWS

SO WE -- IN ADDITION TO GIVING THE COURT THE RANGE -- OR

8

EXCUSE ME -- THE AVERAGE, WHICH IS WEIGHTED BY DEFINITION

9

TOWARDS CERTAIN DEFENDANTS THAT ARE LARGER, WE ALSO WANTED TO

10
11

SHOW THE RANGE SO YOUR HONOR COULD SEE THE RANGE.
AND, I MEAN, THIS MIGHT BE A GOOD PLACE TO POINT OUT THAT

12

IN THE REED CASE ON WHICH MR. MITTELSTAEDT HAS RELIED

13

EXTENSIVELY, THERE WAS -- THERE WAS ALSO A CORRELATION ANALYSIS

14

DONE IN THAT CASE, AND THE EXPLANATORY VALUE OF THE CORRELATION

15

ANALYSIS IN THAT CASE WAS I THINK 48 TO 63 PERCENT.

16

IN OTHER WORDS, THE PLAINTIFFS IN THAT CASE, WHEN THEY

17

WERE TRYING TO EXPLAIN HOW NURSES ARE PAID, WHICH IS A VERY

18

DIFFERENT EXERCISE THAN WHAT WE'RE DOING HERE, COULD ONLY

19

EXPLAIN 48 TO 63 PERCENT, I THINK, OF THE SALARY, OR OF THE PAY

20

EARNED BY NURSES.

21

THE MANY FACTORS THAT THE COURT CONSIDERED IN THAT LENGTHY

22

OPINION.

23

AND THAT WAS A FACTOR THAT THE COURT, ONE OF

HERE YOU CAN SEE THAT OUR RANGE IS MUCH HIGHER THAN THAT.

24

I MEAN, I'M NOT SEEING THE LOWEST FIGURE HERE.

25

THE LOWEST FIGURE IS PROBABLY THE .77 FOR GOOGLE AT THE END IN

UNITED STATES COURT REPORTERS

I WANT TO SAY

196

35

1
2

2010.

OH, THERE'S A .75 ABOVE THAT, EXCUSE ME.

BUT IT'S QUITE CLEAR HERE, THE REASON THAT THE AVERAGE IS

3

AROUND 90 TO 95 IN EVERY YEAR IS BECAUSE FOR EVERY EMPLOYER FOR

4

EVERY YEAR WE ARE MORE OR LESS EXPLAINING IN THE BALL PARK OF

5

THAT AMOUNT OF THEIR COMPENSATION.

6

NOW, TO CORRECT ONE OTHER POSSIBLE MISCONCEPTION, THE --

7

JUST BECAUSE WE'VE ONLY EXPLAINED -- BECAUSE THE ANALYSIS ONLY

8

EXPLAINS THIS MUCH OF THE COMPENSATION, IT DOESN'T MEAN THE

9

REST OF IT IS RANDOM OR THAT IT IS ALL DISCRETIONARY.

10
11

IT

SIMPLY MEANS WE HAVEN'T EXPLAINED IT.
THERE ARE OTHER COMMON OBJECTIVE FACTORS THAT, IF WE KNEW

12

THEM, WE MIGHT BE ABLE TO EXPLAIN YET MORE OF THE COMPENSATION.

13

AND ONE THAT CAME UP IN, SPECIFICALLY IN DR. LEAMER'S

14

DEPOSITION IS EDUCATION.

15

WE HAVE.

16

BECAUSE THEY DON'T ALL KEEP IT, AND SO WE COULD NOT RUN A

17

CORRELATION ANALYSIS THAT WOULD INCLUDE THAT VARIABLE.

18

AND, AGAIN, WE SIMPLY HAVE THE DATA

WE DON'T HAVE EDUCATION DATA FOR ALL DEFENDANTS

BUT DR. LEAMER EXPRESSED AT HIS DEPOSITION HE FELT PRETTY

19

CONFIDENT THAT IF YOU PUT EDUCATION IN THERE, YOU WOULD BE

20

EXPLAINING SOME MORE OF THE SALARIES, OR OF THE COMPENSATION.

21

SO THEN 13 AND 14 ARE THE SAME EXERCISE, BUT FOR THE

22

TECHNICAL CLASS.

23

THE COURT:

WAIT.

24

MR. GLACKIN:

25

THE COURT:

LET ME ASK YOU --

SURE.

-- SO, FOR EXAMPLE, ONE COMP IN 2001,

UNITED STATES COURT REPORTERS

197

36

1

.91, DOES THAT MEAN THAT 91 PERCENT OF THE COMPENSATION IS

2

DETERMINED BY THE EMPLOYEE'S AGE, THEIR TENURE AT THE COMPANY,

3

THEIR GENDER, THE LOCATION WHERE THEY WORK, AND THEIR TITLE?

4
5

MR. GLACKIN:

CORRECT.

ON AVERAGE, YES, THAT'S WHAT

IT MEANS.

6

THE COURT:

OKAY.

7

MR. GLACKIN:

AND THAT -- AND 9 PERCENT OF IT WE

8

JUST DON'T KNOW.

IT COULD BE DETERMINED BY EDUCATION.

9

COULD BE DETERMINED BY MANAGER DISCRETION.

IT

IT COULD BE

10

DETERMINED BY -- ONE COULD IMAGINE OTHER FACTORS, BUT WE JUST

11

DON'T KNOW.

12

THE COURT:

OKAY.

13

MR. GLACKIN:

AND THEN 13 AND 14 ARE THE SAME THING

14

FOR THE TECH CLASS AND THEY SHOW -- I MEAN, AGAIN, WE WERE SORT

15

OF TAKEN TO TASK ABOUT NOT ASKING THESE QUESTIONS.

16

BUT WE DID ASK THESE QUESTIONS, AND IF THE CORRELATION

17

ANALYSIS HAD SHOWED THAT IT WAS PERFORMING VERY BADLY FOR THE

18

LARGER CLASS AND PERFORMING VERY WELL FOR THE TECHNICAL CLASS,

19

THEN WE MIGHT HAVE NOT PROPOSED THE LARGER CLASS.

20

BUT IT TURNS OUT THAT THE CORRELATION ANALYSIS PERFORMS

21

PRETTY MUCH THE SAME FOR BOTH, WHICH IS NOT -- I MEAN, I DON'T

22

KNOW IF IT'S SURPRISING OR NOT, BUT IT IS WHAT IT IS.

23

TRUE.

24
25

IT'S

SO WHAT YOU SEE FROM THIS IS THAT FOR BOTH THAT SMALLER
CLASS AND FOR THE CLASS OF EMPLOYEES ALL TOGETHER, THERE IS A

UNITED STATES COURT REPORTERS

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37

1

PAY STRUCTURE.

2

I THINK DR. MURPHY AND DR. LEAMER BOTH AGREE, FROM LOOKING AT

3

THE DATA, THAT IT'S VERY DRIVEN BY JOB TITLE.

4

THERE IS SOME KIND OF A PAY STRUCTURE HERE, AND

THE COURT:

WELL, YOU CAN'T TELL THAT BY -- YOU

5

CAN'T TELL THAT BY THESE FIGURES BECAUSE THEY DON'T GIVE YOU

6

ANY NUMERICAL ESTIMATE FOR TITLE.

7

MR. GLACKIN:

8

THE COURT:

9
10

YOU CAN'T DISAGGREGATE AGE OF THE

BECAUSE THIS IS A -MR. GLACKIN:

THAT'S CORRECT.

WE DON'T REPORT -- WE

DON'T REPORT THE PERCENTAGE.

13
14

THAT'S TRUE.

EMPLOYEE, TENURE AT THE COMPANY, GENDER, LOCATION, AND TITLE,

11
12

IT JUST SAYS YES.

THE COURT:

SO WHAT DO THEY BASE THAT ON, THAT IT'S

BASED ON THE TITLE?

15

MR. GLACKIN:

WHAT I AM RECALLING IS THAT DR. LEAMER

16

WAS ASKED AT HIS DEPOSITION, BY MR. PICKETT, SOMETHING ALONG

17

THE LINES OF, "WOULD IT SURPRISE YOU THAT MOST OF THIS

18

CORRELATION IS DRIVEN BY THE JOB TITLE?"

19
20
21
22
23

AND DR. LEAMER SAID, "NO, NOT AT ALL.

I BELIEVE THAT'S

TRUE."
AND I THINK THAT DR. MURPHY REFERRED TO THIS IN HIS REPORT
AS WELL, BUT I WOULD HAVE TO CHECK.
THE COURT:

WHY ARE THE, THE NUMBERS FOR HOW MUCH A

24

COMPENSATION IS DETERMINED BY EMPLOYEE AGE, COMPANY TENURE,

25

GENDER, LOCATION, AND TITLE PRETTY CONSISTENTLY LOWER FOR THE

UNITED STATES COURT REPORTERS

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38

1

TECHNICAL ALTERNATIVE CLASS VERSUS THE ALL EMPLOYEE CLASS?

2
3

MR. GLACKIN:
THAT.

I DON'T KNOW THAT WE COULD.

4

THE COURT:

5

MR. GLACKIN:

6

I DON'T BELIEVE WE TRIED TO EXPLAIN

OKAY.

ALL RIGHT.

SO THAT'S THOSE FIGURES.

THEN YOU GO TO FIGURES 15 AND 16 AND 17 -- AND JUST FOR

7

CONTEXT'S SAKE, THESE ARE THE FIGURES THAT I THINK ARE THE

8

SUBJECT OF ALL THE SUPPLEMENTAL MATERIAL THE DEFENDANTS MOVED

9

TO ADMIT I BELIEVE LATE LAST WEEK.

10

AND WHAT THESE FIGURES SHOW IS -- SO IT SAYS CONSTANT

11

CONTRIBUTE -- EXCUSE ME -- CONSTANT ATTRIBUTE COMPENSATION OF

12

MAJOR JOB TITLES.

13

AND WHAT DR. LEAMER HERE IS DOING IS HE'S LOOKING AT THE

14

PREDICTED VALUE OF THESE JOB TITLES, PREDICTED BY THE

15

CORRELATION, WITHIN A PERSON'S COMPENSATION.

16

AND I'M PROBABLY NOT SAYING -- I'M PROBABLY NOT SAYING

17

THAT VERY WELL, BUT THE IDEA HERE IS TO ASK YOURSELF, IS THE

18

VALUE OF THE JOB TITLE CHANGING ON A YEAR TO YEAR BASIS WITHIN

19

THESE COMPANIES?

20

AND THE REASON YOU ASK THAT QUESTION -- IT ALWAYS GOES

21

BACK TO THE SCIENTIFIC METHOD.

THE REASON YOU ASK THAT

22

QUESTION IS BECAUSE IF, IF IT DOES, IF IT -- IF YOU SEE SOME

23

EVIDENCE, OR IF YOU SEE A LOT OF EVIDENCE THAT IS, YOU KNOW,

24

THAT JOB TITLE COMPENSATION GOES WAY UP IN ONE YEAR AND WAY

25

DOWN IN ANOTHER YEAR AND THIS IS ALWAYS TRUE FOR JOB TITLES,

UNITED STATES COURT REPORTERS

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39

1

YOU WOULD NOT BE REASSURED THAT THE -- THAT YOU'RE REALLY

2

DETECTING A STRUCTURE HERE THAT'S DRIVEN BY JOB TITLE.

3

AND SO HE MAPS THESE -- HE CONSIDERS WHAT --

4

THE COURT:

SO TELL ME, HOW IS FIGURE 15 CREATED?

5

MR. GLACKIN:

THIS -- I'M TRYING TO THINK OF THE

6

BEST WAY TO EXPRESS THIS.

7

THE VALUE OF COMPENSATION, DOLLAR VALUE OF COMPENSATION FOR A

8

PARTICULAR JOB TITLE THAT IS PREDICTED BY THE REGRESSION, THE

9

CORRELATION ANALYSIS IN ANY PARTICULAR YEAR.

10

THE COURT:

THIS IS THE PERCENTAGE OF -- THIS IS

SO YOU'RE SAYING THAT DR. LEAMER DID

11

WHATEVER HE DID TO CALCULATE THE NUMBERS IN FIGURES 11 AND

12

13 --

13

MR. GLACKIN:

14

THE COURT:

15

AS THE ONLY DEPENDENT VARIABLE?

-- THAT HE DID THAT AND ISOLATED TITLE

16

MR. GLACKIN:

17

THE COURT:

18
19

UM-HUM.

NO, NO, NO.

HOW DID HE COME UP WITH THIS GRAPH IN

FIGURE 15?
MR. GLACKIN:

SO THE -- WELL, ACTUALLY THAT MIGHT --

20

I THINK THE WORDS "DEPENDENT VARIABLE" MIGHT BE WRONG.

21

WHAT YOU MIGHT -- THE WAY I UNDERSTAND IT IS YOU LOOK AT THE

22

CORRELATION -- YOU LOOK AT THESE SIX FACTORS AND YOU PUT IN A

23

VALUE FOR EACH OF THE FACTORS, JOB TITLE, AGE, TENURE AT THE

24

COMPANY AND WHAT HAVE YOU, GENDER, AND THE ANALYSIS WILL SPIT

25

OUT A VALUE, OR PREDICT -- I SHOULDN'T SAY "SPIT OUT" -- IT

UNITED STATES COURT REPORTERS

I MEAN,

201

40

1
2

PREDICTS A DOLLAR AMOUNT OF COMPENSATION BASED ON THAT FACTOR.
AND THIS IS -- SO, I MEAN, HERE --

3

THE COURT:

IS THIS --

4

MR. GLACKIN:

SO HERE HE'S ISOLATING -- "ISOLATING"

5

IS THE RIGHT WORD -- HE'S ISOLATING WHAT YOU PREDICT JUST BASED

6

ON AN INDIVIDUAL'S JOB TITLE.

7

SO FOR HERE, IF YOU'RE LOOKING AT THE TOP LINE, WHICH IS

8

THE LIGHT PURPLE, WHICH IS SOFTWARE DEVELOPER ENGINEER 4 --

9

HOPEFULLY I GOT THE COLORS RIGHT -- THE CORRELATION ANALYSIS IS

10

PREDICTING THAT IF ALL YOU KNOW ABOUT A PERSON IS THAT THEY

11

HAVE THAT POSITION, THEY'RE MAKING $130,000 A YEAR.

12

KNOW ANYTHING ELSE ABOUT THEM.

13

THE COURT:

18
19

NO.

MR. GLACKIN:

THE COURT:

AND THEN BELOW IS TOTAL COMP,

SO WHAT WAS THIS BASED ON, THE TOTAL

DATA OF ALL -MR. GLACKIN:

21

THE COURT:

23

RIGHT.

RIGHT.

20

22

THE TOP OF FIGURE 15 IS BASE

SALARY.

16
17

YOU JUST KNOW THAT.

AND THAT'S TOTAL COMPENSATION HERE, NOT SALARY.

14
15

YOU DON'T

RIGHT, ALL THE DATA.

NO.

THIS WAS JUST APPLE.

RIGHT?

FIGURE 15 IS JUST APPLE AND 16 IS JUST GOOGLE.
MR. GLACKIN:

YEAH, I THINK THAT'S RIGHT.

I MEAN,

24

ALL THE DATA IS IN THE SET, BUT I THINK YOU'RE BASING THAT ON

25

APPLE AND GOOGLE DATA.

UNITED STATES COURT REPORTERS

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41

1
2

THE COURT:
WHAT THESE ARE.

SO WHAT -- I'M JUST TRYING TO FIGURE OUT

IT'LL HELP IN THE ORDER.

3

MR. GLACKIN:

4

THE COURT:

SO WHAT HELPS --

THIS IS SAYING THAT -- THIS IS LOOKING

5

AT ALL OF THE BASE SALARY AND TOTAL COMPENSATION DATA OF THESE

6

TEN CATEGORIES OF JOBS AT APPLE --

7

MR. GLACKIN:

8

THE COURT:

9

-- AND PREDICTING WHAT THEIR SALARY

WOULD BE --

10

MR. GLACKIN:

11

THE COURT:

12

UM-HUM.

UM-HUM.

-- BASED SOLELY ON THE JOB TITLE?

IS

THAT WHAT THIS --

13

MR. GLACKIN:

14

THE COURT:

15

MR. GLACKIN:

THAT'S PRETTY MUCH RIGHT.

I DON'T UNDERSTAND WHAT THIS IS.
THAT'S PRETTY MUCH RIGHT.

AND THE

16

SIGNIFICANCE OF THAT IS, AGAIN, THAT THE -- THIS IS, AGAIN, AN

17

EXERCISE IN ATTEMPTING TO FALSIFY, RIGHT?

18

IF -- IF THIS WERE A LOT DIFFERENT, THEN DR. LEAMER WOULD

19

BE OF THE OPINION THAT THERE -- YOU KNOW, IT WOULD BE

20

QUESTIONABLE, I GUESS.

21

YOU'D HAVE TO MAYBE DO MORE ANALYSIS.

BUT YOU'D BE TROUBLED WITH YOUR CONCLUSION THAT THERE'S A

22

PAY STRUCTURE THAT PERSISTS OVER TIME THAT'S DRIVEN BY THIS

23

ADMINISTRATIVE PAY SYSTEM.

24
25

I MEAN, BECAUSE -- IN OTHER WORDS, WHEN YOU LOOK AT THE
CORRELATION ANALYSIS, YOU'RE LOOKING AT A SNAPSHOT OF A

UNITED STATES COURT REPORTERS

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42

1

PARTICULAR YEAR, AND THAT SHOWS A STRUCTURE.

2

IT DOES SHOW A

STRUCTURE.

3

BUT YOU ALSO WANT TO ASK YOURSELF IF THAT, IF THOSE

4

CORRELATIONS ARE HOLDING OVER TIME, BECAUSE IF THEY AREN'T, YOU

5

MIGHT HAVE TO DO SOME INVESTIGATION TO UNDERSTAND WHY THEY'RE

6

NOT.

7

THE COURT:

SO WHAT DOES YOUR THEORY REQUIRE BE

8

SHOWN IN FIGURE 15?

9

TECHNICAL JOBS AT APPLE ARE GENERALLY INCREASING OR DECREASING

10

THAT ALL OF THESE DIFFERENT CATEGORIES OF

TOGETHER?

11

MR. GLACKIN:

12

THE COURT:

13

MR. GLACKIN:

NO.

WHAT DOES YOUR THEORY REQUIRE?
IT ABSOLUTELY DOESN'T.

I DON'T

14

ACTUALLY THINK THAT -- I DON'T THINK THAT THE THEORY REQUIRES

15

THAT THESE LOOK A PARTICULAR WAY, OTHER THAN THEY NOT BE A

16

COMPLETE MISHMASH, I GUESS.

17

THE COURT:

WELL, DOESN'T YOUR INTERNAL EQUITY

18

THEORY REQUIRE THAT THEY SOMEWHAT RISE OR FALL TOGETHER?

19

OTHERWISE YOU'RE GOING TO HAVE RESENTMENT, JEALOUSLY,

20

DISCONTENTMENT, PEOPLE START LEAVING?

21

MR. GLACKIN:

NO, ABSOLUTELY NOT.

AND THE REASON

22

FOR THAT IS THAT INTERNAL EQUITY IS -- AND WE'VE NEVER SAID

23

THIS, BY THE WAY.

24

DRIVES EMPLOYEE COMPENSATION.

25

DRIVES EMPLOYEE COMPENSATION.

INTERNAL EQUITY IS NOT THE ONLY FACTOR THAT
IT IS SIMPLY A FACTOR THAT

UNITED STATES COURT REPORTERS

204

43

1

SO PEOPLE -- I'M SORRY.

2

THE COURT:

I DIDN'T MEAN TO INTERRUPT YOU.

WELL, I GUESS I'M JUST NOT -- I'M NOT

3

CLEAR ON WHAT THIS IS SHOWING, BASE SALARY VERSUS TOTAL

4

COMPENSATION, BROKEN DOWN BY TEN DIFFERENT ENGINEERING JOBS AT

5

TWO COMPANIES.

6

WHAT IS FIGURE 15 AND 16 SUPPOSED TO CONVEY?

MR. GLACKIN:

WHAT IT'S SUPPOSED TO CONVEY IS THAT

7

THE -- THE INDIVIDUAL STRUCTURE THAT'S BEEN SHOWN IN EVERY YEAR

8

BY THE CORRELATION ANALYSIS, WHICH IS FIGURES 11 THROUGH 14,

9

IS -- APPEARS TO BE PERSISTENT, MORE OR LESS, OVER TIME.

10

AND IT'S NOT -- IT'S NOT RANDOMLY RESETTING EVERY YEAR,

11

WHICH OF COURSE THERE'S NO EVIDENCE OF IN THE RECORD, RIGHT?

12

THEY DON'T DO A COMPLETE REBOOT OF THEIR PAY SYSTEM EVERY 12

13

MONTHS.

14

THE COURT:

AND WHAT DOES THAT MEAN?

THAT YOUR JOB

15

TITLE IS LARGELY GOING TO DETERMINE YOUR COMPENSATION IN A

16

GIVEN YEAR?

17

MR. GLACKIN:

18

THE COURT:

19

YEAH, AND IN FUTURE YEARS.

I GUESS I JUST DON'T SEE THE

RELATIONSHIP OF THAT WITH THE PLAINTIFFS' OVERALL THEORY.

20

MR. GLACKIN:

WELL, AGAIN, IT'S JUST TO -- I MEAN,

21

AT THIS POINT WE'RE REALLY CONFIRMING SOMETHING THAT WE HAD NO

22

REASON TO DOUBT TO BEGIN WITH, WHICH IS THAT THESE COMPANIES

23

HAVE ADMINISTRATIVE PAY SYSTEMS THAT PAY PEOPLE ACCORDING TO A

24

STRUCTURE.

25

I MEAN, LET ME POSIT -- MAYBE I CAN EXPLAIN THIS BETTER.

UNITED STATES COURT REPORTERS

205

44

1

LET'S SAY YOU HAVE RUN THE CORRELATION ANALYSIS FOR DIFFERENT

2

YEARS, AND EVERY YEAR YOU'RE SHOWING THAT 95 PERCENT OF --

3

YOU'RE EXPLAINING 95 PERCENT OF COMPENSATION BASED ON SIX

4

FACTORS, OKAY?

5

THAT LOOKS GREAT.

THAT LOOKS LIKE A STRUCTURE.

BUT WHAT IF, WHAT IF, IN 2001, JOB TITLE IS DRIVING 90

6

PERCENT OF IT AND, IN 2002, GENDER IS DRIVING 90 PERCENT OF IT

7

AND JOB TITLE IS ONLY DRIVING 10 PERCENT OF IT?

8
9
10
11

WELL, YOU'RE STILL EXPLAINING 90 PERCENT, BUT YOUR THEORY
OF A STRUCTURE IS QUESTIONABLE, TO SAY THE LEAST, UNDER THOSE
CIRCUMSTANCES.
AND WHAT THIS IS SHOWING IS THAT THAT DIDN'T HAPPEN, THAT

12

JOB TITLE CONTINUED TO BE IMPORTANT EVERY YEAR, AND THAT THE

13

SYSTEM WASN'T REBOOTING SO THAT IT WAS JOB TITLE ONE YEAR,

14

GENDER ANOTHER YEAR, AND THEN THE THIRD YEAR, THEY THREW THE

15

JOB TITLE BOOK OUT AND THEY JUST PAID PEOPLE BASED ON HOW LONG

16

THEY'D BEEN AT THE COMPANY, YOU GOT 50 GRAND FOR EVERY YEAR OF

17

SERVICE.

18
19
20

THAT DIDN'T HAPPEN.

WE KNOW AS A FACTUAL MATTER THAT THAT

DIDN'T HAPPEN, AND THIS SIMPLY CONFIRMS THAT IT DIDN'T HAPPEN.
THE COURT:

OKAY.

SO WHAT IS THE RELATIONSHIP

21

BETWEEN THE THEORY THAT AN EMPLOYEE'S SALARY IS LARGELY

22

DETERMINED BY THEIR TITLE --

23

MR. GLACKIN:

24

THE COURT:

25

UM-HUM.

THEORY OF THIS CASE?

-- WHAT DOES THAT HAVE TO DO WITH YOUR

UNITED STATES COURT REPORTERS

206

45

1

MR. GLACKIN:

WELL, WHAT IT HAS TO DO WITH IS THE

2

OPERATION OF INTERNAL EQUITY DOES REQUIRE SOME KIND OF A PAY

3

STRUCTURE AND -- THAT IS COMPANY-WIDE.

4

BE -- I MEAN, AGAIN, TO BEGIN WITH, WE START FROM THE PREMISE

5

THAT INTERNAL EQUITY IS WIDELY ACCEPTED -- EXCUSE ME -- IT'S

6

TAUGHT IN PERSONNEL HANDBOOKS.

7

TEXTBOOKS.

8
9
10
11

I MEAN, THERE HAS TO

IT'S TAUGHT IN PERSONNEL

IT'S NOT A CONTROVERSIAL PROPOSITION.

SO NOW WE'RE ASKING, WAS INTERNAL -- IS IT REASONABLE TO
BELIEVE THAT INTERNAL EQUITY AFFECTED COMPENSATION AT THESE
COMPANIES?
WELL, ONE THING THAT WOULD GIVE YOU A LOT OF PAUSE IS IF

12

THERE WAS NO STRUCTURE TO HOW THESE COMPANIES PAID THEIR

13

EMPLOYEES -- AND THIS WOULD BE IF THERE WAS NO SYSTEM OR

14

STRUCTURE, BECAUSE IF PAY IS NOT BEING CENTRALIZED AT THESE

15

COMPANIES IN ANY WAY, IT WOULD BE HARD FOR INTERNAL EQUITY TO

16

HAVE A SHARING EFFECT ACROSS THE ENTIRE FIRM.

17

SO THAT IS WHY WE'VE TRIED TO VERIFY HERE WHAT WE KNOW IS

18

TRUE, WHICH IS THAT THE COMPANIES HAVE ADMINISTRATIVE -- THEY

19

HAVE CENTRALIZED, ADMINISTRATIVE PAY SYSTEMS BY WHICH THEY SET

20

COMPENSATION FOR THE ENTIRE FIRM, AND THAT IS A VERY -- THAT

21

STRUCTURE IS A VERY IMPORTANT PART OF HOW THEY SET

22

COMPENSATION.

23

THE COURT:

WELL, THAT SEEMS TO BE SOMEWHAT TRUE FOR

24

BASE SALARY, BUT DOESN'T SEEM TO REFLECT TOTAL COMPENSATION,

25

WHICH I WOULD ASSUME INCLUDES, YOU KNOW, STOCK OPTIONS AND

UNITED STATES COURT REPORTERS

207

46

1

BONUSES.

THERE'S A LOT MORE DEVIATION GOING ON IN TOTAL

2

COMPENSATION.

SO HOW DO YOU --

3

MR. GLACKIN:

4

THE COURT:

WELL, YEAH.

SO HOW DO YOU EXPLAIN THAT, THAT YOUR

5

SORT OF MORE LOCKSTEP INTERNAL EQUITY THEORY MIGHT APPLY TO THE

6

BASE, BUT IT'S NOT GOING TO ACCOUNT FOR THE OTHER FACTORS THAT

7

MAKE UP SOMEONE'S TOTAL COMPENSATION?

8
9

MR. GLACKIN:

SO I GUESS WHAT I WOULD SAY IS THAT --

FIRST OF ALL, I MEAN, YOU CAN CERTAINLY IMAGINE A WORLD IN

10

WHICH THE EFFECTS OF THIS -- THE EFFECTS OF THE INCREASED

11

COMPETITION WOULD HAVE BEEN SHARED SIMPLY THROUGH BASE

12

SALARIES.

13

CERTAINLY POSSIBLE.

14

I MEAN, IT'S NOT HARD TO IMAGINE THAT WORLD.

IT'S

BUT I DON'T THINK THAT THE FACT THAT THE TOTAL

15

COMPENSATION LINES SHOW MORE VARIABILITY IS A PROBLEM.

16

THERE'S -- INTERNAL EQUITY DOESN'T MEAN EQUALITY.

17

MEAN EVERYBODY IS ALWAYS GOING TO GET A RAISE AT THE SAME TIME.

18

IT DOESN'T MEAN THAT EVERYONE IS GOING TO GET A PAY CUT AT THE

19

SAME TIME.

20

I MEAN,

IT DOESN'T

WHAT IT MEANS IS THAT IF SOMEONE, SOMEONE OR SOME GROUP

21

GETS A RAISE, THERE WILL BE AN INCREMENTAL BENEFIT TO OTHER

22

MEMBERS OF THAT COMPANY'S WORK FORCE BECAUSE OF THE GAINS --

23

CAUSED BY THE GAINS MADE BY THAT PERSON OR THAT GROUP.

24
25

SO OTHER PEOPLE WHO ARE GETTING A PAY CUT MIGHT GET LESS
OF A PAY CUT BECAUSE THERE MIGHT BE A BIGGER COMPENSATION

UNITED STATES COURT REPORTERS

208

47

1
2

BUDGET.
IT DOESN'T REQUIRE THAT, AT ALL, THAT COMPENSATION MOVE IN

3

LOCKSTEP, AND COMPENSATION AT THESE COMPANIES DOES NOT MOVE IN

4

LOCKSTEP.

5

THE COURT:

SO WHAT -- WHY DON'T YOU EXPLAIN HOW THE

6

SECOND GRAPH OF FIGURE 16 STILL SUPPORTS YOUR INTERNAL EQUITY

7

THEORY.

8
9

MR. GLACKIN:

SO I GUESS -- I MEAN, DR. LEAMER --

I'M GOING TO REFER TO HIS TESTIMONY, BECAUSE I FEEL LIKE HE

10

SHOULD BE THE ONE EXPLAINING IT.

11

THE COURT:

12

MR. GLACKIN:

UM-HUM.
AND HE TESTIFIED ABOUT THIS SPECIFIC

13

FIGURE AND HE SAID THAT, YOU KNOW, THAT THIS IS -- I MEAN, IT'S

14

NORMAL -- I REALLY OUGHT TO LOOK AT HIS TESTIMONY.

15

RECOLLECTION IS HE SAID THAT IT'S OKAY FOR THERE TO BE SOME

16

OUTLIERS.

17

JOB TITLE TO GET A BIG BUMP IN A PARTICULAR YEAR.

18

I MEAN, IT'S ALL RIGHT.

THE COURT:

19

EQUITY?

20

MY

IT'S OKAY FOR A GROUP OR A

BUT WHAT DOES THAT DO FOR INTERNAL

DISCONTENT?

21

DON'T THE REST OF THE FOLKS GET JEALOUS, RESENTFUL,

MR. GLACKIN:

THE POINT IS THAT THEY DON'T HAVE TO

22

GET THE SAME -- THEY DON'T HAVE TO GET THE SAME BUMP IN ORDER

23

TO NOT FEEL THAT WAY.

24
25

FOR EXAMPLE, IF -- YOU COULD GIVE ONE GROUP OF EMPLOYEES A
PAY RAISE AND GIVE OTHER GROUPS OF EMPLOYEES A SMALLER PAY

UNITED STATES COURT REPORTERS

209

48

1

RAISE AND YOU COULD -- YOU KNOW, BECAUSE IT'S NOT -- WE'RE NOT

2

THE SOVIET UNION AND WE'RE NOT POSTULATING THAT THESE COMPANIES

3

ARE THE SOVIET UNION.

4

COMMUNIST REGIME WHERE EVERYONE HAS AN EXPECTATION THAT THEY'RE

5

GOING TO BE PAID THE SAME AMOUNT AS THEIR COMRADE.

6

WE'RE NOT SAYING THAT THIS IS A

BUT PEOPLE DO CARE ABOUT BEING PAID FAIRLY AND THEY DO

7

BELIEVE IF SOMEONE ELSE IS GETTING SOME GAINS, THEY SHOULD

8

SHARE IN THAT A LITTLE BIT.

9

THE COURT:

SO WHY SHOULDN'T THEY GENERALLY RISE AND

10

FALL TOGETHER, EVEN IF THERE MIGHT BE SLIGHT DEVIATIONS?

11

SHOULDN'T THEY ALL RISE AND FALL TOGETHER UNDER YOUR THEORY?

12
13
14

MR. GLACKIN:

WHY

BECAUSE THERE ARE OTHER FACTORS THAT

AFFECT COMPENSATION.
AND WE'VE NEVER SAID THAT THIS -- THAT THESE AGREEMENTS OR

15

THAT COMPETITION AMONG THESE DEFENDANTS FOR WORKERS OR THAT

16

INTERNAL EQUITY ARE THE ONLY FACTORS THAT AFFECT COMPENSATION.

17

IT -- WE WOULD SAY THAT THERE IS -- THAT THERE ARE -- THAT

18

OTHER FORCES ARE GOING TO CONTINUE TO MOVE SALARIES AROUND, BUT

19

THAT THERE WILL BE -- IF ONE GROUP, IN THIS GREEN LINE HERE, IF

20

THEY GET A BIG BUMP IN ONE YEAR, THAT THAT IS GOING TO BE

21

SHARED, THAT THEY ARE NOT THE ONLY GROUP THAT IS GOING TO DO

22

BETTER THAT YEAR THAN THEY WOULD HAVE.

23

AND, AGAIN, THE THING TO REMEMBER HERE IS WE'RE TALKING

24

ABOUT A BUT-FOR WORLD THAT NEVER HAPPENED WHERE THERE WAS

25

INCREASED COMPETITION, AND WE'RE SAYING THAT IN THAT WORLD, IF

UNITED STATES COURT REPORTERS

210

49

1

INCREASED COMPETITION CAUSED -- NOW, WE'RE NOT SAYING INCREASED

2

COMPETITION CAUSED THAT BUMP, RIGHT, BECAUSE THIS IS 2007 IN

3

THE MIDDLE OF THE AGREEMENTS.

4

BUT WE'RE SAYING IF INCREASED COMPETITION HAD CAUSED A

5

BUMP LIKE THAT FOR A JOB TITLE OR FOR A SMALL GROUP OF PEOPLE,

6

YOU WOULD EXPECT, UNDER INTERNAL EQUITY, THAT SOME -- THAT

7

OTHER PEOPLE IN THE SAME WORK FORCE WOULD SEE SOME GAINS AS

8

WELL.

9

THE COURT:

WHY DID DR. LEAMER USE AVERAGED

10

COMPENSATION NUMBERS TO CREATE THESE CHARTS IN FIGURES 15, 16,

11

AND 17?

12
13
14

MR. GLACKIN:

SO BECAUSE I THINK -- WELL, HE'S NOT

BEEN ASKED THAT QUESTION.
I WOULD SAY THAT WHEN YOU'RE TRYING TO ISOLATE THE

15

RELATIONSHIP THIS WAY, THAT THE MOST DESCRIPTIVE WAY TO DO THAT

16

IS TO USE AN AVERAGE.

17

THERE'S BEEN SOME TALK IN THIS CASE LIKE AVERAGING IS A

18

DIRTY TERM.

19

MATHEMATICAL PROCESSES, AND IT'S -- THERE ARE CERTAIN KINDS OF

20

DATA ANALYSIS THAT SIMPLY CAN'T BE DONE WITHOUT AVERAGING.

21

IT'S A FUNDAMENTAL WAY TO COMPARE DATA SETS TO ONE ANOTHER.

22

IT'S NOT.

IT'S ONE OF THE MOST FUNDAMENTAL

SO I THINK THAT YOU WOULD USE AVERAGING HERE FOR THE SAME

23

REASON YOU WOULD USE IT ANYWHERE, WHICH IS THAT WHEN YOU'RE

24

TRYING TO DISPLAY IN A WAY THAT'S EASY FOR SOMEONE LOOKING AT

25

IT TO SEE THE RELATIONSHIP OVER TIME, THAT AVERAGING IS USEFUL

UNITED STATES COURT REPORTERS

211

50

1

FOR THAT PURPOSE.

2

YOU KNOW, DR. LEAMER TESTIFIED TO THIS AT HIS DEPO BECAUSE

3

HE WAS ASKED, I THINK, PRETTY MUCH THE SAME QUESTION AND HE

4

SAID, "YOU KNOW, WHEN I -- WHEN I TEACH STUDENTS ECONOMETRICS,

5

I SHOW THEM A CHART FULL OF NUMBERS AND THEN I SHOW THEM A

6

GRAPH WITH A LINE THAT REPRESENTS THOSE NUMBERS AND I SAY, WHEN

7

YOU LOOK AT THAT LINE, OR THAT CURVE OR WHATEVER IT IS, YOU ARE

8

SEEING WHAT YOU NEED TO SEE."

9
10

IT'S MORE USEFUL, IT'S MORE INFORMATIVE THAN LOOKING AT A
CHART FULL OF NUMBERS.

11

THE COURT:

AND IS IT THE PLAINTIFFS' POSITION THAT

12

THESE ARE REPRESENTATIVE OF HOW THE REST OF THE CLASS'S

13

ANALYSIS WOULD SIMILARLY COME OUT?

14

MADE A LOT OF THE FACT THAT THESE ARE JUST SORT OF TEN LIMITED

15

TITLES AT TWO OF THE MULTIPLE DEFENDANTS HERE.

16

MR. GLACKIN:

OR -- I KNOW THE DEFENDANTS

SO LET ME -- AND I APOLOGIZE, I NEED

17

TO STEP BACK A MINUTE AND MAKE ONE CORRECTION, WHICH IS, AGAIN,

18

THESE ARE NOT, STRICTLY SPEAKING, AVERAGES.

19
20

WHAT THEY ARE IS THE PREDICTED -- THE DOLLAR VALUE THAT'S
PREDICTED BY THE REGRESSION BASED ON AN AGGREGATE DATA SET.

21

IT'S NOT -- BUT IT'S -- BUT "AVERAGE" IS AN OKAY TERM TO

22

USE.

23

REPRESENTATION OF AGGREGATE DATA USING ONE LINE, SO IT'S AN

24

AVERAGE KIND OF IN THAT SENSE.

25

I MEAN, IT'S CLOSE ENOUGH, I GUESS.

IT IS DEFINITELY A

SO WHAT WOULD WE SAY ABOUT THE REST OF THE DATA?

UNITED STATES COURT REPORTERS

212

51

1

WELL, I THINK -- AGAIN, I MEAN, THE PURPOSE HERE WAS TO,

2

WAS TO ATTEMPT TO FALSIFY, AND SO DR. LEAMER DID NOT DO THIS --

3

I MEAN, HE CERTAINLY HASN'T SHOWN US EVERY JOB TITLE.

4

SHOWN US AN ILLUSTRATION --

5
6

THE COURT:

I DON'T

UNDERSTAND THE CONTEXT IN WHICH YOU'RE USING THAT WORD.

7
8

YOU KEEP SAYING "FALSIFY."

HE'S

MR. GLACKIN:

SURE, OKAY.

WELL, THIS IS ONE OF MY

FAVORITE TOPICS.

9

THE COURT:

10

OKAY.

MR. GLACKIN:

11

KEEP IT SHORT THEN.

WELL --

(LAUGHTER.)

12

MR. GLACKIN:

13

I'LL TRY.

I'LL REALLY TRY.

SO THE CONCEPT OF FALSIFICATION IS CRUCIAL TO THE

14

SCIENTIFIC METHOD.

15

SCIENCE IN PARTICULAR, IT'S VERY HARD TO CONCLUSIVELY PROVE

16

ANYTHING EMPIRICALLY, AND IN ECONOMICS, IT'S PRETTY MUCH

17

IMPOSSIBLE.

18

IN SCIENCE IN GENERAL, AND IN SOCIAL

WHAT YOU CAN DO IS YOU CAN PROPOSE A THEORY AND THEN YOU

19

CAN TEST IT, AND IF YOUR THEORY DOESN'T FAIL, THAT IS

20

INFERENTIAL SUPPORT THAT YOUR THEORY IS VALID.

21

HYPOTHETICAL BECOMES A THEORY UNDER THE SCIENTIFIC METHOD.

22

THAT'S HOW A

AND SO WHAT DR. LEAMER IS DOING HERE IS HE'S SAYING,

23

"HERE'S AN EXAMPLE OF ME ASKING MYSELF IF I'M WRONG.

I LOOK AT

24

THESE CHARTS AND I DON'T NEED THEM TO COME OUT A PARTICULAR

25

WAY.

I DON'T NEED THE LINES TO BE IN A PARTICULAR PLACE.

UNITED STATES COURT REPORTERS

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1

"BUT THESE CHARTS TELL ME THAT MY CORRELATION ANALYSIS

2

DOESN'T HAVE THIS MAJOR PROBLEM, WHICH IS THIS YEARLY RESET

3

SORT OF HYPOTHETICAL, THAT I WAS AFRAID OF.

4

"AND SO, THEREFORE, THAT MAJOR PROBLEM NOT BEING THERE, I

5

AM MORE CONFIDENT IN MY CORRELATION ANALYSIS, WHICH I AM

6

OTHERWISE CONFIDENT IN."

7

THE COURT:

BUT HOW CAN WE EXTRAPOLATE FROM THESE

8

TEN JOB TITLES AT TWO DEFENDANTS THAT THAT WOULD SIMILARLY BE

9

REFLECTED IF THE SAME ANALYSIS WAS DONE FOR ALL THE OTHER JOB

10

TITLES IN THE ALL EMPLOYEE CLASS FOR ALL DEFENDANTS?

11

MR. GLACKIN:

WELL, I GUESS WHAT I WOULD SAY IS

12

THAT -- I MEAN, THERE'S -- THERE'S 500 -- THERE'S 100,000

13

EMPLOYEES.

14

THERE'S 500,000 OBSERVATIONS.

YOU CANNOT CONCLUDE, FROM LOOKING AT THESE, THAT THE

15

ANSWER WOULD BE THE SAME IN EVERY CASE.

16

IT DOESN'T SAY THAT.

17

THIS IS A -- THIS IS A TEST FOR CLASS CERTIFICATION

18

PURPOSES.

19

FLAW EXISTS IN HIS MODEL.

20

I'D AGREE WITH THAT.

THIS SHOWS DR. LEAMER ASKING HIMSELF IF THIS MAJOR

THE COURT:

HE DOESN'T SEE IT, SO WE MOVE ON.

WHAT ABOUT 20 AND 22, PLEASE?

21

I'M UNCLEAR ON WHAT --

22

MR. GLACKIN:

WHAT --

I WILL SAY, IF I CAN JUST POINT ONE

23

THING OUT, THOUGH, WHICH IS THAT -- I MEAN, THESE WERE AT APPLE

24

AND GOOGLE.

25

ASKED ABOUT AT DR. LEAMER'S DEPOSITION -- THESE WERE TITLES FOR

THEY WERE MAJOR TITLES -- AND I BELIEVE THIS WAS

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53

1

WHICH THERE WERE A LOT OF OBSERVATIONS.

2

OF PEOPLE THAT -- A BUNCH OF TITLES THAT WERE INCONSEQUENTIAL

3

TO THE COMPANY I GUESS IS WHAT I WOULD SAY.

4

THE COURT:

WE DIDN'T PICK A BUNCH

LET ME ASK, WITH YOUR 100,000 ALL

5

EMPLOYEE CLASS, AND WITH 60,000 IN THE TECHNICAL ALTERNATIVE

6

CLASS -- NEVER MIND.

I'LL STRIKE THAT QUESTION.

7

MR. GLACKIN:

8

THE COURT:

9

TELL ME ABOUT FIGURES 20 AND 22?

10

OKAY.

LET'S GO AHEAD.

MR. GLACKIN:

OKAY.

SO WHAT ELSE CAN YOU

SO NOW WE ARE AT THE, AT WHAT'S

11

BEEN SOMEHOW -- SOMEBODY CALLED THIS THE CONDUCT REGRESSION AND

12

THAT STUCK AND SO PEOPLE CALL IT THE CONDUCT REGRESSION, AND

13

THIS IS THE REGRESSION ANALYSIS -- THE CORRELATION ANALYSIS WE

14

DISCUSSED IS ALSO A REGRESSION.

15

INCLUDES DEPENDENT VARIABLES, A DEPENDENT VARIABLE, AND

16

ATTEMPTS TO ESTIMATE THE EFFECT OF THE ANTICOMPETITIVE

17

AGREEMENTS.

18
19
20

THIS IS THE REGRESSION THAT

I WILL TELL YOU AS MUCH AS I CAN ABOUT THE REGRESSION
OUTPUTS.
SO IF YOU LOOK AT FIGURE 20, THIS IS THE REGRESSION OUTPUT

21

FOR THE ALL SALARY CLASS.

AND WHAT THAT MEANS IS YOU PUT THE

22

DATA IN, YOU WRITE CODE IN STATA, I THINK THEY -- I DON'T KNOW

23

WHICH OF THE TWO PROGRAMS THEY USE, BUT STATA IS COMMON -- YOU

24

HIT ENTER, AND IT ESTIMATES THESE COEFFICIENTS FOR THESE

25

DIFFERENT VARIABLES.

UNITED STATES COURT REPORTERS

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54

1
2
3
4
5
6
7
8
9

AND THE CONDUCT IS AT 1 THROUGH 4.

I BELIEVE THAT'S

WHAT'S BEING ESTIMATED.
AND THEN THE VARIABLES BELOW THAT ARE THE VARIABLES THAT
ARE DOING THE ESTIMATING.
THE COURT:

HOPEFULLY I GOT THAT RIGHT.

WELL, I JUST DON'T KNOW WHAT -- IS THIS

SHOWING UNDERCOMPENSATION?
MR. GLACKIN:

WHAT IS THIS SHOWING?

YES.

AND I JUST HAVE TO CONFESS,

I'M -- I CAN'T POINT TO -- THE RESULT OF THESE -THE COURT:

IS THIS ALL HYPOTHETICAL?

OR THIS IS

10

THE SAME THING WHERE YOU TOOK AGGREGATED DATA OF ALL EMPLOYEES

11

OF ALL DEFENDANTS?

12

MR. GLACKIN:

WELL, WE DIDN'T TAKE -- SO WE DID NOT

13

TAKE -- I JUST WANT TO BE CAREFUL ABOUT TERMS.

14

WE DIDN'T START WITH AGGREGATE DATA.

WE STARTED WITH THE

15

WHOLE TRANSACTIONAL DATABASE -- EXCUSE ME -- THE WHOLE

16

COMPENSATION DATABASE.

17

OBSERVATIONS A YEAR FOR HOWEVER MANY YEARS.

18
19
20
21
22
23
24
25

SO ALL 500,000 OBSERVATIONS, 100,000

AND -THE COURT:

AND "OBSERVATION" BEING THE TOTAL

COMPENSATION FOR A SINGLE EMPLOYEE AT A DEFENDANT?
MR. GLACKIN:

CORRECT, WHAT SOMEBODY WAS PAID IN A

YEAR, IN A PARTICULAR YEAR IS AN OBSERVATION.
AND WE ASKED -- YES, THAT WAS THE DATA SET THAT WAS USED
TO ESTIMATE THIS.
AND THEN DR. LEAMER HAS PROGRAMMED A STATISTICAL

UNITED STATES COURT REPORTERS

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55

1

REGRESSION ANALYSIS THAT ATTEMPTS TO ANSWER THE QUESTION OF

2

WHAT COMPENSATION -- WHAT THEIR COMPENSATION SHOULD HAVE BEEN

3

IF THE AGREEMENTS HAD NOT BEEN IN PLACE.

4

THE COURT:

SO THIS DEPENDENT VARIABLE THAT'S AT THE

5

TOP OF FIGURE 20, THAT'S THE HYPOTHETICAL INDIVIDUAL'S

6

COMPENSATION?

7

THAT YOU ANALYZED?

8
9

OR THAT'S AN AVERAGE OF ALL OF THE OBSERVATIONS
WHAT IS THAT NUMBER?

MR. GLACKIN:

RIGHT.

SO WHAT -- I'M -- AND THE ONLY

REASON I'M GETTING TRIPPED UP A LITTLE BIT IS BECAUSE THE

10

EXACT -- WHAT EXACTLY EACH OF THESE REPRESENTS I'M -- I WANT TO

11

BE VERY CAREFUL ABOUT WHAT I SAY.

12

THE EASIEST WAY FOR ME TO EXPLAIN IT IS WHAT THE

13

REGRESSION DOES IS IT ESTIMATES, USING ALL THIS DATA, A SINGLE

14

VARIABLE FOR IMPACT OF THE AGREEMENTS, AND I THINK THAT MIGHT

15

BE THE QUESTION YOU'RE TRYING -- YOU'RE GETTING TO, AND I WILL

16

ADMIT THAT THAT IS WHAT IT DOES.

17

VARIABLE REPRESENTING THE ESTIMATED EFFECT OF THE AGREEMENTS.

18

IT IS ESTIMATING A SINGLE

AND I CAN TELL YOU THAT IN BROAD TERMS WHAT IT'S DOING IS

19

IT'S LOOKING AT THE RELATIONSHIP OF COMPENSATION OF EMPLOYEES

20

IN YEARS PRIOR TO AND AFTER THE CONSPIRACY.

21

THE RELATIONSHIP BETWEEN COMPENSATION AND CERTAIN KNOWN

22

VARIABLES, LIKE AGE COMPOSITION -- EXCUSE ME -- LIKE

23

UNEMPLOYMENT IN SANTA CLARA, OR THE EMPLOYMENT RATE IN

24

SANTA CLARA COUNTY WAS USED TO -- EXCUSE ME -- REPRESENT THE

25

ROBUSTNESS OR THE HEALTH OF THE TECHNOLOGY SECTOR IN WHICH

UNITED STATES COURT REPORTERS

IT'S LOOKING AT

217

56

1

THESE COMPANIES OPERATE.

2

IT ESTIMATES THE RELATIONSHIP BETWEEN COMPENSATION AND

3

THAT -- AND A SET OF VARIABLES LIKE THAT, AND THEN IT ASKS,

4

ASSUMING THAT THAT RELATIONSHIP IS MEANINGFUL, WHAT WAS THE

5

EFFECT OF -- WHAT SHOULD HAVE BEEN THE COMPENSATION THAT WAS

6

PAID DURING THE PERIOD UNDER STUDY?

7

AND THEN THAT IS EXPRESSED AS A VARIABLE.

AND THEN IT IS

8

POSSIBLE, USING THAT VARIABLE, TO DERIVE THE -- WELL, AND THEN

9

THE NEXT STEP ACTUALLY IS IN ORDER TO ACCOUNT FOR THE

10

HETEROGENEITY AT THESE FIRMS, IN ORDER TO ACCOUNT FOR THE FACT

11

THAT THEY'RE NOT ALL THE SAME, DR. LEAMER HAS THEN, FOR EVERY

12

FIRM, TAKEN THE CONDUCT VARIABLE AND ALLOWED IT TO BE CHANGED

13

DEPENDING ON FIRM-SPECIFIC FACTORS, SUCH AS A COMPANY'S

14

REVENUES, SUCH AS THE AGE COMPOSITION OF THE WORK FORCE.

15
16

THE COURT:

IS THAT THE MINUS 1 AND MINUS 2?

IS

THAT 5 THROUGH 18?

17

MR. GLACKIN:

YES.

I THINK THAT'S PROBABLY -- YOU

18

KNOW, THAT IS PROBABLY REPRESENTING EXACTLY THE INTERACTIVE

19

RESULT.

20

AND THEN USING THAT DIFFERENT VARIABLE, THE NEW VARIABLE

21

FOR EVERY COMPANY FOR EACH YEAR, DR. LEAMER THEN IS ABLE TO

22

GENERATE AN ESTIMATE OF THE PERCENTAGE BY WHICH TOTAL

23

COMPENSATION WAS REDUCED AT THE COMPANY.

24
25

THE COURT:

SO SOMEHOW HE'S ABLE TO CALCULATE HOW

MUCH EACH EMPLOYEE SHOULD HAVE BEEN PAID AND WHAT PERCENTAGE OF

UNITED STATES COURT REPORTERS

218

57

1

WHAT THEY WERE PAID THAT DELTA IS?

2

SHOWING?

3

MR. GLACKIN:

4

THE COURT:

5

WHAT IS THAT?

6

CORRECT.

IS THAT WHAT THIS IS

WELL, WHAT HE'S --

WHAT IS THIS IN THIS ESTIMATE COLUMN?

THAT'S SAYING HOW MUCH OF THE TOTAL

COMPENSATION --

7

MR. GLACKIN:

8

THE COURT:

9

MR. GLACKIN:

I'M ONLY -- SORRY.

GO AHEAD.
I'M ONLY HESITATING BECAUSE I DON'T

10

THINK THAT -- I DON'T KNOW THAT YOU CAN LOOK AT, FOR EXAMPLE,

11

THE LINE CONDUCT AND SAY THAT THAT MEANS MINUS 16 PERCENT.

12

DON'T THINK THAT THAT'S EXACTLY HOW YOU INTERPRET THAT.

13

I

BUT WHAT THAT IS IS -- IT REPRESENTS THE DELTA, IF YOU

14

WILL, BETWEEN WHAT THE REGRESSION PREDICTS PEOPLE SHOULD HAVE

15

BEEN PAID AND WHAT THEY WERE ACTUALLY PAID.

16

AND IT'S -- STRICTLY SPEAKING, IT'S THE DELTA BETWEEN THE

17

TOTAL COMPENSATION, THE PREDICTED TOTAL COMPENSATION AT THE

18

FIRM AND THE ACTUAL COMPENSATION.

19

THE COURT:

AND HOW DID HE COME UP WITH THE

20

PREDICTED COMPENSATION?

21

MR. GLACKIN:

SO IN -- BY -- THE WAY REGRESSION

22

ANALYSIS WORKS IS YOU PICK A SET OF VARIABLES THAT ARE CALLED

23

THE EXPLANATORY VARIABLES, AND THESE ARE THE VARIABLES THAT YOU

24

THINK SHOULD EXPLAIN COMPENSATION, AND YOU EXAMINE THE

25

RELATIONSHIP BETWEEN THE EXPLANATORY VARIABLES AND COMPENSATION

UNITED STATES COURT REPORTERS

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58

1

DURING A TIME PERIOD NOT AFFECTED BY THE AGREEMENTS AND YOU

2

EXPRESS THAT RELATIONSHIP IN NUMBERS.

3
4

AND I BELIEVE THAT THAT IS THE -- SOME OF THAT IS WHAT'S
HERE IN THE REGRESSION OUTPUT.

5

THEN YOU ASK YOURSELF, IF THOSE RELATIONSHIPS ARE STEADY,

6

AND THERE'S NO REASON TO BELIEVE THEY'RE NOT -- AND THAT'S ONE

7

THING WE TEST FOR, I THINK, AS YOU'RE DOING THE REGRESSION,

8

WHAT SHOULD HAVE BEEN COMPENSATION DURING THE PERIOD THAT THE

9

AGREEMENTS WERE IN EFFECT?

10

I MEAN, LIKE A -- THIS IS A TOTALLY SIMPLISTIC WAY TO LOOK

11

AT IT, BUT SUPPOSE YOU SHOW THAT, OR YOU -- YOUR REGRESSION

12

SHOWS THAT WHEN A COMPANY'S REVENUES GO UP, WORKER COMPENSATION

13

TENDS TO GO UP BY A CERTAIN AMOUNT.

14

BETWEEN INCREASED REVENUES AT A COMPANY AND WORKER

15

COMPENSATION.

16

THERE'S A RELATIONSHIP

THEN YOU LOOK AT THE PERIOD UNDER STUDY AND YOU ASK

17

YOURSELF, WELL, IN THIS AREA WHERE -- YOU KNOW, DURING THIS

18

PERIOD OF TIME WHEN COMPETITION WAS RESTRAINED, DOES THE --

19

DOES THAT RELATIONSHIP APPEAR TO BE RESPECTED?

20

IN REVENUES OR A DIMINISHMENT IN REVENUES HAVING THE EXPECTED

21

EFFECT ON COMPENSATION?

22
23
24
25

IS AN INCREASE

THAT'S THE QUESTION YOU'RE ASKING.

YOU PREDICT THAT, SEEING A COMPANY'S REVENUES GO UP, THE
COMPENSATION SHOULD GO UP BY A CERTAIN AMOUNT.
AND IF YOU SEE THAT NOT HAPPENING, THE REGRESSION IS
TELLING YOU THAT THAT'S THE EFFECT OF THE THING THAT YOU'RE

UNITED STATES COURT REPORTERS

220

59

1
2

STUDYING.
AND THAT'S -- THIS IS A VERY UNEDUCATED WAY FOR ME OF --

3

BECAUSE I'VE REACHED THE LIMITS, I THINK, OF WHAT I CAN

4

EXPLAIN.

5

THE COURT:

WHAT ABOUT FIGURE 22?

6

MR. GLACKIN:

WHAT IS THIS?

SO FIGURE 22 IS TAKING THIS VALUE --

7

SO WHAT THE -- WHAT THE REGRESSION TELLS YOU IS THE VALUE OF

8

THE CONDUCT VARIABLE, AND IF YOU APPLY THE CONDUCT VARIABLE TO

9

TOTAL COMPENSATION, OR -- IT TELLS YOU THE -- THE REGRESSION

10

TELLS YOU THE COMPENSATION THAT SHOULD HAVE BEEN.

11

HERE ON 22 IS THE AMOUNT BY WHICH ACTUAL COMPENSATION WAS LOWER

12

THAN THE COMPENSATION THAT SHOULD HAVE BEEN.

13

THE COURT:

THIS FIGURE

SO EVERY INDIVIDUAL EMPLOYEE OF THESE

14

COMPANIES RECEIVED THIS LEVEL, THIS PERCENTAGE REDUCTION IN

15

THEIR TOTAL COMPENSATION BECAUSE OF THE AGREEMENTS?

16

MR. GLACKIN:

17

THE COURT:

18

MR. GLACKIN:

NO, NO.

THAT'S NOT WHAT WE'RE SAYING.

OKAY.
WHAT WE'RE SAYING IS THAT, FOR

19

EXAMPLE, IN 2005 AT ADOBE, THE TOTAL COMPENSATION PAID TO

20

EMPLOYEES WAS 1.6 PERCENT LOWER THAN THE REGRESSION PREDICTS IT

21

SHOULD HAVE BEEN.

22

THE COURT:

BECAUSE OF THE AGREEMENTS?

23

MR. GLACKIN:

BECAUSE OF THE AGREEMENTS, EXACTLY.

24

BECAUSE THE ONLY THING THAT'S DIFFERENT ABOUT THE TWO PERIODS

25

OF TIME YOU'RE STUDYING IS THE AGREEMENTS.

UNITED STATES COURT REPORTERS

221

60

1
2

THE COURT:

BUT THAT APPLIES TO EVERY EMPLOYEE'S

COMPENSATION AT ADOBE IN THAT YEAR.

3

MR. GLACKIN:

RIGHT?

WELL, IT APPLIES IN THE SENSE THAT

4

EVERY, EVERY MEMBER OF THE CLASS WAS PAID OUT OF THAT PILE OF

5

MONEY, OUT OF THAT TOTAL COMPENSATION.

6

IT DOESN'T APPLY -- WE ARE NOT SAYING THAT THERE WAS A 1.6

7

PERCENT -- THAT IT WAS 1.6 PERCENT FOR EVERY EMPLOYEE.

8

CAN'T -- WE CANNOT ESTIMATE --

9

THE COURT:

WE

OH, YOU'RE SAYING IN TOTAL, THE TOTAL

10

COMPENSATION WAS THAT MUCH LESS?

11

MR. GLACKIN:

12

THE COURT:

13

MR. GLACKIN:

EXACTLY.

I SEE.
TOTAL -- SO IN 2005, ADOBE PAID ITS

14

EMPLOYEES A MILLION DOLLARS -- A BILLION DOLLARS AND, IN

15

REALITY, ADOBE SHOULD HAVE PAID ITS EMPLOYEES 1.6 PERCENT MORE

16

THAN THAT.

17
18

THE COURT:

I SEE.

OKAY.

ALL RIGHT.

I HAVE SOME

MORE QUESTIONS, BUT I'D LIKE TO --

19

LET ME ASK MS. SHORTRIDGE --

20

(DISCUSSION OFF THE RECORD BETWEEN THE COURT AND THE COURT

21
22
23
24
25

REPORTER.)
THE COURT:

AND I DO WANT TO HANDLE THE CMC AND TALK

ABOUT DISCOVERY.
LET ME ASK, SINCE WE DON'T HAVE THE DATA ON WHO WOULD HAVE
BEEN COLD CALLED AND HOW MANY COLD CALLS WOULD HAVE ACTUALLY

UNITED STATES COURT REPORTERS

222

61

1

BEEN CONDUCTED AND A LOT OF THE DATA IS NOT TRANSPARENT FROM

2

THE PAYROLL RECORDS, WHICH ARE SORT OF THE LIMITED UNIVERSE OF

3

WHAT DOES EXIST IN TERMS OF DOCUMENTATION, WHAT IS THERE TO

4

LINK THE DO NOT COLD CALL AGREEMENTS WITH DECREASED MOBILITY?

5

MR. GLACKIN:

SO YOU'RE ASKING -- I GUESS, WHEN YOU

6

SAY WHAT IS IT, ARE YOU ASKING ME FROM A DATA PERSPECTIVE OR A

7

THEORY PERSPECTIVE OR FROM A DOCUMENTARY EVIDENCE PERSPECTIVE?

8
9
10

THE COURT:

WELL, I GUESS I'M ASKING YOU FROM A

HOW DO WE FIND DR. LEAMER AS NOT OVERLY SPECULATIVE
PERSPECTIVE?

11

MR. GLACKIN:

12

THE COURT:

13

MR. GLACKIN:

OKAY.

YEAH.
SO FIRST OF ALL, THE ECONOMIC THEORY

14

PREDICTS THAT REDUCED COLD CALLING WOULD HAVE THIS KIND OF

15

EFFECT.

16

THE COURT:

UM-HUM.

17

MR. GLACKIN:

AND IT'S NOT FRINGE ECONOMIC THEORY.

18

THIS IS MAIN STREAM, NOBEL PRIZE WINNING ECONOMIC THEORY.

19

SO THE THING THAT DR. LEAMER DID FROM A QUANTITATIVE

20

STANDPOINT TO TEST FOR WHAT HE CALLS THE PRICE DISCOVERY

21

PROCESS WAS THAT WAS THE MOVERS AND STAYERS ANALYSIS, AND WHAT

22

DR. LEAMER IS DOING THERE -- AND I CAN POINT YOU TO THE CHART

23

IF YOU WANT TO SEE IT.

24

RIGHT, PAGE 37 AND PAGE 38.

25

I THINK IT'S PAGE 37 AND PAGE 38.

SO THE PREMISE OF THE PRICE DISCOVERY THEORY IS THAT LABOR

UNITED STATES COURT REPORTERS

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1

IS NOT A COMMODITY, AND THAT PEOPLE AREN'T PAID LIKE YOU SELL

2

PORK BELLIES ON THE CBOT, AND THAT WAGES ARE -- THAT PEOPLE --

3

THAT WORKERS AND EMPLOYERS IN THE MARKET ARE CONSTANTLY LOOKING

4

FOR BETTER PRICE OR THE RIGHT PRICE FOR THEIR -- FOR THE SKILLS

5

THAT THEY ARE SEEKING TO BUY OR SELL.

6

NOW, IF YOU -- ONE SYMPTOM OF THAT, IF THAT'S TRUE, ONE

7

SYMPTOM OF THAT WOULD BE THAT WHEN PEOPLE LEAVE A COMPANY, THEY

8

SEE INCREASES IN THEIR PAY, AND IF YOU ASKED YOURSELF WHAT

9

HAPPENS TO PEOPLE WHEN THEY LEAVE THEIR COMPANY AND THE ANSWER

10

WAS THEY DIDN'T GET A BIG BUMP IN PAY, RIGHT, THAT WOULD

11

SUGGEST THAT THERE IS NOT -- YOU'RE WORKING WITH A MARKET WHERE

12

THERE ISN'T AN INFORMATION IMPERFECTION AND THAT EVERYBODY DOES

13

KNOW, SORT OF A PRIORI, WHAT THEY'RE WORTH.

14

SO DR. LEAMER -- WE WERE ABLE -- AGAIN, WE WERE WORKING

15

WITH THE DATA WE HAVE.

16

COMPENSATION THAT PEOPLE EXPERIENCE WHEN THEY MOVE BETWEEN

17

THESE FIRMS BECAUSE WE COULD TRACK THEM USING UNIQUE

18

IDENTIFICATION.

19

WE WERE ABLE TO LOOK AT THE CHANGE IN

AND WHAT WE -- WHAT DR. LEAMER SAW IS THAT WHEN PEOPLE

20

MOVE FIRMS, THEY GOT A BIG PAY RAISE.

21

SURPRISING, ESPECIALLY IN THIS CONTEXT BECAUSE, AGAIN, WE'RE

22

NOT TALKING ABOUT COMMODITIES AND WE'RE NOT -- WE'RE ALSO NOT

23

TALKING ABOUT PEOPLE WHO ARE WORKING FOR MINIMUM WAGE AT A FAST

24

FOOD RESTAURANT.

25

AND THAT'S NOT

THESE ARE SKILLED WORK FORCES.

SO THAT CONFIRMS THAT THERE -- THAT THERE IS AN

UNITED STATES COURT REPORTERS

224

63

1

INFORMATION PROBLEM IN THIS MARKET, THAT THE PEOPLE IN THE

2

MARKET DON'T HAVE PERFECT INFORMATION, THAT THEY ARE LOOKING TO

3

GET A BETTER PRICE FOR THEIR SKILLS, AND THAT WHEN THEY MOVE

4

FROM ONE DEFENDANT TO ANOTHER, THEY DO, ON AVERAGE, GET A MUCH

5

BETTER PRICE FOR THEIR SKILLS.

6

THAT'S WHAT THIS SHOWS.

SO, AGAIN, IT'S AN ATTEMPT TO SAY -- IT'S AN ATTEMPT TO

7

QUESTION, IS THIS THING THAT STANDARD ECONOMIC THEORY PREDICTS,

8

IS IT TRUE OF THIS MARKET WHERE I BELIEVE IT IS TRUE?

9

THIS TEST.

10

I'LL RUN

I -- THE TEST IS CONSISTENT WITH WHAT I WOULD

PREDICT, SO THAT IS A REASON FOR ME TO BELIEVE I AM CORRECT.

11

THE COURT:

HOW DO YOU EXPLAIN THAT THERE HAVEN'T

12

BEEN MANY HIRES AMONGST THE DEFENDANTS AFTER THE INJUNCTION WAS

13

ENTERED IN THE D.O.J. CASE IN D.C.?

14
15
16
17
18

MR. GLACKIN:

SO THAT'S AN EXCELLENT QUESTION.

THAT'S A VERY INTERESTING QUESTION ACTUALLY.
I DON'T -- I CAN'T -- I DON'T HAVE THE EXPLANATION FOR WHY
THAT IS.
I DO KNOW THAT IN SOME OF THE DEPOSITIONS THAT HAVE

19

OCCURRED -- AT LEAST, I KNOW OF ONE WHERE THE WITNESS TESTIFIED

20

THAT THE COMPANY, NOTWITHSTANDING THE INJUNCTION, CONTINUES TO

21

UNILATERALLY, SUPPOSEDLY UNILATERALLY SIMPLY NOT HIRE FROM THE

22

COMPANY WITH WHICH IT PREVIOUSLY HAD AN AGREEMENT.

23

SO IT MIGHT BE THAT THEY ARE CONTINUING TO VIOLATE THE

24

LAW, OR IT MIGHT BE THAT THEY HAVE ALL -- THEY'RE NOT TALKING

25

TO EACH OTHER, BUT THEY ARE ALL UNILATERALLY DECIDING TO

UNITED STATES COURT REPORTERS

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1

CONTINUE TO NOT POACH EACH OTHER'S EMPLOYEES, OR IT MIGHT BE

2

SOME OTHER REASON.

3

EXPLAIN THAT.

4

I DON'T HAVE THE -- WE HAVEN'T TRIED TO

THE COURT:

UM-HUM.

5

OKAY.

LET ME ASK THE DEFENDANTS A FEW QUESTIONS.

6

YOUR EXPERT, DR. MURPHY, FOCUSES ONLY ON PEOPLE WHO

7

ACTUALLY LEFT ONE OF THE DEFENDANT COMPANIES FOR ONE OF THE

8

CO-DEFENDANTS, AND I FIND DR. LEAMER'S THEORY THAT THAT'S TOO

9

LIMITED IN HOW YOU LOOK AT ANY POTENTIAL DAMAGE PERSUASIVE

10

BECAUSE, AS YOU SAID, IF AN EMPLOYEE GETS A BETTER OFFER FROM

11

ANOTHER COMPANY, THEY CAN VERY MUCH GO AND TRY TO NEGOTIATE AN

12

INCREASE IN THEIR OWN SALARY FROM THEIR CURRENT EMPLOYER.

13

AND SO WHY SHOULDN'T THAT BE TAKEN INTO ACCOUNT IN

14

DETERMINING WHETHER THERE'S DAMAGE VERSUS JUST LOOKING AT WHO'S

15

ACTUALLY MOVED, THE MOBILITY VERSUS ACTUAL MOVEMENT SORT OF

16

DISTINCTION THAT DR. LEAMER MAKES?

17

MR. MITTELSTAEDT:

WELL, DR. MURPHY LOOKED AT

18

MOVEMENT FOR A DIFFERENT REASON.

19

PERCENT OF THE EMPLOYEES WHO LEFT THESE DEFENDANTS OR CAME TO

20

THESE DEFENDANTS CAME FROM NON-DEFENDANTS.

21

THE COURT:

22

HIS POINT ON MOVEMENT WAS 99

AGREEMENTS IN EFFECT.

23
24
25

BECAUSE THERE WERE THESE COLLUSIVE

MR. MITTELSTAEDT:
BEFORE THE AGREEMENT.

NO, BEFORE.

BEFORE, YOUR HONOR.

IT DIDN'T CHANGE DURING THE AGREEMENT.

AND THE POINT THAT MAKES IS THESE AGREEMENTS AFFECTED SUCH

UNITED STATES COURT REPORTERS

226

65

1

A SMALL PERCENT OF THE MARKET THAT THERE WOULD BE NO REASON TO

2

THINK THERE WOULD BE ANY MEASURABLE OR BROAD IMPACT AT ALL, AND

3

EVEN FOR THE COMPANIES THAT HAD NO COLD CALL AGREEMENTS.

4

THE INFORMATION THAT AN EMPLOYEE WOULD HAVE RECEIVED WOULD

5

HAVE BEEN REPLACED -- OR WOULD HAVE COME FROM SOMEPLACE ELSE

6

BECAUSE THAT PERSON CONTINUED TO GET COLD CALLS IF THEY WERE

7

GETTING COLD CALLS FROM ALL THE --

8
9

THE COURT:

I THOUGHT THAT HE LIMITED HIS DATA TO

JUST DURING THE CLASS PERIOD AND AFTER, WHEREAS DR. LEAMER

10

LOOKED AT BEFORE THE CLASS PERIOD, DURING THE CLASS PERIOD, AND

11

THEN AFTER.

12

MR. MITTELSTAEDT:

13

THE COURT:

I THINK -- I THINK THIS --

DR. MURPHY LOOKED --

14

NO.

ISN'T THAT IN ONE INSTANCE WHERE

15

DR. MURPHY ONLY LOOKED AT THE CLASS PERIOD AND THEN TWO

16

YEARS -- HE LOOKED AT 2010/2011, BUT DID NOT ANALYZE THE PRE --

17

MR. MITTELSTAEDT:

18
19

THE COURT:
INSTANCE.

20
21
22

I THINK --

-- PERIOD.

I KNOW THAT OCCURRED IN ONE

I CAN'T REMEMBER EXACTLY THE CONTEXT.
MR. GLACKIN:

EXCUSE ME.

I DIDN'T MEAN TO TALK OVER

YOU.
YOU MIGHT BE THINKING OF THE REGRESSION ANALYSIS WHERE

23

DR. MURPHY -- BASICALLY ONE OF HIS SENSITIVITY ANALYSES IS TO

24

ONLY USE HALF THE DATA AND RUN THE REGRESSION USING ONLY THE

25

AFTER PERIOD OR ONLY THE BEFORE PERIOD AND HE CLAIMS THAT

UNITED STATES COURT REPORTERS

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1

THAT'S PROBLEMATIC.

2

THAT MIGHT BE WHAT YOU'RE THINKING OF.

MR. MITTELSTAEDT:

YOUR HONOR, I'M REFERRING TO

3

MURPHY TABLE NUMBER 1 AT PAGE 8 AND APPENDIX 1A, WHICH SHOWS

4

BEFORE AS WELL.

5

BUT, YOUR HONOR, THERE IS A MUCH MORE FUNDAMENTAL PROBLEM

6

HERE, AND WHEN YOU WALK THROUGH WHAT LEAMER SUPPOSEDLY DID,

7

THAT WAS JUST NOT RIGHT.

8

LIKE TO, TO MAKE TWO POINTS.

9

THE COURT:

IT WAS JUST NOT RIGHT, AND I WOULD

CAN I ASK YOU, ALL OF THE DEFENDANTS'

10

POSITIONS SORT OF FLY IN THE FACE OF YOUR DOCUMENTS THAT WERE

11

CREATED CONTEMPORANEOUSLY.

12

CALLING CANDIDATES IS ONE OF THE MOST EFFICIENT AND EFFECTIVE

13

WAYS TO RECRUIT.

14

OFFER, THAT IT CAUSES UNHAPPINESS AND YOU HAVE TO HAVE A

15

SYSTEMATIC APPROACH TO COMPENSATION TO AVOID THESE BIDDING

16

WARS.

17

I MEAN, THE DOCUMENTS SAY COLD

IT TALKS ALL ABOUT WHEN PEOPLE GET A COUNTER

THAT I THINK IS THE BIGGEST PROBLEM FOR THE DEFENDANTS IS

18

THAT THE CONTEMPORANEOUS DOCUMENTS THAT WERE CREATED AT THE

19

TIME SORT OF ACKNOWLEDGE ALL OF THE EFFECTS THAT DR. LEAMER IS

20

TRYING TO PROVE.

21
22
23

I WILL AGREE THAT THERE ARE A LOT OF HOLES IN DR. LEAMER'S
ANALYSIS.
BUT ONE OF THE STRONGEST PIECES OF EVIDENCE THE PLAINTIFFS

24

HAVE IS YOUR OWN DOCUMENTS.

25

MR. MITTELSTAEDT:

I DON'T THINK THAT'S RIGHT, YOUR

UNITED STATES COURT REPORTERS

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1

HONOR.

2

THE COURT:

UM-HUM.

3

MR. MITTELSTAEDT:

THERE IS NOT A SINGLE DOCUMENT

4

THAT SAYS WE'VE GIVEN A RAISE TO SOMEBODY AND SO NOW WE'RE

5

GOING TO RAISE EVERYBODY ELSE IN THAT PERSON'S WORK GROUP, LET

6

ALONE THAT WE'RE GOING TO RAISE EVERYBODY IN THE REST OF THE

7

COMPANY, LET ALONE THAT ALL THE OTHER COMPANIES ARE GOING TO

8

FOLLOW.

9
10
11

THEY DO NOT SAY THAT.
THEY EXPRESS CONCERN ABOUT INTERNAL EQUITY.

THEY TAKE A

LOOK AT IT.

12

BUT, YOUR HONOR, IN THE BEFORE PERIOD, AS I SAID BEFORE,

13

IF THE PLAINTIFFS' RIPPLE THEORY WORKED, THERE WOULD BE A LOT

14

OF EVIDENCE IN IT, OF IT, AND IT WOULD BE IN THE DATA AND IT'S

15

NOT IN THE DATA.

16

THE COURT:

I MEAN, DO YOU WANT ME TO GET INTO THESE

17

E-MAILS?

18

DON'T TALK ABOUT IF SOMEONE GETS A BETTER OFFER FROM A

19

COMPETITOR, YOU HAVE TO MAKE THE DECISION OF WHETHER YOU WANT

20

TO KEEP THIS PERSON BY RAISING THEIR COMPENSATION OR LETTING

21

THEM GO AND HOW WE SHOULDN'T DEAL WITH THIS IN THIS WAY, THAT

22

WE SHOULD HAVE A SYSTEMATIC APPROACH SO WE'RE NOT HAVING TO BUY

23

PEOPLE OFF INDIVIDUALLY.

24
25

I'M HAPPY TO DO IT.

I DISAGREE WITH YOU THAT THEY

I MEAN, IF YOU WANT TO GET INTO THESE DOCUMENTS, I'M HAPPY
TO DO THAT.

BUT TO SAY THEY DON'T EXIST --

UNITED STATES COURT REPORTERS

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1

MR. MITTELSTAEDT:

2

THE COURT:

3

MR. MITTELSTAEDT:

4

THE COURT:

5

MR. MITTELSTAEDT:

6

-- I FIND IS REALLY PROBLEMATIC.
YOUR HONOR --

YEAH.
-- THE DOCUMENT I THINK YOU'RE

REFERRING TO, OR THE DOCUMENTS, TALK ABOUT INDIVIDUALS.

7

IF WE --

8
9

NO.

THE COURT:

AND THEY TALK ABOUT WHY THE INDIVIDUAL

METHOD OF DEALING WITH THIS IS INFERIOR TO HAVING A SYSTEMATIC

10

APPROACH TO AVOIDING THESE BIDDING WARS BY HAVING THESE

11

COLLUSIVE AGREEMENTS WITH THE OTHER CO-DEFENDANTS.

12

MR. MITTELSTAEDT:

13

THE COURT:

14

MR. MITTELSTAEDT:

BUT, YOUR HONOR --

YEAH.
-- THAT DOES NOT HELP DETERMINE

15

WHICH OF THE EMPLOYEES WERE IMPACTED AND WHICH ONES WERE NOT

16

AND WHICH ONES BENEFITED.

17

AND WHEN I SAY THAT, WHAT I MEAN IS FOR ANY EMPLOYEE WHO

18

MISSED OUT ON A COLD CALL AND, THEREFORE, DIDN'T GET THE CHANCE

19

TO NEGOTIATE A JOB RAISE OR GET A NEW JOB, SOMEBODY GOT THAT

20

JOB.

21
22
23

SOMEBODY GOT THAT JOB.
AND BECAUSE -- AND THEY'RE A CLASS MEMBER.

AND SO WHAT WE

HAVE HERE IN THIS GROUP -THE COURT:

SO HOW DO WE KNOW THAT THAT PERSON WHO

24

CAME FROM A NON-DEFENDANT WHO GOT THE JOB WOULDN'T HAVE BEEN

25

PAID MORE BUT FOR THESE COLLUSIVE AGREEMENTS?

UNITED STATES COURT REPORTERS

HOW DO YOU KNOW

230

69

1

THAT?

2

MR. MITTELSTAEDT:

WELL, THAT PERSON IS BETTER OFF

3

BECAUSE THAT PERSON TOOK THE JOB.

4

TAKEN THE JOB OTHERWISE?

5

I MEAN, WHY WOULD THEY HAVE

THEY GOT THE JOB THAT --

6

THE COURT:

BUT WOULD YOU AGREE THAT THEY COULD HAVE

7

POTENTIALLY BEEN PAID MORE, THAT THAT JOB COULD HAVE BEEN WORTH

8

MORE IF THESE AGREEMENTS DIDN'T EXIST?

9

MR. MITTELSTAEDT:

NO, I DON'T THINK THERE'S ANY

10

REASON TO THINK THAT BECAUSE OF THE 99 PERCENT POINT.

99

11

PERCENT OF THE MOVEMENT, MOBILITY, WHATEVER ANYONE WANTS TO

12

CALL IT, WAS UNAFFECTED BY ANY OF THIS.

13

BUT, YOUR HONOR, I REALLY WANT TO EXPLAIN, IF I CAN, WHAT

14

LEAMER IS DOING, BECAUSE THE ANSWERS YOU RECEIVED ARE JUST NOT

15

RIGHT, AND I'VE GOT -- AND I KNOW THAT, YOU KNOW, WE'RE SHORT

16

OF TIME, BUT I'VE HARDLY SAID ANYTHING AND I'VE GOT A BINDER

17

THAT WILL ALLOW ME TO WALK YOUR HONOR THROUGH WHAT'S REALLY

18

GOING ON HERE AS EXPEDITIOUSLY AS POSSIBLE, IF I CAN JUST DO

19

THIS.

20

THE COURT:

21

LOOKING QUITE THICK.

22

HOW MANY PAGES IS THAT BINDER?

MR. MITTELSTAEDT:

IT'S

WELL, I'LL SKIP -- I'LL JUST GO

23

TO THE LEAMER PART, WHICH IS 37 PAGES, AND I CAN WALK YOUR

24

HONOR THROUGH IT QUICK AND I WON'T GO THROUGH ALL OF THEM.

25

JUST WANT TO GIVE YOU A FLAVOR --

UNITED STATES COURT REPORTERS

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70

1

THE COURT:

HAVE YOU SHOWN THAT TO THE PLAINTIFFS?

2

MR. MITTELSTAEDT:

3

THE COURT:

YES.

WE GAVE IT TO THEM.

WHY DON'T I TAKE A COPY OF IT, I'LL

4

REVIEW IT DURING THE BREAK, AND IF I HAVE QUESTIONS, I CAN ASK

5

YOU SPECIFICALLY.

6

I MEAN, I AGREE WITH YOU, FRANKLY, BOTH EXPERTS -- BOTH

7

EXPERTS' REPORTS HAVE A LOT OF ISSUES.

8

I THINK BOTH HAVE --

9

MR. MITTELSTAEDT:

10
11

THE COURT:
ECONOMICS.

12

I'LL PUT IT THAT WAY.

YOUR HONOR --

-- A CONSIDERABLE AMOUNT OF CREATIVE

I'LL PUT IT THAT WAY.
MR. MITTELSTAEDT:

YOUR HONOR, THEY HAVE THE BURDEN

13

HERE, AND THEIR BURDEN, UNDER THEIR OWN METHOD, IS TO SHOW THAT

14

THERE'S THIS RIGID PAY STRUCTURE.

15

GETS A RAISE OR PROMOTION, EVERYBODY ELSE GETS A RAISE OR

16

PROMOTION.

17
18

IT'S SO RIGID IF ONE PERSON

THE DATA, WHICH IS IN THIS BINDER AT TABS 4 AND 6, SHOW
THAT THAT'S JUST NOT RIGHT.

19

THE COURT:

20

MR. MITTELSTAEDT:

THERE IS, AT TAB 4 --

TAB 4, OKAY.
-- THIS SHOWS THE DISTRIBUTION OF

21

ANNUAL CHANGES IN TOTAL COMPENSATION FOR THE TOP TEN GOOGLE

22

JOBS THAT THEY'VE PICKED, AND IT SHOWS THAT WITHIN ONE JOB

23

TYPE -- AND EACH OF THESE ARE THE TEN JOB TYPES AT THE

24

BOTTOM -- IT SHOWS THAT ANNUAL CHANGES FOR INDIVIDUALS VARY

25

EXTREMELY WIDELY.

UNITED STATES COURT REPORTERS

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THE FIRST YEAR, FOR EXAMPLE, A QUARTER --

2

THE COURT:

BUT CAN I ASK YOU, THERE ARE CERTAINLY A

3

LOT OF DOCUMENTS THAT WERE CREATED CONTEMPORANEOUSLY WHERE THE

4

DEFENDANTS SAY THAT THEY ARE CERTAINLY CONSIDERING INTERNAL

5

EQUITY.

6

MR. MITTELSTAEDT:

INTERNAL EQUITY MEANING FAIRNESS,

7

AND FAIRNESS MEANING THESE COMPANIES -- AND EACH OF THEM HAD

8

DIFFERENT PAY SYSTEMS, BUT WHAT THEY HAD IN COMMON WAS THEY

9

PAID FOR PERFORMANCE.

10

AND THE PLAINTIFFS INTERPRET "INTERNAL EQUITY" TO MEAN

11

THAT IF ONE PERSON GETS A RAISE, EVERYBODY GETS A RAISE, AND

12

THAT'S JUST NOT WHAT HAPPENED, AND THESE DATA SHOW THIS.

13

DATA THAT WE'RE LOOKING AT HERE SHOWS THAT WITHIN ONE JOB TYPE,

14

THERE'S A WIDE DISTRIBUTION OF THE ANNUAL CHANGES IN

15

COMPENSATION.

THE

16

SO A QUARTER -- JUST THE FIRST ONE, THE SOFTWARE ENGINEER

17

FOR GOOGLE THE FIRST YEAR, A QUARTER OF THE EMPLOYEES RECEIVED

18

A RAISE MORE THAN 80 PERCENT.

19

AND A QUARTER DROPPED.

20

THAT'S THE TOP OF THE PINK.

THE --

21

THE COURT:

A QUARTER WERE BELOW THAT.

AND I GUESS I DON'T AGREE WITH YOU THAT

22

THEIR POSITION REQUIRES RIGID LOCKSTEP, AND THEN IT REQUIRES

23

THE ABSOLUTE SCENARIO THAT YOU JUST DESCRIBED, THAT IF ONE

24

PERSON GETS A RAISE, EVERYONE GETS ONE.

25

IF WE'RE SAYING THESE ARE GENERAL TRENDS AND GENERALLY

UNITED STATES COURT REPORTERS

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1

THERE COULD BE INDIVIDUAL DEVIATIONS, BUT GENERALLY THAT THERE

2

IS SOME ATTENTION PAID BY THE DEFENDANTS TO OVERALL PAY

3

STRUCTURE --

4

MR. MITTELSTAEDT:

5

THE COURT:

WELL --

-- THAT, YOU KNOW, OVERALL -- THERE

6

COULD BE AN INDIVIDUAL DEVIATION, BUT THAT OVERALL THESE TRENDS

7

ARE TRUE.

8
9

MR. MITTELSTAEDT:

THE QUESTION IS, DO YOU HAVE

TO -- TO DETERMINE IF AN EMPLOYEE WOULD HAVE GOT A RAISE, DO

10

YOU HAVE TO GO EMPLOYEE BY EMPLOYEE?

11

CIRCUMSTANCE?

12
13
14

CIRCUMSTANCE BY

DEPARTMENT BY DEPARTMENT?

OR IS THERE SOME WAY TO SAY, WITH A WAVE OF A HAND,
EVERYBODY WOULD HAVE GOT A RAISE?
AND WHAT LEAMER TRIES TO DO, YOUR HONOR, IS HE DOES TWO

15

STEPS.

16

ACROSS THE BOARD FOR ALL OF THE DEFENDANTS.

17

HIS FIRST STEP IS TO ESTIMATE AN AVERAGE OVERCHARGE

AND SO WHEN YOUR HONOR ASKED THE QUESTION, YOU KNOW, DO

18

FIGURES 20 AND 22 SHOW THAT EACH EMPLOYEE WAS UNDERPAID, THE

19

ANSWER WAS NO.

20

AND IT'S WORSE THAN THAT, YOUR HONOR, BECAUSE WHAT THEY'VE

21

DONE IS INSTEAD OF GOING DEFENDANT BY DEFENDANT, EVEN TO

22

ESTIMATE AN OVER -- AN AVERAGE, THEY LUMP ALL THE DEFENDANTS

23

TOGETHER, AND THE BEST WAY I CAN EXPLAIN THIS IS FIGURE 19,

24

WHICH IS -- WHICH IS ON, IN THE BINDER I'VE HANDED THE COURT,

25

PAGE 7.

UNITED STATES COURT REPORTERS

234

73

1

THE COURT:

2

MR. GLACKIN:

3

MR. MITTELSTAEDT:

4
5

UM-HUM.
TAB 7?
WELL, IT'S TAB 6, PAGE 7.

I'M

SORRY.
AND WHAT HE'S DONE HERE, IT'S CALLED AVERAGE PERCENT

6

CHANGE IN TOTAL COMPENSATION, AND YOU SEE ON THE RIGHT-HAND

7

SIDE HE SAYS "ESTIMATED UNDERPAYMENT," AND THEN THIS LOOKS REAL

8

FANCY BECAUSE HE'S GOT THE NUMBER OF EMPLOYEES AND THEN THE

9

MEAN, THE MEDIAN AND SO FORTH, AND THEN HE'S GOT INITIAL AND

10

CUMULATIVE.

11

WHAT HE'S DONE HERE IS TAKE THE ANNUAL COMPENSATION FOR

12

EACH INDIVIDUAL, AND HE KNOWS WHAT COMPANY THEY'RE WITH, AND

13

INSTEAD OF ADDING IT UP EITHER BY INDIVIDUAL TO SHOW WHO WAS UP

14

OR WHO WAS DOWN DURING THE ALLEGED CONSPIRACY PERIOD, INSTEAD

15

OF DOING IT BY INDIVIDUAL, INSTEAD OF DOING IT BY COMPANY, HE

16

DID IT BY ALL THE DEFENDANTS.

17

AND SO WHEN HE HAD -- WHAT HE DID HERE WAS TAKE 2004, YOUR

18

HONOR, THE LINE, HE SHOWS, IN THE MEAN, THAT AVERAGE

19

COMPENSATION, TOTAL COMPENSATION FOR EVERYBODY WENT UP 10.3

20

PERCENT.

21
22
23
24
25

AND THEN HE TAKES 2011 AND IT GOES UP 9.7 PERCENT, YEAR TO
YEAR.
HE TAKES THE AVERAGE OF THOSE TWO TO GET A BASE LINE, SO
THAT'S 10.
AND THEN HE LOOKS AT THE NEXT YEAR, 2005, THE FIRST YEAR

UNITED STATES COURT REPORTERS

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1

OF THE ALLEGED VIOLATION PERIOD, AND COMPENSATION ONLY WENT UP

2

.5 PERCENT, SO HE SAYS THAT THAT MEANS THE ESTIMATED

3

UNDERPAYMENT, AS A RESULT OF THESE AGREEMENTS, WAS 9.5 -- A

4

NEGATIVE 9.5 OVER ON THE RIGHT.

5

THE COURT:

6

MR. MITTELSTAEDT:

7

10

AND THEN ON THE NEXT PAGE OF HIS REPORT HE SAYS, "WELL,
THIS IS JUST SUGGESTIVE BECAUSE IT'S NOT BROKEN OUT BY
DEFENDANTS."

11
12

AND THEN HE DOES THAT FOR THE

REST OF THE YEARS.

8
9

UM-HUM.

BUT THE QUESTION IS, WHY DIDN'T HE BREAK IT OUT BY
DEFENDANTS?

13

AND THE ANSWER IS ON THE NEXT TAB, PAGE 8.

ON THE

14

RIGHT-HAND SIDE IS LEAMER'S NUMBERS, AND SO YOU'LL SEE FOR 2005

15

THE .5 FROM THE PREVIOUS PAGE.

16

BUT WHEN, INSTEAD OF ADDING IT UP FOR ALL DEFENDANTS

17

TOGETHER, WHEN YOU JUST ADD UP ALL THE INDIVIDUALS IN A

18

COMPANY, YOU SEE THAT ADOBE WENT UP 9.8 PERCENT IN 2008, AND

19

APPLE WENT UP 10.6.

20

UP.

21

TWO COMPANIES WENT DOWN, AND THE REST WENT

AND IF YOU COMPARE THAT, AND ACTUALLY I'VE DONE THE --

22

I'VE BROKEN THIS OUT ON THE NEXT PAGE, PAGE 9.

23

HIS SAME PROCEDURE AND YOU DO A BASELINE FOR ADOBE, WHAT YOU

24

GET IS YOU TAKE THE 1.5 FOR 2004 -- THIS IS AT PAGE 9 -- YOU

25

TAKE THE 1.5 YEAR TO YEAR INCREASE FOR 2004, THE 2011 YEAR TO

UNITED STATES COURT REPORTERS

IF YOU FOLLOW

236

75

1

YEAR INCREASE OF 11.1, AVERAGE THOSE, AND YOU COME UP WITH A

2

6.3 PERCENT BASELINE.

3

IT FOR ALL OF THE DEFENDANTS TOGETHER.

THIS IS THE APPROACH LEAMER TOOK TO DO

4

AND THEN YOU COMPARE THAT 6.3 PERCENT BASELINE WITH THE

5

ACTUAL IN 2005 OF 9.8, AND THAT GIVES YOU AN OVERPAYMENT AS A

6

RESULT OF THESE ALLEGED AGREEMENTS OF 3.4 PERCENT, WHICH IS ON

7

THE BOTTOM PART OF THE PAGE, ADOBE 2005.

8
9

YOU DO THE SAME THING FOR APPLE:

YOU CONSTRUCT APPLE'S

BASELINE, COMPARE IT TO 2005, YOU GET 4.2 PERCENT.

10

YOU GET NEGATIVES FOR GOOGLE AND INTEL.

11

BUT YOU GET POSITIVES FOR INTUIT, LUCASFILM, AND PIXAR IS

12
13

A POSITIVE 35.6 PERCENT.
AND YOU KNOW WHAT LEAMER DID?

HE AVERAGED ALL THOSE

14

TOGETHER IN ORDER TO SUGGEST TO THE COURT THAT THERE WAS AN

15

ESTIMATED UNDERPAYMENT AS A RESULT OF THESE AGREEMENTS, AND

16

THAT'S WHERE HE GETS HIS NEGATIVE 9.5 PERCENT.

17
18
19

WHAT DRIVES THIS CHART IS INTEL BECAUSE INTEL HAS A LITTLE
OVER HALF THE EMPLOYEES IN THE GROUP.
AND SO HE IS MISLEADING THE COURT IN SAYING THAT THIS

20

EXERCISE SHOWS AN ESTIMATED UNDERPAYMENT FOR ALL OF THE

21

DEFENDANTS OF 9.5 PERCENT, WHEREAS IF IT HAD ANY VALUE, IF YOU

22

COULD REALLY MAKE A CAUSE AND EFFECT JUMP FROM YEAR TO YEAR

23

WITHOUT ADJUSTING FOR ANYTHING, IT WOULD SHOW THAT ONE, TWO,

24

THREE, FOUR, FIVE OF THE COMPANIES, UNDER THEIR OWN THEORY,

25

OVERPAID.

UNITED STATES COURT REPORTERS

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1
2
3

AND SO THERE'S NO BASIS TO SAY, FOR THEM TO SAY, WELL,
THERE'S THIS AVERAGE, AVERAGE OVERPAYMENT.
AND THEN WHEN YOU GET TO HIS REGRESSION, IT'S WORSE, YOUR

4

HONOR.

THIS IS FIGURE 20, AND THIS IS AT PAGE 11, PAGE 11 OF

5

THIS SAME THING.

6

THE COURT:

PAGE 11 IS A DEPOSITION TRANSCRIPT.

7

MR. MITTELSTAEDT:

8

THE COURT:

9

MR. MITTELSTAEDT:

YES, YES.

OKAY.
AND WHAT HE SAYS IN THE

10

DEPOSITION IS WHEN YOU DO A REGRESSION, YOU NEED TO DO A

11

SENSITIVITY ANALYSIS.

12

CONCLUSIONS ARE TO A CHOICE OF VARIABLES.

YOU EXPLORE HOW SENSITIVE THE

13

AND THEN HE SAYS, "I'VE DONE SOME ALTERNATE EQUATIONS."

14

AND THEN ON THE NEXT PAGE, DOWN AT THE BOTTOM, "BEFORE YOU

15

RELY ON IT," A REGRESSION, "YOU NEED TO KNOW IF IT'S SENSITIVE

16

BEFORE RELYING ON IT?

17

"THAT'S CORRECT."

18

OKAY.

19

AND THEN THE NEXT PAGE, PAGE 13, WE WERE ASKING

HIM, "WELL, WHAT SENSITIVITY ANALYSIS DID YOU DO?"

20

BECAUSE AS COUNSEL EXPLAINED, ON THIS REGRESSION, FIGURE

21

20, HE HAS A SINGLE CONDUCT VARIABLE FOR ALL OF THE DEFENDANTS

22

WHICH ASSUMES THAT THE EFFECT OF THE PIXAR/LUCASFILM AGREEMENT

23

WAS THE SAME ON PIXAR AS IT WAS ON ADOBE THAT DIDN'T HAVE

24

ANYTHING TO DO WITH IT, AND THEN HE ADJUSTS ONLY FOR THE AGE

25

AND THE HIRING RATE OF THE COMPANY.

UNITED STATES COURT REPORTERS

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1
2
3

SO THAT DOESN'T GIVE YOU ANY INDIVIDUAL COMPANY
INFORMATION WORTH ANYTHING.
BUT HERE'S WHAT HE SAYS, YOUR HONOR.

4

THE COURT:

YOU SAY THESE ARE FROM THE MURPHY

5

REPORT, YOUR PAGES 9 AND 10.

6

MR. MITTELSTAEDT:

7

THE COURT:

8

MR. GLACKIN:

9

MURPHY REPORT, FIGURE 19.

IT'S EXHIBIT 19 -- EXCUSE ME.

IT'S EXHIBIT 19 TO DR. MURPHY'S REPORT.
THE COURT:

11

MR. GLACKIN:

13

GIVE ME THE PAGE NUMBER OF THIS.

IT'S -- IT'S DONE BY EXHIBIT.

10

12

"WELL, I" --

OH.
IT'S NOT DR. LEAMER'S REPORT AT THAT

POINT.
MR. MITTELSTAEDT:

YEAH, IT'S DR. MURPHY'S REPORT ON

14

THE LEFT-HAND SIDE WITH THE POOLING, THE AGGREGATE FROM MURPHY,

15

I MEAN FROM LEAMER.

16
17
18

BUT, YOUR HONOR, THIS REALLY GOES TO THE HEART OF WHAT'S
GOING ON HERE AND HOW MISLEADING IT IS.
AT PAGE 13, THIS IS LEAMER'S DEPOSITION, AND AT LINE 16

19

HE'S ASKED -- AND NOW WE'RE TALKING ABOUT WHAT SENSITIVITY

20

ANALYSES HE RAN TO SEE IF HIS, IF HIS FIGURE 20, HIS

21

REGRESSION, WAS RELIABLE.

22

AND HE SAID, "I RECALL ONE WHICH HAS TO DO WITH THE

23

DISAGGREGATION WITH DATA BY A DEFENDANT.

24

THAT HAS ALL THE DEFENDANTS.

25

"MR. GLACKIN:

WAIT, WAIT, WAIT.

SO I HAVE A MODEL

I'M GOING TO INSTRUCT

UNITED STATES COURT REPORTERS

239

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1
2
3
4
5
6

YOU NOT TO ANSWER FURTHER."
AND THEN THE QUESTION BY MR. PICKETT:

"WHAT WERE THE

RESULTS OF THE DISAGGREGATION?"
THIS IS WHEN HE RAN IT INDIVIDUALLY BY DEFENDANT, SEPARATE
CONDUCT VARIABLES.
AND MR. GLACKIN SAYS, "IF YOU ANSWER SOMETHING OTHER THAN

7

'I DON'T KNOW' OR 'I DON'T REMEMBER,' I'M GOING TO INSTRUCT YOU

8

NOT TO ANSWER."

9
10

AND THE WITNESS, ALMOST PREDICTABLY, SAID, "I DON'T
REMEMBER THE DETAILS."

11

"DID YOU RETAIN THE WORK?"

12

"WELL, IT'S PROBABLY ON MY HARD DRIVE SOMEPLACE."

13

AND THEN HE SAYS AT LINE 12, "WELL, IT'S NOT HARD TO DO.

14

YOUR EXPERTS WILL BE ABLE TO DO IT WITH THE PRESS OF A BUTTON."

15

AND SO THAT'S WHAT OUR EXPERT DID.

16

BEFORE I GO ON TO THAT, ON THE FOLLOWING EXCERPT HERE,

17

HE'S ASKED, "IF YOUR CONDUCT REGRESSIONS COME UP WITH A -- OR

18

CAME UP WITH A POSITIVE CONDUCT COEFFICIENT, MEANING THAT THE

19

ALLEGED AGREEMENT HAD A POSITIVE IMPACT ON COMPENSATION, WHAT

20

WOULD THAT TELL YOU ABOUT THE MODEL?

21

"WELL, IT WOULD RAISE CONCERNS ABOUT THE CONCEPTUAL

22

FRAMEWORK AND THE APPROPRIATENESS OF THE MODEL.

23

QUESTION ABOUT THAT."

24
25

THERE'S NO

AND THEN -THE COURT:

ALL RIGHT.

LET ME ASK YOU A QUESTION.

UNITED STATES COURT REPORTERS

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1

IF THE PLAINTIFFS WERE TO -- WHAT IS YOUR POSITION ON

2

PREDOMINANCE AS TO JUST THE TECHNICAL CLASS?

3
4

MR. MITTELSTAEDT:
THERE WAS ANY JOB CATEGORY --

5

THE COURT:

6

MR. MITTELSTAEDT:

7
8
9
10
11

THERE IS NO BASIS TO THINK THAT

UM-HUM.
-- THAT -- WHERE THERE WAS ANY

BROAD IMPACT OF THESE AGREEMENTS.
WHAT WE HAVE SHOWN -- AND, YOUR HONOR, IF YOU -- I MEAN,
GOING BACK TO TAB 5, THIS SHOWS -- YOU TALKED WITH COUNSEL
ABOUT THE CONSTANT ATTRIBUTE COMPENSATION.
THIS TAKES THE TOP 25 JOBS BY COMPANY AND IT SHOWS THE

12

ANNUAL CHANGES, AND WHAT THIS SHOWS IS THAT SOME JOBS WENT UP

13

IN TOTAL COMP, SOME JOBS WENT DOWN TO A NEGATIVE.

14

AND SO EXHIBIT 18, WHICH IS IN TAB 5, FOR ADOBE, THAT

15

FIRST YEAR, ONE JOB -- AND THESE ARE 25 DIFFERENT JOBS -- ONE

16

JOB COMPENSATION INCREASED 11 PERCENT.

17

BY 14 PERCENT.

18
19

GOOGLE, 2006, EVEN A LARGER SWING.

ANOTHER JOB DECREASED

53 PERCENT TO A

NEGATIVE 70 PERCENT.

20

THIS SHOWS THAT IF THE PLAINTIFFS WERE RIGHT, THERE WOULD

21

BE CORRELATION AMONG THESE JOB GROUPS, CORRELATION BOTH OF THE

22

EMPLOYEES WITHIN THE JOB GROUP AND THE AVERAGE.

23

THIS TAKES IT BY INDIVIDUAL WITHIN THAT -- OR NO.

THIS

24

TAKES IT BY JOB TITLES AND IT SHOWS THAT THEY'RE NOT CORRELATED

25

WHEN THEY MOVE.

UNITED STATES COURT REPORTERS

241

80

1

AND, YOUR HONOR, THE FIRST PART OF WHAT LEAMER DID WAS TO

2

TRY AND SHOW, IN THIS VERY MISLEADING WAY, AN AVERAGE

3

OVERCHARGE FOR EVERYBODY.

4
5

WE ASKED HIM, AT HIS DEPOSITION, AND HE SHOWED -- ON ONE
OF THESE YOU'LL SEE 20 PERCENT UNDERCHARGE FOR LUCASFILM.

6
7

WE ASKED HIM, "HOW DOES IT MAKE ANY SENSE THAT A COMPANY
COULD UNDERPAY BY 20 PERCENT AND STILL HIRE PEOPLE?"

8
9
10
11

AND HE PAUSED ALMOST A MINUTE AND HE SAID THAT HE WAS
TIRED AND IN HIS -- HE COULD NOT CONSTRUCT A STORY TO JUSTIFY
THAT.
AND WHAT THAT TELLS ME IS THAT EVEN HE KNOWS THAT THE

12

RESULTS OF HIS REGRESSION DON'T MAKE SENSE, THEY DON'T COMPORT

13

WITH THE REAL WORLD, AND, WORSE, HE DIDN'T DO IT DEFENDANT BY

14

DEFENDANT.

15

AND WHEN, WHEN --

16

THE COURT:

OKAY.

I'M GOING TO TAKE A BREAK NOW.

17

WE'VE BEEN GOING FOR MORE THAN TWO HOURS AND MS. SHORTRIDGE

18

NEEDS TO BREAK.

OKAY?

19

THANK YOU ALL.

20

(RECESS FROM 3:36 P.M. UNTIL 3:57 P.M.)

21
22

THE COURT:

OKAY.

WELCOME BACK.

PLEASE HAVE A

SEAT.

23

ALL RIGHT.

24

WHAT -- WHAT DISCOVERY DISPUTES ARE STILL OUTSTANDING?

25

LET'S MOVE ON TO THE CMC.
I

WAS GOING TO MAKE A SUGGESTION WITH THE E-MAILS BETWEEN INTUIT

UNITED STATES COURT REPORTERS

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81

1

BOARD CHAIRMAN GLENN CAMPBELL AND GOOGLE'S IN-HOUSE LAWYER, I

2

WAS GOING TO SUGGEST THAT YOU SUBMIT THEM TO ME IN CAMERA.

3

I'LL BE HAPPY TO DECIDE IT FOR YOU AND I WILL SEE IF THERE

4

REALLY IS SOME KIND OF ATTORNEY-CLIENT PRIVILEGE AGREEMENT

5

BETWEEN MR. CAMPBELL AND GOOGLE SUCH THAT IT WOULD ACTUALLY BE

6

PRIVILEGED.

7
8
9
10
11

BUT IF IT'S JUST MORE TALKING ABOUT THESE AGREEMENTS, I
DON'T REALLY THINK THAT'S PRIVILEGED.
SO WHY DON'T YOU SUBMIT THEM TO ME IN CAMERA?

DO YOU WANT

TO DO THAT BY NEXT WEDNESDAY?
MR. RUBIN:

SURE, YOUR HONOR.

WE WOULD ALSO BE

12

SUBMITTING FACTUAL -- WITH THE COURT'S PERMISSION, WE WOULD

13

ALSO BE SUBMITTING FACTUAL DECLARATIONS ABOUT THE NATURE OF THE

14

RELATIONSHIP.

15

THE NATURE OF THE RELATIONSHIP AND WE WOULD LIKE TO SUBMIT

16

THOSE IN CAMERA AS WELL.

I THINK ONE OF THE ISSUES THAT WAS RAISED WAS

17

MS. DERMODY:

18

PLAINTIFF -- EXCUSE ME.

19
20
21
22

MR. RUBIN:

AND, YOUR HONOR, ON BEHALF OF

I'M SORRY.

IF -- YOUR HONOR, IF YOU CAN INDULGE US, IF WE CAN SUBMIT
IT BY FRIDAY?
THE COURT:

LET ME HEAR, WHAT OTHER -- NONE OF THE

23

CEO'S HAVE BEEN DEPOSED, THE SENIOR VICE-PRESIDENT OF HUMAN

24

RESOURCES AT INTEL HAS NOT BEEN DEPOSED.

25

HASN'T BEEN DEPOSED?

WHO ELSE?

UNITED STATES COURT REPORTERS

WHO ELSE

243

82

1

MS. DERMODY:

WELL, YOUR HONOR, JUST FOR THE RECORD,

2

PLAINTIFFS REQUESTED MOST OF THESE INDIVIDUALS BACK IN

3

SEPTEMBER AND IT'S BEEN QUITE A LONG PROCESS OF NEGOTIATION,

4

WITH SOME DEFENDANTS ACTUALLY ASKING THAT WE WAIT UNTIL AFTER

5

THE COURT'S ORDER ON CLASS CERTIFICATION.

6

THE COURT:

NO, THAT'S NOT HAPPENING.

7

MS. DERMODY:

WE HAVE NOT AGREED TO THAT AND WE HAVE

8

AGREED TO ACCOMMODATE SCHEDULES WHENEVER WE COULD, BUT WE'VE

9

INSISTED THAT DEPOSITIONS START.

10
11

I'LL GIVE YOU A LIST, YOUR HONOR, IF YOU'D LIKE OF WHAT'S
ON CALENDAR.

12

THE COURT:

OKAY.

13

MS. DERMODY:

14

THE COURT:

15

MS. DERMODY:

16

THE COURT:

17

MS. DERMODY:

18

THE COURT:

19

MS. DERMODY:

FOR GOOGLE, SHONA BROWN, JANUARY 30TH.

AND SHE'S AN H.R. PERSON?
YES, YOUR HONOR.

OKAY.

THAT'S JANUARY 30TH?

YES.

OKAY.
AND ERIC SCHMIDT HAD BEEN SCHEDULED

20

FOR FEBRUARY 21ST.

I UNDERSTAND WE WERE TOLD BY DEFENSE

21

COUNSEL A FEW MOMENTS AGO THAT THAT DATE MAY NOT WORK FOR

22

MR. SCHMIDT.

23

POSSIBLE.

WE WOULD LIKE TO HAVE ONE SCHEDULED AS SOON AS

24

MR. RUBIN:

YOUR HONOR, WE HAD PROPOSED

25

FEBRUARY 20TH, THE DAY BEFORE.

UNITED STATES COURT REPORTERS

244

83

1

MS. DERMODY:

AND WE HAVE TO CHECK WITH MR. HEIMANN,

2

WHO WAS SCHEDULED TO TAKE THAT DEPOSITION, IF THAT WORKS FOR

3

HIS SCHEDULE.

4

THE COURT:

WELL, LET'S -- I AM REALLY DISAPPOINTED

5

THAT ALL OF THIS DISCOVERY WAS NOT DONE BEFORE THE CLASS

6

CERTIFICATION HEARING.

7

SO LET'S SUBMIT RIGHT NOW, WHAT'S THE DATE FOR

8

ERIC SCHMIDT?

NO ONE IS LEAVING UNTIL WE HAVE THESE DATES SET.

9

IF WE NEED TO BE HERE UNTIL MIDNIGHT, THAT'S WHAT HAPPENS.

10

MR. RUBIN:

HE'S AVAILABLE FEBRUARY 20TH.

11

THE COURT:

CAN YOU TAKE IT FEBRUARY 20TH?

12

MS. DERMODY:

13

THE COURT:

14

17

OKAY.

YOU BETTER MAKE SOMEONE

AVAILABLE.

15
16

SOMEONE WILL TAKE IT, YOUR HONOR, YES.

MS. DERMODY:

YES, YOUR HONOR.

SO LUCASFILM RIGHT NOW, IF I HAVE THIS RIGHT,
MICHELINE CHAU, C-H-A-U, AND IT'S FEBRUARY 20TH.

18

THE COURT:

19

MR. SAVERI:

AND WHAT IS THAT PERSON'S JOB?
SHE WAS, AT VARIOUS TIMES, THE CHIEF

20

OPERATING OFFICER, OR SOMEONE AT THAT LEVEL AT LUCASFILM.

21

TITLE DID CHANGE THROUGHOUT THE PERIOD OF TIME AFFECTED BY THE

22

AGREEMENT, BUT SHE WAS ONE OF THE MOST SENIOR PEOPLE AT

23

LUCASFILM.

24

MR. LUCAS HIMSELF.

25

HER

IN FACT, I BELIEVE SHE REPORTED DIRECTLY TO

THE COURT:

OKAY.

WHO ELSE?

UNITED STATES COURT REPORTERS

245

84

1

MS. DERMODY:

2

THE COURT:

3

MS. DERMODY:

4
5

JAN VAN DER VORT, FEBRUARY 5TH.

HAVE -- LUCAS HAS REFUSED TO GIVE US DATES.
MR. PURCELL:
HONOR.

THAT'S ACTUALLY NOT ACCURATE, YOUR

WE HAVEN'T REFUSED TO GIVE THEM DATES.

8
9

OKAY.

AND WE HAVE REQUESTED MR. LUCAS FOR SOME TIME, BUT WE

6
7

MICHELLE MAUPIN, FEBRUARY 12TH.

THE COURT:

OKAY.

GIVE ME A DATE.

WE'RE SETTING

THEM RIGHT NOW.

10

MR. PURCELL:

11

THE COURT:

I CAN'T GIVE YOU A DATE TODAY.

I'M TELLING YOU, I HAVE BEEN SO TOUGH ON

12

BOTH SIDES AT EVERY CMC ON DISCOVERY.

I DON'T WANT THESE

13

GAMES, OKAY?

14

IN THESE AGREEMENTS HAVEN'T BEEN DEPOSED YET, I REALLY FEEL

15

LIKE YOU INTENTIONALLY WITHHELD THEIR DEPOSITIONS UNTIL AFTER

16

THE CLASS CERT HEARING, OKAY?

SO THE FACT THAT THE PEOPLE WHO ARE MOST INVOLVED

17

MR. PURCELL:

18

THE COURT:

YOUR HONOR --

I'M REALLY DISAPPOINTED BECAUSE THESE

19

ARE THE INDIVIDUALS, LIKE ERIC SCHMIDT IS ON ALL THE E-MAILS

20

THAT WERE IN THIS CMC STATEMENT FROM JANUARY 26TH OF 2012, A

21

YEAR AGO.

22

SO, YOU KNOW, I'M DISAPPOINTED.

23

MR. LUCAS'S DEPOSITION.

24

MR. PURCELL:

GIVE ME A DATE FOR

25

I CANNOT GIVE YOU A DATE TODAY.

DON'T KNOW WHEN HE'S AVAILABLE.

I

I JUST DON'T HAVE THAT

UNITED STATES COURT REPORTERS

246

85

1

INFORMATION.

2
3

THE COURT:

6

SO HOW LONG HAS THIS LAWSUIT BEEN

PENDING AND YOU'VE NEVER GOTTEN A DATE FOR HIM?

4
5

OKAY.

MR. PURCELL:

YOUR HONOR, MR. LUCAS'S DEPOSITION WAS

FIRST REQUESTED IN MID-DECEMBER, NOT IN SEPTEMBER.
THERE WAS ONE LUCASFILM WITNESS WHOSE DEPOSITION WAS

7

REQUESTED PRIOR TO THAT.

8

EARLY NOVEMBER.

9
10

THE COURT:

SHE WAS DEPOSED IN LATE OCTOBER OR

GIVE ME A DATE BY WHICH YOU'RE GOING TO

PROVIDE A DATE.

11

MR. PURCELL:

GIVE YOU A DATE BY WHICH WE'RE GOING

12

TO PROVIDE A DATE?

13

FROM FRIDAY, NEXT FRIDAY?

14
15

HOW ABOUT A WEEK FROM TOMORROW, OR A WEEK

THE COURT:
ALL RIGHT.

I'LL GIVE YOU A WEEK, JANUARY 23RD.

WHAT ELSE?

16

MS. DERMODY:

17

THE COURT:

18

MS. DERMODY:

19

THE COURT:

20

MS. DERMODY:

21

FOR INTEL, YOUR HONOR, PAUL OTELLINI.

ALL RIGHT.

WHEN IS THAT?

JANUARY 29TH.

OKAY.
AND PATRICIA MURRAY, FEBRUARY 14.

AND, EXCUSE ME, YOUR HONOR.

I CAN ALSO PASS YOU UP THIS

22

LIST IF IT WOULD BE HELPFUL SO YOU DON'T HAVE TO TRY TO GET THE

23

SPELLINGS OF EVERY NAME.

24
25

THE COURT:

OKAY.

HAVE THE DEFENDANTS SEEN THAT

LIST?

UNITED STATES COURT REPORTERS

247

86

1

MR. SAVERI:

2

MS. DERMODY:

3
4

I DON'T THINK THEY'VE SEEN THE LIST.
I CAN READ IT ALOUD IF THAT WOULD BE

HELPFUL AND I CAN PASS IT UP IF IT WOULD BE ACCEPTABLE.
MR. SAVERI:

THESE REFLECT DATES THAT WE HAVE HAD

5

EXTENSIVE COMMUNICATION WITH THE DEFENDANTS, SO I THINK WITH

6

RESPECT TO EACH DEFENDANT WHOSE EXECUTIVE IS ON THE LIST, THEY

7

KNOW ABOUT IT.

8
9
10
11
12

BUT WE CAN SHARE IT, READ IT OUT, WHATEVER MAKES SENSE.
MS. DERMODY:

YES.

I JUST WANT TO SAVE THE COURT

TIME, YOUR HONOR, BUT I'M HAPPY TO KEEP READING THE LIST.
THE COURT:

WELL, LET ME SEE THE LIST.

CAN YOU JUST

SHOW IT TO THE DEFENDANTS?

13

MS. DERMODY:

14

MS. HENN:

SURE (HANDING).

I WOULD JUST POINT OUT THAT THE LIST HAS

15

NOTES AT THE BOTTOM AND I'M NOT SURE THEY'RE ACCURATE, FOR

16

EXAMPLE, THAT ALL OF THESE WERE REQUESTED IN SEPTEMBER.

17

AS WE JUST HEARD, SOME OF THEM WERE -- AT LEAST MR. LUCAS

18

WAS FIRST REQUESTED IN DECEMBER.

19

THAT THE COURT'S AWARE THAT THAT'S NOT ACCURATE.

20
21

MR. KIERNAN:

SO I JUST WANT TO MAKE SURE

DAVID KIERNAN.

YOUR HONOR, THERE ARE A FEW DEFENDANTS' WITNESSES THAT

22

WERE MOVED BY PLAINTIFFS, NOT BECAUSE OF ANY ACTION -- FOR

23

EXAMPLE, BRUCE CHIZEN WAS SCHEDULED FOR DEPOSITION IN DECEMBER

24

AND WE ACCOMMODATED MR. SAVERI'S SCHEDULE AND WE WENT TO

25

JANUARY, AND THEN IT HAD TO GET MOVED AGAIN UNTIL FEBRUARY.

UNITED STATES COURT REPORTERS

248

87

1

THE COURT:

2

MR. KIERNAN:

3

THE COURT:

4

MR. KIERNAN:

5

WHY DID IT HAVE TO MOVE UNTIL FEBRUARY?
THERE WAS ANOTHER SCHEDULING CONFLICT.

ON WHOSE PART?
ACTUALLY, I THINK IT MIGHT HAVE BEEN

YOURS AS WELL.

6

MR. SAVERI:

I BELIEVE ONE OF THEM WAS --

7

MR. KIERNAN:

BUT WE'VE BEEN WORKING TOGETHER.

8

MEAN, THE POINT IS WE'VE BEEN WORKING TOGETHER ABOUT THE

9

SCHEDULING ISSUES.

I

10
11
12
13
14
15
16
17

IT HASN'T BEEN QUITE AS CHARACTERIZED -- AS

PLAINTIFFS' COUNSEL CHARACTERIZED IT.
THE COURT:

WHY DON'T YOU JUST LIST THE NAMES AND

THE DATES, PLEASE?
MS. DERMODY:

SURE, YOUR HONOR, YES.

FOR ADOBE, MR. BRUCE CHIZEN.
THE COURT:

SO FOR INTEL, IT'S ONLY MS. MURRAY AND

MR. OTELLINI?
MS. DERMODY:

YES, IN TERMS OF DEPOSITIONS THAT HAVE

18

BEEN SET, YOUR HONOR.

THERE ARE MORE THAT WERE REQUESTED.

19

MR. HINMAN:

YOUR HONOR, FRANK HINMAN FOR INTEL.

20

BEFORE WE LEAVE MR. OTELLINI, THERE'S JUST A LITTLE BIT OF

21

A DETAIL THERE ACTUALLY HAVING TO DO WITH THIS MOTION THAT'S

22

BEEN FILED WITH RESPECT TO THESE GOOGLE -- THE GOOGLE DOCUMENTS

23

AND THE PRIVILEGE ISSUE BECAUSE MR. OTELLINI, AS I UNDERSTAND

24

IT, IS ALSO ON A NUMBER OF THOSE DOCUMENTS.

25

SO I THINK WE HAVE AN UNDERSTANDING WITH MR. SAVERI THAT

UNITED STATES COURT REPORTERS

249

88

1

THERE MAY BE A CONTINGENCY IN WHICH MR. OTELLINI'S DEPOSITION

2

MIGHT HAVE TO MOVE, BUT I DON'T THINK WE HAVE ANY -- I THINK

3

WE'RE BOTH ON THE SAME PAGE AS TO HOW THAT'S GOING TO WORK, IF

4

IT HAS TO WORK.

5

BUT PLEASE GO AHEAD.

6

THE COURT:

OKAY.

LET ME -- I'M SORRY.

LET ME

7

UNDERSTAND SOMETHING, WHICH I DIDN'T UNDERSTAND WITH THE

8

SEALING REQUEST, EITHER.

9

YOU HAVE THIRD PARTY COMPETITORS, THEY HAVE AGREED TO

10

ENTER INTO THESE AGREEMENTS, AND NO ONE HAS EVER ALLEGED THAT

11

THERE'S A NONDISCLOSURE AGREEMENT.

12

SO WHAT IS THE BASIS FOR CONFIDENTIALITY AND FOR SEALING

13

OF DOCUMENTS OF THIRD PARTY COMPETITORS?

OKAY?

UNLESS YOU'RE

14

TELLING ME THAT ALL OF THESE CEO'S ARE ACTUALLY CONSULTANTS AND

15

ADVISORS FOR ALL THEIR COMPETITORS, WHICH WOULD REALLY SHOCK

16

ME, WHAT IS THE BASIS FOR AN EXPECTATION OF CONFIDENTIALITY AND

17

OF SEALING?

18

IT HAPPENED TIME AND AGAIN ON THE SEALING REQUEST.

YOU

19

HAVE THIRD PARTY COMPETITORS WHO HAVE CHOSEN TO TALK TO EACH

20

OTHER AND SUDDENLY THAT'S -- HOW IS THAT CONFIDENTIAL?

21

MR. RUBIN:

MR. OTELLINI IS ON THE BOARD OF

22

DIRECTORS FOR GOOGLE.

HE IS A MEMBER OF THE BOARD OF

23

DIRECTORS.

24

CONFIDENTIAL COMMUNICATIONS WITH YOUR BOARD ON MATTERS RELATING

25

TO RUNNING THE CORPORATION.

AS FAR AS I KNOW, YOU'RE ENTITLED TO HAVE

UNITED STATES COURT REPORTERS

250

89

1

THE COURT:

TELL ME ABOUT THIS EDWARD COLLIGAN FROM

2

PALM AND STEVE JOBS OF APPLE.

3

EXPECTATION OF CONFIDENTIALITY WHEN THEY'RE TALKING TO EACH

4

OTHER?

5

WHAT IS THE BASIS FOR ANY

DON'T TELL ME THAT THEY'RE ACTUALLY CONSULTANTS AND

6

ACTUALLY WORK FOR THEIR COMPETITORS.

7

I WOULD FIND THAT REALLY

HARD TO BELIEVE.

8

THOSE KINDS OF THINGS JUST KEEP POPPING UP, AND I'M

9

TELLING YOU, THAT'S NOT CONFIDENTIAL AND IT'S NOT GOING TO BE

10

SEALED.

11

OF NDA OR SOME BASIS FOR THAT TO BE CONFIDENTIAL, I'M NOT GOING

12

TO SEAL IT.

13
14
15
16

UNLESS YOU TELL ME THAT THERE WAS ACTUALLY SOME KIND

MR. TUBACH:

YOUR HONOR, MICHAEL TUBACH FOR APPLE.

I DON'T BELIEVE APPLE MOVED TO HAVE THAT SEALED AS
CONFIDENTIAL.
I BELIEVE PALM DID.

17

THE COURT:

ANYWAY, OKAY.

18

MS. DERMODY:

SO --

YOUR HONOR, IF I MIGHT CLARIFY FOR THE

19

COURT, WE BELIEVE THAT PALM, AS A THIRD PARTY, TRIED TO AVAIL

20

ITSELF UNDER THE PROTECTIVE ORDER IN THE CASE AND THE COURT

21

DISAGREED WITH PALM'S DESIGNATION.

22
23

SO I THINK ALL THE PARTIES ACCEPT THAT.
DEFENDANTS.

I WON'T SPEAK FOR

PLAINTIFFS EXCEPT THAT.

24

MR. SAVERI:

25

THE COURT:

RIGHT.
OKAY.

SO YOU'RE SAYING WHO ELSE IS ON

UNITED STATES COURT REPORTERS

251

90

1

THESE PRIVILEGED E-MAILS BETWEEN -- WHO IS THE GOOGLE IN-HOUSE

2

LAWYER?

3

WHO IS ON THESE PRIVILEGED E-MAILS?
MR. RUBIN:

THE GOOGLE -- THERE ARE A NUMBER OF

4

GOOGLE IN-HOUSE, BUT ONE OF THEM BEING KENT WALKER, THE GENERAL

5

COUNSEL.

6

ASSISTING THE BOARD.

7

AT OTHER TIMES IT'S LAWYERS WHO WERE INVOLVED IN

SO MR. OTELLINI, AS I SAID, IS ON COMPENSATION COMMITTEE

8

DOCUMENTS WHERE THERE'S PRIVILEGED ADVICE BEING GIVEN TO THE

9

BOARD OF DIRECTORS AND MR. -- IN MR. CAMPBELL'S ROLE AS A

10

SENIOR ADVISER TO THE COMPANY, AND AS I SAID, WE'LL PROVIDE YOU

11

MORE DETAIL ABOUT THE LEGAL STATUS OF THAT RELATIONSHIP --

12
13

THE COURT:

ALL RIGHT.

TELL ME HOW MANY PRIVILEGED

COMMUNICATIONS ARE THE SUBJECT OF THE MOTION TO COMPEL.

14

MR. RUBIN:

WELL, YOUR HONOR, WE'RE ACTUALLY TRYING

15

TO GET THAT BREAKDOWN.

16

PLAINTIFFS LISTED ABOUT 160, BUT I THINK WE'RE -- RIGHT NOW, AS

17

WE SPEAK, WE'RE TRYING TO DE-DUPE THOSE BECAUSE I THINK THERE

18

ARE ACTUALLY SIGNIFICANTLY FEWER E-MAILS AT ISSUE.

19

I THINK, THE NUMBER THAT WERE IDENTIFIED.

20

I BELIEVE THAT THE -- I BELIEVE

MS. DERMODY:

YES, YOUR HONOR.

BUT THAT'S,

IT PROBABLY HASN'T

21

COME ACROSS THE COURT'S DESK YET, BUT WE FILED A MOTION TO

22

COMPEL YESTERDAY ON THESE DOCUMENTS WHICH DESCRIBES 166 E-MAILS

23

AND SETS FORTH --

24
25

THE COURT:
THAT.

I'M GOING TO LET JUDGE GREWAL HANDLE

I MEAN, IT WAS FILED BEFORE HIM.

UNITED STATES COURT REPORTERS

252

91

1

I THOUGHT THERE WAS A DISCRETE AMOUNT.

I MEAN, I'M

2

LOOKING AT THE DECEMBER 5TH JOINT CASE MANAGEMENT STATEMENT AND

3

IT LOOKED LIKE IT WAS A VERY DISCRETE NUMBER.

4

MR. RUBIN:

AT THAT TIME, YOUR HONOR, I THINK TWO

5

HAD BEEN IDENTIFIED, AND THEN AS PART OF OUR SUPPLEMENTAL

6

PRODUCTION, WE PRODUCED SUPPLEMENTAL LOGS THAT INCLUDED

7

ADDITIONAL E-MAILS THAT INCLUDED MR. CAMPBELL.

8
9

THE COURT:

THAT'S RIGHT.

THERE WERE ONLY TWO

E-MAILS THAT WERE THE SUBJECT OF THIS ANTICIPATED MOTION TO

10

COMPEL AS OF DECEMBER.

11

E-MAILS?

12

MS. DERMODY:

BUT YOU'RE SAYING THAT'S GROWN TO 166

YES, BECAUSE THEY PRODUCED PRIVILEGE

13

LOGS SINCE THAT TIME, INCLUDING THOUSANDS OF E-MAILS ON

14

PRIVILEGE LOGS OVER THE HOLIDAYS.

15

SO WE JUST IDENTIFIED THEM AND MOVED TO COMPEL AS QUICKLY

16

AS POSSIBLE.

17

FOR A DEPONENT WHERE WE THOUGHT THESE E-MAILS WOULD BE

18

NECESSARY TO BE PRODUCED BECAUSE THEY WERE ON THAT DEPONENT'S

19

PRIVILEGE LOG AND WE HAD A DISCUSSION WITH DEFENDANTS ABOUT

20

GOING FORWARD WITH THE DEPO AND KEEPING IT OPEN.

21
22
23
24
25

WE HAD A DEPOSITION ON CALENDAR FOR LAST THURSDAY

THEY DISAGREED TO KEEP IT OPEN AND SAID THEY WOULD
CONTINUE IT SUBJECT TO OUR MOTION BEING HEARD.
SO WE FILED IT ON AN EXPEDITED TIME TABLE AND HOPEFULLY IT
WILL BE HEARD SOON.
THE CRUX OF THE ISSUE REALLY IS MORE THAN JUST THE NATURE

UNITED STATES COURT REPORTERS

253

92

1

OF THE RELATIONSHIPS, BUT ALSO THE MEANS OF COMMUNICATION.

2

SO WHATEVER THE RELATIONSHIP WAS TO GOOGLE, WHETHER A

3

PERSON WAS ON THE BOARD OF DIRECTORS OR SOMETHING ELSE,

4

GOOGLE'S DECISION TO SEND THOSE E-MAILS WITHOUT ANY EXPECTATION

5

OF PRIVACY TO THEIR COMPETITOR'S E-MAIL ADDRESSES, SO IN

6

MR. CAMPBELL'S CASE, THEY WERE SENDING WHATEVER IT WAS,

7

SENSITIVE, WHAT THEY WOULD CALL PRIVILEGED INFORMATION TO

8

INTUIT.COM WHERE INTUIT ITSELF HAS A PERSONNEL POLICY TELLING

9

ALL EMPLOYEES THAT ANY OF THE COMPUTER SYSTEMS BELONG TO INTUIT

10
11
12

AND INTUIT CAN INVESTIGATE THEM AT ANY TIME.
THERE SHOULD HAVE BEEN NO EXPECTATION OF PRIVACY.

IT WAS

A WAIVER OF THE PRIVILEGE IN OUR VIEW.

13

SO WHATEVER YOU FIND THE RELATIONSHIP TO BE SEEMS TO ME TO

14

BE ALMOST BESIDE THE POINT GIVEN HOW THEY FAILED TO PROTECT THE

15

PRIVILEGE AND SENT IT OFF TO THEIR COMPETITOR'S E-MAIL ADDRESS.

16

MR. RUBIN:

WELL, OBVIOUSLY, YOUR HONOR, THESE ARE

17

ALLEGATIONS IN THEIR MOTION, BUT THERE'S A SIGNIFICANT FACTUAL

18

SHOWING THAT WE'RE PREPARED TO MAKE, BOTH ON THE NATURE OF THE

19

RELATIONSHIP BEING CONSISTENT WITH PRIVILEGE, AND THE FACT THAT

20

MR. CAMPBELL, IN THE STATUS THAT HE HAD, TREATED THEM WITH

21

CONFIDENTIALITY AND UNDERSTOOD HE HAD A DUTY TO DO SO AND THAT

22

NOBODY EVER REVIEWED OR SAW OR TOOK PART IN PART OF THE REVIEW

23

OF THESE E-MAILS.

24
25

THE COURT:

SO WHO ELSE IS -- I'M SORRY TO INTERRUPT

YOU -- WHO ELSE IS ON THESE 166 E-MAILS THAT STILL NEEDS TO BE

UNITED STATES COURT REPORTERS

254

93

1
2

DEPOSED?

ARE THERE OTHERS OTHER THAN MR. OTELLINI?
MR. RUBIN:

WELL, PERHAPS SHONA BROWN MAY WELL BE ON

3

THEM, AND THOSE ARE THE ONLY OTHER TWO GOOGLE INDIVIDUALS WHOSE

4

DEPOSITIONS HAVE BEEN REQUESTED.

5

MR. SAVERI:

EXCUSE ME.

MR. CAMPBELL IS ONE OF THE

6

PRIME ACTORS FROM OUR PERSPECTIVE IN THE CONSPIRACY.

7

HIS NAME IS ALL OVER THESE DOCUMENTS AND RIGHT NOW I THINK WE

8

HAVE A DATE FOR MR. CAMPBELL'S DEPOSITION ON FEBRUARY 5.

9
10

MS. DERMODY:
MR. RUBIN:

HE IS --

YES.

I KNOW MS. DERMODY MADE THE REFERENCE TO

11

THE FACT THAT WE GOT THEM TO THEM OVER THE HOLIDAYS.

12

ACTUALLY EXPEDITED THEM TO GET THEM TO THEM OVER THE HOLIDAYS

13

AT THEIR REQUEST SO THAT WE COULD TEE THIS ISSUE UP TO THE

14

EXTENT THAT THEY WANTED TO PURSUE IT AS QUICKLY AS WE COULD.

15

SO THE OVER THE HOLIDAYS WAS AT PLAINTIFFS' REQUEST.

16
17
18
19
20
21
22
23
24
25

THE COURT:

THAT'S -- WHAT DATE WAS THAT?

WE

BECAUSE I

THINK JUDGE GREWAL SET THE MOTION FOR FEBRUARY 26TH.
IS THAT RIGHT?
MS. DERMODY:

UNDER NORMAL TIME, AND WE MADE A

MOTION FOR SHORTENED TIME, WHICH HAS NOT BEEN RULED ON.
MR. SAVERI:

SO LET ME ANSWER TWO QUESTIONS.

THE

DATE FOR MR. CAMPBELL RIGHT NOW IS FEBRUARY 5.
WITH RESPECT TO THE MOTION, AS I UNDERSTAND IT, WE HAVE
ASKED GOOGLE TO AGREE TO SHORTEN TIME.
MR. RUBIN:

AND WE'RE PREPARED TO DO THAT.

UNITED STATES COURT REPORTERS

I THINK

255

94

1

THE INITIAL REQUEST WAS TO HAVE IT DUE TOMORROW, WHICH WE

2

WEREN'T IN A POSITION TO DO GIVEN THIS WEEK.

3
4

THE COURT:
NOW.

OKAY.

LET'S SET THIS SCHEDULE RIGHT

WHEN ARE YOU GOING TO FILE THE OPPOSITION?

5

MR. RUBIN:

WE CAN FILE A RESPONSE --

6

THE COURT:

WHEN ARE YOU GOING TO FILE A REPLY?

7

MR. RUBIN:

WE CAN FILE A RESPONSE BY NEXT FRIDAY,

8

AND I BELIEVE PLAINTIFFS SAID THEY DON'T NEED A REPLY AND THEY

9

WERE PREPARED TO SUBMIT.

10

AND SO I THINK THAT WE WOULD BE PREPARED TO DO THAT.

11

BE PREPARED TO SET -- AN EIGHT PAGE BRIEF I THINK IS WHAT THEY

12

PROPOSED, SUBMIT ANY SUPPORTING DECLARATIONS, AND SUBMIT WITH

13

THE EIGHT PAGE BRIEF AND LET EITHER YOUR HONOR OR JUDGE GREWAL

14

DECIDE THE ISSUE.

15

THE COURT:

I THINK JUDGE GREWAL --

16

MR. RUBIN:

OKAY.

17

THE COURT:

-- IS THE DECIDER ON THAT.

18

MS. DERMODY:

WE'D

19

YES, WE WOULD WAIVE THE REPLY AND WE

WOULD WAIVE ARGUMENT JUST TO MOVE THIS ALONG.

20

THE COURT:

OKAY.

21

MR. RUBIN:

SO WE'LL SEND THAT BY FRIDAY, THE 25TH.

22

THE COURT:

THE 24TH.

23

WRONG YEAR.

24

RIGHT.

25

I'M SORRY.

OH, MAYBE I'M LOOKING AT THE

MR. RUBIN:

I'M LOOKING AT THE WRONG YEAR.

YOU'RE

JANUARY 25TH.

UNITED STATES COURT REPORTERS

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1

THE COURT:

I'M A LITTLE BIT UNCLEAR ON HOW THIS

2

DOCUMENT DISCOVERY WORKED SO FAR.

3

PRODUCE DOCUMENTS OF CUSTODIANS THAT ARE IDENTIFIED BY THE

4

PLAINTIFFS?

5

MS. DERMODY:

DID THE DEFENDANTS ONLY

THAT HAS BEEN A POINT OF CONTENTION,

6

YOUR HONOR, ACTUALLY.

7

THAT IF A WITNESS IS ON THE RULE 26 DISCLOSURE, THEY SHOULD BE

8

A CUSTODIAN BECAUSE THEY WERE IDENTIFIED AS A WITNESS IN THE

9

CASE.

10

WE HAVE -- WE BELIEVED FOR SOME TIME

IT BECAME CLEAR TO US OVER TIME THAT THAT WASN'T ALWAYS

11

THE PRACTICE OF EVERY DEFENDANT, AND WE'VE HAD -- AS THE COURT

12

MIGHT HAVE SEEN IN THE DECEMBER 12TH CMC STATEMENT THAT WE

13

PREVIOUSLY SUBMITTED, THERE WAS A LOT OF DISAGREEMENT BETWEEN

14

THE PARTIES ABOUT WITNESSES AND THE TIMING OF DISCLOSING

15

WITNESSES.

16

I THINK THAT WE NOW AT LEAST HAVE MADE CLEAR OUR REQUEST

17

THAT EVERYONE WHO'S ON DEFENDANTS' RULE 26 DISCLOSURE LIST

18

SHOULD BE A CUSTODIAN AND THEIR DOCUMENTS SHOULD BE DISCLOSED.

19

PRESUMABLY WE'LL TAKE THE DEPOSITIONS OF ALL OF THOSE PEOPLE.

20

WE -- AS WE'RE GETTING MORE DOCUMENTS, WE'VE BECOME AWARE

21

OF THE PEOPLE WHO ARE MOST INSTRUMENTAL IN THE CHAIN AND WE, AS

22

QUICKLY AS WE CAN, RAISE THOSE ISSUES WITH THE DEFENDANTS.

23

WE'VE HAD VERY EXTENSIVE MEET AND CONFERS WITH A NUMBER OF

24

DEFENDANTS, INCLUDING APPLE AND GOOGLE, TRYING TO ACCOMMODATE

25

RESISTANCE OF THE DEFENDANTS TO SOME OF OUR WITNESS LISTS AND

UNITED STATES COURT REPORTERS

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96

1

WE'VE CUT DOWN WITNESS LISTS AND WE'VE TRIED TO REDUCE

2

REDUNDANCIES.

3

IT'S A CHALLENGE WITH THOSE COMPANIES.

GOOGLE IN

4

PARTICULAR HAD SUCH A BIG RECRUITING DEPARTMENT THAT FOR US TO

5

GET A SENSE OF HOW THINGS WERE DONE, WE THOUGHT WE HAD TO GET A

6

FEW MORE PEOPLE THAN WE HAD INITIALLY REQUESTED.

7

ONGOING DEBATE WITH THEM.

8

COURT ON THAT.

9
10
11

THAT'S AN

WE MIGHT HAVE TO COME BACK TO THE

SO FAR I THINK THAT WE'RE WORKING PRETTY SMOOTHLY, BUT
THERE HAVE BEEN SOME HICCUPS IN THE ROAD.
THE COURT:

SO THERE'S NO DOCUMENT REQUEST THAT

12

SAYS, YOU KNOW, "PRODUCE ALL DOCUMENTS THAT YOU INTEND TO RELY

13

ON AT TRIAL OR FOR THE CLASS CERTIFICATION MOTION"?

14

MS. DERMODY:

15

MR. SAVERI:

16
17

YEAH.
WE -- I THINK ACTUALLY THERE'S MORE

THAN ONE THAT SAYS, IN SUM OR SUBSTANCE, THAT.
THE COURT:

OKAY.

BECAUSE I DIDN'T UNDERSTAND WITH,

18

FOR EXAMPLE, MS. MAUPIN, LUCASFILM SAYS, "WELL, WE PROPOSED

19

ONLY 16 KEY CUSTODIANS OUT OF THE PLAINTIFFS' LIST OF 57, AND

20

THEY NEVER RESPONDED TO OUR LETTER, SO WE HAD NO OBLIGATION TO

21

DISCLOSE THE DOCUMENTS OF ANYONE OTHER THAN OUR 16, EVEN IF WE

22

WERE INTENDING TO RELY ON THESE INDIVIDUALS IN OUR OPPOSITION

23

TO CLASS CERT."

24
25

I THOUGHT THAT WAS KIND OF A WEAK ARGUMENT.
MR. PURCELL:

I'M NOT SURE, DID WE ACTUALLY SAY

UNITED STATES COURT REPORTERS

258

97

1

THAT?

2

I'M NOT SURE THAT WE SAID EXACTLY THAT.

WHAT WE SAID WAS THAT WE HAD A MEET AND CONFER WITH THEM,

3

WE WERE TRYING TO IMPOSE A REASONABLE LIMIT ON THE NUMBER OF

4

CUSTODIANS AND WE MADE A COUNTER PROPOSAL THAT THEY NEVER

5

RESPONDED TO.

6
7

AT THE POINT THAT WE HAD THAT DISCUSSION, THAT WAS IN
MARCH OF LAST YEAR.

8
9

THE COURT:

MS. MAUPIN -SO TELL ME, FOR THE ENTIRE YEAR, SINCE

MARCH, YOU'VE ONLY BEEN PRODUCING DOCUMENTS AS TO THE 16 PEOPLE

10

THAT YOU UNILATERALLY SELECTED --

11

MR. PURCELL:

12

THE COURT:

13

MR. PURCELL:

14

WE DIDN'T UNILATERALLY --

-- AS THE CUSTODIANS?
WE DIDN'T UNILATERALLY SELECT THEM.

WE SELECTED THEM --

15

THE COURT:

OUT OF THE 57.

16

MR. PURCELL:

-- IN A MEET AND CONFER WITH

17

PLAINTIFFS, AND IF THEY HAD A COUNTER PROPOSAL, WE WOULD EXPECT

18

THEM TO MAKE A COUNTER PROPOSAL.

19

THE COURT:

OKAY.

SO IF THERE ARE ANY OTHER

20

WITNESSES YOU ARE INTENDING TO RELY ON AT TRIAL, YOU ARE NOT

21

PRODUCING THEIR DOCUMENTS BECAUSE THEY'RE NOT ON YOUR LIST OF

22

16?

23

MR. PURCELL:

WE'VE SUBSEQUENTLY HAD ADDITIONAL MEET

24

AND CONFERS AND WE'VE PRODUCED FROM OTHER CUSTODIANS, INCLUDING

25

MS. MAUPIN WHO, BY THE WAY, WAS NOT ADDED TO OUR INITIAL

UNITED STATES COURT REPORTERS

259

98

1

DISCLOSURES UNTIL SEPTEMBER OF THIS YEAR.

2

LITTLE LATER, BUT IN PLENTY OF TIME TO BE DEPOSED AND TO HAVE

3

HER DOCUMENTS PRODUCED, BOTH OF WHICH THINGS ARE SCHEDULED AND

4

ARE GOING TO BE COMPLETED IN THE NEXT FEW WEEKS.

5
6

THE COURT:

SHE WAS ADDED A

WHEN DID YOU FIRST PRODUCE DOCUMENTS FOR

MS. MAUPIN?

7

MR. PURCELL:

WE PRODUCED THE VAST VOLUME OF WHAT WE

8

CALL TRACK ONE DOCUMENTS EARLIER THIS YEAR, I THINK IN THE

9

MIDDLE OF THE YEAR, WHICH CONSISTS BASICALLY OF ALL OF

10

LUCASFILM'S COMPENSATION DATA, ALL OF THE THINGS THAT

11

DR. LEAMER PURPORTED TO RELY ON IN HIS REPORT.

12

WE HAVE SOME ADDITIONAL DOCUMENTS FROM MS. MAUPIN THAT ARE

13

IN PROCESS NOW AND THAT ARE GOING TO BE PRODUCED AROUND

14

FEBRUARY 1ST.

15

AND THAT WAS --

16

THE COURT:

I DON'T UNDERSTAND.

WHY ARE YOU -- YOU

17

RELY ON HER DECLARATION FOR YOUR OPPOSITION THAT'S FILED, WHAT,

18

IN DECEMBER, AND THEN YOU PRODUCE HER DOCUMENTS IN FEBRUARY?

19
20
21

MR. PURCELL:

WELL, THEY ASKED FOR THE DOCUMENTS AND

THEY ASKED FOR THE DEPOSITION IN DECEMBER OR NOVEMBER.
YOUR HONOR, I DON'T BELIEVE THERE'S ANY OBLIGATION THAT

22

EVERYBODY ON YOUR RULE 26 DISCLOSURE HAS TO BE A DOCUMENT

23

CUSTODIAN.

24

THE RULE.

25

I JUST DON'T THINK THAT'S THE LAW.

THE COURT:

THAT'S NOT IN

WELL, I THINK THERE'S BEEN A DOCUMENT

UNITED STATES COURT REPORTERS

260

99

1

REQUEST THAT YOU PRODUCE DOCUMENTS THAT YOU INTEND TO RELY ON

2

FOR YOUR DEFENSES, SO WHY WOULD THAT NOT INCLUDE WHATEVER YOU

3

HAVE FOR MS. MAUPIN?

4

MR. PURCELL:

5

ARE PRODUCING THEM NOW.

6

THE COURT:

WELL, IT IS INCLUDING IT.

I MEAN, WE

YOU'RE PRODUCING THEM FEBRUARY 1ST AFTER

7

YOU'VE ALREADY RELIED ON HER DECLARATION FOR YOUR OPPOSITION

8

FOR YOUR EXPERT REPORT.

9

MR. PURCELL:

10
11

I THINK THAT'S PROBLEMATIC.
I GUESS I WOULD DISAGREE, YOUR HONOR.

I DON'T SEE WHY THAT'S PROBLEMATIC.
THEY RAISED THE ISSUE, OBVIOUSLY --

12

THE COURT:

WOULD YOU BE SATISFIED IF YOU DIDN'T

13

HAVE THE PLAINTIFFS' DOCUMENTS AND YOU'RE REQUIRED TO FILE AN

14

OPPOSITION TO THEIR MOTION FOR CLASS CERT WITHOUT HAVING ALL

15

THE PLAINTIFFS' DOCUMENTS AND THE PLAINTIFFS COME IN AND SAY,

16

"WELL, WE'RE PRODUCING THEM ON FEBRUARY 1ST"?

17
18

MR. PURCELL:

WELL, I MIGHT RAISE THE ISSUE, YOUR

HONOR.

19

BUT THEY HAD THE OPPORTUNITY TO ASK FOR ADDITIONAL

20

CUSTODIANS, INCLUDING MS. MAUPIN -- THEY KNEW WHO MS. MAUPIN

21

WAS -- AND THEY NEVER RESPONDED TO A LETTER THAT WE SENT THEM

22

SAYING "WE THINK 57 CUSTODIANS IMPOSES AN UNREASONABLE BURDEN.

23

HOW ABOUT THESE 16 WHICH ARE THE CORE PEOPLE?"

24
25

WE NEVER HEARD FROM THEM FOR SIX TO EIGHT MONTHS.

THAT'S

NOT DILIGENCE, YOUR HONOR.

UNITED STATES COURT REPORTERS

261

100

1

THE COURT:

A CASE OF THIS MAGNITUDE -- YOU THINK 57

2

CUSTODIANS IS TOO MUCH TO COLLECT DOCUMENTS FROM IN A CASE OF

3

THIS MAGNITUDE?

4
5
6

MR. PURCELL:

IN A COMPANY OF 400 WORKERS, YES, YOUR

HONOR.
AND IN ANY EVENT, IF THEY DISAGREED, WHICH THEY DID

7

EVENTUALLY AFTER THE FACT, THEY HAD AN OBLIGATION TO BE

8

DILIGENT AND FOLLOW UP WITH US, WHICH THEY DIDN'T DO.

9

CAN'T SIT ON THEIR HANDS FOR SIX TO EIGHT MONTHS AND THEN COME

10
11

THEY

IN AND COMPLAIN THAT WE DIDN'T PRODUCE SOMETHING.
MS. DERMODY:

WELL, YOUR HONOR, I THINK IT'S A

12

LITTLE UNFAIR TO CHARACTERIZE OUR ACTION THAT WAY.

13

HAD TO RELY, AS YOU DO WHEN YOU HAVE NO INFORMATION, ON THE

14

GOOD FAITH OF THE DEFENDANTS IN PRODUCING THE RELEVANT

15

DOCUMENTS, THE CORE DOCUMENTS.

16

I MEAN, WE

WHEN MID-JUNE CAME AND WENT AND WE HAD A CHANCE TO LOOK AT

17

DOCUMENTS, WHAT IT REVEALED TO US IS WE WERE MISSING A LOT AND

18

WE GOT BACK TO DEFENDANTS WITH NAMES AS THEY CAME TO US.

19

IT WAS A SURPRISE TO US, QUITE CANDIDLY, WHEN WE

20

DISCOVERED THAT THE DEFENDANTS' EXPERT HAD BEEN TALKING TO

21

WITNESSES, DOING INTERVIEWS OVER THE SUMMER, AND THAT THOSE

22

PEOPLE WERE NOT DOCUMENT CUSTODIANS AND THOSE DOCUMENTS WEREN'T

23

PRODUCED TO US AND WE WERE STILL EXPECTED TO TELL THE

24

DEFENDANTS, "THESE PEOPLE THAT YOUR EXPERT THOUGHT WERE

25

IMPORTANT ENOUGH TO INTERVIEW, THE PLAINTIFFS HAVE TO COME

UNITED STATES COURT REPORTERS

262

101

1
2

FORWARD AND TELL YOU TO PRODUCE THOSE DOCUMENTS."
SO WE HAVE DONE THAT.

WE HAVE COME FORWARD AND WE HAVE

3

REQUESTED THINGS, AND SOMETIMES WE'VE HAD TO NEGOTIATE FOR

4

WEEKS ON SOMETHING AS SIMPLE AS THAT.

5

BUT WE HAVE DONE IT AND WE THINK THAT WE'RE DOING

6

EVERYTHING THAT WE CAN TO GET THE DOCUMENTS AS QUICKLY AS

7

POSSIBLE.

8

BUT THE NOTION THAT WE'RE SITTING ON OUR HANDS I DON'T

9

THINK IS A VERY FAIR ASSESSMENT OF WHAT HAS HAPPENED SO FAR FOR

10
11

PLAINTIFFS.
THE COURT:

IF AT SUMMARY JUDGMENT ANY PARTY RELIES

12

ON THE DECLARATION OF A WITNESS THAT THEY HAVE NOT PREVIOUSLY

13

PRODUCED DOCUMENTS FOR, I'M GOING TO STRIKE THAT DECLARATION.

14

MR. PURCELL:

15

THE COURT:

UNDERSTOOD, YOUR HONOR.

OKAY?

SO I'M REALLY DISPLEASED WITH THE

16

DEFENDANTS ON THIS EMPLOYEE ISSUE AND I'M GOING TO STRIKE

17

SEVERAL OF THOSE DECLARATIONS, IF NOT ALL OF THEM.

18

TO BE GAMESMANSHIP AND I'M REALLY DISAPPOINTED.

19

I FIND THIS

I HAD HOPED THAT I'D MADE IT CLEAR AT PREVIOUS CMC'S THAT

20

I REALLY DIDN'T WANT TO SEE THIS KIND OF GAMESMANSHIP, SO TO

21

PLAY HIDE THE BALL AND THEN SAY, "WELL, IT'S THEIR OBLIGATION

22

TO BE ABLE TO LOOK THROUGH OUR OPAQUE COMPANY AND FIGURE OUT

23

WHO IS THE RELEVANT PERSON THEY SHOULD ASK FOR DOCUMENTS FROM"

24

WHEN THEY'RE NOT ON YOUR INITIAL DISCLOSURES IN MOST INSTANCES,

25

I'M JUST VERY DISAPPOINTED.

UNITED STATES COURT REPORTERS

263

102

1

ANYWAY, ALL RIGHT.

2

DEPOSITIONS.

3

LET'S GO THROUGH WITH THE REST OF THE

GOING TO GO FORWARD.

4
5
6
7

THESE ARE GOING TO BE SCHEDULED AND THESE ARE

MS. DERMODY:

THANK YOU, YOUR HONOR.

FOR PIXAR, WE HAVE ED CATMULL, C-A-T-M-U-L-L, ON
JANUARY 24TH.
FOR INTUIT, BILL CAMPBELL, FEBRUARY THE 5TH.

AND WE

8

TALKED ABOUT HIM EARLIER AND THE DOCUMENTS THAT ARE

9

OUTSTANDING.

10
11

AND THEN WE HAVE REQUESTED QUITE A FEW WITNESSES FROM
APPLE THAT HAVE NOT BEEN SCHEDULED.

12

THE COURT:

OKAY.

13

MS. DERMODY:

WHO HAVE YOU REQUESTED?

SO ON THE RULE 26 DISCLOSURES, THERE

14

ARE ONE, TWO, THREE, FOUR, FIVE, SIX, SEVEN, EIGHT, NINE PEOPLE

15

THEY'VE LISTED.

16

THE NAMES IF YOU'D LIKE, YOUR HONOR.

WE'VE REQUESTED ALL OF THEM.

17

THE COURT:

18

MS. DERMODY:

19

THE COURT:

20

I CAN GIVE YOU

AND YOU DON'T HAVE ANY DATES?
NO DATES.

ALL RIGHT.

WHO'S HERE FROM APPLE?

IS

THAT MR. TUBACH?

21

MR. TUBACH:

22

THE COURT:

23

PROVIDE DATES FOR THE WITNESSES.

24

MR. TUBACH:

25

YES.
GIVE ME A DATE BY WHICH YOU'RE GOING TO

I CAN GIVE YOU THE DATES, SAME AS FOR

GOOGLE, A WEEK FROM FRIDAY IF THAT'S OKAY WITH THE COURT.

UNITED STATES COURT REPORTERS

264

103

1

THE COURT:

2

WHEN DID YOU REQUEST THESE DEPOSITIONS?

MR. TUBACH:

DECEMBER 17TH, YOUR HONOR, IN ONE

3

LETTER THEY SENT TO ALL DEFENDANTS SAYING, "WE WANT DATES FOR

4

EVERY PERSON ON YOUR RULE 26 LIST."

5
6
7

THE COURT:

10

SO THAT WOULD BE

JANUARY 25TH.
ALL RIGHT.

8
9

ALL RIGHT.

WHO ELSE DO YOU NEED?

MS. DERMODY:

YOUR HONOR, THAT SO FAR IS THE LIST OF

NAMES THAT I HAVE.
AS I MENTIONED, WE HAVE REQUESTED ALL THE RULE 26 PEOPLE

11

FROM ALL DEFENDANTS.

12

WITNESSES.

13

WE HAVE NOT RECEIVED EVERYONE'S

AND WE HAVE BEEN WORKING WITH GOOGLE ON AN ADDITIONAL

14

GROUP OF CUSTODIANS.

15

DEPOSITION DATES FOR ALL OF THEM OR SOME SUBSET OF THEM.

16
17
18

THE COURT:

I IMAGINE THAT WE ARE GOING TO REQUEST

OKAY.

I DO WANT TO TALK ABOUT

CUSTODIANS -- I'M SORRY TO INTERRUPT YOU.
WHAT ABOUT DEBORAH CONRAD?

SHE WAS IN YOUR CMC STATEMENT.

19

HAS SHE BEEN DEPOSED OR NOT?

I HAD ON MY LIST THAT IT WAS

20

PATRICIA MURRAY, THE SENIOR VICE-PRESIDENT --

21

MR. SAVERI:

YES.

22

MR. HINMAN:

YOU TOOK THAT DEPOSITION.

23

MR. SAVERI:

I TOOK DEBORAH CONRAD'S DEPOSITION.

24

THE COURT:

25

MR. SAVERI:

OKAY.

SO THAT'S DONE.

THAT'S DONE.

UNITED STATES COURT REPORTERS

265

104

1
2

THE COURT:

OTHER THAN THE ONES THAT YOU'VE LISTED?

3
4
5

SO ANYONE ELSE THAT NEEDS TO BE DEPOSED,

MR. SAVERI:

THAT WE'VE -- AGAIN, MS. DERMODY

IDENTIFIED WHERE WE ARE WITH GOOGLE.
AND YOU KNOW, OF COURSE PART OF THE PROBLEM WE FACE, YOUR

6

HONOR, IS THAT WHEN WE REVIEW DOCUMENTS, WE MAY FIND ADDITIONAL

7

WITNESSES.

8
9
10

BUT TO THE BEST OF OUR RECOLLECTION AT THIS POINT, WE'VE
GIVEN YOU A COMPLETE LIST OF WHO WE'VE IDENTIFIED AND REQUESTED
AT THIS TIME.

11

THE COURT:

12

MS. DERMODY:

13

THE COURT:

14

MR. SAVERI:

15

MS. DERMODY:

16
17

ALL RIGHT.
I'M SORRY --

LET'S TALK ABOUT THE DOCUMENT REQUESTS.
I'M SORRY.

DID I MISSPEAK?

I WANT TO MAKE SURE THE RECORD IS

CLEAR.
FOR APPLE, YOUR HONOR, I DID SAY THERE ARE OUTSTANDING

18

RULE 26 WITNESSES.

THERE IS ALSO ONE SEPARATE WITNESS,

19

TIM COOK, THAT THERE'S BEEN A NEGOTIATION FOR A WHILE ABOUT A

20

DATE, I BELIEVE, FOR TIM COOK, AND IF THAT CAN BE ON THE LIST

21

FOR NEXT FRIDAY OF SOMEONE TO SCHEDULE --

22

MR. TUBACH:

NO, YOUR HONOR, WE HAVEN'T AGREED TO

23

PRODUCE TIM COOK FOR DEPOSITION.

24

WE AMENDED THAT LIST, PROVIDED IT TO PLAINTIFFS, AND TOOK HIM

25

OFF THE LIST.

HE WAS ON OUR RULE 26 LIST.

UNITED STATES COURT REPORTERS

266

105

1

BASED ON THE DEPOSITIONS OF TWO APPLE WITNESSES, THEY

2

CONFIRM THAT MR. COOK WAS NOT INVOLVED AND DOES NOT HAVE

3

FIRSTHAND KNOWLEDGE OF ANY OF THESE AGREEMENTS AND DOES NOT

4

HAVE DISCOVERABLE INFORMATION, SO WE REMOVED HIM FROM THE RULE

5

26 LIST.

6
7
8
9
10

PLAINTIFFS TOLD US TWO DAYS AGO THAT THEY DISAGREED WITH
THAT, SO IF THAT NEEDS TO BE BROUGHT TO THE -THE COURT:

WHEN DID HE ASSUME HIS ROLE?

I MEAN, I

KNOW HE'S BEEN AT APPLE FOR A VERY LONG TIME.
MR. SAVERI:

WELL, AND THAT'S -- YOUR HONOR, HIS

11

ROLE HAS CHANGED, AND IT CHANGED IN A SIGNIFICANT WAY.

12

BECAME MORE SENIOR WITH THE PASSAGE OF TIME IN THE COMPANY.

13

DON'T KNOW EXACTLY WHEN THE DATES ARE.

14

THE COURT:

15

MR. SAVERI:

16

THE COURT:

17

MR. SAVERI:

HE
I

WAS IT DURING THE CLASS PERIOD?
YES.
IT'S BEFORE 2009?
YES.

SO THERE ARE DOCUMENTS, WE

18

BELIEVE, AND WE -- THIS IS PART OF THE DISAGREEMENT.

19

DOCUMENTS, RELEVANT DOCUMENTS IN THIS CASE THAT, FRANKLY, WE

20

THINK ARE GOING TO BE EVIDENCE AT TRIAL THAT MR. COOK RECEIVED

21

AND HAS KNOWLEDGE OF.

22

THE COURT:

23
24
25

THERE ARE

WHEN -- I KNOW HE'S HAD VARIOUS ROLES.

TELL ME WHAT HIS ROLE WAS BEFORE DECEMBER OF 2009.
MR. RILEY:

YOUR HONOR, HE WAS THE -- THIS IS

GEORGE RILEY FOR APPLE -- HE WAS THE CHIEF OPERATING OFFICER OF

UNITED STATES COURT REPORTERS

267

106

1
2
3

THE COMPANY.

HE HAD NO ROLE IN H.R., NO ROLE IN RECRUITING.

SUBSEQUENT, AFTER MR. JOBS HAD AN OPERATION, HE BECAME
ACTING CEO.

4

LATER WHEN MR. JOBS RETURNED TO THE COMPANY, MR. COOK

5

BECAME CEO IN AUGUST OF 2011, WELL AFTER THE CLASS PERIOD.

6

THE COURT:

WELL, I JUST FIND IT REALLY HARD TO

7

BELIEVE THAT A CHIEF OPERATING OFFICER WOULD HAVE NO SAY OVER

8

SALARIES AND COMPENSATION OF ALL OF THE EMPLOYEES OF THE

9

COMPANY.

10

MR. RILEY:

AT APPLE --

11

MR. SAVERI:

EXCUSE ME.

12

MR. RILEY:

AT APPLE, THE CHIEF OPERATING OFFICER

13

WORKS ON OPERATIONS.

THE COMPENSATION OFFERS ARE SET BY THE

14

COMPENSATION COMMITTEE.

15

MR. COOK HAD NO REPORTING OBLIGATIONS, NO REPORTING LINES

16

AT ALL TO THE COMPENSATION COMMITTEE.

17

APPLE REPORTS DIRECTLY TO THE CEO, MR. JOBS.

18
19
20

THE H.R. DIRECTOR AT

SO, YOUR HONOR, THAT'S WHY WE -- THEY TOOK THE
DEPOSITION -THE COURT:

SO SOMEONE IN CHARGE OF OPERATION HAS NO

21

SAY OR NO KNOWLEDGE ABOUT THE GREATEST PROBABLY EXPENSE OF

22

OPERATIONS, WHICH IS SALARIES AND COMPENSATION OF EMPLOYEES?

23
24
25

MR. RILEY:

OBVIOUSLY HE WOULD HAVE THE SAME

KNOWLEDGE AS ANY EXECUTIVE OFFICER WOULD OF THE BUDGET.
BUT IN TERMS OF ACTUALLY SETTING COMPENSATION LEVELS FOR

UNITED STATES COURT REPORTERS

268

107

1

THE COMPANY COMPANY-WIDE, HE DID NOT PLAY A ROLE IN THAT.

2

AND THEY HAVE HAD AN OPPORTUNITY TO DEPOSE THOSE

3
4

INDIVIDUALS WHO DID PLAY THOSE ROLES.
AND, YOUR HONOR, THEY HAVE NOT PRODUCED IN THIS CASE ANY

5

E-MAIL THAT HAS MR. COOK'S NAME ON IT THAT RELATES TO THESE

6

AGREEMENTS AT ALL.

7

THE COURT:

HAVE YOU PRODUCED MR. COOK'S DOCUMENTS?

8

MR. SAVERI:

WELL, I'M SORRY, THEY ARE MR. COOK'S

9
10

DOCUMENTS.
THE COURT:

I KNOW.

THAT'S WHAT I'M ASKING.

I'M

11

ASKING -- YOU'RE SAYING PLAINTIFFS HAVEN'T PRODUCED A SINGLE

12

E-MAIL FROM MR. COOK.

13
14

SO LET ME ASK YOU, HAVE YOU PRODUCED MR. COOK'S E-MAILS?
BECAUSE YOU WOULD HAVE THEM MORE THAN THE PLAINTIFFS.

15

MR. RILEY:

WE --

16

THE COURT:

HAS THERE BEEN ANY DOCUMENT COLLECTION

17

OF MR. COOK'S DOCUMENTS SUCH THAT THE PLAINTIFFS COULD HAVE

18

POINTED TO A DOCUMENT, THE RELEVANT DOCUMENT THAT HE WOULD BE

19

LISTED AS A RECIPIENT OR SENDER?

20

MR. RILEY:

YES, YOUR HONOR.

IN CONNECTION WITH THE

21

DEPARTMENT OF JUSTICE INVESTIGATION, WE DID A SEARCH AND WE

22

PRODUCED DOCUMENTS, AND I BELIEVE THEY HAVE GOTTEN A HANDFUL OF

23

DOCUMENTS, NOT RELEVANT TO THESE AGREEMENTS, THAT HAVE

24

MR. COOK'S NAME ON THEM.

25

BUT THAT'S -- THAT IS THE POINT, YOUR HONOR, AND THAT'S

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WHY THEY HAVEN'T ASKED FOR HIS DEPOSITION ANY EARLIER IS THAT

2

HE DID NOT PLAY A ROLE IN THESE AGREEMENTS.

3
4

THE COURT:

WHEN WAS THE DOCUMENT PRODUCTION IN THE

D.O.J. CASE?

5

MR. SAVERI:

6

WAS THEIR PRODUCTION.

7

MR. RILEY:

8

MR. SAVERI:

9

WHEN WAS IT?

AGAIN, I DON'T KNOW.

IT

YOUR HONOR -IT WAS PRESUMABLY SOME TIME DURING THE

PROCEEDING.

10

MR. RILEY:

11

PRODUCE FOR MR. COOK.

12

THE COURT:

YOUR HONOR, WE DID THOROUGHLY SEARCH AND
HE WAS A CUSTODIAN.
I JUST DON'T THINK THAT HIS ROLE -- IF I

13

REMEMBER CORRECTLY THE DATES OF THAT D.O.J. CASE, I THINK IT

14

MAY HAVE PRECEDED HIS SORT OF ASCENDENCY AT THE COMPANY.

15

MR. SAVERI:

AND YOUR HONOR, IF I MAY, I MEAN, I --

16

THERE'S AT LEAST ONE DOCUMENT, I BELIEVE, THAT IS -- THAT HAS

17

RELEVANT INFORMATION THAT THE DEFENDANTS DID PRODUCE TO US.

18

DON'T KNOW THE GENESIS OF IT AND WHOSE FILE IT CAME FROM, BUT

19

IT HAS MR. COOK'S NAME ON IT.

20

I

AND MR. COOK, WE BELIEVE, FROM WHAT WE UNDERSTAND, WAS

21

AWARE OF APPLE'S DO NOT COLD CALL LIST AND SO WE THINK HE'S A

22

PERCIPIENT WITNESS.

23

AND IT STANDS TO REASON THAT SOMEONE AT THAT LEVEL IN THE

24

COMPANY KNEW ABOUT THE EXISTENCE OF THE DO NOT COLD CALL LIST,

25

KNEW ABOUT WHAT WAS GOING ON WITH RESPECT TO COMPENSATION.

UNITED STATES COURT REPORTERS

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1
2
3

BUT AGAIN, YOUR HONOR, WE'D LIKE TO PUT HIM UNDER OATH AND
ASK THE QUESTIONS.

THAT'S THE WAY THE PROCEDURE WORKS.

I MEAN, WE'RE NOT -- THIS ISN'T JUST A WILD GOOSE CHASE.

4

MR. RILEY:

YOUR HONOR, WE PRODUCED ALL OF HIS

5

DOCUMENTS.

WE UPDATED THAT PRODUCTION AFTER THE D.O.J. CASE.

6

THEY DIDN'T HAVE ANY DOCUMENTS TO MR. COOK THAT RELATE TO THESE

7

AGREEMENTS OR TO THE DO NOT CALL LIST.

8

THEY DEPOSED THE HEADS OF H.R., BOTH PAST AND CURRENT, WHO

9

TESTIFIED UNDER OATH THAT THEY HAD NO DISCUSSIONS WITH MR. COOK

10

WHATSOEVER ABOUT THIS.

11

THE COURT:

I'M GOING TO ORDER HIS DEPOSITION.

12

MR. RILEY:

YOUR HONOR, WE WOULD LIKE IT LIMITED TO

14

THE COURT:

I THINK A LIMIT OF HOURS IS REASONABLE.

15

MR. SAVERI:

13

16

TWO HOURS.

ASKING A LOT.

YOUR HONOR, I THINK TWO HOURS IS REALLY

PERHAPS --

17

THE COURT:

MAKE A COUNTER PROPOSAL.

18

MR. SAVERI:

I WOULD SAY HALF A DAY.

19

THE COURT:

20

MR. SAVERI:

21

MS. DERMODY:

FOUR HOURS?
FOUR HOURS IS FINE.
AND WE WOULD ASK, YOUR HONOR, THAT HE

22

BE A DOCUMENT CUSTODIAN SO THAT THAT DEPOSITION BECOMES MORE

23

FRUITFUL THAN JUST ON A BLANK RECORD.

24
25

MR. RILEY:
DOCUMENT CUSTODIAN.

I WILL SAY FOR THE THIRD TIME, HE WAS A
WE DID PRODUCE HIS DOCUMENTS.

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2

THE COURT:

WELL, I WOULD JUST ASK THAT YOU CONFIRM

MR. SAVERI:

AND MAYBE I DO -- WE NEED TO CLARIFY

THAT.

3
4

THIS.

WHEN MR. -- WHEN APPLE AFFIRMS THAT HE WAS A DOCUMENT

5

CUSTODIAN, DOES THAT MEAN HE WAS A DOCUMENT CUSTODIAN FOR THE

6

D.O.J. CASE AND THIS CASE OR BOTH?

7
8
9
10

MR. RILEY:

BOTH.

OR --

WE -- EARLY ON IN THIS CASE WE

PRODUCED ALL THE DOCUMENTS THAT WE PRODUCED TO THE D.O.J.
WE'VE SUBSEQUENTLY SEARCHED HIS DOCUMENTS AS A CUSTODIAN
IN THIS CASE.

I DON'T KNOW IF I CAN BE ANY CLEARER THAN THAT.

11

MR. SAVERI:

THAT'S CLEAR.

12

MS. DERMODY:

I MISUNDERSTOOD YOU.

YOU'RE -- SO WE

13

UNDERSTAND, YOU'RE SAYING THAT YOU ACTUALLY USED THE SEARCH

14

TERMS AGREED TO IN THIS CASE AGAINST HIS E-DISCOVERY?

15

MR. RILEY:

16

MS. DERMODY:

17

THE COURT:

18
19

YES.
OKAY.

THANK YOU.

ALL RIGHT.

HE'LL BE DEPOSED FOR FOUR

HOURS.
WHO ELSE?

20

WHO ELSE NEEDS TO BE DEPOSED IN THIS CASE?

MS. DERMODY:

I THINK THAT'S THE COMPLETE LIST THAT

21

WE HAVE RIGHT NOW, YOUR HONOR.

THANK YOU FOR THE OPPORTUNITY.

22

THE COURT:

LET'S TALK ABOUT DOCUMENT

23
24
25

ALL RIGHT.

REQUESTS.
WITH REGARD TO KARINE KARPATI, CARSON PAGE, PATRICK FLYNN,
YOU'RE GOING TO PRODUCE THEIR DOCUMENTS.

I KNOW YOU'RE SAYING

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THEY'RE LOW LEVEL H.R. PEOPLE.

2

DOCUMENTS.

3

THEIR NAMES ON ARE RELEVANT

THEM.

YOU NEED TO REVIEW AND PRODUCE DOCUMENTS AS TO

4

LET ME HEAR ABOUT LARRY PAGE AND SERGEY BRIN.

5

MY UNDERSTANDING OF THIS CASE IS THAT THESE AGREEMENTS

6

HAPPENED AT THE HIGHEST LEVELS OF ALL OF THESE COMPANIES AND

7

THE HIGHEST LEVELS OF THESE COMPANIES WERE INVOLVED IN

8

ENFORCEMENT OF THE AGREEMENTS.

9
10
11

SO LET ME HEAR WHY LARRY PAGE AND MR. BRIN SHOULD NOT BE
CUSTODIANS.

GO AHEAD.

MR. RUBIN:

YOUR HONOR, FIRST OF ALL, WE HAD ALREADY

12

REACHED AT LEAST PARTIAL AGREEMENT ABOUT THE GROUP THAT YOU HAD

13

ALREADY SAID AND WE WOULD AGREE TO SEARCH KARINE KARPATI'S

14

E-MAILS AND I BELIEVE -- WHO WAS THE OTHER -- WHAT WAS THE

15

OTHER NAME?

16

THE COURT:

CARSON PAGE AND PATRICK FLYNN.

17

MR. RUBIN:

PATRICK FLYNN.

18

THE COURT:

IN THE JOINT CASE MANAGEMENT STATEMENT,

19

YOUR POSITION IS THEY ARE TWO LOW LEVEL H.R. PEOPLE AND YOU

20

WOULDN'T GET ANYTHING RELEVANT FROM THEM.

21

MR. RUBIN:

AND WE HAD ACTUALLY AGREED THAT BECAUSE

22

KARINE CARPATTI AND CARSON PAGE WERE DUPLICATE, THEY AGREED TO

23

DROP CARSON PAGE.

24

WAS WHAT THE LETTER SAID.

25

THAT'S PART OF OUR ONGOING DISCUSSION.

MS. SHAVER:

I'M SORRY.

THAT

ANNE SHAVER FOR PLAINTIFFS.

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WE'VE HAD ONGOING MEET AND CONFER EFFORTS.

2

REACHED AN AGREEMENT.

3

MR. RUBIN:

WE HAVEN'T

4
5

COULD I ASK PLAINTIFFS' COUNSEL, THAT

WAS A PROPOSAL IN THE LAST LETTER, THAT WE DROP CARSON PAGE.
MS. SHAVER:

AND WE -- THE PROPOSAL WAS DEPENDENT ON

6

A HOST OF AGREEMENTS, ALL THE CUSTODIANS THAT ARE AT ISSUE, AND

7

WE HAVEN'T HEARD BACK FROM YOU YET.

8
9
10
11

MR. RUBIN:

RIGHT.

SO --

SO ANYWAY, I HAD UNDERSTOOD WE

HAD REACHED A TENTATIVE AGREEMENT TO DROP CARSON PAGE, BUT KEEP
THE OTHER TWO.
WITH LARRY PAGE AND SERGEY BRIN, WE HAD AGREED TO, IN

12

CONCEPT, PRODUCE DOCUMENTS, WHICH WE ARE IN THE MIDDLE OF

13

WORKING WITH THE PLAINTIFFS ON PARTICULAR SEARCH TERMS.

14

WE'VE DONE SOME RUNNING OF TERMS AND WE'RE FINDING THERE'S

15

A GOOD NUMBER OF WHAT I'LL CALL FALSE POSITIVES, AND THEY ARE

16

SIGNIFICANT NUMBERS.

17
18
19

SO WE'RE SIMPLY TRYING TO NARROW IT DOWN IN A WAY THAT I
THINK EACH SIDE CAN LIVE WITH AND THEN RUN THOSE TERMS.
SO WE'RE NOT TAKING A POSITION NOT TO RUN THEM.

WE'RE

20

JUST SIMPLY SAYING LET'S KEEP THEM NARROWED TO WHAT THE LIKELY

21

ISSUES ARE FOR THOSE TWO CUSTODIANS.

22

THE COURT:

ALL RIGHT.

YOU'RE GOING TO PRODUCE

23

DOCUMENTS FOR ALL FIVE OF THEM, LARRY PAGE, SERGEY BRIN,

24

KARINE KARPATI, CARSON PAGE, AND PATRICK FLYNN.

25

OKAY?

NOW, I WANT TO KNOW THE DATES OF WHEN THESE

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1

DOCUMENTS ARE GOING TO BE PRODUCED, OKAY?

2

DATES.

3

LET'S START DOING

SO YOU TELL ME.
MR. RUBIN:

YOUR HONOR, I WOULD THINK FROM THE TIME

4

THAT WE COULD -- WE WOULD TRY TO MEET AND CONFER WITH

5

PLAINTIFFS NEXT WEEK TO AGREE ON IF WE CAN --

6

THE COURT:

NO.

I WANT A DATE.

I DON'T WANT THIS

7

HANGING OUT THERE.

8

TO SET A HEARING AND EVERYTHING LIKE THAT.

9

I DON'T WANT THIS TO BE BRIEFED AND HAVING

MR. RUBIN:

I WANT A DATE.

JANUARY 25TH, SO I WOULD SAY THREE WEEKS

10

FROM THE 25TH, SO WHATEVER THAT DATE IS.

11

FEBRUARY THE 15TH.

12

THE COURT:

THAT WOULD BE

NOW, I GUESS THIS IS THE PROBLEM.

YOU

13

HAVE DEPOSITIONS OF SHONA BROWN HAPPENING JANUARY 30TH AND

14

ERIC SCHMIDT ON FEBRUARY 20TH, AND I'M NOT GOING TO HAVE

15

DELAYED PRODUCTION OF DOCUMENTS BE THE REASON WHY THESE HAVE TO

16

CONTINUE TO BE POSTPONED.

SO --

17

MR. RUBIN:

WELL, THOSE CUSTODIANS --

18

THE COURT:

-- I THINK FEBRUARY 15TH IS TOO LATE.

19

MR. RUBIN:

WELL, THOSE DOCUMENTS HAVE BEEN FULLY

20

PRODUCED, SHONA BROWN'S AND ERIC SCHMIDT'S.

21

HAVE BEEN SUBJECT TO INITIAL PRODUCTIONS, SUPPLEMENTAL

22

PRODUCTIONS.

23

THOSE DOCUMENTS

SO I CERTAINLY CAN'T TELL YOU THAT THEY WOULDN'T SHOW UP

24

ON AN E-MAIL THAT WASN'T IN THEIR CUSTODIAL FILES AND NOW WOULD

25

BE IN THE OTHERS.

UNITED STATES COURT REPORTERS

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1

BUT I DO THINK THAT, YOUR HONOR, JUST BY WAY OF NECESSITY,

2

THERE'S SOME SEQUENCING THAT HAS TO TAKE PLACE.

3

SITUATION LIKE THIS WHERE I THINK PLAINTIFFS EXPLAINED THEY

4

CAME BACK, THEY ASKED FOR ADDITIONAL NAMES BASED UPON THE

5

PRODUCTION THAT WE HAD MADE, WE'VE THEN GONE BACK AND SAID YES

6

AS TO SOME, WHY AS TO OTHERS.

7

SO THERE HAS TO BE SOME SEQUENCING.

I MEAN, IN A

OTHERWISE EVERYBODY

8

WOULD WAIT UNTIL -- WE'RE JUST TRYING TO RESPOND TO THE

9

REQUESTS THAT HAVE COME AFTER OUR INITIAL PRODUCTIONS.

10

THE COURT:

WELL, I UNDERSTAND.

THE PROBLEM IS

11

WE'RE BREATHING DOWN THE NECK OF A MARCH 29TH FACT DISCOVERY

12

CUT OFF AND THE LATER THESE GET PRODUCED, THEN IT'S GOING TO

13

CREATE THIS MAD SCRAMBLE FOR EITHER ANY FOLLOW-UP DISCOVERY

14

REQUESTS OR MORE DEPOSITIONS AND THIS DEADLINE IS LOOMING, SO I

15

NEED IT SOONER THAN THAT.

16

MR. RUBIN:

WELL, I THINK WE COULD DO -- I THINK WE

17

COULD DO THE THREE -- WE'VE ALREADY -- THERE WERE FOUR THAT WE

18

HAD ALREADY AGREED TO.

19

EARLIER.

20
21

I THINK THOSE COULD BE PRODUCED

THE THREE, CARSON PAGE AND KARINE KARPATI AND
PATRICK FLYNN, PERHAPS THE WEEK BEFORE.

22

THE COURT:

OKAY.

23

MR. RUBIN:

BUT I REALLY DO -- WE REALLY DO NEED THE

24

TIME, YOUR HONOR, TO PRODUCE THE PAGE AND BRIN DOCUMENTS, SO --

25

WE REALLY DO.

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1

SO IF WE -- I CERTAINLY CAN PROPOSE A ROLLING PRODUCTION

2

OVER THE TWO WEEK PERIOD BEGINNING FEBRUARY 1, FEBRUARY 8TH,

3

FEBRUARY 15TH, AND THEN SUBSTANTIALLY COMPLETE THIS

4

SUPPLEMENTAL GROUP THAT WE'RE TRYING TO FOLLOW UP ON AT THEIR

5

REQUEST, THAT WE FINISH BY FEBRUARY 15TH, UNDERSTANDING THAT

6

PAGE AND BRIN MAY TAKE THE LONGEST TIME.

7
8

THE COURT:

WELL, I'D LIKE TO SAY FEBRUARY 1ST FOR

KARPATI, PAGE, AND FLYNN.

I'M SORRY, CARSON, PAGE, AND FLYNN.

9

MR. RUBIN:

CARSON PAGE IS ONE PERSON.

10

THE COURT:

FRANKLY --

11

MR. RUBIN:

THERE ARE TWO PAGES.

12
13
14

THERE'S LARRY PAGE

AND CARSON PAGE.
THE COURT:

KARINE KARPATI, CARSON PAGE, AND

PATRICK FLYNN, FEBRUARY 1ST.

15

MR. RUBIN:

OKAY.

16

THE COURT:

OKAY?

17

MR. RUBIN:

BUT IF WE COULD HAVE UNTIL THE 15TH,

I --

18

YOUR HONOR, FOR THE OTHER TWO, THAT WOULD -- I'M JUST TRYING TO

19

BE REALISTIC.

20

DOCUMENTS AND IT'S -- WE NEED THAT TIME.

21

WE'VE BEEN PRODUCING SUBSTANTIAL AMOUNTS OF

THE COURT:

I'LL GIVE YOU UNTIL FEBRUARY 11TH, OKAY,

22

JUST BECAUSE THEY MAY NEED THOSE DOCUMENTS FOR THE ERIC SCHMIDT

23

DEPOSITION ON FEBRUARY 20TH.

24

CAN KEEP GETTING KICKED DOWN THE ROAD.

25

CLOSE TO ALL OF THIS.

I DON'T WANT TO KEEP HAVING THE
WE NEED TO BRING A

UNITED STATES COURT REPORTERS

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1
2

ALL RIGHT.

LET'S GO TO APPLE.

TO PRODUCE THE DOCUMENTS.

3

MR. SAVERI:

4

THE COURT:

5
6

9

YOUR HONOR -TONY FADELL, F-A-D-E-L-L.

HE COMMUNICATED WITH STEVE JOBS ABOUT THE POACHING, AND
YOU'RE SAYING HE DOESN'T HAVE RELEVANT DOCUMENTS.

7
8

TONY FADELL, YOU'RE GOING

MR. TUBACH:

YOUR HONOR, THE PLAINTIFFS HAD AGREED

TO TAKE HIM OFF THE LIST AND THEY TOOK HIM OFF THE LIST.
THEY DID NOT ASK FOR THE DEPOSITION UNTIL TWO DAYS AGO,

10

AND FOR THE FIRST TIME THEY SAID, "WE ADMIT WE'RE CHANGING OUR

11

MINDS AND WE'VE NOW CHANGED OUR MINDS AND WE WANT TONY FADELL

12

AFTER ALL."

13
14
15
16
17

WE HEARD ABOUT THIS FOR THE FIRST TIME TWO DAYS AGO, YOUR
HONOR.
THE COURT:

WELL, THIS IS BRIEFED IN THE CMC -- THE

JOINT CASE MANAGEMENT STATEMENT FOR THE DECEMBER CMC.
MR. TUBACH:

THAT'S WHY WE FILED AN ADDITIONAL CMC

18

STATEMENT, YOUR HONOR, PROVIDING WHAT ARE THE NOW CURRENT SETS

19

OF DISPUTES, AND WE HAD AGREED WITH THE PLAINTIFFS THAT THEY --

20

THAT THEY WOULD NOT BE DOING TONY FADELL.

21

THE COURT:

22

MR. TUBACH:

OKAY.

WELL, I --

THE PLAINTIFFS HAD AGREED WE DON'T HAVE

23

TO DO TONY FADELL, YOUR HONOR.

24

THE COURT:

25

MR. SAVERI:

THESE DOCUMENTS HAVE BEEN RESOLVED?
WE DO.

WE WANT THE DOCUMENTS.

UNITED STATES COURT REPORTERS

278

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1

MS. DERMODY:

2

MR. TUBACH:

YES.
YOUR HONOR, UNTIL TWO DAYS AGO, THE

3

ANSWER WAS NO, AND THAT ANSWER WAS NO FROM NOVEMBER 30TH UNTIL

4

TWO DAYS AGO.

5
6
7

MR. SAVERI:

YOUR HONOR, WE'D LIKE MR. FADELL'S

DOCUMENTS.
THE COURT:

I MEAN, IF HE COMMUNICATED WITH

8

STEVE JOBS ABOUT THE ANTI-POACHING WITH GOOGLE, I JUST DON'T

9

SEE HOW YOUR POSITION WAS THAT HE DOESN'T HAVE RELEVANT

10
11

INFORMATION.
MR. TUBACH:

THE PLAINTIFFS AGREED THEY DIDN'T NEED

12

TO TAKE HIS DEPOSITION OR GET DOCUMENTS, YOUR HONOR.

13

A MATTER OF OUR POSITION.

14

IT'S NOT

THEY AGREED WITH IT.

AND IF THE PLAINTIFFS WANT TO CHANGE THEIR MIND, WHAT WE

15

ASKED THEM TO DO TWO DAYS AGO, WHICH THEY SHOULD BE REQUIRED TO

16

DO, IS TO AT LEAST SEND US A LETTER.

17

YOUR HONOR.

18

LETTER AND EXPLAIN TO US WHY THEY WANT TO GO BACK ON AN

19

AGREEMENT THAT WE REACHED TWO MONTHS AGO.

20
21
22

THIS WAS IN A PHONE CALL,

THEY SHOULD AT LEAST BE REQUIRED TO SEND US A

MR. SAVERI:

AND YOUR HONOR, IF WE WERE TO SEND THE

LETTER, IT WOULD BE SOME VERSION OF WHAT YOU JUST SAID.
AND WE'RE HAPPY TO SEND MR. TUBACH A LETTER AND WE'RE

23

HAPPY IF HE WANTS TO LOOK AT IT, BUT I CAN PREDICT WITH SOME

24

CERTAINTY THAT WE'RE GOING TO ASK FOR THE DOCUMENTS.

25

MR. TUBACH:

I'D LIKE TO SEE WHAT THE LETTER SAYS,

UNITED STATES COURT REPORTERS

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1

YOUR HONOR.

2

THEY ADMITTED THEY WERE CHANGING THEIR MINDS FROM THE AGREEMENT

3

WE HAD TWO MONTHS AGO, A CALL TWO DAYS AGO.

4

SO FAR IT'S BEEN ONE PHONE CALL TWO DAYS AGO WHERE

THE COURT:

ALL RIGHT.

IF HE IS ON CORRESPONDENCE

5

WITH STEVE JOBS ABOUT WHETHER IT'S PERMISSIBLE TO POACH FROM

6

GOOGLE, WHAT WAS THE BASIS OF YOUR POSITION THAT HE HAD NO

7

RELEVANT DOCUMENTS?

8
9
10

MR. TUBACH:
DOCUMENT.

YOUR HONOR, I DON'T RECALL THE PRECISE

THAT'S WHY -- WE HAVEN'T THOUGHT ABOUT THIS FOR TWO

MONTHS BECAUSE THE PLAINTIFFS AGREED --

11

THE COURT:

WELL, THIS IS A DECEMBER 5TH DOCUMENT

12

FOR A DECEMBER 12TH CASE MANAGEMENT CONFERENCE, AND I'M SORRY I

13

WAS IN A PATENT TRIAL AT THAT TIME AND I COULDN'T HAVE THE CMC

14

AND I APOLOGIZE THAT I CONTINUED IT TO TODAY.

15

MR. TUBACH:

16

THE COURT:

THAT'S NOT THE COURT'S FAULT.
BECAUSE THIS IS NOW JUST -- YOU KNOW,

17

I'M JUST CONCERNED THAT WE'RE RUNNING UP AGAINST THIS DEADLINE

18

OF THE END OF MARCH, AND SO I CAN'T HAVE THESE DISPUTES

19

CONTINUING TO JUST DRAG ON.

20

ON THIS.

21

MR. TUBACH:

I MEAN, WE NEED TO COME TO CLOSURE

WE CAN COME TO CLOSURE WITH THE

22

PLAINTIFFS ON THIS, YOUR HONOR, AND IF WE CAN-NOT, WE WILL COME

23

BACK TO THE COURT EXPEDITIOUSLY.

24

BUT IT IS SIMPLY NOT FAIR FOR THEM TO CALL US TWO DAYS AGO

25

AND SAY, "YES, WE CHANGED OUR MIND," AND HAVE THE COURT RULE ON

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119

1

IT TODAY.

IT'S JUST NOT FAIR.

2

MS. DERMODY:

3

MR. TUBACH:

4
5

BUT NOW THAT WE'RE ALL HERE -WE WILL ACT EXPEDITIOUSLY TO RESPOND TO

THE PLAINTIFFS' REQUEST.

WE WILL RESPOND IMMEDIATELY.

BUT WE HAVE THE RIGHT TO HEAR WHAT THEY HAVE TO SAY, TO

6

LOOK BACK INTO THE ISSUE, AND TO DECIDE WHETHER OR NOT THIS IS

7

SOMETHING THAT WE WANT TO AGREE TO OR NOT.

8
9

THE COURT:

ALL RIGHT.

THIS IS WHAT IT SAYS.

IS DEFENDANT'S STATEMENT ON ECF NUMBER NUMBER 245.

THIS

"WITH

10

RESPECT TO THE SIXTH AND FINAL PROPOSED CUSTODIAN, TONY FADELL,

11

PLAINTIFFS HAVE IDENTIFIED NO SPECIFIC REASON FOR NEEDING HIS

12

DOCUMENTS, APART FROM IDENTIFYING A SINGLE DOCUMENT IN WHICH HE

13

INQUIRED ABOUT APPLE'S 'POACHING' PRACTICES, AND APPLE HAS

14

EXPLAINED THAT IT DOES NOT BELIEVE ADDING HIM AS A CUSTODIAN IS

15

WARRANTED."

16
17

I JUST -MR. TUBACH:

YOUR HONOR, I NEED TO GO BACK AND LOOK

18

AT THAT DOCUMENT.

IF IT'S A SINGLE DOCUMENT, IT PROBABLY IS

19

NOT WORTH HAVING THE ENTIRE PRODUCTION --

20

THE COURT:

IT'S A SINGLE DOCUMENT BECAUSE YOU

21

HAVEN'T PRODUCED HIS DOCUMENTS.

22

CUSTODIAN, SO YOU HAVEN'T PRODUCED HIS DOCUMENTS.

23

IS REALLY CIRCULAR.

24

THE DOCUMENTS UNTIL THE PLAINTIFFS CAN POINT TO OUR DOCUMENT

25

THAT SHOWS THAT THIS IS A RELEVANT CUSTODIAN."

YOU DON'T CONCEDE HE'S A
I MEAN, THIS

YOU'RE SAYING, "WE'RE NOT GOING TO PRODUCE

UNITED STATES COURT REPORTERS

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120

1

MR. TUBACH:

2

THE COURT:

3

MR. TUBACH:

4

WE PRODUCED DOCUMENTS -THAT IS A RIDICULOUS BURDEN.
THAT'S NOT -- I DON'T BELIEVE IT'S

RIDICULOUS FOR THIS REASON, YOUR HONOR.

5

THE COURT:

6

OKAY.

MR. TUBACH:

WE PRODUCED DOCUMENTS FROM LOTS OF

7

OTHER CUSTODIANS, ALL OF WHOM HAVE BEEN INVOLVED IN ONE WAY OR

8

THE OTHER IN COMPENSATION, IN THE COLLABORATIVE VENTURES, OR IN

9

THE AGREEMENTS, AND THAT'S WHAT WE'VE PRODUCED.

10

AND IF THEY CAN POINT TO ONE E-MAIL, WHICH WE NEED TO GO

11

BACK AND LOOK AT -- IT DEPENDS ON WHAT THE E-MAIL SAYS, YOUR

12

HONOR.

13
14
15

THE COURT:

IT'S A HIGHLY RELEVANT E-MAIL.

IT'S AN

E-MAIL TO STEVE JOBS ABOUT POACHING.
SO I DON'T GET IT.

MR. RILEY MADE THE SAME ARGUMENT,

16

LIKE, "WELL, IF YOU CAN'T POINT TO OUR DOCUMENTS, THEN WE'RE

17

NOT GOING TO PRODUCE THOSE DOCUMENTS."

18

I MEAN, THAT JUST MAKES NO SENSE.

19
20
21

AS A CUSTODIAN OF RECORD.

YOU HAVEN'T TREATED HIM

YOU HAVEN'T COLLECTED HIS DOCUMENTS.

YOU'RE SAYING YOU HAVE TO GET HIM ON EVERYONE ELSE'S
DOCUMENTS TO PROVE THAT HE'S RELEVANT.

22

WELL, THEY HAVE ACTUALLY FOUND HIM ON A VERY HIGHLY

23

RELEVANT DOCUMENT, AND NOW YOU'RE NOT WILLING TO PRODUCE HIS

24

DOCUMENTS?

25

KNOW THAT EVEN IF YOU CAPTURE ANOTHER PEOPLE'S E-MAILS, THEY

IT JUST MAKES -- IT MAKES NO SENSE BECAUSE WE ALL

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282

121

1

WON'T CAPTURE EVERYTHING THAT YOU HAVE SENT, THAT YOU HAVE

2

RECEIVED.

3

I MEAN, MAYBE HE'S A CC ON SOMEBODY ELSE'S E-MAIL.
MR. TUBACH:

IT MADE ENOUGH SENSE, YOUR HONOR, THAT

4

THE PLAINTIFFS AGREED TO IT, AND ALL I'M ASKING IS THAT THEY

5

SEND US A LETTER AND GIVE US A CHANCE TO LOOK AT THE E-MAIL

6

AGAIN.

7

BEFORE A CLASS CERTIFICATION HEARING.

8

SHOULD HAVE THIS RESOLVED HERE TODAY.

9

WE HEARD ABOUT THIS LITERALLY TWO DAYS AGO, TWO DAYS

MR. SAVERI:

I DON'T BELIEVE WE

YOUR HONOR, I AM HAPPY TO SEND

10

MR. TUBACH A LETTER, BUT IT'S GOING TO COME AS NO SURPRISE

11

BECAUSE IT'S GOING TO REPEAT BASICALLY WHAT YOUR HONOR JUST

12

SAID TO HIM.

13

BUT IF -- I'M WILLING TO DO THAT.

14

MR. TUBACH:

AND WE'LL TAKE AN IMMEDIATE AND CLOSE

15

LOOK AT WHAT THEY SAY AND RESPOND RIGHT AWAY.

16

TO SLOW DOWN --

17

THE COURT:

WHICH IS TO DO WHAT?

WE'RE NOT TRYING

YOU'VE ONLY

18

POINTED TO ONE E-MAIL THAT MR. TUBACH HAS SENT.

19

ENOUGH.

20

MR. TUBACH:

21

THE COURT:

THAT'S NOT

I'M MR. TUBACH.
SHOW ME, WHAT, 10, 25, 30, 75, A

22

THOUSAND TO SHOW THAT HE'S RELEVANT?

23

STANDARD HERE?

24

SAYING, "CAN WE POACH FROM GOOGLE?"

25

I MEAN, WHAT'S THE

THEY HAVE A DOCUMENT FROM HIM TO STEVE JOBS

MR. TUBACH:

IF THAT'S ALL IT IS --

UNITED STATES COURT REPORTERS

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1

THE COURT:

2

MR. TUBACH:

3

THE COURT:

4

ADMISSIBLE EVIDENCE?

5
6
7
8
9

THAT'S NOT RELEVANT?
IF THAT -THAT'S NOT GOING TO LEAD TO RELEVANT,

MR. TUBACH:

IF THAT'S ALL IT IS AND THERE'S NO

RESPONSE, PROBABLY NOT.

PROBABLY NOT.

IF THERE'S MORE, WE'LL LOOK INTO IT, AND WE'LL LOOK INTO
IT IMMEDIATELY.

ALL I'M ASKING FOR IS AN OPPORTUNITY.

THE COURT:

OKAY.

BUT YOU'RE SAYING, "WE'RE NOT

10

WILLING TO PRODUCE HIS DOCUMENTS UNTIL THEY SHOW US ENOUGH OF

11

HIS DOCUMENTS TO MAKE US HAVE TO DO A COLLECTION."

12

MR. TUBACH:

13

THE COURT:

14

THAT'S NOT WHAT I'M SAYING, YOUR HONOR.
DOES THAT MAKE SENSE?

THAT'S WHAT

YOU'RE SAYING.

15

MR. TUBACH:

16

THE COURT:

NO.
YOU'RE SAYING, "THEY NEED TO POINT TO

17

ENOUGH OF HIS DOCUMENTS FOR US TO CONCEDE THAT HIS DOCUMENTS

18

ARE RELEVANT."

19

TO A SINGLE DOCUMENT OF HIS TO SHOW THAT HE'S RELEVANT AND,

20

THEREFORE, WE SHOULD DO A COLLECTION OF THIS PERSON'S

21

DOCUMENTS."

22
23

THAT'S YOUR ARGUMENT.

"THEY'RE ONLY POINTING

THAT MAKES NO SENSE TO ME.
MR. TUBACH:

I'M NOT SAYING THEY HAVE TO POINT TO

24

MORE THAN ONE DOCUMENT FOR US TO CHANGE OUR MIND.

25

TAKE A LOOK AT THE DOCUMENT.

UNITED STATES COURT REPORTERS

I WANT TO

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1

THE COURT:

2

MR. TUBACH:

3
4
5
6

OKAY.
OBVIOUSLY THE COURT MAY NOT BE

PERSUADED.
THE PLAINTIFFS WERE PERSUADED BY THE ARGUMENT AND DROPPED
HIM TWO MONTHS AGO.
SO ALL I WANT TO DO IS TAKE -- WE MAY CHANGE OUR MINDS.

7

WE'VE NOW PRODUCED MORE DOCUMENTS.

8

WE'LL TALK TO PEOPLE.

9

WE'LL LOOK THROUGH THOSE.

WE MAY CHANGE OUR MINDS.

I'M NOT PUTTING A NUMERIC NUMBER ON HOW MANY E-MAILS HAVE

10

TO BE FROM A PARTICULAR WITNESS BEFORE HE'S A CUSTODIAN.

11

I'M ASKING FOR IS AN OPPORTUNITY TO TAKE A LOOK AT IT, AND

12

WE'LL RESPOND IMMEDIATELY.

13

ALL

AND I APPRECIATE MR. SAVERI'S OFFER TO WRITE A LETTER, AND

14

WE'LL RESPOND TO IT IMMEDIATELY.

15

THE COURT:

16

ALL RIGHT.

TOMORROW, JANUARY 18TH.

17

MR. TUBACH:

18

THE COURT:

19

MR. TUBACH:

20

THE COURT:

21

THAT LETTER IS GOING OUT

ALL RIGHT.

THANK YOU.
WHEN IS YOUR RESPONSE COMING IN?
WE CAN RESPOND BY TUESDAY, THE 22ND.
ALL RIGHT.

JANUARY 22ND.

AND I WANT A STATUS REPORT, YOU ALL FILE A

22

STATUS REPORT BY THURSDAY, THE 24TH, AS TO WHAT'S GOING ON WITH

23

MR. FADELL'S DOCUMENTS.

24

THINK THEY SHOULD BE PRODUCED, SO I HOPE THAT YOU REACH A

25

SUITABLE AGREEMENT.

I FIND THAT THEY'RE RELEVANT AND I

UNITED STATES COURT REPORTERS

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1
2
3
4

MR. SAVERI:

I DON'T WANT TO PROMISE, BUT I'LL TRY

TO GET THE LETTER TONIGHT.
THE COURT:

I'LL GO BACK AND WRITE A LETTER.

WHAT ELSE?

I'M TRYING TO BE VERY CLEAR,

EVERY TIME WE HAVE A CMC, PLEASE, LET'S NOT HAVE THESE ISSUES.

5

MR. SAVERI:

6

THE COURT:

YOUR HONOR -I HAMMERED THE PLAINTIFFS WHEN THEY

7

WEREN'T BEING TIMELY WITH THEIR PRODUCTION.

8

IT'S ALL EQUAL OPPORTUNITY HAMMERING.

9

GET THIS CASE RESOLVED.

YOU KNOW, IF --

I MEAN, WE NEED TO JUST

WE'RE COMING UP AGAINST THE FACT

10

DISCOVERY CUT OFF DATE AND WE JUST NEED THESE ISSUES TO MOVE

11

FORWARD AND THIS CASE TO PROGRESS TO THE MERITS.

12
13
14
15

SO ANYWAY, IS THERE ANY OTHER DISPUTE AS TO APPLE
CUSTODIANS OF RECORD?
MS. DERMODY:

NO, YOUR HONOR, NOT THAT I'M AWARE OF.

BUT I WANTED JUST TO GO BACK TO -- ON GOOGLE, WE TALKED

16

ABOUT THE DOCUMENTS, AND I THINK THAT WHAT THAT ALSO HIGHLIGHTS

17

IS THAT THERE IS LIKELY GOING TO NEED TO BE A DISCUSSION ABOUT

18

DEPOSITION DATES FOR CUSTODIANS, AND WE WANTED TO GET AN

19

AGREEMENT WITH GOOGLE ON A DATE CERTAIN WHEN THEY WILL GIVE US

20

THOSE DATES.

21

PROBABLY FOR LARRY PAGE AND MR. BRIN, WE WILL HAVE TO DO

22

DEPOSITIONS IN MARCH GIVEN THE PRODUCTION TIMEFRAME WE'RE

23

TALKING ABOUT.

24

BUT WE WANT TO MAKE SURE WE START TALKING ABOUT SCHEDULES

25

BECAUSE IT'S BEEN VERY HARD TO SCHEDULE THE SENIOR EXECUTIVES.

UNITED STATES COURT REPORTERS

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1

THE COURT:

NOW, THAT'S ONLY IF YOU FIND RELEVANT

2

DOCUMENTS WITHIN THEIR PRODUCTION.

3

MS. DERMODY:

4

THE COURT:

YES.

I CERTAINLY DON'T WANT HARASSMENT

5

DEPOSITIONS JUST TO TIE UP A TOP EXECUTIVE'S TIME AND BURDEN

6

THEM.

7

MS. DERMODY:

8

TO MAKE SURE WE GET --

9

MR. RUBIN:

ABSOLUTELY, YOUR HONOR.

WE JUST WANT

YOUR HONOR, WE'RE CERTAINLY HAPPY TO

10

TALK TO THEM AS SOON AS -- AFTER THEY GET THE DOCUMENTS.

11

THINK WE'RE ALWAYS WILLING TO TAKE ANYBODY'S CALL FROM

12

LIEFF CABRASER.

13

WE'RE ALWAYS AVAILABLE.

I

WE WILL TALK TO THEM.

AS SOON AS THEY LOOK AT DOCUMENTS AND THEY WANT TO TALK

14

ABOUT THE NEED FOR A DEPOSITION AND WHY, WE'LL RESPOND

15

PROMPTLY.

16

BUT I AGREE WITH YOUR HONOR THAT WE'RE NOT QUITE THERE

17

YET.

18

WE'RE NOT QUITE THERE YET TO TALK ABOUT THOSE DATES.

19

I KNOW THAT MS. DERMODY IS LAYING DOWN A MARKER, BUT

THE COURT:

ALL RIGHT.

20

REASONABLE ABOUT THIS.

21

MS. DERMODY:

22

THE COURT:

WELL, PLEASE, EVERYONE BE

23
24
25

THANK YOU, YOUR HONOR.

ALL RIGHT.

SO LET'S FIGURE OUT WHEN WE

SHOULD GET TOGETHER AGAIN FOR A CASE MANAGEMENT CONFERENCE.
I THINK WE SHOULD PROBABLY DO ONE IN MARCH OR EARLY APRIL,
BUT I WOULD LIKE TO HEAR FROM THE PARTIES OF WHEN MAKES SENSE.

UNITED STATES COURT REPORTERS

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1
2

MR. MITTELSTAEDT:

ANY DATE IS FINE WITH US, YOUR

HONOR.

3

MS. DERMODY:

4

OFF MIGHT MAKE SENSE, YOUR HONOR.

5

PROBLEM MEETING IT, BUT IT MIGHT BE GOOD TO CHECK IN WITH THE

6

COURT.

7

I THINK MARCH BEFORE THE DISCOVERY CUT

MR. MITTELSTAEDT:

WE EXPECT THERE WILL BE NO

YOUR HONOR, WOULD IT BE OKAY FOR

8

THE PARTIES TO MEET AND CONFER AND AGREE ON A COUPLE OF DATES

9

IN MARCH AND CHECK WITH YOUR STAFF TO SEE IF THAT'S ACCEPTABLE

10

WITH THE COURT?

11
12
13

THE COURT:

THAT'S FINE.

BUT CAN WE NOT DO THAT

TODAY?
MR. SAVERI:

I'M HAPPY TO TALK TO MR. MITTELSTAEDT,

14

BUT IT SEEMS TO ME THAT WE'RE MORE THAN LIKELY TO HAVE DATES

15

THAT WE CAN AGREE ON AND KEEP IF WE DO IT RIGHT NOW.

16

MR. MITTELSTAEDT:

17

TIME, BUT EITHER WAY IS FINE WITH US.

18
19
20
21
22
23
24
25

THE COURT:

OKAY.

I JUST THOUGHT IT WOULD SAVE SOME

I JUST DON'T WANT TO HAVE A LOT

OF LOOSE ENDS.
SO WHAT DATES DO WE HAVE IN MARCH?
THE CLERK:

JUST FROM OUR CALENDAR, IT LOOKS AS

THOUGH THE 20TH WOULD BE THE BEST.
THE COURT:

OKAY.

WHAT ABOUT MARCH 20TH?

I GUESS

IT'LL BE WEDNESDAY AT 2:00 O'CLOCK.
THE CLERK:

OR THE 6TH ALSO WOULD WORK.

UNITED STATES COURT REPORTERS

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1

THE COURT:

LET'S DO IT THE 20TH.

2

MS. DERMODY:

IS IT POSSIBLE, YOUR HONOR, TO DO IT

3

THE WEEK BEFORE THAT?

4

THE COURT:

I THINK THE 13TH MIGHT BE LONG.

5

THE CLERK:

THE 13TH WE HAVE SIX.

6

THE 6TH WE ONLY HAVE THREE.

7

MS. DERMODY:

8

THE COURT:

9
10
11

IS THE 6TH IS NOT --

BUT IS ONE OF THEM THE PRETRIAL

CONFERENCE -THE CLERK:

NO.

THREE J & J CASES.

HOW THAT HAPPENED.

12

MS. DERMODY:

13

THE COURT:

14

I DON'T HAVE A TRIAL SET THEN.

15

THE CLERK:

16
17

I DON'T KNOW

DO YOU DO MONDAYS, YOUR HONOR?

I WOULD BE HAPPY TO SPECIALLY SET IT IF
I JUST DON'T KNOW.

LET ME SEE.

ALL THE MONDAYS IN MARCH WE CURRENTLY

HAVE TRIALS SET.
THE COURT:

YEAH.

OKAY.

I'D BE RELUCTANT TO

18

SPECIALLY SET IT BECAUSE I DO HAVE A CIVIL RIGHTS CASE THAT MAY

19

GO ON MARCH 4, SO -- YOU KNOW, WE COULD ADD IT TO THE 13TH.

20

THE CLERK:

WE HAVE NOTHING ON THE 22ND.

21

THE COURT:

WE DON'T HAVE ANYTHING ON THE 22ND?

22

THE CLERK:

THAT'S BETWEEN SMITH AND FERRETTI.

23

MS. DERMODY:

24
25

THE 13TH WOULD BE BETTER FOR ME, BUT I

CAN MAKE THE 22ND.
MR. MITTELSTAEDT:

I'M TOLD THE 22ND ISN'T GOOD FOR

UNITED STATES COURT REPORTERS

289

128

1

US, EITHER.

2

THE COURT:

3

MR. MITTELSTAEDT:

4

THE COURT:

5

MR. MITTELSTAEDT:

6

THE COURT:
THAT RIGHT?

9
10
11

IS NOT.

IS THE 13TH GOOD FOR THE DEFENDANTS?
I SUSPECT WE CAN GET A

REPRESENTATIVE FROM EACH COMPANY HERE ON THE 13TH.

7
8

IS NOT GOOD?

OTHERWISE YOU CAN'T DO THE 20TH?

IS

SOMEBODY CAN'T DO THE 20TH?

MS. DERMODY:

YES, THAT'S ME, YOUR HONOR.

I'M

SORRY.
THE COURT:

ALL RIGHT.

12

YEAH, ON THE 13TH.

13

LET'S DO IT ON THE 13TH.

13TH OF 2013 AT 2:00 O'CLOCK.

14

SO THE NEXT CMC IS GOING TO BE MARCH THE

LET ME ASK A COUPLE OF QUESTIONS ON THE MOTION TO STRIKE

15

AND I'LL TRY TO WRAP THIS UP.

16

TAKING A LONG TIME.

17

I APOLOGIZE THE HEARING IS

DID MR. MURPHY OR ANY OF HIS TEAM RELY ON THE INTERVIEW

18

NOTES WHEN FORMING THE OPINIONS ABOUT WHICH DR. MURPHY WROTE,

19

TESTIFIED, FORMED?

20
21

MR. HINMAN:

YOUR HONOR, FRANK HINMAN.

THE ANSWER TO THAT IS NO.

22

THE COURT:

23

MR. HINMAN:

24

THE COURT:

25

MR. HINMAN:

NOT AT ALL?
CORRECT, YOUR HONOR.
ALL RIGHT.
MR. MURPHY DIDN'T TAKE ANY NOTES, SO HE

UNITED STATES COURT REPORTERS

290

129

1

DIDN'T HAVE ANY OF HIS OWN TO RELY ON, NOR DID HE RELY ON ANY

2

NOTES THAT ANYBODY ELSE MAY HAVE TAKEN.

3

MR. GLACKIN:

4

THE COURT:

SO THE ANSWER IS NO.

BUT THE --

BUT WHAT ABOUT -- WHO WROTE HIS REPORT?

5

I ASSUME SOME MEMBERS OF HIS TEAM HELPED HIM IN DRAFTING HIS

6

REPORT AND FORMING HIS OPINIONS.

THAT'S USUALLY WHAT HAPPENS.

7

DID THAT NOT HAPPEN IN THIS CASE?

HE WROTE IT HIMSELF, ALL 70

8

PAGES?

9
10

MR. HINMAN:
HAPPEN.

NO, YOUR HONOR.

IT ABSOLUTELY DID

THERE WAS A DRAFTING PROCESS, AS THERE OFTEN IS.

11

THE COURT:

12

MR. HINMAN:

OKAY.
BUT THE FINAL REPORT, THE NOTES WERE

13

NOT RELIED UPON IN FORMING THE OPINIONS THAT ARE EXPRESSED IN

14

THE FINAL REPORT.

15
16
17

AND SO, YOU KNOW, NOT ONLY -- I MEAN, PUTTING ASIDE THE
USUAL -THE COURT:

OKAY.

I'M SORRY TO INTERRUPT YOU.

LET

18

ME ASK, DID THE PEOPLE WHO WORKED ON THE TEAM THAT DRAFTED THE

19

REPORT, DID THEY DRAFT INTERVIEW NOTES?

20

MR. HINMAN:

YES.

21

THE COURT:

OKAY.

22

MR. HINMAN:

THEY DID.

23

THE COURT:

ALL RIGHT.

24

MR. HINMAN:

25

BUT THEY WERE NOT -- AS I SAY, THEY

WERE NOT USED BY HIM OR ANYBODY ELSE IN FORMING THE OPINIONS

UNITED STATES COURT REPORTERS

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130

1

THAT ARE CONTAINED IN THE REPORT.

2

AND WE HAVE A STIPULATION IN THIS CASE, YOUR HONOR,

3

THAT'S, I THINK, VERY CLEAR THAT WAS, YOU KNOW -- I MEAN, IT'S

4

NOT UNCOMMON IN THESE ANTITRUST CASES WITH LOTS OF EXPERTS ON

5

BOTH SIDES AND THINGS LIKE THIS THAT WE'RE NOT GOING TO ALLOW

6

DISCOVERY INTO, YOU KNOW, THIS SORT OF PRELIMINARY WORK PRODUCT

7

AND NOTES THAT PEOPLE MAY HAVE TAKEN, ET CETERA.

8
9

AND SO EVEN PUTTING ASIDE -- AND I'M NOT PUTTING IT ASIDE
EXCEPT FOR THE MOVEMENT -- ISSUES OF WORK PRODUCT, THE

10

STIPULATION GOES BEYOND THAT.

11

SUPERSEDES ANY RULE OF CIVIL PROCEDURE THAT MIGHT APPLY.

12

IT EXPLICITLY SAYS THAT IT

I DON'T THINK THAT THESE NOTES ARE PRODUCEABLE EVEN UNDER

13

THOSE RULES, BUT THE STIPULATION SAYS IT'S BROADER AND IT IS

14

INTENDED TO AND DOES CARVE OUT ALL OF THIS KIND OF PRELIMINARY

15

WORK PRODUCT.

16

AND IF THERE'S -- THERE REALLY, I THINK, SHOULDN'T BE ANY

17

DISPUTE ABOUT THAT BECAUSE JUST, FOR EXAMPLE, IN THE INSTANCE

18

OF PROFESSOR LEAMER'S DEPOSITION -- AND IT WASN'T THE ONLY

19

INSTANCE -- THAT MR. MITTELSTAEDT REFERRED TO EARLIER,

20

DR. LEAMER WAS INSTRUCTED NOT TO TESTIFY ABOUT, NOT TO DISCLOSE

21

PRELIMINARY WORK PRODUCT THAT HE HAD DONE THAT, INDEED, HE DID

22

RELY ON, THAT HE DID RELY ON IN ORDER TO -- THIS IS THE

23

SENSITIVITY ANALYSIS.

24
25

HE DID IT, HE RELIED UPON IT TO DECIDE AND CONCLUDE THAT
THE AGGREGATED, I'LL CALL IT, REGRESSION MODEL THAT HE OFFERED

UNITED STATES COURT REPORTERS

292

131

1

WAS SUFFICIENT AND THAT THE DISAGGREGATED SENSITIVITY TEST THAT

2

HE RAN DIDN'T TELL HIM ANYTHING TO THE CONTRARY AS MR. GLACKIN,

3

I THINK, SAID.

4

SO, I MEAN, THIS IS JUST -- THIS IS JUST NOT THE SORT OF

5

THING THAT I THINK ANYBODY CONTEMPLATED WOULD BE PRODUCED, AND

6

I THINK THAT BOTH SIDES ARE READING IT IN JUST THAT WAY.

7

MR. GLACKIN:

WELL, SO FIRST OF ALL, I STILL DON'T

8

THINK YOU HAVE A STRAIGHT ANSWER TO YOUR QUESTION, WHICH IS,

9

DID ANYBODY WHO HELPED WRITE THIS REPORT LOOK AT THE NOTES WHEN

10
11

THEY WERE DOING IT?
WHAT MR. HINMAN SAID WAS THE NOTES WERE NOT RELIED ON IN

12

FORMING THE OPINIONS, AND I DON'T KNOW WHAT THAT MEANS.

13

THINK YOU ASKED A STRAIGHTFORWARD QUESTION, AND I DIDN'T HEAR

14

AN ANSWER.

15

I

SECOND, I THINK TRYING TO BRING UP WHAT WE DID IS

16

COMPLETELY INAPPROPRIATE WITH DR. LEAMER.

17

WHAT WE DID WITH DR. LEAMER FOR MONTHS.

18

WRONG ABOUT WHAT WE DID, THEY'VE HAD EVERY OPPORTUNITY TO RAISE

19

THAT AND ASK FOR THE STUFF AND MOVE ON IT IF THEY DISAGREED

20

WITH US.

21

SO WE'VE ABIDED BY THE STIPULATION.

THEY'VE KNOWN ABOUT

IF THERE WAS ANYTHING

THE STIPULATION SAYS

22

PRELIMINARY DATA ANALYSIS IS NOT PRODUCEABLE.

23

WE DIDN'T

PRODUCE PRELIMINARY DATA ANALYSIS.

24

BUT EVEN BEYOND THE STIPULATION, DR. MURPHY HAS AN

25

OBLIGATION, OR I SHOULD SAY THE DEFENDANTS HAVE AN OBLIGATION,

UNITED STATES COURT REPORTERS

293

132

1
2

TO TELL US THE FACTS ON WHICH HE'S RELYING TO FORM HIS OPINION.
THEY CAN DO THAT A LOT OF DIFFERENT WAYS.

IF YOU -- IN

3

THE CASE OF THESE INTERVIEWS, ONE WAY THEY COULD DO IT WOULD

4

HAVE BEEN TO RECORD THE INTERVIEWS AND GIVE US THE RECORDINGS.

5

ANOTHER WAY THEY COULD DO IT --

6

THE COURT:

7

MR. GLACKIN:

8
9

THAT'S NOT GOING TO HAPPEN.
WELL, THEY WEREN'T RECORDED, SO IT'S

NOT HAPPENING.
ANOTHER WAY THEY COULD DO IT IS THEY COULD WRITE SUMMARIES

10

UP AT THE TIME AND GIVE US THE SUMMARIES THAT JUST SAID

11

"MR. SO-AND-SO SAID THIS, THAT, AND THE OTHER THING."

12

ANOTHER WAY THEY COULD DO IT IS THEY COULD PRODUCE

13

DR. MURPHY AND HE COULD TESTIFY FROM HIS MEMORY ABOUT WHAT

14

HAPPENED AT THE INTERVIEWS.

15

BUT THEY HAVE AN AFFIRMATIVE DUTY, UNDER RULE 26, TO TELL

16

US THIS INFORMATION, AND WHEN I ASKED DR. MURPHY ABOUT THIS AT

17

HIS DEPOSITION -- I'M GOING TOO FAST, I APOLOGIZE -- OVER AND

18

OVER AND OVER AGAIN HE SAID HE COULDN'T REMEMBER WHAT HAD BEEN

19

SAID OR WHO HAD TOLD IT TO HIM.

20

IMPRESSION FROM THESE INTERVIEWS HE'D DONE THAT THESE FOLLOWING

21

THINGS WERE TRUE ABOUT ALL THESE COMPANIES.

22

HE JUST HAD THIS GENERAL

AND HE SPECIFICALLY TESTIFIED, I BELIEVE, THAT

23

MR. VIJUNGCO HAD TOLD HIM THINGS IN HIS INTERVIEW THAT WERE

24

DIFFERENT THAN WHAT MR. VIJUNGCO HAD TOLD DR. MURPHY -- OR THAT

25

WERE DIFFERENT THAN WHAT MR. VIJUNGCO SAID IN HIS DECLARATION.

UNITED STATES COURT REPORTERS

294

133

1

AND SO THE OBLIGATION, IF THEY WANT TO HAVE AN EXPERT, IS

2

ON THEM TO PRODUCE THE MATERIAL ON WHICH HE'S RELIED, AND THIS

3

IDEA THAT THEY'RE GOING TO TAKE SECRET INTERVIEWS AND HAVE THEM

4

BE A BASIS FOR THE EXPERT'S OPINION IN SUCH A WAY THAT THAT

5

OPINION CANNOT ADEQUATELY BE TESTED, I REALLY HAVE A PROBLEM

6

WITH THAT.

7

THE COURT:

SO WHAT IS YOUR BEST AUTHORITY FOR THE

8

PROPOSITION THAT MS. DERMODY MADE THAT IF A PARTY LISTS A

9

WITNESS ON THEIR RULE 26 DISCLOSURES, THAT AUTOMATICALLY MAKES

10

THEM A CUSTODIAN FOR WHOM THEY HAVE TO COLLECT DOCUMENTS AND

11

PRODUCE DOCUMENTS?

12
13

MR. GLACKIN:
POINT?

14

THE COURT:

15

MR. GLACKIN:

16

WHAT'S OUR BEST AUTHORITY FOR THAT

YEAH.
I'M NOT AWARE OF ANY CASE AUTHORITY

FOR THAT POINT OFFHAND, YOUR HONOR.

17

I MEAN, MY AUTHORITY FOR THAT POINT, I GUESS, WOULD BE

18

RULE 26 WHICH SAYS THAT YOU'RE REQUIRED TO IDENTIFY PEOPLE WITH

19

RELEVANT INFORMATION.

20

AND IF YOU'VE GONE SO FAR AS TO IDENTIFY A PERSON WITH

21

RELEVANT INFORMATION, IT SEEMS TO ME, PRACTICALLY SPEAKING,

22

THAT THEIR DOCUMENTS -- TO IMPLY THEIR DOCUMENTS ARE RELEVANT

23

IN THIS DAY AND AGE WHEN VIRTUALLY -- WHEN SO MUCH

24

COMMUNICATION NOW OCCURS ELECTRONICALLY, I WOULD SAY.

25

MR. MITTELSTAEDT:

BUT, YOUR HONOR, ON THAT POINT,

UNITED STATES COURT REPORTERS

295

134

1

THEY HAVE KNOWN WHO'S ON THE INITIAL DISCLOSURES AND THEY HAVE

2

KNOWN WHO THE CUSTODIANS ARE.

3

WE'VE TALKED ABOUT THAT.

4

THAT -- WE'VE NEGOTIATED THAT.

SO IF THEIR POSITION WAS THAT IF YOU PUT SOMEBODY ON AN

5

INITIAL DISCLOSURE, AUTOMATICALLY THEY'RE A CUSTODIAN, THEY'VE

6

BEEN SITTING IN THE WEEDS ON THAT.

7

THAT'S AN AMBUSH.

SO THAT ISN'T -- AND I -- IF THEY'RE SAYING THAT, THAT

8

CAN'T BE RIGHT.

9

WHEN WE PUT PEOPLE ON THE INITIAL DISCLOSURES AND THEY KNEW

10
11

THE TIME TO TALK TO US ABOUT THAT WAS LONG AGO

THEY WEREN'T CUSTODIANS.
SO THAT -- BUT -- YOUR HONOR, I KNOW THE HOUR IS LATE, BUT

12

GIVEN THE IMPORTANCE OF THE CLASS MOTION, COULD I BE HEARD FOR

13

TWO MINUTES?

14

THE COURT:

15

MR. MITTELSTAEDT:

16

MR. GLACKIN:

17
18

JUST TWO MINUTES.
I WILL TALK FAST.

CAN I GET TWO MINUTES, TOO, AFTER HE'S

DONE?
MR. MITTELSTAEDT:

TO HELP YOUR HONOR WALK THROUGH

19

THE BOOKLET THAT I GAVE YOU, I WOULD SUGGEST LOOKING AT PAGE

20

25, WHICH HAS THE ANSWER TO YOUR HONOR'S QUESTION TO THE OTHER

21

SIDE AS TO WHETHER FIGURES 11 TO 14 ARE CORRELATED OVER TIME.

22

THAT'S A DEPOSITION ADMISSION THAT THEY ARE NOT CORRELATED.

23

PAGE 28 TO 31 SHOWS THAT THE CHARTS ARE NOT

24

REPRESENTATIVE.

YOUR HONOR ASKED THE QUESTION, ARE THE CHARTS

25

REPRESENTATIVE?

THE DEPOSITIONS AT PAGE 28 THROUGH 31 OF TAB 6

UNITED STATES COURT REPORTERS

296

135

1

GIVE MR. LEAMER'S ANSWER WHERE HE ADMITS THEY ARE NOT

2

REPRESENTATIVE.

3

PAGE 32 SHOWS THAT BECAUSE THOSE CHARTS ARE JUST AVERAGES,

4

THEY WOULD BE CONSISTENT WITH A NON-RIGID STRUCTURE, AS WELL AS

5

A RIGID STRUCTURE, AND THEREFORE, THEY DO NOT PROVE A RIGID

6

STRUCTURE, WHICH IS WHAT LEAMER SETS OUT TO DO IN HIS STEP 2.

7

HIS FIRST STEP IS TO SHOW AN AVERAGE OVERCHARGE.

8

SECOND STEP IS TO TRY AND SHOW THAT THERE WOULD HAVE BEEN A

9

SPREAD TO ALL OR NEARLY ALL OF THE EMPLOYEES.

10

THE COURT:

11

MR. MITTELSTAEDT:

HIS

UM-HUM.
AND HE TOLD US THAT FIGURES 11

12

THROUGH 14 DID NOT DO THE TRICK BECAUSE THEY DID NOT SHOW

13

CORRELATION OVER TIME.

14

17."

15

HE SAID, "THAT'S WHY I NEED 15 THROUGH

BUT WHEN WE GOT TO 15 TO 17, HE ADMITTED -- THIS IS AT

16

PAGE 32 IN THE BINDER -- THAT THEY WOULD BE CONSISTENT WITH A

17

NON-RIGID SYSTEM, MEANING THAT THEY DON'T SHOW RIGIDITY.

18

PAGE 28 IN THE BINDER, TAB 6, IS A DOCUMENT THEY OBJECT

19

TO, BUT WHAT IT SHOWS IS IF YOU TAKE THE INTEL JOB THAT THEY

20

CHERRY PICKED, FINANCIAL ANALYST 3 --

21

MR. GLACKIN:

I'M SORRY.

22

THE COURT:

23

MR. GLACKIN:

24

MR. MITTELSTAEDT:

25

THE COURT:

WHICH PAGE ARE YOU ON?

PAGE 28 OF TAB 6.
OKAY.
I'M SORRY, 37.

OKAY.

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MR. MITTELSTAEDT:

THIS IS A CHART OF THE

2

COMPENSATION GROWTH FOR NINE INTEL EMPLOYEES WHO HOLD THE SAME

3

SMALL SLIVER OF A JOB, FINANCIAL ANALYST 3.

4

GENDER, THEY'RE THE SAME AGE, AND THEY HAVE THE SAME WORK

5

EXPERIENCE.

6

MR. GLACKIN:

THEY ARE THE SAME

I JUST WANT TO -- I APOLOGIZE FOR

7

INTERRUPTING, BUT I WANT TO POINT OUT THAT THIS IS YET ANOTHER

8

REHASHING OF THE SUPPLEMENTAL DATA THAT THE DEFENDANTS HAVE

9

MOVED TO HAVE, WE SAY IMPROPERLY, CONSIDERED BY THE COURT, AND

10

I COMPLETELY -- I -- WE HAVE NOT HAD THE OPPORTUNITY TO

11

VENTILATE IT WITH OUR EXPERTS.

12
13

I HAVE NO IDEA IF IT'S ACCURATE.

TIME LAST NIGHT AT ABOUT 7:00 OR 8:00 O'CLOCK.

14
15

I SAW THIS FOR THE FIRST

MR. MITTELSTAEDT:

SO IT'S JUST --

YOUR HONOR, LET ME FINISH IF I

COULD?

16

MR. GLACKIN:

I'M SORRY.

17

MR. MITTELSTAEDT:

YOUR HONOR, TAB -- OR PAGE 33 IS

18

THE LETTER THEY SENT TO THE COURT CORRECTING A STATEMENT THEY

19

HAD MADE IN THEIR BRIEF AND THAT DR. LEAMER HAD SAID IN HIS

20

BRIEF.

21

THEIR POINT WAS THE ORIGINAL SAID THAT THERE WERE ONLY

22

SEVEN INTEL GRADE 3 EMPLOYEES WHO HELD THAT TITLE, SAME OTHER

23

CHARACTERISTICS, AND THAT THE AVERAGE -- OR THAT THE DIFFERENCE

24

BETWEEN THE HIGHEST AND THE LOWEST PAID WAS ONLY $300.

25

AND THEY CITED THAT AS AN EXAMPLE OF SOMETHING SHOWING

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THAT THERE IS NO VARIATION IN PAY AND, THEREFORE, A RAISE FOR

2

ONE WOULD BE A RAISE FOR EVERYBODY BECAUSE THEY WOULD ALL GO UP

3

TOGETHER.

4

THEY DID NOT SUBMIT THE DATA.

BUT THEY LOOKED AT THE DATA AFTER SUBMITTING THEIR REPLY

5

AND WHAT THEY REALIZED WAS, ACTUALLY, THERE ARE 28 PEOPLE THAT

6

SHARE THOSE VERY NARROW CHARACTERISTICS, AND THE RANGE OF

7

SALARY WAS NOT 300, IT WAS 5300.

8

WHAT WE DID WITH DR. MURPHY WAS TO ACTUALLY SUBMIT THE

9

DATA, AND THEN WE CHARTED THE DATA, AND WHAT THE DATA SHOWS

10

IS -- THE FIRST CHART, 36, SHOWS ALL 28 OF THEM, AND YOU'LL SEE

11

THE LINES CROSSING.

12

AND THE IMPORTANT THING TO REMEMBER IN REVIEWING THESE

13

CHARTS IS WHEN THE LINES CROSS, THAT MEANS PEOPLE ARE NOT

14

MOVING THE SAME.

15

AND THEN THEY SAID, "WELL, 28 IS TOO MANY BECAUSE SOME OF

16

THOSE PEOPLE WERE PROMOTED TO DIFFERENT JOBS," AND WE SAID,

17

"EXACTLY.

18

PEOPLE ARE TREATED DIFFERENTLY.

THAT'S OUR POINT."

BUT WE SAID WE'LL JUST TAKE THE NINE PEOPLE WHO HELD THE

19

SAME JOB, STILL THEY WERE THE SAME GENDER, STILL THE SAME AGE,

20

STILL THE SAME TENURE, FOR THREE YEARS AND LOOK AT THAT VERY

21

SMALL SLICE, AND WHAT YOU SEE IS LINES CROSSING.

22

SOME PEOPLE GO UP, SOME PEOPLE GO DOWN.

23
24
25

PEOPLE --

AND, YOUR HONOR, WE'RE TALKING ABOUT WITHIN THE SAME VERY,
VERY SMALL SLICE OF JOB CONTROLLED FOR THE OTHER FACTORS.
THAT SINGLE DOCUMENT, YOUR HONOR, SHOWS THAT THEIR IDEA OF

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A RIGID PAY STRUCTURE, WHATEVER IS IN THE DOCUMENTS, IS NOT

2

TRUE.

3
4
5

ON -- OKAY.

SO THAT'S WALKING YOUR HONOR QUICKLY THROUGH

THOSE.
ON THE DOCUMENTS, I WOULD ASK YOUR HONOR TO TAKE A LOOK AT

6

SHAVER EXHIBIT 59 AND HARVEY EXHIBIT 30.

7

DOCUMENTS YOUR HONOR ASKED ME ABOUT WHEN I SAID THAT I THINK

8

THEY SHOW THE INDIVIDUALIZED NATURE OF THE IMPACT.

9

THOSE ARE TWO OF THE

THEY ALSO, I THINK, READ CLOSELY SHOW THE OPPOSITE OF A

10

RIGID STRUCTURE.

11

DOCUMENT, THE OCTOBER 7TH ONE, IT SHOWS THAT GOOGLE WAS MAKING

12

COUNTEROFFERS TO PEOPLE AND THAT CAUSED WHAT THEY CALL

13

DISCONTINUITY AND UNFAIR BUMPS.

14

THE GOOGLE DOCUMENT, WHEN YOU READ THE FIRST

THE MERITS OF THESE AGREEMENTS ASIDE, YOUR HONOR, WE'RE

15

NOT HERE TO TALK ABOUT THOSE, WHAT WE'RE HERE TO TALK ABOUT IS,

16

WHO WAS IMPACTED?

17

AND WHAT THIS DOCUMENT SHOWS IS AS OF OCTOBER 2010,

18

GOOGLE'S POLICY WAS TO MAKE COUNTEROFFERS TO SOME PEOPLE, BUT

19

NOT TO ADJUST EVERYBODY ELSE.

20

THAT IS THE OPPOSITE OF THEIR RIGID PAY STRUCTURE.

21

IT MEANS IS THAT TO FIGURE OUT IF SOMEBODY IS IMPACTED, YOU

22

NEED TO GO PERSON BY PERSON, JUST AS IN REED, JUST AS IN

23

JOHNSON.

24
25

WHAT

THE OTHER POINT -- YOU ASKED HIM ABOUT LCD AND
JUDGE ILLSTON'S OPINION.

I ASK YOUR HONOR TO KEEP IN MIND, IN

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REVIEWING THIS, THAT THE DIFFERENCE BETWEEN LCD AND THE JOHNSON

2

AND REED LINE OF CASES -- WHICH LCD IS A TRADITIONAL ANTITRUST

3

CASE.

IT'S PRICE FIXING OF A COMMODITY.

4

AND IF THE DEFENDANTS FIXED THE PRICE OF A COMMODITY,

5

CHANCES ARE EVERYBODY -- AND IF THEY SELL THE COMMODITY FOR ONE

6

PRICE, YOU SHOW IMPACT ON ONE, YOU'VE GOT IMPACT ON EVERYBODY,

7

AND THAT'S WHY COURTS OFTEN, IN TRADITIONAL PRICE FIXING CASES

8

FOR COMMODITIES, FUNGIBLE COMMODITIES, CERTIFY A CLASS AND FIND

9

THAT IMPACT IS NOT HIGHLY INDIVIDUALIZED.

10

WE'RE NOT DEALING WITH COMMODITIES.

WE'RE DEALING WITH

11

HUMAN BEINGS, AND HUMAN BEINGS' WAGES ARE SET INDIVIDUALLY IN

12

THESE COMPANIES.

13

AND THAT'S WHY, IN REED, THE COURT SAID THE NURSES'

14

SALARIES ARE SET INDIVIDUALLY, THEY CAN'T SHOW IMPACT ACROSS

15

THE BOARD, YOU HAVE TO GO NURSE BY NURSE.

16

OUR CASE OBVIOUSLY IS A LOT BIGGER, A LOT MORE COMPLICATED

17

THAN JUST ONE JOB CATEGORY, NURSES.

18

DEFENDANTS, IT INVOLVES 7,000 DIFFERENT JOB TITLES , AND IT

19

INVOLVES INDIVIDUALIZED PAY DECISIONS MADE BY THOUSANDS OF

20

MANAGERS.

21

IT INVOLVES SEVEN

AND SO IF THE CLASSES WERE DENIED IN REED AND IN JOHNSON,

22

THEY SHOULD BE DENIED EVEN MORE SO HERE.

23

YOU KNOW, SETTING OF PRICES OF TV SCREENS WHERE WHEN YOU

24

OVERPRICE ONE, YOU OVERPRICE ALL OF THEM.

25

THIS IS NOT THE LCD,

THE OTHER POINT IS ON THIS SMALLER CLASS, THAT CLASS IS

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NOT DATA DRIVEN.

2

GOING TO LOOK AT THE COMPENSATION DATA, NOT COLD CALLING DATA,

3

THEY TOLD YOUR HONOR THEY WERE GOING TO LOOK AT COMPENSATION

4

DATA AND FIGURE OUT WHERE THE SPREAD WAS.

5

WHEN THE PLAINTIFFS TOLD YOUR HONOR THEY WERE

DR. LEAMER DID NOT COME UP WITH THE TECHNICAL CLASS.

THE

6

LAWYERS CAME UP WITH THAT.

7

RECEIVED THAT DEFINITION FROM THE LAWYERS, SO THAT'S NOT DATA

8

DRIVEN.

9

TWO LAST POINTS.

DR. LEAMER TESTIFIED THAT HE

YOUR HONOR HAS FOCUSSED, UNDERSTANDABLY,

10

ON THE SCOPE OF THE AGREEMENTS, THE UNLAWFULNESS OF THE

11

AGREEMENTS, SOME OF THE E-MAILS.

12

NONE OF THAT GOES TO THE QUESTION THAT I THINK IS CENTRAL

13

HERE, AND THAT IS, HOW DO THEY SHOW IMPACT?

14

THAT SOMEBODY'S WAGES WERE AFFECTED BY NOT GETTING A COLD CALL?

15

HOW DO THEY SHOW

AND AS WE'VE SET FORTH IN THE PAPERS, THE ONLY WAY TO DO

16

THAT IS GO PERSON BY PERSON.

17

WOULD HAVE GOT A COLD CALL.

18
19

YOU CAN'T ASSUME THAT EVERYBODY

YOU CAN'T ASSUME THAT EVERYBODY WHO GOT A COLD CALL -- WHO
WOULD HAVE GOT A COLD CALL WOULD HAVE GOT A RAISE.

20

AND YOU CAN'T ASSUME THAT IF SOMEBODY GOT A RAISE FROM A

21

COLD CALL, THAT WOULD PROPAGATE OR CASCADE OR RIPPLE, WHATEVER

22

VERB THEY WANT TO USE, TO EVERYBODY ELSE.

23

I MEAN, YOU THINK ABOUT THE ABSURDITY OF THAT.

WHY WOULD

24

A COMPANY GIVE A RAISE TO SOMEBODY IN A NEGOTIATION IF IT KNEW

25

THAT IT HAD TO TURN AROUND AND GIVE A RAISE TO EVERYBODY?

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MEAN, THAT WOULDN'T MAKE ANY SENSE.

2

AND THAT'S WHY, WHEN YOU LOOK AT THE DATA, WHEN YOU LOOK

3

AT THE DATA IN OUR FIRST FOUR OR FIVE TABS, IT SHOWS VARIATION

4

AMONG PEOPLE WHO ARE IDENTICAL IN EVERY CHARACTERISTIC.

5

BUT THERE'S VARIATION BECAUSE MANAGERS ARE MAKING THE

6

DISCRETIONARY JUDGMENT, AND IT SHOWS VARIATION FROM JOB TO JOB

7

IN A SNAPSHOT AND ACROSS TIME.

8

THAT'S WHY WHEN YOU LOOK AT THOSE CHARTS, IT SHOWS THE

9

DISTRIBUTION OF CHANGES.

10
11
12
13

JOBS MOVE DIFFERENTLY, AND

SOME JOBS, THE TOTAL COMPENSATION OR

AVERAGE COMPENSATION GOES UP, AND OTHER JOBS IT GOES DOWN.
THEY'RE NOT CORRELATED OVER TIME, WHICH IS WHAT LEAMER HAS
ADMITTED AND WHICH HE'S ADMITTED HIS CHARTS DON'T SHOW.
AND THAT'S WHAT HE'S -- HE UNDERTAKES, IN HIS SECOND STEP,

14

TO SHOW THAT THIS AVERAGE OVERCHARGE WOULD -- OR UNDERPAYMENT

15

WOULD HAVE SPREAD TO EVERYBODY AND HE SAYS HE'S GOING TO DO

16

THAT BY SHOWING HOW CLOSELY CORRELATED ALL THESE JOBS ARE.

17

THAT'S WHEN HE SAYS IT'S A RIGID PAY STRUCTURE.

18

UNDER HIS OWN METHOD, HE'S GOT TO SHOW THAT THE PAY

19

STRUCTURE IS SO RIGID THAT A RAISE FOR ONE OR A RAISE FOR

20

ALL -- EXCUSE ME, A RAISE FOR ONE OR FOR SOME IN A DEPARTMENT

21

IS GOING TO PROPAGATE TO BE A RAISE FOR EVERYBODY IN THAT

22

DEPARTMENT, AND THEN SOMEHOW EVERY OTHER DEPARTMENT, EVERY

23

OTHER JOB TITLE, NO MATTER HOW DISPARATE, AND THEN ONCE IT DOES

24

THAT, IT'S GOING TO DO THE SAME THING AT ALL THE OTHER

25

COMPANIES.

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AND IF YOU THINK -- IF YOU THINK ABOUT IT, WHATEVER THE

2

SCOPE OF THESE AGREEMENTS AFFECTING 1 PERCENT OF THE MARKET

3

THAT THESE COMPANIES OPERATED IN IN TERMS OF LABOR POOLS,

4

THERE'S NO WAY TO THINK THAT THAT WAS GOING TO HAVE A BROAD

5

IMPACT LIKE THEY'RE DESCRIBING, WHICH I THINK IS WHY, FROM THE

6

VERY START, YOUR HONOR SAID, "LOOK, IT CAN'T BE EVERYBODY.

7

LOOK AT THE COMPENSATION DATA AND SEE IF YOU CAN SEE WHERE THE

8

IMPACT WAS."

9
10
11

THAT'S WHAT THEY WERE SUPPOSED TO DO AND THAT'S WHAT THEY
DIDN'T DO.
THEY INSTEAD COME UP WITH LEAMER WITH THIS TWO-STEP

12

PROCESS.

13

WALKED UNDER THROUGH AND AS THESE CHARTS SHOW, THAT DOESN'T

14

SHOW AN AVERAGE OF ANYTHING.

15

TOGETHER, EVEN IF YOU PUT ASIDE ALL THE OTHER TECHNICAL

16

PROBLEMS WITH THE REGRESSION.

17

HIS FIRST STEP TO SHOW THE AVERAGE UNDERPAYMENT, AS I

IT SHOWS EVERYBODY TAKEN

BUT MORE THAN THAT, WHEN YOU DISAGGREGATE IT, AS HE DID

18

BUT AS HE WOULDN'T GIVE US, BUT HE SAID, "OKAY, PRESS A BUTTON

19

AND YOU CAN DO IT."

20
21
22

WHEN WE DID IT, IT SHOWS THAT THREE OR FOUR OF THE
DEFENDANTS GO THE OPPOSITE DIRECTION.
NOW, I'M NOT CITING THAT TO SAY THAT THAT PROVES THAT

23

THESE AGREEMENTS RESULTED IN OVERCOMPENSATION.

24

THAT FOR IS TO SHOW THAT WHEN YOU DO A SENSITIVITY TEST AND YOU

25

GET SOME PEOPLE GOING ONE WAY, SOME COMPANIES GOING THE OTHER

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WHAT WE CITE

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2

WAY, THAT TELLS YOU SOMETHING IS WRONG WITH THE MODEL.
BUT EVEN IF HE HAD A PERFECT SYSTEM --

3

THE COURT:

CAN YOU WRAP UP?

4

MR. MITTELSTAEDT:

5

THE COURT:

6

MR. MITTELSTAEDT:

OKAY.

JUST 15 SECONDS, PLEASE.
TWO LAST POINTS.

ONE IS IN THEIR

7

REPLY BRIEF, THEY SAY MURPHY CONCEDED THIS, MURPHY CONCEDED

8

THAT.

9

WE'VE SUBMITTED SUPPLEMENTAL EXCERPTS FROM MURPHY'S

10

TESTIMONY AND, IF ANY OF THAT MATTERS, WHEN YOU ACTUALLY READ

11

MURPHY'S TESTIMONY, HE DIDN'T COME CLOSE TO MAKING THE

12

CONCESSIONS THAT THEY SAY HE DID.

13

AND FINALLY, YOUR HONOR, YOU KNOW, THIS MATTER IS

14

COMPLICATED.

15

START AND YOUR HONOR DECLINED THAT.

16

WE HAD REQUESTED AN EVIDENTIARY HEARING AT THE

I WOULD ASK YOUR HONOR TO JUST CONSIDER, AS YOU REVIEW

17

WHAT THEY'VE DONE AND THE ANSWERS YOU'VE RECEIVED TODAY ABOUT

18

WHAT THEY DID, AND THE CONSTANT REFRAIN WAS, "WELL, YOU KNOW,

19

WE REALLY NEED DR. LEAMER TO EXPLAIN THAT," GIVEN THAT YOUR

20

HONOR WILL BE MAKING A RIGOROUS ANALYSIS OF WHAT THE EXPERTS

21

DID, AND GIVEN THAT OUR POSITION IS THIS ISN'T A BATTLE OF

22

EXPERTS, THIS IS A CASE WHERE DR. LEAMER HAS ADMITTED THAT

23

HIS -- THAT WHAT HE TRIED TO DO WITH HIS TWO STEPS DON'T WORK

24

BECAUSE THEY DON'T STAND UP TO EVEN THE TEST THAT HE PROVIDED,

25

AND BY THAT WHAT I MEAN IS HE SAID IN HIS STEP TWO HE WAS GOING

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TO SHOW THAT ANY OVERCHARGE WAS CORRELATED OVER TIME, AND HE'S

2

ADMITTED AT THE PAGES I CITED TO YOUR HONOR AT THE START HERE

3

THAT THEY DON'T DO THAT.

4

THEY DON'T DO THAT AT ALL.

AND THEN INTEL 28 AND THE APPLE 4, WHICH IS THE SAME KIND

5

OF THING, SHOWS THAT EVEN WITHIN THE SAME JOB TITLE, THE

6

EMPLOYEES' COMPENSATION GOES DIFFERENT DIRECTIONS, THE OPPOSITE

7

OF THE RIGID SYSTEM THAT THEY SAY THEY NEED TO -- THAT IS THE

8

HEART OF THEIR METHOD OF PROVING COMMON IMPACT.

9

SO WHEN YOU GET DONE WITH ALL OF IT, WHERE YOU END UP IS

10

THE ONLY WAY TO DETERMINE WHO WAS IMPACTED BY THESE

11

AGREEMENTS -- AND I ADMIT AT THE START, WE ARE NOT SAYING THAT

12

NOBODY WAS IMPACTED.

13

TALK ABOUT "WE DON'T WANT SO-AND-SO TO BE COLD CALLED BECAUSE,

14

YOU KNOW, HE MIGHT LEAVE AND MIGHT GET SOME MORE MONEY."

15

PERSON MAY HAVE A CLAIM.

16

YOU LOOK AT SOME OF THESE DOCUMENTS THAT

THAT

BUT IF HE HAS A CLAIM, THAT DOESN'T MEAN THAT ANYBODY ELSE

17

WHO WORKED WITH HIM, ANYBODY ELSE IN ANOTHER DEPARTMENT, THE

18

SOU CHEF, ANYBODY ELSE IN ANY OTHER DEPARTMENT HAS A CLAIM, AND

19

IT DOESN'T MEAN THAT ALL THE OTHER COMPANIES WOULD HAVE GIVEN

20

RAISES TO THEIR PEOPLE IF THIS ONE PERSON HAD GOTTEN A RAISE.

21

THAT'S THEIR THEORY, THE RIPPLE EFFECT.

22

THE DATA SHOWS THAT THEY'RE -- EVEN IN THE BEFORE TIME

23

PERIOD --

24
25

THE COURT:

ALL RIGHT.

I REALLY NEED YOU TO WRAP

UP, OKAY.

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3
4
5

MR. MITTELSTAEDT:

LAST WORD.

WHEN YOU LOOK AT THE

DATA FROM THE -THE COURT:

YOU'RE KILLING ME HERE.

(LAUGHTER.)
MR. MITTELSTAEDT:

WHEN YOU LOOK AT THE DATA FROM

6

THE BEFORE PERIOD, IT SHOWS THAT THESE COMPANIES DID NOT HAVE

7

THE RIGID PAY STRUCTURE THAT IS, UNDER THEIR OWN METHOD, THE

8

CENTERPIECE, THE ESSENTIAL ELEMENT OF THEIR CLAIM, LEAVING US

9

WITH INDIVIDUALIZED INQUIRIES TO DETERMINE WHO WAS IMPACTED.

10

THE COURT:

OKAY.

11

MR. MITTELSTAEDT:

12

THE COURT:

13

MR. MITTELSTAEDT:

14

THE COURT:

THANK YOU, YOUR HONOR.

THANK YOU.
I APPRECIATE THE TIME.

I'M GOING TO KEEP YOU TO TWO MINUTES

15

BECAUSE YOU HAD A LOT OF TIME FOR THIS HEARING AND DEFENDANTS

16

DIDN'T HAVE THAT TIME.

17

MR. GLACKIN:

I UNDERSTAND, YOUR HONOR.

18

TO NOT RESPOND TO ALL OF THAT.

19

BUT I'LL LEAVE IT TO THE RECORD.

20

I'M GOING

BEEN ADDRESSED IN THE RECORD.

21
22
23
24
25

I MEAN, I DON'T AGREE WITH IT,
I THINK ALL THOSE POINTS HAVE

I WANTED TO MAKE -- SO I WANTED TO DRAW THE COURT'S
ATTENTION TO TWO CASES.
MR. MITTELSTAEDT:

BRANDON.

I FORGOT TO SAY THE LAST THING I WAS LEADING UP TO, WHICH
IS NOW THAT YOUR HONOR HAS LOOKED AT ALL OF THIS AND IS

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STARTING TO STUDY IT, OR WHATEVER STAGE YOU'RE IN, I WOULD ASK

2

YOUR HONOR TO RECONSIDER WHETHER AN EVIDENTIARY HEARING WOULD

3

MAKE SENSE GIVEN WHAT THEY'VE SAID ABOUT -- DID I SAY THAT?

4

THE CLERK:

YOU DID.

5

MR. MITTELSTAEDT:

6

MR. GLACKIN:

7

THE COURT:

I DID SAY THAT?

YOU SAID IT ALREADY.

OKAY.

I MEAN, IF THEY CAN'T PROVE IT,

8

THEY CAN'T -- IF THEY CAN'T PRESENT IT TODAY, I'M NOT GOING TO

9

GIVE DR. LEAMER ANOTHER OPPORTUNITY TO TRY TO CORRECT IT.

10

MR. MITTELSTAEDT:

11

MR. GLACKIN:

OKAY.

SO, YOUR HONOR, MR. MITTELSTAEDT SAID

12

THAT THE MOST IMPORTANT CASE YOU NEED TO UNDERSTAND IS THE REED

13

CASE, WHICH IS FROM THE NORTHERN DISTRICT OF ILLINOIS.

14

THEY'VE NEVER ADDRESSED KOHEN AND MESSNER, WHICH ARE THE

15

AUTHORITIES WE CITED FOR THE PROPOSITION THAT YOU DO NOT NEED

16

TO SHOW HARM TO EVERY INDIVIDUAL CLASS MEMBER.

17

THOSE ARE CASES FROM THE SEVENTH CIRCUIT COURT OF APPEALS

18

WHICH, BY THE WAY, OVERSEES THE NORTHERN DISTRICT OF ILLINOIS,

19

SO I THINK THAT THOSE ARE FAR BETTER AUTHORITY ON THIS POINT.

20

AND I WANTED TO CALL THE COURT'S ATTENTION TO THE FACT

21

THAT THERE -- I JUST FIGURED OUT YESTERDAY, AND I TOLD THEM I

22

WOULD RAISE THIS YESTERDAY, I FOUND TWO MORE CASES THAT SHOW

23

THAT THIS RULE OF KOHEN THAT YOU DO NOT NEED TO SHOW INJURY ON

24

AN INDIVIDUAL BY INDIVIDUAL BASIS TO EVERY SINGLE CLASS MEMBER

25

HAS BEEN ADOPTED IN TWO MORE CIRCUITS, THE TENTH CIRCUIT AND

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THE FIFTH CIRCUIT, AND I'M JUST GOING TO READ THE CITATIONS

2

INTO THE RECORD.

3

THE FIRST CASE IS D.G. VERSUS DEVAUGHN, CITE 594 F.3D

4

1188, AND THAT'S IN THE TENTH CIRCUIT; AND THE SECOND

5

CIRCUIT -- EXCUSE ME -- THE SECOND CASE IS MIMS VERSUS STEWART

6

TITLE GUARANTEE COMPANY, THE CITATION IS 590 F.3D 298, AND

7

THAT'S IN THE FIFTH CIRCUIT.

8
9
10
11

AND IN BOTH THOSE CASES, BOTH OF THOSE COURTS SAY YOU DO
NOT NEED TO SHOW INDIVIDUAL PROOF TO EVERY SINGLE MEMBER OF THE
CLASS, AND THEY CITE AND QUOTE KOHEN FOR THAT PROPOSITION.
I WANTED TO ADDRESS -- I WANTED TO SAY ALSO THAT WE HAD A

12

LOT OF QUESTIONS AND A LOT OF ARGUMENT TODAY ABOUT REGRESSION

13

ANALYSIS, AND I WOULD REALLY ENCOURAGE THE COURT TO READ

14

CLOSELY THE SUPREME COURT'S BAZEMORE DECISION.

15

FOR THE GENERAL PROPOSITION THAT IT'S CITED FOR IN EVERY CASE,

16

WHICH IS THAT IF YOU COVER THE MAJOR FACTORS, A REGRESSION

17

ANALYSIS IS NOT, FOR OTHER REASONS, INADEQUATE.

18

WE CITE THAT

THERE'S TWO OTHER THINGS WE DIDN'T HAVE SPACE TO MENTION

19

IN THE BRIEFS, WHICH IS, ONE, BAZEMORE IS A WAGE SUPPRESSION

20

CASE, AND THE PLAINTIFFS IN BAZEMORE WERE SEEKING TO DO EXACTLY

21

THE SAME THING THAT WE ARE SEEKING TO DO HERE, AND THE COURT OF

22

APPEAL REJECTED THEIR REGRESSION ANALYSIS BECAUSE THEY DIDN'T

23

HAVE ALL OF THE VARIABLES THAT THE COURT OF APPEAL THOUGHT WAS

24

RELEVANT AND THE SUPREME COURT REVERSED.

25

THE COURT OF APPEAL ALSO REJECTED THEIR ANALYSIS BECAUSE

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THEY FAILED TO DISAGGREGATE THE DATA ON A COUNTY BY COUNTY

2

BASIS.

3

SHOULD HAVE BEEN EXAMINED COUNTY BY COUNTY BY COUNTY IN ORDER

4

TO EXCLUDE THE POSSIBILITY THAT COUNTY BY COUNTY DIFFERENCES

5

WERE DRIVING THE RESULT OR BEING OBSCURED BY THE RESULT, AND

6

THE SUPREME COURT REJECTED THAT AS WELL AND REVERSED.

7

THE COURT OF APPEAL SAYS THAT THIS -- THAT THESE WAGES

THE SUPREME COURT -- WHETHER OR NOT THIS WAS ADMISSIBLE

8

EVIDENCE WASN'T EVEN ON THE TABLE.

9

THE BENCH VERDICT THAT THE PLAINTIFFS HAD NOT MET THEIR

10

STANDARD OF BURDEN OF PROVING BY A PREPONDERANCE OF THE

11

EVIDENCE BECAUSE IT FOUND THAT THE SUPREME COURT -- EXCUSE

12

ME -- THE COURT OF APPEAL AND THE DISTRICT COURT HAD APPLIED

13

THE WRONG LEGAL STANDARD IN REJECTING THIS EVIDENCE AS

14

PROBATIVE.

15

THE SUPREME COURT REVERSED

SO I THINK THAT A CLOSE READING OF THE BAZEMORE CASE WILL

16

REALLY HELP UNDERSTAND -- HELP ILLUSTRATE JUST HOW COMMON AND

17

ACCEPTED REGRESSION ANALYSIS IS, AND THAT ALL OF THESE POINTS

18

ABOUT SENSITIVITY AND DISAGGREGATION AND WHETHER OR NOT WE USE

19

THE RIGHT VARIABLES ARE -- THEY'RE AT GREAT RISK FOR

20

CROSS-EXAMINATION AND I'VE SEEN IT DONE.

21

AGAINST DR. LEAMER IN TRIAL.

22
23
24
25

I'VE SEEN IT DONE

BUT IT'S NOT AN ISSUE THAT GOES TO THE ADMISSIBILITY OF
THE EVIDENCE.
AND ON THAT LAST POINT, THE ONE THING THAT I JUST HAVE TO
SAY IS THAT WHEN -- IT'S REALLY EASY FOR MR. MITTELSTAEDT TO

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STAND HERE AND SAY THAT LCD WAS A REAL EASY STANDARD PRICE

2

FIXING CASE AND IMPACT WAS PRACTICALLY PRESUMED.

3

NOTHING COULD BE FURTHER FROM THE TRUTH, FRANKLY.

THE

4

DEFENDANTS CONTESTED IMPACT AT EVERY STEP OF THE CASE.

THE

5

DEFENDANTS' ARGUMENT WAS ACTUALLY VERY SIMILAR TO THE ARGUMENT

6

IN THIS CASE.

7

PRODUCT MODELS EVERY YEAR.

8

DIFFERENT FEATURES.

9

INDIVIDUAL PRICE FOR EVERY SINGLE ONE OF THESE PRODUCT MODELS

THEY SAID, "WE HAVE THOUSANDS OF DIFFERENT
THESE PRODUCTS HAVE TONS OF

WE SET IT -- WE NEGOTIATE A DIFFERENT

10

WITH OUR CUSTOMERS, SO HOW CAN YOU POSSIBLY SHOW THAT EVERY

11

CUSTOMER WAS INJURED UNLESS YOU LOOK AT EVERY INDIVIDUAL

12

TRANSACTION BETWEEN THAT CUSTOMER AND THE DEFENDANTS?"

13

AND THE LAW IS CLEAR THAT THAT IS NOT OUR BURDEN AND,

14

FRANKLY, THE TESTIMONY IN THIS CASE IS CLEAR THAT THAT

15

REGRESSION ANALYSIS IS NOT CAPABLE OF THAT KIND OF AN INQUIRY.

16

SO WHAT DID WE DO IN LCD?

WE DID EXACTLY THE SAME THING

17

THAT'S BEEN PROPOSED HERE.

18

SHOW A STRUCTURE IN THE MARKET, AND WE OFFERED A REGRESSION

19

ANALYSIS TO SHOW BOTH IMPACT AND DAMAGES, AND THAT WAS

20

TESTIFIED TO AT TRIAL OVER A DAUBERT MOTION.

WE DID A CORRELATION ANALYSIS TO

21

THAT REGRESSION MODEL PRODUCED AN AVERAGE EFFECT

22

COEFFICIENT FOR THE CONSPIRACY, JUST LIKE IN THIS CASE, THE

23

REASON BEING THAT WE COULD NOT POSSIBLY -- DR. LEAMER COULD NOT

24

POSSIBLY CONTROL FOR EVERY SINGLE DIFFERENT COMBINATION OF

25

PRODUCT FEATURES IN THIS, YOU KNOW, IN THIS MASSIVE MARKET.

UNITED STATES COURT REPORTERS

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150

1

SO INSTEAD THERE WAS A SINGLE -- THERE WAS A SINGLE

2

CONSPIRACY EFFECT VARIABLE FOR THE ENTIRE CONSPIRACY, JUST LIKE

3

HERE; AND THEN DR. LEAMER, JUST LIKE HERE, HE TOOK STEPS TO TRY

4

TO ALLOW THAT VARIABLE TO BE HETEROGENEOUS ACROSS DIFFERENT

5

SCREEN SIZES.

6

THERE WAS DATA ENOUGH TO DO THAT.

SO WE ALLOWED -- JUST LIKE HERE WHERE HE'S ALLOWED TO VARY

7

DEFENDANT BY DEFENDANT BASED ON QUALITIES THAT ARE UNIQUE TO

8

EACH DEFENDANT, IN LCD, HE ALLOWED THE IMPACT OF THAT VARIABLE

9

TO DIFFER SCREEN SIZE BY SCREEN SIZE BASED ON DIFFERENT

10
11

FEATURES OF THOSE MARKETS.
IT'S EXACTLY THE SAME EVIDENCE.

AND THE DEFENDANTS MADE

12

THE SAME ARGUMENTS IN THAT CASE, THAT HIS REGRESSION ANALYSIS

13

WAS SENSITIVE.

14

IF YOU MOVE THE END DATE OF THE CONSPIRACY --

THE COURT:

I NEED YOU TO WRAP UP.

THIS IS CRUEL

15

AND UNUSUAL PUNISHMENT TO MS. SHORTRIDGE WHO'S BEEN

16

TRANSCRIBING FOR NEARLY FOUR HOURS, OKAY?

17

CONCLUDE HERE.

18
19
20

FIVE MINUTES.

SO YOU NEED TO

FIVE SECONDS.

MR. GLACKIN:

I DON'T EVEN NEED FIVE SECONDS.

I

DON'T HAVE ANY MORE TO ADD.

21

THANK YOU VERY MUCH.

22

THE COURT:

23

OKAY.

I'M GOING TO GIVE MR. HINMAN --

RIGHT? -- THE LAST WORD.

24

MR. HINMAN:

YES.

THANK YOU, YOUR HONOR.

25

DON'T WANT TO ADD TO THE MISERY.

AND I

JUST VERY BRIEFLY.

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WITH RESPECT TO THESE NOTES, TO THE EXTENT THAT THIS IS

2

STILL AN ISSUE AT ALL IN YOUR HONOR'S MIND, I THINK WE HEARD

3

SOME THINGS THAT, FRANKLY, AREN'T IN THE RECORD AND I DON'T

4

THINK ARE QUITE RIGHT.

5
6
7

SO WHAT I WOULD SAY IS THE ARGUMENT BOILS DOWN TO
DR. MURPHY HAS GOT TO DISCLOSE WHAT HE RELIED ON.
HE WAS ASKED IN HIS DEPOSITION WHAT HE RELIED ON, AND HE

8

SAID, "SPECIFICALLY I'M RELYING ON THOSE DECLARATIONS," SO THE

9

DECLARATIONS THAT ARE BEFORE THE COURT AND IN THE RECORD,

10

"THAT'S CONSISTENT WITH OTHER THINGS THAT, IN THE INTERVIEWS,

11

THAT PEOPLE SAID."

12

THAT'S AT PAGE 133 TO -34.

AND THEN AT PAGE 122, HE SAID, "IN GENERAL, IT WAS RELYING

13

ON THE GENERAL BACKGROUND.

14

THINK IN THAT REGARD, I THINK THE INFORMATION FROM THE

15

INTERVIEWS AND THE INFORMATION FROM THE DECLARATIONS.

16

JUST AT THE END OF THE DAY, GIVEN THAT WE HAD THE DECLARATIONS,

17

IT MADE MORE SENSE TO RELY UPON THEM."

18

AS I'VE SAID NUMEROUS TIMES, AND I

IT'S

SO HE'S DISCLOSED THE DECLARATIONS, HE'S DISCLOSED THE

19

PEOPLE WHO HE INTERVIEWED, HE WAS ASKED MANY, MANY QUESTIONS

20

ABOUT THE INTERVIEWS HAVING TO DO WITH THE UNDERLYING FACTS

21

THAT HE LEARNED THERE, AND IF THE PLAINTIFFS THINK THAT IT'S A

22

PROBLEM THAT HE COULDN'T SPECIFICALLY REMEMBER WHAT EACH PERSON

23

TOLD HIM OR THAT HIS OPINIONS ARE BASED ON FACTS THAT ARE

24

INCORRECT, THEN I WOULD THINK THAT THEY WOULD HAVE COME IN AND

25

ARGUED THAT.

UNITED STATES COURT REPORTERS

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WELL, THEY HAVEN'T.

2

OR THEY COULD HAVE PURSUED IT FURTHER WITH HIM, AND THEY

3
4

DIDN'T.
OR THEY COULD HAVE DEPOSED THOSE PEOPLE, MANY OF WHOM THEY

5

NEVER ASKED TO DO, NOTWITHSTANDING THAT THEY WERE FULLY

6

DISCLOSED, AND SAY, YOU KNOW, "WHAT DID YOU TELL DR. MURPHY?"

7

AND THEN TEST HIS OPINIONS AGAINST THAT.

8
9

SO THE POINT IS, HE DISCLOSED WHAT HE NEEDED TO DISCLOSE.
THERE WERE MANY WAYS -- IF THEY WANT TO CHALLENGE WHAT THOSE

10

UNDERLYING FACTS ARE, THEY WERE ENTITLED TO DO THAT IN ALL OF

11

THE USUAL WAYS.

12

AND AS I SAID BEFORE, THERE'S NOTHING EITHER LEGALLY OR,

13

FRANKLY, LOGICALLY THAT GETS YOU TO THESE PRELIMINARY NOTES

14

THAT WERE TAKEN, ESPECIALLY WHEN WE HAVE THIS VERY BROAD

15

STIPULATION.

16
17
18

THE COURT:

ALL RIGHT.

WELL, THANK YOU ALL VERY MUCH.

MARCH 13TH IS WHEN WE SET THIS, RIGHT?

19

THE CLERK:

20

MR. GLACKIN:

21

MR. MITTELSTAEDT:

22

MR. HINMAN:

23

MR. GLACKIN:

24
25

WE'LL SEE YOU, THEN, ON --

YES.
THANK YOU VERY MUCH, YOUR HONOR.
THANK YOU, YOUR HONOR.

THANK YOU, YOUR HONOR.
AND THANK YOU MEMBERS OF THE COURT

STAFF.
THE COURT:

THANK YOU VERY MUCH FOR ALL OF YOUR

UNITED STATES COURT REPORTERS

314

153

1
2
3

PRESENTATIONS.
MR. MITTELSTAEDT:

THANK YOU, YOUR HONOR.

(THE PROCEEDINGS IN THIS MATTER WERE CONCLUDED.)

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5
6
7
8
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10
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25

UNITED STATES COURT REPORTERS

315

1
2
CERTIFICATE OF REPORTER

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4
5
6
7

I, THE UNDERSIGNED OFFICIAL COURT REPORTER OF THE UNITED

8

STATES DISTRICT COURT FOR THE NORTHERN DISTRICT OF CALIFORNIA,

9

280 SOUTH FIRST STREET, SAN JOSE, CALIFORNIA, DO HEREBY

10
11

CERTIFY:
THAT THE FOREGOING TRANSCRIPT, CERTIFICATE INCLUSIVE, IS

12

A CORRECT TRANSCRIPT FROM THE RECORD OF PROCEEDINGS IN THE

13

ABOVE-ENTITLED MATTER.

14
15

17

_______________________________
LEE-ANNE SHORTRIDGE, CSR, CRR
CERTIFICATE NUMBER 9595

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DATED:

16

FEBRUARY 5, 2013

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UNITED STATES COURT REPORTERS

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IN THE UNITED STATES DISTRICT COURT
FOR THE NORTHERN DISTRICT OF CALIFORNIA
SAN JOSE DIVISION
CONFIDENTIAL – TO BE FILED UNDER SEAL
SUBJECT TO PROTECTIVE ORDER

IN RE: HIGH-TECH EMPLOYEES ANTITRUST
LITIGATION

No. 11-CV-2509-LHK

_____________________________________
THIS DOCUMENT RELATES TO:
ALL ACTIONS

EXPERT REPORT OF EDWARD E. LEAMER, PH.D.

October 1, 2012

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TABLE OF CONTENTS

I. 

Experience and Qualifications ...................................................1 

II. 

Introduction, Assignment, and Summary of Conclusions ..........2 

III.  Case and Background ................................................................ 6 
A.  Defendants..................................................................................... 6 
B.  The Non-Compete Agreements .......................................................... 9 
1.  Pixar-Lucasfilm ......................................................................... 12 
2.  The Apple Non-Compete Agreements ........................................... 14 
3.  The Google Non-Compete Agreements ......................................... 19 
4.  Department of Justice Investigation and the End of the Collusion..... 22 
C.  Named Plaintiffs ............................................................................ 22 
D.  Background on Defendants’ Recruiting and Hiring Practices ................. 25 

IV. 

Common Evidence and Analysis Are Capable of Showing that
the Non-Compete Agreements Artificially Reduced the
Compensation of Defendants’ Salaried Employees ..................28 
A.  Class-wide Evidence is Capable of Showing that the Non-Compete
Agreements Suppressed Compensation Generally .............................. 29 
1.  Economic Theory Offers a Classwide Basis for Linking Non-Compete
Agreements to Suppressed Compensation Incurred by Members of
the All-Employee Class and Technical Employee Class .................... 29 
2.  Defendants’ Internal Documents Provide Additional Class-wide
Evidence Capable of Showing that the Non-Compete Agreements
Artificially Suppressed Compensation ........................................... 33 
3.  Analysis of Defendants’ Compensation Data Is Additional Class-wide
Evidence Capable of Showing that the Compensation of AllEmployee Class and Technical Employee Class Members Was
Suppressed by the Non-Competition Agreements .......................... 35 
4.  Common Evidence Confirms that the Non-Compete Agreements
Coincided with Periods of Economic Expansion that Otherwise
Would Have Increased Compensation to Class Members ................. 38 
B.  Classwide Evidence is Capable of Showing that the Non-Compete
Agreements Suppressed the Compensation of All or Nearly All
Members of the All-Employee Class and Technical Employee Class ....... 42 

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1.  Defendants’ Internal Documents Constitute an Additional Form of
Common Proof Capable of Showing that the Non-Compete
Agreements Suppressed Compensation to All or Nearly All
Members of the All-Employee Class and Technical Employee Class ... 45 
2.  Econometric and Statistical Analysis of Defendants’ Compensation
Data Is Also Capable of Demonstrating That the Compensation
Suppressing Effects of the Non-Compete Agreements Would Be
Broadly Experienced By Members of the All-Employee Class and
Technical Employee Class .......................................................... 49 
3.  Standard Econometric Analysis Is Capable of Showing That the
Non-Compete Agreements Artificially Suppressed Compensation to
the Members of Each Class Generally........................................... 62 

V. 

Conclusion............................................................................... 70 

APPENDIX A. 

Defendant Data Relied Upon ...................................72 

A.  Description of Data Requested and Produced ..................................... 72 
1.  Employment Data ..................................................................... 72 
2.  Recruiting Data ........................................................................ 72 
B.  Datasets Created for Analysis ......................................................... 73 

APPENDIX B. 

Definition of the Technical Employee Class .............74 

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TABLE OF FIGURES

Figure 1: Periods of the Alleged Collusive Agreements ................................................... 9 
Figure 2: Relationships of the Alleged Agreements Among Defendants ........................... 10 
Figure 3: Class Employee Summary .......................................................................... 23 
Figure 4: Technical Employee Class Summary ............................................................ 23 
Figure 5: Named Plaintiffs’ Employment Histories ....................................................... 25 
Figure 6: Inter-firm Movement Results in Higher Base Compensation ............................ 37 
Figure 7: Inter-firm Movement Results in Higher Total Compensation ............................ 38 
Figure 8: Use of Equity Compensation ....................................................................... 40 
Figure 9: Growth of Apple's Revenue and Compensation .............................................. 41 
Figure 10: Use of Supplemental Compensation was Widespread ................................... 53 
Figure 11: Common Factors Identify a Firmwide Compensation Structure....................... 54 
Figure 12: Common Factors Explain Within-Firm Compensation Structure ...................... 56 
Figure 13: Common Factors Identify a Firmwide Compensation Structure....................... 57 
Figure 14: Common Factors Explain Within-Firm Compensation Structure ...................... 58 
Figure 15: Constant Attribute Compensation of Major Apple Job Titles ........................... 59 
Figure 16: Constant Attribute Compensation of Major Google Job Titles ......................... 60 
Figure 17: Constant Attribute Compensation Ranking of Major Apple Job Titles is Generally
Stable .................................................................................................................. 61 
Figure 18: Growth Cycle Periods for the U.S. Economy ................................................ 62 
Figure 19: Average Percent Change in Total Compensation .......................................... 63 
Figure 20: Regression Estimate of Undercompensation to Class .................................... 66 
Figure 21: Data Definitions ...................................................................................... 67 
Figure 22: Estimated Impact on Class Total Compensation ........................................... 67 
Figure 23: Regression Estimate of Undercompensation to Technical Employee Class ........ 69 
Figure 24: Estimated Impact on Technical Employee Class Total Compensation............... 70 
Figure 25: Adobe, Apple, Google, Intel, and Intuit Creative, Technical, and R&D Job Families
........................................................................................................................... 75 

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CONFIDENTIAL

I.

10/1/2012

Experience and Qualifications

1.

I am the Chauncey J. Medberry Professor of Management, Professor of
Economics and Professor of Statistics at the University of California at Los
Angeles. I earned a B.A. degree in Mathematics from Princeton University in
1966, and a Masters in Mathematics and a Ph.D. degree in Economics at the
University of Michigan in 1970. I was an Assistant and Associate Professor of
Economics at Harvard University from 1970 to 1975, and joined the Economics
Department at UCLA in 1975 as a Full Professor. I served as Chair of the
Department of Economics from 1983 to 1987 and Area Head of Business
Economics from 1990 to 1993. I had a tenured appointment in the Economics
Department at Yale University in 1995 and I have been a Visiting Professor at
several universities, including the University of Chicago. I have been a Guest
Professor at the University of Basel in Switzerland, at the Central European
University in Prague, Czech Republic, at the Institute for Advanced Studies in
Vienna, Austria, and at the Universidad de San Andreas in Buenos Aires,
Argentina. I have served as the Director of the UCLA Anderson Forecast since
2000 and Chief Economist of the Ceridian-UCLA Pulse of Commerce Index
from 2010-2012.

2.

I have published extensively in the fields of econometric methodology and
statistical analysis, in international economics, and in macro-economic
forecasting. I have written five books and over 90 academic articles, many of
which deal with the subject of inferences that may appropriately be drawn from
non-experimental data. My academic research in econometrics and international
economics has been profiled in New Horizons in Economic Thought,
Appraisals of Leading Economists, edited by Warren Samuels. My papers in
econometrics have been republished in a volume in the Edward Elgar Series:
Economists of the 20th Century. My research has been funded by the
National Science Foundation, the Ford Foundation, the Sloan Foundation, and
the Russell Sage Foundation.

3.

I am an elected Fellow of two of the most important honorific societies in my
field: the American Academy of Arts and Sciences and the Econometric Society.
I have been a consultant for the Federal Reserve Board of Governors, the
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Department of Labor, the Department of Energy, the International Monetary
Fund, the World Bank, the Inter-American Development Bank, and the
Treasury of New Zealand. I have been a visiting scholar with the Federal
Reserve Board and the International Monetary Fund. I have served as an expert
in a variety of matters dealing with issues of interpretation of data.
4.

My curriculum vita is incorporated in this report as Exhibit 1. My testimonial
experience is incorporated in this report as Exhibit 2. My hourly rate for time
spent working on this matter is $650.

5.

I have in this report relied on the best information available to me at the time of
its preparation. A list of documents on which I relied in the preparation of this
report is provided in Exhibit 3. I understand that discovery in this matter is
ongoing and that Defendants or third parties may produce additional
information that has a bearing on my analysis. I reserve the right to supplement
or amend my conclusions as necessary in light of such additional information.

II.

Introduction, Assignment, and Summary of Conclusions

6.

The defendants in this matter are a group of well-known high-tech firms,
namely Adobe, Apple, Google, Intel, Intuit, Lucasfilm, and Pixar
(“Defendants”).1

7.

The Plaintiffs’ Amended Complaint2 alleges that the Defendants agreed to limit
or eliminate competition for workers amongst each other by refraining from

Adobe Systems Inc. (“Adobe”) is a Delaware corporation with its principal place of business located at 345
Park Avenue, San Jose, California 95110, Apple Inc. (“Apple”) is a California corporation with its principal
place of business located at 1 Infinite Loop, Cupertino, California 95014, Google Inc. (“Google”) is a
Delaware corporation with its principal place of business located at 1600 Amphitheatre Parkway, Mountain
View, California 94043, Intel Corp. (“Intel”) is a Delaware corporation with its principal place of business
located at 2200 Mission College Boulevard, Santa Clara, California 95054, Intuit Inc. (“Intuit”) is a Delaware
corporation with its principal place of business located at 2632 Marine Way, Mountain View, California
94043, Lucasfilm Ltd. (“Lucasfilm”) is a California corporation with its principal place of business located at
1110 Gorgas Ave., in San Francisco, California 94129, and Pixar is a California corporation with its principal
place of business located at 1200 Park Avenue, Emeryville, California 94608.
1

Re: High-Tech Employee Antitrust Litigation, Consolidated Amended Complaint, September 2, 2011
(Consolidated Amended Complaint).
2

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contacting each others’ employees to explore job offers (“Cold-Calling”3),
limiting their actions in negotiating with their workers, and other restrictions.
This was accomplished by means of a collection of express bilateral agreements
among the Defendants. I will refer to these agreements, individually and
collectively, as the “Non-Compete Agreements,” or as the “Agreements.”
8.

I understand that the Plaintiffs are seeking certification of the following class of
employees (the “All-Salaried Employee Class,” or, the “All-Employee Class”):
All natural persons employed on a salaried basis (“salaried employees”)
in the United States by one or more of the following: (a) Apple from
May 2005 through December 2009; (b) Adobe from May 2005 through
December 2009; (c) Google from March 2005 through December
2009; (d) Intel from March 2005 through December 2009; (e) Intuit
from June 2007 through December 2009; (f) Lucasfilm from January
2005 through December 2009; or (g) Pixar from January 2005 through
December 2009. Excluded from the All-Employee Class are: retail
employees; corporate officers, members of the boards of directors, and
senior executives of all Defendants.

9.

I also understand that the Plaintiffs are seeking certification, in the alternative,
of the following alternate class of employees (the “Technical, Creative, and
Research & Development Class,” or, the “Technical Employee Class”):
All natural persons employed on a salaried basis who work in the
creative, research & development, and/or technical fields,4 in the
United States by one or more of the following: (a) Apple from May
2005 through December 2009; (b) Adobe from May 2005 through
December 2009; (c) Google from March 2005 through December
2009; (d) Intel from March 2005 through December 2009; (e) Intuit

“Cold-Calling” refers to communicating directly in any manner (including orally, in writing, telephonically,
or electronically) with another firm’s employee who has not otherwise applied for a job opening.
3

See Appendix B for a description of how I determined the members of the Technical and Creative Alternate
Class.

4

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from June 2007 through December 2009; (f) Lucasfilm from January
2005 through December 2009; or (g) Pixar from January 2005 through
December 2009. Excluded from the Technical Employee Class are:
retail employees; corporate officers, members of the boards of
directors, and senior executives of all Defendants.
10.

I have been asked to analyze the following questions with regard to the AllEmployee Class and Technical Employee Class defined above:
(a) Is there proof common to each proposed class
capable of showing that the Non-Compete Agreements
artificially reduced the competition of its members? In
order to answer this question, I have been asked to
evaluate whether evidence common to each class is
capable of showing that the Non-Competition
Agreements artificially reduced the compensation of: (i)
members of each class generally; and (ii) all or most
members of each class?
(b) Is there a reliable Class-wide or formulaic method
capable of quantifying the amount of suppressed
compensation suffered by each class?

11.

Based upon my work to date, I have reached the following conclusions:
(a) There is evidence common to the All-Employee Class
and Technical Employee Class, respectively, capable of
showing that the Non-Compete Agreements
systematically reduced the compensation of the members
of each class. Specifically, and as explained in the body
of this report, I have concluded that evidence and
economic analyses applicable to each class as a whole are
capable of showing that compensation to the AllEmployee Class and Technical Employee Class was
artificially suppressed generally due to the Non-Compete
Agreements.

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(b) Classwide evidence capable of showing artificial
generalized compensation suppression due to the
agreements falls into three categories: (1) labor
economic studies and theory explaining that by
reducing or eliminating Cold-Calling and other active
competition over employees, the Agreements were likely
to have depressed compensation because they impair
information flow about compensation and job offers,
reduce negotiating leverage of employees, and minimize
movement of employees between firms; (2) documents
from Defendants’ files showing the link between
“Cold-Calling” and increased compensation; and (3)
multiple regression analyses, utilizing Defendants’
internal compensation and other data, showing that the
Agreements artificially suppressed compensation at each
Defendant.
(c) I have further found that evidence and economic
analysis applicable to each class as a whole are capable of
showing that all or nearly all members of the AllEmployee Class and Technical Employee Class had their
compensation suppressed due to the Agreements. Such
classwide evidence falls into three categories: (1)
economic studies and theory, especially regarding the
interest of firms in preserving “internal equity,”
demonstrating that the adverse effects on compensation
due to a poaching ban would be felt not just by those
who would have been poached, but by employees more
generally due to the needs of firms to maintain a salary
structure; (2) documentary evidence from Defendants’
files showing Defendants’ own concerns about
preserving internal equity, as well as other documentary
evidence; and (3) statistical evidence, including a multiple
regression analysis, showing that All-Employee Class and
Technical Employee Class member compensation at any
point in time is governed largely by common factors.
What this analysis means is that any generalized
suppression of compensation due to the Agreements
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would be experienced by all or nearly all members of the
All-Employee Class and Technical Employee Class.
(d) Finally, I have concluded that standard economic
methods are capable of reliably quantifying the aggregate
amount of reduced compensation caused by the
Agreements to the All-Employee Class and Technical
Employee Class, respectively.
12.

III.

The analyses described in this report are performed for the purpose of
demonstrating the availability of proof and statistical methodologies common to
members of the All-Employee Class and the Technical Employee Class capable
of showing that members of each class suffered suppressed compensation due
to the Agreements, and capable of quantifying that harm. I understand that
discovery has not yet been completed and that further evidence might emerge
that is relevant to my analysis. I reserve the right to consider any such evidence
and its impact, if any, on the analysis I have proposed.

Case and Background
A. Defendants

13.

5

Adobe, founded in 1982, is a technology company with its headquarters in San
Jose, California.5 Adobe is well known for a number of software products
including Acrobat, Photoshop, and Illustrator. It is also known for its Flash
media platform which it acquired in late 2005 as part of its acquisition of
Macromedia, which had been the publisher of Dreamweaver and the Flash
media platform.6 In its 2009 fiscal year, Adobe had nearly $3 billion in
revenues.7

Adobe, “Corporate Overview,” http://www.adobe.com/aboutadobe/pressroom/pdfs/profile.pdf.

Adobe, “Adobe completes acquisition of Macromedia,”
http://www.adobe.com/aboutadobe/invrelations/adobeandmacromedia_faq.html.

6

7

Adobe Systems Incorporated, “2009 Form 10-K,” January 22, 2010 at pp.52.
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14.

Apple, founded in 1976, is a technology company that is headquartered in
Cupertino, California.8 The company is a market leader in several consumer
electronics market segments with its iPad, iPhone, and iPod product lines.9
Apple has been a leader in the digital music distribution market with its iTunes
service.10 Apple’s 2011 total revenues exceeded $108 billion.11

15.

Google, founded in 1998, is a technology company headquartered in Mountain
View, California.12 The company is the leading internet search provider.13 The
company went public in 2004. Google’s revenues reached nearly $38 billion in
2011.14

16.

Intel is a technology company, headquartered in Santa Clara, California. The
company was founded in 1968 and is the world’s largest semiconductor chip
maker.15 Intel is most well known for its x86 series of microprocessors, found in
most personal computers today16 but the company also markets other integrated

Time, “Top 10 Apple Moments,”
http://www.time.com/time/specials/packages/article/0,28804,1873486_1873491_1873530,00.html.

8

Reuters,“Company Profile for Apple Inc,”
http://in.reuters.com/finance/stocks/companyProfile?symbol=AAPL.O.

9

Whitney, Lance,“ iTunes reps 1 in every 4 songs sold in U.S,” CNET News, August 18, 2009,
http://news.cnet.com/8301-13579_3-10311907-37.html.
10

11

Apple Inc., “2011 Form 10-K,” October 26, 2011 at pp.24.

12

Google, “Our history in depth,” http://www.google.com/about/company/history/.

Google, “Google Launches World’s Largest Search Engine,” June 26, 2000, McGee, Matt, “Google Still
No. 1 Search Engine On Earth,” Searchengineland, August 31, 2009 and Google Inc., “2010 Annual Report,”
February 11, 2011 at p.25.

13

Google, “2012 Financial Tables – Investor Relations – Google,”
http://investor.google.com/financial/tables.html.

14

Intel, “Intel Company Information,” http://www.intel.com/content/www/us/en/companyoverview/company-facts.html.
15

Edwards, Benj, “Birth of a Standard: The Intel 8086 Microprocessor,” PCWorld, June 16, 2008,
http://www.pcworld.com/article/146957-3/birth_of_a_standard_the_intel_8086_microprocessor.html.

16

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circuits and devices related to communications and computing.17 Intel had
revenue of $54 billion in 2011.18
17.

Intuit is a technology company, headquartered in Mountain View, California.19
The company was founded in 1983 and is known for its QuickBooks, Quicken
and TurboTax software products. In 2011 the company revenues exceeded $3.8
billion.

18.

Lucasfilm is a film production company known for its computer animation
expertise, headquartered in San Francisco, California. Founded in 1971, the
company is best known for producing the Star Wars films, as well as other box
office hits, including the Indiana Jones franchise. Lucasfilm has seven different
divisions: Industrial Light & Magic, LucasArts, Lucasfilm Animation, Skywalker
Sound, Lucas Licensing, Lucas Online and Lucasfilm Singapore. Lucasfilm
Animation has studios both in Marin County, California and Singapore.

19.

Pixar is a computer animation film studio headquartered in Emeryville,
California.20 The company was founded in 1979 as Graphics Group and later
renamed to Pixar in 1986.21 In 2006 the company was acquired by Disney for
approximately $7.4 billion.22 Prior to the acquisition, in 2005 Pixar had annual
revenues of nearly $290 million.23

17

Intel, “Intel Products,” http://www.intel.com/p/en_US/products/productsbyintel.

18

Intel Corporation, “2011 Annual Report,” February 23, 2012 at p.2.

19

Intuit, “Intuit: Corporate Profile,” http://about.intuit.com/about_intuit/profile/.

20

Pixar, “Pixar: Welcome,” http://www.pixar.com/about.

21

Pixar, “Pixar History: 1986,” http://www.pixar.com/about/Our-Story.

Pixar, “Pixar History: 2006,” http://www.pixar.com/about/Our-Story and “Disney buying Pixar for $7.4
billion,”NBC News, 1/25/2006, http://www.msnbc.msn.com/id/11003466/ns/businessus_business/t/disney-buying-pixar-billion.

22

23

Pixar, “2005 10-K,” March 7, 2006 at p.37.
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B. The Non-Compete Agreements

20.

I have studied the allegations of the Plaintiffs’ complaint and evidence of the
Non-Compete Agreements. I have not been asked to form an opinion on the
ultimate question of whether or not the Defendants reached anticompetitive
agreements or should be liable under the law. However, I have reviewed
evidence about the agreements and their enforcement to understand their scope
and duration for purposes of my analysis, and to assure myself that certain
assumptions I have made fit the circumstances.

21.

Based on that review, I understand the time periods of the alleged NonCompete Agreements to have been as follows.
Figure 1: Periods of the Alleged Collusive Agreements

Defendants
(1)

End Date25
(3)

Adobe-Apple
Apple-Pixar
Apple-Google
Google-Intel
Google-Intuit
Lucasfilm-Pixar
22.

Start Date24
(2)
May 2005
April 2007
February 2005
March 2005
June 2007
Before 2000

March 2009
March 2009
March 2009
March 2009
March 2009
March 2009

I also understand that Defendants entered into several additional agreements.
Those agreements include: (1) an agreement between Pixar and Intel that began
in approximately October 2008,26 and (2) agreements Apple apparently had with

See ADOBE_001096-097 and 231APPLE002145 (Adobe-Apple); PIX00003419 (Apple-Pixar);
231APPLE002140 and 231APPLE073139 (Apple-Google); GOOG-HIGH TECH-00008281-284 (GoogleIntel); GOOG-HIGH TECH-00008342-350 (Google-Intuit); and Deposition of James Morris, August 3,
2012 at p. 93 (Lucasfilm-Pixar).

24

These dates are based on the notice send to a party to the alleged agreement. I understand that Apple and
Google each received a Civil Investigative Demand (“CID”) on March 13, 2009. Pixar received a CID on
May 27, 2009.

25

See PIX00015306 (Intel agreed with Pixar that it “will not proactively pursue any Pixar employee going
forward.”) The agreement also included a no-hire without permission provision that prohibited Intel from
hiring Pixar employees, regardless of whether a Pixar employee contacted Intel first, unless the head of Pixar

26

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Intel, Intuit, and Lucasfilm that mirrored Apple’s agreements with Adobe, Pixar,
and Google.27
Figure 2: Relationships of the Alleged Agreements Among Defendants

23.

All of the Non-Compete Agreements covered all employees of the respective
companies, regardless of employee geography, job function, product group, or
time period. Each of the Agreements prohibited cold-calling, meaning that the
parties agreed not to solicit each other’s employees in any manner. This
agreement applied to all recruiters who were either directly employed by or were

approved the hire. See also, 76577DOC000464 (“We cannot recruit (including calling up, emailing, or
enticing in any way) current Pixar employees to come work for Intel. If a Pixar employee applies without
being recruited by Intel, contact Pat Gelsinger [a Senior VP at Intel] and explain to him a Pixar employee
(provide the candidates [sic] name) has applied to Intel without being recruited and he will contact the CEO
of Pixar for approval to hire.”).
See 231APPLE041661 and 231APPLE041662 (Apple’s “Hands Off (Do Not Call List)” included every
Defendant).

27

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headhunters hired by the agreeing firms.28 Some of the agreements included
additional terms, such as:




28

Pre-notify: The parties agreed to notify each other prior to making an
offer to hire an employee at the other firm.30



24.

Do not hire: The parties agreed not to make employment offers to
employees of the other firm without specific approval from the current
employer’s chief executive.29

No counteroffer. The initiating firm that makes an offer to an
employee of the other firm agreed not to improve its initial offer if the
offer was matched by the other firm.31 In other words, “no bidding
wars.”32

The sections below describe each of the agreements among the seven
Defendants as I understand them.

See e.g., 231APPLE001164, GOOG-HIGH TECH-00023500-601 at 520-528., and PIX00000400.

When present, this provision applied even when an employee initiated contact. See, e.g.,
76577DOC000464. Even if certain agreements may not have begun with this express provision, they often
operated in this manner in practice. For example, Pixar and Google sought Steve Jobs’s permission before
making offers to Apple employees. See PIX00006025; 231APPLE002151. Apple refused to consider Adobe
employees unless they first left employment with Adobe. See 231APPLE080776 (“This is a response I
received from an ADOBE employee who applied for a position through our job posting site. I called him to
ensure he is still an ADOBE employee, explained our mutual agreement / guidelines, and asked that he
contact me should his employment with ADOBE terminate, but at this time I am unable to continue
exploring with him. . . . I do not want anything in ‘writing’.”) Apple also attempted to enter into a “no hire”
agreement with Palm, which Palm’s CEO Ed Colligan rejected. See PALM00005 – 008 at 006 and
PALM00022 – 027 at 024. See also, 231APPLE002153 - 154, and 231APPLE002214.

29

30

See e.g., PIX00000400; GOOG-HIGH TECH-00056790.

31

See PIX00000400; LUCAS00009252.

See PIX00004051 (“We just won’t get into bidding wars” for employees.); LUCAS00013507 (“We have
agreed we want to avoid bidding wars.”).

32

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1. Pixar-Lucasfilm

25.

I understand that a Non-Compete Agreement existed between Pixar and
Lucasfilm for many years, beginning well before the year 2000.33 In addition to
not Cold-Calling each other’s employees, each company agreed to inform the
other of any offer made to an employee of the other company pursuant to an
unsolicited application made by the employee.34 The agreements further
specified that in the case of such an unsolicited application the company making
the job offer would make only one offer, and would not improve it in response
to a counter-offer by the employee’s current employer.35 The agreement
covered all employees.36 On May 27, 2009, the DOJ issued a Civil Investigative
Demand (“CID”) to Pixar.37 I have been asked to assume the agreement ended
on that date.

26.

Jim Morris, Pixar’s General Manager and former head of Lucasfilm’s Industrial
Light and Magic division, described the agreement as follows in a videotape
created on December 9, 2008: “We have an anti-poach clause between the
Lucas companies and -- and this company. We don’t -- we don’t recruit from
one another, we don’t call -- if the people want to go from one company to the
other, we, you know, find a way to let that happen. But we have a -- sort of a
gentleman’s agreement that we’ve honored pretty well here for the last many
years.”38

27.

The “gentleman’s agreement” concerned all employees of the companies, had
no geographic limit, and had no expiration date.39 Pixar and Lucasfilm provided

See Deposition of Lori McAdams, August 2, 2012 at p. 127:4-16 (“Well, I was at Lucasfilm from 1984
through 1998, and that understanding was in place at that time.”); p. 132:15 (“[The agreement] had always
been there.”) and Deposition of James Morris, August 3, 2012 at p. 931.

33

34

PIX00002328-329 at 328 and PIX00000038-039; PIX00000400 and PIX00006057.

35

PIX00002328-329 at 328; PIX00000400.

36

PIX00002328-329 at 328.

37

See PIX00001958.

38

See Deposition of Jim Morris, August 3, 2012 at p. 113:10-16.

39

See Deposition of Jim Morris, August 3, 2012 at pp. 126:20-127:10; Deposition of Lori McAdams, August
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the written terms of the agreement to management and certain senior employees
with relevant hiring or recruiting responsibilities.40
28.

It appears the companies abided by this agreement41 and viewed it as important
to avoid competing for each other’s workers.42

29.

The executives of these firms also clearly viewed containing labor costs as a
major priority.43

30.

Pixar’s President Ed Catmull clearly understood the structural effect of
competition on wages. As he observed in an email to a Disney executive:
“Every time a studio tries to grow rapidly, it seriously messes up the pay
structure . . . by offering higher salaries to grow at the rate they desire, people
will hear about it and leave. We have avoided wars up here in Northern
California because all of the companies up here – Pixar, ILM [Lucasfilm],
Dreamworks, and a couple of smaller places – have conscientiously avoided
raiding each other.”44

2, 2012 at p. 160:23-25. See also, Deposition of Donna Morris, August 21, 2012 at pp. 226:22-227:5 and
Deposition of Mark Bentley, August 23, 2012 at pp. 17:21-18:2.
See Deposition of Lori McAdams, August 2, 2012 at p. 145:5-17; PIX00002262-64 (“I created it [summary
of no-solicitation agreement] to give to the recruiting team so they would know what the gentleman’s
agreement was.”).

40

Deposition of Lori McAdams, August 2, 2012 at pp. 149:17-151:17 (PIX0009416); pp. 135:12-137:1
(PIX00003640).

41

42 Deposition of Lori McAdams, August 2, 2012 at pp. 135:12-139:1; PIX00003640 (“[T]hey got really mad
that we hired Rob Rieders.”).
43

PIX00009216-217 at 217. (“I know you are adamant about keeping a lid on rising labor costs”).

44

PIX00000229.
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2. The Apple Non-Compete Agreements
a. Adobe

31.

As of May 2005, the CEOs of Apple and Adobe had entered into an agreement
that their respective companies would not recruit each other’s employees.45 This
agreement covered all employees.46 Apple placed Adobe on its “Do Not Call”
list and Adobe placed Apple on its “Companies that are off limits” list, both of
which instructed recruiters not to solicit employees from the listed companies
and to inform each other if senior executives of each company were actively
seeking employment at the other.47 On March 13, 2009, the DOJ issued CIDs
to Apple and Adobe.48 I have been asked to assume the agreement ended on
that date.

32.

On May 26, 2005, Steve Jobs complained to Adobe CEO Bruce Chizen that
Adobe was recruiting Apple employees.49 Chizen responded, “I thought we
agreed not to recruit any senior level employees … I propose we keep it that
way. Open to discuss. It would be good to agree.”50 Jobs replied: “OK, I’ll tell
our recruiters that they are free to approach any Adobe employee who is not a
Sr. Director or VP. Am I understanding your position correctly?” Chizen
appeared to recognize the threat and capitulated: “I’d rather agree NOT to
actively solicit any employee from either company . . . If you are in agreement I
will let my folks know.” The next day, Adobe HR Vice President Theresa
Townsley announced to her recruiting team, “Bruce and Steve Jobs have an

45

231APPLE002145.

46

231APPLE002145.

47

See 231APPLE001164 -165 and ADOBE_001096-097.

48

See 231APPLE003695 and ADOBE_007392.

49
50

See 231APPLE002143.
See 231APPLE002143.
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agreement that we are not to solicit ANY Apple employees, and vice versa.”51
Mr. Chizen forwarded Ms. Townsley’s email to Steve Jobs. 52
33.

I understand that the two firms abided by the agreement.53

34.

To ensure compliance with the agreement, Apple instructed its recruiting
personnel to adhere to the agreement.54 Adobe, in turn, placed Apple on its
“Companies that are off limits” list, which instructed Adobe employees not to
cold call Apple employees.55
b. Google

35.

51

I understand that by February 2005 Apple and Google agreed that the two
companies would not “cold call” each other’s employees.56 The agreement
covered all employees.57 Apple placed Google on its “Do Not Call” list and
Google placed Apple on its “Do Not Cold Call” list, both of which instructed
recruiters not to solicit employees from the listed companies.58 On March 13,
2009, the DOJ issued CIDs to Apple and Google.59 I have been asked to
assume the agreement ended on that date.

See 231APPLE002145 (emphasis in original).

52

See 231APPLE002145.

53

See ADOBE_001095.

231APPLE002145 (“Please ensure all your worldwide recruiters know that we are not to solicit any Adobe
employee.”); 231APPLE080776-777 (Apple recruiter tells Adobe applicant that she cannot consider him until
he leaves Adobe, even though “the agreement is not to ‘poach’ candidates, that meaning that if you directly
apply to Apple, there should be no issue.”); ADOBE_007186 (“Apple would be a great target to look into,
unfortunately Bruce and Steve Jobs have a gentleman’s agreement not to poach each other’s talent . . . .”).

54

55

See ADOBE_00421-422.

56

See 231APPLE002140 and 231APPLE073139. See also, GOOG-HIGH TECH-00008002-005 at 004.

57

GOOG-HIGH TECH-00008002-005 at 004.

58

See GOOG-HIGH TECH-00008002-005 and GOOG-HIGH TECH-00023500-601 at 520-521.

59

See 231APPLE003695 and GOOG-HIGH TECH-00024585.
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36.

On February 18, 2005, Intuit Chairman and Apple Board Member Bill Campbell
reached out to Google CEO Eric Schmidt regarding Google’s recruitment of
Apple employees.60 Mr. Campbell reported back to Steve Jobs: “Eric told me
that he got directly involved and firmly stopped all efforts to recruit anyone
from Apple.”61 That same day, Apple’s head of HR Danielle Lambert reported
to her recruiting staff: “Please add Google to your ‘hands-off’ list. We recently
agreed not to recruit from one another so if you hear of any recruiting they are
doing against us, please be sure to let me know. Please also be sure to honor
our side of the deal.”62

37.

Later that year, Arnnon Geshuri, Google’s head of recruiting, was asked to
create a formal “Do Not Cold Call” list regarding companies, including Apple,
that had “special agreements” with Google to eliminate Cold-Calling. The draft
was presented to Google’s Executive Management Group (“EMG”), a
committee consisting of Google’s senior executives, including Eric Schmidt,
Larry Page, Sergey Brin, and Shona Brown (Google’s head of HR). Mr. Schmidt
approved the list.63 Mr. Geshuri added or removed a company from Google’s
Do Not Call when instructed to do so by a member of the EMG.64

38.

Once the EMG approved it, Mr. Geshuri formalized the “Special Agreement
Hiring Policy: Protocol for ‘Do Not Cold Call’ and ‘Sensitive’ Companies,” and
ensured that all of Google’s hundreds of recruiters adhered to its terms.65

60

See 231APPLE002140.

61

See 231APPLE002140.

62

See 231APPLE073139.

See GOOG-HIGH TECH-00007725 (Mr. Geshuri sent the draft “Do Not Call” list to Ms. Brown, who
responded: “I would like to finalize with you Monday AM, and then present in EMG . . . .”; GOOG-HIGH
TECH-00007731 (Mr. Schmidt approved the list on October 4, 2005: “This looks very good.”); Deposition
of Arnnon Geshuri, August 17, 2012 at pp. 161:2-167:8.

63

Deposition of Arnnon Geshuri, August 17, 2012 at p. 172:6-8 (Q: And who would tell you whether to put
a company on or off of the do-not-call list? A: It was usually an EMG member.”)

64

GOOG-HIGH TECH 00008283 and GOOG-HIGH TECH-00008342 (example iterations of the Do Not
Call list); Deposition of Arnnon Geshuri, August 17, 2012 at p. 170:19-22 (“I made sure the team was -- was
definitely aware of this protocol”); Deposition of Arnnon Geshuri, August 17, 2012 at pp. 43:20-44:10 (from

65

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I have reviewed evidence of specific instances in which both firms adhered to
the agreement.66 In one case, compliance meant terminating a Google recruiter
who violated the agreement.67 Google referred to this kind of enforcement as
an “Eric [Schmidt] firedrill.”68
c. Pixar

40.

In April 2007 the directors of human resources for Apple and Pixar agreed to a
Non-Compete Agreement that mirrored the terms of the agreement between
Lucasfilm and Pixar.69 Apple placed Pixar on its “Do Not Call” list, which
instructed recruiters not to solicit employees from the listed companies, and
Pixar instructed its human resource personnel to abide by the agreement.

41.

I understand that historically Pixar and Apple restricted employees from moving
from one company to another during the period of time when Steve Jobs was
an executive of Apple and a direct owner of Pixar. On March 13, 2009, the
DOJ issued a CID to Apple.70 I have been asked to assume the agreement
ended on that date.

42.

Beginning no later than 2004, Pixar sought Steve Jobs’ permission before
making an offer of employment to an Apple employee, regardless of whether

2004 to 2009, Mr. Geshuri grew Google’s recruiting operations from 40 recruiters to 900, which allowed
Google to hire at a rate of “
people a week.”).
66

See 231APPLE002149; GOOG-HIGH TECH-0007574-576.

GOOG-HIGH TECH-00009454; GOOG-HIGH TECH-00000107 (In an email in which Mr. Schmidt
was copied: Mr. Geshuri: “the sourcer who contacted this Apple employee should not have and will be
terminated within the hour. We are scrubbing the sourcer’s records to ensure she did not contact anyone
else.” Ms. Brown: “Appropriate response. Please make a public example of this termination with the group.
Please also make it a very strong part of new hire training for the group. I want it clear that we have a zerotolerance policy for violating our policies. This should (hopefully) prevent future occurrences.”); Deposition
of Arnnon Geshuri, August 17, 2012 at pp. 214:7-215:20.

67

GOOG-HIGH TECH-00023106 and GOOG-HIGH TECH-0024458; Deposition of Arnnon Geshuri,
August 17, 2012 at pp. 255:3-260:14.

68

At the time of these agreements Steve Jobs was the largest shareholder of Walt Disney, to which he had
sold Pixar in 2006 and he sat on Disney’s board of directors. See PIX00003978.

69

70

See 231APPLE003695.
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the Apple employee applied to Pixar without being solicited. For example, on
February 8, 2004, Rob Cook, Pixar’s Vice President of Software Engineering,
wrote to Steve Jobs: “Steve, an Apple employee applied for the job of project
coordinator, which is basically an administrative assistant to our project
managers. . . . Would it be OK for us to make her an offer?” Steve Jobs
responded: “Yea, it’s fine.” Mr. Cook forwarded Steve Jobs’s email to Mr.
Catmull, who responded: “The key is to stay away from the engineers.”71 Ten
days after this exchange, Mr. Catmull emailed Steve Jobs regarding entering into
a no-recruit agreement to eliminate competition with Sony: “our people are
become [sic] really valuable and we need to nip this in the bud.”72 The next
year, in November 2005, Pixar recruiter Howard Look stated that Pixar was
struggling to find candidates, but “of course cannot recruit out of Apple.”73
43.

On April 30, 2007, Apple and Pixar formalized their understanding and
expanded it to all employees with a call between Ms. McAdams of Pixar and
Danielle Lambert, Apple’s head of HR. Apple and Pixar modeled their
agreement on the “gentlemen’s agreement” Pixar had with Lucasfilm. Ms.
McAdams told her recruiting team about the “Apple Gentleman’s agreement”:
“I just got off the phone with Danielle Lambert, and we agreed that effective
now, we’ll follow a gentlemen’s agreement with Apple that is similar to our
Lucasfilm agreement. That is . . . we won’t directly solicit any Apple employee
(including outside recruiters if we use them) . . . Danielle will ask her Recruiting
team to follow the same procedure . . . .”74

44.

After entering into the agreement, senior executives of both Pixar and Apple
monitored compliance and policed violations. For example, Lori McAdams
testified that Steve Jobs got angry if Pixar hired an Apple employee.75 When

71

See PIX00006025.

72

See PIX00006023.

73

See PIX0003600.

74

See PIX00004883; emphasis added; Deposition of Lori McAdams, August 2, 2012 at pp. 182:5-183:9.

75

See Deposition of Lori McAdams, August 2, 2012 at p. 159:4-9.
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asked whether Pixar would consider hiring an Apple employee who had
expressed interest in Pixar, Ed Catmull replied, “[Steve] will want the name of
the guy. My guess is that Steve will approve it if he knows that he is going to
lose him, but we would have to go through the step of Apple knowing what was
happening.”76 To ensure compliance with the agreement, Pixar instructed its
human resources personnel to adhere to the agreement and to preserve
documentary evidence establishing that Pixar had not actively recruited Apple
employees.77 Apple, in turn, placed Pixar on its internal “Do Not Call List,”
which instructed Apple employees not to cold call Pixar employees.78
3. The Google Non-Compete Agreements
a. Apple

45.

Google’s Non-Compete Agreement with Apple is described above.
b. Intel

46.

Effective March 6, 2005, Google and Intel entered into a Non-Compete
Agreement.79 Multiple documents confirm this agreement.80 The agreement
covered all Google and Intel employees. Google placed Intel on its “Do Not
Cold Call” list, which instructed recruiters not to solicit employees from the
listed companies, and Intel instructed its human resource personnel to abide by
the agreement. On March 13, 2009, the DOJ issued a CID to Google.81 I have
been asked to assume the agreement ended on that date.

76

PIX00002210.

77

PIX0003629-630.

78

See 231APPLE042669 and 231APPLE041662.

79

See GOOG-HIGH TECH-00008281-284 at 283.

See 76556DOC000003, 76614DOC010212, 76526DOC000007, 76526DOC000011, and GOOG-HIGH
TECH-00056879.

80

81

See GOOG-HIGH TECH-00024585.
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47.

On April 16, 2007, Intel C.E.O. Paul Otellini wrote to an Intel recruiter, “I have
an unofficial no poaching policy with [Google.]”82 On June 4, 2007, Eric
Schmidt wrote Otellini re “hiring”: “I checked as to our recruiting policy with
Intel. ‘Intel has been listed on the Do Not Call List since the policy was
created. No one in staffing directly calls, networks, or emails into the company
or its subsidiaries looking for talent.’ Hopefully there are no exceptions to this
policy and if you become aware of this please let me know immediately!”83
Otellini forwarded the email to Patty Murray, Intel’s Senior Vice President and
Director of HR: “FYI . . . . Do not fwd.”84

48.

Google’s formal “Do Not Cold Call” list included Intel along with Apple, as
“companies [that] have special agreements with Google,” and states the same
“Effective” date for both Apple and Intel: “March 6, 2005.”85

49.

The agreement was enforced by the chief executives of the two companies.
Intuit’s Chairman, Bill Campbell, was also apparently involved in the agreement
between Google and Intel. For example, in August of 2006, Campbell reached
an agreement with Google’s Jonathon Rosenberg (Google’s Senior Vice
President of Product Management) that Google should impose additional
restrictions beyond no solicitation: they agreed that Google would call Otellini
before making an offer to an Intel employee, regardless of whether the Intel
employee first approached Google.86

82

See 76526DOC000007.

83

See 76614DOC010212.

Two days later, in an email titled “global gentleman agreement with Google,” an Intel recruiter asked
Otellini and another senior executive, “Are either of you aware of any agreement with Google that prohibits
us from recruiting Google’s senior talent?” See 76526DOC000011. Otellini replied, “Let me clarify. We have
nothing signed. We have a handshake ‘no recruit’ between eric and myself. I would not like this broadly
known.” See 76526DOC000011.

84

GOOG-HIGH TECH-00008281-284 at 283; GOOG-HIGH TECH-00056879 (“Since the beginning of
the Do Not Call List, Intel has been listed.”).

85

GOOG-HIGH TECH-00056790 (Rosenberg: “Campbell and I already discussed this [talking to Intel
before making an offer to an Intel employee] and agreed that either way [whether Intel was treated as a “Do
Not Call” company, or a “sensitive” company] I should give a courtesy call to Paul Otellini. I’m meeting with

86

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c. Intuit

50.

In June 2007, Google and Intuit entered into a Non-Compete Agreement
between Google and Intuit.87 The agreement also covered all employees.
Google placed Intuit on its “Do Not Cold Call” list, which instructed recruiters
not to solicit employees from the listed companies, and Intuit instructed its
human resource personnel to abide by the agreement. On March 13, 2009, the
DOJ issued a CID to Google.88 I have been asked to assume the agreement
ended on that date.

51.

On June 6, 2007, Google Recruiting Director Arnnon Geshuri wrote Eric
Schmidt: “During a brief conversation with Shona and Bill Campbell, Bill
requested that Intuit be added fully to the Do Not Call list. Currently, our nonsolicit policy only covers 18 Intuit employees . . . The change to our Do Not
Call policy will make our hands-off approach to Intuit explicit and ensure
clarity.”89 By June 12, 2006, Intuit was added fully to the list.90

52.

I have reviewed specific evidence of enforcement of the agreement, including
enforcement by Campbell himself.91

[the Intel candidate] tomorrow and I will ask him how he wants to handle communication to Intel
management before we even get to the stage of specifically discussing an offer.”).
See GOOG-HIGH TECH-00009764. There is some indication an agreement may have existed earlier. In
May 2006, Google employees discussed possibly contacting a candidate from Intuit, finally deciding that
“would effectively be a cold call, so I’ll ask martha j not to contact him.” GOOG-HIGH TECH-00007696 –
697 at 696.

87

88

See GOOG-HIGH TECH-00024585.

89

GOOG-HIGH TECH-00009764.

GOOG-HIGH TECH-00007715; GOOG-HIGH TECH-00009391 (“please update the DNC list to now
include Intuit 100% do not call.”).

90

GOOG-HIGH TECH-00057458. See also, GOOG-HIGH TECH-00058235 (email from Bill Campbell to
Google HR Director Lazlo Bock asking “Can we please not target Intuit”).
91

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4. Department of Justice Investigation and the End of the
Collusion

53.

On June 3, 2009, the New York Times published an article indicating that the
DOJ had begun an investigation into the Defendants’ hiring practices and the
alleged Non-Compete Agreements in particular.92 I understand that by the end
of March 2009, the DOJ had informed the defendants of the investigation. I
have assumed for this analysis that, as of that date the agreements between the
defendants ceased to have an effect on their recruiting and hiring activities.
C. Named Plaintiffs

54.

As described above, I have been asked to consider the effect of the NonCompete Agreements on the All-Employee Class of salaried employees (and the
Technical Employee Class). The members of each proposed class worked for a
Defendant at a time when that Defendant was a party to at least one such
Agreement (excluding retail employees, corporate officers, members of the
boards of directors, and senior executives).

Helft, Miguel, “Unwritten Code Rules Silicon Valley Hiring,” The New York Times, June 3, 2009,
http://www.nytimes.com/2009/06/04/technology/companies/04trust.html?_r=1.

92

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Figure 3: Class Employee Summary

Defendant

Agreement
Period

Number of
Class Members

Total Class
Compensation

(1)

(2)

(3)

(Dollars)
(4)

Adobe
Apple
Google
Intel
Intuit
Lucasfilm
Pixar

05/05-03/09
02/05-03/09
02/05-03/09
03/05-03/09
06/07-03/09
01/01-03/09
01/01-03/09

7,056

$

3,035,176,142

2,081,658,505

109,048

TOTAL

7,186

$ 52,047,039,447

Note: Columns (3) and (4) are calculated using the Class Periods
described in Paragraphs 8 and 9, above.
Source: Defendants' employee compensation data; SEC filings.
Figure 4: Technical Employee Class Summary

Defendant

Agreement
Period

Number of
Class Members

Total Class
Compensation

(1)

(2)

(3)

(Dollars)
(4)

Adobe
Apple
Google
Intel
Intuit
Lucasfilm
Pixar

05/05-03/09
02/05-03/09
02/05-03/09
03/05-03/09
06/07-03/09
1

3,601

$

1,740,210,006

3,236

1,006,035,578

59,550

$ 32,848,992,686

01/01-03/09
01/01-03/09

TOTAL

Note: Columns (3) and (4) are calculated using the Class Periods
described in Paragraphs 8 and 9, above.
1

Missing job title information for 2005.

Source: Defendants' employee compensation data; SEC filings.

55.

I understand the following named plaintiffs are seeking to serve as class
representatives for the proposed All-Employee Class or Technical Employee
Class :
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a.
b.

Mark Fichtner who worked for Intel as a software engineer from May
of 2008 through May 2011;

c.

Siddharth Hariharan who worked for Lucasfilm as a software engineer
from January 8, 2007 through August 15, 2008;

d.

Brandon Marshall, who worked for Adobe as a software production
quality specialist from July 2006 through December 2006; and

e.

56.

Michael Devine who worked for Adobe from October 2006 through
July 7, 2008 as a computer scientist for Adobe Systems;

Daniel Stover, who worked for Intuit as a Web Marketing
Representative, Web Developer, and Software Engineer from July 2006
through December 2010.

I have summarized the employment histories of these individuals as contained
in Defendants’ data. The employment histories of the five named plaintiffs are
reported in Figure 5.

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Figure 5: Named Plaintiffs’ Employment Histories

Name Plaintiff's Employment Profile Summary
Separation

Base Annual

Supplemental

Name

Year

Employer

Title

Hire Date

Date

Salary

Compensation1

(1)

(2)

(3)

(4)

(5)

(6)

(7)

2006
2007
2008
2009

INTUIT
INTUIT
INTUIT
INTUIT

WEB MARKETING REP 2
WEB DEVELOPER 2
SOFTWARE ENGINEER
SW ENGINEER 2

Brandon Marshall

2006

ADOBE

Mark Fichtner

2001
2002
2003
2004
2005
2006
2008
2009
2010
2011
2006
2007
2008

(Dollars)

Daniel Stover

Michael Devine

Siddharth Hariharan

1

10/30/2006
10/30/2006
10/30/2006
10/30/2006

12/3/2009

75,000
83,500
91,300
94,000

SW PROD QUALITY SPEC 1

7/31/2006

12/9/2006

68,000

5,895

INTEL
INTEL
INTEL
INTEL
INTEL
INTEL
INTEL
INTEL
INTEL
INTEL

SOFTWARE ENGINEER, SR
SOFTWARE ENGINEER, SR
SOFTWARE ENGINEER, SR
SOFTWARE ENGINEER
SOFTWARE ENGINEER
SOFTWARE ENGINEER
SOFTWARE ENGINEER
SOFTWARE ENGINEER
SOFTWARE ENGINEER
SOFTWARE ENGINEER

7/12/1993
7/12/1993
7/12/1993
7/12/1993
7/12/1993
7/12/1993
7/12/1993
7/12/1993
7/12/1993
7/12/1993

6/1/2011

84,250
84,250
84,250
86,782
95,132
100,362
108,000
108,000
110,160
111,290

67,461
40,176
25,101
36,592
38,299
48,189
14,013
30,501
42,078
35,973

ADOBE
ADOBE
ADOBE

COMPUTER SCIENTIST, SW DEV 4 9/25/2006
COMPUTER SCIENTIST, SW DEV 4 9/25/2006
COMPUTER SCIENTIST, SW DEV 4 9/25/2006

7/8/2008

110,000
113,135
118,226

21,222
33,405
3,445

8/15/2008

85,000
88,335

17,000
-

2007 LUCASFILM SOFTWARE ENGINEER
2008 LUCASFILM SOFTWARE ENGINEER

1/8/2007
1/8/2007

$

(8)

11/8/2006

$

4,129
19,765
83,877
38,553

Supplemental compensation includes bonus, overtime compensation, options values and restricted stock values
Source: Defendants' employee compensation data; SEC filings

D. Background on Defendants’ Recruiting and Hiring Practices

57.

Defendants classified potential job candidates as either “passive” or “active.”93
Active candidates were searching for employment and could be expected to
discover posted opportunities (e.g., an active candidate might apply through the
company’s website). Passive candidates were not searching for new

76550DOC000014-095 at 024, LUCAS00013673-703 at 683, GOOG-HIGH TECH-00039446-581 at 451
and 76566DOC000005-026 at 010.

93

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opportunities but might be interested if the candidate learned of a good job
opportunity.94
58.

59.

Many companies, including the Defendants, actively pursue Cold-Calling
strategies. For example, the Competitive Intelligence Group at Google created a
“Product Matrix,” profiling competitors and highlighting areas in which these
competitors have employees that would be useful to Google, naming ColdCalling as a method to “strategically reach, engage and close the best talent in
the world.”97

60.

Intuit recruiters were expected to use Cold-Calling as a recruiting technique.98
Google identified Cold-Calling as an activity of its recruiters (“sourcers”).99

61.

94

The Defendants used several types of methods for uncovering (or “sourcing”95)
passive candidates, including referrals.96 The initial contact to a passive
candidate is called “Cold-Calling.”

In preparation for Cold-Calling, the Defendants profiled their competitors,
looking for job categories and titles that corresponded to the positions to be
filled.100 Cold-Calling recruiters would then approach employees who fit into
those categories to determine their potential interest, which could be followed

Deposition of Donna Morris, August 21, 2012 at pp. 106:22-107:19 and Exhibit 212.

Intel defined sourcing as, “the identification and uncovering of candidates through proactive recruiting
techniques.” Sourcing channels included complex internet searches, networking, job fairs and searching
through previous applications. Companies can also use external recruiting agencies to find potential
candidates 76550DOC000014-095 at 19 and 23 and 76545DOC000021-051 at 23.

95

96

76550DOC000014-095 at 023 and LUCAS00004690 at 692-694.

97

GOOG-HIGH-TECH-00054775.

98

See INTUIT_001661-664 at 663.

99

See GOOG-HIGH TECH-00007950-973 at 971.

100

See GOOG-HIGH-TECH-00055116 and GOOG-HIGH-TECH-00055413-414.
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

IV.

Some employers may have failed to anticipate improvements in market
conditions and may have left valuable employees with compensation
packages far below what they could get elsewhere. This can create
clusters of low-hanging fruit.

Common Evidence and Analysis Are Capable of Showing that
the Non-Compete Agreements Artificially Reduced the
Compensation of Defendants’ Salaried Employees

63.

Methods and evidence, common to each Class as a whole, are capable of
demonstrating that the Non-Compete Agreements reduced the compensation
of All-Employee Class and Technical Employee Class members employed by
the Defendants. This Class-wide proof of impact comes in two steps. First,
there is abundant evidence, common to All-Employee Class and Technical
Employee Class members, capable of showing that the Non-Compete
Agreement suppressed the compensation of the members of the All-Employee
Class and Technical Employee Class, generally. Such Class-wide methods and
evidence include, without limitation: (a) standard economic theory regarding the
effects of information asymmetries on labor market contracts, which work to
the disadvantage of the less informed party, and (b) standard economic theory
regarding the effects of movement of employees between firms enticed by
better compensation, and the consequent interest of firms in peremptory
increases in compensation to employees when poaching by key rivals occurs
regularly; (c) multiple regression analyses, using extensive compensation data,
showing that compensation was reduced for Class and Technical Employee
Class members; and (d) documentary evidence, including documents from
Defendants’ own files, describing, e.g., the Non-Compete Agreements,
Defendants’ enforcement of those Agreements, the importance of the
Agreements, and the effects of poaching on movement between firms and
compensation.

64.

I have found further that Class-wide methods and evidence are capable of
demonstrating that the Non-Compete Agreements suppressed the
compensation of all or virtually all members of the All-Employee Class and
Technical Employee Class. In addition to the Class-wide evidence described in
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the previous paragraph, such common proof that the effects of the NonCompete Agreements was broadly felt also includes (a) economic theory
regarding the interest of firms in fostering a concept known in the economic
literature as “internal equity,” such that compensation tracks the success of the
firm’s most highly compensated employees; (b) additional evidence that
compensation of employees tended to move together over time, such that the
effects of Non-Compete Agreements are likely to be broadly felt; and (c)
evidence from Defendants’ own files showing their respective concerns about
preserving internal equity, as well as other documentary evidence, when
Agreements were not in place, that some Defendants responded to periods of
intense poaching by close rivals with across the board salary increases to all
employees.
65.

I describe these methods and evidence in greater detail below.
A. Class-wide Evidence is Capable of Showing that the Non-

Compete Agreements Suppressed Compensation Generally

1. Economic Theory Offers a Classwide Basis for Linking Non-

Compete Agreements to Suppressed Compensation Incurred
by Members of the All-Employee Class and Technical Employee
Class

66.

There are three economic frameworks106 that are particularly useful for
evaluating the likely impact on employees of illegal agreements to suppress
Cold-Calling. These frameworks--each well-accepted in the economics
literature--explain various mechanisms by which anti-Cold-Calling agreements
can suppress worker compensation generally.

67.

The frameworks for considering the effect of the alleged non-compete
agreements discussed below are (1) price discovery, (2) worker compensation
equity and (3) profit-sharing. Each framework has different implications
regarding the way in which the effects are spread across firms, across job

“Frameworks” refers to general views regarding how labor markets function and “model” refers to a
specific example of a framework. A framework is usually communicated in words, while a model is expressed
with either graphs or mathematical formulae.
106

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categories within firms and across time. The frameworks are not mutually
exclusive in that effects of the Agreements can arise through multiple channels.
In this section, I will focus here on frameworks “(1)” and “(3)” as they pertain
mainly to the general linkage between the Non-Compete Agreements and
suppressed compensation. I will elaborate on framework “(2)” regarding
internal equity when I discuss the Class-wide evidence capable of showing
widespread harm to the either class later in my Report.
68.

For all three frameworks, Cold-Calling is part of the information gathering that
reveals the nature of outside opportunities both to workers and to employers.
Anti-Cold-Calling agreements suppress compensation by limiting this flow of
information about attractive outside opportunities.

69.

Cold-Calling is an especially important source of information about outside
opportunities under two circumstances: (a) uneven growth (i.e., firms are
growing at different rates), which requires reallocation of the workforce in favor
of the firms which can offer workers the best contracts, and (b) even growth
(firms are growing at a generally equal rate), which doesn’t necessitate any
reallocation of the workforce but which creates greater competition for the
scarce workforce.

70.

Under either condition, Cold-Calling contributes to economic efficiency. With
uneven growth, Cold-Calling helps to assure that workers are assigned to their
most valued tasks. With even growth, Cold-Calling helps to assure that
workers receive a proper scarcity premium which signals to other workers which
skills are most needed. In both circumstances, economic theory predicts that
agreements restricting Cold-Calling would suppress worker compensation for all
or nearly all employees of the Defendants who agreed to them.
a. Price Discovery Framework

71.

The market equilibrium models that economists often use presume that market
forces are powerful enough and work rapidly enough that virtually all
transactions occur at approximately the same price – the “market price” which
equilibrates supply and demand. In reality, in the face of changed market
conditions, the actual transactions’ prices can deviate from the market
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equilibrium sometimes by large amounts for long periods of time. The process
by which actual transactions prices move to market equilibrium values is called
“market price discovery.”
72.

The speed at which the price discovery process operates is determined by the
frequency at which buyers and sellers get together to haggle over the price, and
by the rate at which information about the outcomes of those bargains,
consummated or not, is dispersed among other potential buyers and sellers.
Non-Compete Agreements that limit the bargaining between employers and
employees thus slow down the price discovery process and affect each and
every labor contract in the markets.

73.

In some settings the price discovery process is so slow and imperfect that the
concept of a “market equilibrium” is of limited value for understanding the
sequence of actual transactions.107 Labor markets that involve infrequent
bargains and limited information flows can have very sluggish price discovery.
High transaction costs and weak information flows create very illiquid labor
services which are transferred via bilateral bargains, not via markets.108 The
expensive and time-consuming task of uncovering and valuing the unique
features of workers slows down the price discovery process and allows many
transactions to occur at prices far from market equilibrium levels.

74.

High-tech jobs involve high costs for transactions including time, money and
personal dislocation. These high transaction costs make transactions very
infrequent and limit the number of workers actively seeking new employers.

75.

The labor market also has weak information flows about specific jobs.
Employees may rely mostly on “water-cooler talk” perhaps supplemented by
Internet sources. Employers, on the other hand, often hire private consulting
firms to provide aggregated information about “market” compensation. For

Stiglitz, Joseph, “Information and the Change in the Paradigm in Economics,” The American Economic
Review, Vol.92, No. 3 (June 2002), pp. 460-501.
107

For related effects in a financial context, see e.g., Green, Richard C., Dan Li and Norman Schürhoff,
“Price Discovery in Illiquid Markets: Do Financial Asset Prices Rise Faster Than They Fall?,” Journal of
Finance, Volume 65, Issue 5, pp. 1669–1702, October 2010.
108

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employees, Cold-Calling is an important channel of information about outside
opportunities. Absent Cold-Calling, many labor contracts are negotiated in
unequal bargains between informed employers and uninformed employees.
76.

Agreements that reduce the number of bilateral bargains further slow the price
discovery process and affect the whole sequence of actual transactions.109 NonCompete agreements do not change the value of the work; they only help
employers keep more of that value.
b. Relationship Framework: Firm-Specific Assets

77.

Net revenues of high-tech intellectual service firms accrue to one of the two
assets that drive value: the “brand” (the firm) or the workers. The division of
the net revenues between the firm and the workers is determined by outside
competition for workers, which pressures firms to pay their workers at least as
much as the best outside offer.110

78.

When firm-specific knowledge assets reside within the brains of workers, the
movement of workers between firms is a form of “creative destruction”
meaning that the increased value of the worker at the new job is offset by
destruction of value at the old. This is economically inefficient unless the value
of the asset created exceeds the value of the asset destroyed. If neither party to
the new employment contract is incented to worry about the destruction, there
will be too much destruction, the consequence of which is too little creation. A
new employer is unconcerned about the “destruction” of the previous
employer’s asset, or likes it if it impairs a competitor. It is therefore essential for
firms to form relationships that make workers sensitive to the asset destruction
that would occur if they switched employees. This can be done by making them
joint owners of the intellectual assets of the firm, through stock option plans

See Tappata, Mariano, “Rockets and Feathers Understanding Asymmetric Pricing,” UCLA Job Market
Paper, January 2006 and Yang, Huanxing and Ye, Lixin, “Search with learning: understanding asymmetric
price adjustments,” Ohio State University, August 2006.
109

GOOG-HIGH-TECH-00193377-382, GOOG-HIGH TECH-00038103-128 at 125, PIX00000038-039
and LUCAS00004446-452 at 451-452.

110

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and restricted stock grants. These plans can help limit movement of critical
workers.
79.

If firms have not created adequate incentives to assure worker loyalty, ColdCalling can seriously threaten loss of the critical intellectual assets. In periods
when demand for the critical workforce is weak, firms may feel little threat of
loss of workers, and may let grants of stock options and restricted stocks recede.
Firms may be surprised when the market starts to heat up again and they start to
lose critical workers. A legal countermeasure to limit loss of the critical workers
would be increased use of stock options and restricted stock grants.
Management which prefers not to share ownership with their workforce may
instead choose the countermeasure of anti-Cold-Calling agreements, even if it
may be illegal.

80.

Economic theory therefore predicts that agreements such as the Non-Compete
Agreements artificially suppress employee compensation on a widespread basis.
Furthermore, evidence common to all potential class members in this case can
be used to confirm this predicted effect.
2. Defendants’ Internal Documents Provide Additional Class-wide
Evidence Capable of Showing that the Non-Compete
Agreements Artificially Suppressed Compensation

81.

The Defendants’ internal documents can be used to confirm that company-wide
prohibitions on recruiting would tend to artificially suppress the compensation
of the members of the All-Employee Class and Technical Employee Class.

82.

Documents reveal that the defendants would otherwise have been competing
for employees.111 In the absence of these agreements, Defendants would have
cold called one another’s employees.112

See e.g., ADOBE_005950 - 967 at 966 (“list of [nine] companies Adobe’s Board of Directors benchmarks
against from a compensation standpoint” include Google, Apple, and Intel; with regard to benefits, Adobe is
in a “six horse race” with Google, Apple, Intel and two other companies); PIX00006023 (“Our people are
becoming really desirable and we need to nip this in the bud.”); GOOG-HIGH TECH-00023206-212 at 209
(“The Recruiting Wars: How To Beat Google To Tech Talent”).

111

112

See GOOG-HIGH TECH-00056840 (“Cold-Calling into companies to recruit is to be expected unless
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83.

Prior to the Agreements the Defendants were concerned with successful
poaching by other firms—and particularly other Defendants. In an email
discussing Adobe’s policy toward Apple under the Agreements, Adobe’s Bruce
Chizen wrote, “… Knowing Steve, he will go after some of our top Mac talent
like Chris Cox and he will do it in a way in which they will be enticed to come
(extraordinary packages and Steve wooing).”113

84.

Thus Defendants recognized that Cold-Calling and other forms of poaching had
the potential to drive up the cost of specific employees. They also recognized
that the effects of poaching would extend well beyond the employees directly
approached by a cold-call. Pixar’s top executive Ed Catmull noted, “we learned
that the company that Zemeckis is setting up in San Rafael has hired several
people away from Dreamworks at a substantial salary increase… every time a
studio tries to grow rapidly… it seriously messes up the pay structure.”114

they’re on our ‘don’t call’ list.”); GOOG-HIGH TECH-00053679-681 at 680 (“Over the 8 years of my
executive search experience, I’ve worked with hundreds of clients. And for every search assignment, the first
thing we do is to target the direct competitors of the respective clients.”); ADOBE_001092-093 at 092
(“Apple would be a great target to look into. Unfortunately, Bruce and Steve Jobs have a gentleman’s
agreement not to poach each other’s talent.”); GOOG-HIGH TECH-00023132 (as soon as eBay and PayPal
were removed from Google’s Do Not Call list, “staffing is ready to pursue several hundred leads and
candidates”); 76506DOC000773-990 at 845 (in an Intel presentation titled “Intel’s Complete Guide to
Sourcing,” on the slide regarding “Cold-Calling”: “Calling candidates is one of the most efficient and effective
was to recruit.”); LUCAS00005403-446 at 405 (“The Recruiting Strategy for LucasArts for the next 2-3 years
must be focused on the passive candidate.”); ADOBE_002773-788 at 775 (Adobe presentation regarding
sourcing focused on “passive” candidates:” “top performers tend to be entrenched, ‘heads down.’”); GOOGHIGH TECH-00024149-218 at 152 (in a Google “Sourcing Diagnostic”: “Passive sourcing will play an
increasingly large role in recruiting as we move forward as a company.”); and GOOG-HIGH TECH00007729 (a year before entering into its first no-solicit agreement with Apple, Shona Brown wrote: “We
have historically always allowed recruiters to find talent wherever it is – even when it is with key partners . . .
or sensitive competitors . . . Which is the right answer.”). In response to one of Mr. Geshuri’s “periodic
reminders” to his recruiters regarding the “Do Not Call list,” a Google recruiter remarked in frustration: “I
guess the candidates I have been sourcing from Burger King, Jiffy Lube and Der Wienerschnitzel are still fair
game.” See GOOG-HIGH TECH-00008249 and Deposition of Arnnon Geshuri, August 17, 2012 at pp.
262:4-264:13.
113

ADOBE_001096-001097 at 097.

PIX00000229. Also noting, “I know that Zemeckis’ company will not target Pixar, however, by offering
higher salaries to grow at the rate they desire, people will hear about it and leave. We have avoided wars up in
Northern California because all of the companies up her – Pixar, ILM, Dreamworks, and a couple of smaller
places- have conscientiously avoided raiding each other.”
114

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85.

These documents indicate defendants saw a significant potential benefit from
reducing or limiting this competition for employees (e.g., relating to the
perceived impact of actual and potential poaching on compensation).

86.

In contexts not covered by the non-compete agreements, the defendants
regularly and openly used Cold-Calling to find new employees. For example, in
an Intuit email, Intuit officials looking to fill a position discuss “good target
companies to go after.”115

87.

Even during the period of agreements, the Defendants considered Cold-Calling
a useful tool in recruiting employees from companies other than those
participating in the Agreements.116

88.

In November 2007, after agreement between Adobe and Apple was officially
terminated, a Hiring Analysis from Adobe’s Competitive Intelligence Group
reported, “recruiting and retaining top talent will likely be more competitive to
the extent that the high tech sector remains economically healthy… As
Microsoft, Google and Apple dial-up the volume on attracting Adobe resources,
what changes or new approaches would assist Adobe in retaining top talent?”117
3. Analysis of Defendants’ Compensation Data Is Additional

Class-wide Evidence Capable of Showing that the
Compensation of All-Employee Class and Technical Employee
Class Members Was Suppressed by the Non-Competition
Agreements

89.

90.

115

My analysis of Defendants’ compensation data is additional common evidence
capable of showing that restricting Cold-Calling would artificially suppress
employee compensation by impeding the price discovery process.
Compensation of new recruits compared with existing employees can reveal the
price discovery process at work. If compensation of current workers were close

INTUIT_002372.

See e.g., PIX00003610-00003611 at 610; GOOG-HIGH TECH-00008233 (6/21/2008 email’ “actively
recruiting key Yahoo! Employees was a recommended course of action given current industry dynamics”).
116

117

ADOBE_004964 – 004997 at 975.
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to a “market equilibrium” level, the new recruits would be paid similarly to
existing employees, net of “moving costs.” If the market value of the workers
were then to increase, that would set in motion a price discovery process during
which new recruits were paid distinctly more than current employees with
similar skills and experience. In the early phases of the price discovery process,
the salaries of these new recruits might also be below equilibrium levels, and the
compensation packages offered new recruits can improve over time in search of
the higher equilibrium. As firms become aware of the increased external
competition, compensation packages of current employees may be improved to
bring them more in line with outside opportunities. It can take considerable
time for this complicated price discovery process to find a new equilibrium in
which new recruits and existing employees are paid about the same. It can take
much longer if information about superior opportunities is suppressed by NonCompete Agreements.
91.

Thus, a symptom of price discovery at work would be better compensation
packages for those who moved between Defendants than for those who stayed.
In Figure 6 and Figure 7 below I compare on a year-by-year basis the percent
changes in compensation of the movers versus the stayers--those who moved
between Defendants and those who didn’t. As Figure 6 shows, the increase in
base salary of the movers was almost always above the stayers. But in 2006, the
movers received almost 16 percent increases in base salary compared with about
5 percent for the stayers. That gap is a symptom of the price discovery process
at work in search of higher wages, a process that was the apparent target of the
anti-Cold-Calling agreements put in place at that time.

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95.

Cold-Calling is likely to be most active during the industry expansions in which
the industry overall is enjoying rapid growth and facing supply constraints of
workers at every level of experience.

96.

During much of the class period, the Defendants collectively were experiencing
a phase of rapid economic expansion and exhibited strong financial
performance. Google grew from a startup with just eight employees in 1999 to a
publicly traded company with over 30,000 employees in 2012. Apple tripled its
revenue between 2005 and 2010 with widespread success of its consumer
electronic products including the iPhone, iPod Touch and iPad. Adobe
generated about $980 million in owner earnings in 2007, up from $580 million
and $540 million in 2006 and 2005, respectively.118 Between 1998 and 2011,
Pixar released 11 blockbuster feature films resulting in more than $6 billion at
the worldwide box office.119


97.

‘It’s surreal in the Valley, compared to the rest of the country,’ said
Harj Taggar, a partner at startup incubator Y Combinator [in 2011].
‘It’s so hard to hire people here – and salaries for engineers are going
through the roof.’120

Equity distributions are especially important for retaining critical employees
during expansions when many firms are actively recruiting talent. The normal
vesting periods of three or four years align compensation with stock market
performance, and create a loss for workers who leave. This makes them share
in the loss of firm-specific knowledge assets that their departure creates. Equity
grants and profit-sharing are used to promote employee loyalty and retain firmspecific knowledge assets,121 as that term is understood in economic literature.

Ponzio, Joe, “With Adobe, Growth and Value are Joined at the Hip,” Seeking Alpha, February 4, 2008,
http://seekingalpha.com/article/62919-with-adobe-growth-and-value-are-joined-at-the-hip.
118

Pixar, “Corporate Overview,” http://www.pixar.com/companyinfo/about_us/overview.htm [Accessed
04/06/2012].
119

Wagner, Alex, “As National Employment Stalls, Job Market Booms In Silicon Valley,” Huffington Post,
July 8, 2011.

120

121

See e.g., Grant, R. M., “Toward a Knowledge-Based Theory of the Firm,” Strategic Management Journal, 17
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Revenues are required to support salary increases, and a surge in profits over
time is likely to be spent partly on raising wages and retaining key employees.
Figure 9 illustrates the growth in revenue per worker at Apple and the average
total compensation per worker. Apple revenues per worker doubled from
around $500,000 in 2001 around $1,000,000 in 2005, but
The
Apple Non-Compete Agreements went into effect when Apple revenues surged,
and when the risk of sharing the gains with the workforce was a threat to the
firms’ high levels of profits.
Figure 9: Growth of Apple's Revenue and Compensation

Apple's Revenue and Average Total Compensation Per Employee

Source: Defendants' employee compensation data; SEC Filings.

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Following a period of industry weakness122 in which the forces for increases in
compensation were weak, normal market forces in 2005 and subsequently
would have resulted in a distribution of some of that net revenue to the
workforce. It is not surprising that the anti-Cold-Calling agreements were put in
place in 2005 and subsequently, when employment and revenues began to grow
substantially and when competition for critical workers was likely more intense.
The agreements were formed when they were most likely to be effective and to
matter.

B. Classwide Evidence is Capable of Showing that the Non-Compete
Agreements Suppressed the Compensation of All or Nearly All
Members of the All-Employee Class and Technical Employee
Class

101.

Common evidence can likewise be used to demonstrate that the artificial
suppression of employee compensation would have been widespread, extending
to all or nearly all members of the All-Employee Class and Technical Employee
Class. This Class-wide evidence includes all of the evidence set forth above
capable of showing the link between the Non-Compete Agreements and
suppressed compensation plus three additional categories of evidence: (a)
economic theory implicating firm incentives to maintain worker loyalty by
adhering to principles of internal equity through a rigid salary structure; (b)
Defendants’ documents reflecting their recognition and implementation of
internal equity principles and more specifically demonstrating the broad effects
on compensation of the Non-Compete Agreements; and (c) multiple regression
analyses capable of showing both that compensation of All-Employee Class and
Technical Employee Class members is governed largely by common factors and
that Defendants maintained rigid salary structures such that one would expect
Non-Compete Agreements to have widespread effects on compensation of AllEmployee Class and Technical Employee Class members.

Luo, Tian and Mann, Amar, “Crash and Reboot: Silicon Valley high-tech employment and wages, 200008,” Monthly Labor Review, January 2010, p.61-65 and NOVA Workforce Board, “Silicon Valley in
Transition,” July 2011.
122

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102.

One key economic framework (introduced above) is built on the concept of
firms’ incentives to maintain and promote worker loyalty. Although economists
often refer to the labor “market,” most labor services are mediated not by
commodity markets but by committed long-term relationships built on trust and
understanding and mutual interests. If it were literally a commodity market the
compensation paid to any particular employee would have to be both the
highest that the employee could find and also the lowest that the employer
could find at any particular point in time. If workers were commodities, every
small change to external or internal conditions would lead to recontracting,
separation, or termination. This would create enormous uncertainty and
disruption and insecurity for employer and employee. Both sides of the bargain
thus seek ways to turn the market transaction into a long-term relationship. A
secure long-term relationship can come either from commitment (emotional or
financial) to the mission of the organization, or from jointly owned firm-specific
assets.123

103.

Firms attempt to create loyalty by getting buy-in to the firm’s mission and by
making the place of work as appealing as possible.124 If these intangibles are
insufficient, firms also have employee stock options (ESOPs) that give
employees a stake in their firm.125

104.

One foundation of employee loyalty is a feeling of fairness that can translate
into a sharing of the rewards with more equality than a market might otherwise
produce. “Equitable” compensation practices spread wage increases or
reductions across broad categories of workers.126 This implies that when

Becker, Gary, “Nobel Lecture: The Economic Way of Looking at Behavior,” The Journal of Political Economy,
Vol. 101, No.3 (June 1993), pp. 385-409.
123

124

See GOOG-HIGH TECH-00038364-395 at 368-369.

125 Oyer, Paul and Schaefer, Scott, “Why Do Some Firms Give Stock Options To All Employees?: An
Empirical Examination of Alternative Theories,” March 26, 2003.

See e.g., Rees (1993) who describes the role of demand and the impact of market forces on salary
structures of university faculty. (Rees, A. "The Role of Fairness in Wage Determination," Journal of Labor
Economics, 1993, Vol. 11, No. 1, pt. 1.) See also, Mas, “Pay, Reference Points, and Police Performance,” The
Quarterly Journal of Economics, August 2006.
126

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outside opportunities put pressure at one point in the wage structure calling for
higher wages for a few, firms tend to maintain the overall firm wage structure,
rewarding everyone for the improved outside opportunities of some workers.127
105.

To maintain loyalty, it is usually better for a firm to anticipate rather than to
react to outside opportunities, since if a worker were to move to another firm at
a much higher level of compensation, coworkers left behind might feel they
have not been fairly compensated. That can have an adverse effect on worker
loyalty, reducing productivity and increasing interest in employment elsewhere.
To avoid this reduction in loyalty in the face of competition, firms may make
preemptive improvements in their compensation packages.128

106.

As discussed throughout this Report, Class-wide evidence is capable of showing
that Cold-Calling--as well as just the threat of Cold-Calling--puts upward
pressure on compensation. Economic theory describes factors that drive firms,
like the Defendants, toward equitable pay practices that would be expected to
spread the impact of an agreement to suppress Cold-Calling across all or almost
all workers in a firm. Non-compete agreements allow firms to be more relaxed
in maintaining competitive compensation packages because such agreements 1)
suppress competition directly; 2) reduce the risk of employees becoming aware
of pay practices elsewhere; and 3) otherwise eliminate competition for “passive”
employees.

127 Concerns about fairness are observed within the defendants and in public discussions relating to salaries at
firms like the defendants. See e.g., 76512DOC000638-677 at 644 and 656-658 (“Use benchmark salary
surveys to create criteria on which to evaluate jobs across Intel… supports consistence and equity within and
across business groups.”). See also, ADOBE_008047-049 at 047 and GOOG-HIGH-TECH-00193377-382
at 380-381.
128

See e.g., GOOG-HIGH-TECH-00194945 –946.
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bonus of $1,000 for every salaried employee.142 Google referred to this project
as the “Big Bang,” and discussed it extensively beforehand with Intuit’s Bill
Campbell and Intel’s Paul Otellini.143 These discussions provide a powerful
illustration of the common impact of Defendants’ Agreements.
111.

112.

This is an illustration of all three frameworks: (1) Price Discovery; (2) Equity
and Loyalty; and (3) Firm-Specific Assets.

113.

First, when employees discover information regarding their labor’s value by
receiving an offer from a competing employer, those employees use that
information to negotiate higher salaries at their current employer, and so on, in
an iterative process.

114.

142

On October 8, 2010, Jonathan Rosenberg emailed Google’s senior executives
(and Bill Campbell) summarizing concerns from the “broader population” at
Google regarding Google’s counteroffer strategy. Employees who heard about
other “Googlers” receiving counteroffers were upset: “It’s impossible to keep
something like this a secret. The people getting counter offers talk, not just to
Googlers and Ex-Googlers, but also to the competitors where they received
their offers (in the hopes of improving them), and those competitors talk too,
using it as a tool to recruit more Googlers.”144 “And for the time that the
person remains, there will be serious resentment among his/her peers for what
seems like an unfair jump.”145

Second, those individuals tell others at their employer, who then “resent[]” the
perceived “unfair jump” in pay, increasing pressure to match compensation

GOOG-HIGH-TECH-00193377-382 at 380.

143 See GOOG-HIGH-TECH-00195005 – 007, GOOG-HIGH-TECH-00196108, GOOG-HIGH-TECH00196687, GOOG-HIGH-TECH-00196689, and GOOG-HIGH-TECH-00194945 –946.
144

INTUIT_039098-100 at 098.

145

INTUIT_039098-100 at 098. See also, GOOG-HIGH-TECH-00194721-722.
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increases broadly.146 This is often experienced in emotional terms: “it feels like
my loyalty is being punished.”147
115.

Third,
148

116.

Alan Eustace, a Senior VP of Google, confirmed these frameworks in the same
document (again, in an email also sent to Bill Campbell): “every time an
employee has a better offer, a company is forced to decide how badly they want
the employee, and what they are ultimately worth. . . . You can’t afford to be a
rich target for other companies.”149

117.

Eustace also explained why many employee candidates will not learn “what they
are ultimately worth” without Cold-Calling by a competing company: actively
seeking out such offers and using them to negotiate for higher compensation “is
a high risk strategy” that “seriously questions your loyalty and character, which
could have long-term consequences to your career that offset any financial
gain.”150 The “right approach” to respond to such recruiting efforts by a labor
market competitor “is to not deal with these situations as one-off’s but have a
systematic approach to compensation that makes it very difficult for anyone to
get a better offer.”151

118.

Google’s announcement did not escape the attention of other Defendants.
First, the same executives at Intuit and Intel who entered into the Agreements

146

See INTUIT_039098-100 at 099.

147

INTUIT_039098-100 at 099.

148

INTUIT_039098-100 at 099.

149

INTUIT_039098-100 at 098.

150

INTUIT_039098-100 at 098.

151

INTUIT_039098-100 at 098.
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with Google were sent them directly.152 Other Defendants paid close attention
as well.153
119.

155

2. Econometric and Statistical Analysis of Defendants’

Compensation Data Is Also Capable of Demonstrating That
the Compensation Suppressing Effects of the Non-Compete
Agreements Would Be Broadly Experienced By Members of
the All-Employee Class and Technical Employee Class

120.

A firm’s commitment to principles of “internal equity” is evidenced by the
imposition and maintenance of a somewhat rigid salary structure. What that
means is that Cold-Calling and related practices would be expected to increase
compensation across the board rather than be narrowly focused on the skills
that are most in demand at any point in time.156 As a result, analysis of the
application of standard economic labor theory to this case constitutes common
evidence bolstering Plaintiffs’ proof that the Non-Compete Agreements would
broadly affect members of the All-Employee Class and Technical Employee
Class. Moreover, economic analysis of Defendants’ salary structures and
compensation data reveal that each Defendant had a rigid salary structure,

152 See, e.g., INTUIT_039098. (Campbell); 76616DOC005974 and “Google,Board of Directors,”
http://investor.google.com/corporate/board-of-directors.html (Paul Otellini at Intel, who was a Google
Board Member throughout the conspiracy period).

See, e.g., ADOBE_025894-898 at 898 (internal discussion in which Adobe considers whether its
employees will want a raise similar to the one Google announced).
153

154See
155

GOOG-HIGH TECH-00193377-382.

See GOOG-HIGH-TECH-00193406-411 at 406
.”).

See eg. GOOG-HIGH TECH-00042588-640 at 633 (Talking about the equity program, “In special cases
and with VP approval, we can exceed target if supported by sound business rationale. In practice, we rarely
deviate from the guidelines given our philosophy around internal equity.”).
156

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where compensation of employees within specific positions and within each
company tended to move together over time through the relevant periods.
121.

The Class-wide evidence I have reviewed and analyzed shows that Defendants
had highly structured compensation systems built on a two dimensional matrix
with several grades and many titles. In many firms, compensation is first and
foremost linked to the grades, each of which encompasses diverse kinds of
activities which nonetheless receive roughly the same level of compensation.157
For example, Defendants Adobe, Apple, Google, Intel, and Intuit used grades
explicitly and Defendants Pixar and Lucasfilm may have done so as well (though
their data in this regard was unclear at the time of this Report). The titles
identify specific activities and defined career paths, as in Software Engineer Step
1, Software Engineer Step 2, and so on.

122.

Typically, high level management established ranges of salaries for grades and
titles which left relatively little scope for individual variation.158 Defendants
established and regularly updated compensation levels with the following aims:
a.
b.

Providing specific relative compensation levels for employees in
different, hierarchically ordered, employment categories, or “salary
grades,”160

c.

Retaining employees,161 and

d.

157

Providing similar compensation for all employees in the same
employment category,159

Maintaining employee productivity and contentment.

See e.g., 76512DOC000638-677 at 643 and 656-660.

See e.g., 76512DOC000638-677 at 644 (“Use benchmark salary surveys to create criteria on which to
evaluate jobs across Intel”) and GOOG-HIGH TECH-00042588-640 at 612 and 632.
158

159

PIX00006026-6036 at 034 and GOOG-HIGH TECH-00042588-640 at 643.

See e.g., 76512DOC000638-677 at 671 (“
HIGH TECH-00028981- 9027 at 9007.
160

161

”). See also, GOOG-

GOOG-HIGH-TECH-00036781-839 at 785.
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loss of employees to Facebook (described above). The ten percent increase in
base salary across the board was said to “attract new recruits and preempt
defections.”166
“Reporting from San Francisco — Google Inc.'s
decision to give all of its 23,300 employees a 10% pay
raise next year — and a $1,000 bonus to boot — is just
the latest volley in what has become a full-fledged war
for top Silicon Valley talent.”167
126.

All Defendants offered stock grants or options, and/or bonuses. While inequity
in this form of compensation could offset pay equity in base compensation,
stock options and bonuses may be calculated formulaically based on individual
and company performance in a way that maintains an equitable total
compensation structure.168 Indeed, stocks or bonuses were granted to the
majority of employees at all of the Defendants. As shown in Figure 10, 93
percent of the employee-year169 compensation records included these salary
supplements.

Amir Efrati and Pui-Wing Tam "Google Battles to Keep Talent" Wall Street Journal, November 11, 2010,
http://online.wsj.com/article/SB10001424052748704804504575606871487743724.html

166

167

Guynn, Jessica, “War heats up for top Silicon Valley talent,” Los Angeles Times, November 10, 2010.

See e.g., 76512DOC000638-677 at 668 (“Option run rates typically non-negotiable”). See also,
76512DOC000638-677 at 644, and 656-667.

168

An employee employed in December of a particular year. An employee of a firm for five years (each of
which he was present for December), would have five employee-years.
169

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Figure 10: Use of Supplemental Compensation was Widespread

Fraction of Employee-years with Bonus or Equity Grants
Employer
(1)

Mean
(2)

Number of
Observations
(3)

Adobe
Apple
Google
Intel
Intuit
Lucasfilm
Pixar

0.84

50,862

0.88
0.51
0.74

63,700
9,118
12,654

All

0.93

985,428

Source: Defendants' employee compensation data.

127.

Evidence of the structure of compensation in each of ten years from 2001 to
2011 is reported in the ten regression equations in Figure 11 below.

128.

Each equation explains the total compensation inclusive of stock grants of each
salaried employee in terms of a number of basic observable employee
characteristics such as age, number of months in the company, gender, location,
title, and employer.170 What these analyses show is that about 90 percent of the
variability in a class member’s compensation can be explained by these
variables.171 This and the additional fact that the coefficients in these
regressions vary slowly over time (meaning the role played by these factors is

170 These types of regressions can be found in many academic studies of wage structure. See e.g., MenezesFilho, N. A., Muendler, M., and Garey Ramney. "The Structure of Worker Compensation in Brazil, With A
Comparison To France And The United States." The Review of Economics and Statistics, May 2008, 90(2): 324346.

Other variables that would have been known to the employee and employer but where not available at all
or for large numbers of employees in the data (such as education) would likely explain substantially more of
the variation.
171

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relatively stable), are symptoms of firmwide compensation structures, and the
formulaic way in which total compensation was varied over time.
Figure 11: Common Factors Identify a Firmwide Compensation Structure
Hedonic Regressions Of Wage Structure
All-Salaried Employee Class
Observation: Employee ID record in December of each year
Dependant Variable: Log(Total Annual Compensation)

Variable
Log(Age) (Years)
Log(Age)^2
Log(Company Tenure) (Months)
Log(Company Tenure)^2
Male
Employer Indicators
Location (State Indicators)
Title Indicators
Constant
Observation
R-square

Dec-01
Estimate St. Error T-Value
0.72
-0.10
-0.07
0.00
0.00
YES
YES
YES
YES

0.08
0.01
0.00
0.00
0.00

9.60
-9.66
-17.28
9.38
1.15

64,264
0.95

Observation
R-square

0.77
-0.09
0.08
-0.01
0.01
YES
YES
YES
YES

0.08
0.01
0.00
0.00
0.00

9.93
-8.74
38.46
-27.73
9.18

71,768
0.928

Observation
R-square

1.10
-0.15
0.04
0.00
0.01
YES
YES
YES
YES
73,722
0.922

0.08
0.01
0.00
0.00
0.00

13.26
-13.06
-29.45
20.40
3.60

Dec-06
Estimate St. Error T-Value
0.96
-0.12
-0.03
0.01
0.02
YES
YES
YES
YES

0.09
0.01
0.00
0.00
0.00

11.54
-11.59
9.35
-3.14
7.59

0.09
0.01
0.00
0.00
0.00

11.28
-10.69
-9.31
13.28
9.57

78,673
0.898

0.74
-0.09
-0.02
0.00
0.01
YES
YES
YES
YES

0.08
0.01
0.00
0.00
0.00

9.29
-8.62
-4.88
1.70
4.49

Dec-07
Estimate St. Error T-Value
1.25
-0.17
-0.03
0.00
0.01
YES
YES
YES
YES

0.10
0.01
0.00
0.00
0.00

9.57
-9.29
6.33
-3.29
8.17

Dec-04
Estimate St. Error T-Value
1.23
-0.16
0.01
0.00
0.01
YES
YES
YES
YES

0.08
0.01
0.00
0.00
0.00

15.16
-14.38
4.99
-6.04
6.81

62,645
0.93

0.10
0.01
0.00
0.00
0.00

12.71
-12.53
-9.55
9.36
4.97

71,804
0.909

Dec-10
Estimate St. Error T-Value
0.95
-0.12
0.02
0.00
0.02
YES
YES
YES
YES

Dec-03
Estimate St. Error T-Value

60,764
0.94

72,380
0.923

Dec-09
Estimate St. Error T-Value
Log(Age) (Years)
Log(Age)^2
Log(Company Tenure) (Months)
Log(Company Tenure)^2
Male
Employer Indicators
Location (State Indicators)
Title Indicators
Constant

1.03
-0.14
-0.12
0.01
0.01
YES
YES
YES
YES
61,768
0.94

Dec-05
Estimate St. Error T-Value
Log(Age) (Years)
Log(Age)^2
Log(Company Tenure) (Months)
Log(Company Tenure)^2
Male
Employer Indicators
Location (State Indicators)
Title Indicators
Constant

Dec-02
Estimate St. Error T-Value

Dec-08
Estimate St. Error T-Value
1.13
-0.15
0.02
0.00
0.01
YES
YES
YES
YES

0.09
0.01
0.00
0.00
0.00

13.06
-12.59
6.84
-3.89
8.73

73,897
0.916

Dec-11
Estimate St. Error T-Value
0.97
-0.13
0.05
0.00
0.01
YES
YES
YES
YES

0.08
0.01
0.00
0.00
0.00

11.54
-11.19
17.99
-7.39
8.79

88,431
0.918

Note: (1) Total Annual Compensation is computed as sum of base annual compensation (in December),
overtime pay, bonus, value of equity compensation granted.
(2) Value of equity compensation is computed using the weighted average grant-date fair values
for stock options and restricted stock units from SEC Filings.
Source: Defendants' employee compensation data; SEC Filings.

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129.

The regressions reported in the figure above are based on data from all
defendants and presume that each defendant had a similar internal
compensation system although the “employer effect” allows compensation to
differ by a fixed percent across firms. Figure 12 shows a summary of the Rsquared statistic for hedonic regressions performed separately for each
defendant and year. The R-squared statistic measures the percentage of the
variability in compensation that is explained by the variables in the model. The
majority of the R-squared statistics are around 90 percent demonstrating that
almost the entire variation in salaries within each firm at each point in time can
be explained by a common set of employee characteristics.

130.

The fact that nearly all variability in class member compensation at any point in
time can be explained by common variables means there was a systematic
structure to employee compensation at each of the Defendant firms. As a
result, one would expect that significant exogenous factors like the imposition
of Non-Compete Agreements would be expected to have effects that would be
felt across a broad swathe of employees. Furthermore, the fact that the
coefficients in my regressions did not vary substantially over time suggests that
compensation structures were relatively stable over time. The systematic
structure and the formulaic way in which compensation changed over time is
consistent with internal equity considerations as discussed in the economic
literature. In other words, my regression analyses are capable of showing that
the compensation of class members tended to move together over time and in
response to common factors. Accordingly, this evidence, along with my other
analysis of the economics of Defendants’ compensation, is capable of showing
that the effects on compensation from the Non-Compete Agreements would be
expected to be broadly experienced by all or nearly all members of the AllEmployee Class and Technical Employee Class.

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Figure 12: Common Factors Explain Within-Firm Compensation Structure

Summary of R-squared From Yearly Hedonic Regressions By Defendant
All-Salaried Employee Class
Observation: Employee ID record in December of each year
Dependant Variable: Log(Total Annual Compensation)
Year

ADOBE

APPLE

GOOGLE

INTEL

INTUIT

PIXAR

LUCASFILM

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011

0.91
0.93
0.92
0.94
0.87
0.94
0.92
0.93
0.88
0.91
0.93

0.89
0.87
0.91
0.91
0.91
0.89
0.87
0.87
0.87
0.86
0.86

0.93
0.94
0.79
0.89
0.80
0.79
0.75
0.80
0.86
0.77
0.83

0.96
0.95
0.96
0.96
0.97
0.97
0.96
0.97
0.96
0.96
0.97

0.88
0.90
0.90
0.89
0.89
0.89
0.88
0.88
0.88
0.88
0.88

0.84
0.71
0.85
0.83
0.90
0.92
0.93
0.94
0.93
0.95

0.88
0.87
0.92
0.94
0.94
0.94

Note: Hedonic regressions performed separately for each defendant and year by using
log(Total annual compensation) as a dependant variable and the following independent variables:
log(age), log(age)2, log(company tenure), log(company tenure)2, male indicator, location indicators, and
title indicators. Pixar's R-squared in 2001 is missing due to insufficient observations. Regressions for Lucasfilm
were not performed for 2001-2005 due to absence of employee titles in the data.
Source: Defendants' employee compensation data; SEC Filings.

131.

The Technical Employee Class also has a compensation structure that is
captured by the regression equations reported in Figure 13 that apply to
employees at all firms and also R-squared statistics for the regressions defendant
by defendant as reported in Figure 14.

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Figure 13: Common Factors Identify a Firmwide Compensation Structure
Hedonic Regressions Of Wage Structure
Technical, Creative, and R&D Class
Observation: Employee ID record in December of each year
Dependant Variable: Log(Total Annual Compensation)

Variable
Log(Age) (Years)
Log(Age)^2
Log(Company Tenure) (Months)
Log(Company Tenure)^2
Male
Employer Indicators
Location (State Indicators)
Title Indicators
Constant
Observation
R-square

Dec-01
Estimate St. Error T-Value
0.41
-0.06
-0.07
0.00
0.00
YES
YES
YES
YES

0.12
0.02
0.01
0.00
0.00

3.40
-3.84
-13.28
6.38
1.46

33,993
0.89

Observation
R-square

0.62
-0.07
0.10
-0.01
0.01
YES
YES
YES
YES

0.11
0.02
0.00
0.00
0.00

5.57
-4.84
33.58
-26.68
5.33

39,736
0.879

Observation
R-square

1.28
-0.18
0.04
0.00
0.02
YES
YES
YES
YES
44,839
0.885

0.12
0.02
0.01
0.00
0.00

7.96
-8.19
-23.33
15.50
2.32

Dec-06
Estimate St. Error T-Value
0.95
-0.13
-0.03
0.00
0.02
YES
YES
YES
YES

0.12
0.02
0.00
0.00
0.00

10.56
-10.84
8.83
-3.39
6.50

0.12
0.02
0.00
0.00
0.00

8.16
-7.88
-6.07
7.72
7.93

48,401
0.841

0.70
-0.09
0.01
0.00
0.00
YES
YES
YES
YES

0.12
0.02
0.00
0.00
0.00

5.94
-5.70
2.69
-5.57
1.54

Dec-07
Estimate St. Error T-Value
1.47
-0.20
-0.03
0.00
0.01
YES
YES
YES
YES

0.13
0.02
0.00
0.00
0.00

8.45
-8.45
4.98
-2.31
7.21

Dec-04
Estimate St. Error T-Value
1.28
-0.17
0.04
-0.01
0.01
YES
YES
YES
YES

0.12
0.02
0.00
0.00
0.00

10.62
-10.24
10.75
-12.58
4.23

32,999
0.88

0.13
0.02
0.00
0.00
0.00

10.89
-11.02
-6.12
5.52
3.05

41,862
0.848

Dec-10
Estimate St. Error T-Value
1.08
-0.15
0.02
0.00
0.02
YES
YES
YES
YES

Dec-03
Estimate St. Error T-Value

33,072
0.88

40,458
0.870

Dec-09
Estimate St. Error T-Value
Log(Age) (Years)
Log(Age)^2
Log(Company Tenure) (Months)
Log(Company Tenure)^2
Male
Employer Indicators
Location (State Indicators)
Title Indicators
Constant

0.95
-0.13
-0.13
0.01
0.01
YES
YES
YES
YES
33,431
0.89

Dec-05
Estimate St. Error T-Value
Log(Age) (Years)
Log(Age)^2
Log(Company Tenure) (Months)
Log(Company Tenure)^2
Male
Employer Indicators
Location (State Indicators)
Title Indicators
Constant

Dec-02
Estimate St. Error T-Value

Dec-08
Estimate St. Error T-Value
1.34
-0.18
0.04
0.00
0.02
YES
YES
YES
YES

0.11
0.02
0.00
0.00
0.00

11.86
-11.65
9.42
-6.98
7.24

43,643
0.859

Dec-11
Estimate St. Error T-Value
1.03
-0.14
0.05
0.00
0.02
YES
YES
YES
YES

0.11
0.01
0.00
0.00
0.00

9.79
-9.69
13.42
-5.61
7.89

54,695
0.878

Note: (1) Total Annual Compensation is computed as sum of base annual compensation (in December),
overtime pay, bonus, value of equity compensation granted.
(2) Value of equity compensation is computed using the weighted average grant-date fair values
for stock options and restricted stock units from SEC Filings.
Source: Defendants' employee compensation data; SEC Filings.

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Figure 14: Common Factors Explain Within-Firm Compensation Structure

Summary of R-squared From Yearly Hedonic Regressions By Defendant
Technical, Creative, and R&D Class
Observation: Employee ID record in December of each year
Dependant Variable: Log(Total Annual Compensation)
Year

ADOBE

APPLE

GOOGLE

INTEL

INTUIT

PIXAR

LUCASFILM

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011

0.86
0.91
0.89
0.92
0.89
0.92
0.88
0.90
0.86
0.87
0.91

0.83
0.84
0.87
0.87
0.87
0.84
0.81
0.81
0.80
0.79
0.76

0.79
0.87
0.66
0.83
0.62
0.68
0.66
0.68
0.81
0.68
0.76

0.92
0.90
0.91
0.90
0.94
0.93
0.93
0.94
0.93
0.94
0.95

0.78
0.84
0.86
0.85
0.86
0.85
0.82
0.85
0.86
0.85
0.84

0.64
0.52
0.67
0.65
0.75
0.83
0.86
0.86
0.87
0.87

0.86
0.83
0.90
0.92
0.92
0.93

Note: Hedonic regressions performed separately for each defendant and year by using
log(Total annual compensation) as a dependant variable and the following independent variables:
log(age), log(age)2, log(company tenure), log(company tenure)2, male indicator, location indicators, and
title indicators. Pixar's R-squared in 2001 is missing due to insufficient observations. Regressions for Lucasfilm
were not performed for 2001-2005 due to absence of employee titles in the data.
Source: Defendants' employee compensation data; SEC Filings.

132.

The compensation structure around a common baseline can also be seen by
looking at compensation trends of some of the major titles at Defendants.
These data use the regressions reported in Figure 12 to control for changes
within each title in age, tenure, and location. We refer to these as “constant
attribute” compensation.

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Figure 15: Constant Attribute Compensation of Major Apple Job Titles

Base Salary

Source: Defendants' employee compensation data.

Total Compensation

Source: Defendants' employee compensation data; SEC filings.

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Figure 16: Constant Attribute Compensation of Major Google Job Titles

Base Salary

Source: Defendants' employee compensation data.

Total Compensation

Source: Defendants' employee compensation data; SEC filings.

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133.

10/1/2012

To illustrate this further, Figure 17 depicts salary trends of top titles for Apple.
Each line represents a single year. The collection of lines indicates that,

Figure 17: Constant Attribute Compensation Ranking of Major Apple Job Titles is
Generally Stable

Source: Defendants' employee compensation data; SEC filings

134.

These charts reveal a persistent salary structure across employees consistent
with important elements of equity in the Defendants’ compensation practices.
The non-compete-agreements which might tend to focus on subsets of workers
would nonetheless have effects that would spread across all or almost all
employees at the firm in order to maintain the overall salary structure.

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3. Standard Econometric Analysis Is Capable of Showing That the
Non-Compete Agreements Artificially Suppressed
Compensation to the Members of Each Class Generally

135.

I have concluded that standard forms of econometric analysis are capable of
computing the aggregate amount of compensation suppression to the AllEmployee Class and Technical Employee Class caused by the Non-Compete
Agreements.

136.

An estimate of the effect of the Non-Compete Agreements on employee
compensation can be found by contrasting compensation during the periods
when the Agreements were in effect with compensation before and after the
Non-Compete Agreements.

137.

A search for comparison periods needs to be sensitive to the economic cycle.
The interval of time for which all the Defendants have produced compensation
data extends from 2001 to 2011. This ten-year interval includes a mild U.S.
recession, a severe global recession, two tepid U.S. recoveries and a brief period
of housing-led high growth. Roughly speaking, we can divide the 2001 to 2011
period as shown in Figure 18.
Figure 18: Growth Cycle Periods for the U.S. Economy

Period

Growth

(1)

(2)

2001
2002 - 2003
2004 - 2005
2006 - 2007
2008 - 2009
2010 - 2011

138.

Mild US recession
Tepid recovery
Housing led growth
Weakening  growth from weakening  housing
Severe global recession
Tepid recovery

Figure 19 reports the average percent change by year in total compensation for
all seven Defendants.172 Total compensation is the sum of December base

In addition to the mean, the table includes the median, the 90th percentile, the standard deviation and the
number of observations.

172

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salary bonuses, overtime and equity compensation. Observations are restricted
to cases in which there was no change in employer.
139.

The year 2002 in the wake of the 2001 recession has a large 4.7 percent decline
in average total compensation and that was followed by another 2.3 percent
decline in 2003. Circumstances for employees improved dramatically in 2004
with an average 10.3 percent increase in total compensation. Next comes the
out-of-place small 0.5 percent increase in 2005, coincident with the start of the
Non-Compete Agreements. Subsequently the average gains in compensation
fluctuated between 6 percent and 9 percent, with the value of 6.8 percent in
2008 in the midst of the severe global recession.
Figure 19: Average Percent Change in Total Compensation
Change in Total Compensation

Estimated Underpayment

Number of
Employees

Median

90th Percentile

Std. Dev.

Initial1

Cumulative

(2)

(3)

(4)

(5)

(6)

(7)

(4.7)%
(2.3)
10.3
0.5
9.1
7.4
6.8
7.4
6.5
9.7

(1.5)%
(0.0)
11.5
0.2
8.8
4.3
8.9
2.8
8.0
7.6

10.2 %
13.2
22.9
14.7
24.7
26.8
23.1
34.9
22.9
29.4

19.5 %
19.9
18.7
20.3
23.3
26.0
25.7
24.4
22.7
23.5

5.1 %

2002
2003
2004
2005
2006
2007
2008
2009
2010
2011

Mean

(1)

Year

5.1 %

22.3 %

22.4 %

58,465
58,176
57,835
59,494
64,620
64,680
66,055
69,178
69,727
74,989

Average

(9.5)%
(0.9)
(2.6)
0.0
0.0

(9.5)%
(10.3)
(12.9)
(12.9)
(12.9)

1

Calculated as the average change in total compensation for the year minus the average changes
in total compensation in 2004 and 2011.

Notes: (1) Change in compensation measured only on employees that did not switch jobs from previous year
(2) Total compensation measured as base salary as of December plus annual bonuses, overtime compensation,
and stock options and restricted stock awards.
Source: Defendants' employee compensation data; SEC filings.

140.

Before undertaking a formal regression analysis of damages, we can use these
annual numbers to do a preliminary informal impact assessment. The impact is
suggested by comparing what was happening during the agreement period with
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what was happening in relevant periods before and after. The years 2004 and
2011 arguably are useful before and after comparisons since these reveal the
kind of compensation increases that occur in expansion periods that were
similar to 2005-2007. The “during” years 2008 and 2009 were severe recession
years for which there may be no relevant direct comparisons. The column
labeled “Estimated Underpayment” has values in 2005-2007 equal to the
difference between the percent increase in total compensation that actually
occurred minus the average of total compensation in 2004 and 2011. This same
column has zero values for 2008 and 2009, built on the idea that the weak
economy would not have resulted in increases in those periods. The last
column cumulates these effects to find the total impact year by year. A large
impact on compensation comes in 2005 since that 0.5 percent actual change in
average total compensation translates into a 9.5 percent undercompensation.
The under-compensation cumulates to 12.9 percent in 2009.
141.

While the results in Figure 19 are suggestive, they rely on informal choices of
comparison period, and they do not make any distinctions among the
defendants. Regression analysis is a better approach because it allows the choice
of comparison period to be “constructed” statistically, and it allows for
differences among defendants as well as for employees. Figure 20 reports a
regression equation which explains the logarithm of total compensation at the
individual level with a variety of individual, firm and temporal effects. The
variables are defined in Figure 21 and the implied effects of the agreements on
total compensation are recorded in Figure 22.

142.

The variables in the regression in Figure 20 are divided by solid borders into five
principle categories:


Conduct Effects: How the Agreements affected total compensation
and how the effects vary across time, firms and individuals,



Persistence: How the effects linger over time,



Worker Effects: How compensation normally varies across workers,



Industry Effects: How compensation normally varies over time, and
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

Employer Effects: How compensation normally varies across firms.

143.

The worker variables are age, company tenure, and gender. The variables that
drive the temporal changes are rate of growth of payroll jobs in information in
Santa Clara County, the number of new employees hired by all defendants, the
number of workers who moved between Defendants and a time trend. The
effects that vary across employers are global revenue relative to the global
workforce and the rate of growth thereof, the number of new workers hired
relative to the previous year’s workforce, and indicators that allow for distinct
differences in compensation for each employer.

144.

The persistence variables are the levels of total compensation in the previous
year and the year before that, two for each employer. The fact that these
numbers sum to around 90 percent indicates very persistent effects, meaning
when a worker gets a bump up in compensation in some year that makes him or
her better off than comparable coworkers, that effect lingers on for many years.

145.

The CONDUCT variable measures the fraction of months in each year during
which the employer was involved in one or more of the agreements. The
conduct variable is interacted with three variables to allow for the possibility
that the agreements had effects that varied over time, across firms and across
individuals.

146.

This regression model can be used to estimate the undercompensation year by
year, employer by employer, reported in Figure 22. The part of the estimated
regression that involves the CONDUCT variable is used to estimate the
immediate impact of the illegal CONDUCT. These immediate impacts are
propagated over time as implied by the dynamic structure of the model
determined by the coefficients on the once-lagged and twice-lagged total
compensation explanatory variables that follow the CONDUCT variables in the
regression. The totals of the direct and secondary effects of the agreements on
total compensation by year and by defendant are reported in Figure 22.

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Figure 20: Regression Estimate of Undercompensation to Class
All-Salaried Employee Class
Observation: Employee ID record in December of each year
Dependant Variable: Log(Total Annual Compensation/CPI)
Variable

Conduct * Age
Conduct * Age^2
Conduct * Log(Number of New Hires In the Firm/Number of Employees(-1))
Conduct
ADOBE * Log(Total Annual Compensation/CPI) (-1)
APPLE * Log(Total Annual Compensation/CPI) (-1)
GOOGLE * Log(Total Annual Compensation/CPI) (-1)
INTEL * Log(Total Annual Compensation/CPI) (-1)
INTUIT * Log(Total Annual Compensation/CPI) (-1)
PIXAR * Log(Total Annual Compensation/CPI) (-1)
LUCASFILM * Log(Total Annual Compensation/CPI) (-1)
ADOBE * Log(Total Annual Compensation/CPI) (-2)
APPLE * Log(Total Annual Compensation/CPI) (-2)
GOOGLE * Log(Total Annual Compensation/CPI) (-2)
INTEL * Log(Total Annual Compensation/CPI) (-2)
INTUIT * Log(Total Annual Compensation/CPI) (-2)
PIXAR * Log(Total Annual Compensation/CPI) (-2)
LUCASFILM * Log(Total Annual Compensation/CPI) (-2)
Log(Age) (Years)
Log(Age)^2
Log(Company Tenure) (Months)
Log(Company Tenure)^2
Male
DLog(Information Sector Employment in San-Jose)
Log(Total Number of Transfers Among Defendants)
Year (trend)
Log(Number of New Hires In the Firm/Number of Employees(-1))
Log(Total Number of New Hires)
Log(Firm Revenue Per Employee/CPI) (-1)
DLog(Firm Revenue Per Employee/CPI) (-1)
APPLE
GOOGLE
INTEL
INTUIT
LUCASFILM
PIXAR
Location (State) Indicators
Constant
R-Square
Observations

St. Error

T-Value

(1)

1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
21.
22.
23.
24.
25.
26.
27.
28.
29.
30.
31.
32.
33.
34.
35.
36.
37.
38.

Estimate

(2)

(3)
(1)/(2)

0.0067 ***
-0.0001 ***
0.0028 ***
-0.1647 ***
0.6949 ***
0.7404 ***
0.4945 ***
0.6690 ***
0.7090 ***
0.6944 ***
0.8131 ***
0.2963 ***
0.2610 ***
0.3732 ***
0.3001 ***
0.2551 ***
0.1983 ***
0.1779 ***
-0.3591 ***
0.0394 ***
0.0107 **
-0.0012 **
0.0027 ***
1.4353 ***
0.0961 ***
-0.0038 ***
0.0154 ***
-0.2485 ***
-0.1070 ***
0.2170 ***
0.0627 ***
1.0364 ***
0.1522 ***
0.1462 ***
0.1352 ***
0.7251 ***
YES
YES

0.0005
0.0000
0.0008
0.0100
0.0054
0.0027
0.0017
0.0024
0.0058
0.0069
0.0363
0.0053
0.0027
0.0016
0.0023
0.0056
0.0067
0.0367
0.0415
0.0056
0.0050
0.0006
0.0005
0.0147
0.0015
0.0003
0.0009
0.0021
0.0035
0.0033
0.0162
0.0174
0.0146
0.0193
0.0481
0.0422

14.1138
-14.0235
3.6947
-16.5007
127.9743
278.6889
291.4208
282.4408
123.0243
100.1556
22.4035
55.9130
95.3635
228.3877
130.2277
45.7056
29.5094
4.8520
-8.6468
6.9805
2.1371
-2.1619
4.9116
97.4954
63.7243
-14.3189
16.6057
-116.9807
-30.1447
66.3627
3.8765
59.6506
10.4453
7.5835
2.8127
17.1808

0.926
504,897

Note: (1) *** Significant at 1% level; ** Significant at 5% level; * Significant at 10% level.
(2) Total Annual Compensation is computed as sum of base annual compensation (in December),
overtime pay, bonus, and value of equity compensation granted.
(3) Value of equity compensation is computed using the weighted average grant-date fair values for stock options and
restricted stock units from SEC Filings.
(4) Firm Revenue Per Employee is computed as a ratio of global revenue to global number of
employees, both obtained from SEC Filings. Lucasfilm revenues were obtained from PrivCo and public sources.
(5) Observations are restricted to cases in which there was no change in employer in the previous two years.

Source: Defendants' employee compensation data; St. Louis Fed Reserve; SEC Filings; PrivCo and public sources.

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Figure 21: Data Definitions
Variable

1.

Description

(1)

(2)

Total Annual Compensation

Sum of base annual salary as of December, total bonuses, overtime
amount and equity compensation received in the year

2.

CPI

U.S. Consumer Price Index (St. Louis Federal Reserve)

3.

Conduct

Indicator defined as a fraction of the year the defendant
had an active cold-calling agreement

4.

Age

Age of the employee in years

5.

Number of New Hires In the Firm

Number of employees newly hired in the year (i.e. not counting
individuals who might have been previously employed in the company)

6.

Company Tenure

Number of months an employee has been affiliated with the company

7.

Male

Indicator for male employees

8.

Information Sector Employment in San Jose

Employment in San Jose/Santa Clara Valley in the Information Sector
(St. Louis Federal Reserve)

9.

Total Number of Transfers Among Defendants

Total number of employees who moved from one defendant
to another in the year

10.

Total Number of New Hires

Total number of original employees hired by all defendants in the year

11.

Firm Revenue Per Employee

Global revenue of the company divided by global employment
in the company (SEC Filings; PrivCo; and public sources)

Figure 22: Estimated Impact on Class Total Compensation

Annual Undercompensation Percentages
All-Salaried Employee Class
ADOBE
2005
2006
2007
2008
2009

APPLE

GOOGLE

INTEL

-1.61%
-4.28%
-6.64%
-9.08%
-9.15%

-1.59%
-4.43%
-6.94%
-9.56%
-9.73%

-1.78%
-4.44%
-6.39%
-8.40%
-7.51%

-1.67%
-4.70%
-7.46%
-10.05%
-9.95%

INTUIT

LUCASFILM

PIXAR

-3.24%
-5.64%
-5.70%

-12.13%
-14.63%
-17.24%
-19.94%
-20.12%

-10.56%
-12.44%
-14.28%
-15.76%
-14.65%

Source: Regression Estimates of Undercompensation to All-Salaried Employee Class.

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147.

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I performed the same analysis for the set of employees in the Technical
Employee Class. The regression model for this Technical Employee Class is
reported in Figure 23 and the corresponding damage estimates in Figure 24.

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Figure 23: Regression Estimate of Undercompensation to Technical Employee Class
Technical, Creative and R&D Class
Observation: Employee ID record in December of each year
Dependant Variable: Log(Total Annual Compensation/CPI)
Variable

Conduct * Log(Age)
Conduct * Log(Age)^2
Conduct * Log(Number of New Hires In the Firm/Number of Employees(-1))
Conduct
ADOBE * Log(Total Annual Compensation/CPI) (-1)
APPLE * Log(Total Annual Compensation/CPI) (-1)
GOOGLE * Log(Total Annual Compensation/CPI) (-1)
INTEL * Log(Total Annual Compensation/CPI) (-1)
INTUIT * Log(Total Annual Compensation/CPI) (-1)
PIXAR * Log(Total Annual Compensation/CPI) (-1)
LUCASFILM * Log(Total Annual Compensation/CPI) (-1)
ADOBE * Log(Total Annual Compensation/CPI) (-2)
APPLE * Log(Total Annual Compensation/CPI) (-2)
GOOGLE * Log(Total Annual Compensation/CPI) (-2)
INTEL * Log(Total Annual Compensation/CPI) (-2)
INTUIT * Log(Total Annual Compensation/CPI) (-2)
PIXAR * Log(Total Annual Compensation/CPI) (-2)
LUCASFILM * Log(Total Annual Compensation/CPI) (-2)
Log(Age) (Years)
Log(Age)^2
Log(Company Tenure) (Months)
Log(Company Tenure)^2
Male
DLog(Information Sector Employment in San-Jose)
Log(Total Number of Transfers Among Defendants)
Year (trend)
Log(Number of New Hires In the Firm/Number of Employees(-1))
Log(Total Number of New Hires)
Log(Firm Revenue Per Employee/CPI) (-1)
DLog(Firm Revenue Per Employee/CPI) (-1)
APPLE
GOOGLE
INTEL
INTUIT
LUCASFILM
PIXAR
Location (State) Indicators
Constant
R-Square
Observations

St. Error

T-Value

(1)

1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
21.
22.
23.
24.
25.
26.
27.
28.
29.
30.
31.
32.
33.
34.
35.
36.
37.
38.

Estimate

(2)

(3)
(1)/(2)

0.0079 ***
-0.0001 ***
-0.0121 ***
-0.2196 ***
0.6744 ***
0.7234 ***
0.4367 ***
0.6401 ***
0.6703 ***
0.6491 ***
0.8462 ***
0.3053 ***
0.2538 ***
0.3659 ***
0.3179 ***
0.2857 ***
0.1045 ***
0.1448 **
-0.5894 ***
0.0696 ***
0.0297 ***
-0.0025 ***
0.0065 ***
1.4378 ***
0.0973 ***
-0.0008 **
0.0240 ***
-0.2720 ***
-0.0661 ***
0.2068 ***
0.1220 ***
1.3682 ***
0.1569 ***
0.1393 ***
0.0127
1.5864 ***
YES
YES

0.0007
0.0000
0.0010
0.0140
0.0073
0.0037
0.0022
0.0030
0.0085
0.0106
0.0692
0.0071
0.0038
0.0021
0.0029
0.0082
0.0097
0.0693
0.0588
0.0080
0.0068
0.0008
0.0008
0.0204
0.0020
0.0004
0.0013
0.0029
0.0049
0.0044
0.0245
0.0259
0.0219
0.0315
0.1037
0.0771

11.6667
-11.4844
-11.5872
-15.6471
92.4832
197.6595
200.6585
215.3504
79.1708
61.3919
12.2257
42.7525
67.0286
174.3271
110.4491
34.8914
10.8013
2.0884
-10.0182
8.7006
4.3581
-3.3821
7.8837
70.3710
47.5566
-2.1643
18.6766
-92.8937
-13.4914
46.8319
4.9879
52.7958
7.1705
4.4202
0.1226
20.5741

0.874
292,489

Note: (1) *** Significant at 1% level; ** Significant at 5% level; * Significant at 10% level.
(2) Total Annual Compensation is computed as sum of base annual compensation (in December),
overtime pay, bonus, and value of equity compensation granted.
(3) Value of equity compensation is computed using the weighted average grant-date fair values for stock options and
restricted stock units from SEC Filings.
(4) Firm Revenue Per Employee is computed as a ratio of global revenue to global number of
employees, both obtained from SEC Filings. Lucasfilm revenues were obtained from PrivCo and public sources.
(5) Observations are restricted to cases in which there was no change in employer in the previous two years.

Source: Defendants' employee compensation data; St. Louis Fed Reserve; SEC Filings; PrivCo and public sources.

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Figure 24: Estimated Impact on Technical Employee Class Total Compensation

Annual Undercompensation Percentages
Technical, Creative and R&D Class
ADOBE

APPLE

GOOGLE

INTEL

-1.56%
-4.29%
-6.48%
-8.80%
-8.44%

-1.90%
-4.96%
-7.79%
-10.64%
-10.51%

-3.07%
-7.23%
-9.36%
-11.20%
-9.00%

-1.64%
-3.06%
-3.38%
-4.76%
-4.19%

2005
2006
2007
2008
2009

INTUIT

LUCASFILM

PIXAR

-3.41%
-5.21%
-4.96%

-10.80%
-14.77%
-18.08%
-20.44%
-20.54%

-9.28%
-10.47%
-10.61%
-11.87%
-9.62%

Source: Regression Estimates of Undercompensation to Technical, Creative, and R&D Class.

148.

V.

Accordingly the undercompensation figures resulting from the estimation of
this econometric model of employee compensation (as reported in Figure 22
and Figure 24 can be used in a straightforward formulaic fashion in conjunction
with the All-Employee Class and Technical Employee Class compensation data
(as reported in Figure 3 and Figure 4) to calculate damages for employees in
either the All-Employee Class or the Technical Employee Class.

Conclusion

149.

I therefore conclude that common proof, in the form of documents, data,
economic theory, and statistical methodologies, is capable of demonstrating that
the Non-Compete Agreements artificially suppressed compensation of all or
nearly all members of the All-Employee Class and Technical Employee Class. I
conclude further that reliable econometric methods are capable of computing

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APPENDIX A. Defendant Data Relied Upon
A. Description of Data Requested and Produced

150.

Defendants produced two types of data: employee compensation and hiring and
recruiting data. Employee compensation data contains compensation
information for salaried employees that were active during the period of January
1, 2001 through February 1, 2012 at each defendant.173 Hiring and recruiting
data contains job applicant information for all potential candidates during the
period of January 1, 2001 through February 1, 2012 for each defendant.
1. Employment Data

151.

Plaintiffs requested each defendant produce compensation histories for all
salaried employees that were active during the period of January 1, 2001 through
February 1, 2012. The information requested includes personal information (an
encrypted social security number allowing employees to be matched across
defendants, hire date, previous employer information, birth year, gender,
education level, and channel of hiring) and on-going job information (job title
and level, salary, bonus awards, benefits, stock option grants, office location,
and manager ID). Additionally plaintiffs requested employee information that
identifies drivers of compensation (information regarding changes in titles or
jobs within a company) and exit information for employees that were
terminated.
2. Recruiting Data

152.

Plaintiffs requested each defendant produced recruiting data for the period of
January 1, 2001 through February 1, 2012. The information contained in the
recruiting data should consist of application date, applicant’s resume
information (employer, job title, and education level), the source through which

Employees can be “exempt” or “non-exempt”. See e.g., 76512DOC000638-677 at 641. Exempt workers
are salaried and generally not entitled to overtime pay. They generally have advanced professional training or
a degree. Class members are salaried and so are generally exempt.
173

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the application originated (cold called by recruiter, applied on website, etc.), and
outcome (hired, rejected, etc.).
153.

Additionally, plaintiffs requested that defendants provide detailed Cold-Calling
data for the period of January 1, 2001 through February 1, 2012. The
information contained in the Cold-Calling recruiting data should consist of a
unique identifier for each candidate contacted, date of contact, and candidate’s
resume information (employer, job title, education level, experience), the source
through which the application originated (cold called by recruiter, applied on
website, etc.), and outcome (hired, rejected, etc.). Though some defendants
have produced some of their candidate tracking information, they have yet to
produce enough information to determine Cold-Calling activities.

B. Datasets Created for Analysis

154.

Compensation data from all defendants was cleaned and processed in order to
generate a Master Employee dataset with monthly compensation and employee
information for 2001 - 2012. The information included in the master dataset
includes each person’s hashed SSN, employer and job title for each month in
2001-2012 for which a person is employed by one of the defendants, person’s
information (age, gender), original and current hire dates, termination dates,
tenure of employment, annual performance evaluation score, dates of changes
in salary and title, previous employer information, department, job grade and
job family information, leave of absence dates, annualized base compensation,
bonus compensation, stock options and equity compensation,174 overtime
compensation for non-exempt employees, and employee status identifiers
(FLSA status, part time and full time identifiers, temporary employee identifiers,
etc.).

To compute employee stock compensation, the ‘Weighted average grant date fair value’ for stock options
and restricted stock as reported by the defendants in their annual SEC filings was multiplied by the number of
options or restricted stock units granted to the employee.

174

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APPENDIX B. Definition of the Technical Employee Class

155.

I was asked to identify employees that fit with in Technical Employee Class,
defined to include all full-time salaried employees of Defendants during the
period of the alleged agreements (see Figure 1) that worked in technical,
creative, and research & development positions. The following job descriptions
were included within this Technical Employee Class :
1.

Software Engineers,

2.

Hardware Engineers and Component Designers,

3.

Application Developers,

4.

Programmers,

5.

Product Developers,

6.

User Interface or User Experience Designers,

7.

Quality Analysts,

8.

Research and Development,

9.

Animators, Digital Artists, Creative Directors and Technical Editors,

10.

Graphic Designers and Graphic Artists,

11.

Web developers,

12.

IT professionals,

13.

Systems engineers and administrators, and

14.

Employees classified as technical professionals by their employers.

The Technical Employee Class does not include the following types of employees:
1.

Non-technical employees (marketing, accounting, finance, operations,
etc.)

2.

Senior executives,
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3.
4.

Network administrators,

5.

Systems support/maintenance personnel,

6.

Facilities maintenance employees, or

7.
156.

Non-US employees,

Manufacturing technicians.

Several defendants provided a “Job Family” designation with their employment
data. The majority of class members fall under the job families listed in Figure
25 below.

Figure 25: Adobe, Apple, Google, Intel, and Intuit Creative, Technical, and R&D Job
Families
Adobe

Apple

Google

Intel

RSCH & DEV

IS&T
R&D

ADSALES_CSE
ENG_DEV_ADV
ENG_MEMBER
ENG_PROG
ENG_RES
ENG_SOFT
ENG_SOFT_MGR
ENG_SQAE
ENG_SRE_SWE
ENG_SRE_SYSADMIN
ENG_TECH_WRITERS
ENG_TECHPROG
ENG_UI
ENG_USAB
ENT_ESO
ENT_SE
MKTG_CREATIVE
ONLINE_SALES_TECH_OPS
OPS_DCFAC_ENG
OPS_NET
OPS_SYS
OPS_TECH
SALES_ENG
SALES_TSE

Intuit

CAD ENGINEERING
COMPONENT DES ENGINEERING
ELECTRONIC ENGINEERING
ENGINEERING
ENGINEERING MANAGEMENT
HARDWARE ENGINEERING
INFORMATION DATA ANALYSES
INFORMATION NETWORKS
INFORMATION SERVICES
INFORMATION TECH MANAGEMENT
MASK DESIGN
MECHANICAL ENGINEERING
MKTG ENGINEERING MANAGEMENT
PROCESS ENGINEERING
PRODUCT ENGINEERING
PROGRAMMING
PROJ/PROG MANAGEMENT
QUALITY ENGINEERING
RESEARCH & DEVELOPMENT
RESEARCH ENGINEERING
SOFTWARE ENGINEERING
SYSTEMS ENGINEERING
SYSTEMS SUPPORT
TECH
TECH MARKETING ENGINEERING
TECHNICAL
TECHNICAL WRITING
TEST ENGINEERING

APPLICATIONS
CREATIVE DESIGN
DATA ADMIN-ANALYST
DATABASE ADMINISTRATION
DESKTOP SYSTEMS
DEVELOPMENT MANAGEMENT
DOCUMENTATION
INFORMATION SECURITY
INFORMATION TECHNOLOGY
INTERACTION DESIGN
IT
IT MANAGEMENT
NETWORK ADMINISTRATION
NETWORK ENGINEERING
PRODUCT DEVELOPMENT MGMT
PRODUCT MANAGEMENT
QA ENGINEERING
SCM ENGINEERING
SOFTWARE ENGINEERING
SOFTWARE QA ENGINEERING
SYSTEMS
USER INTERFACE DESIGN
WEB DEVELOPMENT
WEB ENGINEERING
WEB PRODUCTION

Source: Defendants' employee compensation data

157.

There are additional Technical Employee Class members who fall under other
categories. Additional criteria were taken to select class titles:
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a. Adobe

Employees classified by Adobe as “Technical
Professionals” based on the field “AAP Code
Description” in its compensation data as well as the
“Business Unit” and “Function Name” fields were
included in the Technical Employee Class.175
b. Apple

Non-facilities engineers, web developers, graphic
designers, and other technical titles not classified as part
of the R&D or IS&T job families were included in the
Technical Employee Class. All R&D and IS&T support
titles (librarian, technicians, etc.) were excluded.
c. Google

Google identifies technical employees by job grade levels
beginning with “T”.176 Additionally, technical employees
in operating and support fields such as IT, Systems, as
well as web designers, application developers and other
creative and technical roles were included in the
Technical Employee Class. Excluded from the Technical
Employee Class were support roles (e.g., tech support
and desktop support).
d. Intel

Intel identifies technical employees through their job
families.
Additional job families included in the
Technical Employee Class were all non-facilities
engineering job families, as well as graphic and web
design and developer families. Excluded were nontechnical roles as well as manufacturing technicians and
machinery operators.

175

See Adobe compensation data (FY2001_HighlyConfidentialAEO-FY2012_HighlyConfidentialAEO).

176 GOOG-HIGH

TECH-00057189.
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e. Intuit

Intuit identifies technical employees through their job
families.
Additional job families included in the
Technical Employee Class were all software engineering
and application developer families, non-facilities
engineering job families, as well as graphic and web
design and developer families. Excluded were nontechnical roles as well system support and technician
roles.
f. Lucasfilm and Pixar

Neither Lucasfilm nor Pixar provided job families to
identify creative, R&D, and technical employees. For
both cases, class members were selected on the basis of
their job titles.177 Employees were identified as Technical
Employee Class members if their titles identified them as
Animators, Artists, Software Engineers, Engineers,
Scientists, Researchers, R&D professionals, Technical
Directors, Designers, Modelers, or IT and Systems staff.
Excluded from the list were videographers, camera
operators, technicians and system support employees.
Lucasfilm employees prior to 2006, for whom we are
missing job title information, are identified as being in
the Technical Employee Class if their titles in the 20062012 compensation data are flagged as Technical
Employee Class titles.

Pixar did provide department information that groups technical roles such as the Studio Tools group, the
Systems group, and others as well.
177

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IN THE UNITED STATES DISTRICT COURT
FOR THE NORTHERN DISTRICT OF CALIFORNIA
SAN JOSE DIVISION
CONFIDENTIAL – TO BE FILED UNDER SEAL
SUBJECT TO PROTECTIVE ORDER

IN RE: HIGH-TECH EMPLOYEES ANTITRUST
LITIGATION

No. 11-CV-2509-LHK

_____________________________________
THIS DOCUMENT RELATES TO:
ALL ACTIONS

REPLY EXPERT REPORT OF EDWARD E. LEAMER, PH.D.

December 10, 2012

398

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TABLE OF CONTENTS

I. 

Introduction, Assignment, and Summary of Conclusions .............................................1 

II. 

Dr. Murphy Has No Sound Basis for His Conclusion that the Agreements Did
Not Materially Limit Information about Outside Opportunities ..................................3 
A.  Dr. Murphy Has No Basis to Support His Assertion That Other Channels of
Information Are More Important than Cold Calling......................................................3 
B.  Dr. Murphy Incorrectly Assumes that Inter-Defendant Hiring Produces
Information that is Equivalent to Cold-Calling .............................................................7 
C.  Dr. Murphy Does Not Understand the Important Difference between Movement
and Mobility ...................................................................................................................8 
D.  Dr. Murphy Understates the Information Provided by Cold Calling...........................10 
E.  Dr. Murphy’s Analysis of Defendants’ Hiring Is Irrelevant and His Conclusion
from It of No Effect on Compensation Is Unsupported ...............................................11 
F.  Dr. Murphy Has Not Disputed that the Agreements Reduced Cold-Calling and
Competition Among the Defendants for Employees ...................................................13 
G.  Dr. Murphy Incorrectly Argues that Interference in the Information Flow Would
Not Affect Compensation At All .................................................................................14 

III.  Contrary to Dr. Murphy’s Opinion Under-Compensation Would Have Impacted
All or Almost All Class Members ...................................................................................16 
A.  There is Ample Evidence in the Defendants’ Documents and Depositions that
Internal Equity Played a Key Role in Wage Setting. ...................................................18 
B.  There is Abundant Economics Literature on the Role of Fairness in Wage Setting ...19 
C.  Class-Wide Evidence That Includes Google’s “Big Bang” Response to Facebook
Demonstrates How Competitive Pressure From One Peer Firm Can Move An
Entire Pay Structure Overnight ....................................................................................23 
D.  Dr. Murphy is Incorrect that the Defendants’ Data Do Not Indicate that Fairness
and Internal Equity Matter ...........................................................................................27 
E.  Dr. Murphy is Incorrect that My Hedonic Analysis of Named Plaintiffs’
Compensation Performed Poorly .................................................................................31 
IV. 

My Conduct Regressions Are Reliable Class-Wide Evidence That the
Agreements Suppressed Compensation on a Widespread Basis .................................33 
A.  Calculation of Standard Errors Assumes Statistical Independence .............................35 

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1.  Dr. Murphy Relies on a “Somewhat” Rigid Wage Structure in his Adjustment
of the Standard Errors. ...........................................................................................36 
2.  The Best Solution is to Include Variables that Eliminate the Correlation
Problem ..................................................................................................................37 
3.  Dr. Murphy’s Employer-Year Fixed Effects Proves too much as it would
Invalidate Any Before-During-and-After Model ...................................................37 
B.  Dr. Murphy’s “Sensitivity Analysis” is Flawed ..........................................................38 
1.  Dr. Murphy’s Study of Data Subsets Typifies What Happens When a Model is
Overloaded .............................................................................................................45 
2.  Dr. Murphy's Partial Disaggregation by Defendant is Improperly Implemented
in a Manner Designed to Make the CONDUCT Variable Perform Poorly ...........46 
3.  Firm-Wide Data Can Correct for the Correlation Problem ...................................48 
C.  Both Dr. Murphy’s and My Conduct Regression Analyses Demonstrate the
Feasibility of the Regression Approach .......................................................................53 
V. 

Conclusion ........................................................................................................................53 

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I.

12/10/2012

Introduction, Assignment, and Summary of Conclusions

1.

I have been asked by counsel for Class Plaintiffs in this matter to review the Report
and Deposition of Defendants' expert Dr. Murphy and reply to his comments that
bear on the conclusions in my Original Report. A list of materials I have relied
upon (in addition to those listed in my original report) is provided in Exhibit 1.

2.

Dr. Murphy lists five opinions in his summary that can be combined into three
principal categories:1 In this report I explain why each of these opinions of Dr.
Murphy is in error. I stand by the conclusions in my original report, namely that
common theoretical, documentary and quantitative evidence can be used to prove
the common impact of the agreements on class members.

3.

My summaries of Dr. Murphy’s three central opinions and summaries of my
rebuttal arguments are as follows:

4.

Murphy Opinion:2 As a matter of economic theory, the agreements are too limited
and too inconsequential to matter at all, given the multiple methods by which firms
recruit workers, and given the small fraction of overall hiring that was covered by
the agreements, and given the small number of inter-defendant transfers from 2001
to 2011.

5.

Rebuttal: (1) The market equilibrium models to which Dr. Murphy refers are not
applicable to Defendants’ agreements because these models assume perfect
knowledge, whereas the direct effect of the agreements was to reduce the
information available about outside opportunities. While models of market
equilibrium which assume perfect information imply that the agreements might be
inconsequential, models with imperfect information allow for the possibility or even
the likelihood that small changes in the information flow have large consequences.
(2) The cold calling that was suppressed in principle would have provided better
information in a more timely way than any other information channel. (3) For
wages to respond to outside competition what matters is mobility, not movement of
workers. The amount of hiring and the amount of inter-defendant movement is an

1

Expert Report of Kevin M. Murphy, November 12, 2012 (the “Murphy Report”), pp.6-13.

2

Murphy Report, pp.6-8.
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unreliable indictor of mobility, since there can be mobility without movement and
there can also be movement without mobility, for example, when a worker is fired.

6.

7.

Rebuttal: (1) The fact that “fairness” and internal equity can affect compensation is
clearly established in the economics literature. (2) The fact that fairness and
internal equity actually did affect compensation at the seven Defendants is clearly
established by the HR documents and depositions of the Defendants, and also by
Google’s decision in 2010 to do an across-the-board increase in base salaries by 10
percent in response to a relatively small loss of workers to Facebook. (3) My
common factor regressions are consistent with a “somewhat rigid” compensation
system but are not by themselves a proof of fairness effects. These regressions
confirm the hierarchical title/grade method of determining compensation that all of
the Defendant firms used. This hierarchical compensation structure allows the
force of fairness to play a role in setting compensation levels, something that is
established in the economics literature.4

8.

Murphy Opinion:5 Neither Leamer’s conduct regression model nor any other
similar regression model based on data from the proposed classes can be relied
upon to determine the effects of the agreements because the regression model has
residuals and because the estimates change “too much” when new variables are
added into the equation.

9.

3

Murphy Opinion:3 Whatever impact there might have been on a few individuals,
this effect was not spread across all or most members of the proposed classes
because these firms do not allow internal equity concerns (fairness and revenue
sharing) to play a role in the determination of compensation of employees. In
particular, the “common factor” regressions that Leamer reports do not establish
that internal equity mattered.

Rebuttal: (1) The method of regression is a completely standard way of carrying
out a damage analysis. (2) The existence of unexplained residuals, large or small,

Murphy Report, p.10.

4

See e.g., Rees, A. "The Role of Fairness in Wage Determination," Journal of Labor Economics,
1993, Vol. 11, No. 1, pt. 1.
5

Murphy Report, p. 11.
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does not in any way invalidate the method of regression. (3) Estimated regression
models will almost always change when new variables are added. (4) Dr. Murphy’s
modifications to my conduct regression (defendant disaggregation, and regression
with subsets) more than exhaust the information in the data set and are
predetermined to produce wild results. (5) The other variable that Murphy explores
(the S&P 500) illustrates that nonsense variables can also produce wild results. Dr.
Murphy uses the S&P index’s annual closing value in his estimation, as opposed to
the annual average of the S&P index. By making this choice, he implies that
compensation decisions throughout the year depend only on the end-of-year level of
the index, nothing in between, and do so with perfect foresight. More importantly,
this variable doesn’t belong in this equation because the link between the S&P
index and compensation at the seven Defendants is very remote, given the other
control variables in my equation.
II.

Dr. Murphy Has No Sound Basis for His Conclusion that the Agreements Did Not
Materially Limit Information about Outside Opportunities

10.

Dr. Murphy’s conclusion that information about outside opportunities was not
limited by the agreements is based on an unsupported assumption and an irrelevant
fact. Absent any data regarding the breadth or frequency of cold calling, or any
way of measuring the amount of information provided by cold calls compared with
other sources, Dr. Murphy merely assumes either that the cold calls provided
redundant information because of the amount of hiring not covered by the
agreements or he assumes that the prevented cold calls were replaced with other
information flows. Absent any evidence about the effects of the agreements on
mobility of the affected workers, Dr. Murphy uses an unreliable proxy for mobility,
the level of inter-Defendant hiring.6
A. Dr. Murphy Has No Basis to Support His Assertion That Other Channels of
Information Are More Important than Cold Calling

11.

6

Dr. Murphy’s first proposition, that “cold-calling” accounted for a small amount of
Defendants’ hiring activity is founded on little more than an irrelevant anecdote
collected in an unscientific and unrepresentative “survey” of Defendants’ HR

Murphy Report, ¶ 27.
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employees hand-picked by lawyers, and it reveals nothing about the importance of
cold calling in the provision of information.

12.

Cold-calling is a distinct and special channel of information that accesses job
candidates who otherwise would be left unaware of attractive opportunities. The
record does not indicate that there are close substitutes for cold calling, and Dr.
Murphy’s unscientific surveys of a group of Defendant HR employees has produced
nothing to the contrary. What he has learned is only that there are other means of
recruiting:
“But nonetheless, I think a number of the individuals from
the various companies gave some quantitative assessments
in their declarations and in their discussions. They talked
about the fraction of people hired through various means.” 7

13.

Dr. Murphy’s reference to vague information about the fractions of people hired by
various methods tells us nothing about what was irretrievably lost when the anticold-calling agreements were put in place, if anything. By relying on a few
interviews to conclude that the anti-cold-calling agreements had little or no impact
on the information flow, Dr. Murphy effectively assumes that the information
conveyed by Google’s hiring activities at a college job fair, for example, is a
perfect substitute for cold-calls by Google to Apple employees.8 As I describe
below, this unlikely hypothesis would need to be tested, which Dr. Murphy has not
done.

14.

Dr. Murphy says that the data do not exist to test his hypothesis.9 Instead, Dr.
Murphy’s basis seems little more than that Defendants’ employees told him that
referrals account for a much larger percentage of hiring than “cold-calling.” One of
the many problems with this approach is that Dr. Murphy redefines the alleged
conduct covered by the agreements to exclude referrals and to apply only to “totally
passive candidate[s]” who had not in any way expressed interest in new

7

Murphy Deposition, pp. 61-62.

8

Deposition of Kevin M. Murphy, Ph.D., December 3, 2012 (Murphy Deposition), p. 127.

9

Murphy Report, p. 17, fn. 31.
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employment.10 But, as I described in my report, the agreements are alleged to have
prohibited cross-solicitation of the parties’ employees in any manner, whether as a
result of a referral or not and whether recruiters identified potential candidates via
networking websites such as LinkedIn or not.11 As I understand it, these
agreements applied to all recruiters who were either directly employed by or were
headhunters hired by the agreeing firms.12 Some of the agreements apparently went
further, prohibiting hiring, requiring notification of hires, and prohibiting
counteroffers.13

15.

10

The agreements also applied to employee referrals. Adobe senior executives made
their understanding clear at the time. When the question arose “if an Adobe
employee refers an Apple employee through our employee referral program are you
okay with that?” the answer that Bruce Chizen, CEO of Adobe agreed with was, “I
think the spirit has to be that we don’t initiate contact with Apple employees even

Murphy Report, pp. 3-4, fn. 8.

11

See Expert Report of Edward E. Leamer, Ph.D., October 1, 2012 (“Leamer Report” or “my
Report”), ¶ 23.

12

See e.g., 231APPLE001164, GOOG-HIGH TECH-00023500-601 at 520-528, and
PIX00000400.
13

When present, this provision applied even when an employee initiated contact. See, e.g.,
76577DOC000464. Even if certain agreements may not have begun with this express provision,
they often operated in this manner in practice. For example, Pixar and Google sought Steve
Jobs’s permission before making offers to Apple employees. See PIX00006025;
231APPLE002151. Apple refused to consider Adobe employees unless they first left
employment with Adobe. See 231APPLE080776 (“This is a response I received from an
ADOBE employee who applied for a position through our job posting site. I called him to ensure
he is still an ADOBE employee, explained our mutual agreement / guidelines, and asked that he
contact me should his employment with ADOBE terminate, but at this time I am unable to
continue exploring with him. . . . I do not want anything in ‘writing’.”) Apple also attempted to
enter into a “no hire” agreement with Palm, which Palm’s CEO Ed Colligan rejected. See
PALM00005 – 008 at 006 and PALM00022 – 027 at 024. See also, 231APPLE002153 - 154,
and 231APPLE002214. See also, PIX00000400; GOOG-HIGH TECH-00056790 and
PIX00004051 (“We just won’t get into bidding wars” for employees.); LUCAS00013507 (“We
have agreed we want to avoid bidding wars.”).
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through our employees.”14 [emphasis added] Google and Pixar documents also
show this to be the case.15

16.

14

The agreements affected the recruiting of even “non-passive candidates” i.e. those
who were actively searching and who submitted applications in response to job
postings or posted their resumes on the companies’ websites. Notice was given
regardless of who initiated contact, as Google did before making an offer to an Intel
employee who had not been cold-called.16 Notice also had to be given to Apple by
Pixar before making an offer to an Apple employee (“My understanding was in
order for us to consider an Apple employee as a candidate, we couldn’t make an
offer without letting Steve Jobs know”).17 The same arrangement existed between
Pixar and Intel.18

See ADOBE_001096-97 at 96.

15

Google enforced its “Do Not Call” agreements in the same way. “The key is the DNC
candidate is initiating the ‘I am looking’ and there is written proof.” This included employee
referrals: “All Googlers fall under the same DNC rules.” “If the Googler did reach out and
initiate first contact (e.g., at a cocktail party) then we should walk away and not pursue the
lead.” GOOG-HIGH TECH-00009270-276 at 270. See also Deposition of Arnnon Geshuri,
August 17, 2012 at 187:25-189:1. Also see PIX00009271-72 at71 “You could check in, invite
her over for coffee, see if she offers up any opening. If she did, we could talk to her, If not, we’d
have to respect the truce.”
16

In August of 2006, Campbell agreed with Google’s Jonathon Rosenberg (Senior Vice
President of Product Management) that Google should call Otellini before making an offer to an
Intel employee, regardless of whether the Intel employee first approached Google. Shaver Decl.,
Ex. 37 [GOOG-HIGH TECH-00056790] (Rosenberg: “Campbell and I already discussed this
[talking to Intel before making an offer to an Intel employee] and agreed that either way
[whether Intel was treated as a “Do Not Call” company, or a “sensitive” company] I should give
a courtesy call to Paul Otellini. I’m meeting with [the Intel candidate] tomorrow and I will ask
him how he wants to handle communication to Intel management before we even get to the stage
of specifically discussing an offer.”).

17

Deposition of Pamela Zissimos, November 13, 2012 at 125:6-8.

18

“We cannot recruit (including calling up, emailing or enticing in any way) current Pixar
employees to come work for Intel. If a Pixar employee applies to Intel without being recruited
by Intel, contact Pat Gelsinger [a Senior VP at Intel] and explain to him a Pixar employee
(provide the candidates [sic] name) has applied to Intel without being recruited and he will he
will [sic] contact the CEO of Pixar for approval to hire.” 76577DOC000464-466 at 466.
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17.

Hence, Dr. Murphy fails to acknowledge the full scope of the agreements and does
not recognize that these agreements directly affected more than just “totally
passive” employees. He therefore has no basis for the first thing he says we need to
know to understand the agreements.

18.

Moreover, debating or defining the scope of the agreements is not a proper exercise
for an economist. I studied the agreements to have a factual background for
statistical methods that I used to measure their effects empirically. Their actual
meaning or scope will presumably be determined someday in a court of law. If Dr.
Murphy’s opinion depends on his own evaluation of the true meaning of the
agreements based on self-serving interviews with Defendant employees, then the
first step in his formation of an opinion is not based on economic expertise.
B. Dr. Murphy Incorrectly Assumes that Inter-Defendant Hiring Produces
Information that is Equivalent to Cold-Calling

19.

Dr. Murphy’s attempt to determine the effect of the agreements based on the level
of inter-Defendant hiring is similarly unfounded. Dr. Murphy asserts that:
If hiring by one Defendant of employees from another
Defendant were economically important in the pricediscovery process, then employee movement between
Defendants should account for a substantial part of the
overall movement of workers.19

20.

Dr. Murphy’s support for this assertion is in footnote 35:
Hiring should be a reasonable proxy for the price discovery
process given that information on compensation is most
commonly provided to candidates only at the later stages of
the recruiting process (once the number of candidates has
been reduced to a small group that then is interviewed for a
job or job opening). Both Adobe and Intuit clearly state
that they do not discuss compensation until the later stages
of the recruiting process.20

19

Murphy Report, ¶ 31.

20

See Declaration of Jeff Vijungco, November 9, 2012 at pp. 5-6 and Declaration of Chris Galy
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21.

This is Dr. Murphy’s key justification for using inter-Defendant hiring to evaluate
the agreements. It has no foundation in economic theory or fact.

22.

As Dr. Murphy acknowledged at his deposition a cold-call can transmit information
about compensation to a candidate regardless of whether the recruiter makes a
concrete salary offer.21 If the recruiter assesses the market value of the position,
this conveys information; if the recruiter provides feedback about the candidate’s
salary expectations, this conveys information; if the recruiter even calls the
candidate back after he or she has stated salary expectations, this conveys
information. Most recruiters are well aware of salary levels and ranges at
competing firms since companies routinely survey compensation levels at their
labor market competitors. Employees on the other hand aren’t equally aware of
salary distributions or of the precise skill sets valued in other firms. That
asymmetric information is partly remedied by the cold call alone. The very fact that
a recruiter initiated contact and expressed interest in an employee provides a signal
to the employee that he may be under-placed or that his skills may be under-valued
at the current employer and that there are might be better opportunities elsewhere.
C. Dr. Murphy Does Not Understand the Important Difference between
Movement and Mobility

23.

Dr. Murphy’s opinions indicate he has little or no understanding of the important
difference between movement and mobility. As opposed to actual movement, i.e.,
an employee leaving one firm and joining another, mobility is a reflection of
employees’ satisfaction or lack thereof with compensation at their current firms and
recognition or understanding of the availability of other employment opportunities.
Cold calling enhances mobility, without necessarily creating movement. Contrary
to what seems the basis for Dr. Murphy’s opinions, movement is a very imperfect
and unreliable symptom of mobility because while one possible result of increased
mobility is more movement, another involves firms’ enhancing compensation to
prevent movement. In other words, evidence of a lack of movement is entirely
consistent with my findings that class-wide evidence is capable of showing that in
the absence of Defendants’ agreements, Class member compensation would have

November 9, 2012 (Galy Declaration) at pp. 3-4.
21

Murphy Deposition, pp. 135-136.
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been broadly higher. Thus, Dr. Murphy’s first three opinions are speculations,
lacking empirical support.

24.

The important elements in the distinction between movement and mobility are:

a.

Movement refers to the departures and arrivals of workers at firms.
Mobility is the credible threat of movement if a better offer were to
materialize.

b.

Mobility between firms puts pressure on each firm to offer compensation
packages that are attractive enough to retain employees. If workers were
completely immobile, potential external competition for existing workers
could not materialize as a force for higher compensation. If workers were
perfectly and instantaneously mobile, then firms would be compelled to
match outside opportunities on a day by day basis in order to retain
employees. Normal, unimpeded mobility lies somewhere between these
two extremes, greater for some kinds of workers and less for others.

c.

Mobility is impaired by lack of information. Recruiters target the socalled “passive” candidates with cold-calling because that passivity is
likely to leave the workers under-informed about outside opportunities.
By providing information to under-informed workers cold-calling
increases mobility.

d.

Movement is evident in the payroll records but mobility is not directly
observable. Movement is a possible correlate of mobility, but not reliably
so because most swings in movement come from other sources. Not
surprisingly the anti-cold-calling agreements were put in place in 2005
when the market for tech workers was heating up again after the 2001 tech
bust.22 Whatever suppressive impact the agreements had on mobility was
masked by the coincident unpredictable rise in movement.

e.

There can be mobility without movement. Indeed, in response to outside
offers, firms routinely counteroffer to try to retain valuable employees. If
the response is adequate, there is mobility without movement and a wage
response without movement as well.

f.

There can be changes in movement without changes in mobility.

22

Luo, T. and A. Mann, “Crash and Reboot: Silicon Valley high-tech employment and wages,
2000-08,” Monthly Labor Review, January 2010, pp. 61-65 .
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1. Involuntary separations create movement with or without mobility.
Separations initiated by a firm either because of substandard
performance of the individual or because of reductions-in-force are
not likely to create upward pressure on wages of the workers who
stay behind. These separations are obviously not symptoms of
mobility of the affected workers.
2. There are also a variety of worker-chosen separations that have
nothing to do with getting a better job. Health problems and
retirement are obvious instances. Family matters like a spouse
getting an attractive job offer in a different city or the desire to be
closer to aging parents can also create separations.

25.

The agreements had their effect by reducing the information flow about outside
opportunities, and thus reducing the mobility of workers as well as their perceptions
of the equitable wage within their firm. Dr. Murphy has provided no reliable
support for his apparent opinion that the agreements did not substantially reduce the
information flow to passive experienced workers who were satisfied with their jobs
and not actively engaged in a search for alternatives.
D. Dr. Murphy Understates the Information Provided by Cold Calling

26.

Dr. Murphy’s factual assertion—that recruiters do not discuss compensation with
candidates until late in the recruitment process23—also has no empirical support.
He relies on two declarations and conversations with Defendant employees for
which there are no notes.24 But even these information sources are contradictory:
the Galy Declaration he relies on states that recruiters do discuss compensation with
recruits.25 Even Dr. Murphy admitted at his deposition that this happens.26

27.

This is the problem with relying on sources such as these and “casual empiricism”
to draw empirical conclusions. An economist qualified and trained in survey-based
research could have designed and administered a survey of recruiters at the

23

Murphy Report, fn. 35.

24

Id.

25

Galy Declaration, ¶ 15.

26

Murphy Deposition, p. 136.
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Defendants, like the survey administered in one of Dr. Murphy’s sources.27 Such
work might have been informative, if properly executed. However, there is little or
no useful economic evidence on which to base empirical conclusions in
unstructured conversations with interested persons. Some economists use
interviews with industry participants to frame exercises in symbolic theory; they
expressly disclaim using them as a basis for empirical conclusions and they admit
their “methodology…moves beyond the boundary of economics itself into the
realm of anthropology and the territory of hermeneutics[.]”28
E. Dr. Murphy’s Analysis of Defendants’ Hiring Is Irrelevant and His Conclusion
from It of No Effect on Compensation Is Unsupported

28.

Dr. Murphy also argues that “my claim that average compensation at these firms
was suppressed is implausible because of the high level of hiring by Defendants
during the class period.”29 The only support offered by Dr. Murphy for this opinion
is the rate of movement of workers to the Defendants: “Collectively, between 2005
and 2009, Defendants hired an average of over 8,000 new workers per year – equal
to 11 percent of their combined workforces.”30

29.

This single fact is irrelevant to his sweeping conclusion. There is no inconsistency
between the levels of hiring by Defendants during the class period and my
conclusion that there is reliable class-wide evidence capable of showing that
Defendants’ under-compensated employees as a result of the agreements.

27

Honoree, A. I. and D. E. Terpstra. “The Relative Importance of External, Internal,
Individual and Procedural Equity to Pay Satisfaction,” Compensation & Benefits Review,
November/December 2003. Dr. Murphy was apparently unacquainted with any written
standards for survey design or mixed methods (qualitative and quantitative) research prior to
undertaking it. See, e.g., Creswell, J. W., and V. L. Plano Clark, Designing and Conducting
Mixed Methods Research, SAGE Publication: 2007, Chapter 6.; Creswell, J. W., Research
Design: Qualitative, Quantitative, and Mixed Methods Approaches, SAGE: 2009, Chapter 9.
28

Piore, M. J., “Qualitative Research: Does It Fit In Economics?,” European Management
Review, (2006) 3, 17-23.
29

Murphy Report, p. 6.

30

Id.
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30.

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Dr. Murphy appears to miss or misunderstand the following key facts about hiring
and cold-calling:

a.

Much of the Defendants’ hiring volume was at entry levels. The
information conveyed by the hiring of an entry level employee at the entry
level rate in the firm’s compensation structure is not comparable to the
information conveyed in a cold call of an experienced worker by a
competitor.

b.

When firms hire a new employee they have control over the internal
disruption that a new employee with exceptional compensation might
cause. This disruption can be minimized by slotting a new employee into
an appropriate title-compensation combination in the firm’s hierarchy, and
by offering one-time signing bonuses, thus leaving the new employees
appropriately located in the hierarchy going forward. Defendants’ new
employees could be slotted into a “comfortable” place in the internal
hierarchy with compensation comparable to other employees.

c.

Although firms can exercise control over the contracts offered to new
employees, they do not have control over cold-calls and departures to
better positions, unless they enter into illegal agreements. Thus, as far as
movement is concerned, the focus should be more on the impact of
departures to better positions rather than hiring. As described above and in
my original report, Defendants clearly found departures highly
disruptive.31

d.

I accommodated the potential significance of differences in the rate of
hiring by embodying it in my conduct regression.32
1. My conduct regression explicitly allows for the possibility that
high levels of firm hiring affect the amount of undercompensation
caused by the agreements.
2. My conduct regression explicitly allows for the possibility that the
effect on compensation levels is different for young employees and
for employees with short tenure at their firms, and so the effect of
the agreements on employees at a firm might vary according to the

31

Leamer Report, pp. 34 and 45.

32

Leamer Report, Figure 20.
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firm’s composition in this regard. These are workers who, as a
group, might be less likely to be cold-called.

31.

The bottom line is that Dr. Murphy’s characterization of the significance of
Defendants’ hiring is misleading and mistaken.
F. Dr. Murphy Has Not Disputed that the Agreements Reduced Cold-Calling and
Competition Among the Defendants for Employees

32.

33.

33

As described above, documents show Defendant executives’ frustration with coldcalling when it occurred, whether or not it resulted in a poached employee. They
wanted to stop it, and actively undertook procedures at the highest levels to do so.
Dr. Murphy has not disputed this. Dr. Murphy has not addressed the effectiveness
of the agreements in actually deterring cold calling. As I described in my Report,33
documents indicate that CEOs of the Defendant firms placed a priority on ensuring
compliance.34
Thus it is undisputed that but for the agreements some workers would have
otherwise learned that a competitor would have been willing to pay higher salaries
than the worker was currently receiving. Some of these workers would likely have
accepted the higher wage, or used this information to negotiate a higher salary from
their employer, and told colleagues about the alternative employment opportunities.

Leamer Report, ¶ 39

34

See, e.g., GOOG-HIGH TECH-00009454-9454 at 9454 (Email from Apple showing concern
about poaching from Google and assurance from Eric Schmidt that the employee responsible
would be terminated from Google), 231APPLE002140 (Bill Campbell assures Steve Jobs that
Dave from Apple would not accept Google’s offer as they stopped the hiring process for two
other people from Dave’s team), and 231APPLE002145 (Bruce Chizen forwards an Adobe email
to Steve Jobs showing that Jerry from Adobe has been asked to back off from soliciting the one
person he was after from Apple).
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G. Dr. Murphy Incorrectly Argues that Interference in the Information Flow
Would Not Affect Compensation At All

34.

In addition to asserting incorrectly that the agreements could not affect the
information flow about outside opportunities, Dr. Murphy argues the impact on
compensation would have been nil, or even positive because:35

a.

The agreements were not broad enough to affect the “market price.”

b.

“As a matter of economic theory, the alleged conspiracy to restrict a small
number of employers from using a single recruiting tool when
approaching employees at one or a few other firms would not lower
compensation on a class-wide basis.”36

c.

“As a matter of economics, reduced cold calling (to the extent it has an
effect) could raise, rather than reduce, average compensation. If less cold
calling reduced the number of potential candidates contacted by
Defendants, it would reduce the pool of potential hires for those
Defendants.”37

35.

These comments are a highly selective and misleading characterization of the state
of economy theory.

36.

The reference to market prices in item (a) is startling and suggests that Dr. Murphy
ignored what I said in my report. My findings about the effect of the agreements on
compensation relate to the price-discovery process that was impeded by the anticold-calling agreements. I do not rely on the notion that the equilibrium market
price is affected by the agreements. What I argue instead is that the whole sequence
of contracts in search of that market price is affected. This is why market definition
and market price are not relevant inquiries here: the process of getting to a market
price across markets, across firms, and for all employees was disrupted by the
agreements. Dr. Murphy’s commentary about market prices and equilibrium is thus
irrelevant.

35

Murphy Report, pp. 9-10.

36

Murphy Report, p. 9.

37

Murphy Report, p. 10.
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37.

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The reference to economic theory in item (b) is also startling. While there may be
some assumptions that are able to produce the result Dr. Murphy claims, other
assumptions—widely accepted in the economic literature—imply the opposite. In
particular, Dr. Murphy’s assertion regarding the supposedly limited nature of the
recruiting restriction at issue in the agreements is at odds with widely accepted
economic research into the workings of markets with less-than-perfect (imperfect)
information. Contradicting Dr. Murphy, here is what Nobel Prize Winner Joseph
Stiglitz wrote in an article cited in my previous report (emphasis added):
“For more than 100 years, formal modeling in economics
had focused on models in which information was assumed
to be perfect. Of course, everyone recognized that
information was in fact imperfect, but the hope, following
Marshall's dictum ‘Natura non facit saltum,’ was that
economies in which information was not too imperfect
would look very much like economies in which information
was perfect. One of the main results of our research was to
show that this was not true; that even a small amount of
information imperfection could have a profound effect
on the nature of the equilibrium.”38

38.

It is not just the work of Dr. Stiglitz that Dr. Murphy has failed to appreciate. Two
other recent Nobel Prize winners have also done work on the consequences of
imperfect information. Vernon L. Smith won the 2002 Nobel Prize “for having
established laboratory experiments as a tool in empirical economic analysis,
especially in the study of alternative market mechanisms.”39 These laboratory
experiments study the price discovery process, with various informational
limitations and transactions costs. Since I filed my report, Alvin Roth was awarded
the 2012 Nobel Prize for “for the theory of stable allocations and the practice of

38

Stiglitz, J., “Information and the Change in the Paradigm in Economics,” The American
Economic Review, Vol. 92, No. 3 (June 2002), p. 461.
39

"The Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel 2002,"
Nobelprize.org., December 10, 2012,
http://www.nobelprize.org/nobel_prizes/economics/laureates/2002/
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market design.”40 Here the words “market design” refer to a broad concept and
would include restrictions on cold-calling.

39.

Dr. Murphy’s item (c) is another reference to some unstated economic model that,
according to Dr. Murphy, apparently says that if less-preferred cold-calling is
substituted for the most-preferred cold calling, then workers are made better off.
But it is not enough to claim that there is a theory that allows workers to be better
off. What we need is some wisdom that offers advice on whether this is likely to be
the case in the present context. I consider it highly unlikely that the Defendant
firms would engage in these secret, illegal and egregious agreements if the
agreements increased compensation for their workers.

40.

Dr. Murphy’s logic violates a basic principle of modern economics, which he did
not really dispute at his deposition:
“The most fundamental reason that markets with imperfect
information differ from those in which information is
complete is that, with imperfect information, market
actions or choices convey information.”41
“… The fact that actions convey information leads people
to alter their behavior, and changes how markets function.
This is why information imperfections have such profound
effects.”42

III.

Contrary to Dr. Murphy’s Opinion Under-Compensation Would Have Impacted All
or Almost All Class Members

41.

Dr. Murphy describes my opinion as follows:

40

"The Prize in Economic Sciences 2012," Nobelprize.org., December 10 2012,
http://www.nobelprize.org/nobel_prizes/economics/laureates/2012/
41

Stiglitz, J., “Information and the Change in the Paradigm in Economics,” The American
Economic Review, Vol. 92, No. 3 (June 2002), p. 468.
42

Stiglitz, J., “Information and the Change in the Paradigm in Economics,” The American
Economic Review, Vol. 92, No. 3 (June 2002), p. 473.
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“Dr. Leamer’s analysis has three essential steps. First, the
challenged agreements must materially reduce the
information available to Defendants’ employees. Second,
that reduction in information must cause the salaries of
individual employees to be reduced. Third, the “somewhat
rigid” compensation structures of the Defendants must
cause the reductions in the compensation of some
employees to reduce compensation on a class-wide
basis.”43

42.

Dr. Murphy claims that “[n]one of the required links in the chain hold, let alone all
three.”44 However he has left major elements of these three steps unanswered, has
made substantial errors in his characterization of the economics of the case, has
ignored or mischaracterized evidence, and as a result has failed to support his claim
that there would be no substantial or class-wide impact from the Defendants’
agreements.

43.

The previous section has addressed the very substantial economic theory and
documentary evidence that supports (1) the finding that the agreements limited
information about outside opportunities and (2) suppressed compensation of
affected workers. With regard to the third step in Dr. Murphy’s characterization of
my opinion–that these firms have a somewhat rigid salary structure that spreads the
harm to all or almost all employees –Dr. Murphy sometimes disagrees but it is a
great surprise to discover that when he feels his argument is strengthened by the
opposite opinion, he changes his mind.

44.

As Murphy puts it: “He [Leamer] failed to take into account when performing
his statistical test that, aside from the challenged agreements, employees at a
firm are affected by common factors that influence their compensation – e.g., a
highly successful movie at Pixar can result in large and unusual bonuses for all
Pixar employees, or a short-term reduction in the demand for PCs and the

43

Murphy Report, p. 5

44

Murphy Report, p. 6.
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microprocessors that power them can cause a decline in Intel’s revenue and
profitability and lead Intel to impose a wage freeze such as occurred in 2009.”45

45.

I quite agree with the second Dr. Murphy on this.
A. There is Ample Evidence in the Defendants’ Documents and Depositions that
Internal Equity Played a Key Role in Wage Setting.

46.

The proposition that these firms allowed salaries to be influenced by internal equity
considerations is clear from Defendant HR documents and from depositions of their
HR personnel. For example, managers at Apple take internal equity into careful
consideration on top of performance when making a merit decision to determine an
existing employee's merit increase.46 Similar approaches are used by other
Defendants, where internal equity is assessed and equity report is run prior to
making offers, merit increases and promotions.47 Internal equity played an
important role during the negotiation processes for all Defendants, e.g., Apple had
to extend an offer that was lower than what a candidate was getting at his previous
job due to internal equity,48 and while a hiring manager at Adobe stated that while
he does not subscribe to the ‘internal equity’ issue which assumes “all people are
created equal,” he understands the sensitivity, and hence suggested spot-on bonuses
for a candidate if an increase in base salary offer would skew internal equity.49

47.

One expression of internal equity and fairness in Defendants’ compensation
practices is their adoption and adherence to compensation structures. These
structures played a substantial role in decisions regarding hiring, promotions, salary
raises,50 and even demotions or lateral movements.51 Numerous Defendant

45

Murphy Report, ¶ 124 (emphasis added).

46

See 231APPLE094041-67 at 50.

47

See e.g., 76512DOC000926, ADOBE_009327, ADOBE_016608, GOOG-HIGH TECH00036370, GOOG-HIGH-TECH-00233026, LUCAS00004721 and PIX00023020.

48

See 231APPLE056385.

49

See ADOBE_002764.

50

See e.g., 76582DOC000902 (Intel follows a pay line guideline when making changes to
employees’ salaries).
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supported the observations of reference-dependant fairness and also shown that
fairness concerns are economically significant […]. Employers who violate rules of
fairness are punished by reduced productivity, and merchants who follow unfair
pricing policies can expect to lose sales.”
a. Levine (1993)59 surveyed 139 compensation executive at large US
corporations to discern their attitudes towards fairness in wage structure. He
found that the executives show strong preference to maintain constant relative
wages and keep a stable wage structure within career paths and within broad
occupational groups. In interviews these executives indicated reasons for
maintaining relative pay, including:
1. “There is a morale cost.... People complain.”
2. If you pay new workers more than senior ones, “You will have an
employee revolt on your hands,”
3. And employees start to “type up a resume, gossip.”
Even the companies that claimed to be market-driven agreed that changing
‘relative’ wages in response to market forces reduced morale and
increased turnover.
b. Isaac (2001)60 reviews literature and theory and finds support for the idea that
pay-for-performance schemes are not effective if they do not maintain fairness
(emphasis added):
“Labour is not a commodity. Efficiency has a different time dimension
and a different conceptual framework when dealing with the labour factor as
compared to capital equipment or raw materials. Labour is subject to
complex social and psychological forces. People are less receptive to
direction than is a piece of equipment. They react to their environment. The
pace and quality of work is critically dependent on their minds and hands. In

59

Levine, D. I., “Fairness, markets, and ability to pay: Evidence from compensation
executives,” The American Economic Review, Vol. 83, No. 5 (December 1993), pp. 1241-1259.
60

Isaac, J. E. , “Performance related pay: The importance of fairness,” Journal of Industrial
Relations, Vol. 43, No. 2 (June 2001), pp. 111-123.
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their working environment, they are not individuals but form part of a
group, open to group pressures and values. The place of work is not merely
part of an economic process but also a social institution. And so is the labour
market. In such a context, people develop norms about what is right and
wrong and fair. Work is not merely a way to earn income. It has meaning
in itself. The size of payment for work reflects on the worth, status and selfesteem of the person concerned. People measure their worth not in absolute
terms but relative to one another. But while the financial incentive is
important, people are also motivated by non-financial considerations.
This is not to deny the importance of the forces of supply and demand,
but merely to point out that they work differently for the labour market
compared to the commodity market; that the payment of a higher wage
may not necessarily induce a better performance; and that the
determination of wages in a workplace or an industry is not an
impersonal process but an administrative act in which norms of fairness
must be given substantial weight in the interest of productive efficiency.
These norms are not necessarily immutable but the strength of convention
into which notions of fairness are locked in, asserts itself when changes
occur.”
c. Similarly, according to Fehr et al. (2009)61
“[I]mportant labor market phenomena can be better understood if one takes
(a) the inherent incompleteness and relational nature of most employment
contracts and (b) the existence of reference-dependent fairness concerns
among a substantial share of the population into account. Theory shows and
experiments confirm that, even if fairness concerns were to exert only weak
effects in one-shot interactions, repeated interactions greatly magnify the
relevance of such concerns on economic outcomes.” (emphasis added)
d. In a leading textbook on this topic, Milkovich, Newman and Gerhart62 explain
that many different factors influence a company’s pay structure. These include,

61

Fehr, E., L. Goette and C. Zehnder, “A Behavioral Account of the Labor Market: The Role of
Fairness Concerns," Annual Review of Economics, (2009), pp. 355-384.

62

Gerhart, M., G. Milkovich and J. Newman, Compensation, New York: McGraw-Hill Irwin,
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but are not limited to, economic pressures, government policies and regulations,
stockholders’ attitudes and cultures and customs. “An important factor
influencing the internal pay structure is its acceptability to the employees
involved”. Employees judge the fairness of their organization's internal pay
structure by making several comparisons:


Comparing to jobs similar to their own (internal alignment),



Comparing their job to others at the same employer (internal alignment),
and



Comparing their jobs' pay against external pay levels (external
competitiveness).

e. A seminal article by Hamermesh (1975)63 develops a theoretical model that
demonstrates the implications of changing relative wages when there is
interdependence in utility (relative wage enters the utility function). “Increases in
one wage in a plant may affect the effort both of those workers receiving the
increase and of other workers who are aware of it.” The latter group reduces
effort. “The role of information is thus crucial to the analysis of
interdependence.” (emphasis added)
f. Di Maria & Metzler (2009)64 analyze wage structure amongst workers at
Luxemburg banks in 2002
“The main results indicate that some wage dispersion is needed to increase
efficiency among workers who have similar characteristics and a strong unequal
wage structure between workers having different job positions will adversely
affect efficiency in the bank.”

2011, Chapter 3.
63

Hamermesh, D.S., “Interdependence in the labour market,” Economica, (1975), pp. 420-429.

64

Di Maria, C. H., and S. Metzler, "Internal Wage Structure and Bank Performance in
Productivity in the Financial Services Sector," The European Money and Finance Forum Vienna
(2009), Chapter 9.
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“..[A]mong workers sharing similar characteristics some wage disparity will also
increase efficiency, but too much inequality will adversely affect efficiency and
may even lower efficiency.” (emphasis added)
g. Machin and Manning (2004)65 put competitive labor market theory to a test by
studying the market for care assistants in residential homes for the elderly on
England’s “sunshine coast.” The authors find that the wage structure deviates in
from what a theory of competitive labor market would predict. They find that
wage dispersion is small within firms, but large between firms; and that the wage
dispersion that is present does not seem to be explained by workers’ productivity
related characteristics.
C. Class-Wide Evidence That Includes Google’s “Big Bang” Response to
Facebook Demonstrates How Competitive Pressure From One Peer Firm Can
Move An Entire Pay Structure Overnight

50.

I described above how class-wide evidence is capable of showing that competitive
pressure—when it was not impeded by the agreements—did result in substantial
firm-wide compensation adjustments (including entry level and new employees66)
in order to both retain high-quality workers and ensure all workers felt equitably
compensated.

51.

The most particular example of how this could affect class-wide compensation is
Google’s Big Bang, which illustrates all three of these impacts in action. In 2010,
Google announced it would raise compensation to all employees by 10 percent and
made other systematic compensation changes to retain employees in the face of
poaching by Facebook. Defendants’ top executives recognized that competitors’
poaching could create important disruptions to the firms’ compensation structures.
As a result every Google employee (including new and entry level employees)

65

Machin, S. and A. Manning, "A test of competitive labor market theory: the wage structure
among elder care assistants in the South of England," ILRReview, Vol. 57, No. 3 (April 2004),
pp. 371- 385.
66

Defendants mischaracterize my testimony regarding the agreements’ impact on entry level and
new employees. Defendants’ Motion to Strike, November 12, 2012, pp. 4-5. As I described in
my Report and deposition, firm-wide compensation structures imply that there would have been
impact on all employees including entry level and new employees. Leamer Report, ¶ 120-134;
Leamer Deposition, pp. 159:3-163:18.
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D. Dr. Murphy is Incorrect that the Defendants’ Data Do Not Indicate that
Fairness and Internal Equity Matter

57.

Dr. Murphy’s fourth opinion is that “Defendants’ compensation structures are not
rigid,” but he supports this opinion by attacking only the conclusions I made from
my analysis of Defendants’ data, leaving intact the important economic theory and
decisive HR documents. Here is what Dr. Murphy has argued:75
(a) Defendants had (and exercised) substantial flexibility in
setting compensation of individual employees. Dr.
Leamer’s own model implies that employee compensation
was highly individualized, with large variations even within
particular job categories and between observationally
similar individuals (see Part IV.D, below). As I
demonstrate below, in every year and for each Defendant,
there is substantial dispersion in employee compensation
unexplained by Dr. Leamer’s model. Dr. Leamer has
shown that different jobs have different average
compensation, but not that increases in an individual’s
compensation resulting from a cold call results in higher
compensation for other employees.
(b) Dr. Leamer’s premise is also flawed. A rigid wage
structure, even if one existed, would not imply that a
change in compensation for one or more employees would
shift the entire structure, because the cost of increasing
compensation for one employee would be enormous (an
increase for all employees), and would be resisted. Thus,
Dr. Leamer’s theory makes no economic sense.
(c) Finally, Dr. Leamer’s analysis cannot distinguish the
impact he hypothesizes from an alternative hypothesis that
compensation of Defendants’ employees is broadly
determined by competition in a vast labor market, and that
adjustments
for
individual
employee’s
unique
circumstances (such as an attractive outside offer) are
highly individualized (see Part V.D.3, below).

75

Murphy Report, pp. 10-11.
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58.

The issue here is not some technical characterization of what is rigid and what is
not. The issue is whether internal equity concerns spread the anti-cold-calling
effects on compensation broadly across all or most members of the classes. I wrote,
“A firm’s commitment to principles of ‘internal equity’ is evidenced by the
imposition and maintenance of a somewhat rigid salary structure.”76 Dr. Murphy
attacks the regression equations that I used to describe the internal salary structure
but ignores the real question: do these firms spread the compensation suppressing
effects of the agreements broadly because of internal equity considerations?

59.

The information revealed from my analysis of Defendants’ employment records
adds to this body of evidence. However, my opinions regarding common impact do
not rest wholly or even mostly upon that analysis.

60.

I do not (and did not) suggest that the “Hedonic” regressions I reported were
conclusive proof that internal equity influenced compensation. They serve a
different purpose. Defendant documents reveal a top-down salary-setting
mechanism with overall increases in compensation determined by the top
management leaving limited salary setting discretion at lower levels of
management.77 Market driven compensation setting would be bottom-up with each
employee receiving compensation commensurate with their outside opportunities.
A bottom-up market-driven approach ignores internal equity completely. A topdown approach allows internal equity to play a role in the determination of
compensation. The hedonic regressions are a numerical representation of the topdown compensation setting which allows but does not necessitate internal equity to
play a role in salary setting.

61.

In various instances (Dr. Murphy’s Report, Declarations, questions during my
deposition), the Defendants have focused on the variability in the compensation
received by Class Members.78 This discussion misses the mark. Even in firms with
a “somewhat” rigid salary structure, it is to be expected that there will be salary
variations for people sharing a title. This is not a symptom of firms setting

76

Leamer Report, p.49.

77

Leamer Report, ¶ 121.

78

Defendants Opposition to Class Certification, November 12, 2012, pp. 7-8.
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compensation randomly but almost certainly reflects differences in the people and
jobs that are part of the compensation structure. In any regression analysis that
seeks to explain employee compensation, if sufficient data are available regarding
these employee and job characteristics, much of the dispersion would be explained,
and the unexplained dispersion (the residuals) would be small. However if
sufficiently detailed data are not available (such as is the case here) these residuals
will not necessarily be small.

62.

Defendants’ anecdotal examples purport to show that similar Class Members have
very disparate and unexplainable differences in compensation. However, even here
the effects of Defendants’ compensation structures are apparent. For example,
Defendants say
79
But Defendants fail to note that

63.

For example,

.

64.

Defendants also attach an example of Apple’s “
.”80 Again, common
objective factors, such as title, confirm a lack of variation among similar
employees. Thus,

65.

Figure 2 shows that for every firm in every year the prediction error of the common
factors regression is typically small (about 10 percent of total compensation and
often less). Figure 3 shows that there is strong overall relationship between Class
Members' actual total compensation and the total compensation predicted by the

79

Declaration of Danny McKell, November 12, 2012 at ¶ 10.

80

Declaration of Steven Burmeister, November 12, 2012, Ex. B.
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common factors regression, with these two figures generally having very high
positive correlations.
Figure 2: Common Factors Explain Most of Class Members’ Compensation Variation

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Figure 3: Hedonic Model’s Predictions Generally Are Highly Correlated with Actual
Compensation

66.

Though these firms may have provided certain managers limited and closely
supervised discretion over setting compensation levels, that discretion can be
exercised (and if not, corrected) in favor of internal equity (and given the
documents and other evidence here, very likely was). Discretion is not synonymous
with market-driven.
E. Dr. Murphy is Incorrect that My Hedonic Analysis of Named Plaintiffs’
Compensation Performed Poorly

67.

Although Dr. Murphy attempts to use the Named Plaintiffs to show that my hedonic
model of compensation performs poorly, actually the opposite is the case. Figure 4
below shows a scatter of predicted versus actual total compensation of the Named
Plaintiffs computed by Dr. Murphy. The hedonic model performs well in predicting
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the actual compensation of these individuals, especially considering the fact that as mentioned above—the model was only a partial representation of their salary
within each firm’s structure. The overall correlation between the Named Plaintiffs’
actual total compensation and total compensation predicted by the hedonic model is
0.75. To the extent these individuals might indicate room for improvement in that
model, it is with respect to the effect of changes in employment. The larger
differences in predicted versus actual are for observations where an employee
started a job or had a promotion (particularly Mr. Stover in 2008). Excluding those
observations the correlation is 0.94. This model could potentially be improved—
particularly if there were additional information for all the employees in the data
such as their education, skills, and performance. Those data would assist in filling
out the picture on the Defendants’ compensation structure.

68.

In addition, Dr. Murphy’s assessment that the hedonic regressions show
“overcompensation” for these individuals81 is a gross misapplication of these
equations, which were not designed to determine who was under-compensated and
who was over-compensated, or by how much. These regressions serve only to
demonstrate the salary structures that each Defendant used to determine
compensation. However, the CONDUCT regressions in my Report were designed
to determine the amount of over- or under-compensation by each Defendant
consequent to the agreements.82 Those CONDUCT regressions show only undercompensation during the conspiracy period.

81

Murphy Report, ¶ 93.

82

Leamer Report, Figure 20-24.
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class.” First, my reactions to Dr. Murphy’s comments need to be put into the
proper context.

71.

This allegedly illegal conduct did not target any single individual. This was an
attack on the information network that keeps employees informed of opportunities
elsewhere. Thus, in this case, damages are not determined at the individual level.
Damages are a consequence of being a part of the information network under
attack. Additional damages flow from the forces of internal equity that spread the
harm across all or most members of these firms. These additional damages are
completely a consequence of being a member of this group.

72.

I have thus used a regression model to demonstrate “a reliable Class-wide or
formulaic method capable of quantifying the amount of suppressed compensation
suffered by each class.” This regression model is a widely accepted way of
determining whether and by how much an act or a set of acts affected price or
compensation. It does so by contrasting statistically the periods in which illegal
behavior was occurring with the periods in which it was absent. The model
quantifies the harm to the class and in doing so tells us something about the
existence of that harm and its widespread nature.

73.

Tellingly, rather than casting aside this approach in favor of something else, Dr.
Murphy has conducted variations of my proposed model with the same approach in
mind. For example, by estimating the “conduct regression” using only the pre- or
post-agreement periods Dr. Murphy has attempted to evaluate the effect on class
member compensation by contrasting compensation of individuals during the
agreement period with compensation during periods absent of the agreements.84
Another example is Dr. Murphy’s “conduct regression” that uses the non-conduct
period in attempt to model the compensation absent the agreements, and then
estimates the but-for salaries during the period of agreements.85 With this model,
Dr. Murphy again has made an attempt to assess class-wide impact of the
agreements.

84

Murphy Report, Appendix 12A-12D.

85

Murphy Report, Appendix 13A-13B.
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74.

Although he takes the same approach that I have used, and apparently accepts it as a
valid way to proceed, Dr. Murphy has made critical errors in implementation of the
approach which led to him to a wrongful conclusion that the model shows no undercompensation to the classes. I describe this in detail below.

75.

A critical step in using the regression tool is to decide what control variables need
to be included in the equation. In my report, I have tried to suggest the seriousness
with which I approached this task partly by listing the categories of variables that
need to be included and by making sure that my regression includes variables from
each category: Conduct Effects, Persistence, Worker Effects, Industry Effects, and
Employer Effects. I have included variables that reflect each and every one of these
categories. My opinion is that the list of categories is complete and reliable as it
currently stands, though the choice of variables within each category is open to
further refinement (as it almost always is with non-experimental data).
A. Calculation of Standard Errors Assumes Statistical Independence

76.

Dr. Murphy has raised an issue of dependence among the observations and has
suggested the treatment of the problem is to correct upward the standard errors of
the coefficients. While Dr. Murphy has here identified an issue, he does not
propose an appropriate solution. One response would be to include a variable or
variables in the equation that account(s) for the correlation, leaving the residuals
adequately independent. The many variables that I have included to some extent
already accomplish this task.

77.

Incidentally, and importantly, there is nothing in my report that refers directly or
indirectly to the standard errors that Dr. Murphy is complaining about. This is
because I did not rely on them and my conclusions do not depend on them.

78.

The regression I estimated makes use of data on nearly 98,888 individuals and
assumes that the variables in the regression account for all of the similarities among
the individuals, and what is left over is uncorrelated “noise.” If what is left over is
correlated among individuals in a known way, then one treatment is to adjust both
the regression coefficients and the standard errors. I have written the words “one
treatment” so as not to lose track that the better treatment is to find a variable or
variables that are causing the correlated error structure.

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79.

If the correlations among individual observations are mostly positive as Dr. Murphy
suggests, then the standard errors would be adjusted upward, though it is impossible
to tell what would happen to the estimated coefficients, and the statistical
significance of selected variables can go up or down.

80.

Unfortunately, it is impossible for anyone to know what is the covariance matrix
that is needed to revise the estimates of my model. In addition, we cannot use these
data to estimate the covariance matrix. The huge covariance matrix that describes
the covariance of all pairs of individuals has 98,888x98,887/2 = 4,889,368,828
elements to be estimated from only ten annual observations at most on each
individual. That’s impossible. Instead, the right variables must be chosen to
describe how the covariances change across individuals.
1. Dr. Murphy Relies on a “Somewhat” Rigid Wage Structure in his Adjustment
of the Standard Errors.

81.

82.

86

If this issue is transformed from theory into practice there has to be some structure
imposed on the huge number of new parameters introduced by the vague idea of
correlation among the residuals. We need a careful analysis to decide on that
structure. To do this, Dr. Murphy relies on his observation that there are somewhat
rigid salary structures at Defendant firms. This is a rather important concession,
contradicting his claims elsewhere that salary structures are not rigid. Here, Dr.
Murphy criticizes me for failing to recognize how common elements determine
compensation of all individuals at all Defendant firms. As Murphy puts it: “He
[Leamer] failed to take into account when performing his statistical test that,
aside from the challenged agreements, employees at a firm are affected by
common factors that influence their compensation – e.g., a highly successful
movie at Pixar can result in large and unusual bonuses for all Pixar employees,
or a short-term reduction in the demand for PCs and the microprocessors that
power them can cause a decline in Intel’s revenue and profitability and lead
Intel to impose a wage freeze such as occurred in 2009.”86
In addition to this rejection of his own opinion, this explanation by Dr. Murphy
ignores the fact that revenues of both Intel and Pixar are included in my model, and
to the extent that movements in revenue account for common within-firm

Murphy Report, ¶ 124 (emphasis added).
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movements, then that is fully taken into account in my regression, and does not
need treatment of the type that Dr. Murphy is recommending. As an aside, Dr.
Murphy’s emphasis of these facts shows that he well understands the importance of
internal equity to the pay structures of the Defendants; the events he describes
cannot be reconciled with the “classical” model of economics he elsewhere
advocates where workers contract and re-contract at the whim of supply and
demand.
2. The Best Solution is to Include Variables that Eliminate the Correlation
Problem

83.

This connects to the most important point. If we can measure items like revenues
that create important commonalities across individuals, we should generally include
those variables in the equation and suitably adjust the coefficients on all the
variables as well as the standard errors. In the process we would remove the
observable commonalities from the residuals, perhaps making the unexplained part
of the model sufficiently uncorrelated across individuals that the independence
assumption of the regression technique is adequately satisfied. In other words, it
would be a mistake merely to adjust the standard errors—as Dr. Murphy suggests—
if the estimated coefficients would be substantially affected by the same issue.
Thus I included revenue variables in my model.
3. Dr. Murphy’s Employer-Year Fixed Effects Proves too much as it would
Invalidate Any Before-During-and-After Model

84.

Dr. Murphy has hypothesized that revenue increases at Intel and Pixar may cause
correlated increases in compensation at these two firms. But since my model
already includes revenues, Dr. Murphy’s follow-on to his criticism about the
standard errors in my model does not refer to revenues even though that was the
only reason cited for going down this path. Instead he opts for “employer-year”
effects, which are the basis for his adjusted standard errors. There are two basic
problems with these employer-year effects. First, these variables collectively stand
for some unnamed variable like firm revenue that explains why the residuals are
correlated. That variable should be named and utilized. Second, these variables
together seriously overload the model and make it impossible to estimate the
CONDUCT effect if all these variables were added to the model. Dr. Murphy has
not included the employer/year effects in the regression, but conceptually he has
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edged significantly in that direction when he adjusts the standard errors for
clustering based on years. The much better route is to find why the model does not
track the employer-year averages well enough to render this issue moot. This just
requires another well-chosen explanatory variable.
B. Dr. Murphy’s “Sensitivity Analysis” is Flawed

85.

Dr. Murphy purports to have performed a “sensitivity analysis” of the conduct
regression but in reality he has done no such thing. His “analyses” consist of (a)
clustering the standard errors, (b) adding the S&P 500 as a variable, and (c)
“disaggregating” the model.

86.

The large and statistically significant firm-year effects in the regression serve as
Murphy’s basis both for his clustered standard errors and for including the S&P
Stock Price in the equation.
“The test resoundingly rejects the hypothesis that there are
no such omitted firm-specific factors, and establishes the
need to use ‘clustered’ standard errors (or correct for that
correlation in other ways).”87
“A consequence of omitting important determinants of
firm-level compensation is that Dr. Leamer’s estimated
conduct effects will capture the impact of variables (other
than the challenged agreements) that differ systematically
between the conduct and non-conduct periods. To illustrate
the potential problem, I considered what would happen if I
simply add a variable measuring the performance of the
stock market from his regression, which potentially would
measure general economic and financial performance in the
economy that Dr. Leamer acknowledges likely affect
compensation (see his Figure 8 and related discussion).183
Exhibit 26 shows the results from adding the change in the

87

Murphy Report, ¶ 137.
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S&P 500 index as an explanatory variable in his conduct
regression.”88

87.

While it is wise to be looking for variables to include in the model rather than just
playing technical games with the standard errors, it is a major mistake to include the
S&P index. As Dr. Murphy noted in his deposition, there are literally thousands of
macroeconomic variables that might be included.89 Some of these variables are sure
to destroy the damage estimate. Locating such a destructive variable is not a
success. There has to be some wisdom in the selection of variables to be included.

88.

Why would the stock market variable be included at all? My model includes
employment in the information sector to capture the overall business cycle effects
and also includes firm revenues to capture the cycles afflicting each of the seven
Defendants. Dr. Murphy has not provided a persuasive reason that that the S&P
500 index captures cycle issues not already captured by these variables.

89.

A stock market index reflects the expected future revenue of the firms that comprise
the index. Included among the 500 firms in the S&P index are many firms (e.g.,
Goldman Sachs) that have no bearing on the Defendant’s compensation. Adobe
and Apple do not decide to increase their compensation when the prospects of
future revenue at Goldman Sachs improve. It might be more sensible to use the
stock market values of the firms themselves (see below) but the revenue variables in
my model should capture most of the information in these stock market valuations.

90.

Worse yet, Dr. Murphy has used the end-of-year value of the S&P Net Total
Revenue Index. If Dr. Murphy's intent was to control for the effect of “general
economic and financial performance in the economy”90 on compensation, then his
variable must adequately capture this effect and align the timing of the effect with
the timing of the dependent variable—in this case total annual compensation, which
is not determined until the last minute of the last trading day of the year—since
there are stock options, restricted grants and bonuses that accrue throughout the

88

Murphy Report, ¶ 138.

89

Murphy Deposition at 302:18-304:1:4.

90

Murphy Report, ¶ 138.
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year. This is a flawed variable which is not a logical candidate for inclusion in the
model.
Figure 5: December 31 Was Not a Key Date for Employee Compensation

Timing of Substantial Adobe Base Salary Adjustments
and Equity Compensation Payouts

Date

Percent of
Workforce Receiving
Base Salary Adjustment

Date

(Percent)
(1)
Jun-01
Jul-02
Jul-03
Jun-04
Jun-05
Jun-06
Mar-07
Mar-08
Mar-10
Mar-11

Percent of
Workforce Receiving
Equity Compensation Payout
(Percent)
(2)

95 %
95
94
94
95
96
95
96
93
91

Mar-01
Nov-01
Nov-02
Dec-03
May-04
May-05
Jun-06
Jan-07
Jan-08
Jan-09
Jan-10
Jan-11

92 %
33
22
47
43
95
65
67
68
51
49
57

Notes: The above lists all the months in which 10 % or more of the workforce
received a base salary adjustment or equity compensation payout from 2001-2011.
Values are rounded to nearest percentage.
Source: Defendants' employee compensation data.

91.

One critical problem is that the value of the S&P Index on any particular day does
not capture any fluctuations that occurred during the year. If, for example, the S&P
were either to rise or fall substantially the last days of December, that movement
cannot possibly have had an effect on all the compensation decisions during the
preceding year. The total compensation figure that is being explained here reflects
base salary as of December and all the bonus and stock payments accumulated over
the preceding year. Defendants, like many employers, adjust the salaries and hand
out supplemental compensation with a “schedule” that occurs in different points
throughout the year. Figure 5 shows the months in each year when large fractions of
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Adobe’s employees received their base salary adjustments or equity compensation.
There were only two instances where compensation adjustments for the largest
group of employees were made in December. For example, Adobe adjusted most of
its employees’ salaries in March, June, and July depending on the year. Adobe’s
stock grants were largely paid out in January, May, and November. Figure 6 and
Figure 7, below, show that these dates varied across Defendants and across years,
but were often earlier in the year. Thus, Dr. Murphy tries to explain an employee's
compensation at a point in time with the future level (unknown at the time) of the
stock market.

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In Figure 8 and Figure 9 below I show the results of a corrected version of Dr.
Murphy's sensitivity analysis with the growth of annual average value of S&P 500
Index in place of the end-of-year values. Contra Dr. Murphy, the original results
are not sensitive to this change. Dr. Murphy’s finding that the S&P end-of-year
appreciation changes my result is a great example of how sensitivity analysis can go
wrong.
Figure 8: Murphy Damages Model with the Average S&P 500 Index (All)

Annual Undercompensation Percentages
All-Salaried Employee Class
ADOBE
2005
2006
2007
2008
2009

-1.13%
-3.02%
-4.69%
-6.43%
-6.49%

APPLE
-1.13%
-3.15%
-4.94%
-6.79%
-6.90%

GOOGLE
-1.31%
-3.27%
-4.68%
-6.13%
-5.48%

INTEL
-1.19%
-3.37%
-5.36%
-7.23%
-7.17%

INTUIT

LUCASFILM
-8.58%
-10.34%
-12.17%
-14.05%
-14.16%

-2.30%
-4.00%
-4.03%

PIXAR
-7.36%
-8.56%
-9.73%
-10.62%
-9.66%

Source: Regression Estimates of Undercompensation to All-Salaried Employee Class.

Figure 9: Murphy Damages Model with the Average S&P 500 Index (R&D)

Annual Undercompensation Percentages
Technical Employee Class
ADOBE
2005
2006
2007
2008
2009

-1.62%
-4.44%
-6.73%
-9.15%
-8.82%

APPLE
-1.93%
-5.05%
-7.91%
-10.80%
-10.66%

GOOGLE
-2.97%
-7.02%
-9.13%
-10.97%
-8.83%

INTEL
-1.69%
-3.31%
-3.86%
-5.41%
-4.85%

INTUIT

-3.50%
-5.37%
-5.12%

LUCASFILM
-10.96%
-14.83%
-18.08%
-20.46%
-20.50%

PIXAR
-9.66%
-10.99%
-11.34%
-12.67%
-10.52%

Source: Regression Estimates of Undercompensation to Technical Employee Class.

93.

In addition, I have estimated the conduct regression models incorporating each
firm’s annual average stock price values. This variable has a much greater ability to
capture any remaining but pertinent effect of “general economic and financial
performance” potentially not captured by the revenue variables. Figure 10 and
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Figure 11 below show the undercompensation percentages derived from this
regression.
Figure 10: Murphy Damages Model with Defendants’ Stock Prices (All)

Annual Undercompensation Percentages
All-Salaried Employee Class
ADOBE
2005
2006
2007
2008
2009

-2.73%
-7.24%
-11.21%
-15.33%
-15.40%

APPLE
-2.66%
-7.41%
-11.62%
-15.97%
-16.27%

GOOGLE
-2.62%
-6.59%
-9.66%
-12.79%
-11.45%

INTEL
-2.78%
-7.92%
-12.65%
-17.06%
-16.94%

INTUIT

-5.44%
-9.47%
-9.59%

Source: Regression Estimates of Undercompensation to All-Salaried Employee Class.

Figure 11: Murphy Damages Model with Defendants’ Stock Prices (R&D)

Annual Undercompensation Percentages
Technical Employee Class
ADOBE
2005
2006
2007
2008
2009

-2.83%
-7.55%
-11.50%
-15.65%
-15.26%

APPLE
-3.04%
-8.16%
-12.72%
-17.34%
-17.22%

GOOGLE
-3.77%
-9.04%
-12.25%
-15.22%
-12.55%

INTEL
-2.89%
-6.93%
-9.83%
-13.37%
-12.75%

INTUIT

-5.83%
-9.39%
-9.19%

Source: Regression Estimates of Undercompensation to Technical Employee Class.

1. Dr. Murphy’s Study of Data Subsets Typifies What Happens When a Model is
Overloaded

94.

A misleading, but unfortunately common, tactic when attacking a regression model
is to overload the model with so many variables that it produces wild and
statistically insignificant results. This is exactly what Dr. Murphy has done in
several different ways.
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95.

Dr. Murphy has modified my proposed model of class-wide damages to test for
sensitivity to benchmark periods. First, he estimates the conduct regression using
only the pre-period as the benchmark. Then he estimates the conduct regression
using only the post-period as the benchmark.91

96.

In order for a regression model to have any ability to estimate an effect on
compensation, the model has to utilize an adequately informative benchmark
period. By modifying the regression model to include only pre-conduct (or postconduct) period as a benchmark, Dr. Murphy is trying to estimate the effect of the
conduct that occurred over five years by utilizing the experience of merely two nonconspiracy years. It is startling that Dr. Murphy would conduct such an exercise in
light of his understanding that the information in the data is limited.92

97.

Another “sensitivity” test he conducts is to “first estimate [the] conduct regression
using data outside [the] conduct periods, and then use the coefficient estimates to
predict compensation during the conduct period.”93 Again, Dr. Murphy puts an
enormous burden on a regression model to explain compensation using two
disjointed two-year periods. It is important to note that the regression model is
dynamic, i.e. incorporates the evolution of both total compensation and
macroeconomic factors in explaining compensation levels. Thus, to throw away
data in the middle of the time-period in hand (that also covers half of the entire
time-period) is not sensible and may lead to an inaccurate and misleading result.
2. Dr. Murphy's Partial Disaggregation by Defendant is Improperly
Implemented in a Manner Designed to Make the CONDUCT Variable
Perform Poorly

98.

91

Any econometric analysis rests on wisely chosen assumptions about similarities
among the observations. A standard similarity assumption is that an individual’s
responses to opportunities and stimuli are similar over time, and to the extent that
there are dissimilarities these are captured by control variables that change over

Murphy Report, ¶ 133.

92

"...[the dataset] effectively [has] fewer than 60 observations from which to estimate [the]
conduct variable" (parentheses omitted). Murphy Report, ¶ 123.

93

Murphy Report, ¶ 134.
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time such as age. A similarity assumption is what allows one to use observations of
a single individual at different points in time to estimate a model. Without that
similarity assumption, estimation of the model cannot proceed. The assumption of
similarity of individuals over time is entirely standard. It is also an entirely
standard assumption that two individuals in the same firm are similar, and two
individuals in different firms are also similar, in the sense that their dissimilarities
can be adequately controlled for in the model. This is what allows the estimation of
a model based on individual data taken from the same firm and from different firms.

99.

Depending on the context, the right place to position a data analysis is somewhere
between the extremes of perfect similarity and perfect dissimilarity. But if the data
set is large and informative enough, it does little damage to allow perfect
dissimilarity in the model, and then let the data decide how much dissimilarity
actually applies. However, the weaker and/or briefer is the data set the more reliant
we are on making the right similarity assumption. This data set we are studying is
too limited to throw away the similarity-across-firms assumption as Dr. Murphy
proposes.

100.

Dr. Murphy, in his critique regarding the correlation across individuals, says that
the dataset in reality is not as large as it seems. “Dr. Leamer’s sample contains over
500,000 individual observations, but fewer than 60 unique combinations of
employer and year (and thus effectively fewer than 60 observations from which to
estimate his conduct variable).”94 This should have been an alert to Dr. Murphy that
one can only go so far in including variables that could reliably identify the conduct
effect. By incorporating an additional 42 conduct interaction variables, Dr. Murphy
has overwhelmed the model, making the conduct effect virtually unidentifiable.95

101.

Complete disaggregation would require an entirely distinct model for each
Defendant. Per Dr. Murphy’s thinking about the effective number of observations,
this would reduce the number to at most 11 annual observations for each Defendant,
and it would be impossible to estimate a model of the scope of mine with so few
time-series experiments. Dr. Murphy has not gone that far. What he has done is to
disaggregate each and every variable in my model that is directly related to the

94

Murphy Report, ¶ 123.

95

Murphy Report, Appendix 9A-9B.
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CONDUCT effect, but he has left all other variables free of the Defendant effect.
This seems designed only to minimize artificially the CONDUCT variable, not to
approach sensibly the disaggregation issue.

102.

In my model I allow some amount of variability in the CONDUCT effect across
Defendants depending on their rates of hiring. In my model, I have allowed for the
lagged dependent variables to vary by Defendant because it became apparent that
the time series patterns were different, especially for the Google data. If I were
going to disaggregate one more effect it would be revenue, based on the idea that
these seven firms might have had different approaches to sharing their revenue
gains with their employees. In other words, disaggregation requires better judgment
than just throwing an excessive set of additional variables into the model, as Dr.
Murphy has done.
3. Firm-Wide Data Can Correct for the Correlation Problem

103.

As Dr. Murphy points out, the issue with correlation across individuals can be
solved in different ways.96 One of Dr. Murphy’s sources identifies “use group
averages instead of microdata” as one of three solutions to correlated
observations.97 The perils of disaggregation with this dataset can be clearly seen if
one estimates the model with an annual averaged dataset by employer-year.

104.

With these firm-level annual aggregates, as Dr. Murphy points out (if we reject his
earlier opinion regarding the absence of Defendants’ compensation structures),
there are only have 60 observations to work with. With only nine or fewer
observations per Defendant it is impossible to estimate a separate equation for each
Defendant. Expressed differently, with a fully disaggregated model the standard
errors of the coefficients are very large–infinite in fact. Inevitably, as we move in
the direction of full disaggregation, the standard errors are going to get larger and
larger. We thus need some wisdom to decide how much disaggregation is best.

96

“[The test] establishes the need to use ‘clustered’ standard errors (or correct for the correlation
in other ways.)” Murphy Report, ¶137.

97

Angrist, J. D. and J. Pischke, Mostly Harmless Econometrics, New Jersey: Princeton
University Press, 2009, Chapter 8.2, pp. 312-313.
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105.
106.

The challenge with estimating a model with few observations and many potential
variables is to choose wisely the similarity assumption. Using the employer-year
data we can allow the conduct effect to vary freely for each Defendant as proposed
by Dr. Murphy. We can also incorporate the firms’ stock prices to fully account for
“general economic and financial performance,” of which Dr. Murphy expressed
concern. However, with so few observations we have to make a judgment about
how many other variables we want to include. I have decided to limit the
persistence variables to one-lag, common across defendants, and to exclude the
trend variable, both for the same reason–this is a too short a times series to pick up
these effects. Figure 12 and Figure 14 show the corresponding conduct regression
model which uses annual average data at company-year levels instead of individual
employee observations. Here, a single conduct variable is interacted with each
employer, meaning that the effect of the agreement is allowed to be completely
distinct for each Defendant. In addition, I include the lag of annual average stock
prices of the companies, similar to Dr. Murphy’s use of the S&P 500 index.

107.

With a small sample size (30 degrees of freedom) the burden is too high to allow
statistical significance of the collection of all variables at conventional 95 percent or
90 percent levels. However, the T-values on the conduct coefficients are relatively
high and provide evidence that the negative coefficients did not occur by mere
chance. The p-value on all conduct coefficients is less than 0.5 which suggests that
it is more likely than not that the compensation of employees were decreased during
the period of the agreements. In addition, the test of joint significance of the
conduct effect shows statistical significance for both the All Employee Class and
the Technical Employee Class.

108.

98

Though the information in the employer-year data is limited, we can still extract
some useful information from it.

Figure 13 and Figure 15 contain the associated conduct effects from the model
showing under-compensation for all Defendants in all years.98

Pixar and Lucasfilm effects have not been computed due to unavailability of stock price data.
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Figure 12: Conduct Regression with Firm-Wide Compensation Data
All-Salaried Employee Class
Observation: Firm record in each year
Dependant Variable: Log(Average Annual Compensation/CPI)
Estimate
(1)

Variable

Conduct_ADOBE
Conduct_APPLE
Conduct_GOOGLE
Conduct_INTEL
Conduct_INTUIT
Log(Average Annual Compensation/CPI)(-1)
DLog(Information Sector Employment in San-Jose)
Log(Total Number of Transfers Among Defendants)
Log(Number of New Hires in the Firm/Number of Employees(-1))
Log(Annual Average Stock Price )(-1)
Log(Total Number of New Hires)
Log(Firm Revenue Per Employee/CPI) (-1)
APPLE
GOOGLE
INTEL
INTUIT
Constant
Observations
R-square
P-Value of the test for Joint Significance of Conduct Coefficients

-0.1369
-0.0675
-0.2045
-0.1401
-0.0510
-0.2491
0.1529
0.1516
0.0067
0.1609
-0.1627
0.3455
-0.2395
-0.1639
-0.3122
-0.0817
9.2323
47
0.961
0.006

St. Error
(2)

**
***
**
*
***
***
**
***
***
***
***

T-Value
(3)
(1)/(2)

0.0561
0.0552
0.0669
0.0547
0.0588
0.1315
0.2649
0.0358
0.0298
0.0330
0.0607
0.0999
0.0819
0.1020
0.0642
0.0511
0.9529

P-Value
(4)

-2.44
-1.22
-3.06
-2.56
-0.87
-1.89
0.58
4.23
0.23
4.88
-2.68
3.46
-2.92
-1.61
-4.86
-1.60
9.69

0.02
0.23
0.00
0.02
0.39
0.07
0.57
0.00
0.82
0.00
0.01
0.00
0.01
0.12
0.00
0.12
0.00

***

Note: (1) *** Significant at 1% level; ** Significant at 5% level; * Significant at 10% level
(2) Average Annual Compensation is computed as the mean of employee annual total compensation
Employee's total compensation is the sum of base annual compensation (in December), overtime pay, bonus,
and value of equity compensation granted
(3) Value of equity compensation is computed using the weighted average grant-date fair values for stock options and
restricted stock units from SEC Filings
(4) Firm Revenue Per Employee is computed as a ratio of global revenue to global number of
employees, both obtained from SEC Filings
(5) Pixar and Lucasfilm are omitted from these equations
(6) Defendant stock prices are computed as the annual average of the daily adjusted closing prices
Source: Defendants' employee compensation data; St Louis Fed Reserve; SEC Filings; Yahoo Finance

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Figure 13: Under-Compensation with Firm-Level Compensation Data

All-Salaried Employee Class
ADOBE
2005
2006
2007
2008
2009

-6.85%
-11.99%
-10.71%
-11.03%
-0.68%

APPLE
-3.37%
-5.90%
-5.27%
-5.43%
-0.33%

GOOGLE
-10.23%
-17.91%
-15.99%
-16.47%
-1.01%

INTEL
-7.00%
-12.26%
-10.95%
-11.28%
-0.69%

INTUIT
-5.10%
-3.83%
-0.32%

Source: Regression Estimates of Firm-level Undercompensation
to All-Salaried Employee Class.

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Figure 14: Conduct Regression with Firm-Level Compensation Data (R&D)
Technical Employee Class
Observation: Firm record in each year
Dependant Variable: Log(Average Annual Compensation/CPI)
Variable

Estimate
(1)

Conduct_ADOBE
Conduct_APPLE
Conduct_GOOGLE
Conduct_INTEL
Conduct_INTUIT
Log(Average Annual Compensation/CPI) (-1)
DLog(Information Sector Employment in San-Jose)
Log(Total Number of Transfers Among Defendants)
Log(Number of New Hires in the Firm/Number of Employees(-1))
Log(Annual Average Stock Price)(-1)
Log(Total Number of New Hires)
Log(Firm Revenue Per Employee/CPI) (-1)
APPLE
GOOGLE
INTEL
INTUIT
Constant
Observations
R-square
P-Value of the test for Joint Significance of the Conduct Coefficients

-0.1314
-0.1020
-0.1657
-0.1139
-0.0363
-0.3001
0.0384
0.1575
0.0491
0.1537
-0.1883
0.4845
-0.3421
-0.1707
-0.0807
0.0015
9.7441
47
0.931
0.093

St. Error
(2)

*
*

*
***
***
**
***
***

***

T-Value
(3)
(1)/(2)

0.0719
0.0731
0.0859
0.0704
0.0764
0.1576
0.3368
0.0464
0.0403
0.0390
0.0786
0.1366
0.1105
0.1303
0.0704
0.0641
1.2094

P-Value
(4)

-1.83
-1.40
-1.93
-1.62
-0.48
-1.90
0.11
3.40
1.22
3.94
-2.39
3.55
-3.10
-1.31
-1.15
0.02
8.06

0.08
0.17
0.06
0.12
0.64
0.07
0.91
0.00
0.23
0.00
0.02
0.00
0.00
0.20
0.26
0.98
0.00

*

Note: (1) *** Significant at 1% level; ** Significant at 5% level; * Significant at 10% level
(2) Average Annual Compensation is computed as the mean of employee annual total compensation
Employee's total compensation is the sum of base annual compensation (in December), overtime pay, bonus,
and value of equity compensation granted
(3) Value of equity compensation is computed using the weighted average grant-date fair values for stock options and
restricted stock units from SEC Filings
(4) Firm Revenue Per Employee is computed as a ratio of global revenue to global number of
employees, both obtained from SEC Filings
(5) Pixar and Lucasfilm are omitted from these equations
(6) Defendant stock prices are computed as the annual average of the daily adjusted closing prices
Source: Defendants' employee compensation data; St Louis Fed Reserve; SEC Filings; Yahoo Finance

Page 52
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CONFIDENTIAL

12/10/2012

Figure 15: Under-Compensation with Firm-level Compensation Data (R&D)

Technical Employee Class
ADOBE
2005
2006
2007
2008
2009

-6.57%
-11.16%
-9.79%
-10.20%
-0.22%

APPLE
-5.10%
-8.67%
-7.60%
-7.92%
-0.17%

GOOGLE
-8.28%
-14.08%
-12.34%
-12.87%
-0.28%

INTEL
-5.69%
-9.68%
-8.48%
-8.84%
-0.19%

INTUIT
-3.63%
-2.54%
-0.15%

Source: Regression Estimates of Firm-level Undercompensation
to Technical Employee Class.

C. Both Dr. Murphy’s and My Conduct Regression Analyses Demonstrate the
Feasibility of the Regression Approach

109.

V.

The analyses described in this report are performed for the purpose of
demonstrating the availability of proof and statistical methodologies common to
members of the All-Employee Class and the Technical Employee Class capable of
showing that all or nearly all members of each class suffered suppressed
compensation due to the agreements, and capable of quantifying that harm. I
understand that discovery has not yet been completed and that further evidence
might emerge that is relevant to my analysis. I reserve the right to consider any
such evidence and its impact, if any, on the analysis I have proposed.

Conclusion

110.

I therefore conclude that common proof, in the form of documents, data, economic
theory, and statistical methodologies, is capable of demonstrating that the
agreements artificially suppressed compensation of all or nearly all members of the
All-Employee Class and Technical Employee Class. I conclude further that reliable
Page 53
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CONFIDENTIAL

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Figure 16: Conduct Regression with Average S&P 500
Damages Model Sensitivity
Average Annual S&P 500 Price Index
All-Salaried Employee Class
Observation: Employee ID record in December of each year
Dependant Variable: Log(Total Annual Compensation/CPI)
Variable

Conduct * Age
Conduct * Age^2
Conduct * Log(Number of New Hires In the Firm/Number of Employees(-1))
Conduct
ADOBE * Log(Total Annual Compensation/CPI) (-1)
APPLE * Log(Total Annual Compensation/CPI) (-1)
GOOGLE * Log(Total Annual Compensation/CPI) (-1)
INTEL * Log(Total Annual Compensation/CPI) (-1)
INTUIT * Log(Total Annual Compensation/CPI) (-1)
PIXAR * Log(Total Annual Compensation/CPI) (-1)
LUCASFILM * Log(Total Annual Compensation/CPI) (-1)
ADOBE * Log(Total Annual Compensation/CPI) (-2)
APPLE * Log(Total Annual Compensation/CPI) (-2)
GOOGLE * Log(Total Annual Compensation/CPI) (-2)
INTEL * Log(Total Annual Compensation/CPI) (-2)
INTUIT * Log(Total Annual Compensation/CPI) (-2)
PIXAR * Log(Total Annual Compensation/CPI) (-2)
LUCASFILM * Log(Total Annual Compensation/CPI) (-2)
Log(Age) (Years)
Log(Age)^2
Log(Company Tenure) (Months)
Log(Company Tenure)^2
Male
DLog(Information Sector Employment in San-Jose)
Log(Total Number of Transfers Among Defendants)
Year (trend)
Log(Number of New Hires In the Firm/Number of Employees(-1))
Log(Total Number of New Hires)
Log(Firm Revenue Per Employee/CPI) (-1)
DLog(Firm Revenue Per Employee/CPI) (-1)
DLog(Average Annual S&P 500 Index/CPI) (-1)
APPLE
GOOGLE
INTEL
INTUIT
LUCASFILM
PIXAR
Location (State) Indicators
Constant
R-Square
Observations

St. Error

T-Value

(1)

1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
21.
22.
23.
24.
25.
26.
27.
28.
29.
30.
31.
32.
33.
34.
35.
36.
37.
38.
39.

Estimate

(2)

(3)
(1)/(2)

0.0063
-0.0001
0.0020
-0.1462
0.7019
0.7360
0.4957
0.6767
0.7009
0.6874
0.8040
0.2889
0.2636
0.3704
0.2929
0.2612
0.1777
0.1868
-0.3420
0.0374
0.0011
-0.0002
0.0031
1.4161
0.0699
-0.0015
0.0082
-0.2188
-0.0653
0.1495
0.0283
0.0459
1.0149
0.1389
0.1720
0.7927
0.0688
YES
YES

***
***
***
***
***
***
***
***
***
***
***
***
***
***
***
***
***
***
***
***

***
***
***
***
***
***
***
***
***
***
***
***
***
***

0.0005
0.0000
0.0008
0.0101
0.0055
0.0027
0.0017
0.0024
0.0058
0.0055
0.0364
0.0053
0.0027
0.0016
0.0024
0.0056
0.0053
0.0368
0.0415
0.0056
0.0050
0.0006
0.0005
0.0156
0.0023
0.0005
0.0009
0.0022
0.0032
0.0029
0.0042
0.0162
0.0174
0.0146
0.0194
0.0264
0.0482

13.2360
-13.3757
2.6888
-14.5355
128.7812
276.8118
291.0496
276.7756
121.2948
124.2378
22.0576
54.3200
96.0626
225.9483
123.0515
46.6472
33.6197
5.0733
-8.2341
6.6385
0.2292
-0.2769
5.6325
90.8003
30.1449
-3.2232
8.9620
-100.3416
-20.6351
51.6893
6.7791
2.8270
58.3255
9.4968
8.8857
30.0816
1.4272

0.926
508,969

Note: (1) *** Significant at 1% level; ** Significant at 5% level; * Significant at 10% level.
(2) Total Annual Compensation is computed as sum of base annual compensation (in December),
overtime pay, bonus, and value of equity compensation granted.
(3) Value of equity compensation is computed using the weighted average grant-date fair values for stock options and
restricted stock units from SEC Filings.
(4) Firm Revenue Per Employee is computed as a ratio of global revenue to global number of
employees, both obtained from SEC Filings. Lucasfilm revenues were obtained from PrivCo and public sources.
(5) Observations are restricted to cases in which there was no change in employer in the previous two years.
(6) S&P 500 Index is computed as the average of the daily adjusted close values.
Source: Defendants' employee compensation data; St. Louis Fed Reserve; SEC Filings; Yahoo Finance; PrivCo and public sources.

Page 55
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CONFIDENTIAL

12/10/2012

Figure 17: Conduct Regression with Average S&P 500 (R&D)
Damages Model Sensitivity
S&P 500 Price Index
Technical Employee Class
Observation: Employee ID record in December of each year
Dependant Variable: Log(Total Annual Compensation/CPI)
Variable

Conduct * Age
Conduct * Age^2
Conduct * Log(Number of New Hires In the Firm/Number of Employees(-1))
Conduct
ADOBE * Log(Total Annual Compensation/CPI) (-1)
APPLE * Log(Total Annual Compensation/CPI) (-1)
GOOGLE * Log(Total Annual Compensation/CPI) (-1)
INTEL * Log(Total Annual Compensation/CPI) (-1)
INTUIT * Log(Total Annual Compensation/CPI) (-1)
PIXAR * Log(Total Annual Compensation/CPI) (-1)
LUCASFILM * Log(Total Annual Compensation/CPI) (-1)
ADOBE * Log(Total Annual Compensation/CPI) (-2)
APPLE * Log(Total Annual Compensation/CPI) (-2)
GOOGLE * Log(Total Annual Compensation/CPI) (-2)
INTEL * Log(Total Annual Compensation/CPI) (-2)
INTUIT * Log(Total Annual Compensation/CPI) (-2)
PIXAR * Log(Total Annual Compensation/CPI) (-2)
LUCASFILM * Log(Total Annual Compensation/CPI) (-2)
Log(Age) (Years)
Log(Age)^2
Log(Company Tenure) (Months)
Log(Company Tenure)^2
Male
DLog(Information Sector Employment in San-Jose)
Log(Total Number of Transfers Among Defendants)
Year (trend)
Log(Number of New Hires In the Firm/Number of Employees(-1))
Log(Total Number of New Hires)
Log(Firm Revenue Per Employee/CPI) (-1)
DLog(Firm Revenue Per Employee/CPI) (-1)
DLog(Average Annual S&P 500 Index/CPI) (-1)
APPLE
GOOGLE
INTEL
INTUIT
LUCASFILM
PIXAR
Location (State) Indicators
Constant
R-Square
Observations

St. Error

T-Value

(1)

1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
21.
22.
23.
24.
25.
26.
27.
28.
29.
30.
31.
32.
33.
34.
35.
36.
37.
38.
39.

Estimate

(2)

(3)
(1)/(2)

0.0073 ***
-0.0001 ***
-0.0111 ***
-0.2043 ***
0.6785 ***
0.7207 ***
0.4390 ***
0.6425 ***
0.6598 ***
0.6715 ***
0.8388 ***
0.3008 ***
0.2554 ***
0.3620 ***
0.3159 ***
0.2944 ***
0.1046 ***
0.1484 **
-0.5788 ***
0.0686 ***
0.0206 ***
-0.0016 **
0.0066 ***
1.4834 ***
0.0839 ***
-0.0012 **
0.0139 ***
-0.2433 ***
-0.0417 ***
0.1344 ***
-0.0120 **
0.1156 ***
1.3634 ***
0.1430 ***
0.1581 ***
1.3259 ***
-0.0045
YES
YES

0.0007
0.0000
0.0010
0.0141
0.0073
0.0037
0.0022
0.0031
0.0085
0.0082
0.0694
0.0072
0.0038
0.0021
0.0030
0.0082
0.0075
0.0695
0.0587
0.0080
0.0068
0.0008
0.0008
0.0215
0.0032
0.0006
0.0013
0.0030
0.0043
0.0039
0.0059
0.0245
0.0259
0.0219
0.0316
0.0456
0.1040

10.8468
-10.8864
-10.8652
-14.4664
92.8530
197.2983
201.3110
209.3370
77.9206
82.2910
12.0842
42.0295
67.3782
172.2609
106.0838
35.9215
13.9643
2.1350
-9.8583
8.5921
3.0315
-2.0654
8.0584
68.9315
25.9499
-1.9713
11.0076
-81.5647
-9.6674
34.7738
-2.0435
4.7167
52.5895
6.5202
5.0062
29.0711
-0.0429

0.873
295,136

Note: (1) *** Significant at 1% level; ** Significant at 5% level; * Significant at 10% level.
(2) Total Annual Compensation is computed as sum of base annual compensation (in December),
overtime pay, bonus, and value of equity compensation granted.
(3) Value of equity compensation is computed using the weighted average grant-date fair values for stock options and
restricted stock units from SEC Filings.
(4) Firm Revenue Per Employee is computed as a ratio of global revenue to global number of
employees, both obtained from SEC Filings. Lucasfilm revenues were obtained from PrivCo and public sources.
(5) Observations are restricted to cases in which there was no change in employer in the previous two years.
(6) S&P 500 Index is computed as the average of the daily adjusted close values.
Source: Defendants' employee compensation data; St. Louis Fed Reserve; SEC Filings; Yahoo Finance; PrivCo and public sources.

Page 56
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456

Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page60 of 66
CONFIDENTIAL

12/10/2012

Figure 18: Conduct Regression with Average Defendant Stock Prices
Damages Model Sensitivity
Defendants Stock Prices
All-Salaried Employee Class
Observation: Employee ID record in December of each year
Dependant Variable: Log(Total Annual Compensation/CPI)
Variable

Conduct * Age
Conduct * Age^2
Conduct * Log(Number of New Hires In the Firm/Number of Employees(-1))
Conduct
ADOBE * Log(Total Annual Compensation/CPI) (-1)
APPLE * Log(Total Annual Compensation/CPI) (-1)
GOOGLE * Log(Total Annual Compensation/CPI) (-1)
INTEL * Log(Total Annual Compensation/CPI) (-1)
INTUIT * Log(Total Annual Compensation/CPI) (-1)
ADOBE * Log(Total Annual Compensation/CPI) (-2)
APPLE * Log(Total Annual Compensation/CPI) (-2)
GOOGLE * Log(Total Annual Compensation/CPI) (-2)
INTEL * Log(Total Annual Compensation/CPI) (-2)
INTUIT * Log(Total Annual Compensation/CPI) (-2)
Log(Age) (Years)
Log(Age)^2
Log(Company Tenure) (Months)
Log(Company Tenure)^2
Male
DLog(Information Sector Employment in San-Jose)
Log(Total Number of Transfers Among Defendants)
Year (trend)
Log(Number of New Hires In the Firm/Number of Employees(-1))
Log(Total Number of New Hires)
Log(Firm Revenue Per Employee/CPI) (-1)
DLog(Firm Revenue Per Employee/CPI) (-1)
DLog(Firm Stock Price/CPI) (-1)
APPLE
GOOGLE
INTEL
INTUIT
Location (State) Indicators
Constant
R-Square
Observations

St. Error

T-Value

(1)

1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
21.
22.
23.
24.
25.
26.
27.
28.
29.
30.
31.
32.
33.

Estimate

(2)

(3)
(1)/(2)

0.0059 ***
-0.0001 ***
0.0050 ***
-0.1641 ***
0.6791 ***
0.7447 ***
0.4969 ***
0.6765 ***
0.7036 ***
0.3128 ***
0.2563 ***
0.3677 ***
0.2933 ***
0.2640 ***
-0.3530 ***
0.0387 ***
-0.0066
0.0006
0.0024 ***
1.5922 ***
0.1345 ***
-0.0102 ***
0.0106 ***
-0.2832 ***
-0.1324 ***
0.2879 ***
-0.0635 ***
0.1072 ***
1.0906 ***
0.1434 ***
0.1166 ***
YES
YES

0.0005
0.0000
0.0008
0.0099
0.0054
0.0026
0.0017
0.0023
0.0057
0.0052
0.0027
0.0016
0.0023
0.0055
0.0409
0.0056
0.0049
0.0005
0.0005
0.0160
0.0020
0.0004
0.0011
0.0023
0.0037
0.0039
0.0024
0.0160
0.0172
0.0143
0.0189

12.6097
-12.7988
6.1651
-16.6155
126.6528
284.8534
294.8958
289.6740
123.4117
59.7396
95.2506
227.2142
129.1129
47.7498
-8.6315
6.9805
-1.3269
1.1477
4.3928
99.7455
67.2381
-29.1819
9.8170
-125.2556
-36.0708
74.6261
-26.4568
6.7153
63.4232
10.0217
6.1546

0.929
499,964

Note: (1) *** Significant at 1% level; ** Significant at 5% level; * Significant at 10% level.
(2) Total Annual Compensation is computed as sum of base annual compensation (in December),
overtime pay, bonus, and value of equity compensation granted.
(3) Value of equity compensation is computed using the weighted average grant-date fair values for stock options and
restricted stock units from SEC Filings.
(4) Firm Revenue Per Employee is computed as a ratio of global revenue to global number of
employees, both obtained from SEC Filings. Lucasfilm revenues were obtained from PrivCo and public sources.
(5) Observations are restricted to cases in which there was no change in employer in the previous two years.
(6) Firm Stock Price computed as the average of the daily adjusted close values.

Source: Defendants' employee compensation data; St. Louis Fed Reserve; SEC Filings; Yahoo Finance; PrivCo and public sources.

Page 57
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457

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CONFIDENTIAL

12/10/2012

Figure 19: Conduct Regression with Average Defendant Stock Prices (R&D)
Damages Model Sensitivity
Defendants Stock Prices
Technical Employee Class
Observation: Employee ID record in December of each year
Dependant Variable: Log(Total Annual Compensation/CPI)
Variable

Conduct * Age
Conduct * Age^2
Conduct * Log(Number of New Hires In the Firm/Number of Employees(-1))
Conduct
ADOBE * Log(Total Annual Compensation/CPI) (-1)
APPLE * Log(Total Annual Compensation/CPI) (-1)
GOOGLE * Log(Total Annual Compensation/CPI) (-1)
INTEL * Log(Total Annual Compensation/CPI) (-1)
INTUIT * Log(Total Annual Compensation/CPI) (-1)
ADOBE * Log(Total Annual Compensation/CPI) (-2)
APPLE * Log(Total Annual Compensation/CPI) (-2)
GOOGLE * Log(Total Annual Compensation/CPI) (-2)
INTEL * Log(Total Annual Compensation/CPI) (-2)
INTUIT * Log(Total Annual Compensation/CPI) (-2)
Log(Age) (Years)
Log(Age)^2
Log(Company Tenure) (Months)
Log(Company Tenure)^2
Male
DLog(Information Sector Employment in San-Jose)
Log(Total Number of Transfers Among Defendants)
Year (trend)
Log(Number of New Hires In the Firm/Number of Employees(-1))
Log(Total Number of New Hires)
Log(Firm Revenue Per Employee/CPI) (-1)
DLog(Firm Revenue Per Employee/CPI) (-1)
DLog(Firm Stock Price/CPI) (-1)
APPLE
GOOGLE
INTEL
INTUIT
Location (State) Indicators
Constant
R-Square
Observations

St. Error

T-Value

(1)

1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
21.
22.
23.
24.
25.
26.
27.
28.
29.
30.
31.
32.
33.

Estimate

(2)

(3)
(1)/(2)

0.0068 ***
-0.0001 ***
-0.0068 ***
-0.2093 ***
0.6547 ***
0.7255 ***
0.4402 ***
0.6492 ***
0.6566 ***
0.3255 ***
0.2508 ***
0.3647 ***
0.3099 ***
0.3034 ***
-0.5858 ***
0.0692 ***
0.0133 **
-0.0008
0.0064 ***
1.6607 ***
0.1384 ***
-0.0083 ***
0.0127 ***
-0.3042 ***
-0.0889 ***
0.2670 ***
-0.0750 ***
0.1724 ***
1.3815 ***
0.1377 ***
0.1070 ***
YES
YES

0.0007
0.0000
0.0011
0.0139
0.0072
0.0036
0.0022
0.0029
0.0084
0.0071
0.0037
0.0021
0.0029
0.0081
0.0581
0.0079
0.0068
0.0007
0.0008
0.0223
0.0027
0.0005
0.0015
0.0031
0.0051
0.0052
0.0033
0.0242
0.0256
0.0216
0.0311

10.1839
-10.2118
-6.2079
-15.0404
90.5135
200.5749
203.3944
220.4243
78.0298
45.9360
67.1304
174.9147
108.6765
37.2460
-10.0799
8.7670
1.9736
-1.1196
7.8292
74.6125
50.6807
-17.1490
8.4763
-97.8766
-17.4255
51.1627
-22.4884
7.1223
53.8927
6.3813
3.4413

0.878
290,089

Note: (1) *** Significant at 1% level; ** Significant at 5% level; * Significant at 10% level.
(2) Total Annual Compensation is computed as sum of base annual compensation (in December),
overtime pay, bonus, and value of equity compensation granted.
(3) Value of equity compensation is computed using the weighted average grant-date fair values for stock options and
restricted stock units from SEC Filings.
(4) Firm Revenue Per Employee is computed as a ratio of global revenue to global number of
employees, both obtained from SEC Filings. Lucasfilm revenues were obtained from PrivCo and public sources.
(5) Observations are restricted to cases in which there was no change in employer in the previous two years.
(6) Firm Stock Price computed as the average of the daily adjusted close values.

Source: Defendants' employee compensation data; St. Louis Fed Reserve; SEC Filings; Yahoo Finace; PrivCo and public sources.

Page 58
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458

Case5:11-cv-02509-LHK Document518-5 Filed10/07/13 Page62 of 66
CONFIDENTIAL

12/10/2012

Exhibit 1
List of Additional Materials Relied Upon

Pleadings and Orders

Date

Defendants' Notice of Motion and Motion to Strike the Report of Dr. Edward E. Leamer

11/12/12

Opposition to Plaintiffs' Motion for Class Certification

11/12/12

Declarations
Burmeister, Steven

11/12/12

Galy, Chris

11/09/12

Maupin, Michelle

11/12/12

McAdams, Lori

11/12/12

McKell, Danny

11/12/12

Morris, Donna

11/09/12

Vijungco, Jeff

11/09/12

Wagner, Frank

11/09/12

Depositions and Exhibits

Date

Leamer, Edward

10/26/12

Murphy, Kevin M.

12/03/12

Zissimos, Pamela

11/13/12

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Exhibit 1
List of Additional Materials Relied Upon

Expert Reports

Date

Expert Report of Edward E. Leamer, PhD

10/01/12

Expert Report of Professor Kevin M. Murphy, PhD

11/12/12

Publicly Available Materials
Angrist, J. D. and J. Pischke, Mostly Harmless Econometrics, New Jersey: Princeton University Press, 2009, Chapter 8.2.
Creswell, J. W., and V. L. Plano Clark, Designing and Conducting Mixed Methods Research, SAGE Publication: 2007, Chapter 6.
Creswell, J. W., Research Design: Qualitative, Quantitative, and Mixed Methods Approaches, SAGE Publication: 2009, Chapter 9.
Di Maria, C. H., and S. Metzler, "Internal Wage Structure and Bank Performance in Productivity in the Financial Services Sector,"
The European Money and Finance Forum Vienna (2009), Chapter 9.
Fehr, E., L. Goette and C. Zehnder, “A Behavioral Account of the Labor Market: The Role of Fairness Concerns,"
Annual Review of Economics , (2009).
Gerhart, M., G. Milkovich and J. Newman, Compensation, New York: McGraw-Hill Irwin, 2011, Chapter 3.
Hamermesh, D.S., “Interdependence in the labour market,” Economica , (1975).
Isaac, J. E. , “Performance related pay: The importance of fairness,” Journal of Industrial Relations , Vol. 43, No. 2 (June 2001).
Kahneman, D., Thinking, Fast and Slow, Farrar, Straus and Giroux, 2011.
Levine, D. I., “Fairness, markets, and ability to pay: Evidence from compensation executives,” The American Economic Review ,
Vol. 83, No. 5 (December 1993).
Machin, S. and A. Manning, "A test of competitive labor market theory: the wage structure among elder care assistants in
the South of England," ILRReview , Vol. 57, No. 3 (April 2004).

Page 2 of 5

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Exhibit 1
List of Additional Materials Relied Upon

Piore, M. J., “Qualitative Research: Does It Fit In Economics?,” European Management Review , (2006) 3, 17-23.
Rees, A. "The Role of Fairness in Wage Determination," Journal of Labor Economics , 1993, Vol. 11, No. 1, pt. 1.
Stiglitz, J., “Information and the Change in the Paradigm in Economics,” The American Economic Review , Vol. 92, No. 3 (June 2002).
"The Prize in Economic Sciences 2012," Nobelprize.org., December 10, 2012,
http://www.nobelprize.org/nobel_prizes/economics/laureates/2012/.
"The Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel 2002," Nobelprize.org., December 10, 2012,
http://www.nobelprize.org/nobel_prizes/economics/laureates/2002/.

Documents
Adobe
ADOBE_002764
ADOBE_008098
ADOBE_008398
ADOBE_008692
ADOBE_009327
ADOBE_016608

-

ADOBE_002765
ADOBE_008099
ADOBE_008399
ADOBE_008693

- ADOBE_016655

Apple
231APPLE010841 - 231APPLE010843
231APPLE055294 - 231APPLE055305
231APPLE056385 - 231APPLE056386

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Exhibit 1
List of Additional Materials Relied Upon

231APPLE081072 - 231APPLE081075
231APPLE094041 - 231APPLE094067
Google
GOOG-HIGH TECH-00009270
GOOG-HIGH TECH-00009454
GOOG-HIGH TECH-00036370
GOOG-HIGH TECH-00038253
GOOG-HIGH TECH-00194984
GOOG-HIGH TECH-00195005
GOOG-HIGH TECH-00195364
GOOG-HIGH TECH-00210276
GOOG-HIGH TECH-00233026

-

GOOG-HIGH TECH-00009276
GOOG-HIGH TECH-00009458
GOOG-HIGH TECH-00036461
GOOG-HIGH TECH-00038274
GOOG-HIGH TECH-00194985
GOOG-HIGH TECH-00195007
GOOG-HIGH TECH-00195365
GOOG-HIGH TECH-00210276
GOOG-HIGH TECH-00233057

Intel
76512DOC000025
76512DOC000926
76526DOC000714
76582DOC000902
76616DOC005974

- 76512DOC000026
- 76512DOC000943
- 76582DOC000922
- 76616DOC005981

Page 4 of 5

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Exhibit 1
List of Additional Materials Relied Upon

Intuit
INTUIT_003008 - INTUIT_003011
Lucasfilm
LUCAS00004721 - LUCAS00004753
LUCAS00035991 - LUCAS00035992
LUCAS00036013 - LUCAS00036014
Pixar
PIX00009271 - PIX00009272
PIX00023020 - PIX00023021

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IN THE UNITED STATES DISTRICT COURT
FOR THE NORTHERN DISTRICT OF CALIFORNIA
SAN JOSE DIVISION
CONFIDENTIAL – TO BE FILED UNDER SEAL
SUBJECT TO PROTECTIVE ORDER

IN RE: HIGH-TECH EMPLOYEES ANTITRUST
LITIGATION

No. 11-CV-2509-LHK

_____________________________________
THIS DOCUMENT RELATES TO:
ALL ACTIONS

SUPPLEMENTAL EXPERT REPORT OF EDWARD E. LEAMER, PH.D.

May 10, 2013

[REDACTED]
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TABLE OF CONTENTS

I. 

Introduction, Assignment, and Summary of Conclusions ..........1 

II. 

Defendants’ Use of Compensation Structures............................4 

III.  Empirical Methodologies for Exploring the Somewhat Rigid
Salary Structure ........................................................................6 
A.  Choice of Aggregation Level .............................................................. 6 
B.  Correlation Analysis of Compensation Structure ................................... 7 
C.  Regression Analysis of Compensation Structure ................................... 7 

IV. 

Results of Title Based Correlations and Multiple Regressions ..10 
A.  Title-by-Title Correlation Analysis of Compensation Structure .............. 10 
B.  Title-by-Title Multiple Regressions ................................................... 14 

V. 

Decile Based Correlations and Multiple Regressions ...............18 
A.  Decile Based Correlation Analysis .................................................... 18 
B.  Decile Based Multiple Regression Results .......................................... 20 

VI. 

Additional Exploration of Adobe Correlations ..........................22 
1.  Adobe Correlation Results .......................................................... 22 
2.  Headcount Matters for Interpreting Correlations ............................ 24 
3.  Correlations ............................................................................. 25 
4.  Outliers ................................................................................... 26 

VII.  Internal Versus External Forces .............................................. 29 

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I.

5/10/2013

Introduction, Assignment, and Summary of Conclusions

1.

I have been asked by counsel for Class Plaintiffs in this matter to respond to the
following questions regarding my prior analysis and further analysis that can be
conducted based on the available data in this case. I have been asked to focus
my response on the employees belonging to the proposed Technical, Creative
and R&D Class (“Technical Class”) identified in my initial report.

2.

Question #1: Does the total compensation of Technical Class employees in
specific job titles move together over time, further confirming the existence of a
somewhat rigid pay structure at each Defendant?

3.

Answer: When asked in the deposition (p283) “Could a nonrigid wage
structure, as you've defined it, lead to parallel lines?” I responded to what I
thought to be a hypothetical with “Yes, it could.” I should have added that this
would require highly unusual external labor market conditions which dictated
the parallel movements of vast numbers of titles. Markets typically are not so
orderly, and prices of, for example, gold, silver, copper and zinc do not normally
move in parallel. For that reason, I regard the parallel movements of
compensation for so many titles not only to be consistent with a “somewhat
rigid wage structure” but also evidence specifically in favor of the hypothesis
that internal equity played an important role in determining compensation in all
these firms. In this report, I confirm this opinion with two additional empirical
studies. I have estimated regression models that allow me to separate the
contributions of internal and external forces, and found that the internal forces
are evident but the external forces are not. I have also compared average
compensation for the Technical Class of titles and the non-technical employees
for all the defendants. I found that the compensation curves of these two
groups within each firm are highly parallel while the compensation curves for
the same group from two different firms move in a much more disparate
way. This again is saying that the internal forces are evident but the external
forces are more difficult to detect.

4.

In this Report, I present correlations that compare the movement over time of the
average compensation of each title with the average compensation of the firm’s
Technical Class. To accommodate titles that cannot be accessed on a title-byPage 1
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title basis due to insufficient data (approximately 63 percent of Technical Class
titles, but representing just 6 percent of Class Period employee-years), I also
analyzed correlations of relatively narrow groups of employees (each comprising
approximately a tenth of the Technical Class employees of that firm). These
correlations are computed for all titles, not just 20. They reveal that there is
large amount of co-movement of compensation among most of the Technical
Class titles of each defendant. These correlations are consistent with a topdown budgeting method in which all members of the firm in any given year
receive a common compensation increment, which is adjusted somewhat by title
and possibly by individual within the title depending on specific circumstances.
The evident, substantial, common, firm-wide component of compensation is
what creates what I previously called a “somewhat rigid” salary structure, which
allows the effects of the anti-cold-calling conspiracy to spread broadly across
each firm.
5.

Question #2: Do the data show additional evidence that internal factors such
as internal equity partly drove the Defendants’ compensation structures, as
opposed to only external market forces?

6.

Answer: I have analyzed a model of sharing of compensation effects, title by
title, within Defendant firms relative to movements of other Technical Class
employees compensation. Again, to accommodate titles that cannot be accessed
title-by-title (approximately 70 percent of Technical Class titles, but representing
just 8.4 percent of Class Period employee-years), I also analyzed the
compensation of relatively narrow groups of employees against the
compensation of the overall Technical Class employees.

7.

Specifically, I report below estimated multiple regression models that explain the
year-by-year increases in average compensation at the title level in terms of four
explanatory variables: (1) increases in average Technical Class compensation; (2)
the previous year’s ratio of average Technical Class compensation divided by the
average title compensation; (3) the previous year’s ratio of firm-wide average
revenue divided by the average title compensation; (4) the percent change in
software jobs in the San Jose-Sunnyvale-Santa Clara Metropolitan Statistical
Area (hereafter: San Jose MSA).
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8.

I find that the vast majority of individuals fall within titles or groups that show
1) positive contemporaneous sharing of compensation effects, and 2) sharing
across time that would spread gains in compensation across other job titles.
This is consistent with my previous opinion that all or almost all Defendants’
employees would have been impacted by the non-compete agreements.
Furthermore, the sharing of gains over time strongly indicates the existence of
an internal sharing force driving the structure of class member compensation,
rather than only external market forces.

9.

Question #3: Do the data show the existence of large groups of class
members who necessarily would not have been harmed by a restriction on coldcalling?

10.

Answer: No. I have performed the above-mentioned statistical analyses
separately for distinct subgroups of employees grouped by compensation level. I
do not find persuasive evidence to suggest that there are sizeable groups whose
compensation might have been disconnected from Defendants’ somewhat rigid
compensation structure. The correlation and regression analysis I performed in
this regard show ripple and spillover effects across employees in very different
roles. The analysis shows that when each title or group is studied separately, on
a case-by-case basis, it is found that, compensation almost always moves with
the collection of other titles or groups. All these groups, no matter how much
they differ in the job titles they contain, are found to be tied closely together.

11.

Question # 4: Is it possible to identify and exclude from the Technical Class
job titles based on a lack of these positive correlative relationships?

12.

Answer: No. Although the vast majority of titles exhibit strong positive
correlations with the overall Technical Class, there certainly are exceptions. One
might consider titles with negative correlations with the overall Technical Class
to be candidates for exclusion from the class. However, this is not justified
statistically because statistical variability can cause some negative correlation
estimates among the thousands of titles even if all the true correlations are
positive. An appropriate statistical model for this kind of data allows some
pooling of evidence across titles, and when this is done the analysis indicates
that corrected estimated of many of these negatives is positive. In other words,
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it matters for interpreting the evidence about each title that the vast majority of
estimated correlations are positive.
13.

II.

In sum, the statistical analysis I conduct here--in conjunction with the economic
and econometric evidence in my original reports--supports my original finding
of a somewhat rigid pay structure at each Defendant that would have
transmitted the effects of the agreements broadly, including throughout the
Technical Class.

Defendants’ Use of Compensation Structures

14.

Most, if not all, of these defendants subscribe to services that are intended to
provide them information about “market” prices for various jobs. Such
information helps them keep compensation packages in line with the external
opportunities, with or without the imminent threat of loss of an employee.
However, these external sources provide broad industry averages with limited
relevance and reliability. Regardless of what these services suggest, their
information cannot compare with the information conveyed by an actual
outside offer. That can ring off a loud alarm that is heard all the way up to the
CEO.

15.

The information by an outside offer or even a cold call can stimulate a response
by management that can go much beyond the specific individual directly
affected. A chain of similarities can transmit a bump in compensation for a
single individual broadly across a firm for two reasons. First, when
management becomes aware of an attractive outside opportunity for one
individual this may make management aware also of the implicit competitive
threat to similar individuals and management may feel it wise to make a
preemptive move against that threat by an increase in compensation for these
newly-threatened similar employees. Though the “market” does not require a
bump in compensation for these similar individuals until they actually receive an
outside offer, preemptive action can minimize the disruption to employee
loyalty that might occur when an employee discovers that he or she had been
“unfairly” undercompensated. A broad preemptive response is completely
analogous to salary increases that are tied to information provided by
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employment services regarding the compensation offered by the “market.”
These responses are broad and not necessarily individual-based.
16.

Similarity in worth is one reason why salaries can be tied together. Fairness is
the second reason why a bump in compensation for a single individual can be
transmitted broadly across a firm. A critical problem with “market-based”
individual compensation is that the productivity of each worker in most salaried
jobs is difficult to determine with accuracy, yet the range of achieved
productivity can be broad. Firms need to use HR policies that encourage high
levels of productivity. The highest levels of productivity come from contented
employees who are committed to the mission of the enterprise. In order to
maintain or to increase the contentment and commitment, it is essential for
management to treat employees “fairly.” As discussed in the paragraph above, a
strictly market view of employee compensation doesn’t require an increase in
salary of any individual until an outside threat actually materializes, but the force
of “fairness” can necessitate preemptive increases in compensation. In addition,
employees are likely to have their own views of job and performance similarity,
and these employees can have their productivity adversely affected if they
perceive that some employees are receiving “unfairly” high compensation
compared with them.

17.

Fairness is a matter of personal opinion and there is no sure way to know
exactly who feels equivalent to the employee who got that bump in
compensation and who doesn’t really care. The title and grade structure of
compensation may reflect management’s views of what is fair and it may
influence the perception of similarity that determines employee fairness beliefs.
This is the reason why companies tend to follow guidelines laid out in terms of
salary ranges, so employees can be assured that their compensation falls within
reasonable range of their colleagues.

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III.

5/10/2013

Empirical Methodologies for Exploring the Somewhat Rigid
Salary Structure
A. Choice of Aggregation Level

18.

The data set I explore is composed of compensation records of salaried
individuals on the payrolls of the Defendants. These individuals are grouped by
the Defendants by title and (for some of the Defendants) the titles are grouped
by grade. Based on instructions from counsel regarding the employees in the
Class, except for Lucasfilm I limit the inquiry to the titles that have been
identified as Technical Class titles.1

19.

These data could be studied at the individual level, at the title level or some
more aggregated groups. I have chosen to work first with the title averages,
because the individual data is likely to be dominated by forces that operate at
the individual level, which can make it difficult to detect the firm wide effects
including the spread of the anti-cold-calling agreements broadly across the
firms. Averaging across individuals in a title can average out the individual
effects, thus making the firm-wide effects more transparent. In addition, a titlelevel analysis provides a clearer perspective on the compensation structures the
documentary evidence shows Defendants used to manage their many employees
and maintain internal equity among their employees.

20.

I have discovered that the title-by-title analysis works well for many titles but
there are some titles that were used only briefly, and there are other titles that
are sparsely populated and that seem much influenced by the idiosyncratic
individual behavior which still masks the firm-wide effect that I am seeking to
estimate. The data set contains only eleven annual observations which is
adequate for the statistical work, but not plentiful. Titles that have fewer annual
observations tend to produce what statisticians call “statistically insignificant”
results, meaning the data sets are too small to yield accurate estimates. This is
particularly troublesome for Apple which had a title restructuring in 2005 and

Because Lucasfilm did not provide title data prior to 2006, there are insufficient years of data unless the
inquiry is expanded to cover all Lucasfilm employees. Hence, the analysis presented below is limited to
Technical Class for all Defendants, expect Lucasfilm, for whom it applies to all employees.

1

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for Lucasfilm which did not provide titles prior to 2006. In addition titles that
include just a few individuals may not benefit much from the averaging across
individuals and furthermore, unlike the individual data, the title compensation
for sparsely populated titles can vary wildly as individuals come and go. I give
some examples below of Adobe titles with highly variable headcounts and
highly variable median ages.
21.

To deal with the limitations of the title-by-title data, I also include the same type
of statistical work but applied to ten groups of titles in each firm. I have formed
the ten groups of titles by ordering the titles by average base compensation and
then splitting the titles into ten deciles (based on the number of employeeyears).2
B. Correlation Analysis of Compensation Structure

22.

Economists often look to correlation coefficients to measure statistically how
closely different variables move together. Correlation coefficients range in
absolute value from 0 to 1. One indicates perfect correlation, zero indicates no
relationship. The sign on the correlation indicates whether or not the series in
question move in the same direction. I begin my analysis of Defendant
compensation structures with compensation correlations.

23.

There are two types of correlations relevant for determining if the
compensation movements of two series are similar: correlation of compensation
levels and correlations of compensation changes. The correlations of the log of
the levels of compensation emphasize longer run movements and the
correlations of the change in the log of the levels focus on year-by-year
movements.
C. Regression Analysis of Compensation Structure

24.

Correlation of title compensation and class compensation could come from
sharing effects but could also come from third variables that operate on both

For several Defendants, certain large titles made splits into ten groups impractical. In those cases a smaller
number of groups was used.

2

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title and class compensation at the same time, for example, “market forces.” To
confirm the existence of a somewhat rigid compensation structure revealed by
my correlation analysis, I examine (company by company) a multiple regression
model which forces the class compensation to compete with other variables as
an explanation of title compensation.
25.

This regression model explains increases in title average real (inflation adjusted)
total compensation and includes the increase in class average real total
compensation as one of four explanatory variables.3 By including the increase
in class compensation in the equation, the regression encompasses the
correlation analysis of these two variables. In the multiple regression setting,
this variable allows us to determine at a particular defendant the extent to which
title and class compensation move together, after controlling for the other variables in
the equation, in particular, after controlling for “market forces.” If the coefficient
of this variable were equal to one, then the employee would inherit 100 percent
of the class compensation changes and in that sense the two would be closely
tied together. This is the first sharing effect.

26.

The regression model includes a second sharing variable, which is the ratio of
class compensation to title compensation in the previous year. While the first
sharing effect measures the extent to which the two compensation levels move
together, the second measures the extent to which corrective action is taken at
the company when they move apart. If the coefficient is positive on this
variable it means that following periods in which the class average
compensation at the company is abnormally high compared with the title, the
title tends to get a special increase in compensation to bring it back in line with
the class

27.

The regression model requires both of these sharing variables to compete
against two other determinants of title compensation at the company. One of
these other variables is the previous year’s ratio of firm-wide average revenue
divided by the average title compensation. This variable allows us to determine

For each title regression I exclude from the class average real total compensation, the compensation of the
title itself.

3

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which titles, if any, share increases in firm revenue overall. It might be expected
that critical technical and creative workers are the ones who would have revenue
sharing relationships with their firms since they may have an accentuated effect
on the firm’s success.
28.

The fourth variable is the percent growth in software jobs in the San Jose- MSA.
This the external job market variable which is intended to reflect how hot or
cold was the technical job market generally, not just in the San Jose MSA.

29.

I illustrate this regression in Figure 1, as estimated for one Intel title.4 In this
example, the two coefficients for the two sharing variables are positive, meaning
that workers with this title can expect to receive a compensation increase if 1)
there are general increases in the compensation of other Technical Class titles at
the firm, and 2) a title that received a relatively small percent increase relative to
other Technical Class titles at the company last year will tend to receive a larger
increase in subsequent years. This indicates a positive sharing and internal equity
effect. Both the contemporaneous and lagged coefficients suggest that internal
equity forces move in a fashion that helps align worker’s compensation together
with that of employees in other roles at the firm.

As mentioned before this regression is estimated separately for each title and company. Titles that do not
afford a sufficient number of observations (6 observations, or 7 consecutive years) are treated as ‘Not
Estimated’ and are excluded from the coefficient distribution calculations presented in this report.

4

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Figure 1
Illustrative Example of Compensation Sharing Regression Model
Intel Named Plaintiff Title SOFTWARE_ENGINEER_7

Variable

Coefficient

Std.-Error

T-value

P-value

(1)

(2)

(3)

(4)

(5)

0.784 ***

0.064

12.238

0.000

0.251 *

0.098

2.562

0.051

-0.032

0.094

-0.346

0.743

0.092

0.126

0.731

0.498

-0.223

0.541

-0.411

0.698

Dependant Variable
DLog(Title Average Annual Total Compensation)
Contemporaneous Effect Variable
DLog(R&D Average Annual Total Compensation)
Lagged Effect Variable
Log( (R&D Avg Annual Total Comp (-1) /
( Title Avg Annual Total Compensation (-1)
External Forces Variables
Log( (Firm Revenue Per Employee (-1) /
( Title Avg Annual Total Compensation (-1)
DLog( San-Jose Information Sector Employment)
Constant
Observations
R-squared

10
0.986

Note: (1) *** Significant at 1% level; ** Significant at 5% level; * Significant at 10% level.
(2) Title Average Compensation is computed as the average of title employee's annual total compensation.
R&D Avg Total Comp is computed over all Technical, Creative and R&D employees other than the tilte itself
(3) All Compensation Variables are Inflation Adjusted
Source: Defendants' employee compensation data

IV.

Results of Title Based Correlations and Multiple Regressions
A. Title-by-Title Correlation Analysis of Compensation Structure

30.

The correlations for all Defendants are reported in Exhibit 1 (Adobe) and
Exhibit 2 (other Defendants). Below I will discuss the Adobe results in detail,
but here it is enough to summarize the overall results with Figure 2 and Figure
3, which indicate the fractions of titles (weighted by employee years) with
positive correlations between title compensation and Technical Class
compensation at the same firm, restricted to titles with six or more annual
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observations. The titles with five or fewer tend to produce a more extreme
distribution of correlations.
31.

Although there are some negative estimated correlations, that does not mean
that any true correlations are negative. These estimates are computed with
statistical error which is large enough to produce some negative estimates
among the thousands of titles included even if all true correlations were positive.

32.

Moreover, the fact that the vast majority of cases are positive is strong support
for the conclusion that all the true correlations are positive. There are formal
statistical methods that allow pooling of results across titles based on the
assumption that the titles probably have similar correlations. These methods
would shrink the estimates for each title toward the mean across all titles, which
is of course positive. Once this shrinkage is done, the results indicate that for
many of these negatives the corrected results will be positive, strengthening the
conclusion that all titles in the class share movements with the class overall.
Figure 2: Large Share of Change Correlations are Positive

Compensation Change Correlation by Titles
100

Share (%)

80

60

40

20

0

ADOBE

APPLE

GOOGLE
Negative

INTEL

INTUIT

PIXAR

Positive

Source: Defendant Employee Compensation Data; Correlation Analysis
Note: Distribution of growth in avg compensation correlation over titles with six or more years of data.
Weighted by class-period employee years

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Figure 3: Large Share of Level Correlations are Positive

Compensation Correlation by Titles
100

Share (%)

80

60

40

20

0

ADOBE

APPLE

GOOGLE
Negative

INTEL

INTUIT

PIXAR

Positive

Source: Defendant Employee Compensation Data; Correlation Analysis
Note: Distribution of log avg compensation correlation over titles with six or more years of data.
Weighted by class-period employee years

33.

It is not just statistical variability that can explain the negative or small
correlations. Changes in the composition of employees within a title as
employees come and go can cause changes in title compensation and mask the
normal correlation with the class overall. I will illustrate this point below with a
close examination of some of the Adobe titles that have low or negative
correlations with the class.

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Figure 4

Summary of Compensation Change Correlation
Positive Sign
Employer

Negative Sign

Not Significant

Significant

Not Significant

Total

(Percent)
ADOBE
APPLE
GOOGLE
INTEL
INTUIT
PIXAR

Significant

(Percent)

(Percent)

(Percent)

(Percent)

67 %
54
76
94
81
86

32 %
35
22
6
14
13

0%
1
0
0
0
0

0%
10
2
1
5
1

100 %
100
100
100
100
100

Source: Defendants' employee compensation data; Correlation Analysis
Note: Distribution of growth in compensation correlation over titles with six or more years of data.
Weighted by class-period employee years.

Figure 5

Summary of Compensation Level Correlation
Positive Sign
Employer

Negative Sign

Not Significant

Significant

Not Significant

Total

(Percent)
ADOBE
APPLE
GOOGLE
INTEL
INTUIT
PIXAR

Significant

(Percent)

(Percent)

(Percent)

(Percent)

92 %
78
83
85
45
84

5%
16
16
14
40
15

0%
1
0
0
2
0

3%
5
1
1
12
0

100 %
100
100
100
100
100

Source: Defendants' employee compensation data; Correlation Analysis
Note: Distribution of log avg compensation correlation over titles with six or more years of data.
Weighted by class-period employee years.

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B. Title-by-Title Multiple Regressions

34.

As described above, I also analyzed a multiple regression model of
compensation that explains the year-by-year increases in average compensation
at the title level in terms of four explanatory variables: (1) increases in average
Technical Class compensation at the firm; (2) the previous year’s ratio of
average Technical Class compensation at the firm divided by the average title
compensation; (3) The previous year’s ratio of firm-wide average revenue
divided by the average title compensation; (4) the percent change in software
jobs in the San Jose MSA.

35.

The data set is limited to eleven annual observations from 2001 to 2011, and
many titles have fewer observations. A four-variable regression is a heavy
burden with such data, which is reflected in the number of statistically
insignificant coefficients. The statistically insignificant results are particularly
prevalent for the external market effects and the revenue-sharing effects.5 The
two sharing variables have more statistically significant coefficients. In other
words, in the competition for statistical significance, it is sharing that wins.

36.

I present in Figure 6 and Figure 7, below, class-wide results for titles with at
least seven observations (approximately 30 percent of all Technical Class titles
and more than 91 percent of their Class Period employee years).

37.

Those results show the following. First, the vast majority of titles have a
positive sharing effect in either the contemporaneous relationship or the lagged
relationship. Second, of those that are negative a small fraction are statistically
significant. Third, even these negative results occur in the context of body of
evidence that there is a general relationship supported by sharing relationships
for the vast majority of titles. Many of these are statistically significant. In sum,
this analysis provides support for internal relationships across all Class titles at a

This model is completely appropriate if the sharing force came from the class overall, equally across all titles.
If on the other hand, title A were connected only to title B, then my attempt to link A to the class overall
would yield a small and probably insignificant effect unless the variability in compensation of the class were
largely determined by variability in compensation of title B. To put this in simple terms, the model that I am
estimating makes it less likely not more likely to find a sharing effect.

5

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firm that would tend to make impact of the agreements common to all Class
members.
Thus, the vast majority of these titles have a positive internal equity sharing
relationship with other Technical Class titles at the same firm. The implication
of these results is to support my previous conclusion that the impact of the
alleged non-compete agreements would be common across the class and
common across the Technical Class employees in particular.
Figure 6: Large Share of Contemporaneous Coefficients are Positive

Contemporaneous Coefficient by Titles
100

80

Share (%)

38.

60

40

20

0

ADOBE

APPLE

GOOGLE
Negative

INTEL

INTUIT

PIXAR

Positive

Source: Defendant Employee Compensation Data; Regression Analysis
Note: Distribution of estimated contemporaneous coefficient over titles with seven or more years of data.
Weighted by class-period employee years

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Figure 7: Large Share of Lagged Coefficients are Positive

Lagged Coefficient by Titles
100

Share (%)

80

60

40

20

0

ADOBE

APPLE

GOOGLE

INTEL

Negative

INTUIT

PIXAR

Positive

Source: Defendant Employee Compensation Data; Regression Analysis
Note: Distribution of estimated lagged coefficient over titles with seven or more years of data.
Weighted by class-period employee years

Figure 8

Summary of Contemporaneous and Lagged Net Effect
Positive Sign
Employer

Negative Sign

Not Significant

Significant

Not Significant

Total

(Percent)
ADOBE
APPLE
GOOGLE
INTEL
INTUIT
PIXAR

Significant

(Percent)

(Percent)

(Percent)

(Percent)

22 %
23
12
88
73
60

75 %
62
69
11
23
39

0%
0
2
0
0
0

3%
14
17
1
4
0

100 %
100
100
100
100
100

Source: Defendants' employee compensation data; Regression Analysis
Note: Distribution of the sum of estimated contemporaneous and lagged coefficients over titles with six or more years of data.
Weighted by class-period employee years.

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39.

It may be important to understand that in principle there is a matrix of sharing
relationships that connect titles directly affected by the conspiracy with other
titles that are tied together with these affected titles. For example, with 101
Adobe titles in the class with six or more observations, this would require
potentially the estimation of a 101 by 101 matrix of connections, which is far
too many parameters to estimate with only eleven years of data. The regressions
that I have estimated have a much simpler structure connecting each title not
separately with all of the other titles but instead with the Adobe-wide variables.6

40.

The regression results for Adobe titles with seven or more years of data are
reported in Exhibit 1. The first two Sections give descriptive information about
the data and the two correlations. These titles are sorted by the correlations of
the log levels of average real compensation (Column 7). Column (9) which is
the correlation between the percent change in average real compensation is
more relevant here because this correlation is part of the estimated regression.7
The regression coefficients of the four variables are collected together in Section
3 and the corresponding t-statistics are reported to their right in Section 4.

41.

Roughly, a t-statistic in excess of 2 in absolute value is said to produce
“statistically significant” estimate by conventional standards. For that reason, tstatistics in excess of 2 are highlighted. Among the titles with eleven years of
data it is the two sharing variables that jump out with high t-statistics, more
often the “corrective” variable (Column 16) than the class-wide
contemporaneous effect (Column 15). The external market variable (Column
18) has a t-value in excess of 2 only 4 of 41 titles, and the revenue variable
(Column 17) has one negative and no positive significant t-stats. The results are
more mixed deeper into the table as the number of observations diminishes.

As I noted above, this model looks for a sharing force that comes from the class overall, equally across all
titles. If on the other hand, title A were connected only to title B, then my attempt to link A to the class
overall would yield a small and probably insignificant effect unless the variability in compensation of the class
were largely determined by variability in compensation of title B. The model that I am estimating makes it
less likely not more likely to find a sharing effect.
6

The increment in the fit of the model associated with the last three explanatory variables can be found by
comparing the R-sq in the last column with the squared of the correlation.

7

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42.

V.

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This confirms the summary above, providing direct evidence of sharing across
titles. The almost always positive coefficients on the “corrective” variable equal
to the lagged ratio of compensation relative to title compensation in the title
indicates that if the title compensation departs from its normal relationship with
the class, then corrective action is taken to either raise or lower compensation in
the title.

Decile Based Correlations and Multiple Regressions

43.

The title-based study just described by necessity excludes titles that are
infrequently populated. To include these titles in this study, I have formed
groups of titles on which to conduct the correlation analysis and the multiple
regressions. I split each Defendant’s Technical Class titles into ten groups. To
form the ten groups, I ranked titles on the basis of average (inflation-adjusted)
total compensation over the lifetime of the title and then divided these up into
deciles based on employee-years.8
A. Decile Based Correlation Analysis

44.

The correlation analysis of the ten groups yields strong evidence of both short
and long-run compensation structures for each subgroup of the Defendants’
Technical Class employees. Figure 9 and Figure 10 indicate the numbers of the
ten groups that had positive correlations with the Technical Class: 10 out of 10
for the levels correlation and 10 out of 10 for the percent change correlations.
Thus, every group shares in its firm’s compensation structure. Every group
shows both immediate and long-run correlation structure for every group. This
is consistent with and supports my conclusion that the Defendants’
compensation was semi-rigid.

Since Lucasfilm did not provide title data, individuals were ranked in a similar fashion for Lucasfilm.
Although I attempted to break the firms up into 10 equal sized groups (equal based on employee years), some
groups end up being larger than others because of some big titles.

8

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Figure 9: Large Share of Change Correlations are Positive

Compensation Change Correlation by Deciles
100

Share (%)

80

60

40

20

0

ADOBE

APPLE

GOOGLE

INTEL

Negative

INTUIT

LUCASFILM

PIXAR

Positive

Source: Defendant Employee Compensation Data; Correlation Analysis
Note: Distribution of growth in avg compensation correlation weighted by class-period employee years

Figure 10: Large Share of Level Correlations are Positive

Compensation Correlation by Deciles
100

Share (%)

80

60

40

20

0

ADOBE

APPLE

GOOGLE

INTEL

Negative

INTUIT

LUCASFILM

PIXAR

Positive

Source: Defendant Employee Compensation Data; Correlation Analysis
Note: Distribution of log avg compensation correlation weighted by class-period employee years

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B. Decile Based Multiple Regression Results

45.

Multiple regressions have also been estimated with these decile data. As
summarized in Figure 11 and Figure 12, below, positive sharing effects—both
contemporaneous and lagged—are the rule.

Figure 11: Large Share of Contemporaneous Coefficients are Positive

Contemporaneous Coefficient by Deciles
100

Share (%)

80

60

40

20

0

ADOBE

APPLE

GOOGLE

INTEL

Negative

INTUIT

LUCASFILM

PIXAR

Positive

Source: Defendant Employee Compensation Data; Regression Analysis
Note: Distribution of estimated contemporaneous coefficient weighted by class-period employee years

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Figure 12: Large Share of Lagged Coefficients are Positive

Lagged Coefficient by Deciles
100

Share (%)

80

60

40

20

0

ADOBE

APPLE

GOOGLE

INTEL

Negative

INTUIT

LUCASFILM

PIXAR

Positive

Source: Defendant Employee Compensation Data; Regression Analysis
Note: Distribution of estimated lagged coefficient weighted by class-period employee years

46.

The almost always positive coefficients on the “corrective” variable in Figure 12
indicate that if the title compensation of a decile departs from its normal
relationship with the class, then corrective action is taken to either raise or lower
compensation in the decile. The cold-calling conspiracy that would have direct
impact suppressing wages in some titles would have some effect on the classwide averages which in turn would suppress compensation in all or almost all of
the titles in the class.

47.

Figure 11 and Figure 12 contain a few instances of negative estimates. There
are several important things to note. First, every group has a positive sharing
effect in either the contemporaneous relationship or the lagged relationship.
Second those that are negative are not statistically significant. Third, these occur
in the context of evidence of positive sharing relationships for almost every
group. Many of these are statistically significant. In sum, this analysis provides
support for internal relationships across all these groups that would tend to
make impact common to each.

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48.

49.

VI.

Here I want to issue another warning about misinterpretation of negative
coefficients. It is important to realize that these coefficients can be affected by
the changing composition of the workforce within each title.9 For instance,
adding a number of junior workers might bring down the title’s average
compensation (or vice versa) for reasons unrelated to the question of whether
workers share broadly in things such as the gains of the company and the
impact of the unlawful agreements. Idiosyncratic variability of individual
characteristics within a title is going to be a bigger problem for titles with just a
few employees and for titles that experience large changes10 in their headcounts.
Taking into account the limitations of these data, I find no compelling reason in
this analysis to exclude any of the titles from the Technical Class.

Additional Exploration of Adobe Correlations

50.

To test this opinion I have closely examined the correlation outputs for the
Adobe dataset as set forth below. They confirm my view. I have similarly
examined the data of the other defendants, and find nothing in that data to
contradict this conclusion.
1. Adobe Correlation Results

51.

The numerical correlations reported in compare the movement of real
compensation for each title in the Technical Class with the movement of the
compensation of the Technical Class overall, but excluding the selected title. A
high positive correlation means that compensation of a title moves in a way that
is similar to compensation in the rest of the Technical Class, thus supporting the
conclusion that the title and the class have “coordinated” compensation levels, a
fact which is consistent with sharing of gains and broad impact of the anti-cold-

I previously demonstrated with the Common Factors Analysis that compensation at the individual level in
any year depends on the title but also depends on measured individual characteristics including age. This is
statistical confirmation that at least some individual characteristics matter, and this raises the possibility that
changes in the individual characteristics within a title can cause changes in title compensation that can mask
the firm-wide common component.

9

10

Though a stable headcount can come from equal numbers of departures and new arrivals.
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calling conspiracy whether it directly affects the title under study or the rest of
the Technical Class.
52.

Titles are included in the table if they are populated in 6 or more years. The
correlations based on 5 or fewer observations are often statistically insignificant.
The table is sorted first by the number of years the title was populated, from 11
to 6, and then by the correlation of the title with the Technical Class overall.
Titles with the strongest statistical correlation with the Technical Class at Adobe
are shaded in green. Titles with the weakest statistical correlation with the
Technical Class at Adobe are shaded in yellow.

53.

The first column of numbers in Exhibit 1 has the first year of data for each title.
This is important since the early years from 2001 to 2003 had a sharp decline in
Technical Class compensation for Adobe, as illustrated in Figure 13 and these
early years thus are an important test bed for identifying which titles moved
together. It would not be surprising to find statistically weaker results if these
years are not included.
Figure 13

Average Total Compensation ($)

Adobe Technical Class Average Total Compensation

Source: Defendant Employee Compensation Data
Note: Inflation-adjusted average compensation with 2011 as base year

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54.

The second column reports the number of years during which the title was
populated. This is also important since the statistical accuracy of the estimate of
correlation depends on the number of observations. For that reason, I have
truncated this table at the number of years equal to 6 or more since the cases
with 5 or fewer years populated are estimated with greater statistical error.

55.

The third column measures the number of employee-years.
2. Headcount Matters for Interpreting Correlations

56.

It is my view that compensation is influenced by the title structure, but not fully
determined by the title structure. Variables like age, experience, company tenure
and personal characteristics are likely to have an impact on compensation, and
consequently some of the change in compensation at the title level comes from
changes in the distribution of employee characteristics as employees come and
go. Titles that have just a few employees may have unusual employee
characteristics, and titles that lose or gain a large fraction of employees may have
variability in average compensation that is substantially influenced by variability
of these characteristics, which masks a close connection with the Technical
Class overall.

57.

The Technical Class overall has experienced a rising headcount, as illustrated in
Figure 14. Titles with movement in headcounts similar to the Technical Class
may experience similar movements in employee characteristics, while titles that
are losing workers or gaining workers much more rapidly than the Technical
Class overall may have average compensation histories different from the
Technical Class, not because there is no sharing, but because the group of
employees in the title is changing enough to mask the sharing.

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Figure 14

Adobe Technical Class Average Headcount per Title
40

Employees/Title

30

20

10

0
2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

Source: Defendant Employee Compensation Data

3. Correlations

58.

As described above, there are two types of correlations which are relevant for
determining if the movements of the two series are similar. The first column of
correlations (Section 2) in Exhibit 1 compares the logarithm of average total real
compensation in the title and the logarithm of average real total compensation
of the rest of the Technical Class. The third column of Section 2 compares the
change in the logarithm of average real total compensation of the title with the
Technical Class (excluding the title).

59.

The corresponding t-statistics for these correlations are reported immediately
following each correlation and the statistically significant correlations with tstatistics greater than two are shaded. The table is sorted first by the number of
years in which the title is populated and second by the correlation between the
log levels.

60.

The statistically most significant correlations with the shaded t-statistics come
from the longest time series with all eleven years of data populated. That is a
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feature of any statistical exercise – the longer is the time series the more
statistically significant are the findings.
61.

There are no negative correlations for the 41 titles with all eleven years
populated. These positive correlations are statistically larger than zero
(statistically significant) in 39 out of the 41 cases.
4. Outliers

62.

To fully understand these correlations, and the significance (or not) of the
anomalies, it may be helpful to look at some data displays. Figure 15 and Figure
16 have the average real compensation for ten Adobe titles and for the Adobe
employees in the Technical Class overall. Figure 15 illustrates the five titles with
eleven years of data that are most highly correlated with the Technical Class
overall, and Figure 16 has the least correlated titles. All these titles move
together. The title with the lowest correlation is TECHNICAL_WRITER_2
which is different, but not dramatically so.

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Figure 15: Selected Adobe Titles with a Full 11 years of Data

Average Total Compensation ($)

Most Correlated Titles Average Total Compensation

Source: Defendant Employee Compensation Data; Correlation Analysis
Note: Titles with highest log compensation correlation among fully populated titles
Inflation-adjusted average total compensation with 2011 as base year

Figure 16

Average Total Compensation ($)

Average Total Compensation ($)

Least Correlated Titles Average Total Compensation

Source: Defendant Employee Compensation Data; Correlation Analysis
Note: Titles with highest log compensation correlation among fully populated titles
Inflation-adjusted average total compensation with 2011 as base year

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63.

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However, as noted above, when headcounts change substantially, employee
characteristics may change substantially too. The headcounts for the two titles
with the lowest correlation are illustrated in Figure 17. The headcount for
, is very volatile with a standard deviation of
the percent change equal to 72 percent compared with the Technical Class
benchmark of 11 percent.
title is basically
withering away, with an average annual percent increase of –12 percent
compared with the Technical Class benchmark of +5 percent.
Figure 17: Headcounts: Least Correlated Titles

Least Correlated Titles Headcount
12

Title Headcount

10

8

6

4

2

0
2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

Source: Defendant Employee Compensation Data; Correlation Analysis
Note: Titles with lowest log compensation correlation among fully populated titles

64.

The variability in the headcounts for these two titles is not just a hypothetical
problem. It has affected substantially the median ages for these titles which are
contrasted with the median age of the Technical Class overall in Figure 18. In
contrast to the smooth elevation of the median age of the class, the median age
of
has a big jump upward in 2006, and the median
age of
is highly volatile. These facts surely
contribute to the apparent disconnect between compensation in these titles and
compensation in the Technical Class overall. And, in any event, these results
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offer no reason to question my conclusion that Adobe exhibits a somewhat rigid
pay structure that applied to all of its salaried employees, including those in
these titles. I offer these two examples simply to illustrate the point that the
presence of a few outlier titles in the analyses does not challenge our basic
conclusions about how these companies pay their employees, which are also
supported by economic theory and the evidentiary. I have not seen any
evidence, let alone convincing evidence, that any of these titles would not have
been harmed by the anti-competitive behavior I have studied.
Figure 18: Median ages: Least Correlated Titles

Least Correlated Titles Median Age
45

Median Age

40

35

30
2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

Technical Class
Source: Defendant Employee Compensation Data; Correlation Analysis
Note: Titles with lowest log compensation correlation among fully populated titles

VII. Internal Versus External Forces

65.

The regression analysis reported above indicates that the internal sharing effects
are generally more detectable than either revenue sharing or the external market
forces. I expand on this finding in this section with an examination of the
average real compensation for the Technical Class employees and the nonTechnical Class employees of each of the defendants. I show here that there is
generally more correlation within firms between these two groups, than between
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firms for either group. Thus again I observe that the internal sharing forces are
very evident while the external market forces are more difficult to detect.
66.

Figure 19 below illustrates for each defendant the average total compensation
for the Technical Class employees (RD) and for the non-Technical Class
employees (NRD). For most defendants these two subgroups have total
compensation that closely tracks one another. It should also be evident that
average total compensation is generally much more similar within each firm
than between firms. In other words, the internal sharing forces dominate and
keep the compensation of the Technical Class employees and the non-Technical
Class employees closely aligned.

67.

This visual observation is confirmed numerically by the computation of the
correlations over time of the change in logarithms of the average total real
compensation between these fourteen groups of employees, reported in Table 1.
Correlations in excess of 0.9 are shaded. The boxes down the diagonal contain
the within firm correlations between RD and NRD. Correlations outside these
boxes refer to comparisons between firms. Four out of five of the shaded
correlations are in these boxes, and in addition Google has an internal
correlation of 0.86. Furthermore, the within firm correlation is the largest
correlation in every row and column except for Lucasfilm. Lucasfilm has a very
short time series with very little variability in the percent change in
compensation, making it hard to estimate correlation . The Pixar data are
contaminated by very large bonuses for producers and directors in 2002 and
2006.

68.

Table 2 has the levels correlations that capture the longer term co-movements
of the compensation series. These confirm the importance of the internal
forces compared with the external forces. forces for all but Lucasfilm, in the
sense that the within firm correlation is the largest correlation in every row and
column except for Lucasfilm. Lucasfilm and Intel appear to move together only
because the Lucasfilm data is confined to a brief period of stable growth of
compensation at both firms.

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Figure 19: Defendant RD vs. NRD Average Total Compensation

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Table 1

Correlations of Changes in Defendants' Average Total Compensation
2001-2011
Adobe

Apple
Google
Intel
Intuit
Lucasfilm
Pixar

Google

Intel

Intuit

Lucasfilm

Pixar

NRD RD
Adobe

Apple
NRD RD

NRD RD

NRD RD

NRD RD

NRD RD

NRD RD

NRD

1.00 0.94

0.66 0.56

0.17 -0.16

0.47 0.60

0.63 0.60

0.19 -0.62

-0.53 -0.53

RD

0.94 1.00

0.64 0.65

0.13 -0.24

0.34 0.45

0.53 0.51

-0.12 -0.67

-0.51 -0.37

NRD

0.66 0.64

1.00 0.93

0.48 0.17

0.02 0.16

0.85 0.73

-0.08 -0.87

-0.56 -0.16

RD

0.56 0.65

0.93 1.00

0.42 0.07

-0.12 0.00

0.77 0.63

-0.11 -0.83

-0.45 0.05

NRD

0.17 0.13

0.48 0.42

1.00 0.86

-0.51 -0.39

0.20 0.17

0.49 -0.89

-0.62 0.21

-0.16 -0.24

0.17 0.07

0.86 1.00

-0.53 -0.50

-0.09 -0.06

0.68 -0.83

-0.50 0.19

NRD

0.47 0.34

0.02 -0.12

-0.51 -0.53

1.00 0.97

0.31 0.30

-0.01 0.92

0.00 -0.89

RD

0.60 0.45

0.16 0.00

-0.39 -0.50

0.97 1.00

0.38 0.33

0.23 0.70

-0.03 -0.89

NRD

0.63 0.53

0.85 0.77

0.20 -0.09

0.31 0.38

1.00 0.91

-0.15 -0.17

-0.43 -0.28

RD

0.60 0.51

0.73 0.63

0.17 -0.06

0.30 0.33

0.91 1.00

-0.51 0.55

-0.63 -0.34

RD

NRD

0.19 -0.12

-0.08 -0.11

0.49 0.68

-0.01 0.23

-0.15 -0.51

1.00 -0.24

0.03 -0.38

RD

-0.62 -0.67

-0.87 -0.83

-0.89 -0.83

0.92 0.70

-0.17 0.55

-0.24 1.00

0.58 -0.29

NRD

-0.53 -0.51

-0.56 -0.45

-0.62 -0.50

0.00 -0.03

-0.43 -0.63

0.03 0.58

1.00 0.29

RD

-0.53 -0.37

-0.16 0.05

0.21 0.19

-0.89 -0.89

-0.28 -0.34

-0.38 -0.29

0.29 1.00

Note: Values above 0.9 shaded.
Source: Defendants' employee compensation data.

Page 32
Supplemental Expert Report of Edward E. Leamer, Ph.D.

497

Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page35 of 62
CONFIDENTIAL

5/10/2013

Table 2

Correlations of Defendants' Average Total Compensation
2001-2011
Adobe
NRD RD
Adobe
Apple
Google
Intel
Intuit
Lucasfilm
Pixar

Apple
NRD RD

Google
NRD RD

Intel
NRD RD

Intuit
NRD RD

Lucasfilm
NRD RD

Pixar
NRD RD

NRD

1.00 0.88

-0.17 -0.17

-0.43 -0.73

0.18 0.58

0.50 0.41

0.15 -0.04

-0.33 -0.38

RD

0.88 1.00

0.24 0.27

-0.05 -0.63

0.47 0.72

0.69 0.61

0.40 0.32

-0.48 -0.51

NRD

-0.17 0.24

1.00 0.99

0.91 0.38

0.65 0.33

0.64 0.68

0.74 0.58

-0.48 -0.39

RD

-0.17 0.27

0.99 1.00

0.90 0.33

0.69 0.37

0.64 0.66

0.83 0.72

-0.46 -0.40

NRD

-0.43 -0.05

0.91 0.90

1.00 0.67

0.53 0.13

0.36 0.44

0.81 0.59

-0.46 -0.28

RD

-0.73 -0.63

0.38 0.33

0.67 1.00

-0.05 -0.44

-0.20 -0.08

0.47 0.04

-0.22 0.12

NRD

0.18 0.47

0.65 0.69

0.53 -0.05

1.00 0.87

0.64 0.66

0.93 0.98

-0.54 -0.86

RD

0.58 0.72

0.33 0.37

0.13 -0.44

0.87 1.00

0.65 0.62

0.91 0.96

-0.48 -0.90

NRD

0.50 0.69

0.64 0.64

0.36 -0.20

0.64 0.65

1.00 0.94

0.63 0.54

-0.55 -0.54

RD

0.41 0.61

0.68 0.66

0.44 -0.08

0.66 0.62

0.94 1.00

0.78 0.91

-0.72 -0.62

NRD

0.15 0.40

0.74 0.83

0.81 0.47

0.93 0.91

0.63 0.78

1.00 0.88

-0.63 -0.83

RD

-0.04 0.32

0.58 0.72

0.59 0.04

0.98 0.96

0.54 0.91

0.88 1.00

-0.62 -0.86

NRD

-0.33 -0.48

-0.48 -0.46

-0.46 -0.22

-0.54 -0.48

-0.55 -0.72

-0.63 -0.62

1.00 0.65

RD

-0.38 -0.51

-0.39 -0.40

-0.28 0.12

-0.86 -0.90

-0.54 -0.62

-0.83 -0.86

0.65 1.00

Note: Values above 0.9 shaded.
Source: Defendants' employee compensation data.

Page 33
Supplemental Expert Report of Edward E. Leamer, Ph.D.

498

Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page36 of 62

499

Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page37 of 62

Exhibit 1
500

Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page38 of 62
Exhibit 1
Adobe
Section 1
Job Title

First
Year
(1)
2001
2001
2001
2001
2001
2001
2001
2001
2001
2001
2001
2001
2001
2001
2001
2001
2001
2001
2001
2001
2001
2001
2001
2001
2001
2001
2001
2001
2001
2001
2001
2001
2001
2001
2001
2001
2001
2001
2001
2001
2001
2002
2002
2002
2002
2001
2001
2004
2001
2001
2001
2001
2001
2004
2001
2004

Years
of Data
(2)

Section 2

Total
Emp-Years Avg Emp dlog Avg dlog Std Dev
(3)
(4)
(5)
(6)
11
11
11
11
11
11
11
11
11
11
11
11
11
11
11
11
11
11
11
11
11
11
11
11
11
11
11
11
11
11
11
11
11
11
11
11
11
11
11
11
11
10
10
10
10
9
9
8
8
8
8
8
8
8
8
8

170
311
371
29
82
108
96
250
559
93
14
152
202
550
234
273
327
434
196
353
309
94
2095
514
35
215
496
466
234
1441
302
222
975
2041
56
2064
100
1008
41
66
47
36
37
26
330
44
104
94
143
8
93
88
64
50
32
18

15
28
34
3
7
10
9
23
51
8
1
14
18
50
21
25
30
39
18
32
28
9
190
47
3
20
45
42
21
131
27
20
89
186
5
188
9
92
4
6
4
4
4
3
33
5
12
12
18
1
12
11
8
6
4
2

0.27
0.05
0.11
0.16
0.10
-0.03
0.12
0.04
0.11
0.11
0.00
0.28
0.06
0.06
0.07
0.17
0.11
0.07
0.13
-0.06
0.08
0.08
0.05
0.08
0.00
0.07
0.05
0.06
0.09
0.06
0.00
0.09
-0.12
0.05
0.03
0.05
0.09
0.06
0.00
-0.06
-0.12
0.10
0.08
0.00
0.20
-0.30
-0.21
0.30
-0.40
0.00
-0.28
-0.10
-0.43
0.14
0.20
0.00

0.34
0.19
0.16
0.65
0.25
0.40
0.37
0.16
0.20
0.26
0.45
0.15
0.25
0.18
0.22
0.19
0.14
0.18
0.24
0.19
0.23
0.27
0.13
0.22
0.32
0.53
0.20
0.11
0.33
0.19
0.21
0.15
0.23
0.20
0.54
0.08
0.31
0.27
0.59
0.72
0.30
0.40
0.43
0.48
0.29
0.50
0.48
0.91
1.08
0.00
1.28
1.44
0.54
0.33
0.81
0.61

Level Correlation
Coeff
T-Stat
(7)
(8)
0.90
0.89
0.89
0.87
0.85
0.84
0.84
0.84
0.83
0.81
0.80
0.78
0.78
0.78
0.78
0.77
0.74
0.74
0.74
0.73
0.71
0.71
0.70
0.70
0.69
0.69
0.67
0.67
0.67
0.65
0.64
0.63
0.63
0.61
0.61
0.61
0.60
0.59
0.58
0.51
0.09
0.80
0.14
-0.02
-0.13
0.52
0.30
0.84
0.70
0.62
0.56
0.38
0.31
0.28
0.15
-0.17

6.07
5.89
5.73
5.37
4.87
4.73
4.65
4.60
4.53
4.19
3.97
3.74
3.74
3.70
3.68
3.60
3.34
3.29
3.27
3.23
3.03
3.03
2.91
2.90
2.90
2.88
2.74
2.74
2.71
2.55
2.49
2.44
2.42
2.33
2.32
2.29
2.27
2.17
2.11
1.77
0.26
3.72
0.39
-0.06
-0.37
1.59
0.85
3.82
2.38
1.92
1.64
1.02
0.80
0.73
0.36
-0.41

1 of 2

Section 3

Change Correlation
Coeff
T-Stat
(9)
(10)
0.89
0.78
0.79
0.78
0.72
0.82
0.85
0.85
0.88
0.67
0.63
0.72
0.70
0.95
0.73
0.74
0.82
0.65
0.82
0.56
0.61
0.62
0.69
0.63
0.53
0.46
0.75
0.69
0.77
0.48
0.91
0.62
0.48
0.57
0.52
0.52
0.61
0.56
0.34
0.37
0.14
0.77
-0.59
0.14
0.08
0.46
0.37
0.63
0.68
-0.36
0.52
0.58
0.30
0.65
0.40
0.60

5.55
3.55
3.59
3.56
2.97
4.08
4.56
4.47
5.31
2.54
2.29
2.96
2.78
8.29
2.98
3.11
4.00
2.39
4.06
1.91
2.20
2.25
2.68
2.27
1.75
1.48
3.18
2.71
3.39
1.56
6.03
2.22
1.55
1.94
1.70
1.71
2.20
1.91
1.02
1.13
0.40
3.22
-1.93
0.37
0.22
1.28
0.99
1.80
2.05
-0.78
1.37
1.58
0.71
1.89
0.75
1.66

Section 4

Section 5

Section 6

Regression Coefficients
Contemp Lagged Revenue SJ Emp
(11)
(12)
(13)
(14)

Regression T-Stats
Lagged Revenue
(16)
(17)

Net Effect
C+L
T-Stat
(19)
(20)

Obs. r2
(21) (22)

Contemp
(15)

SJ Emp
(18)

1.18
1.07
0.67
2.67
0.89
0.93
0.80
1.28
0.94
3.21
2.50
0.54
0.68
0.99
0.97
0.34
0.66
0.72
1.23
0.81
0.96
0.65
0.26
0.71
0.58
0.35
0.08
0.27
0.10
0.24
0.62
0.05
0.24
0.07
0.27
-0.07
1.92
0.36
0.41
-1.62
-1.20
1.91
0.12
3.38
-0.35
-0.47
-0.36
1.70
1.42
4.15
-0.50
0.41
1.40
1.28

1.04
1.18
1.33
1.08
1.09
0.88
0.59
0.97
0.80
0.89
0.06
0.65
1.24
0.15
1.14
1.32
0.40
1.09
0.57
1.43
1.13
1.02
0.49
0.97
1.09
1.26
0.47
0.62
0.27
0.71
0.10
0.45
0.49
0.43
1.04
0.44
0.91
0.56
1.61
-0.86
0.28
1.28
1.09
0.87
0.30
0.51
1.29
0.88
1.60
2.48
0.43
2.01
0.61
0.54

0.12
-0.09
-0.12
-0.33
-0.46
0.04
0.05
0.08
0.21
-0.24
0.51
0.13
0.21
0.06
0.12
0.23
0.11
0.21
0.09
0.17
0.06
0.11
0.12
0.08
0.15
-0.07
0.14
0.10
-0.17
0.11
-0.17
0.11
0.00
0.14
0.08
0.13
0.00
0.26
0.19
-0.57
-0.07
-0.39
0.06
0.35
0.13
0.04
0.16
-0.61
0.16
-0.14
-0.07
-0.02
0.34
0.27

0.02
-0.31
-0.34
-0.48
0.58
0.51
0.84
0.19
-0.04
-1.55
-0.17
0.54
0.34
0.43
0.29
0.33
0.19
0.30
0.02
0.44
0.24
0.58
0.35
0.45
-0.15
0.47
0.56
0.27
1.23
0.54
0.94
0.75
0.40
0.55
1.06
0.65
-3.12
0.29
-0.56
1.57
1.62
0.00
0.40
5.30
0.64
1.39
1.66
1.82
0.45
-0.81
1.14
2.16
-0.70
2.46

5.15
0.67
0.66
1.49
0.65
2.43
1.93
2.60
2.27
1.03
0.50
0.98
1.30
2.87
1.56
0.60
1.39
1.29
1.48
1.59
1.27
0.89
0.60
0.91
0.45
0.51
0.17
0.49
0.21
0.35
2.20
0.07
0.39
0.14
0.36
-0.14
1.44
0.57
0.42
-4.28
-1.61
1.54
0.19
1.21
-1.22
-0.42
-0.15
5.22
4.02
1.02
-0.33
0.60
0.63
4.87

6.71
1.38
1.95
1.80
1.99
3.32
2.68
3.59
2.28
0.75
0.04
1.60
4.27
0.54
2.19
2.67
1.12
2.84
1.38
4.09
2.23
2.65
1.35
2.30
2.12
3.49
1.29
1.62
1.12
1.51
0.67
1.04
1.05
1.04
2.96
1.13
1.96
1.18
2.35
-3.06
1.16
1.76
2.35
1.33
1.84
0.97
0.67
4.89
3.62
1.65
0.71
3.63
0.51
4.48

1.77
-0.25
-0.45
-0.80
-1.23
0.37
0.45
0.47
1.45
-0.30
0.40
0.89
1.40
0.47
0.43
1.59
0.74
1.33
0.29
1.21
0.24
0.49
0.88
0.29
0.47
-0.39
0.89
0.59
-1.01
0.58
-1.72
0.51
-0.01
0.80
0.39
0.82
0.00
1.41
0.55
-4.84
-0.33
-1.17
0.43
0.52
1.72
0.12
0.19
-6.25
1.15
-0.13
-0.13
-0.07
0.47
2.92

0.07
-0.25
-0.36
-0.32
0.39
1.38
1.89
0.37
-0.08
-0.62
-0.04
1.07
0.67
0.94
0.48
0.66
0.38
0.56
0.02
0.94
0.34
0.79
0.79
0.57
-0.09
0.69
0.91
0.48
2.21
0.89
2.57
0.95
0.71
1.04
1.55
1.29
-2.95
0.48
-0.42
5.82
2.25
0.00
0.73
1.81
1.89
1.19
0.56
3.47
0.85
-0.19
0.66
2.27
-0.28
5.63

2.22
2.25
2.01
3.75
1.97
1.81
1.38
2.25
1.74
4.10
2.57
1.18
1.91
1.14
2.11
1.66
1.06
1.82
1.80
2.23
2.09
1.68
0.75
1.68
1.67
1.61
0.56
0.89
0.38
0.94
0.72
0.50
0.73
0.50
1.30
0.37
2.83
0.91
2.01
-2.48
-0.92
3.19
1.20
4.25
-0.05
0.04
0.93
2.59
3.02
6.63
-0.07
2.42
2.01
1.82

8.15
1.66
1.99
2.24
1.39
3.34
2.66
3.83
3.24
1.49
0.56
1.43
3.24
2.66
2.22
2.77
1.67
2.39
1.87
3.21
1.95
1.74
1.25
1.66
1.05
1.88
0.87
1.33
0.63
0.98
2.18
0.52
0.86
0.67
1.43
0.52
2.36
1.09
1.37
-3.98
-1.12
2.50
1.25
1.45
-0.13
0.03
0.47
6.88
7.37
1.22
-0.05
3.81
1.01
6.05

1.10

0.66

0.04

2.14

1.76

3.36

0.15

2.00

1.76

2.76

501

10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
9
9
9
9
8
8
7
7
6
7
7
7
7

0.98
0.74
0.81
0.79
0.77
0.94
0.95
0.93
0.92
0.63
0.57
0.81
0.92
0.94
0.82
0.86
0.78
0.84
0.78
0.87
0.73
0.83
0.72
0.77
0.81
0.82
0.83
0.71
0.87
0.61
0.95
0.70
0.42
0.62
0.83
0.66
0.86
0.62
0.71
0.91
0.61
0.78
0.76
0.96
0.83
0.71
0.51
0.98
0.98
0.90
0.60
0.93
0.50
0.99

7 0.91

Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page39 of 62
Exhibit 1
Adobe
Section 1
Job Title

First
Year
(1)
2005
2001
2001
2001
2005
2005
2001
2001
2001
2001
2001
2001
2001
2001
2001
2001
2001
2001
2001
2001
2001
2001
2001
2001
2001
2001
2001
2001
2001
2001
2006
2001
2001
2006
2006
2001
2001
2001
2006
2004
2001
2001
2002
2002
2006

Years
of Data
(2)

Section 2

Total
Emp-Years Avg Emp dlog Avg dlog Std Dev
(3)
(4)
(5)
(6)
7
7
7
7
7
7
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6

22
42
88
17
93
59
46
25
19
87
13
89
108
20
16
33
22
23
35
57
10
24
21
92
68
13
27
8
15
26
7
18
105
27
19
15
12
15
19
6
15
11
115
11
24

3
6
13
2
13
8
8
4
3
15
2
15
18
3
3
6
4
4
6
10
2
4
4
15
11
2
5
1
3
4
1
3
18
5
3
3
2
3
3
1
3
2
19
2
4

0.18
-0.27
-0.41
0.00
0.00
0.05
0.14
0.36
-0.06
0.03
-0.28
0.11
0.01
0.00
-0.06
-0.08
0.03
0.22
0.09
0.06
0.22
-0.25
-0.36
0.19
0.00
0.00
0.42
0.00
-0.08
-0.04
-0.14
0.00
-0.04
0.14
-0.08
-0.14
0.22
-0.22
0.28
0.00
0.06
0.08
0.40
0.14
0.37

0.41
0.76
0.33
0.36
0.27
0.36
0.21
0.95
0.45
0.12
1.05
0.43
0.23
0.20
0.70
0.33
0.74
0.49
0.26
0.53
0.32
1.15
0.59
0.16
0.21
0.29
0.63
0.49
0.34
0.41
0.31
0.51
0.36
0.46
0.52
0.90
0.32
0.32
0.53
0.00
0.73
0.52
0.29
0.31
0.73

Level Correlation
Coeff
T-Stat
(7)
(8)
0.76
0.57
0.53
0.48
0.40
0.08
0.98
0.97
0.96
0.96
0.94
0.94
0.93
0.93
0.92
0.92
0.89
0.89
0.89
0.88
0.88
0.88
0.88
0.87
0.86
0.86
0.86
0.85
0.85
0.82
0.81
0.67
0.66
0.62
0.61
0.61
0.57
0.57
0.34
0.13
0.10
0.03
-0.03
-0.17
-0.45

2.64
1.56
1.38
1.21
0.98
0.18
10.31
8.18
7.28
6.72
5.50
5.29
5.23
5.11
4.77
4.62
3.99
3.90
3.87
3.77
3.74
3.70
3.66
3.60
3.44
3.43
3.38
3.28
3.18
2.84
2.81
1.79
1.74
1.57
1.55
1.54
1.39
1.38
0.72
0.26
0.20
0.05
-0.06
-0.34
-1.00

2 of 2

Section 3

Change Correlation
Coeff
T-Stat
(9)
(10)
-0.15
0.39
0.38
0.93
0.97
0.52
0.90
0.86
0.93
0.83
0.94
0.82
0.74
0.78
0.58
0.66
0.94
0.67
0.91
0.47
0.50
0.83
0.49
0.78
0.66
0.59
0.74
0.93
0.27
0.76
0.85
0.43
0.68
0.61
0.54
-0.14
0.76
0.56
-0.21
0.28
0.62
0.16
-0.72
0.11
-0.93

-0.31
0.84
0.82
4.88
7.56
1.21
3.49
2.98
4.41
2.55
4.92
2.47
1.90
2.17
1.23
1.52
4.80
1.54
3.90
0.91
1.00
2.11
0.97
2.16
1.51
1.28
1.92
4.31
0.49
2.03
2.85
0.82
1.59
1.34
1.11
-0.24
2.05
1.17
-0.38
0.50
1.36
0.28
-1.47
0.20
-4.22

Section 4

Section 5

Section 6

Regression Coefficients
Contemp Lagged Revenue SJ Emp
(11)
(12)
(13)
(14)

Regression T-Stats
Lagged Revenue
(16)
(17)

Net Effect
C+L
T-Stat
(19)
(20)

Obs. r2
(21) (22)

0.14
-3.13
-3.36
0.58
1.30
0.49

0.93
2.20
5.49
0.42
0.10
0.70

-0.38
-0.57
-1.61
-0.13
0.07
0.24

-0.36
3.68
7.47
0.77
0.02
-0.26

Contemp
(15)
0.11
-2.63
-4.12
0.54
2.06
0.34

1.48
2.79
6.77
0.84
0.28
0.76

-0.68
-1.65
-4.51
-0.54
0.24
0.40

SJ Emp
(18)
-0.21
2.92
5.53
0.89
0.03
-0.13

1.07
-0.93
2.13
1.00
1.40
1.19

0.60
-1.11
10.60
0.71
1.76
0.61

502

6
6
6
6
6
6

0.91
0.93
1.00
0.95
0.94
0.73

Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page40 of 62

Exhibit 2
503

Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page41 of 62
Exhibit 2
Apple
Section 1
Job Title

Years
of Data
11
11
11
11
11
11
11
11
11
11
11
10
10
10
10
9
8
8
8
8
8
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7

Total
Emp-Years
294
501
229
169
352
189
428
156
118
686
58
82
184
110
66
116
44
35
19
52
13
71
193
626
184
2566
29
253
130
447
244
125
1364
54
236
475
1304
110
902
371
68
61
26
549
127
118
682
167
146
29
121
63
1363
16

Section 2
Level Correlation
Coeff
T-Stat
0.98
13.53
0.98
13.42
0.98
13.33
0.97
12.72
0.95
9.16
0.93
7.38
0.91
6.72
0.88
5.54
0.68
2.82
-0.49
-1.69
-0.50
-1.71
-0.67
-2.52
-0.81
-3.84
-0.81
-3.93
-0.89
-5.57
-0.85
-4.33
0.98
11.69
0.97
9.97
0.76
2.89
-0.82
-3.57
-0.96
-7.90
0.99
22.21
0.99
20.45
0.99
16.77
0.99
16.70
0.99
14.96
0.99
13.76
0.98
12.12
0.98
10.75
0.98
10.68
0.98
10.66
0.98
9.93
0.98
9.91
0.97
9.77
0.97
9.58
0.97
9.33
0.97
9.17
0.97
8.72
0.97
8.62
0.97
8.61
0.97
8.25
0.96
8.15
0.96
8.01
0.96
7.91
0.96
7.88
0.96
7.80
0.96
7.79
0.96
7.75
0.96
7.71
0.96
7.63
0.96
7.62
0.96
7.52
0.96
7.33
0.95
7.10

Change Correlation
Coeff
T-Stat
0.74
3.11
0.87
4.91
0.65
2.41
0.70
2.79
0.71
2.82
0.84
4.39
0.65
2.45
0.39
1.21
0.36
1.09
0.43
1.33
0.07
0.20
0.03
0.08
-0.25
-0.68
0.71
2.64
0.04
0.11
-0.55
-1.59
0.59
1.27
0.78
2.48
-0.62
-1.78
0.02
0.05
0.24
0.55
0.95
5.95
0.95
6.20
0.94
5.77
0.96
6.91
0.92
4.55
0.81
2.81
0.92
4.72
0.89
3.94
0.95
6.15
0.88
3.63
0.86
3.39
0.93
4.96
0.81
2.81
0.97
7.42
0.84
3.04
0.81
2.81
0.95
6.06
0.82
2.84
0.94
5.61
0.96
6.93
0.59
1.48
0.86
3.40
0.94
5.57
0.93
5.24
0.69
1.90
0.88
3.70
0.91
4.31
0.62
1.59
0.56
1.36
0.87
3.46
0.90
4.06
0.91
4.37
0.73
2.15

Section 3
Contemp
0.80
2.46
1.15
1.29
0.92
1.68
0.51
0.71
0.58
0.66
0.03
-0.38
-0.17
0.69
-0.14
-0.43
1.84
0.30
-0.16
0.14
0.09
0.54
1.49
1.41
1.16
0.88
0.24
0.76
-0.47
1.48
-0.18
0.99
0.85
1.59
0.99
0.55
0.66
1.93
0.83
0.64
1.64
0.73
3.03
1.06
2.07
1.62
1.09
1.32
0.74
1.70
-0.61
2.37
0.94
2.74

Regression Coefficients
Lagged
Revenue
0.04
0.34
1.09
-0.70
0.97
0.09
1.49
-0.57
-0.22
0.76
0.36
0.20
4.63
-2.48
0.25
0.28
0.17
-0.11
0.47
-0.15
-0.11
0.21
0.08
0.18
0.08
0.18
0.07
-0.04
-0.06
0.06
0.03
0.14
3.27
-2.40
0.21
1.02
0.16
0.02
0.08
-0.13
0.05
-0.03
-0.46
0.07
1.49
-0.41
1.40
-0.29
1.48
-0.31
0.60
0.16
-0.38
0.08
1.16
0.20
5.06
1.65
0.65
0.02
-4.02
1.70
1.14
0.05
0.41
0.34
2.35
-1.09
0.57
0.28
0.80
0.42
0.37
0.03
1.07
-0.23
0.68
0.49
-0.22
0.04
0.38
0.00
0.90
0.29
1.10
-0.85
-0.90
0.48
1.20
-0.26
1.95
-0.25
0.81
0.48
0.59
0.02
0.99
0.05
2.20
-0.62
5.97
-1.48
2.06
-0.91
0.75
0.28
8.01
-4.63

1 of 22

Section 4
SJ Emp
-0.06
-0.67
-0.08
0.28
0.16
0.87
1.62
-0.62
-0.23
-0.49
-0.27
0.01
-0.91
-0.53
0.20
-0.95
1.69
-0.21
-0.78
-0.07
-0.22
0.06
0.82
0.07
0.23
-0.65
0.22
-0.64
-5.63
-0.45
-0.93
0.09
-1.08
2.20
-0.18
-1.16
-0.87
0.24
-1.09
-0.32
-0.12
-1.36
-1.59
-0.87
0.97
1.40
-0.70
0.75
-0.79
1.55
-0.02
2.63
-1.10
8.30

Contemp
1.64
5.33
2.58
2.17
1.56
1.81
0.53
0.95
0.86
0.68
0.05
-0.39
-0.20
2.98
-1.03
-1.37
1.13
-0.78
0.50
0.84
1.39
12.36
30.92
3.69
10.23
0.48
1.85
-0.64
2.89
-0.73
4.26
5.64
5.11
2.55
2.01
9.39
108.02
13.99
3.23
1.64
2.84
8.22
21.14
3.58
4.18
5.58
1.37
3.63
2.79
-1.34
16.54
1.79
9.55

Section 5

Regression T-Stats
Lagged
Revenue
0.05
0.81
1.71
-1.82
1.52
0.26
1.67
-1.00
-0.39
1.55
0.38
0.26
2.82
-2.28
0.38
0.40
0.31
-0.16
0.60
-0.18
-0.28
0.49
0.10
0.22
0.11
0.24
0.36
-0.18
-0.53
0.47
0.14
0.54
0.37
0.97
0.28
0.50
-0.22
3.86
4.57
0.99
3.85
-0.29
1.01
1.93
0.47
-3.21
3.10
1.91
4.37
1.16
1.71
3.50
31.38
9.36
-0.70
0.20
2.23
0.94
-4.50
1.36
3.14
2.55
0.39
3.13
2.35
5.40
8.37
0.89
7.14

3.49
0.13
-0.51
-0.27
0.15
-2.99
-3.71
-0.69
1.64
0.14
0.73
1.97
0.04
3.80
0.20
2.09
-4.08
0.76
1.67
0.50
-14.63
7.98
0.13
0.00
1.66
-1.26
9.58
-0.58
-0.85
2.39
0.03
0.34
-1.22
-4.59
-8.14
0.73
-6.76

SJ Emp
-0.13
-1.18
-0.19
0.46
0.26
0.87
1.57
-0.67
-0.24
-0.40
-0.47
0.01
-0.81
-1.86
1.12
-1.36
-0.93
-1.91
-0.36
-0.69
0.04
1.89
0.27
0.27
-3.23
0.12
-0.66
-1.78
-0.35
-7.34
0.19
-2.89
2.80
-0.24
-1.34
-5.68
4.22
-7.66
-0.45
-0.08
-2.62
-0.56
-8.12
0.57
1.50
-1.62
0.46
-1.83
1.13
-0.04
4.46
-1.05
4.97

Section 6

Net Effect
C+L
T-Stat
0.84
0.76
3.56
4.85
2.12
2.15
2.78
2.20
0.71
0.72
2.04
1.39
5.14
2.93
0.96
0.77
0.75
0.70
1.13
0.73
-0.09
-0.11
-0.30
-0.19
-0.09
-0.07
0.76
2.06
-0.20
-0.92
-0.39
-0.79
0.50
0.00
0.22
0.14
0.08
2.98
2.82
2.64
1.48
-0.14
1.92
4.59
2.12
-4.20
2.14
1.26
3.94
1.56
1.35
1.03
3.00
1.52
0.42
2.03
1.63
4.13
0.16
3.27
3.57
1.90
1.92
1.72
3.91
5.36
4.43
1.69
10.75

0.73
-0.01
0.40
0.78
0.03
6.80
8.34
1.81
7.27
-0.08
1.84
2.36
1.64
-2.81
5.47
4.61
6.55
3.63
2.55
6.50
79.73
14.05
1.05
1.35
2.69
3.04
0.82
3.17
3.90
4.53
1.38
3.72
2.72
7.02
16.33
1.98
8.46

504

r2
0.71
0.92
0.73
0.72
0.78
0.82
0.82
0.29
0.16
0.52
0.10
0.34
0.40
0.75
0.36
0.83
0.99
0.86
0.57
0.51
0.94
1.00
1.00
0.97
0.99
0.80
0.95
0.97
0.96
1.00
0.98
0.99
0.98
0.97
0.95
0.99
1.00
1.00
0.96
0.93
0.95
0.99
1.00
0.97
0.97
0.98
0.91
0.96
0.94
0.99
1.00
0.94
0.99

Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page42 of 62
Exhibit 2
Apple
Section 1
Job Title

Years
of Data
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7

Total
Emp-Years
17
127
142
63
45
98
70
182
2915
134
143
476
53
275
255
300
125
262
16
115
33
16
35
297
57
58
26
115
103
35
49
23
431
21
64
56
14
59
48
108
79
7
109
76
260
330
123
22
242
13
32
130
24
245

Section 2
Level Correlation
Coeff
T-Stat
0.95
7.08
0.95
6.94
0.95
6.80
0.95
6.73
0.95
6.73
0.95
6.52
0.94
6.46
0.94
6.42
0.94
6.33
0.94
6.30
0.94
6.27
0.94
6.23
0.94
6.18
0.94
6.09
0.93
5.78
0.93
5.69
0.93
5.69
0.93
5.65
0.93
5.63
0.93
5.58
0.93
5.56
0.93
5.55
0.93
5.46
0.92
5.42
0.92
5.39
0.92
5.35
0.92
5.30
0.92
5.30
0.92
5.23
0.92
5.21
0.92
5.14
0.92
5.12
0.91
5.03
0.91
4.94
0.91
4.93
0.91
4.86
0.91
4.86
0.91
4.83
0.90
4.69
0.90
4.67
0.90
4.60
0.90
4.59
0.90
4.56
0.90
4.54
0.89
4.48
0.89
4.48
0.89
4.46
0.89
4.45
0.89
4.45
0.89
4.43
0.89
4.41
0.89
4.34
0.89
4.34
0.89
4.30

Change Correlation
Coeff
T-Stat
0.71
2.01
0.52
1.21
0.83
2.99
0.69
1.92
0.99
12.42
0.84
3.11
0.88
3.72
0.96
7.04
0.60
1.52
0.66
1.76
0.48
1.10
0.91
4.31
0.79
2.54
0.70
1.97
0.74
2.21
0.38
0.82
0.79
2.56
0.51
1.18
0.72
2.10
0.27
0.57
0.55
1.31
0.47
1.06
0.68
1.85
0.84
3.04
0.72
2.05
0.78
2.48
0.67
1.80
0.64
1.68
0.35
0.74
0.59
1.45
0.67
1.79
0.89
3.94
-0.24
-0.50
0.54
1.30
0.33
0.71
0.93
4.90
-0.40
-0.86
0.88
3.68
-0.20
-0.42
0.18
0.37
0.58
1.43
0.85
3.17
0.66
1.75
0.66
1.76
0.98
9.92
0.84
3.12
0.46
1.04
0.84
3.09
0.21
0.42
0.60
1.50
0.94
5.69
0.94
5.72
0.57
1.38
0.68
1.88

Section 3
Contemp
1.88
0.56
-0.30
1.09
2.37
0.42
1.03
1.85
0.75
0.94
0.38
3.20
1.14
0.82
-0.07
0.33
0.64
0.99
1.20
0.71
1.06
2.57
0.43
0.57
0.69
0.81
2.23
0.86
0.71
0.67
1.20
1.50
-0.05
3.18
0.14
3.28
-0.07
1.77
0.20
0.56
2.25
1.51
0.62
0.71
1.92
-0.25
0.94
0.72
0.45
0.25
1.90
1.20
1.48
0.59

Regression Coefficients
Lagged
Revenue
6.66
-3.36
0.19
-0.28
3.49
-0.40
2.55
-0.84
-0.57
0.11
-0.03
0.15
3.36
0.26
0.66
-0.02
0.73
-0.18
1.02
-0.16
0.26
0.73
-2.66
-1.18
0.91
0.12
0.80
0.45
2.18
0.57
0.33
-0.09
1.88
0.06
1.54
-0.46
1.08
-0.14
0.94
0.29
1.69
-0.48
3.07
-1.01
0.40
0.43
1.74
0.21
0.70
0.36
0.46
0.29
2.43
-1.17
0.53
0.05
2.91
-1.10
4.66
-1.96
0.72
0.03
-0.38
0.73
0.05
0.05
3.81
-0.09
0.85
0.65
-0.05
-0.48
-0.01
-0.16
1.31
-0.18
0.71
0.09
0.99
-0.05
2.31
-0.76
0.38
0.42
-0.68
0.70
3.16
-0.98
-0.16
-0.02
1.86
0.99
1.07
-0.18
1.53
0.46
0.63
0.82
5.91
-2.76
0.50
0.31
-0.23
0.25
2.06
-0.58
0.07
0.68

2 of 22

Section 4
SJ Emp
7.09
1.66
-0.56
2.00
-0.28
-0.86
1.34
-0.43
-0.36
0.07
-1.64
5.55
0.64
-1.06
-1.09
-0.42
0.58
-0.24
0.10
-1.78
-0.89
2.89
-1.40
-0.65
-0.74
-0.50
-0.57
-1.73
-0.68
0.59
-2.50
-0.15
-0.41
4.43
-1.56
-3.16
0.43
0.90
-0.37
-1.00
1.25
-1.42
1.44
-1.60
0.42
-1.48
-1.32
1.41
-1.10
-2.58
0.22
-0.86
-0.57
-1.60

Contemp
7.10
15.61
-0.28
2.49
3.89
2.29
1.02
20.57
3.05
8.01
0.87
2.00
3.07
2.39
-0.15
1.51
5.01
4.29
2.30
0.41
11.73
2.51
0.92
0.73
2.04
3.21
5.76
81.85
1.67
1.56
2.41
3.16
-0.10
4.28
2.39
26.16
-1.14
13.53
102.47
0.88
35.83
5.15
0.91
1.07
2.63
-0.16
15.21
6.32
0.56
0.21
4.09
2.24
7.04
0.97

Regression T-Stats
Lagged
Revenue
9.22
-8.26
2.26
-7.87
2.08
-0.91
4.60
-2.54
-0.73
0.43
-0.16
0.60
0.65
0.33
4.80
-0.28
2.18
-0.96
7.07
-1.52
0.46
1.94
-1.31
-1.16
1.95
0.41
1.55
1.68
4.59
2.06
1.22
-0.67
16.56
0.79
4.47
-2.58
1.36
-0.24
0.33
0.52
10.86
-6.30
2.15
-1.27
0.30
0.85
2.15
0.46
2.46
0.95
2.06
0.77
2.33
-1.86
34.93
6.57
3.08
-2.22
5.68
-4.15
0.57
0.03
-0.60
1.79
0.09
0.19
3.52
-0.31
11.13
11.42
-0.30
-13.49
-0.23
-1.50
9.61
-1.45
285.17
64.33
1.11
-0.11
27.91
-13.71
0.96
1.67
-0.52
1.31
2.06
-1.27
-0.31
-0.05
1.60
0.94
13.64
-4.06
24.02
5.39
0.71
0.44
0.98
-0.82
1.22
0.98
-0.34
0.58
7.13
-3.42
0.11
0.86

Section 5
SJ Emp
6.61
16.05
-0.41
2.18
-0.38
-1.47
0.29
-1.92
-0.70
0.25
-1.39
1.44
0.78
-1.39
-1.39
-1.12
2.97
-0.49
0.08
-1.46
-4.69
1.18
-1.10
-0.55
-0.86
-0.78
-0.37
-83.66
-0.72
0.64
-1.91
-0.15
-0.45
2.38
-6.65
-7.06
1.66
2.78
-73.80
-0.78
7.62
-2.03
0.68
-1.10
0.39
-0.80
-10.29
10.38
-0.28
-0.84
0.24
-0.74
-1.13
-1.01

Section 6

Net Effect
C+L
T-Stat
8.54
10.88
0.75
7.07
3.19
2.94
3.64
5.17
1.80
3.15
0.39
1.18
4.39
1.02
2.51
19.20
1.48
2.83
1.97
9.04
0.64
0.68
0.53
0.75
2.05
3.12
1.62
2.24
2.11
4.69
0.66
1.43
2.52
18.16
2.53
5.03
2.28
2.10
1.65
0.36
2.75
12.46
5.64
2.42
0.83
0.53
2.30
2.76
1.39
2.85
1.28
3.10
4.66
3.32
1.39
58.99
3.62
3.03
5.33
5.82
1.92
1.15
1.12
1.44
0.01
0.01
6.99
3.91
0.99
9.56
3.23
35.05
-0.08
-0.84
3.09
24.05
0.91
225.62
1.55
1.10
4.56
34.64
1.89
3.45
-0.06
-0.05
3.87
2.30
1.77
2.70
1.61
1.45
2.01
15.88
2.25
20.45
1.08
0.73
6.17
1.04
2.40
3.79
0.97
1.38
3.55
8.33
0.65
0.59

505

r2
1.00
1.00
0.95
0.98
0.98
0.93
0.95
1.00
0.92
0.99
0.84
0.96
0.98
0.97
0.98
0.82
1.00
0.97
0.97
0.76
1.00
0.92
0.92
0.95
0.94
0.94
1.00
1.00
0.94
0.99
0.98
0.98
0.23
0.96
1.00
1.00
0.79
1.00
1.00
0.64
1.00
0.99
0.92
0.94
0.97
0.92
1.00
1.00
0.46
0.81
0.99
0.95
0.99
0.75

Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page43 of 62
Exhibit 2
Apple
Section 1
Job Title

Years
of Data
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7

Total
Emp-Years
37
34
8
103
7
8
28
61
25
7
501
74
192
11
116
239
10
44
21
17
563
12
57
145
33
131
267
47
60
8
50
57
20
20
40
144
23
72
47
19
49
29
23
332
109
18
15
11
103
38
96
103
135
14

Section 2
Level Correlation
Coeff
T-Stat
0.88
4.25
0.88
4.25
0.88
4.20
0.88
4.17
0.88
4.15
0.88
4.11
0.88
4.08
0.88
4.08
0.87
4.01
0.87
3.98
0.87
3.94
0.87
3.94
0.87
3.93
0.87
3.91
0.87
3.89
0.87
3.89
0.86
3.83
0.86
3.78
0.86
3.69
0.85
3.65
0.85
3.60
0.85
3.58
0.85
3.58
0.85
3.57
0.85
3.55
0.85
3.55
0.84
3.52
0.84
3.43
0.84
3.42
0.84
3.40
0.83
3.35
0.83
3.34
0.83
3.33
0.83
3.32
0.82
3.24
0.82
3.24
0.82
3.21
0.82
3.17
0.81
3.07
0.80
3.03
0.80
3.01
0.80
3.01
0.80
3.01
0.78
2.78
0.77
2.74
0.77
2.68
0.76
2.65
0.74
2.49
0.74
2.48
0.74
2.45
0.73
2.40
0.73
2.39
0.72
2.34
0.72
2.32

Change Correlation
Coeff
T-Stat
-0.04
-0.07
0.15
0.30
0.89
3.94
0.40
0.87
0.72
2.05
-0.04
-0.09
0.45
1.02
0.26
0.55
0.59
1.45
0.26
0.53
0.85
3.21
0.61
1.53
-0.50
-1.16
0.49
1.14
0.21
0.43
0.89
3.90
0.54
1.30
0.52
1.22
0.69
1.91
0.68
1.84
0.92
4.56
0.06
0.12
0.46
1.03
0.90
4.16
0.04
0.07
0.76
2.36
-0.16
-0.32
0.29
0.60
0.52
1.21
-0.06
-0.12
0.61
1.56
0.11
0.22
0.35
0.75
-0.38
-0.83
0.94
5.74
0.91
4.27
0.55
1.31
-0.01
-0.02
0.71
2.01
0.04
0.08
0.92
4.70
0.94
5.36
-0.58
-1.42
0.90
4.05
0.59
1.45
0.66
1.76
0.89
3.97
-0.72
-2.05
0.30
0.62
0.27
0.57
0.54
1.29
-0.04
-0.08
0.07
0.14
0.74
2.23

Section 3
Contemp
0.57
1.13
1.47
0.34
0.53
0.44
0.07
1.31
0.28
1.98
3.43
0.61
-0.27
-0.28
6.50
0.95
-4.35
-0.32
0.77
1.99
1.94
0.12
-0.26
1.96
0.55
0.54
0.22
0.83
0.83
0.13
0.65
0.25
0.24
-0.34
1.96
1.43
-1.37
-0.59
1.22
2.69
1.73
2.26
-0.22
1.12
0.35
-0.37
1.36
-0.09
0.49
1.08
1.10
0.34
-0.09
-2.58

Regression Coefficients
Lagged
Revenue
0.88
-0.53
2.90
-1.26
-0.70
0.91
0.62
0.43
0.22
-0.32
1.15
0.14
3.01
-0.73
2.69
-1.24
3.71
-1.43
2.62
-1.42
-3.62
-0.07
1.04
0.29
0.05
0.31
2.39
-0.62
7.89
-2.48
-0.13
0.56
6.24
-1.52
-0.27
0.00
-0.40
0.84
1.43
-0.04
-0.26
-0.17
0.13
-0.26
1.45
0.06
-0.40
-0.23
0.93
0.28
0.17
0.73
0.30
1.27
1.09
0.45
0.25
-0.30
3.20
-1.30
0.05
0.93
0.75
0.33
0.46
0.59
1.47
-0.20
-0.82
0.43
-0.33
0.57
-5.78
2.74
-0.65
-1.04
0.50
0.87
4.63
-3.04
0.34
0.58
0.64
-0.32
0.76
0.03
0.36
0.31
-0.21
0.95
1.16
0.51
0.10
0.69
1.42
-0.90
0.98
0.23
3.23
-1.67
0.25
1.33
0.64
0.29
0.65
0.91
0.95
3.21

3 of 22

Section 4
SJ Emp
0.36
0.78
-1.65
-0.72
-0.27
-0.78
-2.35
-1.51
-0.39
5.06
5.76
-1.97
-0.87
-0.66
6.52
-0.89
-7.36
0.96
1.36
-0.81
0.60
-0.46
1.52
2.66
-2.78
-1.81
-2.14
1.22
-0.36
-2.42
-1.56
-0.60
1.46
-0.34
0.51
-0.59
-18.75
2.39
-1.01
0.25
-0.22
-0.27
0.23
-0.44
-2.33
1.22
-1.38
1.22
-1.43
0.78
-1.24
-2.45
-0.28
19.13

Contemp
1.77
2.87
9.23
1.28
3.42
0.71
0.56
3.08
8.63
1.68
2.07
1.40
-0.23
-0.16
2.32
1.43
-0.67
-0.20
0.94
2.93
0.89
0.51
-0.14
15.41
0.76
1.90
0.14
1.10
0.54
0.36
4.31
0.87
0.59
-2.79
3.60
1.18
-0.55
-0.45
2.88
9.26
2.31
10.93
-0.21
4.74
0.61
-0.10
1.23
-0.09
1.27
1.70
2.47
2.71
-0.15
-0.23

Regression T-Stats
Lagged
Revenue
2.44
-2.49
5.65
-3.68
-2.78
5.87
1.65
1.75
1.74
-1.18
1.55
0.31
12.67
-6.31
3.00
-2.32
82.49
-54.77
2.14
-1.30
-1.57
-0.14
2.07
0.84
0.04
0.66
0.99
-0.48
2.22
-1.95
-0.16
1.08
0.87
-0.63
-0.17
0.00
-0.44
1.35
1.69
-0.07
-0.17
-0.12
0.68
-1.37
1.18
0.06
-5.76
-2.47
0.91
0.66
0.72
2.37
0.19
0.35
1.76
0.48
0.17
-0.26
3.70
-2.62
0.32
7.83
2.96
1.13
1.17
1.77
7.80
-1.91
-1.74
1.46
-0.30
0.81
-1.16
1.17
-0.50
-0.46
1.31
2.57
12.60
-10.11
0.68
1.06
8.05
-1.48
0.66
0.05
2.55
0.95
-0.28
2.19
0.75
0.29
0.13
0.90
1.62
-1.38
2.94
0.68
5.32
-3.32
0.67
3.13
5.28
3.23
1.69
1.26
0.38
0.42

Section 5
SJ Emp
0.57
0.93
-4.83
-1.23
-0.56
-0.53
-6.82
-2.70
-6.26
1.91
1.48
-1.88
-0.51
-0.16
1.50
-0.59
-0.57
0.74
0.74
-0.45
0.17
-0.74
0.40
9.44
-3.50
-2.35
-0.20
0.69
-0.29
-2.29
-4.65
-0.67
1.65
-1.02
0.51
-0.26
-1.69
0.44
-1.08
0.44
-0.16
-1.13
0.10
-0.89
-1.70
0.23
-0.68
0.68
-1.50
0.56
-1.27
-9.15
-0.14
1.02

Section 6

Net Effect
C+L
T-Stat
1.45
2.29
4.03
5.04
0.78
2.62
0.96
1.71
0.75
3.01
1.58
1.29
3.09
11.64
4.00
3.06
3.99
78.44
4.61
2.14
-0.19
-0.18
1.64
2.22
-0.22
-0.10
2.11
0.87
14.39
2.27
0.82
0.81
1.89
0.66
-0.59
-0.21
0.37
0.30
3.42
2.63
1.68
1.12
0.25
0.65
1.19
0.60
1.55
13.27
1.48
0.86
0.71
1.63
0.51
0.17
1.91
1.62
1.09
0.41
3.33
3.00
0.70
2.62
1.00
2.18
0.70
1.04
1.14
3.94
1.14
2.01
1.11
0.79
-7.16
-0.96
-1.24
-0.49
1.72
2.53
7.32
11.71
2.08
2.10
2.90
13.34
0.54
0.26
1.48
4.45
0.13
0.12
0.79
0.20
1.47
1.02
1.33
0.76
1.47
2.39
4.31
4.19
1.35
1.85
0.99
4.33
0.56
0.68
-1.62
-0.12

506

r2
0.89
0.98
1.00
0.99
0.94
0.81
1.00
0.99
1.00
0.98
0.94
0.93
0.51
0.81
0.94
0.90
0.80
0.54
0.95
0.97
0.84
0.79
0.89
1.00
0.95
0.96
0.51
0.85
0.36
0.97
1.00
0.95
0.99
1.00
0.98
0.89
0.99
0.22
0.98
1.00
0.97
1.00
0.76
0.99
0.92
0.84
0.92
0.87
0.95
0.98
0.96
0.99
0.95
0.91

Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page44 of 62
Exhibit 2
Apple
Section 1
Job Title

Years
of Data
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7

Total
Emp-Years
26
25
38
18
58
26
13
51
14
57
11
24
127
45
36
52
137
18
13
59
16
34
35
41
46
15
646
14
47
27
17
13
63
85
60
19
10
69
36
18
918
127
25
16
13
181
66
71
7
33
55
133
10
116

Section 2
Level Correlation
Coeff
T-Stat
0.70
2.22
0.70
2.20
0.70
2.20
0.66
1.95
0.66
1.95
0.65
1.90
0.65
1.90
0.64
1.88
0.64
1.87
0.64
1.86
0.63
1.82
0.63
1.80
0.62
1.79
0.62
1.79
0.58
1.58
0.57
1.57
0.56
1.51
0.55
1.49
0.55
1.48
0.55
1.46
0.54
1.45
0.54
1.42
0.53
1.39
0.53
1.38
0.52
1.36
0.52
1.35
0.52
1.35
0.51
1.33
0.51
1.31
0.50
1.30
0.49
1.25
0.49
1.24
0.47
1.20
0.47
1.18
0.45
1.11
0.44
1.10
0.44
1.08
0.42
1.04
0.42
1.03
0.41
1.01
0.41
1.00
0.39
0.96
0.38
0.93
0.38
0.93
0.38
0.91
0.37
0.90
0.37
0.88
0.36
0.86
0.34
0.80
0.32
0.76
0.31
0.73
0.29
0.68
0.26
0.61
0.09
0.20

Change Correlation
Coeff
T-Stat
0.23
0.48
0.68
1.86
0.79
2.56
0.11
0.22
0.07
0.15
0.43
0.95
0.51
1.18
0.23
0.47
0.38
0.82
-0.03
-0.05
0.45
1.01
0.57
1.40
0.04
0.08
0.82
2.90
0.86
3.38
0.56
1.34
0.25
0.51
0.33
0.69
0.52
1.23
0.06
0.12
0.47
1.07
0.41
0.90
0.50
1.17
0.52
1.21
0.33
0.69
0.73
2.16
0.00
0.00
-0.20
-0.41
0.96
6.64
-0.11
-0.23
0.19
0.38
-0.72
-2.07
-0.14
-0.29
0.43
0.96
-0.74
-2.18
-0.46
-1.03
-0.78
-2.50
-0.10
-0.20
-0.34
-0.73
-0.78
-2.47
0.53
1.24
0.22
0.46
-0.74
-2.21
0.36
0.78
0.88
3.65
0.11
0.22
0.37
0.81
-0.17
-0.34
0.37
0.79
-0.86
-3.42
0.08
0.16
-0.14
-0.28
0.40
0.87
0.41
0.89

Section 3
Contemp
-0.23
0.94
9.17
2.32
-0.76
1.80
-1.56
1.80
0.56
-0.09
1.68
-0.12
2.05
1.18
3.09
0.91
0.93
-0.11
0.42
0.37
3.59
0.50
0.35
0.82
1.08
0.40
-0.17
0.55
1.90
-1.00
0.61
-2.54
-0.42
0.01
-0.54
0.96
-5.10
-0.58
-0.26
-0.78
0.12
1.37
-0.57
0.25
0.55
1.10
-2.58
-2.34
-0.05
-2.38
0.42
-3.16
-1.11
0.90

Regression Coefficients
Lagged
Revenue
-0.43
0.86
0.69
0.33
2.35
-7.19
2.16
-0.46
0.61
1.32
1.36
-0.95
2.39
-0.40
1.79
-0.28
0.52
0.89
0.08
1.16
1.26
-0.17
-7.51
4.87
1.96
4.08
0.46
0.62
0.55
-1.14
-0.24
2.01
0.88
-0.89
-0.48
2.73
-1.07
2.09
0.17
0.75
2.10
0.38
-0.48
1.73
-0.64
1.85
0.14
0.66
1.05
-0.12
0.56
0.89
-0.16
-0.08
0.31
1.05
-0.37
0.00
1.69
0.29
0.30
1.50
2.26
-1.08
0.43
1.07
-0.28
1.09
-0.10
0.20
1.03
1.13
0.41
-0.38
-2.48
1.20
0.23
-0.76
0.43
0.76
-0.15
-0.03
-0.53
2.19
0.13
0.23
-0.84
2.33
-0.32
0.73
0.88
1.18
-4.59
3.42
-1.29
1.86
-1.04
1.86
0.60
-0.17
-0.13
1.60
0.80
2.56
-1.81
3.41
0.57
-0.01

4 of 22

Section 4
SJ Emp
-0.85
-3.50
-19.15
7.71
-2.62
0.78
6.21
0.82
-4.00
-3.51
-1.18
-14.39
-9.17
0.77
3.47
5.19
-1.03
-0.70
-2.76
-5.12
3.17
-2.69
-0.64
-1.97
0.61
-2.38
-0.05
0.73
0.63
-2.35
-1.86
0.56
-1.20
0.67
0.50
-5.03
7.95
12.14
0.15
-2.52
-1.01
-1.56
0.63
-2.61
-1.04
-2.46
0.76
2.49
-5.93
0.62
-2.53
-15.71
4.00
-0.97

Contemp
-15.24
0.89
1.03
1.39
-1.44
1.91
-0.64
1.11
1.07
-2.94
3.40
-0.13
7.13
1.08
0.92
0.41
2.28
-0.25
0.47
0.25
2.25
1.25
0.37
1.45
6.60
0.20
-2.19
0.34
3.25
-5.14
1.24
-0.86
-0.49
0.01
-1.72
2.16
-0.71
-0.30
-1.39
-0.18
3.62
1.97
-0.87
0.53
1.59
0.60
-1.62
-0.88
-0.34
-0.64
0.67
-10.86
-0.22
1.77

Regression T-Stats
Lagged
Revenue
-28.90
49.37
0.45
0.39
2.58
-0.73
1.67
-0.35
1.90
2.40
1.85
-0.84
1.99
-0.29
1.29
-0.21
1.02
2.18
2.71
47.78
3.03
-0.42
-2.03
2.22
7.37
9.16
0.92
0.50
0.56
-0.39
-0.17
1.13
2.86
-1.87
-1.33
3.40
-1.46
3.04
0.10
0.87
1.44
0.44
-1.52
5.22
-0.92
2.26
0.32
0.93
8.54
-0.68
0.51
0.62
-2.67
-0.66
0.25
0.34
-1.24
0.00
10.67
1.89
0.79
3.44
0.91
-0.51
0.68
1.03
-0.41
0.72
-0.44
0.46
3.27
4.56
0.11
-0.12
-0.89
1.11
1.93
-2.82
0.16
0.64
-5.88
-0.58
-1.00
3.99
0.31
0.29
-2.31
5.52
-1.27
1.52
0.62
0.54
-1.77
1.94
-0.51
1.11
-8.33
18.36
0.27
-0.09
-0.27
2.48
4.11
10.87
-0.52
0.90
1.37
-0.02

Section 5
SJ Emp
-12.29
-1.53
-0.53
1.99
-1.36
0.32
1.79
0.21
-3.39
-40.82
-1.01
-3.54
-8.99
0.58
0.63
1.29
-1.16
-0.55
-1.39
-2.95
0.55
-2.97
-0.30
-1.55
1.70
-0.68
-0.17
0.15
0.50
-4.56
-1.64
0.10
-0.38
0.15
0.35
-5.89
0.81
0.64
0.32
-0.31
-9.93
-1.05
0.30
-2.38
-1.00
-0.65
0.77
0.14
-20.13
0.11
-1.65
-9.37
0.41
-0.80

Section 6

Net Effect
C+L
T-Stat
-0.66
-25.59
1.62
0.82
11.52
1.20
4.48
1.69
-0.14
-0.20
3.16
2.12
0.83
0.26
3.59
1.32
1.08
1.20
-0.01
-0.26
2.93
3.65
-7.63
-1.69
4.01
7.51
1.64
1.07
3.64
0.88
0.67
0.21
1.81
2.82
-0.59
-0.78
-0.65
-0.46
0.54
0.18
5.69
1.95
0.01
0.02
-0.30
-0.20
0.96
1.08
2.13
8.30
0.96
0.38
-0.33
-2.68
0.86
0.37
1.53
2.14
0.69
2.25
0.91
1.17
-0.28
-0.06
0.01
0.01
-0.27
-0.14
-0.64
-1.31
1.98
2.79
-4.69
-0.46
-3.06
-1.33
-0.03
-0.10
-0.36
-0.05
-0.03
-0.56
0.84
0.77
-0.43
-0.46
-0.59
-0.80
0.23
0.42
1.98
0.67
-7.17
-1.79
-3.63
-1.08
-1.09
-4.77
-1.78
-0.32
0.29
0.29
-2.36
-6.72
-2.92
-0.38
1.46
1.77

507

r2
1.00
0.88
0.97
0.93
0.97
0.83
0.97
0.74
0.97
1.00
0.97
0.99
0.99
0.97
0.87
0.91
0.94
0.98
0.97
0.93
0.93
0.98
0.94
0.86
1.00
0.84
0.95
0.55
0.97
1.00
0.98
0.95
0.91
0.90
0.88
1.00
0.79
0.87
0.94
0.81
1.00
0.98
0.85
0.99
0.93
0.52
0.85
0.86
1.00
0.79
0.94
1.00
0.89
0.89

Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page45 of 62
Exhibit 2
Apple
Section 1
Job Title

Years
of Data
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6

Total
Emp-Years
29
117
26
22
31
11
46
52
50
49
166
36
21
59
40
16
19
54
48
44
20
73
19
6
15
24
6
57
8
10
6
6
8
11
19
12
19
18
166
16
57
13
39
18
8
10
28
12
24
114
22
6
90
87

Section 2
Level Correlation
Coeff
T-Stat
0.08
0.18
0.04
0.08
-0.04
-0.08
-0.04
-0.10
-0.07
-0.16
-0.27
-0.63
-0.28
-0.66
-0.36
-0.87
-0.43
-1.06
-0.48
-1.23
-0.49
-1.25
-0.50
-1.29
-0.54
-1.42
-0.62
-1.79
-0.65
-1.92
0.98
9.32
0.96
7.34
0.96
7.16
0.93
4.91
0.87
3.58
0.87
3.48
0.85
3.24
0.77
2.41
0.76
2.35
0.76
2.31
0.75
2.27
0.75
2.26
0.73
2.13
0.72
2.05
0.71
2.04
0.67
1.81
0.63
1.61
0.63
1.61
0.60
1.49
0.59
1.45
0.48
1.08
0.47
1.07
0.42
0.93
0.42
0.92
0.41
0.89
0.38
0.82
0.36
0.78
0.34
0.73
0.27
0.55
0.27
0.55
0.13
0.27
0.13
0.27
0.11
0.22
0.08
0.17
0.08
0.16
0.04
0.08
0.04
0.07
-0.01
-0.02
-0.11
-0.23

Change Correlation
Coeff
T-Stat
0.33
0.70
0.26
0.55
0.21
0.43
0.17
0.34
0.29
0.62
0.23
0.48
0.02
0.03
0.37
0.79
-0.96
-6.86
0.27
0.57
-0.44
-0.97
0.05
0.10
0.80
2.66
0.31
0.65
0.35
0.74
0.93
4.31
0.85
2.85
0.89
3.46
0.94
4.62
0.64
1.18
0.45
0.72
-0.41
-0.78
0.51
1.03
-0.46
-0.91
0.90
3.49
0.08
0.12
0.53
1.07
-0.47
-0.92
0.36
0.55
0.55
1.14
0.59
1.26
0.81
1.95
0.82
2.00
0.83
2.59
0.05
0.08
-0.06
-0.09
0.04
0.07
-0.61
-1.09
-0.55
-1.14
0.60
1.07
-0.32
-0.58
-0.14
-0.24
0.87
3.11
-0.84
-2.21
0.78
1.77
0.10
0.14
0.83
2.58
-0.61
-1.10
0.12
0.22
0.94
4.93
0.58
1.22
0.90
3.64
0.26
0.47
-0.44
-0.84

Section 3
Contemp
0.04
-0.56
-0.76
4.02
-0.47
0.75
2.17
1.19
-0.30
-0.03
-0.12
1.28
1.42
0.43
0.75

Regression Coefficients
Lagged
Revenue
0.09
1.00
1.36
-6.15
0.43
1.14
1.91
-5.35
-1.28
2.00
0.14
0.01
-1.69
6.68
0.84
-0.81
0.06
-0.07
-0.11
-0.46
0.34
-0.76
3.22
-5.96
0.36
-0.68
0.52
-0.51
0.85
-0.63

5 of 22

Section 4
SJ Emp
-2.10
1.05
-2.09
23.44
-1.97
-0.87
-6.27
-2.05
-0.09
1.13
0.70
8.31
-1.28
0.18
-0.30

Contemp
0.04
-1.15
-0.93
2.41
-0.26
0.25
1.26
2.75
-6.12
-0.06
-1.22
0.99
6.57
0.46
0.43

Regression T-Stats
Lagged
Revenue
0.12
0.78
3.45
-3.63
0.73
1.69
1.95
-2.23
-0.93
1.01
0.05
0.00
-1.10
1.77
2.07
-1.17
1.64
-0.89
-0.26
-0.43
3.94
-3.94
1.06
-0.97
1.85
-1.97
0.58
-0.70
0.46
-0.41

Section 5
SJ Emp
-0.64
0.97
-1.20
2.84
-0.32
-0.37
-1.60
-2.10
-0.54
0.48
2.00
1.00
-2.37
0.24
-0.22

Section 6

Net Effect
C+L
T-Stat
0.13
0.08
0.80
1.44
-0.34
-0.26
5.94
2.26
-1.74
-0.61
0.89
0.17
0.48
0.21
2.04
2.78
-0.24
-3.24
-0.14
-0.18
0.22
1.43
4.50
1.10
1.77
4.71
0.94
0.59
1.61
0.50

508

r2
0.73
0.96
0.99
0.97
0.64
0.21
0.82
0.95
0.99
0.55
0.96
0.61
0.99
0.48
0.32

Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page46 of 62
Exhibit 2
Apple
Section 1
Job Title

Years
of Data
6
6
6
6
6
6
6
6

Total
Emp-Years
17
16
6
40
6
1398
15
19

Section 2
Level Correlation
Coeff
T-Stat
-0.16
-0.32
-0.29
-0.60
-0.30
-0.62
-0.31
-0.65
-0.45
-1.02
-0.65
-1.70
-0.76
-2.36
-0.85
-3.22

Change Correlation
Coeff
T-Stat
-0.07
-0.13
0.78
2.16
-0.55
-1.13
-0.11
-0.19
0.84
2.67
0.32
0.59
-0.93
-4.48
-0.43
-0.83

Section 3
Contemp

Section 4

Section 5

Section 6

Regression Coefficients
Lagged
Revenue

Regression T-Stats
Lagged
Revenue

Net Effect
C+L
T-Stat

r2

6 of 22

SJ Emp

Contemp

SJ Emp

509

Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page47 of 62
Exhibit 2
Google
Section 1
Job Title

Years
of Data

Total
Emp-Years

Section 2
Level Correlation
Coeff
T-Stat
0.94
8.15
0.91
6.58
0.91
6.51
0.86
5.00
0.82
4.29
0.79
3.89
0.79
3.86
0.79
3.83
0.79
3.82
0.78
3.75
0.74
3.33
0.71
3.05
0.71
3.01
0.70
2.90
0.67
2.68
0.62
2.39
0.59
2.20
0.56
2.05
0.51
1.78
0.48
1.63
0.27
0.84
0.81
3.90
0.80
3.75
0.75
3.16
0.71
2.82
0.66
2.47
0.52
1.74
0.32
0.95
0.84
4.08
0.78
3.27
0.73
2.80
0.71
2.63
0.67
2.38
0.64
2.18
0.56
1.79
0.44
1.28
0.34
0.95
0.31
0.86
0.26
0.72
0.22
0.59
0.09
0.23
0.06
0.17
-0.15
-0.40
-0.24
-0.66
-0.54
-1.69
0.78
3.05
0.78
3.04
0.71
2.50
0.69
2.34
0.64
2.06
0.55
1.60
0.51
1.45
0.39
1.03
0.37
0.97
0.35
0.91
0.30
0.76
0.21
0.52
0.20
0.50
0.17
0.42

Section 3

Change Correlation
Coeff
T-Stat
0.89
5.63
0.88
5.21
0.83
4.27
0.76
3.30
0.82
4.05
0.78
3.55
0.75
3.22
0.61
2.21
0.84
4.31
0.82
4.01
0.75
3.24
0.72
2.91
0.83
4.25
0.70
2.78
0.50
1.64
0.47
1.52
0.55
1.84
0.53
1.77
0.23
0.66
0.39
1.21
-0.02
-0.05
0.77
3.21
0.72
2.51
0.85
4.29
0.47
1.42
0.50
1.53
0.62
2.09
0.68
2.45
0.82
3.45
0.77
2.94
0.80
3.23
0.70
2.43
0.71
2.45
0.60
1.84
0.83
3.70
0.63
2.00
0.18
0.46
0.54
1.58
0.45
1.12
0.30
0.77
-0.11
-0.27
0.01
0.02
-0.25
-0.64
-0.10
-0.24
-0.22
-0.55
0.71
2.28
0.92
5.32
0.70
2.21
0.76
2.58
0.76
2.65
0.85
3.66
0.34
0.81
0.49
1.26
0.63
1.81
0.29
0.68
0.38
0.92
0.24
0.55
-0.11
-0.25
0.52
1.36

Contemp
0.08
0.26
0.80
0.16
-0.08
-0.21
0.45
-0.27
0.61
0.38
0.64
-0.30
0.68
-0.29
-0.72
0.27
-1.63
-2.49
-1.01
-0.98
0.15
0.35
-0.11
1.58
1.78
1.25
0.46
1.20
1.37
0.96
1.06
1.73
0.80
0.28
0.12
2.00
1.05
-0.17
0.44
-0.23
0.35
0.56
-2.18
-1.80
-0.63
1.10
1.88
0.75
0.56
1.02
1.26
0.53
0.46
0.32
-1.44
-0.60
1.32
0.76
-0.08

7 of 22

Regression Coefficients
Lagged
Revenue
0.07
1.36
0.10
0.73
0.26
0.48
0.08
0.70
-1.78
2.60
-1.42
2.46
0.57
0.45
-0.71
2.24
0.50
0.12
0.24
0.53
0.88
-0.45
-2.66
3.51
0.53
0.03
-1.04
1.65
-1.63
2.36
0.41
0.37
-4.50
5.16
-7.13
7.79
-1.63
2.56
-2.45
3.07
0.67
0.31
0.43
0.23
-0.45
1.71
2.53
-1.92
3.60
-2.30
1.78
-1.19
0.10
0.22
1.43
-0.38
2.09
-0.38
1.43
-0.46
1.36
-0.75
2.75
-2.01
0.83
-0.13
0.10
0.34
0.02
1.64
0.63
0.47
1.92
-0.72
-0.39
2.01
0.25
-0.04
-1.16
2.30
0.55
0.79
1.41
-0.72
-3.28
3.77
-3.72
4.55
-1.27
2.21
1.74
0.04
2.60
-2.06
1.66
0.17
0.45
0.11
1.13
-0.62
-0.55
1.38
0.15
1.09
0.80
0.61
0.51
1.07
-4.65
5.64
-2.22
3.62
1.39
-0.83
1.14
0.60
-0.37
1.79

Section 4
SJ Emp
-2.10
-0.87
-1.30
-1.49
0.26
-2.14
-2.87
-3.07
-1.31
-2.31
-0.85
-1.03
-1.25
-1.88
-3.79
-1.40
-4.24
-5.04
-2.55
-5.23
-4.53
-2.19
-3.16
-2.75
0.40
1.94
1.96
-3.13
-0.78
1.25
0.45
1.05
0.74
-0.24
-0.59
0.85
-0.01
1.80
1.69
-0.22
2.64
-1.11
-6.73
-2.91
-1.20
3.10
-4.37
-3.81
1.61
2.14
2.37
0.81
0.32
-0.52
-3.81
4.53
8.66
3.34
-0.64

Contemp
0.45
1.01
0.87
0.40
-0.11
-0.56
0.99
-0.83
1.49
1.00
2.62
-0.32
1.35
-0.93
-2.59
0.48
-1.47
-2.28
-1.52
-0.85
0.32
1.13
-0.14
3.14
2.18
3.31
0.71
1.21
4.96
5.78
2.63
7.82
2.41
0.63
0.18
0.89
1.31
-0.23
0.59
-0.78
1.22
1.04
-1.31
-2.13
-1.34
0.75
3.56
2.83
1.59
3.30
0.69
0.40
0.75
0.57
-0.38
-0.29
0.97
0.68
-0.26

Regression T-Stats
Lagged
Revenue
0.26
3.49
0.27
1.53
0.13
0.35
0.14
0.89
-1.70
2.30
-2.52
4.01
0.55
0.79
-1.34
4.09
0.56
0.20
0.27
0.99
1.79
-1.17
-1.73
2.31
0.47
0.04
-2.14
2.97
-3.56
4.96
0.50
0.37
-2.51
2.86
-3.94
4.41
-1.63
2.14
-1.26
1.94
0.91
0.40
0.64
0.53
-0.24
1.71
2.44
-2.19
2.42
-1.61
3.15
-1.67
0.09
0.15
0.71
-0.24
3.34
-0.84
3.93
-1.70
1.44
-1.12
6.48
-5.33
1.03
-0.21
0.10
0.55
0.03
1.22
0.16
0.13
1.32
-0.55
-0.39
1.39
0.24
-0.03
-2.06
4.60
1.12
0.93
1.55
-0.68
-1.20
1.38
-2.64
3.35
-1.50
2.05
0.51
0.02
1.63
-1.79
2.60
0.37
0.57
0.16
1.62
-1.01
-0.15
0.40
0.05
0.45
0.80
0.43
0.58
0.97
-0.58
0.75
-0.54
0.77
0.50
-0.31
0.56
0.33
-0.67
2.41

Section 5
SJ Emp
-3.85
-1.28
-0.64
-1.13
0.15
-2.41
-1.95
-3.87
-1.16
-1.54
-0.82
-0.42
-0.83
-1.92
-5.62
-0.72
-1.61
-1.94
-1.56
-2.93
-3.20
-1.75
-2.76
-1.43
0.12
1.23
1.13
-1.47
-0.51
1.37
0.23
0.90
0.54
-0.18
-0.27
0.07
0.00
0.70
0.85
-0.12
1.48
-0.37
-0.72
-0.63
-0.46
0.24
-1.79
-3.67
1.11
1.81
0.32
0.30
0.22
-0.59
-0.48
0.24
1.46
0.78
-0.70

Section 6

Net Effect
C+L
T-Stat
0.15
0.37
0.36
0.62
1.06
0.37
0.24
0.26
-1.86
-1.10
-1.63
-1.80
1.02
0.69
-0.98
-1.19
1.11
0.87
0.62
0.50
1.52
2.14
-2.97
-1.23
1.21
0.75
-1.33
-1.73
-2.35
-3.28
0.68
0.51
-6.13
-2.16
-9.62
-3.40
-2.64
-1.62
-3.43
-1.12
0.82
0.70
0.78
0.81
-0.56
-0.21
4.11
2.77
5.38
2.41
3.03
3.39
0.56
0.33
2.62
0.89
3.46
4.07
2.40
4.80
2.42
1.86
4.48
7.35
1.62
1.47
0.38
0.27
0.14
0.11
2.63
0.45
2.97
1.39
-0.56
-0.34
0.69
0.39
-1.39
-1.72
0.91
1.23
1.96
1.43
-5.46
-1.31
-5.52
-2.58
-1.90
-1.52
2.84
0.58
4.48
2.23
2.41
2.73
1.01
0.92
2.15
2.18
0.71
0.14
0.68
0.17
1.26
0.79
0.83
0.58
-6.10
-0.52
-2.82
-0.47
2.71
0.67
1.90
0.61
-0.45
-0.53

r2

510

0.96
0.91
0.88
0.75
0.89
0.94
0.77
0.95
0.79
0.80
0.74
0.86
0.75
0.84
0.91
0.59
0.82
0.91
0.68
0.83
0.75
0.77
0.90
0.92
0.86
0.89
0.63
0.77
0.97
0.96
0.82
0.97
0.93
0.80
0.92
0.77
0.63
0.85
0.60
0.97
0.74
0.74
0.58
0.88
0.70
0.85
0.96
0.96
0.87
0.96
0.87
0.96
0.95
1.00
0.92
0.68
0.78
0.91
0.97

Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page48 of 62
Exhibit 2
Google
Section 1
Job Title

Years
of Data

Total
Emp-Years

Section 2
Level Correlation
Coeff
T-Stat
0.11
0.26
0.10
0.25
0.09
0.22
0.08
0.19
0.00
0.00
-0.19
-0.47
0.94
6.31
0.88
4.22
0.81
3.05
0.80
2.97
0.78
2.79
0.77
2.68
0.76
2.60
0.73
2.36
0.72
2.31
0.70
2.22
0.69
2.14
0.67
2.00
0.64
1.87
0.63
1.80
0.62
1.76
0.61
1.74
0.60
1.68
0.60
1.67
0.57
1.56
0.56
1.52
0.50
1.29
0.49
1.26
0.47
1.20
0.44
1.11
0.44
1.09
0.43
1.06
0.41
1.02
0.40
0.97
0.23
0.53
0.22
0.51
0.21
0.49
0.18
0.41
0.13
0.29
-0.30
-0.69
-0.30
-0.69
0.94
5.52
0.82
2.84
0.81
2.78
0.79
2.55
0.78
2.53
0.74
2.19
0.71
2.02
0.70
1.99
0.68
1.86
0.63
1.62
0.59
1.45
0.58
1.44
0.57
1.40
0.56
1.37
0.54
1.30
0.54
1.27
0.52
1.21
0.47
1.06

Section 3

Change Correlation
Coeff
T-Stat
0.05
0.12
0.40
0.98
0.47
1.20
0.61
1.74
0.54
1.44
0.36
0.87
0.98
10.15
0.98
9.66
0.93
5.04
0.89
3.87
0.92
4.85
0.87
3.50
0.79
2.55
0.77
2.38
0.73
2.15
0.77
2.40
0.75
2.28
0.86
3.38
0.87
3.48
0.55
1.14
0.63
1.61
0.68
1.83
0.64
1.66
0.75
2.29
0.90
4.02
0.76
2.33
0.39
0.83
0.67
1.78
0.38
0.82
0.37
0.81
0.42
0.92
0.45
0.99
0.49
0.79
0.54
1.30
0.45
1.01
0.16
0.22
0.41
0.90
0.31
0.66
0.00
-0.01
-0.11
-0.22
-0.60
-1.51
0.96
5.86
0.88
3.25
0.92
4.09
0.82
2.51
0.98
9.30
0.84
2.71
0.79
2.22
0.75
1.95
0.97
6.88
0.84
2.71
0.55
1.13
0.63
1.41
0.51
1.02
0.63
1.40
0.56
1.17
0.75
1.95
0.78
2.19
0.48
0.94

Contemp
1.78
-0.64
-0.22
-0.11
-0.19
-0.44
0.92
1.71
2.09
1.89
-0.04
-0.01
-2.08
-0.48
-2.48
-0.78
-0.69
1.48
-0.04
0.39
-0.92
0.01
-0.89
0.41
0.15
0.78
4.23
1.37
-0.80
-1.66
-0.82
-0.65
1.37
-5.72
0.28
2.68
-0.83
-0.20
-0.36
3.76
-1.75

8 of 22

Regression Coefficients
Lagged
Revenue
4.82
-3.95
-1.19
2.95
-0.67
2.13
-0.73
1.64
-1.04
2.39
-1.21
2.37
0.44
0.15
1.08
-1.17
1.73
-1.40
2.59
-2.38
-1.56
2.30
-0.93
1.40
-3.14
6.08
-1.11
2.62
-6.19
6.26
-1.84
3.07
-2.40
3.41
1.36
-0.94
-0.79
1.30
-0.10
2.24
-2.25
3.15
-0.21
1.26
-1.99
3.14
0.22
0.58
-0.71
1.44
0.82
-0.11
8.54
-8.63
-4.14
4.70
-1.63
2.83
-2.94
4.48
-1.60
2.92
-1.18
2.15
2.80
-2.02
-13.34
10.00
0.43
0.82
4.65
-1.97
-3.92
4.02
-0.67
2.19
-0.84
1.88
6.86
-6.03
-2.91
2.70

Section 4
SJ Emp
-8.75
-1.74
-1.85
0.18
4.19
-2.43
1.14
1.74
4.09
-0.19
0.05
1.72
-2.19
0.84
-2.27
-1.89
-7.95
2.69
0.83
12.58
-0.31
0.28
-0.82
1.15
1.90
0.71
-7.90
24.13
-2.19
-6.60
-2.97
-1.97
0.00
5.70
0.22
0.00
7.39
2.29
-1.39
2.52
-1.26

Contemp
0.53
-0.96
-0.22
-0.35
-0.27
-0.85
1.60
2.76
11.51
1.24
-0.07
-0.03
-1.36
-6.23
-3.18
-9.88
-0.25
0.97
-0.15

Section 5

Regression T-Stats
Lagged
Revenue
0.77
-0.59
-1.03
2.17
-0.39
1.04
-1.26
2.37
-0.75
1.17
-1.21
2.05
0.34
0.13
0.95
-0.95
5.52
-4.20
0.96
-0.73
-1.45
2.12
-1.46
2.31
-1.38
1.95
-8.70
18.00
-3.57
4.53
-12.40
19.74
-0.42
0.61
0.51
-0.33
-1.63
2.67

SJ Emp
-0.38
-0.98
-0.85
0.16
1.85
-1.36
0.94
1.42
10.69
-0.07
0.04
2.49
-0.97
7.53
-2.61
-11.61
-1.33
0.73
1.56

Section 6

Net Effect
C+L
T-Stat
6.61
0.72
-1.83
-1.01
-0.89
-0.33
-0.84
-0.97
-1.24
-0.59
-1.66
-1.10
1.36
0.76
2.78
1.63
3.82
7.88
4.48
1.07
-1.60
-0.99
-0.94
-1.01
-5.22
-1.38
-1.59
-7.81
-8.67
-3.46
-2.62
-11.63
-3.09
-0.37
2.85
0.69
-0.83
-1.15

r2
0.69
0.98
0.96
0.92
0.95
0.94
0.99
0.99
1.00
0.91
0.99
0.99
0.98
1.00
1.00
1.00
0.93
0.94
0.99

-4.54
0.02
-5.88
0.85
0.22
1.67
1.16
0.11
-3.13
-0.97
-0.73
-0.59

-5.33
-0.15
-6.81
0.25
-0.49
0.94
1.18
-0.20
-3.15
-0.89
-0.68
-0.57

8.35
0.74
10.24
0.60
1.27
-0.12
-1.07
0.22
6.13
1.31
1.34
0.99

-0.79
0.18
-2.59
1.23
1.40
0.79
-1.13
0.91
-4.50
-1.73
-1.06
-0.91

-3.17
-0.20
-2.88
0.64
-0.56
1.60
12.77
-2.77
-2.43
-4.59
-2.42
-1.83

-5.10
-0.09
-6.54
0.47
-0.26
1.20
1.17
-0.08
-3.16
-0.92
-0.70
-0.58

1.00
0.89
1.00
0.99
0.97
0.99
0.85
0.84
0.99
0.93
0.88
0.98

-1.24
0.38

-1.29
0.26

1.52
0.38

1.11
0.10

-19.06
0.71

-1.27
0.30

0.94
1.00

-2.91
-0.92
-1.32
6.36
-2.35

-5.34
-1.76
-1.38
5.97
-2.34

6.73
4.10
3.83
-5.30
2.92

2.49
1.40
-0.58
2.11
-1.03

-4.76
-0.87
-1.20
10.62
-4.65

-4.89
-1.55
-1.43
6.14
-2.36

0.99
0.98
0.99
1.00
0.94

511

Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page49 of 62
Exhibit 2
Google
Section 1
Job Title

Years
of Data

Total
Emp-Years

Section 2
Level Correlation
Coeff
T-Stat
0.44
0.99
0.42
0.93
0.38
0.83
0.35
0.74
0.34
0.72
0.30
0.63
0.30
0.63
0.29
0.61
0.25
0.51
0.22
0.45
0.19
0.39
0.15
0.31
0.14
0.29
0.12
0.23
0.10
0.20
0.09
0.18
0.07
0.13
-0.04
-0.09
-0.05
-0.11
-0.24
-0.48

Section 3

Change Correlation
Coeff
T-Stat
0.60
1.32
0.50
0.99
0.42
0.81
0.27
0.49
0.64
1.45
0.95
3.20
0.18
0.32
0.17
0.30
0.18
0.32
0.08
0.14
0.55
1.13
0.30
0.45
0.37
0.69
0.15
0.27
0.58
1.24
0.01
0.01
0.07
0.12
-0.37
-0.69
-0.28
-0.51
-0.60
-1.31

Contemp

9 of 22

Section 4

Section 5

Section 6

Regression Coefficients
Lagged
Revenue

Regression T-Stats
Lagged
Revenue

Net Effect
C+L
T-Stat

r2

SJ Emp

Contemp

SJ Emp

512

Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page50 of 62
Exhibit 2
Intel
Section 1
Job Title

Years
Total
of Data Emp-Years
11
432
11
1501
11
233
11
3042
11
5042
11
293
11
724
11
59
11
394
11
3991
11
715
11
437
11
6082
11
912
11
31
11
216
11
1681
11
103
11
2903
11
413
11
1438
11
2235
11
4821
11
638
11
760
11
501
11
1538
11
292
11
528
11
75
11
244
11
5735
11
2120
11
328
11
1011
11
811
11
262
11
1332
11
104
11
91
11
127
11
1525
11
9515
11
369
11
6476
11
73
11
1580
11
165
11
573
11
155
11
598
11
548
11
1676
11
473
11
402
11
373

Section 2
Level Correlation
Coeff
T-Stat
0.96
10.82
0.96
9.78
0.94
8.46
0.94
8.03
0.92
7.30
0.91
6.73
0.88
5.65
0.88
5.56
0.88
5.52
0.88
5.51
0.86
4.96
0.85
4.85
0.85
4.85
0.85
4.76
0.84
4.74
0.83
4.50
0.83
4.45
0.81
4.17
0.81
4.12
0.81
4.11
0.81
4.08
0.80
4.01
0.80
4.00
0.80
3.98
0.80
3.97
0.79
3.91
0.79
3.90
0.79
3.89
0.79
3.81
0.78
3.80
0.78
3.78
0.78
3.75
0.78
3.72
0.77
3.66
0.77
3.64
0.77
3.62
0.77
3.61
0.77
3.61
0.77
3.57
0.76
3.52
0.75
3.44
0.75
3.43
0.75
3.39
0.74
3.35
0.74
3.31
0.74
3.27
0.74
3.26
0.73
3.24
0.73
3.18
0.72
3.15
0.72
3.14
0.72
3.11
0.72
3.08
0.72
3.07
0.71
3.06
0.71
3.04

Change Correlation
Coeff
T-Stat
0.95
8.41
0.94
7.56
0.91
6.14
0.89
5.67
0.91
6.21
0.89
5.46
0.94
8.07
0.72
2.91
0.88
5.34
0.96
9.32
0.96
9.29
0.84
4.41
0.94
7.51
0.94
7.60
0.82
4.00
0.83
4.23
0.92
6.69
0.87
4.91
0.95
8.50
0.95
8.85
0.93
7.04
0.89
5.55
0.96
9.45
0.91
6.09
0.93
7.45
0.88
5.24
0.91
6.15
0.82
4.10
0.75
3.23
0.81
3.88
0.90
5.76
0.91
6.32
0.95
9.08
0.77
3.41
0.91
6.37
0.84
4.31
0.91
6.02
0.92
6.65
0.84
4.35
0.89
5.55
0.90
6.00
0.89
5.39
0.86
4.86
0.97
10.62
0.97
10.58
0.54
1.83
0.93
7.07
0.94
7.74
0.97
11.28
0.91
6.37
0.89
5.39
0.82
4.03
0.94
7.83
0.93
7.05
0.88
5.17
0.89
5.66

Section 3
Contemp
2.03
1.56
1.47
0.61
0.81
2.30
1.43
1.12
0.63
1.21
1.41
0.76
0.81
0.95
0.59
0.66
0.78
0.76
0.92
0.88
0.96
0.73
0.80
0.77
0.94
0.75
0.78
0.70
0.84
2.04
0.68
0.76
0.74
0.75
0.74
0.67
0.75
0.79
0.53
1.09
0.35
0.78
0.89
0.80
0.88
0.69
0.83
0.74
0.74
1.26
0.65
0.60
0.64
0.78
0.60
0.86

10 of 22

Regression Coefficients
Lagged
Revenue
-0.51
0.64
0.30
0.32
1.33
-0.23
0.39
-0.20
2.22
-0.06
0.95
-0.19
0.58
0.19
0.73
0.22
0.35
-0.13
0.07
0.45
-0.28
0.49
0.75
0.30
0.45
0.34
0.69
0.20
0.35
0.44
0.62
0.09
0.39
0.30
0.70
0.09
0.20
0.32
0.38
0.07
0.63
0.02
0.22
0.42
0.19
0.27
0.53
0.13
0.34
0.23
0.24
0.46
0.20
0.22
0.83
0.05
1.07
0.36
0.36
0.21
0.61
0.06
0.29
0.30
0.29
0.11
0.71
0.38
0.36
-0.06
0.44
0.10
0.54
0.02
0.51
0.18
0.19
0.54
0.23
-0.37
0.00
0.00
0.45
-0.05
0.85
-0.21
0.28
0.13
0.17
0.11
1.21
-0.10
0.46
0.21
0.42
0.07
0.18
-0.01
-0.07
0.62
0.32
0.32
0.45
0.46
0.29
-0.03
0.23
0.24
0.22
0.25
0.10
0.41

Section 4
SJ Emp
-0.34
-0.54
-0.09
0.31
-0.63
-0.45
-0.55
-0.33
0.06
-0.45
-0.32
-0.49
-0.48
-0.59
-0.13
0.03
-0.37
-0.30
-0.30
-0.09
-0.19
-0.36
-0.26
-0.22
-0.29
-0.50
-0.05
-0.23
-0.95
-0.24
-0.23
-0.31
-0.08
-0.88
0.16
-0.20
-0.17
-0.35
-0.50
0.29
0.08
0.15
0.02
-0.19
-0.05
-0.26
-0.44
-0.14
0.08
-0.88
-0.39
-0.71
0.09
-0.21
-0.11
-0.58

Contemp
6.11
6.76
4.71
7.76
3.59
4.05
1.48
2.35
4.97
5.45
4.26
4.90
6.95
3.95
3.17
4.10
5.05
4.60
8.74
5.34
3.97
7.48
12.44
4.39
5.66
4.67
3.77
3.30
4.51
3.00
9.04
6.40
11.59
4.32
6.31
3.33
4.38
4.64
4.55
3.84
3.84
5.52
4.12
12.18
9.63
3.46
4.96
12.31
10.93
3.47
5.41
2.24
12.56
11.30
4.23
3.13

Regression T-Stats
Lagged
Revenue
-0.78
1.25
0.36
0.73
0.74
-0.25
2.09
-1.33
2.93
-0.23
0.63
-0.18
0.38
0.39
0.84
0.37
1.77
-0.54
0.12
2.00
-0.51
1.60
1.85
1.46
1.58
2.34
1.52
0.76
0.95
1.78
2.02
0.34
1.16
1.60
2.74
0.41
0.80
2.51
1.23
0.34
1.40
0.08
1.12
3.34
1.28
3.21
1.74
0.59
1.03
1.16
0.68
2.22
0.59
0.79
2.23
0.16
2.41
1.37
0.25
0.19
4.38
0.55
1.23
2.00
2.62
1.25
2.20
1.67
1.72
-0.35
1.31
0.35
2.21
0.07
1.60
0.85
0.98
3.37
0.37
-0.82
0.02
0.00
1.98
-0.25
2.74
-0.75
2.90
1.51
1.06
0.97
4.54
-0.32
1.46
1.03
4.81
0.79
1.79
-0.09
-0.14
1.57
1.65
2.06
0.98
1.36
3.94
-0.39
1.86
2.72
1.02
1.29
0.26
1.26

Section 5
SJ Emp
-0.76
-1.63
-0.15
1.93
-2.53
-0.54
-1.04
-0.49
0.30
-1.73
-0.87
-2.05
-2.61
-1.49
-0.52
0.08
-1.35
-1.11
-1.67
-0.31
-0.43
-2.29
-2.23
-0.74
-1.11
-1.90
-0.17
-0.52
-3.86
-0.23
-1.62
-1.53
-0.67
-3.46
0.66
-0.63
-0.64
-1.17
-2.61
0.50
0.63
0.54
0.06
-1.69
-0.28
-0.91
-1.57
-1.28
0.67
-2.13
-1.93
-1.45
1.04
-1.66
-0.47
-1.61

Section 6

Net Effect
C+L
T-Stat
1.52
1.78
1.86
2.07
2.80
1.46
1.00
4.39
3.03
4.40
3.25
1.88
2.00
2.26
1.85
1.54
0.98
3.77
1.28
2.52
1.13
2.18
1.51
3.13
1.27
4.17
1.64
3.53
0.94
2.06
1.28
3.57
1.17
3.20
1.46
4.40
1.12
4.24
1.26
3.91
1.58
3.38
0.95
4.04
1.00
5.90
1.31
3.66
1.28
3.47
0.99
2.42
0.98
2.32
1.53
3.43
1.91
3.58
2.40
1.22
1.29
7.24
1.06
3.83
1.03
7.72
1.46
3.53
1.09
4.25
1.11
2.49
1.28
4.18
1.30
3.57
0.72
2.80
1.32
2.15
0.35
1.75
1.24
4.20
1.74
4.39
1.08
8.85
1.05
5.69
1.91
5.11
1.30
3.58
1.16
10.29
0.92
7.00
1.20
1.99
0.97
3.95
1.05
1.88
0.93
9.19
1.00
6.68
0.82
2.88
0.96
1.92

r2

513

0.95
0.96
0.92
0.95
0.96
0.88
0.91
0.81
0.87
0.97
0.95
0.95
0.97
0.94
0.91
0.93
0.96
0.93
0.98
0.95
0.92
0.98
0.99
0.94
0.96
0.96
0.90
0.85
0.96
0.83
0.97
0.97
0.99
0.93
0.95
0.81
0.92
0.94
0.96
0.83
0.86
0.95
0.91
0.99
0.98
0.90
0.95
0.99
0.98
0.92
0.97
0.88
0.99
0.99
0.94
0.89

Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page51 of 62
Exhibit 2
Intel
Section 1
Job Title

Years
Total
of Data Emp-Years
11
1906
11
3531
11
934
11
1873
11
130
11
2037
11
88
11
366
11
137
11
828
11
969
11
87
11
179
11
8983
11
934
11
1049
11
146
11
509
11
1402
11
2097
11
268
11
546
11
12004
11
577
11
50
11
358
11
753
11
517
11
547
11
834
11
556
11
361
11
955
11
188
11
169
11
91
11
94
11
59
11
537
11
249
11
557
11
1504
11
159
11
629
11
427
11
498
11
465
11
7219
11
641
11
1364
11
117
11
3942
11
198
11
9310
11
910
11
1690

Section 2
Level Correlation
Coeff
T-Stat
0.71
3.04
0.71
3.03
0.71
3.03
0.71
3.02
0.71
2.99
0.70
2.98
0.70
2.98
0.70
2.95
0.70
2.94
0.70
2.92
0.70
2.91
0.69
2.89
0.69
2.87
0.69
2.87
0.69
2.86
0.69
2.85
0.69
2.84
0.69
2.84
0.69
2.83
0.68
2.81
0.68
2.77
0.68
2.76
0.68
2.75
0.67
2.74
0.67
2.72
0.67
2.72
0.67
2.70
0.67
2.69
0.67
2.68
0.66
2.67
0.66
2.66
0.66
2.65
0.66
2.65
0.66
2.64
0.66
2.63
0.66
2.62
0.66
2.60
0.65
2.59
0.65
2.59
0.65
2.59
0.65
2.58
0.65
2.54
0.64
2.53
0.64
2.51
0.64
2.50
0.64
2.49
0.64
2.49
0.64
2.47
0.64
2.47
0.63
2.45
0.63
2.44
0.63
2.42
0.63
2.42
0.63
2.40
0.62
2.40
0.62
2.39

Change Correlation
Coeff
T-Stat
0.97
10.58
0.89
5.61
0.92
6.73
0.96
9.25
0.90
5.77
0.92
6.42
0.91
6.08
0.95
8.65
0.67
2.53
0.93
7.12
0.91
6.08
0.75
3.25
0.87
5.06
0.96
9.77
0.96
10.05
0.89
5.67
0.65
2.41
0.89
5.51
0.94
7.53
0.97
11.50
0.95
8.82
0.94
7.55
0.95
8.95
0.96
9.51
0.45
1.42
0.85
4.50
0.97
11.28
0.84
4.39
0.95
9.06
0.94
7.57
0.89
5.49
0.55
1.88
0.95
8.72
0.88
5.23
0.92
6.63
0.84
4.34
0.84
4.32
0.81
3.93
0.97
11.61
0.78
3.47
0.90
5.76
0.90
5.82
0.85
4.66
0.94
7.72
0.87
5.03
0.91
6.15
0.92
6.44
0.93
7.41
0.97
10.80
0.95
8.60
0.86
4.68
0.97
10.47
0.75
3.16
0.93
7.13
0.94
7.87
0.96
10.06

Section 3
Contemp
0.85
0.72
0.72
0.85
0.86
0.63
0.69
0.67
0.71
0.63
0.66
0.92
0.64
0.78
0.83
0.68
0.39
0.70
0.77
0.78
0.83
0.72
0.76
0.82
1.17
0.58
0.91
0.49
0.78
0.81
0.73
1.08
0.67
0.67
0.78
1.85
0.61
0.97
0.81
0.69
0.61
0.64
0.60
0.84
0.58
0.51
0.72
0.70
0.70
0.84
0.66
0.80
0.68
0.67
0.72
0.63

11 of 22

Regression Coefficients
Lagged
Revenue
0.22
0.13
0.21
0.33
0.36
0.04
0.36
0.21
0.03
0.42
0.23
0.18
0.06
0.27
0.18
0.16
0.37
0.76
0.27
-0.10
0.35
-0.18
1.57
-0.16
0.05
0.57
0.25
-0.03
0.15
0.12
0.28
0.40
0.43
0.29
0.18
0.30
0.19
0.26
0.15
0.07
0.00
0.24
0.29
0.07
0.28
-0.02
0.18
0.02
0.66
0.28
0.40
-0.23
0.20
-0.12
0.28
0.06
0.29
0.08
0.02
0.36
0.28
-0.05
1.40
-0.82
0.22
-0.09
0.43
-0.06
-0.01
0.43
0.51
0.49
0.00
0.79
0.78
-0.29
0.20
0.12
0.54
-0.26
0.06
0.35
0.19
0.22
0.38
0.23
0.25
-0.04
0.23
0.07
0.13
0.12
0.14
0.13
0.15
-0.07
0.06
0.07
0.26
-0.09
0.34
0.73
0.17
0.06
0.59
0.33
0.26
-0.11
0.22
0.02
0.21
-0.01

Section 4
SJ Emp
-0.14
-0.26
-0.02
-0.43
-0.38
-0.11
-0.13
-0.11
-0.67
0.06
0.26
-0.84
-0.77
0.09
-0.04
-0.60
-0.16
-0.17
-0.34
-0.02
-0.10
-0.04
0.07
0.02
-0.65
0.30
0.25
0.02
-0.16
-0.27
0.02
0.92
0.12
0.11
-0.34
-0.64
-0.89
0.10
-0.17
0.23
-0.26
-0.12
-0.42
0.15
0.02
-0.02
-0.04
0.21
0.06
0.15
-1.36
-0.07
-0.81
0.23
0.05
-0.03

Contemp
9.03
7.95
7.71
9.91
3.38
8.43
3.97
13.19
3.37
5.89
6.39
4.41
5.02
12.24
12.79
4.91
1.82
4.88
4.41
13.52
7.42
10.66
16.18
6.42
1.34
4.89
18.00
3.39
9.05
8.80
3.34
4.01
6.90
7.43
4.71
3.26
1.50
2.52
12.42
3.24
4.22
4.79
3.11
6.63
3.76
4.81
4.33
6.35
21.06
7.62
1.62
7.41
1.45
12.47
6.85
9.53

Regression T-Stats
Lagged
Revenue
1.52
1.05
1.32
2.79
2.74
0.33
2.60
2.01
0.07
1.28
1.93
1.78
0.21
1.20
2.16
2.20
1.01
2.72
1.78
-0.60
2.57
-1.14
3.84
-0.58
0.28
3.39
2.56
-0.35
1.57
1.42
1.15
2.29
1.34
1.00
0.78
1.58
0.81
1.16
1.65
0.91
-0.01
1.66
2.99
0.76
4.10
-0.24
1.06
0.12
0.35
0.19
2.47
-1.27
2.81
-1.70
1.48
0.26
2.41
0.68
0.16
3.17
1.08
-0.15
3.26
-2.79
1.62
-0.63
3.15
-0.46
-0.04
2.09
0.37
0.49
0.00
1.68
1.75
-0.57
2.35
1.33
1.77
-0.82
0.27
1.84
1.02
1.19
1.51
0.77
1.51
-0.25
1.03
0.32
0.92
0.74
0.57
0.55
0.90
-0.43
1.36
1.47
1.56
-0.57
0.75
1.47
1.11
0.37
0.87
0.59
3.48
-1.33
1.61
0.13
2.25
-0.08

Section 5
SJ Emp
-0.83
-1.66
-0.10
-2.80
-0.96
-0.85
-0.54
-1.16
-2.35
0.37
1.47
-2.69
-4.03
0.73
-0.31
-2.62
-0.52
-0.74
-1.27
-0.15
-0.55
-0.29
0.81
0.08
-0.47
1.51
2.54
0.07
-1.08
-1.75
0.07
2.83
0.72
0.60
-1.30
-0.66
-1.45
0.15
-1.54
0.62
-1.16
-0.54
-1.05
0.67
0.07
-0.12
-0.16
1.00
1.02
0.63
-1.93
-0.39
-1.25
2.29
0.28
-0.26

Section 6

Net Effect
C+L
T-Stat
1.07
6.07
0.93
4.71
1.08
6.22
1.21
7.24
0.89
1.59
0.86
5.50
0.75
2.06
0.85
8.03
1.08
2.16
0.89
4.25
1.01
5.16
2.49
5.00
0.69
2.74
1.03
8.27
0.98
8.03
0.96
3.24
0.82
1.81
0.88
2.97
0.96
3.11
0.93
8.04
0.83
3.85
1.01
7.77
1.04
11.58
1.00
4.25
1.83
0.73
0.98
4.17
1.11
11.93
0.77
2.76
1.07
6.51
0.83
4.89
1.00
2.64
2.48
3.84
0.89
4.72
1.09
5.97
0.77
2.49
2.36
1.55
0.61
0.89
1.75
2.67
1.01
8.64
1.23
2.81
0.67
2.34
0.82
3.28
0.97
2.75
1.09
4.72
0.81
2.57
0.64
3.09
0.86
2.54
0.85
3.70
0.76
11.66
1.10
5.05
1.00
1.57
0.97
4.63
1.26
1.42
0.93
8.81
0.94
4.81
0.84
6.39

r2

514

0.98
0.98
0.98
0.99
0.89
0.98
0.91
0.99
0.96
0.92
0.94
0.93
0.96
0.99
0.99
0.96
0.84
0.95
0.94
0.99
0.97
0.99
0.99
0.95
0.66
0.90
0.99
0.87
0.98
0.99
0.84
0.79
0.95
0.97
0.96
0.91
0.87
0.82
0.99
0.77
0.94
0.95
0.87
0.96
0.88
0.93
0.91
0.94
1.00
0.96
0.87
0.96
0.78
0.99
0.96
0.97

Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page52 of 62
Exhibit 2
Intel
Section 1
Job Title

Years
Total
of Data Emp-Years
11
283
11
142
11
2959
11
880
11
202
11
1662
11
731
11
2205
11
2086
11
1156
11
91
11
1393
11
96
11
281
11
128
11
601
11
303
11
147
11
261
11
282
11
223
11
5107
11
213
11
347
11
135
11
1471
11
2090
11
197
11
35
11
159
11
126
11
223
11
934
11
403
11
1801
11
400
11
390
11
115
11
556
11
120
11
5274
11
1349
11
29
11
83
11
120
11
167
11
379
11
164
11
57
11
2080
11
92
11
225
11
1020
11
209
11
732
11
567

Section 2
Level Correlation
Coeff
T-Stat
0.62
2.37
0.62
2.37
0.62
2.36
0.62
2.36
0.61
2.34
0.61
2.32
0.61
2.29
0.61
2.29
0.61
2.29
0.61
2.29
0.61
2.29
0.60
2.26
0.60
2.26
0.60
2.25
0.60
2.24
0.60
2.23
0.60
2.23
0.59
2.21
0.59
2.20
0.59
2.19
0.59
2.18
0.59
2.18
0.59
2.18
0.58
2.15
0.58
2.15
0.58
2.13
0.58
2.13
0.58
2.13
0.58
2.12
0.57
2.11
0.57
2.10
0.57
2.09
0.57
2.08
0.57
2.07
0.57
2.06
0.57
2.06
0.57
2.06
0.56
2.04
0.56
2.03
0.56
2.03
0.56
2.02
0.56
2.01
0.56
2.01
0.56
2.00
0.54
1.91
0.54
1.91
0.53
1.90
0.53
1.89
0.53
1.89
0.53
1.89
0.53
1.89
0.53
1.86
0.53
1.86
0.52
1.85
0.52
1.82
0.51
1.79

Change Correlation
Coeff
T-Stat
0.94
7.52
0.83
4.28
0.92
6.75
0.93
7.34
0.85
4.49
0.91
6.38
0.94
7.46
0.68
2.62
0.95
8.39
0.71
2.86
0.64
2.33
0.84
4.44
0.84
4.38
0.80
3.74
0.94
7.89
0.91
6.20
0.55
1.87
0.85
4.64
0.68
2.60
0.68
2.59
0.88
5.13
0.95
8.21
0.82
4.07
0.93
6.90
0.76
3.34
0.93
7.06
0.95
9.03
0.91
6.18
0.76
3.32
0.85
4.48
0.69
2.71
0.95
8.28
0.91
6.20
0.87
4.91
0.96
9.45
0.85
4.49
0.88
5.26
0.57
1.97
0.95
8.49
0.62
2.25
0.92
6.52
0.85
4.53
0.59
2.04
0.61
2.18
0.70
2.80
0.47
1.53
0.85
4.56
0.89
5.65
0.23
0.68
0.91
6.07
0.86
4.78
0.19
0.56
0.96
9.33
0.90
5.89
0.88
5.35
0.84
4.34

Section 3
Contemp
0.65
0.72
0.72
0.70
0.77
0.61
0.95
0.68
0.76
0.74
0.90
0.72
0.60
0.73
0.75
0.57
0.48
0.47
0.63
0.54
0.59
0.84
0.45
0.76
0.38
0.65
0.60
0.77
0.76
0.98
1.14
0.68
0.82
0.55
0.70
0.67
0.57
0.29
0.65
0.48
0.60
0.74
0.58
1.56
0.45
0.64
0.43
0.64
0.06
0.62
1.23
2.13
0.69
0.93
0.66
0.55

12 of 22

Regression Coefficients
Lagged
Revenue
0.05
0.30
0.31
0.18
0.20
0.13
0.32
-0.11
0.28
0.22
0.23
0.05
0.31
-0.11
0.79
-0.41
0.23
0.10
0.86
-0.51
1.18
0.26
0.19
0.02
0.15
0.30
0.65
-0.11
0.26
-0.11
0.17
0.08
0.48
0.59
0.12
0.26
0.93
0.49
0.63
-0.41
0.14
0.15
0.24
0.15
0.03
0.45
0.02
0.21
0.13
0.15
0.32
-0.21
0.18
0.03
0.16
0.05
0.57
0.11
0.74
-0.47
1.07
-0.90
0.18
0.13
0.33
-0.01
0.13
0.29
0.22
0.06
0.45
-0.41
0.16
0.17
0.20
0.31
0.18
0.00
0.36
0.00
0.23
-0.29
0.46
-0.15
0.34
0.51
1.26
-1.03
0.23
0.24
1.07
0.19
0.14
0.20
0.30
-0.11
0.28
0.22
0.33
-0.32
-0.01
0.01
5.05
-3.95
0.06
0.14
0.43
-0.28
0.43
-0.28
0.25
0.04

Section 4
SJ Emp
-0.25
-0.06
-0.05
0.18
-0.61
0.04
0.18
0.54
-0.10
0.62
-1.23
0.05
-0.21
-0.15
0.04
0.06
-0.82
-0.16
-1.91
0.42
-0.09
-0.28
-0.36
-0.24
0.03
0.23
-0.01
-0.05
-0.36
0.30
0.54
-0.18
0.06
-0.30
-0.09
0.40
-0.11
-0.21
0.02
-0.07
0.32
-0.10
-0.46
0.95
-0.29
-0.58
-0.18
0.09
0.10
0.36
-0.02
3.09
-0.06
0.07
0.18
-0.15

Contemp
7.48
8.01
8.49
16.35
5.44
6.83
5.47
4.01
11.64
6.12
2.02
2.62
2.16
3.57
6.10
7.66
1.84
5.01
1.52
4.24
2.98
5.52
2.95
3.83
2.29
8.65
8.79
3.57
1.09
4.51
4.38
6.80
6.86
3.25
13.13
5.67
3.80
1.24
6.90
1.78
6.74
4.78
0.98
2.13
1.75
1.25
3.10
4.61
0.35
9.83
2.89
1.46
9.28
5.65
7.75
3.28

Regression T-Stats
Lagged
Revenue
0.42
2.54
2.32
1.48
1.69
1.18
5.74
-1.75
1.53
1.16
1.91
0.38
1.49
-0.46
2.68
-2.34
2.61
1.13
4.08
-4.06
1.38
0.41
0.50
0.06
0.44
0.84
2.18
-0.38
1.57
-0.60
1.70
0.72
1.14
1.74
0.93
2.02
1.85
1.07
3.97
-1.95
0.53
0.52
1.16
0.75
0.14
2.19
0.08
0.78
0.56
0.61
3.35
-1.84
1.97
0.27
0.62
0.15
0.86
0.14
2.97
-1.57
3.53
-2.14
1.40
0.96
2.24
-0.05
0.58
1.23
3.09
0.78
2.89
-2.06
0.78
0.81
0.60
0.89
1.45
0.01
0.90
0.00
1.85
-2.08
2.27
-0.65
0.40
0.67
0.97
-0.99
0.70
0.55
1.71
0.23
0.78
0.93
1.67
-0.52
1.17
0.89
4.08
-3.13
-0.01
0.02
2.76
-2.11
0.59
1.33
2.15
-1.20
3.94
-2.08
1.11
0.17

Section 5
SJ Emp
-1.81
-0.33
-0.35
2.20
-2.85
0.23
0.60
2.66
-0.81
4.03
-2.07
0.13
-0.51
-0.43
0.20
0.46
-2.12
-1.06
-3.78
1.85
-0.31
-1.03
-1.50
-0.66
0.13
1.76
-0.07
-0.13
-0.34
0.79
1.07
-1.01
0.28
-1.05
-0.93
1.68
-0.43
-0.54
0.13
-0.15
2.13
-0.40
-0.59
0.70
-0.58
-0.65
-0.77
0.35
0.36
3.14
-0.03
1.66
-0.47
0.29
1.18
-0.53

Section 6

Net Effect
C+L
T-Stat
0.71
4.13
1.03
5.73
0.92
5.64
1.03
12.77
1.05
3.95
0.85
4.89
1.26
4.15
1.47
3.36
0.99
8.19
1.60
5.14
2.07
1.92
0.90
1.70
0.75
1.50
1.37
3.32
1.01
4.27
0.74
5.09
0.96
1.62
0.59
3.12
1.56
2.22
1.18
4.79
0.72
1.93
1.08
3.87
0.48
1.57
0.79
1.98
0.50
1.49
0.97
6.81
0.79
5.91
0.94
2.36
1.33
1.21
1.72
4.57
2.21
4.76
0.86
4.66
1.15
5.30
0.68
2.07
0.91
9.09
1.11
4.91
0.73
2.48
0.49
1.00
0.84
4.56
0.83
1.46
0.83
4.58
1.20
4.06
0.93
0.76
2.82
1.62
0.68
1.36
1.71
1.82
0.57
2.13
0.94
3.52
0.33
0.94
0.95
7.84
1.22
1.18
7.18
2.51
0.75
5.24
1.36
4.54
1.08
6.67
0.81
2.41

r2

515

0.98
0.99
0.98
0.99
0.94
0.97
0.94
0.81
0.99
0.91
0.87
0.74
0.84
0.84
0.93
0.97
0.90
0.96
0.93
0.89
0.83
0.95
0.92
0.88
0.80
0.96
0.97
0.86
0.72
0.90
0.86
0.97
0.97
0.89
0.99
0.90
0.91
0.64
0.95
0.50
0.93
0.88
0.66
0.49
0.66
0.62
0.86
0.89
0.77
0.97
0.74
0.81
0.98
0.91
0.95
0.81

Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page53 of 62
Exhibit 2
Intel
Section 1
Job Title

Years
Total
of Data Emp-Years
11
147
11
86
11
102
11
4667
11
1283
11
54
11
222
11
43
11
56
11
536
11
7841
11
325
11
249
11
666
11
150
11
106
11
101
11
1976
11
353
11
56
11
137
11
105
11
125
11
117
11
65
11
156
11
35
11
98
11
225
11
171
11
45
11
533
11
243
11
774
11
47
11
199
11
111
11
30
11
31
11
361
11
734
10
901
10
102
10
1266
10
952
10
529
10
186
10
262
10
391
10
1514
10
30
10
794
10
25
10
1764
10
50
10
189

Section 2
Level Correlation
Coeff
T-Stat
0.51
1.78
0.51
1.77
0.50
1.75
0.50
1.75
0.50
1.74
0.50
1.74
0.49
1.67
0.48
1.66
0.47
1.62
0.46
1.56
0.46
1.55
0.46
1.55
0.46
1.54
0.46
1.54
0.46
1.54
0.44
1.49
0.44
1.46
0.44
1.46
0.43
1.43
0.43
1.42
0.43
1.42
0.42
1.38
0.41
1.34
0.41
1.33
0.40
1.32
0.38
1.22
0.35
1.14
0.35
1.12
0.34
1.10
0.34
1.08
0.34
1.08
0.34
1.07
0.33
1.05
0.33
1.04
0.29
0.92
0.27
0.84
0.25
0.76
0.21
0.64
0.17
0.52
0.12
0.38
-0.03
-0.08
0.92
6.51
0.91
6.40
0.90
5.74
0.88
5.29
0.84
4.32
0.84
4.30
0.82
4.10
0.81
3.94
0.79
3.64
0.78
3.53
0.76
3.31
0.75
3.21
0.74
3.12
0.72
2.97
0.71
2.89

Change Correlation
Coeff
T-Stat
0.54
1.81
0.79
3.65
0.81
3.91
0.98
12.47
0.96
9.47
0.57
1.94
0.70
2.76
0.60
2.11
0.76
3.30
0.88
5.16
0.94
7.67
0.68
2.65
0.53
1.79
0.96
9.70
0.91
6.38
0.78
3.50
0.72
2.94
0.83
4.16
0.82
4.00
0.49
1.57
0.87
4.89
0.86
4.75
0.58
2.03
0.58
2.03
-0.02
-0.07
0.74
3.13
0.59
2.08
0.57
1.97
0.71
2.82
0.80
3.76
0.50
1.62
0.41
1.28
0.86
4.84
0.83
4.27
0.73
3.05
0.60
2.10
0.48
1.56
0.09
0.25
0.66
2.46
0.79
3.70
0.47
1.51
0.96
9.16
0.96
8.44
0.83
3.66
0.92
6.33
0.94
7.21
0.98
12.18
0.82
3.73
0.91
5.67
0.97
9.92
0.77
2.94
0.88
4.88
0.69
2.31
0.96
9.71
0.55
1.62
0.39
1.04

Section 3
Contemp
1.24
1.01
0.54
0.61
0.92
0.57
0.62
0.79
0.53
0.70
0.82
0.21
1.23
0.68
0.52
0.66
0.57
0.68
0.71
1.04
0.81
0.84
0.57
0.53
0.48
0.60
0.13
0.63
0.58
0.70
0.09
1.15
0.61
0.45
0.47
0.44
0.31
0.14
0.23
0.59
0.65
1.00
0.74
1.53
1.18
0.69
0.58
0.59
0.77
0.76
0.81
0.54
0.85
0.68
0.85
0.20

13 of 22

Regression Coefficients
Lagged
Revenue
1.41
-0.21
0.67
-0.58
0.33
0.22
0.16
-0.13
0.32
-0.18
-0.03
0.42
0.56
-0.36
1.05
-0.64
0.16
0.41
-0.04
0.16
0.32
-0.37
-0.18
0.74
1.07
-0.31
0.13
-0.01
0.03
0.28
0.53
-0.14
0.04
0.50
0.48
-0.47
0.28
-0.25
1.39
-0.40
0.36
-0.30
0.39
-0.31
0.70
-0.34
-0.23
0.87
1.30
-0.35
0.32
-0.49
-0.31
0.80
0.55
-0.53
-0.08
0.58
0.12
-0.43
-0.43
1.15
1.12
-0.12
0.24
-0.31
0.16
-0.02
-0.13
0.47
0.37
-0.19
0.18
0.21
0.54
-0.12
-0.65
0.88
0.11
-0.24
-0.02
0.22
1.35
0.01
0.98
0.53
0.26
0.50
0.77
-0.03
0.27
0.27
0.14
0.08
0.48
-0.14
0.74
0.20
0.29
0.13
-0.01
0.72
0.32
0.04
0.88
0.44
0.20
0.15
0.33
0.16
0.58
0.07

Section 4
SJ Emp
0.81
0.49
-0.52
0.18
0.20
-0.12
0.29
0.46
-0.70
-0.24
0.32
-0.69
0.93
-0.03
-0.35
-0.07
-0.56
0.38
0.20
-0.48
0.35
0.05
0.12
-1.07
0.08
0.61
-0.34
0.51
-0.82
0.34
-1.06
1.23
0.42
0.16
-0.46
0.36
-0.29
0.12
-0.73
0.14
-0.63
-0.46
-0.89
-0.39
0.15
-0.19
-0.07
0.23
-0.06
-0.09
-0.73
0.00
-0.76
-0.09
-0.42
-0.14

Contemp
1.90
3.20
3.49
23.02
11.04
0.99
2.67
2.16
1.48
3.19
9.49
1.37
1.94
6.56
6.29
2.86
1.39
6.73
2.97
1.87
3.47
6.05
2.36
0.83
1.01
3.02
0.31
1.92
1.30
3.96
0.44
1.70
4.09
3.29
1.38
1.43
1.00
0.33
0.98
3.26
3.20
15.91
3.30
4.28
5.46
6.57
11.57
3.88
5.36
8.76
2.23
3.95
1.86
10.13
1.54
0.57

Regression T-Stats
Lagged
Revenue
1.26
-0.23
1.85
-1.27
1.69
0.97
4.67
-3.16
3.34
-1.57
-0.03
0.60
1.82
-0.99
2.61
-1.17
0.37
0.91
-0.13
0.51
2.99
-2.82
-0.86
3.29
0.98
-0.36
1.02
-0.06
0.24
2.44
2.01
-0.44
0.07
0.93
3.82
-2.95
0.92
-0.68
1.86
-0.52
1.33
-0.87
2.44
-1.50
2.39
-0.99
-0.25
1.07
2.07
-0.47
1.23
-1.54
-0.61
1.51
1.28
-1.03
-0.14
0.92
0.49
-1.54
-1.56
3.87
1.00
-0.13
1.26
-1.28
0.89
-0.08
-0.30
1.06
0.96
-0.38
0.46
0.51
0.99
-0.19
-1.97
2.75
0.46
-0.90
-0.07
0.77
4.71
0.11
2.03
1.81
0.19
0.67
1.56
-0.11
1.38
1.92
1.62
1.10
1.95
-0.45
3.11
1.24
2.15
1.07
-0.01
1.42
1.57
0.20
2.05
0.80
1.90
1.56
0.42
0.28
1.23
0.16

Section 5
SJ Emp
0.75
1.00
-1.88
3.88
1.40
-0.17
0.69
0.66
-1.23
-0.82
2.15
-2.77
0.84
-0.15
-2.80
-0.16
-0.89
2.20
0.53
-0.57
0.85
0.24
0.34
-1.28
0.10
1.64
-0.55
0.93
-1.07
1.13
-3.50
1.01
1.53
0.75
-0.98
0.55
-0.68
0.19
-2.07
0.50
-2.03
-2.98
-2.45
-0.91
0.39
-1.09
-0.83
0.61
-0.25
-0.58
-1.61
0.02
-0.99
-0.78
-0.75
-0.27

Section 6

Net Effect
C+L
T-Stat
2.66
1.76
1.68
2.97
0.87
2.97
0.77
14.83
1.24
8.41
0.54
0.38
1.18
2.61
1.84
2.77
0.70
1.05
0.66
1.60
1.14
7.10
0.04
0.12
2.29
1.50
0.81
4.14
0.55
3.42
1.19
2.82
0.62
0.76
1.16
5.99
0.99
2.16
2.43
2.24
1.18
2.78
1.23
4.84
1.27
2.77
0.30
0.24
1.78
1.85
0.92
2.34
-0.18
-0.23
1.18
1.83
0.50
0.59
0.82
2.35
-0.34
-0.82
2.27
1.42
0.85
2.92
0.60
2.26
0.34
0.53
0.81
1.32
0.49
0.81
0.68
0.80
-0.42
-0.85
0.70
1.96
0.63
1.49
2.35
7.74
1.72
3.81
1.78
1.16
1.95
3.84
0.97
4.10
0.72
6.46
1.07
3.34
1.51
5.96
1.05
6.44
0.80
0.80
0.86
3.10
1.73
2.23
0.88
6.55
1.18
0.95
0.78
1.17

r2

516

0.77
0.78
0.90
0.99
0.98
0.54
0.70
0.79
0.81
0.81
0.96
0.89
0.62
0.94
0.96
0.87
0.76
0.92
0.72
0.67
0.83
0.92
0.77
0.67
0.59
0.73
0.82
0.50
0.67
0.78
0.87
0.66
0.85
0.86
0.69
0.68
0.53
0.43
0.79
0.71
0.84
0.99
0.98
0.96
0.96
0.97
0.98
0.86
0.98
0.98
0.90
0.88
0.93
0.98
0.73
0.77

Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page54 of 62
Exhibit 2
Intel
Section 1
Job Title

Years
Total
of Data Emp-Years
10
149
10
1401
10
81
10
1872
10
53
10
31
10
40
10
951
10
20
10
37
10
113
10
464
10
86
10
29
10
107
10
878
10
42
10
281
10
49
10
340
10
44
10
42
10
157
10
20
10
40
9
72
9
46
9
105
9
18
9
50
9
64
9
172
9
50
9
67
9
17
9
13
9
52
8
283
8
864
8
1526
8
50
8
420
8
288
8
1097
8
92
8
1185
8
119
8
51
8
355
8
52
8
34
8
303
8
258
8
143
8
24
8
612

Section 2
Level Correlation
Coeff
T-Stat
0.69
2.70
0.68
2.61
0.68
2.61
0.63
2.29
0.62
2.26
0.61
2.20
0.60
2.09
0.59
2.06
0.58
2.04
0.58
2.04
0.57
1.98
0.57
1.97
0.55
1.88
0.48
1.55
0.48
1.54
0.47
1.52
0.46
1.45
0.45
1.42
0.37
1.13
0.34
1.02
0.26
0.78
0.26
0.76
0.23
0.68
-0.28
-0.83
-0.34
-1.02
0.84
4.12
0.78
3.34
0.78
3.31
0.77
3.16
0.75
3.01
0.75
2.98
0.72
2.73
0.61
2.03
0.43
1.26
0.36
1.01
0.17
0.46
0.08
0.22
0.99
17.90
0.98
12.28
0.98
11.20
0.97
10.69
0.97
10.36
0.97
9.49
0.96
8.48
0.96
8.30
0.96
8.16
0.95
7.73
0.94
7.02
0.94
6.66
0.93
6.35
0.93
6.18
0.92
5.96
0.92
5.71
0.92
5.70
0.91
5.51
0.91
5.50

Change Correlation
Coeff
T-Stat
0.84
3.75
0.96
9.53
0.75
2.96
0.95
8.08
0.46
1.25
0.94
7.06
0.89
5.10
0.93
6.70
0.56
1.66
0.89
4.84
0.73
2.61
0.82
3.86
0.56
1.64
0.90
5.35
0.78
3.31
0.92
6.26
0.87
4.28
0.66
2.34
0.94
7.27
0.92
6.08
0.91
5.82
0.79
3.13
0.40
1.17
-0.32
-0.88
-0.48
-1.45
0.73
2.59
0.77
2.94
0.79
3.13
0.75
2.57
0.85
3.89
0.92
4.79
0.85
3.92
0.70
2.19
0.21
0.49
0.55
1.31
0.58
1.41
0.60
1.81
0.97
9.74
0.98
9.96
0.96
7.28
0.96
7.81
0.97
8.73
0.94
6.39
0.93
5.58
0.89
4.29
0.87
4.03
0.95
6.85
0.78
2.77
0.83
3.30
0.93
4.25
0.79
2.87
0.93
5.53
0.90
4.56
0.92
5.17
0.96
7.81
0.81
3.09

Section 3
Contemp
0.24
0.72
1.20
0.69
0.68
1.28
1.03
0.62
0.30
1.29
0.21
0.84
1.30
0.63
0.67
0.96
0.72
0.30
0.64
0.52
1.04
3.52
0.28
0.07
-0.16
2.09
1.06
1.15
0.57
0.77
3.72
0.82
0.92
0.05
5.91
0.10
1.09
0.86
0.75
0.74
0.91
0.74
0.61
0.33
0.96
0.83
2.48
1.06
0.43
0.95
1.11
0.90
0.79
1.24
1.50
0.44

14 of 22

Regression Coefficients
Lagged
Revenue
1.11
0.15
0.27
0.06
1.12
-0.39
0.29
-0.05
0.75
0.23
-0.42
0.82
0.47
0.29
0.30
-0.24
-0.27
0.47
0.23
0.09
0.27
0.20
0.93
0.34
2.76
0.18
0.27
0.06
0.81
0.22
0.40
-0.12
0.53
0.35
0.20
0.23
-0.15
0.13
0.16
0.11
-0.03
0.32
1.68
-0.54
0.30
0.16
0.37
0.13
0.33
-0.16
0.76
0.09
0.67
0.54
0.86
0.01
0.15
0.76
0.92
0.37
0.33
-1.05
0.28
0.19
0.94
-0.21
-0.30
0.88
3.81
-2.42
-0.15
0.52
0.34
0.38
-0.01
0.14
0.36
0.18
-0.02
0.19
0.17
-0.09
0.26
0.09
-0.04
0.04
0.09
0.08
0.07
0.18
1.18
0.23
0.75
-0.22
-0.02
0.37
0.46
0.05
1.33
-0.16
1.33
0.17
0.61
0.24
0.15
0.00
0.94
0.02
-0.86
1.10
-0.08
0.40

Section 4
SJ Emp
-0.83
-0.09
0.27
0.06
-0.32
-1.13
-0.81
0.25
-0.38
0.05
0.09
-0.18
-0.29
-0.22
-0.33
0.15
-0.76
-0.09
-0.28
-0.21
-0.06
1.64
-0.07
-1.18
-1.00
-1.59
-0.76
0.49
-0.64
-1.82
1.80
-0.33
0.16
-0.96
0.48
-0.29
-0.65
-0.01
-0.24
-0.29
-0.12
-0.37
-0.20
-0.19
0.08
-0.63
-0.28
-1.71
-0.18
-0.76
-0.44
-0.11
-0.13
0.19
-1.27
-0.43

Contemp
0.32
9.38
2.19
8.10
5.31
5.65
2.39
10.29
1.05
2.39
0.34
1.89
2.28
4.22
3.00
4.86
0.50
1.79
5.60
6.64
3.33
6.75
0.52
0.16
-0.30
1.57
1.37
16.00
0.99
0.50
1.60
1.36
3.01
0.13
2.49
0.10
3.50
6.72
12.01
4.74
4.85
14.77
3.39
6.90
2.47
6.14
10.75
1.74
6.58
5.31
2.37
2.48
3.82
6.40
2.85

Section 5

Regression T-Stats
Lagged
Revenue
2.13
0.30
2.52
0.50
1.58
-0.57
2.53
-0.42
4.85
1.71
-1.31
2.71
0.97
0.62
3.72
-2.57
-0.68
1.35
0.41
0.19
0.52
0.37
1.44
0.72
1.89
0.22
1.40
0.28
3.39
0.89
1.53
-0.43
0.79
0.45
0.88
0.85
-0.83
0.83
1.52
0.96
-0.08
0.84
2.12
-0.79
0.43
0.22
0.68
0.21
0.52
-0.25
0.30
0.04
0.24
0.30
9.29
0.16
0.19
1.43
0.82
0.35
0.23
-0.69
0.33
0.19
1.38
-0.49
-0.54
1.61
2.36
-2.09
-0.12
0.49
1.05
1.09
-0.02
1.05
1.90
2.63
-0.04
1.16
0.29
-0.41
1.66
1.63
-0.12
0.20
1.22
1.57
0.07
0.43
1.86
1.17
1.97
-0.77
-0.02
0.46
3.98
0.68
2.15
0.56
0.24
1.16
-2.06
-0.31

0.87
0.68
0.01
0.06
3.94
2.41

SJ Emp
-1.34
-0.62
0.35
0.42
-1.26
-3.26
-1.30
2.31
-0.78
0.08
0.15
-0.27
-0.34
-0.76
-0.77
0.32
-1.06
-0.28
-1.38
-1.61
-0.10
1.94
-0.09
-1.75
-1.38
-0.56
-0.43
3.20
-0.64
-0.91
0.79
-0.26
0.26
-1.59
0.41
-0.29
-0.99
-0.05
-1.88
-0.93
-0.31
-3.65
-0.59
-2.02
0.10
-2.32
-0.58
-1.30
-1.37
-1.46
-0.16
-0.20
0.30
-4.57
-1.42

Section 6

Net Effect
C+L
T-Stat
1.35
1.70
0.99
6.88
2.31
2.29
0.98
6.08
1.42
5.73
0.86
2.03
1.50
2.17
0.92
7.78
0.03
0.04
1.51
2.05
0.48
0.52
1.77
2.36
4.05
2.12
0.90
3.16
1.48
4.16
1.37
3.79
1.24
0.73
0.50
1.48
0.49
2.03
0.68
4.43
1.01
1.83
5.21
4.68
0.58
0.54
0.44
0.52
0.17
0.16
2.86
0.82
1.73
0.56
2.02
14.45
0.72
0.80
1.69
0.90
4.05
1.75
1.10
0.91
1.86
2.00
-0.26
-0.31
9.72
3.51
-0.05
-0.02
1.43
2.58
0.85
1.38
1.12
5.69
0.72
1.51
1.08
1.69
1.00
6.01
0.56
1.27
0.42
4.06
1.04
0.95
2.01
3.07
3.23
6.38
1.04
0.65
0.89
5.85
2.27
2.44
3.08
1.52
1.58
0.94
1.20
2.18
2.46
0.64
1.47
0.36
1.01

r2

517

0.92
0.98
0.76
0.97
0.97
0.98
0.90
0.97
0.87
0.90
0.81
0.95
0.73
0.90
0.98
0.93
0.95
0.78
0.93
0.96
0.91
0.97
0.43
0.68
0.68
0.81
0.81
0.99
0.89
0.87
0.92
0.75
0.97
0.71
0.96
0.79
0.95
0.97
0.99
0.95
0.94
1.00
0.91
0.98
0.83
0.98
0.99
0.87
0.97
1.00
0.97
0.93
0.82
0.93
0.99
0.93

Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page55 of 62
Exhibit 2
Intel
Section 1
Job Title

Years
of Data
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8
8

Total
Emp-Years
359
152
98
374
689
203
291
65
318
24
217
201
214
304
266
116
180
1077
155
57
48
64
246
157
33
41
87
62
72
69
10
460
29
53
102
33
324
14
132
34
79
730
1281
355
206
4110
644
108
64
23
82
412
434
97
41
151

Section 2
Level Correlation
Coeff
T-Stat
0.91
5.42
0.91
5.32
0.90
5.00
0.90
4.94
0.90
4.92
0.88
4.53
0.87
4.41
0.86
4.07
0.84
3.77
0.83
3.68
0.82
3.50
0.82
3.49
0.81
3.36
0.81
3.36
0.80
3.32
0.80
3.30
0.78
3.03
0.77
2.97
0.77
2.92
0.76
2.91
0.76
2.90
0.76
2.90
0.76
2.87
0.75
2.81
0.75
2.81
0.75
2.81
0.75
2.79
0.75
2.77
0.75
2.75
0.72
2.56
0.72
2.51
0.71
2.50
0.71
2.44
0.70
2.38
0.69
2.34
0.69
2.32
0.67
2.23
0.67
2.20
0.65
2.11
0.65
2.10
0.65
2.08
0.56
1.65
0.55
1.60
0.52
1.51
0.48
1.33
0.47
1.30
0.46
1.26
0.45
1.24
0.45
1.24
0.44
1.19
0.43
1.18
0.39
1.04
0.37
0.98
0.26
0.65
0.19
0.48
0.10
0.24

Change Correlation
Coeff
T-Stat
0.84
3.53
0.67
2.01
0.94
6.09
0.70
2.19
0.94
6.39
0.95
6.80
0.94
6.05
0.65
1.90
0.91
4.83
0.74
2.49
0.96
7.70
0.84
3.43
0.94
6.24
0.52
1.37
0.91
4.94
0.91
4.95
0.88
4.13
0.92
5.43
0.95
6.98
0.54
1.45
0.40
0.99
0.56
1.52
0.93
5.66
0.88
4.13
0.83
3.26
0.39
0.95
0.11
0.24
0.94
6.08
0.37
0.89
0.20
0.46
0.15
0.34
0.91
5.04
0.29
0.67
0.41
1.00
0.66
1.76
0.74
2.47
0.58
1.60
0.55
1.48
0.94
5.98
0.52
1.38
0.85
3.63
0.64
1.86
0.61
1.71
0.79
2.88
0.76
2.59
0.91
4.91
0.88
4.20
-0.42
-1.03
0.74
2.44
0.47
1.18
0.31
0.72
-0.03
-0.07
0.91
5.06
0.13
0.30
0.43
1.06
-0.46
-1.15

Section 3
Contemp
0.59
0.43
1.44
0.58
0.87
2.06
0.64
1.50
0.65
0.68
0.63
0.54
0.62
0.23
0.48
0.62
0.40
0.57
0.93
1.12
0.70
0.81
0.99
0.60
2.33
0.84
0.77
0.71
0.42
0.04
0.79
0.53
0.18
0.47
1.06
1.60
0.29
1.25
0.89
0.59
0.62
0.68
0.53
0.72
0.64
1.00
0.56
0.73
0.77
0.54
0.42
0.18
0.62
0.31
1.06
-0.41

15 of 22

Regression Coefficients
Lagged
Revenue
-0.10
0.50
0.75
0.12
0.21
0.34
0.04
0.53
1.50
0.11
0.25
0.42
0.46
0.13
0.76
-1.51
0.35
0.12
2.29
-0.04
0.17
-0.21
0.30
-0.04
0.24
-0.01
-0.07
0.37
-0.43
0.41
0.34
0.34
0.16
0.13
0.26
0.09
0.43
0.15
1.05
-0.14
0.73
0.12
1.22
-0.14
-0.13
-0.37
0.45
0.59
0.41
-1.63
0.76
0.40
1.02
0.04
0.47
0.37
0.15
0.43
0.06
0.24
1.77
-0.84
0.31
0.03
0.87
0.37
0.78
0.27
2.22
-0.21
0.84
-1.27
0.18
0.23
0.61
0.13
0.41
-0.13
0.38
0.09
-0.05
0.59
0.64
-0.30
0.64
-0.17
0.44
-0.25
0.48
-0.37
0.51
-0.33
0.31
-0.10
0.61
0.36
0.88
-0.32
0.53
0.02
0.30
0.30
0.64
-0.14
0.30
-0.01
0.33
0.16
-0.70
1.54
-0.50
0.48

Section 4
SJ Emp
-0.47
-0.29
-0.88
-0.61
-0.83
-0.73
-0.17
1.81
-0.06
-3.04
0.27
0.29
-0.06
-0.43
-0.06
-0.76
0.04
-0.20
0.20
1.02
0.95
0.05
0.25
-0.51
0.25
0.84
0.44
-0.27
-0.35
-0.32
0.75
-0.20
-1.00
0.65
-0.04
1.94
0.05
1.89
-0.37
0.89
-1.07
0.87
0.62
0.06
0.49
0.45
0.24
0.72
0.58
0.79
0.17
0.58
-0.13
0.99
-0.95
-0.43

Contemp
4.46
3.08
2.61
1.66
1.67
43.99
7.62
3.06
4.53
1.06
32.69
3.36
5.00
0.84
4.05
6.72
2.75
5.81
9.92
2.78
4.75
1.51
6.76
1.01
2.80
2.52
1.60
85.90
0.63
0.34
0.58
8.28
0.59
0.89
3.56
8.75
2.30
6.47
5.32
10.55
1.95
5.55
3.75
1.72
3.56
5.46
6.06
0.39
2.46
1.33
0.65
1.06
4.92
2.27
0.70
-2.83

Regression T-Stats
Lagged
Revenue
-0.38
3.44
3.03
0.66
0.25
0.71
0.04
1.49
1.34
0.30
2.43
7.04
3.81
1.42
1.28
-1.46
1.09
0.46
2.31
-0.04
6.94
-8.81
1.40
-0.22
1.47
-0.07
-0.18
1.44
-1.36
2.10
2.40
3.96
0.51
0.48
2.02
0.83
4.50
1.94
1.86
-0.43
3.51
0.65
1.36
-0.12
-0.56
-2.17
0.65
1.45
0.74
-2.32
1.52
1.13
1.67
0.10
58.69
59.28
0.13
0.81
0.35
1.65
1.22
-0.48
3.96
0.37
1.92
1.14
1.19
0.45
2.14
-0.18
5.92
-5.09
1.15
1.57
2.56
0.58
2.31
-0.80
5.92
1.33
-0.11
1.98
5.21
-1.91
4.51
-0.97
1.02
-0.51
2.52
-1.65
3.02
-1.71
3.00
-0.96
0.34
0.25
3.63
-0.96
1.22
0.03
0.36
0.44
3.52
-0.61
2.26
-0.08
2.30
0.93
-0.30
0.82
-3.01
3.66

Section 5
SJ Emp
-1.76
-1.03
-0.98
-1.07
-1.87
-9.31
-1.07
3.42
-0.15
-1.88
6.75
0.89
-0.25
-0.91
-0.27
-4.87
0.12
-1.08
1.44
1.65
3.27
0.04
0.84
-0.67
0.76
1.30
0.68
-22.97
-0.32
-1.25
0.26
-1.66
-1.66
0.62
-0.03
5.55
0.20
4.51
-1.43
7.48
-1.94
3.72
2.35
0.08
1.38
1.44
1.35
0.27
1.22
0.97
0.13
1.70
-0.59
3.30
-0.31
-1.77

Section 6

Net Effect
C+L
T-Stat
0.49
1.50
1.18
3.69
1.65
2.00
0.62
0.51
2.37
3.38
2.32
23.84
1.10
7.90
2.26
5.65
1.00
2.51
2.97
2.25
0.80
22.98
0.84
2.75
0.86
3.82
0.16
0.25
0.05
0.12
0.95
6.30
0.56
1.37
0.83
4.79
1.36
12.17
2.17
2.40
1.44
4.66
2.02
1.58
0.86
3.16
1.06
1.60
2.74
6.78
1.60
2.23
1.79
1.75
1.17
129.23
0.57
0.33
0.10
0.41
2.56
1.06
0.84
7.81
1.05
1.65
1.25
1.31
3.28
2.68
2.44
10.41
0.47
2.02
1.86
5.42
1.30
5.86
0.96
10.05
0.57
1.11
1.32
6.73
1.17
5.18
1.16
1.83
1.13
3.80
1.52
5.74
0.87
5.57
1.34
0.39
1.65
3.75
1.07
1.56
0.72
0.57
0.82
2.81
0.91
4.64
0.65
2.74
0.36
0.11
-0.91
-3.25

r2

518

0.97
0.92
0.94
0.92
0.99
1.00
0.99
0.95
0.98
0.94
1.00
0.88
0.96
0.72
0.98
0.99
0.94
0.98
1.00
0.80
0.95
0.70
0.97
0.94
0.98
0.90
0.62
1.00
0.67
0.76
0.64
0.99
0.93
0.74
0.95
0.99
0.90
0.98
0.98
0.99
0.95
0.97
0.96
0.76
0.90
0.97
0.97
0.74
0.95
0.75
0.47
0.91
0.97
0.97
0.76
0.90

Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page56 of 62
Exhibit 2
Intel
Section 1
Job Title

Years
of Data
8
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7

Total
Emp-Years
17
104
163
283
245
236
18
43
26
116
38
118
331
23
47
58
389
114
78
11
10
154
38
57
14
93
12
61
40
70
81
45
35
8
90
82
31
569
15
17
39
83
123
32
351
10
47
252
162
59
196
38
17
15
100
34

Section 2
Level Correlation
Coeff
T-Stat
0.09
0.23
0.99
14.44
0.99
13.23
0.98
10.30
0.97
9.67
0.97
8.77
0.96
8.21
0.95
7.10
0.95
6.90
0.95
6.82
0.95
6.61
0.94
6.35
0.94
6.31
0.94
6.28
0.94
6.16
0.94
6.02
0.93
5.80
0.92
5.11
0.91
4.78
0.91
4.77
0.90
4.64
0.90
4.59
0.89
4.28
0.88
4.22
0.88
4.19
0.88
4.10
0.87
3.95
0.86
3.80
0.86
3.79
0.86
3.74
0.86
3.72
0.86
3.70
0.85
3.68
0.85
3.62
0.85
3.55
0.84
3.43
0.84
3.42
0.83
3.32
0.82
3.24
0.82
3.23
0.82
3.22
0.80
3.02
0.80
2.98
0.78
2.78
0.77
2.72
0.76
2.61
0.73
2.42
0.73
2.41
0.73
2.40
0.73
2.38
0.71
2.27
0.71
2.27
0.71
2.22
0.67
2.03
0.61
1.73
0.61
1.73

Change Correlation
Coeff
T-Stat
0.04
0.10
0.82
2.85
0.85
3.20
0.90
4.19
0.79
2.57
0.68
1.87
0.38
0.82
0.23
0.47
0.26
0.53
0.67
1.83
0.71
2.03
0.25
0.52
0.74
2.23
0.30
0.64
-0.04
-0.08
0.84
3.08
0.58
1.41
0.86
3.44
0.84
3.06
0.56
1.36
-0.21
-0.43
0.89
3.86
0.91
4.34
-0.01
-0.03
0.79
2.58
0.51
1.17
-0.28
-0.59
0.51
1.18
0.46
1.03
0.39
0.84
0.78
2.53
0.69
1.91
0.64
1.66
0.43
0.95
0.67
1.79
0.15
0.31
0.72
2.06
0.32
0.67
0.74
2.23
-0.32
-0.69
0.14
0.27
0.86
3.43
0.53
1.26
0.28
0.58
0.64
1.69
0.96
6.79
0.35
0.75
0.47
1.06
0.50
1.15
0.53
1.26
0.48
1.09
0.31
0.65
0.37
0.81
0.22
0.40
-0.14
-0.27
-0.05
-0.09

Section 3
Contemp
-0.56
1.14
0.57
0.89
1.32
1.14
-0.14
0.31
-0.70
0.38
0.38
0.97
0.48
1.69
0.69
0.65
0.81
0.98
0.64
0.52
-0.52
0.70
2.43
0.30
1.41
0.39
1.73
-2.12
0.91
-0.20
1.55
1.92
-0.36
-3.96
1.34
2.16
1.23
0.93
2.26
0.87
-5.32
2.81
0.33
1.45
-0.31
1.00
2.28
-0.88
0.33
-0.14
1.52
-13.06
0.54
-0.74
-0.53
2.16

16 of 22

Regression Coefficients
Lagged
Revenue
-0.38
1.10
1.18
-0.09
0.15
0.26
0.35
0.06
0.61
-0.15
0.88
-0.17
0.87
-0.01
0.93
0.23
0.15
0.73
0.04
0.24
0.23
0.56
1.19
0.03
1.24
0.22
1.01
-0.35
0.12
-0.28
0.16
0.42
0.37
-0.06
1.26
-0.50
0.46
0.57
0.56
0.59
0.03
0.29
-0.35
0.38
1.12
-0.12
1.33
0.01
1.63
-0.08
0.53
0.14
1.98
0.00
-1.62
1.89
0.00
-0.55
-0.03
0.30
-1.09
1.49
1.03
-0.04
-0.35
0.80
-4.09
3.34
0.61
-0.07
1.13
-0.81
1.76
-0.59
0.64
-0.26
1.27
-0.47
2.52
-0.26
-2.53
3.26
0.85
-0.20
0.33
0.45
2.36
-0.44
-0.68
1.13
1.04
0.13
1.32
-0.60
-0.61
0.51
0.19
0.32
-0.74
1.35
0.71
-0.41
-9.42
3.60
0.91
0.53
-0.05
2.31
-0.77
2.84
1.40
-1.80

Section 4
SJ Emp
-1.61
-0.01
-0.17
-0.14
0.49
0.10
-0.31
-0.25
-1.01
-0.10
-0.87
-0.07
0.07
1.06
1.02
-0.70
0.32
0.28
-0.63
-0.99
0.55
-0.27
0.31
0.44
0.17
-0.10
0.02
-2.71
0.22
-1.19
-0.68
0.46
-1.47
-7.26
0.26
1.24
0.20
0.11
0.09
1.72
-4.08
0.69
-0.39
-0.57
-1.28
0.47
0.97
-1.11
-0.52
-0.76
0.47
-2.98
0.09
-3.50
-3.35
0.84

Contemp
-0.55
1.48
170.84
2.34
3.19
17.95
-0.12
0.21
-0.49
2.45
0.16
3.96
0.32
8.89
4.52
0.37
1.48
9.71
3.30
0.18
-0.13
0.72
1.55
0.14
3.38
0.19
155.52
-2.11
0.56
-0.15
2.23
1.64
-0.46
-2.93
6.07
2.08
0.98
1.39
0.83
0.39
-1.61
2.06
0.17
0.39
-0.19
1.14
7.20
-1.10
0.31
-0.11
0.89
-0.77
0.82
-0.91
3.65

Section 5

Regression T-Stats
Lagged
Revenue
-0.23
0.59
1.03
-0.25
47.89
194.68
1.14
0.36
2.10
-0.84
15.99
-6.89
1.14
-0.02
0.95
0.33
0.12
1.14
0.44
4.00
0.16
0.55
6.27
0.33
0.76
0.30
8.16
-3.65
0.77
-3.15
0.12
0.54
1.15
-0.25
4.95
-2.37
1.03
1.65
0.33
0.46
0.02
0.15
-0.53
0.94
1.02
-0.19
0.80
0.01
1.26
-0.13
0.43
0.15
275.61
-0.38
-1.70
3.49
0.00
-0.99
-0.03
0.65
-2.74
5.13
1.63
-0.07
-0.60
2.23
-3.93
4.56
4.89
-0.77
1.99
-1.91
0.50
-0.27
1.68
-0.95
0.48
-0.55
1.54
-0.33
-1.16
1.98
1.02
-0.32
0.30
0.53
0.82
-0.23
-0.62
1.51
1.18
0.27
8.06
-4.27
-1.37
1.79
0.32
0.72
-0.86
2.25
0.77
-0.57
-0.79
0.82
1.05
0.72
-0.63
4.04

1.41
-7.06

SJ Emp
-0.80
-0.01
-80.66
-0.51
1.67
2.33
-0.36
-0.22
-1.09
-1.02
-0.48
-0.46
0.05
7.14
7.38
-0.54
0.87
1.04
-1.35
-0.38
0.17
-0.44
0.28
0.23
0.20
-0.07
3.81
-4.25
0.23
-1.40
-1.23
0.53
-2.45
-5.07
1.70
1.82
0.13
0.23
0.07
0.81
-1.77
0.68
-0.27
-0.22
-1.12
0.52
4.22
-2.35
-0.67
-0.88
0.38
-0.84
0.05
-1.40
1.98

Section 6

Net Effect
C+L
T-Stat
-0.94
-0.37
2.32
1.59
0.71
117.74
1.24
1.91
1.94
2.94
2.02
18.15
0.73
0.49
1.24
0.59
-0.55
-0.21
0.42
1.74
0.61
0.19
2.16
5.16
1.72
0.69
2.70
9.52
0.81
3.08
0.81
0.32
1.19
1.41
2.24
7.23
1.10
1.96
1.09
0.28
-0.48
-0.09
0.34
0.22
3.56
1.80
1.63
0.45
3.04
1.94
0.91
0.31
3.72
205.65
-3.75
-1.93
0.91
0.33
-0.23
-0.11
0.46
0.53
2.95
1.79
-0.71
-0.54
-8.05
-3.88
1.94
5.87
3.29
2.12
2.99
0.65
1.57
1.55
3.53
0.67
3.38
0.89
-7.85
-1.51
3.67
1.84
0.66
0.23
3.81
0.58
-0.99
-0.39
2.04
2.97
3.60
7.82
-1.48
-1.22
0.53
0.33
-0.88
-0.44
2.23
0.88
-22.47
-0.78
1.45
1.22
-1.29
3.56

r2

-0.77
3.92

519

0.70
0.85
1.00
0.97
0.95
1.00
0.87
0.60
0.84
0.99
0.77
0.99
0.87
0.99
0.99
0.84
0.83
0.99
0.98
0.74
0.38
0.92
0.95
0.68
0.96
0.54
1.00
0.99
0.75
0.92
1.00
0.93
0.97
0.98
0.99
0.83
0.75
0.89
0.78
0.95
0.91
0.94
0.78
0.96
0.93
0.97
0.99
0.90
0.89
0.97
0.57
0.48
0.87
0.90
0.99

Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page57 of 62
Exhibit 2
Intel
Section 1
Job Title

Years
of Data
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6

Total
Emp-Years
12
16
224
27
52
31
878
88
9
14
15
68
34
11
12
47
24
14
187
10
15
17
201
98
8
222
8
28
72
17
25
131
12
18
402
41
77
12
36
8
93
23
31
53
485
12
44
7
21
15
6
8
22
14
20
18

Section 2
Level Correlation
Coeff
T-Stat
0.60
1.69
0.60
1.67
0.59
1.64
0.59
1.62
0.58
1.59
0.54
1.45
0.50
1.31
0.49
1.27
0.49
1.26
0.42
1.04
0.39
0.95
0.38
0.91
0.36
0.85
0.34
0.81
0.31
0.74
0.24
0.55
0.12
0.26
0.08
0.17
-0.08
-0.17
-0.18
-0.42
-0.22
-0.50
-0.43
-1.07
0.97
7.68
0.96
7.13
0.96
6.83
0.95
5.98
0.95
5.93
0.93
5.17
0.92
4.79
0.92
4.72
0.91
4.36
0.91
4.26
0.90
4.06
0.90
4.03
0.89
3.99
0.89
3.96
0.89
3.95
0.88
3.76
0.88
3.74
0.87
3.57
0.87
3.55
0.87
3.50
0.85
3.28
0.84
3.09
0.84
3.07
0.84
3.06
0.83
3.00
0.83
2.96
0.82
2.89
0.82
2.89
0.78
2.52
0.78
2.48
0.77
2.45
0.75
2.25
0.75
2.24
0.73
2.16

Change Correlation
Coeff
T-Stat
0.69
1.90
0.68
1.85
0.33
0.70
-0.59
-1.47
-0.79
-2.62
0.67
1.83
0.59
1.48
-0.79
-2.57
0.61
1.34
0.60
1.48
0.62
1.59
-0.51
-1.17
-0.62
-1.57
-0.14
-0.27
0.60
1.29
0.29
0.61
0.09
0.17
0.24
0.50
0.37
0.78
0.29
0.62
0.53
1.26
0.48
1.10
0.90
3.51
0.97
6.67
0.92
4.03
0.92
4.09
0.72
1.48
0.09
0.15
0.48
0.95
0.83
2.13
0.24
0.35
0.91
3.08
0.78
1.78
0.86
2.35
0.79
2.26
0.90
2.05
0.77
2.12
0.76
1.68
-0.03
-0.05
0.13
0.22
0.56
1.16
0.91
3.87
0.68
1.61
-0.14
-0.25
0.76
2.02
0.62
1.37
0.56
1.17
0.68
1.62
0.38
0.59
0.70
1.39
0.68
1.32
0.97
5.92
0.61
1.34
0.43
0.84
1.00
19.25
-0.06
-0.10

Section 3
Contemp
1.46
0.81
1.58
-2.44
-0.26
2.56
1.85
-0.24
-2.99
5.60
7.30
-4.24
-0.33
3.17
-8.69
2.29
4.06
0.71
-0.10
15.96
1.02
5.55

17 of 22

Regression Coefficients
Lagged
Revenue
4.18
-1.01
0.54
0.75
0.63
-0.86
0.08
0.44
0.23
-0.06
0.74
0.13
0.75
-0.70
0.32
-0.37
-4.04
3.39
3.82
-2.25
2.86
-2.56
-1.64
1.33
0.65
-0.02
2.67
-1.80
-11.14
12.08
1.15
-0.73
2.08
-1.49
-0.45
0.92
-0.08
0.12
30.79
-17.07
-0.23
0.62
2.37
-2.37

Section 4
SJ Emp
-6.31
0.35
0.91
-1.28
-0.07
0.92
0.51
0.19
-3.51
1.36
3.35
-1.91
0.24
1.00
-6.51
0.52
2.58
0.81
-0.82
35.69
-0.63
1.63

Contemp
1.14
0.11
1.44
-0.37
-0.49
0.54
46.85
-2.49

Section 5

Regression T-Stats
Lagged
Revenue
1.33
-0.55
0.15
0.24
1.03
-2.22
0.02
0.24
0.88
-0.33
0.30
0.06
35.03
-45.73
6.95
-11.05

SJ Emp
-2.46
0.07
1.42
-0.25
-0.20
0.26
19.62
3.14

Section 6

Net Effect
C+L
T-Stat
5.64
1.53
1.35
0.14
2.21
1.32
-2.36
-0.24
-0.03
-0.04
3.30
0.50
2.60
43.87
0.08
0.54

r2
0.99
0.82
0.87
0.75
0.92
0.76
1.00
1.00

2.90
5.09
-0.76
-0.27
0.34

2.25
4.58
-0.62
1.18
0.63

-2.54
-3.84
0.88
-0.05
-0.44

0.88
3.05
-0.79
0.27
0.15

9.42
10.16
-5.88
0.32
5.84

3.07
5.44
-0.72
0.19
0.45

0.96
0.97
0.64
0.93
0.55

0.66
18.07
0.43
-0.08
5.13
0.20
3.35

0.61
20.25
-0.54
-0.12
4.95
-0.09
2.98

-0.66
-14.21
1.27
0.24
-4.84
0.27
-3.45

0.29
15.65
0.70
-0.97
5.17
-0.16
1.37

3.44
6.14
0.27
-0.18
46.74
0.79
7.92

0.65
19.43
0.11
-0.10
5.01
0.10
3.33

0.46
1.00
0.95
0.77
0.98
0.56
0.96

520

Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page58 of 62
Exhibit 2
Intel
Section 1
Job Title

Years
of Data
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6

Total
Emp-Years
149
22
10
8
14
10
34
15
9
31
12
8
13
10
40
24
11
10
170

Section 2
Level Correlation
Coeff
T-Stat
0.71
2.03
0.68
1.86
0.61
1.56
0.55
1.32
0.52
1.20
0.51
1.19
0.51
1.18
0.49
1.14
0.42
0.93
0.41
0.90
0.27
0.55
0.24
0.49
0.23
0.47
0.21
0.42
0.18
0.37
0.09
0.18
-0.02
-0.04
-0.41
-0.90
-0.74
-2.21

Change Correlation
Coeff
T-Stat
0.98
7.11
0.36
0.66
0.98
8.07
-0.12
-0.18
0.93
2.58
-0.65
-1.47
-0.76
-1.67
0.50
0.99
0.35
0.52
0.16
0.16
-0.80
-2.34
-0.33
-0.61
0.89
2.81
0.67
1.28
0.60
1.29
0.42
0.65
0.58
1.23
-0.20
-0.20
0.06
0.10

Section 3
Contemp

18 of 22

Section 4

Section 5

Section 6

Regression Coefficients
Lagged
Revenue

Regression T-Stats
Lagged
Revenue

Net Effect
C+L
T-Stat

r2

SJ Emp

Contemp

SJ Emp

521

Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page59 of 62
Exhibit 2
Intuit
Section 1
Job Title

Years
of Data
11
11
11
11
11
10
10
10
10
9
9
9
9
9
9
9
8
8
8
8
8
8
8
7
7
7
7
7
7
7
7
7
7
7
7
7
7
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6

Total
Emp-Years
2981
597
293
150
140
170
1571
69
194
57
1073
94
81
758
46
486
113
24
29
114
22
177
206
48
22
7
43
354
58
110
143
26
136
16
378
25
15
16
180
17
120
26
14
145
90
377
167
268
203
31
10
53
118
146
39

Section 2
Level Correlation
Coeff
T-Stat
0.60
2.26
0.59
2.18
0.54
1.91
0.40
1.29
0.26
0.81
0.78
3.55
0.55
1.85
0.49
1.60
0.40
1.25
0.67
2.39
0.64
2.22
0.59
1.94
0.54
1.70
0.53
1.67
0.17
0.46
-0.01
-0.02
0.80
3.25
0.68
2.25
0.61
1.87
0.46
1.25
0.33
0.87
0.33
0.85
-0.63
-2.00
0.82
3.26
0.74
2.48
0.72
2.33
0.70
2.17
0.65
1.93
0.62
1.75
0.31
0.72
0.21
0.48
0.04
0.10
-0.10
-0.23
-0.33
-0.78
-0.55
-1.49
-0.73
-2.36
-0.83
-3.37
0.95
6.25
0.93
5.09
0.93
4.88
0.92
4.71
0.90
4.15
0.89
3.88
0.86
3.33
0.84
3.14
0.84
3.05
0.84
3.04
0.83
3.02
0.81
2.81
0.81
2.77
0.80
2.65
0.78
2.46
0.75
2.28
0.75
2.27
0.74
2.22

Change Correlation
Coeff
T-Stat
0.97
12.05
0.95
8.57
0.97
11.05
0.76
3.31
-0.05
-0.13
0.98
10.93
0.79
3.16
-0.30
-0.78
0.76
2.86
0.08
0.21
0.69
2.34
0.57
1.56
0.77
2.94
0.68
2.05
0.74
2.70
0.46
1.28
0.91
4.90
0.72
2.32
0.76
2.62
0.81
3.08
-0.04
-0.10
0.94
5.94
0.13
0.30
0.65
1.73
0.87
3.60
0.86
3.41
0.54
1.28
0.79
2.61
0.71
2.01
-0.45
-1.01
0.90
4.19
-0.21
-0.43
-0.09
-0.18
0.12
0.25
0.73
2.11
0.14
0.28
0.60
1.52
0.98
8.84
0.93
4.44
0.98
8.53
0.71
1.74
0.92
4.10
0.96
6.19
0.62
1.36
0.57
1.20
0.92
4.14
0.96
5.81
0.98
9.39
0.42
0.81
0.91
3.70
0.33
0.61
0.83
2.55
0.85
2.83
0.88
3.28
0.93
4.32

Section 3
Contemp
1.50
1.13
1.50
2.01
0.69
1.08
1.34
-0.19
1.39
0.62
1.15
1.10
1.63
0.34
2.01
1.34
0.44
1.52
2.07
1.40
0.37
2.15
1.48
2.10
2.05
3.15
0.89
1.31
0.76
-0.86
1.05
1.11
1.45
-0.39
1.15
-0.19
0.27

Regression Coefficients
Lagged
Revenue
1.01
-0.26
1.33
-0.48
1.17
-0.49
1.70
-0.80
1.28
-0.43
-0.18
0.15
1.01
-0.36
0.68
-0.18
1.36
-0.33
0.82
-0.05
0.25
0.30
0.36
0.01
1.09
-0.15
-0.90
0.56
0.71
-0.11
1.60
-0.55
0.22
1.21
2.13
-0.81
2.81
-1.72
1.62
-1.07
0.68
0.51
2.42
-2.11
5.60
-4.14
0.32
-0.98
1.38
-0.10
0.40
0.59
1.50
-0.51
2.39
-0.84
3.57
-1.38
1.35
-0.69
-0.28
0.30
1.49
-0.29
2.96
-1.25
1.05
-1.03
4.61
-3.16
0.70
-0.18
0.93
-0.52

19 of 22

Section 4
SJ Emp
-0.34
-0.04
-0.08
-0.27
1.77
0.12
0.02
0.15
-0.44
0.38
-0.41
1.56
0.23
-0.09
-0.23
0.31
-2.04
-0.39
0.60
0.50
-1.04
1.22
2.16
3.09
0.31
-0.24
-0.15
0.14
2.21
2.45
-0.40
-2.38
-0.62
0.99
-0.29
-0.23
2.08

Contemp
10.44
8.97
8.38
4.41
1.41
4.91
13.75
-0.28
1.89
0.53
3.94
2.52
4.23
0.33
2.20
4.91
1.78
0.39
1.19
0.84
0.95
2.70
1.84
6.73
1.40
1.69
2.01
6.24
0.73
-2.20
5.44
0.35
2.56
-0.83
1.93
-0.04
0.62

Regression T-Stats
Lagged
Revenue
2.21
-1.05
3.99
-3.14
2.13
-1.64
1.72
-1.21
2.27
-0.74
-0.37
0.47
6.15
-3.76
1.47
-0.42
0.78
-0.27
0.91
-0.07
0.68
1.77
0.28
0.01
1.86
-0.49
-0.28
0.37
0.66
-0.16
3.62
-2.13
0.33
2.25
0.24
-0.10
0.79
-0.53
0.48
-0.34
0.84
0.41
1.46
-1.39
1.56
-1.55
1.26
-4.45
1.17
-0.13
0.08
0.14
1.58
-1.42
3.53
-3.28
1.19
-0.94
2.04
-1.87
-0.61
1.27
0.28
-0.06
3.71
-3.39
1.32
-2.01
1.31
-1.27
0.23
-0.07
1.93
-1.36

Section 5
SJ Emp
-1.42
-0.29
-0.29
-0.33
2.01
0.23
0.14
0.17
-0.43
0.24
-0.85
2.86
0.46
-0.02
-0.18
0.90
-5.15
-0.06
0.22
0.17
-0.53
0.96
1.36
4.93
0.20
-0.08
-0.52
0.44
1.30
3.56
-1.51
-0.55
-1.23
2.15
-0.30
-0.03
4.48

Section 6

Net Effect
C+L
T-Stat
2.51
4.97
2.46
5.57
2.67
3.97
3.71
2.77
1.97
2.14
0.89
1.50
2.35
11.01
0.50
0.57
2.75
1.12
1.44
0.92
1.40
2.74
1.47
1.11
2.71
4.12
-0.56
-0.14
2.73
2.07
2.94
4.97
0.66
0.73
3.65
0.29
4.88
0.93
3.01
0.61
1.05
0.99
4.57
1.88
7.08
1.74
2.42
8.37
3.43
2.57
3.54
0.77
2.39
1.78
3.70
5.12
4.33
1.71
0.49
0.54
0.77
1.34
2.60
0.31
4.41
3.45
0.66
0.61
5.76
1.56
0.52
0.08
1.20
1.59

r2

522

0.99
0.98
0.97
0.87
0.71
0.97
0.99
0.52
0.94
0.40
0.89
0.90
0.92
0.51
0.75
0.94
1.00
0.83
0.83
0.74
0.97
0.95
0.93
0.99
0.93
0.95
0.82
0.98
0.87
0.99
0.98
0.83
0.93
0.96
0.86
0.62
0.98

Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page60 of 62
Exhibit 2
Intuit
Section 1
Job Title

Years
of Data
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6

Total
Emp-Years
96
39
91
8
26
26
31
9
8
405
230
14
23
15
8
12
18
78
38
115
37
102
74
24
338
17
6
16
54
98
179
23
19
35
18
15
16
10
38

Section 2
Level Correlation
Coeff
T-Stat
0.71
2.02
0.71
2.01
0.71
2.00
0.69
1.92
0.67
1.81
0.58
1.41
0.57
1.39
0.54
1.27
0.52
1.22
0.46
1.02
0.43
0.96
0.42
0.93
0.41
0.91
0.40
0.88
0.38
0.82
0.38
0.81
0.35
0.75
0.33
0.70
0.33
0.69
0.29
0.60
0.28
0.58
0.23
0.48
0.07
0.14
0.05
0.10
0.01
0.01
0.00
-0.01
-0.05
-0.09
-0.09
-0.17
-0.12
-0.25
-0.13
-0.27
-0.24
-0.50
-0.26
-0.54
-0.29
-0.61
-0.36
-0.78
-0.38
-0.83
-0.40
-0.87
-0.46
-1.02
-0.47
-1.06
-0.85
-3.22

Change Correlation
Coeff
T-Stat
0.95
5.47
0.74
1.93
0.49
0.97
0.68
1.62
0.19
0.33
0.28
0.51
0.77
2.08
-0.38
-0.71
0.78
2.14
0.60
1.30
0.69
1.63
0.36
0.67
0.09
0.15
0.17
0.30
-0.03
-0.06
0.44
0.85
0.27
0.49
0.38
0.70
0.85
2.82
0.09
0.15
0.59
1.27
0.66
1.51
-0.05
-0.09
0.48
0.94
0.43
0.82
-0.30
-0.55
-0.13
-0.23
-0.15
-0.26
-0.93
-4.33
0.81
2.40
0.34
0.63
0.09
0.16
0.07
0.13
0.83
2.61
0.22
0.40
0.53
1.08
0.80
2.29
0.69
1.36
-0.92
-3.98

Section 3
Contemp

Section 4

Section 5

Section 6

Regression Coefficients
Lagged
Revenue

Regression T-Stats
Lagged
Revenue

Net Effect
C+L
T-Stat

r2

20 of 22

SJ Emp

Contemp

SJ Emp

523

Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page61 of 62
Exhibit 2
Pixar
Section 1
Job Title
TECHNICAL_DIRECTOR
ARTIST_SKETCH
ENGINEER_SOFTWARE
ANIMATOR_SUPERVISING
ANIMATOR
ANIMATOR_DIRECTING
LAYOUT_ARTIST
ENGINEER_SR_SOFTWARE
DESIGNER_PRODUCTION
ANIMATOR_FIX
ART_DIRECTOR
ENGINEER_QUALITY_ASSURANCE
SYSTEMS_ADMINISTRATOR_SR
ARTIST_STORY
MGR_DESKTOP_SYSTEMS
SYSTEMS_ADMINISTRATOR
SCIENTIST_SR
TECH_DIRECTOR_SUPERVISING
MGR_FINANCIAL_SYSTEMS
ENGINEERING_MANAGER
ENGINEER_ASSOCIATE
ARTIST_GRAPHIC
ADMINISTRATOR_TECH_DEPT
TECH_DIRECTOR_LEAD_CRTV_SVCS
DEVELOPER_RENDERMAN_PRODUCTS
TECH_DIRECTOR_CRTV_SVCS
SCULPTOR
ENGINEER_PRODUCTION_SUPPORT
PROJECT_MGR_STUDIO_TOOLS
MGR_SYSTEMS_OPERATIONS
ENGINEER_RENDERMAN_SUPPORT
VP_SOFTWARE_ENGINEERING
USER_INTERFACE_DESIGNER
DIR_RENDERMAN_PRODUCT_DEV
DESIGNER_ENVIRONMENTAL
ARTIST_AFTER_EFFECTS
TECHNICAL_WRITER
TECHNICAL_LEAD_RENDERING
ARTIST_STORY_DEVELOPMENT
ARCHITECT_SYSTEM
TECHNICAL_LEAD_BACKUP_GROUP
ART_DIRECTOR_SHADING
TECHNICAL_DIRECTOR_LEAD
ENGINEER
DIR_STUDIO_TOOLS
MGR_MEDIA_SYSTEMS
ENGINEER_SR_MEDIA_SYSTEM
MGR_TOOLS_WORKFLOW
ENGINEER_MEDIA_SYSTEMS
MGR_QUALITY_ASSURANCE
ENGINEER_PIPELINE
ENGINEER_RECORDING
HR_APPLICATION_DEVELOPER
RENDER_PIPELINE_SPECIALIST

Years
Total
of Data Emp-Years
11
1872
11
141
11
503
11
70
11
772
11
44
11
129
11
53
11
62
11
73
11
70
11
54
11
91
11
247
11
11
11
133
11
62
11
70
11
11
11
11
11
11
11
42
11
24
11
11
11
11
11
44
11
22
11
35
10
35
10
10
10
15
10
12
10
20
9
9
9
15
8
25
8
13
8
8
8
20
7
11
7
8
7
22
7
115
7
7
7
7
7
9
7
12
7
7
7
16
7
7
7
16
7
7
7
7
7
19

Section 2
Level Correlation
Coeff
T-Stat
0.94
8.31
0.91
6.64
0.91
6.41
0.82
4.35
0.81
4.21
0.77
3.57
0.75
3.37
0.74
3.31
0.73
3.20
0.72
3.10
0.70
2.95
0.58
2.16
0.56
2.04
0.55
1.98
0.51
1.79
0.50
1.75
0.50
1.74
0.49
1.67
0.43
1.41
0.42
1.38
0.42
1.38
0.42
1.37
0.38
1.22
0.34
1.09
0.21
0.63
0.19
0.59
0.17
0.52
0.12
0.36
0.50
1.62
0.41
1.28
0.28
0.83
0.26
0.76
0.14
0.40
0.34
0.95
0.17
0.45
0.58
1.73
0.35
0.92
0.34
0.89
0.27
0.70
0.98
10.74
0.96
7.73
0.95
6.70
0.92
5.28
0.85
3.60
0.82
3.21
0.78
2.79
0.76
2.65
0.56
1.50
0.43
1.07
0.25
0.57
0.06
0.14
0.02
0.05
-0.03
-0.06
-0.14
-0.32

Change Correlation
Coeff
T-Stat
0.89
5.65
0.82
4.06
0.93
7.25
0.89
5.41
0.78
3.53
0.89
5.59
0.79
3.68
0.79
3.59
0.86
4.86
0.75
3.21
0.76
3.26
0.82
4.06
0.81
3.97
0.46
1.48
0.81
3.89
0.29
0.86
0.39
1.21
0.72
2.95
0.84
4.41
0.83
4.20
0.88
5.34
0.63
2.29
0.86
4.72
0.84
4.35
0.79
3.66
0.26
0.75
0.41
1.29
0.12
0.35
0.71
2.65
0.74
2.66
0.68
2.45
0.56
1.79
0.66
2.35
0.78
3.01
-0.43
-1.07
0.73
2.36
0.63
1.60
0.81
3.05
-0.03
-0.06
0.85
3.29
0.90
4.22
0.78
2.52
0.79
2.25
0.76
2.31
0.96
7.09
0.86
3.41
0.18
0.36
0.77
2.39
0.26
0.54
0.61
1.53
0.70
1.96
0.92
4.69
-0.06
-0.11
0.55
1.33

Section 3
Contemp
0.55
1.29
0.95
0.23
0.55
-1.79
0.91
0.70
-0.52
0.53
1.18
0.72
1.07
1.27
1.08
0.74
1.06
1.91
0.91
0.88
0.84
1.15
0.60
0.95
1.01
0.57
0.84
0.77
1.47
1.03
1.10
3.29
0.65
1.66
1.85
-0.34
0.56
1.03
-0.05
1.66
-0.83
0.55
1.04
1.18
2.09
2.94
1.90
1.06
-0.71
1.05
2.22
0.97
0.09
1.06

Regression Coefficients
Lagged
Revenue
0.31
0.03
1.53
-0.12
0.70
0.01
2.42
-0.22
0.48
0.06
3.71
0.06
1.27
0.15
1.61
0.00
2.50
-0.22
1.60
-0.05
0.70
-0.04
1.11
0.24
0.56
0.12
1.09
0.01
0.42
0.01
1.15
0.06
1.26
-0.09
0.66
-0.15
0.34
0.00
0.24
0.08
0.21
0.04
0.84
0.08
0.02
0.09
0.24
0.06
0.25
0.03
0.92
0.18
0.35
0.07
0.92
0.01
0.68
0.03
0.40
-0.20
0.49
0.02
0.66
0.72
0.35
0.02
0.14
0.12
1.06
0.30
1.69
0.31
0.96
0.85
0.02
0.22
0.57
0.11
0.21
-0.06
4.13
-0.40
1.40
0.06
1.77
-0.06
0.74
0.09
0.29
0.07
0.52
0.05
1.47
0.15
1.29
-0.21
0.69
0.07
0.53
0.16
0.86
0.07
0.26
0.01
1.52
0.50
0.37
0.29

21 of 22

Section 4
SJ Emp
-0.02
0.18
-0.25
2.26
-0.82
2.65
0.47
0.79
3.16
0.10
1.55
-0.86
0.70
0.41
1.19
-0.16
0.07
3.54
0.90
0.56
0.53
1.67
-0.13
0.73
1.20
-1.39
1.70
-1.08
-4.53
2.10
-0.34
-9.33
0.43
2.32
-1.74
-2.68
-6.04
2.32
-1.05
2.78
2.52
0.28
-0.58
-0.79
5.04
-1.45
-1.79
-9.01
2.87
-0.85
-0.01
0.02
-0.48
0.00

Contemp
3.08
7.17
6.38
0.18
5.27
-1.16
3.97
1.75
-0.22
0.86
4.33
1.07
5.49
2.96
4.76
1.93
2.05
4.54
5.48
4.82
5.76
3.63
4.06
4.89
4.52
2.12
4.85
1.17
2.67
3.42
2.08
2.20
1.94
3.77
5.23
-0.22
11.18
6.00
-0.10
0.99
-0.40
1.35
5.27
0.89
4.09
7.78
0.65
-0.61
18.35
2.35
509.00
0.03
6.82

Section 5

Regression T-Stats
Lagged
Revenue
0.63
0.60
4.44
-1.77
1.64
0.14
1.94
-1.18
1.97
1.47
2.92
0.44
3.23
1.90
2.89
0.03
1.55
-0.97
2.81
-0.33
1.74
-0.33
1.77
1.00
2.03
1.65
2.26
0.07
1.69
0.09
2.43
0.51
2.72
-0.49
1.97
-0.89
1.95
0.03
1.10
1.22
1.20
0.67
2.51
0.76
0.10
1.73
1.21
0.87
1.44
0.42
3.91
1.80
2.20
1.10
1.57
0.04
2.62
0.15
1.19
-0.93
1.33
0.06
1.19
1.18
1.17
0.19
0.40
0.55
12.17
6.25
2.03
0.66
17.44
10.07
0.08
2.32
2.80
0.51
0.19
-0.21
1.31
-1.32
1.81
0.93
3.52
0.21
0.72
8.33
3.32
0.72
16.92
3.50
279.12
0.99
5.52

3.33
0.16
0.45
11.24
-0.40
0.31
22.03
0.68
44.62
0.65
15.44

SJ Emp
-0.06
0.40
-0.62
1.85
-3.57
2.22
0.79
1.11
1.44
0.10
1.81
-0.75
1.48
0.43
1.88
-0.20
0.06
3.08
2.06
1.12
1.39
1.85
-0.36
1.37
2.01
-1.63
4.11
-0.60
-2.08
1.93
-0.13
-2.35
0.35
1.91
-4.55
-1.00
-16.87
3.35
-0.29
0.75
1.09
0.23
-1.49
0.96
-0.50
-5.53
-3.41
0.72
-6.19
-0.01
3.82
-0.07
0.01

Section 6

Net Effect
C+L
T-Stat
0.86
1.32
2.82
6.78
1.65
3.78
2.65
5.34
1.03
3.32
1.92
3.94
2.18
5.50
2.32
5.27
1.98
2.14
2.12
4.47
1.89
3.36
1.83
3.79
1.63
4.81
2.36
2.98
1.50
4.24
1.89
2.50
2.31
2.91
2.56
4.81
1.24
4.99
1.12
3.60
1.05
4.31
1.98
3.68
0.62
2.11
1.19
4.01
1.25
4.30
1.49
3.88
1.19
4.57
1.69
1.58
2.15
3.58
1.44
2.70
1.59
2.68
3.95
2.37
0.99
2.17
1.80
3.41
2.92
7.02
1.35
1.15
1.52
20.27
1.05
3.89
0.52
0.90
1.87
1.13
3.30
2.38
1.95
2.38
1.92
2.38
3.45
3.37
2.35
-0.02
1.58
3.09
1.22
1.61
1.43

r2

5.57
1.63
4.23
8.20
1.54
-0.02
21.97
3.38
620.48
0.50
7.54

524

0.82
0.94
0.91
0.89
0.92
0.92
0.92
0.89
0.83
0.83
0.83
0.80
0.90
0.70
0.86
0.62
0.68
0.87
0.88
0.86
0.88
0.79
0.84
0.86
0.85
0.85
0.92
0.39
0.85
0.81
0.67
0.89
0.61
0.88
0.99
0.85
1.00
0.97
0.86
0.83
0.93
0.94
0.98
0.97
0.97
0.99
0.98
0.80
1.00
0.97
1.00
0.53
1.00

Case5:11-cv-02509-LHK Document424-2 Filed05/17/13 Page62 of 62
Exhibit 2
Pixar
Section 1
Job Title
ENGINEER_SOFTWARE_TECHSUPPORT
ENGINEER_IMAGE_MASTERING
TECHNICAL_LEAD_TELECOM
ENGINEER_SCREENING_ROOM
MGR_IMAGE_MASTERING
CGI_PAINTER
DESIGNER_CAMERA
ENGINEER_APPLICATIONS
FINANCIAL_APPS_DEVELOPER
MGR_SR_PROJECT_STUDIO_TOOLS
LAYOUT_ARTIST_LEAD
MEDIA_SYSTEMS_COORDINATOR

Years
of Data
7
6
6
6
6
6
6
6
6
6
6
6

Total
Emp-Years
7
8
6
6
6
65
6
6
6
6
6
8

Section 2
Level Correlation
Coeff
T-Stat
-0.86
-3.77
0.92
4.74
0.92
4.65
0.88
3.76
0.88
3.69
0.74
2.20
0.60
1.50
0.52
1.22
0.46
1.03
0.46
1.03
0.42
0.93
0.12
0.24

Change Correlation
Coeff
T-Stat
0.01
0.03
0.54
1.13
0.75
1.97
0.79
2.24
0.78
2.18
0.53
1.07
0.76
2.00
0.57
0.98
0.80
2.31
0.21
0.31
0.27
0.49
-0.35
-0.66

Section 3
Contemp
-0.51

Regression Coefficients
Lagged
Revenue
0.02
-0.01

22 of 22

Section 4
SJ Emp
2.20

Contemp
-0.63

Regression T-Stats
Lagged
Revenue
0.07
-0.03

Section 5
SJ Emp
1.07

Section 6

Net Effect
C+L
T-Stat
-0.49
-0.55

r2

525

0.58

Case5:11-cv-02509-LHK Document470-1 Filed07/19/13 Page1 of 40

IN THE UNITED STATES DISTRICT COURT
FOR THE NORTHERN DISTRICT OF CALIFORNIA
SAN JOSE DIVISION
CONFIDENTIAL – TO BE FILED UNDER SEAL
SUBJECT TO PROTECTIVE ORDER

IN RE: HIGH-TECH EMPLOYEES ANTITRUST
LITIGATION

No. 11-CV-2509-LHK

_____________________________________
THIS DOCUMENT RELATES TO:
ALL ACTIONS

REBUTTAL SUPPLEMENTAL EXPERT REPORT OF EDWARD E. LEAMER, PH.D.

July 12, 2013

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TABLE OF CONTENTS

I. 

Introduction, Assignment, and Summary of Conclusions ..........1 
A.  My Opinions ................................................................................... 1 
B.  Dr. Murphy’s Opinions and My Specific Responses ................................ 2 
C.  Summary of My Responses ............................................................... 4 

II. 

Dr. Murphy Considers Only Isolated Individual Cold Calls,
and Ignores the Effects of Bursts of Cold Calls and
Heightened Threats of Future Cold Calls That Would Have
Occurred Absent the Illegal Agreements ...................................7 

III.  Contrary to Dr. Murphy’s Opinion, the Presence of Individual
Effects, Even Large Ones, Leaves Room for Common Factors
Affecting All ............................................................................ 11 
1.  Defendants’ Use of Salary Range Targets is Consistent with My
Title-Focused Analysis ............................................................... 13 
2.  Google’s Big Bang Demonstrates that Dr. Murphy’s Individual-Level
Approach Hides Common Impact ................................................ 13 

IV. 

Dr. Murphy’s Claims about Statistical Errors are False ............16 
A.  Correlations are Informative ........................................................... 17 
B.  There is No “Reflection Problem” in My Analysis ................................. 18 
C.  Dr. Murphy’s Theory of Regression toward the Mean Requires
Randomness That Is Not Part of the Compensation Determination in
the Technical Class ........................................................................ 19 
D.  Dr. Murphy’s Study of Chicago Daily Temperature is Flawed and
Irrelevant ..................................................................................... 21 

V. 

Dr. Murphy’s Analysis of “Sharing” in the ACS Data is Flawed
and Unreliable ......................................................................... 21 
A.  The ACS Data Suffer from Critical Measurement Errors That Make
Them Unsuited to the Analysis that Dr. Murphy Has Carried Out .......... 22 
1.  ACS Survey Practices Create Potentially Serious Response Errors .... 22 
2.  The ACS Annual Data Mix Two Years of Information ....................... 23 
B.  The ACS Correlations Are Much Lower Than the Title-by-Title
Correlations Computed with the Defendant Payroll Data...................... 24 
C.  Other Flaws in the ACS Data for Dr. Murphy’s Analysis ....................... 28 

VI. 

Dr. Murphy’s Concerns about Common Effects Excluded from
My Work Are Strictly Hypothetical ........................................... 28 
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VII.  Conduct Regression................................................................. 30 
VIII. Almost All Employees Received Supplemental Compensation
or Salary Increases ................................................................. 31 
APPENDIX A. 

Defendants’ Use of Salary Ranges .......................... 33 

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I.

July 12, 2013

Introduction, Assignment, and Summary of Conclusions

1.

I have been asked by the Plaintiffs to comment on the Supplemental Report of
Dr. Kevin M. Murphy dated June 21, 2013 (“Murphy Supplemental Report”),
and in particular to say whether any of the opinions expressed by Dr. Murphy
cause me to change the conclusion reached in my Supplemental Report dated
May 10, 2013 (“Leamer Supplemental Report”), that the alleged restraint of
competition by the Defendant firms suppressed compensation to all or nearly all
members of the proposed Technical Class. They do not. Exhibit 1 lists
materials I have relied upon in addition to the materials cited in my previous
reports.
A. My Opinions

2.

Dr. Murphy has distorted my opinions, and to set the record straight I offer a
summary in this section.

3.

The hypothesis that underlies my study of the defendants’ payroll records is that
the non-compete agreements prevented a burst of actual cold calls from
happening and also eliminated the threat of future cold calls between the
agreeing parties. I have never offered the opinion that the effect of a single
isolated cold call would necessarily increase compensation for every employee in
the Technical Class. My opinion is that the information conveyed by each cold
call reinforces the information in other cold calls, making the effects
“superadditive”, meaning that the effect of a burst of cold calls is more than the
sum of the parts. My opinion is that, absent these illegal agreements, bursts of
cold calls and a heightened threat of cold calls would have been met with
increases in compensation for all or almost all individuals in the Technical Class.

4.

Cold calls that were suppressed by the non-compete agreements were likely
more concentrated in some titles than in others. I also have the opinion that the
firms’ assessments of the threat of cold calls—and their responses to those
threats—would have been broader than just the cold calls that actually would
have happened in the but-for world. Because the cold calls in the but-for world
would have been more concentrated in some titles than in others, and because
any broad response to the burst of actual cold calls and the threat of future cold
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calls would have occurred through Defendants’ title-based pay systems, I have
chosen to use the title averages as the basis for my data work to help define the
class. In addition, title averages tend to be less affected by the idiosyncratic
individual variability which is irrelevant to a finding of common impact
throughout the Technical Class.
5.

As a measure of the tightness of the ties that bind titles together, I have
reported correlations of both the levels of compensation and the percent
changes in compensation of each title vis-à-vis the rest of the firm’s Technical
Class absent the title in question.1 My opinion is that this correlation evidence
supports and is supported by the abundance of documents and testimony that
reveal the importance of internal equity issues for firms generally and for these
firms in particular.

6.

Correlations need not be solely the consequence of internal equity concerns that
work to tie compensation together, but may also arise partly from other factors
that are common across titles. I have therefore controlled for what I regard to
be the two most powerful common forces–firm performance (measured by firm
revenue) and external market forces (measured by the employment levels in the
San Jose MSA). In the estimated model that I have presented, these forces have
different impacts on the various titles but these forces do not explain away the
substantial correlation between title compensation and the firm’s overall
Technical Class compensation.
B. Dr. Murphy’s Opinions and My Specific Responses

7.

In his Supplemental Report, Dr. Murphy presents the following opinions:2
a.

Dr. Murphy claims my analysis must, but cannot, demonstrate that “a
raise to employees who receive a cold call would increase
compensation even to other employees with the same job title.”
RESPONSE: This comment refers to the effect of a single cold call,

1

Leamer Supplemental Report, pp. 10-12.

2

Murphy Supplemental Report, pp. 1-2.
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not to the relevant hypothetical: bursts of cold calls and a heightened
threat of future cold calls.
b.

Dr. Murphy claims “correlations of average compensation by job title
with overall average compensation for the proposed Technical Class
cannot show that raises for some employees necessarily would result in
raises for some or all.”
RESPONSE: This also refers to the wrong hypothetical. For the
relevant hypothetical of bursts of cold calls and elevated threats of cold
calls, correlations of compensation, correlations of changes in
compensation, and the contemporaneous and inter-temporal
relationships in compensation across the proposed Class all strongly
support the conclusion that Defendants’ compensation is structured
such that it would make the impact of the non-compete agreements
common to the proposed Class.

c.

Dr. Murphy claims that “neither [my] correlation analysis nor [my]
regression analysis can distinguish a ‘somewhat rigid’ compensation
structure” because they fall “victim” to two well-known statistical
fallacies and that these fallacies “virtually guarantee” my sharing
regression results.
RESPONSE: The “reflection” and “regression-to-the mean” fallacies
do not apply to my work. The first fallacy amounts to the familiar
statement that correlation is not causation, but I have never claimed
otherwise. It also amounts to the familiar generic fact that estimated
regression models change when additional variables are added into the
equation. I am fully aware of this fact, and the reason I added
additional variables into my correlation analysis is to determine the
extent to which the observed correlations are due to two potentially
important common factors. Dr. Murphy, rather than being helpful,
merely states what is obvious: that there theoretically might be other
variables one could study. If that were all that is necessary to invalidate
a regression, no one could ever estimate a regression with nonexperimental data. The second, “regression-to-the-mean,” fallacy
depends on the presence of substantial randomness in the data set;
Defendants do not pay their employees in a substantially random way.
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d.

Dr. Murphy claims that I do not “establish that the proposed class is
properly defined.”
RESPONSE: I have provided evidence that supports the proposed
class. Dr. Murphy has provided no evidence useful for an alternative
definition of the boundaries of the class.

e.

Dr. Murphy implies that I needed to “improve the accuracy” of the
conduct regression.
RESPONSE: My conduct regression demonstrates a reliable
methodology capable of measuring damages on a class-wide basis. The
regression model I proposed utilizes the variation in the data and is
accurate enough to distinguish impact year-by-year and defendant-bydefendant.

C. Summary of My Responses

8.

Dr. Murphy’s first four arguments boil down to claims that 1) the presence of
substantial individual effects implies that there cannot be a common firm-wide
internal equity component to compensation, and 2) the statistical evidence that I
find of the importance of internal equity and sharing as a common factor in
compensation is the result of something else—either some other common
factor(s) he fails to identify or a statistical anomaly. I discuss his final issue
regarding my conduct regressions below.

9.

There are certain similarities in how Dr. Murphy and I view Defendants’
compensation setting and important differences:
a.

Dr. Murphy and I both agree that there are individualized factors in
individual compensation (though he exaggerates their importance and
downplays the extent to which Defendants take a systematic approach
to adjusting compensation in response to those individualized factors
within their firm-wide compensation structures);

b.

Dr. Murphy and I both agree that market factors play a role in
compensation. It is for this very reason that I included market factors
in my sharing regressions to control for these effects; and

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c.

Dr. Murphy and I both agree that there may be common factors within
the firm—not related to the non-compete agreements—that may
influence employee compensation. Firm performance is probably the
most important common factor and the only one identified by Dr.
Murphy. I included firm revenue to control for such effects. While Dr.
Murphy is silent about what other factors may tie firm-wide employee
compensation together, the statistical, theoretical and documentary
evidence I have presented establishes that internal equity and the use of
a salary structure by these firms is also an important factor.

10.

In this Report, I address Dr. Murphy’s claims. First, I point out that Dr.
Murphy incorrectly focuses on the reaction that firms make to individual isolated
cold calls, and he ignores the response that firms make to bursts of cold calls.
He also ignores the broad preemptive responses that firms make to the threat of
cold calls, for example, the across-the-board increase in base salaries for Google
employees in 2011.

11.

Second, Dr. Murphy incorrectly acts as if the data evidence has to stand on its
own in determining the class.3 Wise interpretation of non-experimental data
needs to be sensitive to the context in which the data were generated, and
persuasive conclusions from the numerical data require the information in the
numerical data and the documents to be aligned. The data in this case support
and are supported by substantial documentary and testimonial evidence
including but not limited to the following:
a.

The non-compete agreements covered all employees in the defendant
firms;

b.

The CEOs of the defendant firms confirmed the broad and substantial
impact that the cold calling was likely to have had by the fact that they
personally got involved in these illegal agreements;

c.

HR documents of all these firms confirm the importance of internal
equity in the setting of compensation levels;

Deposition of Kevin Murphy Vol. 2, July 5, 2013 at p.443:12-14, “The court can read the documents. I’m an
economist. I got no particular advantage of reading documents.”

3

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d.

Depositions of HR professionals within these organizations also
confirm the importance of internal equity; and

e.

There is substantial literature in economics which Dr. Murphy ignores
regarding the importance of internal equity in the compensation
setting, brought forward by my previous reports and Dr. Hallock.4

12.

13.

Moreover, a direct causal inference such as the one alluded to by Dr. Murphy
requires experimental evidence like a clinical trial in which the treatment is
randomized, but as Dr. Murphy surely knows, there is nothing like that in this
data set. Accordingly, we analyze correlations, which are routinely used by
economists to draw causal conclusions when supported by compelling
frameworks and complementary information. The fact that all or almost all of
the titles are tied closely together is evidence that the impact of the agreements
would spread at least throughout the Technical Class.

14.

4

Only by incorrectly focusing on the impact of individual isolated cold calls and
by incorrectly ignoring the substantial documentary and testimonial evidence is
Dr. Murphy able to issue the challenge that I have not shown the causal chain
linking a cold call to compensation of the recipient and to anyone else. This
challenge is only marginally relevant for the bursts of cold calls prevented by the
agreements and irrelevant for the preemptive compensation increases that firms
can make to prevent cold calls from happening and to mitigate the damage that
attractive cold calls might cause. In neither case is the impact spread through
the firm per the causal chain to which Dr. Murphy refers.

Third, the fallacies that Dr. Murphy identifies simply do not apply to this
context. First, I anticipated and addressed the potential “reflection problem” by
analyzing correlations between non-overlapping sets of employees. I used these
correlations to assess whether these titles have compensation levels that are tied
together, and in the face of competitive pressure they are likely to remain tied
together. Second, I reject Dr. Murphy’s notion that compensation is subject to
the same kind of randomness as the daily weather in Chicago. For that reason,
Dr. Murphy’s concerns about “regression toward the mean” are unjustified by

Expert Witness Report of Kevin F. Hallock, May 10, 2013 (“Hallock Report”).
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the circumstances and not connected to any factual evidence that describes how
these firms chose compensation levels. Employee compensation is the outcome
of a deliberate decision making process followed by the firms and is not subject
to the degree of randomness that Dr. Murphy suggests.
15.

16.

To further suggest the existence of omitted variables, Dr. Murphy also uses data
on U.S. compensation by occupation collected by the American Community
Survey. It is evident that Dr. Murphy has not seriously studied these ACS data
and presumes that his cursory look is enough. In the brief period of time I have
had to review this work, I have uncovered numerous serious errors both with
the data and with the way they have been (mis-)interpreted by Dr. Murphy. The
ACS-based work of Dr. Murphy is irrelevant and unreliable.

17.

II.

Fourth, Dr. Murphy again emphasizes that left-out variables can cause
problems with regression analysis. However, he has not put forward any
specific example of such an effect. This argument remains entirely hypothetical
and entirely unconvincing. While I have controlled for the external and internal
non-sharing effects that he claims pollute my results, he has not presented any
evidence showing that omitted non-sharing external or internal effects are
actually responsible for the positive sharing in my results. He has not
elaborated on what his claimed ‘other common factors’ could be. Nor has he
proposed any test of whether my results are flawed.

Fifth, the conduct regressions in my Report and Reply Report illustrate a
method of computing damages for the Technical Class and are capable of
providing reliable estimates of Defendants’ under-compensation of their
employees.

Dr. Murphy Considers Only Isolated Individual Cold Calls, and
Ignores the Effects of Bursts of Cold Calls and Heightened
Threats of Future Cold Calls That Would Have Occurred Absent
the Illegal Agreements

18.

Dr. Murphy proposes that all impact begins with individuals who would have
been cold-called but-for the non-compete agreement. He insists on proof of a
causal chain linking other employees to the ones that would have had a cold call.
This theory is a strictly reactive theory, i.e., any compensation-setting reaction
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by management is in response to a specific cold call. This view is clearly stated
by Dr. Murphy [emphasis added]:
8. Dr. Leamer’s empirical analysis focuses on whether
changes in average compensation for various job titles
are correlated with movements in the average
compensation level for the proposed class as a whole.
He does not examine whether changes in
compensation at the individual level, which is where
the initial impact of any cold call would occur,
necessarily cause changes in compensation for all or
nearly all employees in the same job title or for the
proposed class as a whole.5
19.

And:
22. […] Even if, as Dr. Leamer claims, a “Large Share of
[Job Title] Change Correlations are Positive,” it does not
follow that Defendants have compensation structures
that require them to change compensation for all, or
nearly all, class members if they raise one employee’s
compensation in response to a cold call.6

20.

This theory of Dr. Murphy’s presumes incorrectly that the impact of cold calls is
additive, as if a burst of 1,000 cold calls were equivalent to 1,000 times the effect
of a single isolated cold call. On the contrary, the information in one call would
tend to reinforce the information in others, and the effect is consequently likely
to grow rapidly with the number of calls (or to use Dr. Murphy’s preferred term,
“super-additive”). Given this aspect of the cold-call effects, it is my opinion
that the high degree of historical co-movement in compensation across titles
supports the conclusion that the response of these firms to a burst of cold calls
would have spread at least to the edge of the Technical Class.

5

Murphy Supplemental Report, ¶ 8.

6

Murphy Supplemental Report, ¶ 22.
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21.

Another avenue for the effect of the agreements—and perhaps the most
important one—is their disruption of proactive strategies in response to cold
calls. By completely eliminating the threat of cold calls between the agreeing
parties, the agreements also completely eliminated the need for management to
make a preemptive response. The greatest error of Dr. Murphy’s response is that he
ignores completely the avenue of effect through preemptive responses to threatened cold calls in
the form of broad increases in compensation intended both to suppress the cold calling rate and
to make the cold calls that nonetheless occur relatively unimportant.

22.

For studying the case of preemptive responses to threatened cold calls, the job
of the analyst is not to trace out the impact of cold calls from individual to
individual or from title to title but instead to identify the sets of individuals that
management would likely include for preemptive increases in compensation.
These preemptive responses apply not just to those workers who are
experiencing increased external competition but also to all the others who
would be included because of internal equity considerations. The historical
correlations help to identify the subset of titles that would likely be excluded –
those titles that historically had compensation levels that were unconnected with
the rest of the firm.

23.

My theory of damages includes the reaction to a burst of cold calls and also the
broad preemptive responses that management would make to the threat of cold
calls.7 There is substantial evidence in this case for the occurrence and
importance of these types of responses. Some examples already offered by Dr.
Hallock are:
[Intuit]
8

[Google]

7

Leamer Supplemental Report, ¶ 15.

8

Deposition of Mason Stubblefield, Intuit, March 29, 2013 at p. 70.
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24.

25.

III.

Preemptive adjustments are intended to minimize the damage that attractive
cold calls might cause to the behavior of not just the individuals who (in the
but-for world) would have been cold-called—but also the broad swath of
employees whose loyalty might be diminished by knowledge of better
opportunities via cold calls received by their colleagues.
In an earlier report, Dr. Murphy pointed out that the amount of movement
between the Defendants was never very great in any of the years for which
Defendants have provided payroll records, and he has used that as an argument
that the agreements could not have had much effect.13 However, the fact that
the CEOs of these firms got involved in this non-compete scheme means that
the cold calls prevented by the agreements potentially had serious systemic
effects even if there wasn’t much movement of employees. The CEOs who
formed these agreements must have expected that the impact was not just
through the loss of an individual employee or two consequent to a cold call but
through the broad increased threat of movement and the reduced worker loyalty
that can be created by knowledge of better opportunities elsewhere.14

Contrary to Dr. Murphy’s Opinion, the Presence of Individual
Effects, Even Large Ones, Leaves Room for Common Factors
Affecting All

26.

Dr. Murphy’s first opinion is:
The variation in individual compensation, which Dr.
Leamer’s analyses ignore, shows that a raise for one or
some does not necessarily cause a raise for all or nearly
all.15

13

Murphy Report, pp. 18-20, and Leamer Reply Report, pp. 11-13.

As Pixar’s President Ed Catmull observed in an email to a Disney executive: “Every time a studio tries to
grow rapidly, it seriously messes up the pay structure . . . by offering higher salaries to grow at the rate they
desire, people will hear about it and leave.” PIX00000229.

14

15

Murphy Supplemental Report, p. 2.
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27.

This view is completely off-point. To determine whether the employees in the
proposed Technical Class were harmed by the non-compete agreements, I do
not have to demonstrate (nor do I believe) that a “raise for one or some does
necessarily cause a raise for all or nearly all.” My opinion is that the documents
and the data support the conclusion that the response to the bursts of cold calls
prevented by the agreements and the response to the threat of cold calls
prevented by the agreements would together have had effects that extended
throughout the proposed Technical Class, increasing compensation in the butfor world for all or almost all of the proposed class members. The reason for
this is that both the response to bursts of cold calls and, even more, the
response to the threat of cold calls would surely raise internal equity concerns
that would spread the impact to the edge of the class.

28.

My work is based on the assumption that there are individual effects in
compensation and there are also common firm-wide effects that tend to tie the
individuals together. My opinion is that the class should include (1) all
individuals who were in the group of probable recipients of the burst of cold
calls, and (2) all who were in the group of individuals who would have
experienced heightened risk of cold calls and also (3) those individuals who are
linked to the first two groups by internal equity considerations.

29.

The payroll data that I have studied cannot be used to identify the first two
affected groups, but the written record indicates that these individuals are very
likely concentrated inside the Technical Class. It is possible that the increased
cold calls and heightened threat of cold calls extended very broadly, affecting all
or almost all members of the Technical Class, but I do not rely on that
possibility. What I rely on is that the forces of internal equity are very broad
and likely to extend the impact of the anti-cold-calling agreements to all or
almost all members of the Technical Class. The statistical task is to identify the
common factors in the individual data and to apportion these common factors
between internal and external forces.

30.

As I explained in my report, one of the reasons that I chose to work with titlebased averages is that averaging across the individuals in any title can reduce the

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individual idiosyncratic effects and make the common factors more evident.16
The other reason for using a title-based data set is that it is the title structure
that allows senior management to control compensation throughout the firm.
The right class definition consequently should be title-based, and I have
explored the technical-class titles to determine if there are any titles with average
compensation packages that are not tied internally to compensation packages in
other titles. I have not found any titles that are immune to the forces of internal
equity and that should be excluded from the class. Dr. Murphy has not made
any attempt to argue that any titles should be excluded.
1. Defendants’ Use of Salary Range Targets is Consistent with My
Title-Focused Analysis

31.

This approach is supported by Defendants’ use of target salary ranges in
determining their employees’ base compensation. As shown in Appendix A, the
target salary range data17 matched with their payroll data indicates that
Defendants conformed their employees’ compensation to those ranges
percent of the time (employee-years for which data were available).
2. Google’s Big Bang Demonstrates that Dr. Murphy’s IndividualLevel Approach Hides Common Impact

32.

16

Dr. Murphy claims that the search for impact should begin at the level of
individual compensation. A closer look at the Google data, including the 10
percent across-the-board increase that occurred on January 1, 2011, illustrates
why the title is an appropriate level of aggregation for this analysis: the inherent
noise in the individual level data tends to drown out the signal of the internal
pay structure we are trying to detect. I will demonstrate here that individual
variation in the data masks even such a sweeping common phenomenon as the
Google Big Bang, which we know occurred. An analyst working with this data
will do much better justice to such common phenomena by studying the titles as
opposed to the individual employees.

Leamer Supplemental Report, p. 6.

This analysis is based upon salary range data produced by Adobe, Apple, Google, and Intel. Intuit did not
produce adequate data, and thus was not included in this study.

17

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33.

Table 1 reports summary statistics for year-by-year percent increase in base
compensation for Google’s employees in the Technical Class. These include the
mean, or average, increase in base compensation and the standard deviation, a
measure of the variability in that increase across Technical Class employees.
According to Dr. Murphy’s theory that making a company-wide change in pay
largely precludes individual variation, he would apparently expect something like
a 10 percent mean and a 0 standard deviation for the percent change in base
salary for the period that includes January 1, 2011 (December 31, 2010 to
December 31, 2011). This would indicate that all effects are common effects
and there are no individual effects. However, the mean for the year 2011 is
percent,
, and the standard deviation is percent.
The standard deviation in 2011 is similar in size to all the other years, and
usually exceeds the mean. This demonstrates that there was very substantial
individual variation in all years, even 2011 - the year in which we know there
was a large common factor.

34.

Table 2 provides the same information about total compensation, which also
shows variability even in the year 2011 in which we know there was a common
factor affecting compensation. Hence, the presence of individual variation, such
as seen in Table 2 and emphasized by Dr. Murphy, is entirely consistent with
common impact.

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Table 1

Google Base Salary Increase
Technical Class Employees with Google for the last Two Years
Year

Mean

Median

Max

Min

Std. Dev

Obs.

2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
All
Source: Google Employee Compensation Data

Table 2

Google Total Compensation Increase
Technical Class Employees with Google for the last Two Years
Year

Mean

Median

Max

Min

Std. Dev

Obs.

2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
All
Source: Google Employee Compensation Data

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“reversion toward the mean.” His claims are false and my work does not suffer
from either of these problems.
A. Correlations are Informative

37.

Dr. Murphy’s second opinion is a repeat of the familiar statement that
“correlation is not causation.”
In the language of economics, Dr. Leamer implies that
his correlations reflect causality – that a change in one
variable leads to or causes a change in the other – but he
then offers only evidence of co-movement. However,
correlation, or similar movement, in average job-title
compensation does not establish the necessary causation
to support Dr. Leamer’s theory.18

38.

18
19

Correlations are an accepted part of the scientific enterprise in economics and
economists routinely study them in pursuit of knowledge. For example, a
textbook cited by Dr. Murphy describes correlation as a “measure… of the
strength of a relationship between two random variables.”19 Moreover, in a
published article, Dr. Murphy uses correlation analysis to establish a “strong link
between… crack [cocaine] and increased homicide rates by the young.”20 This
article also makes use of a simple regression formulation despite recognizing
that “[i]t is possible that omitted variables… affects both crack and outcomes
like homicide.” In this same article Dr. Murphy and his co-authors use
aggregation which “increases the signal-to-noise” ratio in a fashion similar to my
averaging across individuals to reduce the noise in individual compensation.21

Murphy Supplemental Report, ¶ 21.
Casella G. and R. L. Berger, Statistical Inference, Cengage Learning; Second Edition (June 18, 2001), p. 169.

Fryer, R. G., P. S. Heaton, S. D. Levitt and K. M. Murphy, “Measuring crack cocaine and its
impact,” Economic Inquiry, Vol. 51, No. 3, (July 2013), pp.1651-1681.

20

“[B]ecause each of our individual proxy measures is quite noisy, combining them into a single index
substantially increases the signal-to-noise ratio” Fryer, R. G., P. S. Heaton, S. D. Levitt and K. M. Murphy,
“Measuring crack cocaine and its impact,” Economic Inquiry, Vol. 51, No. 3, (July 2013), pp.1651-1681.

21

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Absent experimental evidence, what we have to rely on are simple correlations
and regressions (“partial” correlations which hold fixed other potentially
important confounding effects). I have provided both.
B. There is No “Reflection Problem” in My Analysis

40.

41.

Still, there remains an issue regarding direction of causation which would more
accurately be described as a “simultaneity problem.” As an illustration, consider
the compensation of just two distinct individuals. Here there is no Manksi-type
average group behavior to worry about and there is no way to use the
correlation between A and B to distinguish the possibility that A affects B, or B
affects A, or some outside force “causes” both A and B.

42.

22

Dr. Murphy uses Professor Manski’s somewhat vague definition of what he calls
the “reflection problem” which is: “This identification problem arises because
mean [average] behavior in the group is itself determined by the behavior of
group members. Hence, data on outcomes do not reveal whether group
behavior actually affects individual behavior, or group behavior is simply the
aggregation of individual behaviors.”22 I have to some extent anticipated this
issue by comparing compensation in each title, not simply with the Technical
Class overall, but with the Technical Class overall with all the individuals in the
title removed. This means I am comparing completely non-overlapping sets of
individuals in each of my regressions.

Correlations are informative regardless of the direction of causation, especially
for the preemptive theory in which the issue is whether titles are “tied together.”
However, even for causation, as Manski suggests,23 it is possible to use lagged
values to see if A data tend to be followed by similar B data. A temporal
ordering such as A routinely preceding B is known as “Granger causality.”24 As

Murphy Supplemental Report, ¶ 35.

23 “One alternative supposes that the researcher observes the dynamics of a process in which individual
behavior varies with lagged rather than contemporaneous values of group mean behavior.” Manski, C. F.,
“Economic Analysis of Social Interactions,” Journal of Economic Perspectives, Vol. 14, No. 3 (Summer 2000), pp.
115-136.
24

Enders, W., Applied Econometric Time Series, Hoboken: John Wiley & Sons, Inc., Third Edition (2010), pp.
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the adjective suggests, this is an indication of causality (though not definitively).
That is why I have used the lagged value of the title compensation compared
with the rest-of-firm compensation to determine if departures of the title
compensation from the normal relationship with compensation in the rest of
the firm tend to predict corrective action – and I find that they do.
43.

After quoting Manski regarding group behavior, Dr. Murphy diverts to the
familiar left-out variable problem (which is different from the simultaneity
problem): “Generally, when individuals in a group are subject to at least some
common influences, it will appear that they are responding to each other even
when they are not.”25 That is exactly the reason in my deposition I agreed that
the high degree of co-movement of compensation title-by-title could
hypothetically be coming from external market forces, although this seems
highly unlikely.26 Hence, I have added two new variables that might be able to
explain fully the intra-firm correlations. I chose variables to include in my
model that measure what I regarded to be the two most promising explanations
for the co-movement of title compensation: (1) revenue sharing, meaning that
variability in firm revenue that was shared broadly with the workforce and (2)
external market forces, which could affect more than one title at the same time.
C. Dr. Murphy’s Theory of Regression toward the Mean Requires
Randomness That Is Not Part of the Compensation
Determination in the Technical Class

44.

Dr. Murphy has made a reference to “regression toward the mean” as a way of
dismissing my result that there is a lagged corrective effect measured by the ratio
of the firm’s Technical Class average compensation (excluding a title) and the
title’s average compensation, lagged one year. Regression toward the mean
refers to sequences of repeated random draws from the same population, and
thus the tendency for a draw that is abnormally high to be followed by
something closer to the mean – thus regression toward the mean. Per Dr.

318-319.
25

Murphy Supplemental Report, ¶ 35.

26

Deposition of Edward Leamer Vol. 2, June 11, 2013 at pp. 528:7-16.
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Murphy, “[t]he regression fallacy arises when an analyst examines a data series
that is subject to shocks that are, at least to some extent, temporary, and ignores
the tendency of such data to “regress” or revert to the mean of the
distribution.”27
45.

46.

The only example that Dr. Murphy provides is salespeople on commission. For
salespeople the regression toward the mean phenomenon may arguably have
some validity. But absent the evidence, I am not so sure that annual
compensation even for salespeople exhibits regression toward the mean. Dayby-day randomness could be there, but averaged out over 365 days we may be
getting mostly constant ability and variable external market sales opportunities.

47.

But, in any case, there are no salespeople in the Technical Class. They have
been excluded as indicated in Exhibit B of my October 1, 2012, report. Nor are
there any employees who are paid based on random factors. Firm revenue to
some extent may behave like a random variable, and some titles may share in
revenues more than others, but I have included the firm revenue as a variable
which should soak up that effect.

48.

27

The applicability of regression toward the mean to payroll records of
Defendants seems to me extremely doubtful. Defendants do not set annual title
compensation the way that Mother Nature chooses Chicago weather, day-byday. Compensation levels in the Technical Class are all determined thoughtfully
by management, not by random devices.

In sum, Dr. Murphy has produced a purely hypothetical claim about regression
toward the mean which relies on an implausible firm approach to compensation
setting.28

Murphy Supplemental Report, ¶ 45.

On the other hand, as I discuss below, randomness in reported compensation is likely an important issue in
the data collected by the American Community Survey (ACS) that Dr. Murphy used.

28

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D. Dr. Murphy’s Study of Chicago Daily Temperature is Flawed and
Irrelevant

49.

V.

Dr. Murphy’s temperature regression model that seeks to explain Chicago
temperature changes is another example of an analysis designed to illustrate an
intended result. Chicago and Milwaukee are within two hours driving distance,
so in the absence of any reasonable control variables, it should not be surprising
that the regression shows a high degree of association. It would be a surprising
result only if it were true for several far apart cities in totally different climate
zones and it persisted even after using adequate control variables.

Dr. Murphy’s Analysis of “Sharing” in the ACS Data is Flawed
and Unreliable

50.

Dr. Murphy mindlessly applies my analysis of co-movement to the economywide American Community Survey (“ACS”) compensation data collected by the
U.S. Census Bureau. Dr. Murphy uses this analysis to support his claim that the
analysis I performed would indicate relationships even where none existed.
There is no support in Dr. Murphy’s work for this conclusion. There are
important measurement error and reliability problems with the ACS data that
render it inappropriate for the time series analysis that Dr. Murphy has
performed. Additional and equally compelling methodological problems with
his work are set forth below.

51.

Beyond the issue of measurement problems the basic premise of this work is
mistaken. Although Dr. Murphy claims that discovery of co-movement in his
ACS analysis reflects a statistical anomaly that would infect any analysis of the
type I have done, some co-movement due to market forces can be expected as
individuals are attracted into high-paying occupations and as firms find
substitutes for exceptionally expensive workers.

52.

The word “Community” in the ACS title tells us the purpose for which this
survey was designed, stated explicitly on the ACS website: “Data from the
American Community Survey helps your community. The information that the
Census Bureau collects helps to determine how more than $400 billion dollars

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of federal funding each year is spent on infrastructure and services.”29 Thus the
income and population data collected by the ACS helps to allocate federal
spending at any point in time across American Communities and was not designed
to trace occupational wages over time as Dr. Murphy has done.
A. The ACS Data Suffer from Critical Measurement Errors That Make
Them Unsuited to the Analysis that Dr. Murphy Has Carried Out

1. ACS Survey Practices Create Potentially Serious Response
Errors

53.

One serious problem with the ACS data is that the questionnaire asks for
information about all residents at the address but is filled in by only one
respondent, who may or may not be the primary income earner.30 This
respondent is likely to provide more accurate information about his or herself
than about other adults at the address.

54.

Another serious problem is that the one respondent at each address is not
encouraged to consult any records and most respondents presumably report
from memory both for themselves and for each of the other adults.31 Unlike
the defendants, who produced the equivalent of a check register showing what
they actually paid employees, there is far less incentive for accurate reporting of
these income figures by the household respondent. One incentive is to get the
survey finished as quickly as possible but accuracy of the responses is not

U.S. Census Bureau, “American Community Survey: Why should you participate?,”
http://www.census.gov/acs/www/about_the_survey/why_should_you_participate/.

29

U.S. Census Bureau, “The American Community Survey: 2013,” p.2,
http://www.census.gov/acs/www/Downloads/questionnaires/2013/Quest13.pdf, “Person 1 is the person
living or staying here in whose name this house or apartment is owned, being bought, or rented. If there is no
such person, start with the name of any adult living or staying here.”

30

U.S. Census Bureau, “The American Community Survey: 2013,”
http://www.census.gov/acs/www/Downloads/questionnaires/2013/Quest13.pdf, The questionnaire asks
for : 1) wages, salaries, commissions, bonuses, or tips from all jobs; 2) self-employment income; 3) interest,
dividends, and rental income; 4) social security; 5) welfare payments; 6) retirement; 7) other income. The
income variable used in Dr. Murphy’s analysis comes from reported total pre-tax wage and salary income (i.e.
money received as an employee). Sources of income include wages, salaries, commissions, cash bonuses, tips,
and other income received from an employer.

31

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monitored. Another incentive is to not tell the Federal Government anything
that would bring suspicion on the household, which also encourages biased
reporting.
2. The ACS Annual Data Mix Two Years of Information

55.

A further and fatal problem with the ACS data is that each respondent is asked
for income for each adult at the sampled address during the 365 day period
ending the day when the respondent decides to complete the survey (not the
previous month or the current month or the past calendar year). Respondents
are unlikely to know their earnings during these unusual 365 day periods with
accuracy, which contributes to the measurement error. In addition to recall
error, each of these unusual 365 day reporting periods (except the ones ending
on December 31) includes days from two adjacent years. For example, when a
respondent reports income for the year ending on April 1, 2010, the Census
Bureau makes no attempt to apportion the total between the two years to which
the total applies, 2010 and 2009. Instead, the 2010 income figure reported by
Census is an average (or sum) of the numbers collected in the 12 monthly
surveys conducted during 2010. This means that the 2010 income figure is a
mix of 2009 and 2010 data with the greatest emphasis at the beginning of the
2010 year, which is included in the income responses collected in each month
throughout 2010. The Figure 2 below shows the approximate monthly sample
weights, built on the assumption that the January 2010 survey collects data from
February 2009 through January 2010.32 This anomaly occurs throughout all
years of the data.

The triangular shape of this figure is something that Dr. Murphy acknowledges in his deposition.
Deposition of Kevin Murphy Vol. 2, July 5, 2013 at p. 546:8:14.

32

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wages”). This top histogram leans just slightly to the right. If all the
correlations were exactly zero, the standard error would be about 0.378 based
on the approximation: (1/(n-2))1/2 and n = 9. What we have is a mean of 0.18
and a standard error of 0.36, which is compatible with some commonalities, but
not a whole lot. The bottom chart shows the distribution of correlations
weighted by the size of occupation. This chart indicates that most of Dr.
Murphy’s commonality results are driven by a few large occupations.
59.

I contrast these figures with analogous distribution charts constructed using
defendants’ payroll data. Figure 4 shows the distribution of correlations between
Defendants’ title average real compensation growth and real reference
compensation growth. The substantial commonality in the Defendants’ payroll
data is clear. The top histogram leans heavily to the right. The mean correlation
is 0.61 and the standard error is 0.37, which indicates substantial commonality.
The bottom chart which shows the distribution weighted by employee years
indicates that the commonality results are broad and deep. Weighted by
conduct period employee years, the mean correlation is 0.82. The contrast
between the weak correlations in the ACS data and the much stronger
correlations in the Defendant data is further confirmation of the role that
internal equity played in setting compensation levels and the extent to which Dr.
Murphy’s ACS regression analysis is nonsensical.

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Figure 3: Correlations of ACS Occupation Real Wage Growth with ACS Reference
Wage Growth

Distribution of ACS Wage Change Correlations

Share of Occupations (%)

15

10

5

0
-.8

-.7

-.6

-.5

-.4

-3

-2

-.1

0

.1

.2

.3

.4

.5

.6

.7

.8

.9

Source: ACS Data from Murphy Backup

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Figure 4: Correlations of Annual Real Growth of Defendant Title Compensation
with Real Reference Compensation Growth

Distribution of Defendant Compensation Change Correlation
20

Share of Titles (%)

15

10

5

0
-1

-9

-.8

-.7

-.6

-.5

-.4

-.3

-.2

-.1

0

.1

2

.3

.4

.5

.6

.7

8

9

Source: Defendant Employee Data; Correlation Analysis

Distribution of Defendant Compensation Change Correlation
Weighted by Class-Period Employee Years

50

Share of Titles (%)

40

30

20

10

0
-1

-9

-.8

-.7

-.6

-.5

-.4

-.3

-.2

-.1

0

.1

2

.3

.4

.5

.6

.7

8

9

Source: Defendant Employee Data; Correlation Analysis

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C. Other Flaws in the ACS Data for Dr. Murphy’s Analysis

60.

VI.

There are a number of additional problems with the ACS data used in Dr.
Murphy’s analysis. First, ACS does not allow accurate computation of “current
year” dollars. The ACS annual data includes income earned in two adjacent
years at two different price levels.33 Second, the ACS survey does not collect
enough information to determine in which year work occurred when the
individual was not employed in every one of the preceding 52 weeks. Finally,
the mapping of employment information from surveys to occupation categories
(OCC codes) can be an additional source of measurement error. To identify the
individual’s employment category, respondents are asked to answer the question
“What kind of work was this person doing?” The employment responses go
through a process of classification into OCC codes, which is performed by the
clerical staff trained in using the classification system.34 This fuzzy mapping of
respondent answers into occupations is prone to misclassification errors.

Dr. Murphy’s Concerns about Common Effects Excluded from
My Work Are Strictly Hypothetical

61.

Dr. Murphy emphasized that left-out variables can cause problems with
regression analysis, but he has not put forward any specific example of such an
effect. While I controlled for the external and internal non-sharing effects he
claims pollute my results, he has not presented any analysis showing that omitted
non-sharing external or internal effects are responsible for the positive sharing

“The Census Bureau provides a separate variable called ADJUST, which adjusts dollar amounts to the
amount that they would have been had they been earned entirely during the calendar year. Ideally, this
adjustment factor would be unique to each month of data. Consider the example of the 2008 ACS, released in
the fall of 2009 but gathered throughout 2008: people surveyed in January 2008 earned all of their stated
income during 2007 (January 2007 to December 2007), while people surveyed in December earned most of
their stated income during 2008 (December 2007 to November 2008). However, month-specific adjustment
factors would make it easier for individuals to be identified, so the Census Bureau does not provide them.”
Minnesota Population Center, University of Minnesota, “Note on the Standardization of ACS/PRCS Income
Variables and Other Dollar Amount Variables,” https://usa.ipums.org/usa/acsincadj.shtml.
33

U.S. Census Bureau, “ACS Design and Methodology: Data Preparation and Processing for Housing Units
and Group Quarters,” pp 7-8,
http://www.census.gov/acs/www/Downloads/survey_methodology/acs_design_methodology_ch10.pdf,
“Automated coding programs were used for these items for the 2000 Decennial Census, but it was
determined that using trained clerical coders would prove more efficient.”

34

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in my results. He has not elaborated on what his claimed “other common
factors” could be.
62.

One of Dr. Murphy’s innovations to my conduct analysis was his addition of a
stock price variable (namely, the S&P 500 Index) as a common explanatory
factor. He claims to use this variable regularly to check regressions. He also has
said in his deposition that there may be any number of firm success factors that
are not reflected in firm revenue.35 Stock prices provide an indication of the
market’s assessment of a firm’s future success and may contain compensationrelevant information. Thus, as a robustness check, I use each firm’s stock price
data and check whether its addition to the compensation sharing regression
explains away the observed co-movement. It doesn’t.

Deposition of Kevin Murphy Vol. 1, December 3, 2012 at p. 316:11:21; Deposition of Kevin Murphy Vol.
2, July 5, 2013 at p. 485-486.

35

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Figure 5

VII. Conduct Regression

63.

Dr. Murphy expresses his concern that I did not comment on his “more
parsimonious model that included fewer explanatory variables but which still
permitted measurement of separate Defendant-specific conduct effects.”

64.

The conduct regression I presented in my original report differentiates the
conduct effect across years and across defendants by including interactions of
conduct with age, age squared, and the hiring variables. In his ‘parsimonious’
model, Dr. Murphy substitutes these interactions with a single conduct variable
interacted with employer dummies.

65.

This is just a restricted version of my model because, 1) it makes no
differentiation between individuals by eliminating the age interaction, 2) it allows
less employer differentiation by using a single dummy variable, and 3) it does
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not capture business cycle effects as my model does via the hiring variable that
reflects changes in the economic environment. Hence, it appears that Dr.
Murphy’s ‘parsimonious’ model may be a little too restrictive to do justice to the
challenges presented by this data.
66.

I have considered whether to add any variables and I am not aware of any I
need to add at the present time. In my previous report, I discussed the logic
behind my use of basic observable employee characteristics such as age,
company tenure, gender, location, title, and employer along with firm-wide and
economy-wide control variables. I also cited economic literature that uses
similar modeling techniques.36 In my Reply report, I discussed the lack of
sensitivity of my findings to inclusion of alternative external control variables
such as firm stock prices and to a different level of aggregation.37 The work I
have done so far establishes the robustness of my damages model, hence I stand
by my earlier report which demonstrates a method by which class-wide damages
can be computed.

VIII. Almost All Employees Received Supplemental Compensation or
Salary Increases

67.

I was asked to address a claim I understand that Defendants’ expert Dr. Shaw
has made that there may be Class members whose job performance was so poor
they would not have received any increase in pay, regardless of steps the
Defendants would have taken to increase pay in response to increased
competition.38 At her deposition, Dr. Shaw asserts individual managers “were
given guidelines to give zero increases to low performers,” but she says there is
“no way of knowing” how many employees would fall into this category

Leamer Report pp. 53 and 64-65. The adequacy of such variables is echoed by one of Defendants’ experts,
Dr. Shaw, who published an article that used an almost identical set of variables to explain the pattern of
wage variability observed in a survey dataset. See Shaw, Kathryn L., “Wage Variability in the 1970s: Sectoral
Shifts or Cyclical Sensitivity?” The Review of Economics and Statistics, Vol. 71, No. 1 (Feb., 1989), pp. 26-36. Dr.
Shaw builds a regression model that uses individual characteristics such as experience, tenure, marital status,
race and regional dummies etc along with external control variables such as projected employment growth.
36

37
38

Leamer Reply Report pp. 44-45 and 49-54.
Expert Report of Kathryn Shaw, Ph.D., June 21, 2013.
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Figure 6

Percentage of Adobe Technical Class Employees with Base
Compensation within Salary Range

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Figure 7

Percentage of Apple Technical Class Employees with Base
Compensation within Salary Range

Source: 231APPLE004236, 231APPLE007258, 231APPLE008537, 231APPLE008912, 231APPLE011618,
231APPLE100713.

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Figure 8

Percentage of Google Technical Class Employees with Base
Compensation within Salary Range

Source: Google compensation data, GOOG-HIGH TECH-00182929, GOOG-HIGH-TECH-00395420, GOOG-HIGH-TECH00625147, GOOG-HIGH-TECH-00625148.

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Figure 9

Percentage of Intel Technical Class Employees with Base
Compensation within Salary Range

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In re High-Tech Employee Antitrust Litigation

Expert Witness Report of
Kevin F. Hallock

May 10, 2013

May 10, 2013

Expert Witness Report of Kevin F. Hallock

[REDACTED]
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TABLE OF CONTENTS
Page
I.

Qualifications ................................................................................................................................... 1

II.

Assignment and Summary of Conclusions ...................................................................................... 2

III.

Prior Testimony ............................................................................................................................... 4

IV.

Compensation System Design ......................................................................................................... 5

V.

The Defendants Had Formalized Pay Systems .............................................................................. 15

VI.

Issues of Internal Equity ................................................................................................................ 33

VII.

Internal Equity and Pay for Performance Are Not Mutually Exclusive ........................................ 54

VIII.

How Restricting Cold Calling Can Restrict Information and Pay ................................................. 57

IX.

How A Structured Compensation System Can Be Related to Systematic Compensation
Effects ............................................................................................................................................ 60

X.

Examples of How Market Pressure Led to Pay Changes at Defendants........................................ 62

XI.

Agreements of the Kind Described in this Case Could Limit Recruiting and Have
Negative Consequences on Compensation for Employees of Defendant Firms ............................ 66

XII.

Given the Defendants’ Formalized Pay Structures and Compensation Design, Effects on
Compensation Could be Widely Felt ............................................................................................. 69

XIII.

The Technical Class ....................................................................................................................... 70

XIV.

Conclusions .................................................................................................................................... 71

May 10, 2013

Expert Witness Report of Kevin F. Hallock

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1

I.

Qualifications
1.

I am the Donald C. Opatrny ’74 Chair of the Department of Economics, the

Joseph R. Rich ’80 Professor, Professor of Economics and Human Resource Studies and
Director of the Institute for Compensation Studies at Cornell University in Ithaca, NY. I am also
a Research Associate at the National Bureau of Economic Research in Cambridge, MA and a
Distinguished Principal Researcher at The Conference Board in New York, NY. Additionally, I
serve on the Compensation Committee of Guthrie Health in Sayre, PA and on the Board of
Directors of the Society of Certified Professionals at WorldatWork in Scottsdale, AZ. I earned a
B.A. in Economics at the University of Massachusetts at Amherst in 1991 and a Ph.D. in
Economics from Princeton University in 1995. I previously taught at the University of Illinois at
Urbana-Champaign from 1995-2005 and have been at Cornell University since 2005.
2.

My work has covered a variety of fields including compensation design, executive

compensation, the relationship between labor and financial markets, wage differentials and
inequality, the effects of job loss, and labor economics. My work has been published in a variety
of outlets including The American Economic Review, The Journal of Economic Perspectives, the
Journal of Labor Economics, the Journal of Public Economics, the Journal of Corporate
Finance, Labour Economics, the Industrial and Labor Relations Review, Research in Personnel
and Human Resources Management, and Research in Labor Economics. I have edited or coedited a variety of volumes including co-editing Labor Economics (1995) and The Economics of
Executive Compensation (1999). My book regarding compensation, Pay, was published in 2012.
3.

I have served as a referee for over 40 different academic journals, I previously

served as an Associate Editor at the Journal of Labor Economics and at Economics Bulletin and
am currently an Associate Editor at Labour Economics, am on the editorial board of the
Industrial and Labor Relations Review, and am on the advisory boards of the Journal of People
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and Organizational Effectiveness and Compensation and Benefits Review. I have given lectures
at over 30 different Universities. I have taught courses at Cornell on Managing Compensation,
Executive Compensation, Pay, Finance for Human Resources, and Labor Economics. A more
complete description of my qualifications is included in my curriculum vitae in Appendix A.
4.

In connection with this matter, I reviewed and considered materials from this

case, including the consolidated amended complaint, depositions, deposition exhibits, and salary
or market pay range materials produced by or compiled from materials of each defendant.
Information that I considered in forming my opinions include the items listed in Appendix B or
listed in this report and any attached exhibits. The bases for my opinions are described in this
report and any attached exhibits. I reserve the right to supplement this report in view of any new
material or information provided to me after the date of this report.
5.

My compensation for my work in this matter is not contingent upon my findings

or the outcome of this litigation. I am being compensated at my current hourly rate of $750 per
hour.
II.

Assignment and Summary of Conclusions
6.

I understand that plaintiffs are seeking certification of a class of salaried technical,

creative, and research and development employees (the “Class” or “Technical Class”), consisting
of those described in Appendix B to the October 1, 2012 Expert Report of Dr. Edward E.
Leamer, and who worked for a defendant while that defendant participated in at least one “no
cold-call” agreement with another defendant.
7.

I have been asked by counsel for the plaintiffs to:
a.

Analyze defendants’ pay practices to determine whether defendants used
formal administrative pay systems; and

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b.

Determine whether suppressing recruiting of defendants’ workers,
including technical workers, are predicted to have led to the result of
suppressing the pay of their employees, including all or nearly all
members of the Technical Class, including those with different job titles.

8.

As a result of my work to date, the following are among my conclusions.
a.

The defendants had formalized compensation systems. These include
using market surveys, having clear structures, using market pay lines,
grades and many other features of formalized compensation systems.

b.

The defendants made use of the ideas of compensation beyond salary.
These other forms of compensation include components such as bonuses
and stock.

c.

Issues of internal equity and equity in general were important to defendant
firms. Whether they used the terms or not, the concepts of internal equity
and also generally treating similar employees similarly were important to
defendant firms.

d.

Pay moved in defendant firms in systematic and structured ways.

e.

Restrictions on cold-calling clearly had impacts on employees among the
defendant firms. In particular, restrictions on cold-calling hamper
compensation levels for employees. The restrictions could be expected to
hamper levels of compensation for those who would have been cold-called
and for all or nearly all salaried employees of defendant firms.

f.

Agreements such as restrictions on cold-calling could be expected to limit
and have negative consequences on employee compensation for those

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workers directly involved and for nearly all salaried employees. Given the
formalized pay structures and compensation design in defendant firms,
nearly all salaried employees could be expected to have pay that would
otherwise be higher.
g.

The formalized systems in place at the defendants relied on structures,
external data from the market and the like, and notions of equity were
present at defendants. As a result, those effects cycle on to other
employees and their levels of compensation. Therefore, the formal
compensation structures could be expected to lead to an effect on nearly
all class members.

h.

Although I have not been asked to estimate the magnitude of damages in
this case, based on my knowledge of compensations systems and the
materials considered, I believe that agreements against cold calling, such
as the agreements at issue in this case, are predicted to suppress the
compensation of all or nearly all members of plaintiffs’ proposed
Technical Employee Class, including those with different job titles.

III.

Prior Testimony
9.

I have testified at a deposition twice and have not testified at a trial. During the

previous four years, I have testified as an expert at a deposition in the following case: William
Hale Hubbell vs. G.J. Ratcliffe, Richard W. Davies, Andrew NcNally IV., individually and as
trustees. I have never before testified as an expert in a class action lawsuit.

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IV.

Compensation System Design
10.

Many firms use administrative pay systems.1 These systems typically include

standardized features, such as job analysis, job evaluation, use of market surveys and external
market data, market pay lines and salary bands and zones or grades and ranges. This section
briefly outlines the features of these systems.
11.

It is noteworthy that an important feature of these systems is that often the internal

structure is set in advance of using external compensation information. When setting up these
systems the internal structure is set and then external data is then matched to the internal
structure to set pay levels.
12.

Many organizations have a business strategy that is then linked with a

compensation strategy and philosophy. Organizations often start with their own compensation
strategy, which of course can evolve over time, before setting up the more technical features of
the pay system.
13.

Job analysis is the “systematic process of collecting information that identifies

similarities and differences in the work”.2 Harvey (1991) notes two important features of job
analysis. First, job analysis should describe observable characteristics of jobs. Second,
individual people in those jobs should be kept separate from the job analysis. To be sure,
individual differences matter in compensation design but are not used at this point in the
evolution of a compensation system.
14.

Job analysis can become very specific and detailed. In fact, Martocchio (2004)

points out very specific details of job elements in job analysis such as element, task, position,

1
2

See, for example, Milkovich, Newman and Gerhart (2011, 2014), Martocchio (2004), or Hallock (2012).
Milkovich, Newman and Gerhart (2011), p. 97.

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job, job family, and occupation.3 This begins with an “element,” which could be as simple as
putting a piece of paper in a scanner to scan a document all the way up to a “job family”. The
rest of the list from Martocchio (2004) just aggregates to higher and higher levels. A “Task” is
the next up from an element. A position is a group of tasks that make up the activities that a
specific employee might perform. For example a junior administrative assistant might make
flight reservations, distribute mail, answer phones and perform related activities. A job may be
reflected in a set of positions. For example, there might be many different junior administrative
assistants all doing a very similar job. The job family is the next level up.4 A job family might
be administrative jobs, or technical jobs, or marketing jobs. Different organizations may do this
differently. Overall structure is what is important.
15.

An additional step in performing a job analysis involves collecting information on

job content (e.g. tasks, activities, work demands), characteristics of employees who hold these
sorts of jobs (e.g. technical skills, manual dexterity, leadership), internal relationships (e.g.
supervisors, peers), and external relationships (e.g. regulators, customers, suppliers).5 Henderson
(2006) describes a series of examples of questionnaires that are used by firms to collect this kind
of information in their organizations. O*NET6 --a revision of the U.S. Department of Labor
Dictionary of Occupational Titles--is an example of these systems. O*NET has extraordinary
detail of the characteristics of hundreds of jobs but includes a set of overarching descriptors:
knowledge, skills, abilities, work activities, interests, work content, and work values.
16.

Job evaluation in the next step in setting up a pay system using a job-based

structure as described here. Job evaluation “is the process of systematically determining the

3

Martocchio (2004), page 198.
Hallock (2012), page 63-64.
5
Milkovich, Newman and Gerhart (2011), Hallock (2012) and others discuss these issues.
6
See http://online.ontcenter.org.
4

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relative worth of jobs to create a job structure for the organization. The evaluation is based on a
combination of job content, skills required, value to the organization, organizational culture, and
the external market. This potential to blend organizational forces and external market forces is
both a strength and a challenge of job evaluation”.7
17.

Companies sometimes use formulaic approaches to identify relative differences in

their jobs before benchmarking them to external data. One approach to this is sometimes called
the “point method,” in which each job in the organization is assigned a set of “points” as I will
describe further below. For example, suppose that the Engineer I job is assigned8 530 points, the
Engineer II job is assigned 640 points and the Senior Engineer job is assigned 935 points. This
necessarily suggests that the Engineer II job contributes less than the Senior Engineer job but
more than the Engineer I job. It is important to note that the points don’t necessarily ultimately
result in a linear scale in terms of pay.
18.

Obviously there are many ways to order or rank jobs. One example of a

formalized system is that used in classification of U.S. Government jobs as displayed in Figure
1.9
19.

The point system has many important features, including compensable factors,

scaling, weighting, and degrees. Benchmark jobs are important since they are jobs that will
ultimately be used to match the internal structure that is now being discussed with the external
market. Benchmark jobs are typically jobs that are relatively well-known and are common so
that information can be collected about them internally and externally. However, even in the
absence of perfect benchmark jobs, these systems can operate.
7

Milkovich, Newman and Gerhart (2011), pp 129-130.
I describe where these points in this hypothetical example come from below. More detail can be seen in Chapter 6
of Hallock (2012).
9
Source: United States Office of Personnel Management: http://www.opm.gov/oca/11tables/pdf/DCB.pdf See
Hallock (2012), p 69.
8

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20.

In developing a point system, the next step is to identify “compensable factors,”

i.e., the factors for which the company sees value. These might include, for example: technical
ability, leadership, responsibility, communications, and working conditions.10 The idea is that
more of each factor should be linked to more productivity and (ultimately) higher pay. Note,
however, that we still aren’t yet focused on pay levels – just on differentiating jobs. Also note
that one of the factors, working conditions, is unique in that poorer conditions may lead to higher
pay as a compensating differential.11 Working conditions, per se, are not necessarily a positive
attribute of work but they are a factor that may need to be compensated.
21.

Once each compensable factor for a job is defined, a set of degrees for each factor

is created. There does not have to be a common set of degrees for each factor. Martocchio
(2004) includes examples of degrees for the compensable factor he defines as writing ability.
These range from degree one that includes “simple phrases and sentences” up to degree five that
includes “manuals and speeches”.12 It is important to note that the degrees need not be evenly or
linearly spaced. For example, one could set aside 100 points for writing ability and have five
degrees of writing ability. One could assign a job with writing ability as follows: writing ability
“one” gets 20 points, writing ability “two” gets 40 points, “three” gets 60 points, “four” gets 80
points, right up to writing ability “five” at 100 points. But this does not have to increase in lockstep. As an alternative, one could assign writing ability “one” 40 points, writing ability “two” 80
points, writing ability “three” 90 points, writing ability “four” 95 points and writing ability “five”
100 points, of course depending on how the each level of writing ability is defined.

10

These are precisely the five compensable factors I use in Chapter 6 of Hallock (2012).
See Rosen (1986).
12
Martocchio (2004), page 219.
11

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22.

The next step is to define the weight of each factor. For example, in the

hypothetical example I created with five compensable factors, let’s define technical ability 50%,
leadership 20%, responsibility 15%, communications 10% and working conditions 5%.
23.

Next suppose that the firm defines that the maximum number of points any job

can get is 1000. This is an entirely arbitrary number. It could be any number but this is a nice
round number and makes the discussion easier to understand.
24.

So, we have defined that there are 1000 total possible points. We have also

created our weights so that means there are 500 possible points for technical ability (50% of
1000), 200 possible points for leadership (20% of 1000), 150 possible points for responsibility,
100 possible points for communication and 50 possible points for working conditions. In Figure
2, I have included a sample worksheet for assigning points to jobs.
25.

The worksheet in Figure 2 could be used, for example, for all jobs within a

particular “job family”. Consider the Engineer I, Engineer II and Senior Engineer jobs
mentioned previously. This worksheet could be filled out for any of those jobs and any other
jobs in the “engineering” job family.
26.

In Figure 3, the worksheet is filled out for a hypothetical Engineer II job which

has degree 4 technical ability (worth 400 points), degree 2 leadership ability (worth 80 points),
degree 3 responsibility (worth 90 points), degree 3 communications ability (worth 60 points) and
degree 1 for working conditions (worth 10 points). The sum of these is 640 points. To show a
concrete, related example, Pixar has an “Engineering Job Matrix” where it lists “knowledge,”
“job complexity,” “supervision & collaboration” and “experience”. They then list six levels of
each.13

13

Engineering Job Matrix, Pixar, PIX00049042, exhibit 1305.

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27.

This differentiation process is then repeated for all jobs in the job family, and in

all job families. In the hypothetical example in Figure 4, 530 points were assigned for the
Engineer I job, 640 for the Engineer II job and 935 for the Senior Engineer job. In Figure 5, I
have added two other job families (the Attorney job family and the Administrative job family)
and three jobs to slightly increase the complexity of this example. The Attorney and
Administrative job families could have had the same compensable factors, scales and weights as
the Engineer job family, but that is not necessarily so in this hypothetical example.
28.

Note that Figure 5 shows a relative ranking (or number of job evaluation points)

for many different jobs. This is done entirely internally to the organization. No external data
was used and no information on compensation of any kind was used in creating this.
29.

A next step in a formal pay system is to match the set internal structure to external

market data. This is something that defendants in this case have done for many years. Finding
the right market data and the appropriate survey is described in the literature, including Cardinal
and Florin (2012). Benchmark jobs are important since they are jobs that will ultimately be used
to match the internal structure that has been identified (using all or many of the features
discussed above) with the external market. Benchmark jobs are typically jobs that are relatively
well-known and are common so that information can be collected about them internally and
externally. However, even in the absence of perfect benchmark jobs, formal pay systems can
operate.
30.

Internal comparisons among workers are clearly important to workers and to

organizations. This is the case both when organizations are organizing their structures and when
making individual pay decisions. Organizations are also concerned with individual pay

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comparisons, pay and equity and internal equity as confirmed in this case at each defendant
organization, documented below.
31.

Internal comparisons are also studied by academics from different disciplines.

These include a set of studies on fairness (Levine, 1993), and pay secrecy (Milkovich and
Anderson, 1972, Lawler, 1967, Card, Mas, Moretti and Saez, 2012).
32.

A next step in a formal pay system is to match the set internal structure to external

market data. Finding the right market data and the appropriate survey is not a simple task. More
information on that can be found in a variety of sources, including Cardinal and Florin (2012).
33.

Suppose that we have five internal jobs in a particular job family and that they

have different levels of job evaluation points assigned to them. Call the five jobs Associate 1,
Associate 2, Associate 3, Associate 4, and Associate 5. Further assume these five jobs have been
assigned the following job evaluation points internally: 185, 200, 335, 400 and 460,
respectively.
34.

Further assume that the external data include information from a set of employers

on each of the five jobs: Associate 1 – Associate 5. In this case (as in most cases) not all
external organizations that have provided information to the survey consultant are paying each of
the jobs equally. There is dispersion of compensation for each job. Figure 6 is an example that
illustrates how this would look in practice. Note that the external firms all pay jobs in the
Associate 2 position quite similarly, while there is a great deal of dispersion in how external
competitors pay the Associate 4 and 5 jobs.14

14

Note, for example, the testimony of Intuit’s Senior Vice President, Chief of Human Resources, Sherry Whiteley:
Deposition of Ms. Sherry Whiteley, March 14,

2013, page 97.

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35.

After the external market data are overlaid on the internal structure, a “market pay

line” can be created. This can be done in a number of ways. One way, and the one I use in this
example, is to create the “line of best fit” as I have done in Figure 6. In this case, the line is
simply the “ordinary least squares regression line”. It is the line that minimizes the sum of the
squared distances from each point and the line. This shows how the company, given its strategy,
compensable factors, scales, weights, etc., pays, given internal and external market forces.
Individual companies can always pay more or less, depending on their circumstances and
interests. The ordinary least squares regression line15 that comes from Figure 6 is -39,651.77 +
556.93*(Job Evaluation Points).
36.

The market pay line is effectively showing, given the external market, how this

company will pay at a point for a given job. Take, for example, the Associate 2 job in Figure 6.
That job was assigned 200 job evaluation points. So to find the level of pay for an Associate 2 in
the firm, after taking into account the internal structure and the external market data, one would
pay $71,734.43 = -39,651.77 + 556.93*(200). The typical payment for the other jobs can be
found similarly. A useful feature of this system is that jobs that are not included as benchmark
jobs, jobs that are unique to the firm, or jobs that are created after the system is set up can also be
priced using the equation. Say, for example, a job unique to the firm is developed and the
company goes through the job evaluation and job analysis process and finds it is worth 300 job
evaluation points. Even though there is no external market data on that job, a price can be
created for it. It is -39,651.77 + 556.93*(300) = $127,427.53.16

15

See page 80 in Hallock (2012).
Note the explicit reference to a “Pay Line” in powerpoint on pay design, LUCAS 00188717, exhibit 715.10 and
reference at Intel to “pay lines” in powerpoint called FY11 Preliminary Pay lines development update, May 5, 2010,
76582DOC000004_000004, exhibit 399.4. See also references to “pay line” in 2008 Focal Development Process
Overview, 76582DOC000348, page 4 (Intel).
16

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37.

Even in a formal pay structure, it is likely that not all people doing the same job

within a firm are all paid the same salary. There are a wide variety of reasons for this. This is
why, in a final stage, firms create bands and zones or grades and ranges or other systems to
essentially put “boxes” around each type of job.17 A clear example of this is the system for some
Technical Jobs at Google in 2004.18
38.

Figure 7 displays the information as of January 13, 2004 for Google Technical

workers in job grades 1 – 9.19 The figure has features that are consistent with models taught in
compensation textbooks such as Milkovich, Newman and Gerhart (2011),20

.21
39.

Many organizations use various versions of what I have outlined in this section.

40.

So far I have been focused on salaries. Wage and salary income is an important

large part of labor compensation, as I will show below. But there are other components in total
compensation, including bonuses, stock, stock options and other pay.
41.

There is evidence that total compensation is correlated with salary. For example,

17

See Milkovich, Newman and Gerhart (2011), page 265.
See spreadsheet GOOG-HIGH-TECH-00221513.xlsx, tab “Employee Data”.
19
Created from data in spreadsheet GOOG-HIGH-TECH-00221513.xxsx, tab “Employee Data”.
20
See, for example, page 265 of Milkovich, Newman and Gerhart (2011) in Exhibit 8.17.
21
Note, however, the horizontal axis for each job grade has some width so it is a “box” with a top and a bottom. But
it can be characterized as a vertical line with no width, as in many subsequent figures.
18

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.22 Elsewhere I will show the higher the job level the higher the salary in multiple
organizations. Figure 8 is one example of a link between salary and equity.
42.
spreadsheet,

An additional example of the link comes from an Apple Spreadsheet.23 In this
. With respect to this sheet, Apple Senior Director of

Compensation Steve Burmeister was asked, “…
”.24 In Figure 9, I plot
information from this sheet25 and use only three columns of the data:

. In Figure 9, I have plotted three panels. In the first, it is clear that

. To create the panel in the top right of the
figure, I first calculated a new variable which is the “nonbase” cash which I defined as (total
cash) minus base. The top right panel plots this ratio against total cash compensation. Clearly a
. In the bottom
left panel, I plot the bonus percentage against the base salary for
.
43.

I should note that there is substantial evidence in general, that stock (stock, stock

options etc.) as a fraction of total compensation is correlated with job level and salary.26
44.

There can be important credential effects to certain phenomena in labor markets,

such as being associated with a college degree or being associated with well-known
22

Powerpoint, Apple Inc., Compensation Committee, Apple, August 5, 2009, 231APPLE10067, exhibit 1854.5.
Excel spreadsheet, Apple Computer, Inc., 2006 Compensation Analysis, APPLE 231APPLE098912, exhibit
1858.2.
24
Deposition of Mr. Steven Burmeister, Apple, March 15, 2013, page 112.
25
Excel spreadsheet, Apple Computer, Inc., 2006 Compensation Analysis, APPLE 231APPLE098912, exhibit
1858.2.
26
See, for example, Hallock (2012), page 92, for an example of the link between CEO cash compensation and CEO
total compensation (including equity).
23

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organizations. There is a large literature in economics on the economic returns to education (e.g.
Card, 1999, 2001). There is also a literature on estimating the difference between productivity
and the signaling effect of education on earnings (e.g., Spence, 1973, Hungerford and Solon,
1987 and Weiss, 1995). For example, do those with high levels of education have higher
earnings because they learned more in school and are, therefore, more productive workers, or is
the credential of the educational institution a signal to employers of their high ability or work
ethic? Just as there could be signaling and productivity effects of education on earnings, there
too could be productivity and signaling effects of the employer brand on earnings and future
earnings. For example, working for a high-profile or well-known employer, including any of the
seven defendants, could have positive benefits to an employee including monetary and nonmonetary compensation in the future.
V.

The Defendants Had Formalized Pay Systems
45.

There is evidence in the testimony and documents I reviewed in this case that the

defendants each had formalized or sophisticated human resource (HR) or compensation systems
of one type or another. The systems are may not contain all features of the example I outlined
above but they are certainly formalized compensation systems, as evidenced, for example, by
their use of jobs, job families/grades, salaries or market ranges, and benchmark data.
46.

Adobe: There is evidence that Adobe had formalized compensation systems.

Included among the evidence that Adobe had formal structures is data Adobe produced to
plaintiffs.27 That information shows that Adobe had many job families, many grades within job

27

See spreadsheet “Employee Type Count by Employer”.

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families and many job titles within grades. Additional data include a variety of compensation
structure features including salary min, mid and max information.28
47.

Additional evidence that Adobe had formalized pay systems is contained in the

deposition of Ms. Donna Morris, Vice President of Global Human Resources until March 2007,
when she became Senior Vice President of Global Human Resources. Ms. Morris noted with
respect to salary ranges

29

48.

Ms. Morris also testified,
30

49.

Ms. Morris similarly affirms in her declaration, “The target [salary] midpoint has

changed over the years and varied across job functions. For example, the 2005 target midpoint
for various jobs in set forth in Exhibit 1 (ADOBE_015864), which is a true and correct copy of
Adobe’s 2005 Performance, Salary & Stock Focal. The maximum and minimum of the salary
range was then calculated by applying a spread, which also varied over the years and across job
levels. The spread varied between 50% and 70% for different job levels during the class
period”.31
50.

Additional evidence that Adobe had formalized compensation and HR systems

comes from the deposition of Ms. Rosemary Arriada-Keiper, who served as Adobe’s Manager of
28

Spreadsheet, “Adobe_Salary Ranges” (2002-2006); “ADOBE_DATA_000043_SalaryRanges_FY2008” (2008);
“ADOBE_DATA_000044_SalaryRanges_FY2009” (2009); “ADOBE_DATA_000045_SalaryRanges_FY2010”
(2010).
29
Deposition of Ms. Donna Morris, Adobe, August 21, 2012, page 154.
30
Deposition of Ms. Donna Morris, Adobe, August 21, 2012, page 155.
31
Declaration of Ms. Donna Morris of Adobe, September 13, 2011, exhibit 416.7.

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Global Compensation, and was asked

”32
51.

As an example of the structure at Adobe, Ms. Arriada-Keiper mentioned her own

career progression in the company. She said “So no, it was – analyst, senior analyst, program
manager, career level manager, senior level manager, director. So just moving up in levels right?
We have lots of levels at Adobe”.33
52.

Additional evidence that Adobe had formalized compensation and HR systems

was in reference to the “salary planning tool”. Ms. Arriada Keiper was asked “…can you tell me
how the salary planning tool has worked?”34 She replied, “Yeah. So essentially the salary
planning tool is populated with employee information for a particular manager, so the employees
on their team. You have the ability to kind of look at their current compensation. It shows them
what the range is for the current role that they’re in … The tool also has the ability to provide
kind of the guidelines that we recommend in terms of how managers might want to think about
their specific allocated budget”.35

32

Deposition of Ms. Rosemary Arriada-Keiper, Adobe, March 28, 2013, page 24.
Deposition of Ms. Rosemary Arriada-Keiper, Adobe, March 28, 2013, page 31.
34
Deposition of Ms. Rosemary Arriada-Keiper, Adobe, March 28, 2013, page 82.
35
Deposition of Ms. Rosemary Arriada-Keiper, Adobe, March 28, 2013, pages 82-3.
33

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53.

Additional evidence that Adobe had formalized HR and compensation systems is

from the deposition of Mr. Jeffrey Vijungco, Adobe’s Director of Talent Acquisition, who was
asked, “Well, was – in determining base compensation, were the – were ranges of base
compensation established for particular job levels of job titles?” He answered, “There is, you
know, levels and ranges for every single job at Adobe”.36
54.

Additional evidence of formalized systems at Adobe is from the deposition of

Mr. Bruce Chizen, Adobe’s President and CEO from 2000 to 2007, who noted, “For every
position, we would have a salary range. So depending on a person’s individual experience, their
role and responsibility, the job would pay externally between X and Y according to the data we
had, and we said philosophically we wanted to pay within the X percent and Y percent of that
range”. He went on to say, “And I wanted to make sure we were staying within that relative
philosophy. There were always exceptions. Acquisitions, people who had incredible talent and
were really providing a bigger role than their title did, so there were always exceptions. But for
the most part, I took responsibility philosophically to comply with what I believed to be the right
thing to do”.37
55.

Adobe also used external market data. Mr. Chizen testified that salary ranges

were informed by market data. “We – we relied heavily on external data. So it – I don’t – I
don’t know which ones, but Radford would be an example of that, the Radford data”.38
56.

There is also evidence that Adobe focused on particular markets for benchmarks.

For example, Mr. Chizen was asked if there were particular markets that Adobe used as
benchmarks or guidelines for setting salary ranges. He responded affirmatively, explaining, “I

36

Deposition of Mr. Jeffrey Vijungco, Adobe, October 5, 2012, page 29.
Deposition of Mr. Bruce Chizen, Adobe, March 15, 2013, page 96.
38
Deposition of Mr. Bruce Chizen, Adobe, March 15, 2013, page 97.
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don’t know specifics, but they tended to be software, high-tech, those that were geographically
similar to wherever the position existed”.39
57.

Adobe also used market surveys, gathered by Adobe’s “Total Rewards

organization”.40
58.

Additional evidence that Adobe had formalized HR and compensation systems

comes from evidence of their systems of “ranking” employees as “High Performer,” “Solid
Contributor,” and “Low Performer”.41
59.

Adobe also had a salary range website for managers. Ms. Arriada-Keiper

testified, “So a salary range website is a tool that we have available to managers whereby they
can look at a salary range for an associate job”.42
60.

Apple: There is evidence that Apple had formalized compensation systems.43

Additional data include a variety of compensation structure features including
.44
61.

Additional evidence that Apple had formalized HR and compensation systems

comes from a document that lists

in Figure 10.45 These are shown in the form of

39

Deposition of Mr. Bruce Chizen, Adobe, March 15, 2013, page 98.
Deposition of Mr. Jeffrey Vijungco, Adobe, October 5, 2012, page 31.
41
Powerpoint, Adobe, Q1 Workforce Metrics, As of 4 March 2005, Adobe, ADOBE_000622, exhibit 210.12.
42
Deposition of Ms. Rosemary Arriada-Keiper, Adobe, March 28, 2013, pages 159-60.
43
See spreadsheet “Employee Type Count by Employer”. “FY07 U.S. Base Pay Salary Structures,”
231APPLE007258-59 (2007); Spreadsheet, “Apple Titles and Grades” and Spreadsheet, “Apple Titles and Grades
by Year”.
44
See, for example, Base Salary Structures, Apple, Effective July 15, 2008, 231APPLE009282, exhibit 268.5.
45
Base Salary Structures, Apple, Effective July 15, 2008, 231APPLE009282, exhibit 268.5.
40

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graphs in Figure 11.

.46
62.

Additional evidence that Apple had formalized compensation and HR systems

comes from the deposition of Mr. Mark Bentley, Apple’s Senior Director of Recruiting, who was
asked, “From time to time, did Apple raise the compensation for a particular job category or job
level? He replied “I believe that would be taken – I believe if and when that was done, it was
done on an annual basis during compensation planning”.47
63.

Mr. Bentley also described the merit process at Apple which is evidence of a

formal HR and compensation system. He said, “The merit process is, I think, similar to many
companies.
48

64.

Additional evidence of a formal salary and HR system at Apple is from Senior

Director of Compensation Steven Burmeister’s deposition. He testified, “My group is

46

Base Salary Structures, Apple, Effective July 15, 2008, 231APPLE009282, exhibit 268.5.
Deposition of Mr. Mark Bentley, Apple, August 23, 2012, page 252.
48
Deposition of Mr. Mark Bentley, Apple, August 23, 2012, page 262-3.
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responsible for the job structure, the salary range structure, bonus plan design, and equity plan
design and administration for Apple.49
65.

Mr. Burmeister also noted, “compensation budgets are three main compensation

components: base salary, bonus, and stock. And we set the overall compensation budget for
these three compensation elements and then provide them to the line of businesses, which then
allocate them as appropriate to each of their employees based on performance and
contribution”.50
66.

Google: There is evidence that Google had formalized compensation systems.

That information includes the fact that Google has job families, levels, and grades.51 For
example, note again Figure 7 which was created from a Google spreadsheet and additional data
include a variety of compensation structure features
.52 This spreadsheet documented nine job grades. For each job
grade
.
Google Director of Compensation Frank Wagner testified that he could locate the target salary
for jobs at Google through an internal company website. He was asked, “And if you wanted to
identify what the target salary would be for a certain job within a certain grade, could you go

49

Deposition of Mr. Steven Burmeister, Apple, March 15, 2013, page 18.
Deposition of Mr. Steven Burmeister, Apple, March 15, 2013, page 50.
51
Spreadsheet: “Google Census Data, 9-Grade Structure,” GOOG-HIGH-TECH-00625160 and GOOG-HIGHTECH-00625200 (2003); Spreadsheet: “Google 2004 Salary Ranges,” Exhibit 1600; Spreadsheet: “2005 Global
Salary Ranges,” GOOG-HIGH-TECH-00625148; Spreadsheet: “Salary Guidelines,” GOOG-HIGH-TECH00625147 (2006); and Spreadsheet: Market Reference Points, GOOG-HIGH-TECH-00182929 (2007-2012).
Regarding the final spreadsheet covering the years 2007 through 2012, Mr. Frank Wagner verified that
Deposition of Mr. Frank Wagner, Google,
March 7, 2013, pages 56-59.
52
See spreadsheet GOOG-HIGH-TECH-00221513.xlsx, tab “Employee Data.”
50

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online or go to some place in your office and pull up what that was for that job family and that
grade?”53 He answered “Could I do it?...Yes”.54
67.

Additional evidence that Google had formalized structures is in data Google

produced to plaintiffs.55
.
68.

Google former Senior Vice President of People Operations (HR) Shona Brown

also confirmed
. She was asked “
she replied

.56
69.

Google former Senior Vice President of Engineering Alan Eustace confirmed

Google’s formalized pay systems in his deposition,

57

70.

Intel: There is evidence that Intel had formalized compensation systems.

Included among this is evidence that Intel had formal structures in data provided by Intel to

53

Deposition of Mr. Frank Wagner, March 7, 2013, page 57.
Deposition of Mr. Frank Wagner, March 7, 2013, page 58.
55
See spreadsheet “Employee Type Count by Employer”.
56
Deposition of Dr. Shona Brown, January 30, 2013, page 253.
57
Deposition of Mr. Alan Eustace, February 2013, page 132.
54

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58

That information shows that Intel had many job families, many grades within job

families and many job titles within grades. Additional data include a variety of compensation
structure features including salary min, mid and max information.59
71.

Additional evidence that Intel had formalized pay systems comes from a

document called “Compensation 201 Instructor Guide” which includes terms such as
60

72.

Additional evidence that Intel had formalized HR and compensation systems

comes from a document called “Intel Base Pay Comparison Report” which includes mentions of

61

73.

Additional evidence that Intel had formalized pay systems comes from the

deposition of Ms. Patricia Murray, Intel’s former Vice President of Human Resources (19962012). She was asked, “Okay. Can you describe for me the general annual process that was
used to set compensation?”62

58

See spreadsheet “Employee Type Count by Employer”.
Spreadsheet, “SAL_ADMIN_PLAN,” 76586DOC001450 (2004 – 2011); Spreadsheet, “Intel Job Titles and
Grades”.
60
Compensation 201 Instructor Guide, Intel, 76583DOC007693, exhibit 2030, page 65.
61
Powerpoint, Intel Base Pay Comparison Report, Support Overview, WW04 2011, 765825DOC001211, exhibit
400, page 31.
62
Deposition of Ms. Patricia Murray, Intel, February 14, 2013, page 15.
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63

74.

There is additional evidence that Intel had formalized HR systems. Intel Senior

Vice President of Human Resources Deborah Conrad testified, “Yes, we have a compensation
structure”. She explained,

.64
75.

Ms. Conrad noted that

.65
76.

Additional evidence that Intel had formalized compensation and HR systems
66

includes reference to

67

, reference to four types of
68

77.

, reference to a list of

69

Additional evidence that Intel had formalized pay systems comes from the

deposition of Technology Development Manager Mr. Randall Goodwin who was asked,

63

Deposition of Ms. Patricia Murray, Intel, February 14, 2013, pages 15-16.
Deposition of Ms. Deborah Conrad, Intel, November 21, 2012, pages 23-4.
65
Deposition of Ms. Deborah Conrad, Intel, November 21, 2012, page 34.
66
Powerpoint, FSM Pre-Focal Analysis 2007, Intel, January 2007, 76583DOC002007, exhibit 393.13.
67
Powerpoint, FSM Pre-Focal Analysis 2007, Intel, January 2007, 76583DOC002007, exhibit 393.16.
68
Powerpoint, FSM Pre-Focal Analysis 2007, Intel, January 2007, 76583DOC002007, exhibit 393.28.
69
Powerpoint, FSM Pre-Focal Analysis 2007, Intel, January 2007, 76583DOC002007, exhibit 393.19.
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70

He replied,

.71
78.

Additional evidence that Intel had formalized compensation and HR systems

came from the deposition of Compensation and Benefits Specialist Daniel McKell. Mr. McKell
was asked “Can you list all of the different ratings that Intel uses?” He replied

.72
79.

There is additional evidence that Intel has formalized systems. Mr. McKell was

asked “What are the job ranges that Intel currently has?” He answered
. He was then asked

Shortly

thereafter he was asked “can you give me an estimate” of the number of job grades? He replied
73

80.
74

81.

There is also evidence that Intel referred to job families in their structure.

Mr. McKell noted,
75

82.

Mr. McKell described internal benchmarking:

70

Deposition of Mr. Randall Goodwin, Intel, March 15, 2013, page 51.
Deposition of Mr. Randall Goodwin, Intel, March 15, 2013, page 52.
72
Deposition of Mr. Daniel McKell, Intel, March 20, 2013, page 47.
73
Deposition of Mr. Daniel McKell, Intel, March 20, 2013, page 49.
74
Deposition of Mr. Daniel McKell, Intel, March 20, 2013, page 56.
75
Deposition of Mr. Daniel McKell, Intel, March 20, 2013, page 73.
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76

83.

There is additional evidence of formalized pay and HR systems at Intel.

Mr. McKell was asked “Since you have been involved in compensation, have you received from
time to time reports “showing whether Intel’s job codes are being paid relative to the midpoint of
”77 Mr. McKell also noted,

the pay line?” He replied

.78 He was then asked,
He answered
84.

.79

Mr. McKell affirmed at his deposition the statement in his declaration80 that Intel

.81 Soon after Mr. McKell was asked, “Does Intel calculate a market rate for each
of these job combinations?” He replied,

82

85.

Intuit: There is evidence that Intuit had formalized compensation systems.

Included among this is evidence such as salary low, mid and high information, job codes, and

76

Deposition of Mr. Daniel McKell, Intel, March 20, 2013, page 87-8.
Deposition of Mr. Daniel McKell, Intel, March 20, 2013, page 90.
78
Deposition of Mr. Daniel McKell, Intel, March 20, 2013, page 91.
79
Deposition of Mr. Daniel McKell, Intel, March 20, 2013, page 92.
80
Declaration of Mr. Danny McKell, Intel, September 13, 2011.
81
Deposition of Mr. Daniel McKell, Intel, March 20, 2013, page 154.
82
Deposition of Mr. Daniel McKell, Intel, March 20, 2013, page 155.
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percentiles.83 That information shows that Intuit had many job families and many job titles
within job families and other features of formal systems.
86.

Additional evidence that Intuit had formalized HR and compensation systems is

contained on one of the documents that notes a list of codes including

84

When Intuit Director of Talent Acquisition Chris Galy was asked about these codes,
85

87.

Intuit also indicated other evidence of formal pay structures. Vice President of

Human Resources Mason Stubblefield described his responsibility regarding base compensation
work. “So I’d say it’s fairly broad from a base compensation perspective. It’s something we
think of as job architecture. So the job codes that we use, the job titles that we use, the structure
behind that job system that we have really around job codes, job families. And so helping
structure that, set that up. The connections from that into the market data and how we provide
market reference data to the organization to assist with making compensation decisions; the
extension of that into the annual talent and pay process, the merit decisions, performance
decisions and managing that process across the company”.86

.87 In addition, he noted,

83

Spreadsheet: “Market Data,” INTUIT_031024 (2009), INTUIT_048148_2005.
Powerpoint, FY ’09 New Hire Equity Guidelines, Intuit, INTUIT_039756, exhibit 2140.4.
85
Deposition of Mr. Chris Galy, Intuit, March 20, 2013, page 193.
86
Deposition of Mr. Mason Stubblefield, Intuit, March 29, 2013, pages 20-1.
87
Deposition of Mr. Mason Stubblefiled, Intuit, March 29, 2013, page 25.
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88

88.

Intuit also has formal bands by which jobs are categorized. These include five

groups:
89

Related to that, Mr. Stubblefield noted, “Intuit uses the idea

of development bands to help from a learning and development perspective. There are five
bands inside the company … each job that we have fits into a band, and so this is just trying to
display how, as you move up in the organization or move through different levels of jobs, the –
that does move through our band structure, and also kind of the expectation of the scope …”.90
89.

Lucasfilm: There is evidence that Lucasfilm had formalized compensation

systems. Included among this is data provided by Lucasfilm to plaintiffs.91 That information
shows that Lucasfilm had a variety of compensation structure features including salary min, mid
and max information, grades and job titles.
90.

Former Senior Director of Human Resources Ms. Sharon Coker testified that

Lucasfilm had a salary structure.92 “We had – yes, we had identified levels of positions within
our salary structure all the way through nonexempt up to the executive level”. She confirmed
they were maintained in written form, stating, “They were maintained, yes, in a database”.93
91.

Ms. Coker also confirmed Lucasfilm’s use of noted job families: “… So

production family can start with a production assistant, which is the entry-level position, and

88

Deposition of Mr. Mason Stubblefiled, Intuit, March 29, 2013, page 70.
Powerpoint, Leveraging Compensation and Performance, Intuit, January 7, 2005, exhibit 1761.19.
90
Deposition of Mr. Mason Stubblefiled, Intuit, March 29, 2013, page 87.
91
Spreadsheet LUCAS00221117 (2007 – 2012).
92
Deposition of Ms. Sharon Coker, Lucasfilm, November 1, 2012, page 242.
93
Deposition of Ms. Sharon Coker, Lucasfilm, November 1, 2012, page 242.
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work all the way up to an executive producer. And that would be what I would call a job family.
So it’s the production job family”.94
92.

She testified that salary ranges were related to: “…It was almost like an

intersection, if you picture the grid. So within a family of jobs, like if you were to look at like
technical positions or if you were to look at the production family, I’ll stay with that for a
moment, there’s a hierarchy, if you will, of complexity of roles within a family, and that might
be the horizontal part of the grid. The vertical part of the grid would be, you know, how do you
level those positions with – across the board, to compare them to people in different job
families”.95
93.

There is additional evidence that Lucasfilm had formalized HR and compensation

systems. For example, an internal presentation noted “job families,” “levels or bands,” “job title
structure,” and “slot incumbents into the framework”.96
94.

Additional evidence of formalized compensation or HR systems include the

document reference: “Benchmarking: Lucasfilm will benchmark total cash compensation at
for most positions, using compensation surveys that are relevant to the specific
job or job family. Positions that are defined as highly competitive and/or highly critical to
achieving business objectives such as all studio and technical positions are to be benchmarked at
97

95.

Additional evidence for formalized systems for compensation and HR at

Lucasfilm include a series of competencies and scales. For example, for the function
“ADMINISTRATION/PRODUCTION/DIG TECHNOLOGIES” the following levels are listed,
94

Deposition of Ms. Sharon Coker, Lucasfilm, November 1, 2012, page 249.
Deposition of Ms. Sharon Coker, Lucasfilm, November 1, 2012, page 250-1.
96
Powerpoint, Global Compensation Project, Lucasfilm Ltd., September 22, 2005, exhibit 944.9.
97
Powerpoint, PAY FOR PERFORMANCE: 2009 Salary Budget Recommendation, Executive Review, January 21,
2009, Lucasfilm, LUCAS00189288, exhibit 945.13.
95

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“LEVEL I – ENTRY,” “LEVEL II – INTERMEDIATE,” “LEVEL III – SENIOR,” and
“LEVEL IV SPECIALIST,” and four sets of competencies are listed “scope/complexity,”
“knowledge & skills,” and “Supervision/ Discretion”.98
96.

There is additional evidence that Lucasfilm had formalized HR and compensation

systems. For example, Senior Manager, Compensation Michelle Maupin was asked in her
deposition, “Can you tell me the approximate salary range for grade
believe the midpoint , which is what is around
the high would probably be around
97.

?” She answered, “I

The low would probably be around

and

”.99

A Lucasfilm PowerPoint presentation has other reference to formalized systems,

noting “job grading,” “job match to salary survey data,” and “internal equity/factors”.100
98.

Pixar: There is evidence that Pixar had formalized compensation systems.

Included among this is data provided by Pixar to plaintiffs.101 That information shows that Pixar
had many job titles. Additionally Pixar uses compensation data in percentiles (e.g. 10th, 50th,
90th).102
99.

For example, Vice President of Human Resources and Administration Lori

McAdams noted in her deposition, “We establish salary ranges for each of our positions, and an
employee is offered or paid usually within that salary range”. She confirmed, “We participate in
salary surveys in the industry and – and in – in various fields, and use that information to
determine the appropriate salary range”.103

98

LUCAS00188750-LUCAS00188753, exhibit 959.43-959.46.
Deposition of Ms. Michelle Maupin, February 12, 2013, page 39.
100
Powerpoint on pay design, LUCAS 00188763, exhibit 715.56.
101
See spreadsheet “Employee Type Count by Employer”.
102
See, for example, Survey collection forms: PIX00088222 (2009); Market survey results: PIX00056267 (2009);
Matching employees to survey results: PIX00088115 (2009).
103
Deposition of Ms. Lori McAdams, August 2, 2012, page 29.
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100.

Ms. McAdams also noted the structure of the size of the ranges at Pixar:

.104
101.

Ms. McAdams also noted information about adjustments at Pixar: “Well, the

salary range adjustments is something that’s done by human resources so that we have ranges for
all of our established positions. And then the managers are provided any updated salary range
information so that when they are distributing their salary increase pool, they know if someone is
below – you know, they know where their people are in those salary ranges and can provide, you
know – can spend their pool accordingly”.105
102.

Ms. McAdams also was asked about Pixar’s use of salary surveys. “The Croner

Survey is an industry specific survey that surveys positions in the animation and visual effects
industry”.106
103.

While Croner collects data for a broader collection of companies, Pixar

sometimes request subsets of the data. When asked about the minimum number of companies
that can be provided by the Croner Survey, Ms. McAdams replied “I think it’s five”.107
104.

Information from the Croner Survey, used by Pixar (and other organizations)

notes “hierarchy,” “job families,” and “positions,” all terms used in formalized compensation
systems.108
105.

Additional evidence of formal pay systems at Pixar are from Manager of Human

Resources Stephanie Sheehy’s deposition. She was asked, “How are base salaries determined
for Pixar employees?” She replied, “We use survey data for the most part”. She was then asked
104

Deposition of Ms. Lori McAdams, August 2, 2012, page 32.
Deposition of Ms. Lori McAdams, August 2, 2012, pages 40-41.
106
Deposition of Ms. Lori McAdams, August 2, 2012, page 60.
107
Deposition of Ms. Lori McAdams, August 2, 2012, page 61.
108
2009 Croner Animation and Visual Effects Survey, January 8, 2009, PIX00001263, exhibit 119.
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“What do you do with the survey data?” She replied “We use it as a guideline to help us
determine the minimum salary/maximum salary for a job”.109
106.

Ms. Sheehy confirmed Pixar used salary ranges at Pixar”.110 Later she was asked

about job families and replied, “Job families are also called job groups, which I referred to
earlier…They’re a grouping of employees that sit together in our structure”.111
107.

Ms. Sheehy also testified that Pixar used both Croner and Radford market survey

data. When asked about “the steps that you follow to use that data and make the salary ranges”,
Ms. Sheehy answered “Let me think, is there a big difference between them? No, we use them
pretty much the same, both Croner and Radford. So we have met with each manager and gotten
a match for all the matches that are matchable. The employees that are matchable to a job in one
of the two surveys. And we submit our data at certain points during the year. And then when we
get our data back, we compare where the employee match range was that –
, and where the employee presently is in
their salary, what their current salary is, and we see where they land inside that range”.112
108.

Ms. Sheehy also noted job groups at Pixar.113 This is another part of the formal

pay structure.
109.

Pixar, like other defendant organizations, considered salary increase budgets each

year in considering changes to its pay systems. Pixar was also interested in what was happening
at other companies, particularly Lucasfilm. For example, Ms. McAdams sent an email to staff
from Lucasfilm, among others: “Quick questions from me, for those of you who can share this

109

Deposition of Ms. Stephanie Sheehy, Pixar, March 5, 2013, page 49.
Deposition of Ms. Stephanie Sheehy, Pixar, March 5, 2013, page 50.
111
Deposition of Ms. Stephanie Sheehy, Pixar, March 5, 2013, page 78.
112
Deposition of Ms. Stephanie Sheehy, Pixar, March 5, 2013, page 88.
113
Deposition of Ms. Stephanie Sheehy, Pixar, March 5, 2013, page 136.
110

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info. What is your salary increase budget for FY ’07? Ours is 4%, but we may manage it closer
to 3% on average. Are you doing anything close, more, or less?”114
VI.

Issues of Internal Equity
110.

In the best-known text in compensation, by Milkovich, Newman and Gerhart

(2014), Compensation, notes in the glossary under “equity theory,” “A theory proposing that in
any exchange relationship (such as employment) the equality of the outcome/input ratios
between a person and a comparison other (a standard or relevant person/group) will determine
fairness or equity. If the ratios diverge from each other, the person will experience reactions of
unfairness and inequity”.115 Issues of equity are clearly important not only in setting up the
original structure of a compensation system but also when managing it.
111.

There is substantial evidence that issues of internal equity and pay fairness were

important to defendant firms.
112.

Adobe: There is evidence that Adobe followed principles of internal equity. For

example, one document notes a section on the issue of a “Counter Offer”. It states “

.116 The capitalized “ALWAYS” is in the original.

114

Email from Lori McAdams, Pixar, November 17, 2006, LUCAS00184664, exhibit 122.
Milkovich, Newman and Gerhart (2014), page 680.
116
Powerpoint, Retention/Transition Guidelines, Adobe, June 2008, ADOBE_050724, exhibit 216.5.
115

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113.

An additional mention of internal equity at Adobe is in the deposition of

Mr. Digby Horner, Adobe’s Senior Vice President of Engineering. In reference to an email
exchange he had with colleagues that discussed the possibility of raising the pay of an employee
“off cycle,” a list of employees in similar positions at Adobe was included in the message.117
Mr. Horner was asked, “Is it fair to say that you want to consider how

peers are

being compensated to make sure that the compensation he receives is fair in comparison to
them?” He replied, “Yeah. What I would – what I would say here is that, you know, the primary
thing I look at is – so that – that’s a term that we use internally, which is internal equity.”118
114.

Similarly, in 2008, Senior Vice President of Global Human Resources Donna

Morris sent a message with the subject “final review of salaries,” indicating, “I have just finished
the full review of all salary and stock, and would like to recommend some changes relative to
your organization.

”119
115.

Ms. Morris also references internal equity in a series of emails to Adobe’s CEO

Shantanu Narayen. In the first, Ms. Morris wrote concerning a job candidate,

120

117

Email from Ms. Jocelyn Vosburgh, Adobe, October 25, 2010, ADOBE_011976-7, exhibit 1250.1-2.
Deposition of Mr. Digby Horner, Adobe, March 1, 2013, page 200.
119
Email of Ms. Donna Morris, Adobe, January 18, 2008, ADOBE_009425, exhibit, 2501.1.
118

120

Email from Ms. Donna Morris, Adobe, March 4, 2007, ADOBE_005661, exhibit 1158.

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116.

In a different email, Ms. Morris wrote Mr. Narayen, “Shantanu – Please find

attached proposed promotional compensation packages for

and

taking into account

market and internal equity ….”121
117.

In another exchange between Ms. Morris and Adobe’s CEO Mr. Narayen, she

wrote about the compensation for a potential new hire and then listed names and initials of four
people and some details of their compensation, including base and total cash compensation,
under the caption “internal equity.”122
118.

At his deposition, Mr. Narayen was asked about this third email exchange and

what he meant when he emailed Donna Morris, “Does that cause any internal inequities?”123 He
testified, “I think it would have related to, from a scope point of view and a performance point of
view, are you looking at that?”124
119.

Ms. Rosemary Arriada-Keiper also confirmed that internal equity was a principle

used at Adobe. “We use internal equity primarily in the capacity of looking at, again, typically
new hires …”.125 She explained, “So myself, as an example, if I’m bringing in somebody from
the outside and I’m thinking about what’s this offer that I want to make to this individual, I will
generally look at my team and see where they’re positioned, you know, and kind of make a
judgment call there. Because I do know that these individuals are going to be working side by
side, and you know, it can potentially have implications for me as a manager if they’re
performing exactly the same way and they feel like there is not a perceived fairness in terms of
their pay, right?” She further stated, “A conversation to have to explain to the individual why I
made the decision that I did, right? And there may be reasons for why I do that, and I’m
121

Email from Ms. Donna Morris, Adobe, June 5, 2010, ADOBE_019278, exhibit 1159.
Email of Ms. Donna Morris, Adobe, June 13, 2011, ADOBE_9652, exhibit 1160.
123
Email of Mr. Shantanu Narayen, Adobe, June 14, 2011, ADOBE_9652, exhibit 1160.
124
Deposition of Mr. Shantanu Narayen, Adobe, February 28, 2013, page 319.
125
Deposition of Ms. Rosemary Arriada-Keiper, Adobe, March 28, 2013, page 122.
122

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perfectly comfortable with it. And in other instances, I may say you know what? It’s not worth
it to me. I don’t want to create an issue where five people are going to be pissed off because this
person, you know, makes more than them and haven’t been here to prove themselves. So I have
to rationalize that as a manager.”126
120.

Apple: There is evidence that Apple followed principles of internal equity.

Mr. David Alvarez, Apple Recruiting Manager, testified that when making an offer to a new hire
one of the factors to consider in compensation is internal equity. When asked, “What do you
mean by ‘internal equity’”?127, Mr. Alvarez responded “What the population of – let’s say if a
candidate’s coming in at a certain level, we look at someone in that organization at that level to
see what everybody’s making. So who’s the low, the average and the high. That’s what internal
equity is. There’s a lot of calibration to it, so there’s a lot of avenues that we take to come up
with that recommendation”.128
121.

Former recruiter Darrin Baja testified that he was familiar with the term “internal

equity” and that it was a term used in discussing compensation at Apple.129
122.

Mr. Baja was asked “So, for example, if you were hiring somebody onto a team,

and they were doing a job function that was similar to what the other people on the team were
doing, you would look to what the other people on the team were making for comparative
purposes in setting the salary of the new hire?” He replied “That is one thing we would do,
yes.”130
123.

In an email message in response to a suggested level of compensation for a

candidate, Mr. Rob York wrote
126

Deposition of Ms. Rosemary Arriada-Keiper, Adobe, March 28, 2013, pages 124-5.
Deposition of Mr. David Alvarez, Apple, March 5, 2013, page 30.
128
Deposition of Mr. David Alvarez, Apple, March 5, 2013, page 30.
129
Deposition of Mr. Darrin Baja, Apple, March 1, 2013, page 43.
130
Deposition of Mr. Darrin Baja, Apple, March 1, 2013, page 44.
127

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131

Mr. David Alvarez

was asked about this message: “So in setting salaries that would be components of offers for
candidates Apple was interested in hiring, was what a candidates peer group was receiving an
important consideration”? Mr. Alvarez responded “That’s what we call internal equity”.132
124.

Internal equity is also discussed by Director of Executive Recruiting Mr. Richard

Bechtel, although he noted that he uses “the term ‘internal parity’ just to stay away from the term
‘equity,’ which can also mean RSUs and options. But internal parity is – yeah, yes, it does come
up”.133 Mr. Bechtel was later asked “So would it create a problem from the standpoint of
internal parity to offer a new hire more in compensation than is being paid to that new hire’s
peers who have the same job function?”134 Mr. Bechtel responded “Yeah. It’s – it’s something
that – it’s something that we would definitely want to be aware of. We would want to be
sensitive to it and we’d want to know why we were paying somebody more coming in than
somebody who is, you know, their peer that’s performing at a good level. And there have been
circumstances that we’ve done that, but there’s been business reasons for it”. He was then asked
“Well, why would you want to be sensitive about that?” Mr. Bechtel responded “I – we – it –
because people that are good employees at Apple, that are doing good work, that are wellrespected, and that are performing at a high level, you know, we – we want to – we want to make
sure we’re doing right by them”.135
125.

There is other information at Apple that indicated that internal comparisons and

equity mattered. Former recruiter Patrick Burke, was asked “So during your time, you hired or
recruited engineers, correct?” He said “That’s all I did. Yes”. He was then asked, “Now, for
131

Email from Mr. Rob York, Apple, on December 17, 2010, 231APPLE039427, exhibit 1376.2.
Deposition of Mr. David Alvarez, Apple, March 5, 2013, page 208.
133
Deposition of Mr. Richard Bechtel, Apple, March 7, 2013, page 40.
134
Deposition of Mr. Richard Bechtel, Apple, March 7, 2013, pages 43-4.
135
Deposition of Mr. Richard Bechtel, Apple, March 7, 2013, page 44.
132

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any particular engineering candidate, how was the salary range established for that potential
candidate?” Mr. Burke replied “It wasn’t a salary range determined, it was what salary we were
going to offer”.136 He then went on to say “And how that was determined was mostly asking the
hiring manager who they compared to in the team, looking at the candidate’s education,
experience, and knowledge within that experience, and comparing that to different people on
their team. And these were the biggest deciphering things.

. And that’s more what determined it. And then sometimes, depending on where – the
number that we determined for a particular candidate,

, and that’s where kind of sometimes HR would
get involved to do it. But it was generally guided by other people on the team and how they
compared to them”.137
126.

Mr. Burke confirmed that it was important not to pay new people more than those

already working at Apple.138 “That was a determining factor, but it was, again, more about how
they compared to those people. And so the hiring manager would usually not want to pay more
than a person with similar or more experience at Apple. So we called it internal equity or fair
compensation. And we would want to kind of keep it fair to the team on board. Just because this
person was asking for more money than someone with similar experience on the team didn’t
mean we just gave it to him. We would keep it fair to the people, and
.139

136

Deposition of Mr. Patrick Burke, Apple, February 26, 2013, page 37.
Deposition of Mr. Patrick Burke, Apple, February 26, 2013, pages 37-8.
138
Deposition of Mr. Patrick Burke, Apple, February 26, 2013, pages 42-3.
139
Deposition of Mr. Patrick Burke, Apple, February 26, 2013, page 43.
137

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127.

Apple’s Senior Director of Compensation Mr. Steve Burmeister was asked “Have

you heard the term ‘internal equity’”? He replied “I’ve – in a compensation speak language, we
use the term ‘internal equity’”. He elaborated “Internal equity means, to me, that what you’re
looking at, if you’re looking at compensation, that it’s fair based on the individual’s contribution
relative to the other employees in your group, or across your organization, whatever your scope
of management is”. When asked “Is there an internal equity component to determining starting
salaries at Apple?”140 Mr. Burmeister replied “It – internal equity plays into a few, if not all, of
these bullets for managers to consider when looking at a candidate to determine a new starting
salary”.141
128.

There are two other issues related to this issue in an Apple document. A

document notes

On the same page of that document, it is noted

142

129.

Google: There is evidence that Google followed principles of internal equity.

For example, a PowerPoint presentation about determining base salary shows

140

Deposition of Mr. Steven Burmeister, Apple, March 15, 2013, page 63.
Deposition of Mr. Steven Burmeister, Apple, March 15, 2013, pages 63-4.
142
Powerpoint, Compensation Framework, Insuring Global Consistency, Apply, 231APPLE105345, exhibit 1856.4.
141

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.143
130.

Another Google document is related to equity issues. Figure 12 is a reproduction

of a Google document.144 On the vertical axis is the employee performance rating. The
document indicates that the ratings go from

. On the horizontal axis

the “pre-adjustment position” is listed.
.145
131.
. For example, consider someone with
the very-highest performance rating
his or her merit increase will be

). If that person has a pre-adjustment position of
but if that person has a pre-adjustment position of

his or he merit increase will be only
performer

Also consider someone who is rated as an average

If that person is at a pre-adjustment position of

merit increase will be

his or her

but if that person has a pre-adjustment position of

his or her merit increase will be

,

.146 This system essentially is consistent with bringing

salaries in a group back together over time.
132.

The preceding example is a structured situation that shows that issues of equity

need not immediately lead to compensation changes. However, equity can have serious and
large implications for compensation over short, but not immediate, periods of time.
133.

There is a reference to internal equity in an email from Compensation Team

Member Ms. Tiffany Wu, indicating “
143

Powerpoint, Compensation Components Setting a Base Salary, GOOG-HIGH-TECH-00036302, exhibit,
1606.16.
144
Powerpoint, Salary Planning 2007, Presentation to Engineering Directors, 29 October 2007, exhibit, 1609.11.
145
Powerpoint, Salary Planning 2007, Presentation to Engineering Directors, 29 October 2007, exhibit, 1609.11.
146
Powerpoint, Salary Planning 2007, Presentation to Engineering Directors, 29 October 2007, exhibit, 1609.11.

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147

134.

In another Google document the FAQ section contains this question and answer:

148

135.

There is also evidence of this from other defendants but not in such a tabular

form. Some of this is directly related to discussions of equity. There are other instances, for
example at Apple. For example, Mr. Ron Okamoto wrote an email with respect to raises,

.149
136.

Mr. Okamoto was asked about this in his deposition. He said, “And so the

question is, when that happens, what do you do?

.150

147

Email from Tiffany Wu, September 7, 2007, Goog-High-Tech-00473658, exhibit 1613.
Google document, GOOG-HIGH-TECH-00474908, exhibit 1618.12.
149
Email from Mr. Ron Okamoto, Apple, September 17, 2010, 231APPLE099371, exhibit 1130.1.
150
Deposition of Mr. Ron Okamoto, Apple, February 27, 2013, page 135.
148

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137.

Intel: There is evidence that Intel followed principles of internal equity. For

example, in a PowerPoint document from 2002 titled, “NPG Human Resources Job Leveling &
Pay Equity Review,” Intel noted,

”151 The same document states a few pages later:

152

and

153

138.

Another Intel PowerPoint from 2005 describes a

.154
139.
has a section,

Likewise, the document titled “Manage Offer Module Develop External offer”
There it is noted

The document also instructs,

151

Powerpoint, NPG Human Resources Job Leveling & Pay Equity Review, June 6, 2002, 76583DOC00388,
exhibit 392.3.
152
Powerpoint, NPG Human Resources Job Leveling & Pay Equity Review, June 6, 2002, 76583DOC00388,
exhibit 392.5.
153
Powerpoint, NPG Human Resources Job Leveling & Pay Equity Review, June 6, 2002, 76583DOC00388,
exhibit 392.5.
154
Powerpoint, TMG Non-Tech Job Audit – HR, Intel, August 25th, 2005, 76583DOC008097_000003, exhibit
397.3.

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140.

A document referencing internal equity is a spreadsheet stating
.156 Another document notes a

number of suggested actions that would seem to be directly consistent with equity. For example,

So this suggests
merit pay be reduced based on information about a person’s position in salary range in the job.
This also suggests that relatively higher paid individuals (among a set of peers at Intel) would
have relatively smaller raises. This continues similarly for other situations. For example, in the
situation where a
157

141.

A PowerPoint discussing “Base Pay Comparison,” notes that when

158

155

Document, HR Global Staffing, Manage Offer Module, Develop External Offer, document Version 1.3, February
13, 2009, 76579DOC005963, exhibit 398.8.
156
Intel spreadsheet 76579DOC005152_000017.
157
PowerPoint, Base Pay Comparison Report Support Overview WW 042011, 765825DOC001211, exhibit 400.17.
158
PowerPoint, Base Pay Comparison Report Support Overview WW 042011, 765825DOC001211, exhibit 400.17.

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142.

An Intel document from 2008 questioned, “Are there specific areas where we are

experiencing market/internal equity issues?”159
143.

Similarly, in a document called “Worldwide Focal 2001 Questions and Answers.

Intel Confidential,” the following question and answer appear:
144.

145.

160

146.

In reference to the

document mentioned above161, Worldwide

Focal 2001 Questions and Answers, Intel Confidential, Deborah Conrad was asked,
She replied

”162
147.

Ms. Conrad testified that
.163 “Yes, that could be – that could be one of the things that you would

look at.”164
159

Powerpoint, Internal Climate, Intel, 76596DOC017025, exhibit 781.16.
Worldwide Focal 2001 Questions and Answers Intel Confidential, Rev 13, Feb 26, 2001. 76583DOC003753,
exhibit 391.4.
161
Worldwide Focal 2001 Questions and Answers Intel Confidential, Rev 13, Feb 26, 2001. 76583DOC003753,
exhibit 391.4.
162
Deposition of Ms. Deborah Conrad, Intel, November 21, 2012, page 202.
163
Deposition of Ms. Deborah Conrad, Intel, November 21, 2012, page 204.
160

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148.

Ms. Conrad also testified about her understanding of the term internal equity. “I

understand the term to mean people doing a relatively similar – complexity similar of their job
are being compensated in a similar way. So we talked about the grade level example”.
Ms. Conrad continued, “A grade-level engineer and – a grade level 12 engineer, a grade level 12
project manager, a grade level 12 software person are being compensated based on complexity of
that role, and there’s a range that – of the compensation that is allocated to that grade, and that
gives us equity across – internally across job function.”165
149.

CEO Paul Otellini noted in an email,

”166 The fact that
those with relatively high levels of pay as compared to their peers are exempt from raises is
consistent with internal equity.
150.

Ms. Renee James, Manager of Intel’s Software Services Group, testified that she

understood internal equity to mean: “A set of criteria that we use to in aggregate check between
different people in the same grade band across a variety of metrics, performance, pay, equity”.167
She also noted, “I think internal equity is aspirational. I think it is a guideline that helps you look
at, you know, apples and oranges data and give you a sense of what’s going on,

164

Deposition of Ms. Deborah Conrad, Intel, November 21, 2012, page 204-5.
Deposition of Ms. Deborah Conrad, Intel, November 21, 2012, page 50.
166
Email from Mr. Paul Otellini, Intel, January 22, 2010, 76616DOC012164, exhibit 478.1.
167
Deposition of Ms. Renee James, Intel, March 22, 2013, pages 242-3.
165

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168

As I note elsewhere and I think is implied here, concepts of equity

and pay and performance are not independent. They can also be used simultaneously.
151.

Intel Vice President of Human Resources Ms. Patricia Murray also testified about

her understanding of the term “internal equity.” “My general understanding of internal equity, it
is a process by which a manager or group of managers or even a department judges whether
people are being paid fairly next to one another inside the company.”169
152.

Intel Compensation and Benefits Specialist Daniel McKell explained his

understanding of the use of the term “internal equity” at Intel: “internal equity means fairness.
Typically, when we talk about internal equity, it’s how employees are paid relative to each other.
It can also be part of that – “egalitarian” is another term that we would say – so from an internal
equity perspective, everybody participates in stock even though they have different grades. So it
has multiple meanings depending on the specific context, but generally is mean fairness”.170
153.

Mr. McKell testified about HR’s “

explaining,

”171
154.

In a 2005 email, Mr. McKell wrote:

”172 Mr. McKell
explained that
168

Deposition of Ms. Renee James, Intel, March 22, 2013, page 244.
Deposition of Ms. Patricia Murray, Intel, February 14, 2013, page 40.
170
Deposition of Mr. Daniel McKell, Intel, March 20, 2013, page 207.
171
Deposition of Mr. Daniel McKell, Intel, March 20, 2013, page 210.
172
Email from Danny McKell, Intel, February 2005, 76657DOC004599, exhibit 2033.
169

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173

155.

In reference to the same e-mail, Mr. McKell testified that he had written that

internal equity “looks pretty good” because “…the people that they had brought in were
generally being paid about the same as existing Intel employees.”174
156.

Mr. McKell also testified about Intel’s merit budgets.

.175 Note that it is my understanding in this context that Q is
referring to quartile in range with Q1 being the smallest quartile and Q4 being the largest
(elsewhere in documentation from the defendants Q sometimes refers to quarter of the year). So
this suggests that for a given level of performance (e.g. “successful”), those higher in the pay
range in advance of the performance rating have a lower suggested raise.
157.

Mr. McKell explained, “… so there’s a series of goodies that a manager can

allocate, and peanut butter means trying to spread it out as far as it can go”.176 He was then
asked,
He replied,

173

Deposition of Mr. Daniel McKell, Intel, March 20, 2013, page 227.
Deposition of Mr. Daniel McKell, Intel, March 20, 2013, page 228.
175
Deposition of Mr. Daniel McKell, Intel, March 20, 2013, page 100.
176
Deposition of Mr. Daniel McKell, Intel, March 20, 2013, page 188.
174

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177

Mr. McKell was asked,

”178
158.

In my view it is certainly easily possible for organizations to have both a pay for

performance system in place, while simultaneously stressing equity and related concepts. In fact,
Intel’s Daniel McKell testified that the philosophies of both internal equity and meritocracy exist
at Intel. “They do exist. I don’t believe that they’re mutually exclusive. I think meritocracy
definitely exists in pay raises and bonus changes and stock grants, and that it is effective. I also
think internal equity exists, because managers look at pay fairness relative to what each
employee is making, and makes decisions based on that – whether somebody is too high or too
low relative to their peers. So I think there are good checks and balances on each other.”179
159.

Intuit: There is evidence that Intuit followed principles of internal equity. For

example, Director of Talent Acquisition Chris Galy testified about Intuit’s practice of
benchmarking and considering external and internal employees when setting new hire pay:

Again, it’s a data point.

177

Deposition of Mr. Daniel McKell, Intel, March 20, 2013, page 189.
Deposition of Mr. Daniel McKell, Intel, March 20, 2013, page 190.
179
Deposition, Mr. Daniel McKell, Intel, March 20, 2013, pages 269-70.
178

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180

160.

Another example that the pay of one person mattered relative to that of another is

included in this testimony from Mr. Galy: Q. “Can you give me a personal example or example
about which you have some personal knowledge of an off-cycle pay action?”181 A.

Q. “I see.
A. “Right.
Q. “Okay.
A. “

182

Q. “Is it possible that this is one of the situations in which a

manager might – or the business leader might have to go to his manager and ask for a bigger
compensation budget?” A. “Yeah.”183 This very last part indicates that budgets are not always
fixed for increases. In fact, sometimes additional resources are gathered and pay is even
increased off-cycle.

180

Deposition of Mr. Chris Galy, Intuit, March 20, 2013, page 180-1.
Deposition of Mr. Chris Galy, Intuit, March 20, 2013, page 194-5.
182
Deposition of Mr. Chris Galy, Intuit, March 20, 2013, page 195.
183
Deposition of Mr. Chris Galy, Intuit, March 20, 2013, page 195-6.
181

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161.

An email Mr. Galy forwarded also mentions internal equity. That email stated:

184

162.

An Intuit document titled “Talent Acquisition Hiring Plan” also noted internal

equity. In one section, this hiring plan noted
185

163.

There is also mention of “internal equity” in another Intuit document from 2005

that mentions

and notes,

186

164.

An additional Intuit document mentions equity. On a page titled

187

165.

Lucasfilm: There is evidence that Lucasfilm followed principles of internal

equity. For example, Lucasfilm Senior Manager, Compensation Michelle Maupin was asked
“Do you think fairness was considered at all prior to 2006 in setting employee salaries?” She
replied “What do you mean by ‘fairness’”? She was then asked “Was internal equity considered
at all prior to 2006 in setting employees’ salaries?” “Based on my knowledge and information
that I have seen, documents I’ve looked at in the past, yes”.188
184

Email from Mr. Chris Galy, Intuit, March 3, 2010, INTUIT_039793, exhibit 2142.1.
Document from Intuit, Talent Acquisition Hiring Plan, INTUIT_007866, exhibit 1107.2.
186
Powerpoint, INTUIT Total Rewards & Pay Decisions Toolkit, Intuit, May 2005, INTUIT_043560, exhibit
2739.31.
187
Powerpoint, Focal Decisions 2005, Communications Session for Senior Managers, June 2005, Intuit,
INTUIT_052841, exhibit 2740.16.
188
Deposition of Ms. Michelle Maupin, February 12, 2013, page 85.
185

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166.

Ms. Maupin also testified, “I would anticipate that if a junior level or a junior-

skilled employee was at the same or same pay level as a senior employee, that might cause
dissatisfaction for even the manager of those employees.”189
167.

Ms. Maupin was asked, “Can you explain the significance of peer relationships in

setting compensation at Lucasfilm?” She replied, “The significance is to consider individual
employees’ pay within a similar job and pay range using the same type of skill sets to
appropriately align those employees relative to their peers and to market.”190
168.

In her declaration, Ms. Maupin also noted equity: “Lucasfilm occasionally

adjusts salaries outside of the April pay-for-performance process. These are referred to as outof-cycle increased and are given for promotions, and equity adjustments. An equity adjustment
is intended to bring an employee’s compensation more in line with (but not necessarily equal to)
internal peers or the targeted percentile or external peer compensation.”191
169.

Ms. Michelle Maupin stated by email: “…Janetta has already told him I don’t

agree with

Unless we want to raise salaries of the other EA’s [sic], I think
this is fair.”192
170.

In questioning related to an email from Ms. Maupin to Chief Administrative

Officer Jan van der Voort where Ms. Maupin wrote, “Internal equity is a concern, although we

189

Deposition of Ms. Michelle Maupin, February 12, 2013, page 175.
Deposition of Ms. Michelle Maupin, February 12, 2013, page 178.
191
Declaration of Ms. Michelle Maupin, January 17, 2013, page 9.
192
Email from Ms. Michelle Maupin, November 4, 2010, LUCAS00198130, exhibit 729.1.
190

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just hired …”193 Ms. Maupin was asked, “Was the internal equity concern that

might be

paid more than her colleagues?” She answered, “In some cases.”194
171.

In another situation at Lucasfilm, Ms. Jan van der Voort wrote a message noting,

“Steve, I think this needs Jim Ward’s buy-in … at this level, we’re getting in to some interesting
internal equity issues, which I want Jim to be aware of before I decide.”195
172.

Ms. Van der Voort testified about her familiarity with internal equity at

Lucasfilm. “It means generally that you are aware of where similarly situated employees are
from a compensation perspective, either within their division or across the company depending
on what you are looking at.” Then she was asked, “Is internal equity a consideration in setting
salary grades?” She replied, “It is a consideration, yes.”196
173.

Senior Director of Human Resources Sharon Coker discussed internal equity in

her deposition. “Internal equity is that people within the company, internally within the
company – and it has nothing to do with what the market pays, if you want to be literal with it.
But internal equity then means that at my company I’m paid comparably – not exactly, but I’m
paid comparably to other people with the same set of experience and same level of performance
for doing, the same work.”197
174.

Ms. Coker was asked, “Did you understand the idea of – concept of Lucas –

excuse me, the idea of internal equity to be something that all sorts of companies thought about
when constructing or modifying their compensation structures”?198 She answered, “Absolutely.

193

Email from Ms. Michelle Maupin to Jan van der Voort, May 8, 2008, LUCAS00201069, exhibit 727.3.
Deposition of Ms. Michelle Maupin, February 12, 2013, page 182.
195
Email from Ms. Jan van der Voort, July 9, 2007, LUCAS00060705, exhibit 728.1.
196
Deposition of Ms. Jan van der Voort, February 5, 2013, page 200.
197
Deposition of Ms. Sharon Coker, LucasFilm, November 1, 2012, page 259.
198
Deposition of Ms. Sharon Coker, LucasFilm, November 1, 2012, page 259-60.
194

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And if the company didn’t, the employees would remind them. So, you know, again, I think it’s
– it is – internal equity is a consideration in compensation decisions.”199
175.

Ms. Coker also noted in her deposition, “… I would say that almost always when

you made – not always, but often if you would make an individual decision, it could impact other
employees in similar positions. So you had to look at that.”200
176.

Ms. Coker testified about internal equity: “…internal equity would be – it could

mean two things. One is it could mean that there were a group of employees in a job family
doing similar work and at one company, perhaps even they were paying X or a range of X to Y
for those positions. Across the street, more or less in one of the other divisions, they might be
paying from X to Z for those positions. So it was within Lucas companies are there any – can
we identify any areas where we have, you know, what I would call a ‘pay discrepancy,’ where
we’re not paying within reason within ranges.”201
177.

There are multiple references to “call out for equity” in an email from

Ms. Vanessa Hall at Lucasfilm.202
178.

Internal equity is also noted in an additional Lucasfilm document from 2004:

“Evaluate Internal Candidates’ qualifications against market value and internal equity.”203
179.

Likewise, a Lucas film document from 2006 mentions “Gathering input on comp

issues” including “internal equity”.204
180.

Pixar: There is also evidence that Pixar followed principles of internal equity. In

her deposition, Pixar Vice President of Human Resources Lori McAdams was asked, “Now, how
199

Deposition of Ms. Sharon Coker, LucasFilm, November 1, 2012, page 260.
Deposition of Ms. Sharon Coker, LucasFilm, November 1, 2012, page 245.
201
Deposition of Ms. Sharon Coker, LucasFilm, November 1, 2012, page 283.
202
Email from Ms. Vanessa Hall, February 14, 2011, LUCAS00199905-6.
203
Compensation Analysis and Review Process, Internal Transfer, DRAFT Last Updated 11-23-04,
LUCAS00185312, exhibit 716.
204
Powerpoint, Lucasfilm Ltd. Compensation Project Status Executive Review, Lucasfilm, December 7, 2006,
LUCAS00027982, exhibit 359.4.
200

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is the compensation of a new employee – how is the base salary of a new salaried employee
determined?” She answered, “We look at their experience and education and how we evaluate
them against existing employees – and make them an offer relative to their experience and – and
our existing talent”.205 Note the reference to existing talent.
181.

While not directly using the term “equity” the deposition of Stephanie Sheehy

describes related issues. She notes, “The goal of this new salary proposal is to compensate the
lowest paid team-members who are performing at the highest levels. This is a ‘pre-emptive
strike’. We want to send a clear message to these engineers that we value them at least as much
as some new hires who are seeing much more competitive offers from other companies.”206
VII.

Internal Equity and Pay for Performance Are Not Mutually Exclusive
182.

In this section I discuss the issues of pay for performance and internal equity.

Both pay and performance and internal equity are often-discussed in the realm of compensation.
I discuss here that it is possible to have a compensation system that is simultaneously consistent
with pay for performance and also with internal equity.
183.

The Google Figure 12 is quite interesting since it is an example in one space

where one can see a system that reflect both “pay for performance” and equity concerns at the
same time.

205
206

Deposition of Ms. Lori McAdams, August 2, 2012, page 32.
Deposition of Ms. Stephanie Sheehy, Pixar, March 5, 2013, page 151.

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184.

Adobe also has information that is very similar to the Google Figure 12. In Table

13, I have included the left 1/3 (the part that is relevant for the United States) on “salary increase
matrices”.207 The table has two parts. The top is for managers. The bottom is for “individual
contributors”208 (IC). It is clear from Table 13 for Adobe that, again,
.
185.

I found what appears to be similar information at Apple. In an Apple document209

there appears to be evidence that

186.

From a different Adobe PowerPoint slide, I have used information to create

Figure 15 which is a matrix the vertical axis of which (rows) appears that it could be
performance rating with “HI” as highest, “SC” the middle ranking and “LP” the lowest
ranking.211 In fact, Ms. Arriada-Keiper is asked at one point about three levels of performance:
“What were the three levels of performance when there were three?” and she replied “HHI, solid
and low”.212 The shorthand for all three appears to match three of the four in Figure 13.

207

Powerpoint, 2010 Annual Performance Review, Compensation Training for Managers, December 2009,
ADOBE_100614, exhibit 2487.15.
208
Deposition of Ms. Rosemary Arriada-Keiper, Adobe, March 28, 2013, page 165.
209
Powerpoint, Total Rewards Planning, FY07, September 2006, Apple, 231APPLE095052, exhibit 1855.107.
210
Deposition of Mr. Steven Burmeister, Apple, March 15, 2013, page 122.
211
Powerpoint, Global Market Analysis, Adobe, exhibit 2486.33.
212
Deposition of Ms. Rosemary Arriada-Keiper, Adobe, March 28, 2013, page 96.

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This expresses the same concept as in previous examples for Google (Figure 12),
Adobe (Figure 13) and Apple (Figure 14).213
187.

Intel also has a document that appears to be consistent with these ideas but is not

in a tabular format.214 In this document there are various

and then

that I

have reproduced in Figure 16.

.215 Each of these scenario and
action pairs is consistent with the examples in Google (Figure 12), Adobe (Figure 13) and Apple
(Figure 14).
188.

So there is direct evidence of compatibility between principles of internal equity

and pay-for-performance that I found from four of the defendant companies (Google in Figure
12, Adobe in Figure 13 (and perhaps Figure 15 if I have interpreted those data correctly), Apple
in Figure 14 and Intel in Figure 16. These examples make explicit that the companies give
relatively lower raises to those who are relatively more highly paid in a given grade for a given
performance level.
189.

There is also evidence of this from other defendants but not in such an express

tabular form. Some of this is directly related to discussions of equity. There are other instances,
for example at Apple. There, Mr. Ron Okamoto wrote an email with respect to raises, “An

213

Powerpoint, Global Market Analysis, Adobe, exhibit 2486.33.
Powerpoint, Base Pay Comparison report Support Overview WW 042011, 765825DOC001211, exhibit 400.17.
215
Powerpoint, Base Pay Comparison report Support Overview WW 042011, 765825DOC001211, exhibit 400.17.
214

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216

190.

Mr. Okamoto was asked about this in his deposition. He said “And so the

question is, when that happens, what do you do?

.217
191.

It can be shown that pay and performance and issues of equity are not mutually

exclusive in other ways. Consider two employees in a work group who are both paid a base
salary and a “commission” or piece-rate for some level of output (say sales of some item such as
a book or car). Arranging the system so that appropriately grouped workers have similar base
salary and commission rate is certainly equitable. At the same time, this compensation system
has a pay for performance component.
VIII. How Restricting Cold Calling Can Restrict Information and Pay
192.

Restricting cold calling can clearly restrict information and pay. In many

markets, employees are hired due to cold calls.218
193.

This can be illustrated by the findings of the Court in this case. “Plaintiffs have

set forth evidence of Defendants’ anti-solicitation agreements, which were memorialized in
CEO-to-CEO emails and other documents, such as ‘Do Not Call’ lists putting each firm’s

216
217

Email from Mr. Ron Okamoto, Apple, September 17, 2010, 231APPLE099371, exhibit 1130.1.
Deposition of Mr. Ron Okamoto, Apple, February 27, 2013, page 135.

218

There is a difference between an organization’s product market competitors and its labor market
competitors. Some organizations may not compete in the market for goods and services. Nevertheless,
they may hire from among the same pool of workers.
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employees off-limits to other Defendants.”219 “The question presented by this case is not
whether Defendants’ anti-solicitation agreements had an impact on any employees. Defendants
concede that some employees may have been impacted. See Tr. at 144:11-12 (‘And I admit at
the start, we are not saying that nobody was impacted.’).”220
194.

In the instance of this case, the defendant firms limited the market for the

employees by restricting cold calling. This clearly led to what would otherwise be higher levels
of compensation for some of those in the firms, except that the restrictions were in place.
195.

This situation of lower levels of compensation for some can directly lead to lower

levels of others due to the very nature of the formalized pay systems in place at the defendants.
This is even more likely among the technical class consisting of those described in Appendix B
to the October 1, 2012 Expert Report of Dr. Edward E. Leamer, and who worked for a Defendant
while that defendant participated in at least one “no cold-call” agreement with another defendant.
196.

The formalized systems in place at the defendants relied on structures, external

data from the market and the like, and notions of equity were present at defendants. As a result,
those effects cycle on to other employees and their levels of compensation. Therefore, the
formal compensation structures could lead to an effect on nearly all class members.
197.

In a very strict simple supply and demand model with perfect competition and

immediate complete information prices of all sorts can adjust immediately. But many markets
don’t hold all of these characteristics or behave this way. Some economists discuss the idea that
workers are paid their value at any given time. But we know of many instances where pay
changes at discreet moments and surely this is not always coincident with discreet changes in
productivity.

219
220

Order by Judge Lucy H. Koh, Case5:11-cv-02509-LHK Document382 Filed04/05/13, pages 11-12.
Order by Judge Lucy H. Koh, Case5:11-cv-02509-LHK Document382 Filed04/05/13, page 13.

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198.

An example of this is when someone gets a raise at a point in time or when he or

she changes jobs for a higher level of compensation or when, in response to new information,
compensation levels change. Take for example the email from Mr. Arnnon Geshuri from Google
where he notes

221

”.222 Surely, calling in to employees
they previously were not contacting could have positive effects on the compensation of those to
whom they would call, either at their current employer, elsewhere or at Google.
199.

An additional example of a rapid change in compensation due to new information

comes from Intuit. Mr. Alex Lintner was asked “Are you aware of any instances in which Intuit
has identified employees who should be the focus of retention efforts?” He replied “Oh, yes.
Lots of them. We go through that all the time.

221
222

GOOGLE-High_Tech-00379327, exhibit 614, email from Mr. Arnnon Geshuri on Saturday March 15, 2008.
GOOGLE-High_Tech-00379327, exhibit 614, email from Mr. Arnnon Geshuri on Saturday March 15, 2008.

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.223
200.

Again, not all markets react immediately since information is not always perfect

to all parties to a transaction. In fact, due to issues of internal comparisons, sometimes
individuals are hired from the outside (for example) and have relatively higher levels of
compensation than others in their workgroup, even once performance is taken into account. As a
result, they may see slower growth of pay, relative to others in a similar job as a way to bring
compensation together. This is an interesting issue and suggests that issues of internal equity are
not necessarily immediately solved. That is, whether bringing in a new person with a higher
wage to a new workgroup or raising the wage of someone in a work group does not necessarily
mean that the levels of compensation of everyone else need be raised immediately also. Equity
in this sense does not mean that all needs to immediately adjust. But equity can still be an issue
for the organization that they can solve over time.
IX.

How A Structured Compensation System Can Be Related to Systematic
Compensation Effects
201.

A structured compensation system of the type I have described here can lead to

systematic pay effects. In fact, entire pay systems can change at once and everyone can be
affected. The concept of equity is related; this is common in the compensation area and widely
known by practitioners who design pay systems in organizations.
202.

In a recent book (Hallock, 2012), I wrote about what is known as “equity theory,”

among a set of psychological theories that are important to compensation. I wrote, “The idea
behind equity theory (Adams, 1965) is that workers will be motivated when their perceived
223

Deposition of Mr. Alex Lintner, Intuit, March 25, 2013, pages 107-8.

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inputs (e.g. effort) match their perceived outputs (e.g. pay). If someone thinks she is being
unfairly paid (e.g. others are being paid more for the same perceived effort), she will become
uncomfortable and unmotivated”.224
203.

Milkovich, Newman and Gerhart (2011) also discuss equity and fairness.225 In

fact, issues related to internal equity are one important reason organizations set up internal pay
structures as discussed above. Recall that those structures are typically set up internally, even
before going to the external market data.
204.

Milkovich, Newman and Gerhart (2011) note that “the research suggests that

employers judge the fairness of their organization’s internal pay structure by making multiple
comparisons” including “comparing to jobs similar to their own,” “comparing their jobs to others
at the same employer,” and “comparing their jobs’ pay against external pay levels”.226
205.

Google’s “big bang” compensation increase is an important example of how a

stimulus that may appear on the face to affect only a subset of employees, affected all
employees. In this example, all employees of Google were given an instantaneous raise of 10%.
Google’s former Senior Vice President of People Operations (HR) Ms. Shona Brown notes “…
we unilaterally, in other words, without a performance orientation to it, we looked across the
whole company and we said we’re going to give a ten percent – it doesn’t – it was a percentile
but still, we gave it to everybody”.227
206.

Other organizations commonly move the entire pay structure all at once, at least

annually. Refer again to Figure 1. This is an example from the U.S. Government’s salary table.
This entire table can change from year to year. Other examples of this include unionized

224

Hallock (2012), page 121.
See Milkovich, Newman and Gerhart (2011), page 83.
226
Milkovich, Newman and Gerhart (2011), page 83.
227
Deposition of Dr. Shona Brown, Google, January 30, 2013, page 232.
225

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contracts for school teachers and firefighters where the entire schedule moves at once. In fact,
entire structures move from year to year in all kinds of organizations, including at defendants
over the recent past. I will show some examples below.
207.

If it is the case, in a particular organization or organizations, that those at the top

of a pay scale help determine the relative gains of those “below” them, then restricting the pay of
those at the top of a grid necessarily affects those below.
X.

Examples of How Market Pressure Led to Pay Changes at Defendants
208.

There are clear examples of how pay changed at some defendants. I will discuss a

few examples here, including how market pressure led to pay changes at defendants.
209.

One example is from Adobe. Mr. Chizen, commenting on his time as CEO,

noted, “Typically the HR people would come to me and say, we really need to move the ranges
based on the Radford data. Here is the Radford data. So it will be me approving a
recommendation. Again, the philosophy of the company, which I said, we’re going to pay
within this percentile for these – at a high level … for, you know, engineering product, we’ll pay
this, for the rest of the organization we’re paying within the Radford, so if Radford moved
automatically, the – that would move”.228 He was then asked “And that was my question,
whether in order for the compensation for any particular people who fell within that range to
move, did you have – did you have to validate Radford’s conclusions that it moved … 5 percent
of that was just something - ”.229 Mr. Chizen replied “That was typically – no, with one caveat,
we also had to live within our budget. So if Radford moved 20 percent, and we can only afford
to do a merit increase for the company of 5 percent, we had to make a conscious decision of
which positions we were going to let go to the 20 percent versus which ones you were going to
228
229

Deposition of Mr. Bruce Chizen, Adobe, March 15, 2013, page 100.
Deposition of Mr. Bruce Chizen, Adobe, March 15, 2013, pages 100-1.

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keep at 2 percent. That’s when I would get involved”. He was then asked “Did that ever happen
from time to time, that the market data came back in a way that you couldn’t afford?” He
replied, “Typically not. Adobe was such a cash rich company, expense was not my number one
concern”.230
210.

Another example is from Google. Google has provided several sets of salary

grids (including the one already discussed in Figure 7) and I will discuss only a few here. For
example, I start with the 2005 salary structure and compare two sets of categories in two
regions.231 The data are displayed in Figure 17. The regions are referred to as
and

and the categories are

for another.

For these two sets of jobs and regions in 2005, I created the spreadsheet in Figure 17. I repeated
this tabulation in the same figure using data from Google in 2004.232
211.

.233
212.

Multiple comparisons are easily made from these data. For example, using only

2005 data, if one compares

in Figure 18 to

in Figure 18, it is clear to see that nearly every single element of the
different from the “

are precisely

This is true both when comparing each T

grade and each E grade within 2005 and within 2004. The only exception is the maximum
column in 2005 for the T grades. So of 180 possible numbers,

are

This implies

230

Deposition of Mr. Bruce Chizen, Adobe, March 15, 2013, page 101.
GOOG-HIGH-TECH-00625148 Contains a courtesy reproduction of a compensation spreadsheet titled 2005
Global Ranges - for MQU May-06.xls.
232
Exhibit 1600.l “Google 2004 Salary Ranges”.
233
GOOG-HIGH-TECH-00625148 Contains a courtesy reproduction of a compensation spreadsheet titled 2005
Global Ranges - for MQU May-06.xls and Exhibit 1600.l “Google 2004 Salary Ranges”.
231

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a formal structure that is standardized for the company for these pay grades, with a few
exceptions.
213.

In fact, Google was explicit in changing its salary structure at one point in time

and did so universally with the “big bang” in which it increased salaries by 10% across the
board.
214.

234

Google documents

.

215.

235

216.

At Lucasfilm Ms. Micheline Chau testified that over time Lucasfilm changed its
of the external market benchmark.236

payment targets from
217.

Ms. Chau clarified,

, again, like I said, depending on the industry

circumstance, sometimes was in the – sometimes it was
economic conditions didn’t need it, it
218.

for critical talent, and when
”.237

Data from Lucasfilm also show a systematic structure with pay changes and

differences across levels. I created a figure using data on the 2008 and 2006 salary structure at
Lucasfilm in Figure 18.238

234

Deposition of Mr. Frank Wagner, Google, March 7, 2013, page 216.
Email from Anuj Chandarana, Google, December 2, 2010, exhibit 1629.
236
Deposition of Ms. Michelene Chau, Lucasfilm, February 21, 2013, page 126.
237
Deposition of Ms. Michelene Chau, Lucasfilm, February 21, 2013, page 127.
238
LUCAS00188913 (Exhibit 711.29) for 2008 and LUCAS00188912 (exhibit 360) for 2006.
235

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219.

In 2008 there are 23 Salary Grades reported for Lucasfilm and in 2006 there are

21 Salary Grades reported for Lucasfilm.239 As shown in Figure 18, for each of these grades
there is a minimum salary, a midpoint salary and a maximum salary reported in each of the two
years. There is interesting formality and symmetry to the Lucasfilm structure.

220.

Further at Lucasfilm, within each grade,

221.

In addition, at Lucasfilm, within the three metrics (minimum, midpoint or

maximum),

222.

Finally, at Lucasfilm, the entire structure

223.

In the deposition of Stephanie Sheehy at Pixar, there is discussion of changes in

pay for an entire group. Ms. Sheehy was asked, “Why did Pixar decide it was necessary for the
tools group to have their base salaries on average at a higher than

level?” She

answered “We were competing with technology companies in the Bay Area, and our recruiting
team was hearing from candidates that they were getting better offers elsewhere”.240 She was
then asked “What was the percentile level that was the aspiration for this group of employees?”

239
240

LUCAS00188913 (Exhibit 711.29) for 2008 and LUCAS00188912 (exhibit 360) for 2006.
Deposition of Ms. Stephanie Sheehy, March 5, 2013, page 106.

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241

”.242 In the absence of the recruiting team hearing from

She replied, “

candidates that those candidates were getting better offers elsewhere, there would have been less
pressure to target a higher percentile.
XI.

Agreements of the Kind Described in this Case Could Limit Recruiting and Have
Negative Consequences on Compensation for Employees of Defendant Firms
224.

In this section I will discuss more about how the so called no cold calling

agreements could have negative consequences, not only for those directly affected by the no
cold-calling but also for nearly all others at the Defendant firms, particularly in the technical and
creative areas.
225.

Cold calling is an important part of recruiting in some industries. In fact, in some

types of jobs, a large majority of the jobs are filled through this method.
226.

At the same time, many employees can see their salaries increase and stay at their

current employers by using a competing offer (or even the threat of a competing offer). This is
true is many industries.
227.

Restricting cold-calling can have negative consequences for the compensation of

those who are cold called, could be cold called and potentially for nearly all others in their
organization.
228.

A consideration in this case is that the defendants represented very well-known,

celebrated companies. For many reasons these could be thought of as “employers of choice”.
By having restrictive recruiting practices at these firms and for those employees of those firms
who were highly coveted by other employees, there could be negative consequences for pay and
pay growth.

241
242

Deposition of Ms. Stephanie Sheehy, March 5, 2013, page 106-7.
Deposition of Ms. Stephanie Sheehy, March 5, 2013, page 107.

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229.

Important in this argument is the issue of equity as outlined earlier. To the extent

that there is an internal structure, any restriction at the top could have a consequent cascading
effect on those below. This can be seen even back in several of the Figures that either have job
evaluation points or even grades as the horizontal axis. The horizontal axes in each of those
Figures represents job evaluation points or what have been called the things that people do at
work or the contributions that people are having to the organization.243 Taking the example of
Figure 7, if the pay is restricted for any of the kinds of people who may be at the “top” of the
boxes, then the boxes may stop growing from period to period and all employees – even those
not at the top of the box can be affected. But, as indicated elsewhere cascading effects on others
do not rely on the pay of the highest paid being restricted.
230.

There is evidence in economics and in other areas that fairness in wage setting

and considerations of peers in compensation matters (e.g. Levine, 1993 and Card, Mas, Moretti,
and Saez, 2012).
231.

There is substantial evidence from each of the defendants that fairness and equity

considerations mattered.
232.

In addition, it is not only the case that those who are paid at the “top of the box”

are the ones who are being cold called. In the absence of any cold-calling restrictions or
agreements, any employee can be cold called. Even if cold calling affecting pay is restricted at
the mid-point, for example, due to the nature of the structure and use of external data, there can
be negative compensation consequences for even those who would not be cold-called.
233.

I also note that no workers have to move from one company to another for no-

cold-call agreements to have a negative effect on compensation. This is plain to see. If a
recruiter working for company X calls and asks an employee of firm Y of her potential interest in
243

See Hallock (2012) page 62.

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moving, her compensation can’t go down and may go up if she can use any potential or realized
offer to bid up her own pay internally. So even if not a single employee moves, cold-calling
agreements could have negative consequences for pay and pay growth.
234.

It should also be noted performance is not always as easily measured as some

argue. In fact, performance is sometimes very hard to measure and social scientists have devised
ways to consider compensation in interesting ways precisely because performance is difficult to
measure in some situations.244
235.

Intuit also provides an example on competition. In a PowerPoint presentation,

Intuit noted: “The more passive the candidate, the fewer competitors for talent”.245
236.

Also at Intuit, Mr. Chris Galy was asked, “Okay. How – What kind of

conversation would you typically have with candidates about compensation in an initial coldcall?” He replied, “It comes up. Again, generally driven – the goal of – the first, primary goal is
to generate interest and awareness and see if there’s a match. But then the next thing is you
don’t want to waste people’s time and they don’t want to waste yours. And so it’s – these days,
it’s generally, you know, hey, give me a ballpark. Are we doing apples to apples, or are we – are
you in Yankee Stadium and we’re in the Oakland Coliseum?”246 He was then asked, “So is that
usually you asking them how much they make or them asking you what the ballpark is for the
position, or could it be either way?” He replied, “It could be either way. But generally speaking,
I like to leave it up to them to tell me what their experiences are. So … yeah, I mean, it could be
either way”.247

244

See for example, Lazear and Rosen (1981).
Powerpoint, Candidate Generation, Intuit, December 12, 2006, INTUIT_034255, exhibit 2135.25.
246
Deposition of Mr. Chris Galy, Intuit, March 20, 2013, page 165.
247
Deposition of Mr. Chris Galy, Intuit, March 20, 2013, page 166.
245

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XII.

Given the Defendants’ Formalized Pay Structures and Compensation Design,
Effects on Compensation Could be Widely Felt
237.

Given the defendants’ formalized pay structures and compensation design as well

as issues of equity and fairness present in the defendant firms, there can be widespread and
systematic effects on compensation connected to the do-not-call agreements.
238.

Elsewhere in this report, it is documented that the defendant firms had formalized

compensation systems. It is also documented that the defendant firms were interested in internal
equity and issues of fairness. It is also documented how pay changed at defendant companies. A
direct impact on pay could occur if an employee did not receive a cold call, or if the upward
wage pressures on any of the employees in related groups or job families were disrupted.
239.

One way that pay can be lowered at defendant firms for nearly all workers has to

do with the “top” workers. The defendants were very interested in attracting and retaining many
extraordinary workers. The defendant firms include very well-known and prestigious brands for
employees. Some of the cold-calling restrictions were clearly targeted to this very high-end type
of worker. I have shown previously that it is straightforward to show that cold-calling can have a
direct impact on individual workers. Since the “top of the box” is, therefore, lowered in the
presence of cold-calling restrictions, the entire box may be as well, thus effecting nearly all other
workers. But, again, the restrictions need not only affect the highest paid workers for calling
restriction to have effects on others.
240.

Another interesting way in which wages can be influenced is external market

data. Here, there is evidence that defendants benchmark their data to external sources, most
commonly Radford or Croner. But here, to the extent that pay is lowered at other firms through
anti-competitive and other behavior of firms, the market data they use for their own structure will

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be lower. And, as a result, their own pay levels will be lower than they would be in the absence
of such agreements.
XIII. The Technical Class
241.

My understanding of the case is that the plaintiffs originally proposed two types

of potential employee classes. The first has been called the “All-Salaried Employee Class” and
the second has been called the “Technical Class”. My understanding is that the “Technical
Class” is defined in Appendix B of Edward Leamer’s expert report. My findings above apply to
both potential classes. However, I turn now to a specific examination of the proposed technical
class.
242.

In reviewing that list of titles included in the proposed “technical class,” I

observed that it includes “Software Engineers,” “Hardware Engineers and Component
Designers,” and “Employees classified as technical professionals by their employers.” Note that
the following are not included among the “technical class”: employees in “marketing,
accounting, finance, operations, etc.,” “senior executives,” and “non-US” employees, among
others.248 I have examined the definition of the “technical” class and see it as distinct from the
“all-salaried class”. It also seems to me to be a reasonable definition of the technical class based
on the Defendants’ job families for their technical workers.249
243.

It is common to have multiple job titles within job families. Similar jobs, job

titles and occupations are often grouped within the same job family. Milkovich, Newman and
Gerhart (2014) discuss one example of a way to categorize job families, jobs and tasks. They
show a figure where display the relationships among job families, jobs and tasks. They indicate

248
249

Expert Report of Edward E. Leamer, October 3, 2012, pages 74-7.
Expert Report of Edward E. Leamer, October 3, 2012, pages 74-7.

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that a “job family” is a “[g]rouping of related jobs with broadly similar content; e.g., marketing,
engineering, office support, technical”.250
244.

The job families as presented in Appendix B of Edward Leamer’s expert report

also appear to have appropriate types of job titles grouped together, in a way that would be
reasonable from the perspective of compensation design.
245.

I understand that all members of the “technical class” are also members of the

“all-salaried class” but, of course, not all members of the “all salaried class” are members of the
“technical class”.
246.

Based on my review of the evidence and my expertise in compensation design,

my belief is that although the restrictions could affect all or nearly all salaried workers, there was
more concentration and emphasis on the technical class.
XIV. Conclusions
247.

Based on the documents I have considered and my knowledge of labor markets

and compensation systems I have a number of conclusions. These views are expressed in the
report and some are summarized here.
248.

The defendants had formalized compensation systems. These include using

market surveys, having clear structures, using market pay lines, grades and many other features
of formalized compensation systems.
249.

The defendants made use of the ideas of compensation beyond salary. These

other forms of compensation include components such as bonuses and stock.

250

Milkovich, Newman and Gerhart (2014), page 104.

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250.

Issues of internal equity and equity in general were important to the defendant

firms. Whether they used the terms or not, the concepts of internal equity and also generally
treating similar employees similarly were important to defendant firms.
251.

There is documented evidence that pay moved in defendant firms in systematic

and structured ways.
252.

A compensation system that includes pay for performance is not mutually

exclusive from one that takes internal equity into account.
253.

Restrictions on cold-calling clearly had impacts on employees among the

defendant firms. In particular, restrictions on cold-calling hamper compensation levels for
employees. The restrictions could be expected to hamper levels of compensation for those who
would have been cold-called and for all or nearly all salaried employees of defendant firms.
254.

Agreements such as restrictions on cold-calling could be expected to limit and

have negative consequences on employee compensation for those workers directly involved and
for nearly all employees. Given the formalized pay structures and compensation design in
defendant firms nearly all salaried employees could be expected to have pay that would
otherwise be higher.
255.

The formalized systems in place at the defendants relied on structures, external

data from the market and the like, and notions of equity were present at defendants. As a result,
those effects cycle on to other employees and their levels of compensation. Therefore, the
formal compensation structures could be expected to lead to an effect on nearly all class
members.
256.

Although I have not been asked to estimate the magnitude of damages in this

case, based on my knowledge of compensations systems and the materials considered, I believe

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that agreements against cold calling, such as the agreements at issue in this case, are predicted to
suppress the compensation of all or nearly all members of plaintiffs’ proposed Technical
Employee Class, including those with different job titles.
257.

I reserve the right to supplement this report in view of any new material or

information provided to me after the date of this report.

Kevin F. Hallock
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APPENDIX A
Kevin F. Hallock CV

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KEVIN F. HALLOCK

April 2013

OFFICE

HOME

Cornell University
256 Ives Faculty Building
Ithaca, NY 14853
607 255-3193 (phone)
607 255-4496 (fax)
e-mail: [e-mail]
web: www.ilr.cornell.edu/ics
www.economics.cornell.edu

103 Harvard Place
Ithaca, NY 14850
607 319-0545
Born: March 10 1969, Palo Alto, CA
Married: Tina Hallock in 1991
Children: Emily 1994, Tyler 1998

CURRENT POSITIONS
Donald C. Opatrny ’74 Chair of the Department of Economics, Cornell University (2012 –
present)
Joseph R. Rich ’80 Professor, Cornell University (2011 – present)
Professor, Department of Economics, Cornell University (2011 – present)
Professor, Department of Human Resource Studies, Cornell University (2007 – present)
Director, Institute for Compensation Studies (ICS), Cornell University (2009 – present)
Compensation Committee Member, Guthrie Health, Sayre PA (2012 – present)
House Fellow, Carl Becker House, Cornell University (2011 – present)
Research Associate, Labor Studies, National Bureau of Economic Research (2003 - present)
Member, Board of Directors of Society of Certified Professionals, WorldatWork (2012 - present)
Faculty Fellow, Atkinson Center for a Sustainable Future (ACSF), (2012 – present)
Distinguished Principal Researcher, The Conference Board (2011 – present)
Fellow, Stanford University Center for the Study of Poverty and Inequality (2006 – present)
Faculty Affiliate, Center for the Study of Inequality, Cornell University (2007 – present)

EDUCATION
Princeton University – Ph.D. Economics, 1995.
Princeton University – M.A. Economics, 1993.
University of Massachusetts at Amherst – B.A. Economics, Summa Cum Laude, 1991.
Hopkins Academy, Hadley Massachusetts, Valedictorian, 1987.

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OTHER AND PREVIOUS POSITIONS
Chair, Department of Labor Economics, Cornell University (2010 – 2011)
Associate Chair, Department of Economics, Cornell University (2011 – 2012)
Professor, Department of Labor Economics, Cornell University (2007 – 2011)
Chair, Cornell University Financial Policy Committee (2007 – 2008)
Director of Research, Center for Advanced Human Resource Studies (CAHRS), Cornell
University (2007 – 2012)
Senior Fellow, Executive Compensation, Board Compensation and Board Practices, The
Conference Board (2008 – 2011)
Member, Board of Directors, WorldatWork (2009 – 2011)
Member, WorldatWork Executive Compensation Advisory Board (2007 – 2009)
Faculty Member, Graduate Field of Economics, Cornell University (2005 - present)
Faculty Member, Graduate Field of Industrial & Labor Relations, Cornell University (2006 –
present)
Associate Professor of Human Resource Studies, ILR School, Cornell University (2005 - 2007)
Acting Chair, Department of Human Resource Studies, ILR School, Cornell University (Fall
2006)
Associate Professor of Economics and of Labor and Industrial Relations, University of Illinois at
Urbana-Champaign (2001 – 2005)
Associate Professor of Finance, University of Illinois at Urbana-Champaign (2002 – 2005)
Co-Director, Center for Human Resource Management, University of Illinois (2004 – 2005)
Visiting Associate Professor, Institute of Government and Public Affairs, University of Illinois at
Urbana-Champaign (2005)
Research Consultant, Research Department, Federal Reserve Bank of Chicago (2003 – 2005)
Visiting Assistant Professor, Department of Economics and Research Associate, Industrial
Relations Section, Princeton University (1998 - 1999)
Assistant Professor of Economics and of Labor and Industrial Relations, University of Illinois at
Urbana-Champaign (1995 - 2001)

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HONORS AND FELLOWSHIPS
John T. Dunlop Outstanding Young Scholar Award, Industrial Relations Research Association
(Now Labor and Employment Relations Association), 2004.
Outstanding Teaching Award (small class), University of Illinois Economics Graduate Student
Association, 2001-2002.
Faculty Teaching Excellence Award, University of Illinois Institute of Labor and Industrial
Relations, 2000.
Outstanding Teaching Award (small class), University of Illinois Economics Graduate Student
Association, 2000-2001.
Albert Rees Prize for Best Dissertation in Labor Economics from Princeton in the Last Six Years
(awarded every two years), 1999.
University of Illinois College of Commerce and Business Administration Award for Excellence
in Research (first annual Assistant Professor award), 1999.
University of Illinois list of teachers ranked excellent by their students, 1997, 1998, 1999, 2000,
2002.
Princeton University Industrial Relations Section Fellowship, September 1991-May 1995.
United States Department of Education Jacob K. Javits Fellowship, September 1991-May 1995.
Massachusetts William Field Alumni Scholar, 1991.
Phi Beta Kappa, 1990.
Valedictorian, Hopkins Academy, Hadley Massachusetts, 1987.
Paul Brown Senior Baseball Award, Hopkins Academy, Hadley Massachusetts, 1987.
Massachusetts High School State Baseball Champions, 1985. Third base, Hopkins Academy.

BOOKS
Pay: Why People Earn What They Earn and What You Can Do Now to Make More, Cambridge
University Press September 2012.
Managing Layoffs: Why Firms Fire Workers and How it Affects the Bottom Line, Cambridge
University Press, under contract.
The Economics of Executive Compensation, Volume II, (co-editor with Kevin J. Murphy),
Edward Elgar Publishing Limited, Cheltenham, England, 1999.
The Economics of Executive Compensation, Volume I, (co-editor with Kevin J. Murphy), Edward
Elgar Publishing Limited, Cheltenham, England, 1999.

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BOOKS (continued)
Economic Institutions and The Demand and Supply of Labor: The Collected Essays of Orley
Ashenfelter, Volume III, editor, Edward Elgar Publishing Limited, Cheltenham, England, 1997.
Education, Training and Discrimination: The Collected Essays of Orley Ashenfelter, Volume II,
editor, Edward Elgar Publishing Limited, Cheltenham, England, 1997.
Employment, Labor Union, and Wages: The Collected Essays of Orley Ashenfelter, Volume I,
editor, Edward Elgar Publishing Limited, Cheltenham, England, 1997.
Labor Economics, Volume IV: Labor Market Discrimination, Labor Mobility and Compensating
Wage Differentials, (co-editor with Orley Ashenfelter), Edward Elgar Publishing Limited,
Cheltenham, England, 1995.
Labor Economics, Volume III: Unemployment, Trade Unions and Dispute Resolution, (co-editor
with Orley Ashenfelter), Edward Elgar Publishing Limited, Cheltenham, England, 1995.
Labor Economics, Volume II: Employment, Wages and Education, (co-editor with Orley
Ashenfelter), Edward Elgar Publishing Limited, Cheltenham, England, 1995.
Labor Economics, Volume I: Labor Supply and Labor Demand, (co-editor with Orley
Ashenfelter), Edward Elgar Publishing Limited, Cheltenham, England, 1995.

PUBLISHED AND FORTHCOMING PAPERS
“Data Improvement and Labor Economics,” Journal of Labor Economics, 31(2), Part 2, April
2013, S1-S16.
“Adverse Selection and Incentives in an Early Retirement Incentive Program,” (with Kenneth
Whelan, Ronald Ehrenberg and Ronald Seeber), Research in Labor Economics, Volume 36, 159190, 2012.
“Job Loss and Effects of Firms and Workers,” (with Michael Strain and Doug Webber), in Cary
Cooper, Alankrita Pandey and James Quick eds. Downsizing: Is Less Still More?, Cambridge
University Press, 2012.
“New Data for Answering Old Questions Regarding Employee Stock Options,” (with Craig
Olson), in Labor and The New Economy, Katharine G. Abraham, James R. Spletzer and Michael
Harper, editors, National Bureau of Economic Research, 2010.
“Executive Pay and Firm Performance: Methodological Considerations and Future Directions,”
(with Beth Florin and Douglas Webber), Research in Personnel and Human Resources
Management, 2010.
“The Geography of Giving: The Effect of Corporate Headquarters on Local Charities,” (with
David Card and Enrico Moretti), Journal of Public Economics, April 2010, 94(3), 222 -234.
“CEO Pay for Performance Heterogeneity: Examples Using Quantile Regression,” (with Clayton
Reck and Regina Madalozzo), Financial Review, February 2010, 1-19.

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PUBLISHED AND FORTHCOMING PAPERS (continued)
“Job Loss and the Fraying of the Implicit Employment Contract,” Journal of Economic
Perspectives, 23(4), Fall 2009, 69-93.
“The Changing Relationship Between Job Loss Announcements and Stock Prices: 1970-1999,”
(with Henry Farber), Labour Economics, 16(1), January 2009, 1-11.
“Layoffs in Large U.S. Firms from the Perspective of Senior Management,” Research in
Personnel and Human Resources Management, volume 25, 2006.
“Assessing the Impact of Job Loss on Workers and Firms,” (with Kristin Butcher), Chicago Fed
Letter, Federal Reserve Bank of Chicago, April 2006.
“Mass Layoffs and Management Turnover,” (with Sherrilyn Billger), Industrial Relations, 44(3),
July 2005.
“Bringing Together Policymakers, Researchers, and Practitioners to Discuss Job Loss,” (with
Kristin Butcher), Economic Perspectives, Federal Reserve Bank of Chicago, 2nd Quarter, 2005.
“Does Managed Care Change the Management of Nonprofit Hospitals? Evidence from the
Executive Labor Market,” (with Marianne Bertrand and Richard Arnould), Industrial and Labor
Relations Review, 58(3), April 2005.
“Job Loss: Causes, Consequences, and Policy Responses,” (with Kristin F. Butcher), Chicago
Fed Letter, Federal Reserve Bank of Chicago, Number 207, October 2004.
“Managerial Pay in Nonprofit and For-Profit Organizations,” in Improving Leadership in
Nonprofit Organizations, Sarah Smith-Orr and Ron Riggio, editors, Jossey-Bass, 2004, 76 – 101.
“Managerial Pay and Governance in American Nonprofits,” Industrial Relations, 41(3), July
2002, 377-406.
“When Unions ‘Mattered’: Assessing the Impact of Strikes on Financial Markets: 1925-1937,”
(with John DiNardo), Industrial and Labor Relations Review, 55(2), January 2002, 219 - 233.
“Quantile Regression,” (with Roger Koenker), The Journal of Economic Perspectives, 15(4), Fall
2001, 143-156.
“The Gender Gap in Top Corporate Jobs,” (with Marianne Bertrand), Industrial and Labor
Relations Review, 55(1), October 2001, 3-21.
“Individual Heterogeneity in the Returns to Schooling: Instrumental Variables Quantile
Regression using Twins Data,” (with Omar Arias and Walter Sosa), Empirical Economics, 26(1),
March 2001, 7-40. Reprinted in Economic Applications of Quantile Regression, Bernd
Fitzenberger, Roger Koenker, and Jose A. F. Machado, Editors, Physica-Verlag.
“Compensation in Nonprofit Organizations,” Research in Personnel and Human Resources
Management, edited by Gerald R. Ferris, Elsevier Science, Volume 19, 2000, 243-294.

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PUBLISHED AND FORTHCOMING PAPERS (continued)
“The Timeliness of Performance Information in Determining Executive Compensation,” (with
Paul Oyer), Journal of Corporate Finance, 5(4), December 1999, 303-321.
“Capital Markets and Job Loss: Evidence from North America,” (with Henry Farber), Wirtschafts
Politische Blatter, 46(6), December 1999, 573-577.
“Dual Agency: Corporate Boards with Reciprocally Interlocking Relationships,” in Executive
Compensation and Shareholder Value: Theory and Evidence, edited by Jennifer Carpenter and
David Yermack, Kluwer, 1999, 55-75.
“Changing Stock Market Response to Announcements of Job Loss: Evidence from 1970-1997,”
(with Henry Farber), Proceedings of the Industrial Relations Research Association, May 1999,
26-34.
“Introduction,” in The Economics of Executive Compensation, Volume I, (edited by Kevin F.
Hallock and Kevin J. Murphy), Edward Elgar Publishing Limited, Cheltenham, England, 1999,
pp. ix - xxviii.
“Layoffs, Top Executive Pay, and Firm Performance,” The American Economic Review, 88(4),
September 1998, 711-723.
“Discrimination by Gender and Disability Status: Do Worker Perceptions Match Statistical
Measures?” (with Wallace Hendricks and Emer Broadbent), Southern Economic Journal, 65(2),
October 1998, 245-263.
“Reciprocally Interlocking Boards of Directors and Executive Compensation,” Journal of
Financial and Quantitative Analysis, 32(3), September 1997, 331-344. Reprinted in Governance,
Directors, and Boards, Mahmoud Ezzamel, editor, Edward Elgar Publishing Limited, UK.
“Introduction,” in Employment, Labor Unions and Wages: The Collected Essays of Orley
Ashenfelter, Volume I, Edward Elgar Publishing Limited, Cheltenham, England, ix – xxii.
“Seniority and Monopsony in the Academic Labor Market: Comment,” The American Economic
Review, 85(3), June 1995, 654-657.

WORKING PAPERS
“Employees’ Choice of Method of Pay,” (with Craig Olson), February 2012.
“Executive Compensation in American Unions,” (with Felice Klein), January 2012.
“Senior HR Leaders in the “Top 5”: Evidence on Pay, Relative Pay, and Performance Using Data
from 1,500 Firms Over a Decade,” (with Matthew Allen and John Haggerty), January 2008.
“The Value of Stock Options to Non-Executive Employees,” (with Craig Olson), March 2007.
“Are Formal Corporate News Announcements Still Newsworthy?: Evidence from 30 Years of US
Data on Earnings, Splits, and Dividends” (with Farzad Mashayekhi), July 2006.

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WORKING PAPERS (continued)
“The Gender Pay Gap for Managers in Nonprofits,” January 2002.
“Unions and the Labor Market for Managers,” (with John DiNardo, and Jorn-Steffen Pischke),
August 2000.
“A Simple Empirical Model of Welfare or Work Incentives for Single Mothers,” June 1995.

BOOK REVIEWS
Review of Personnel Economics in Imperfect Labour Markets, by Pietro Garibaldi, Oxford
University Press, Journal of Economic Literature, December 2007.
Review of Pay Without Performance: The Unfulfilled Promise of Executive Compensation, by
Lucian Bebchuk and Jesse Fried, Harvard University Press, Industrial and Labor Relations
Review, 59(4), July 2006, 672-674.

OTHER WORK IN PROGRESS
“The Pay Gap and the Total Compensation Gap by Disability Status,” (with Xin Jin and Linda
Barrington)
“Pay and Performance for University Presidents,” (with Orley Ashenfelter, Sherrilyn Billger and
Ronald Ehrenberg)
“The Illinois Historical Salary Census,” (with David Card)
“Estimating the Expected Cost of Employee Stock Options” (with Craig Olson)
“Job Matching and Employment Duration” (with Todd Elder)
“The Night Shift” (with Darren Lubotsky and Douglas Webber)
“Quantile Regression for Management”
“Sleepy Traders and Stock Prices” (with Lawrence DeBrock and Joe Price)

RESEARCH REPORTS
The 2011 U.S. Top Executive Compensation Report, (with Judit Torok), The Conference Board,
2011.
U.S. Salary Increase Budgets for 2012, (with Judit Torok), The Conference Board, 2011.
The 2010 U.S. Top Executive Compensation Report, (with Judit Torok),The Conference Board,
2010.
Top Executive Compensation in 2009, (with Judit Torok), The Conference Board, 2010.

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RESEARCH REPORTS (continued)
Directors’ Compensation and Board Practices in 2009, (with Matteo Tonello and Judit Torok),
The Conference Board, 2010.
Top Executive Compensation 2009 – Key Findings, (with Judit Torok), The Conference Board,
December 2009.
Top Executive Compensation in 2008, (with Judit Torok), The Conference Board, 2008.
Directors’ Compensation and Board Practices in 2008, (with Matteo Tonello and Judit Torok),
The Conference Board, 2008.
Top Executive Compensation 2008 – Key Findings, (with Judit Torok), The Conference Board,
December 2008.
Directors’ Compensation and Board Practices Report 2007, (with Linda Barrington and Judit
Torok), The Conference Board, 2007.
Top Executive Compensation 2007, (with Linda Barrington and Lisa Hunter), The Conference
Board, 2007.
2007 Report on Top Executive Compensation—Key Findings, (with Linda Barrington and Lisa
Hunter), The Conference Board, 2007.
Layoffs, Top Executive Pay and Firm Performance, United States Department of Labor, 1996

COLUMNS
“Pay in Nonprofits,” Workspan, April 2013, 12-13.
“Valuing Employee Stock Options,” Workspan, March 2013, 10-11.
“Pay and Relative Income Within Couples,” Workspan, February 2013, 12-13.
“Presidential Pay,” Workspan, January 2013, 12-13.
“Top Athlete Pay,” Workspan, December 2012, 12-13.
“Economic Effects of the Minimum Wage,” Workspan, November 2012, 12-13.
“How The Olympics Remind Us About Compensation,” Workspan, October 2012, 12-13.
“CEOs Off the Clock,” Workspan, September 2012, 13-14.
“Vacation as Compensation,” Workspan, August 2012, 13-14.
“Paying Professors” Workspan, July 2012, 12-13.
“Does Graduating in a Bad Economy Penalize Your Pay for Life?” Workspan, June 2012, 13-14.

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COLUMNS (continued)
“Governance and Executive Pay in Nonprofits?” Workspan, May 2012, 13-14.
“Why Do We Tip?” Workspan, April 2012, 12-13.
“Massive Kinked Bonuses,” Workspan, March 2012, 12-13.
“Go Big: The Firm-Size Pay (and Pay-Mix) Effect,” Workspan, February 2012, 12-13.
“Nothing Lasts Forever: A Different Way to Structure Severance,” Workspan, January 2012, 12-13.
“Is There Deadweight Loss in Holiday Rewards?” Workspan, December 2011, 11-12.
“Pay System Gender Neutrality,” Workspan, November 2011, 11-12.
“Does More Education Cause Higher Earnings,” Workspan, October 2011, 12-13.
“Say On Pay and Compensation Design,” Workspan, September 2011, 10-11.
“Lessons in Pay Design from the Farm,” Workspan, August 2011, 11-12.
“Linking Compensation and Job Losses During a Recession,” Workspan, July 2011, 12-13.
“Does That Pay Practice Really Have Any Impact?” Workspan, June 2011, 12-13.
“Pay Ratios and Inequality,” Workspan, May 2011, 14-16.
“Pay Secrecy and Relative Pay,” Workspan, April 2011, 10-11.
“Motivating with Efficiency Wages and Delayed Payments,” Workspan, March 2011, 10-11.
“The Relationship Between Company Size and CEO Pay,” Workspan, February 2011, 10-11.
“The Disconnect Between Employer Cost and Employee Value,” Workspan, January 2011, 10-11.

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REFEREE AND EDITORIAL SERVICE
(Advisory Board, Compensation and Benefits Review, 2012 – present)
(Advisory Board, Journal of People and Organizational Effectiveness, 2012 – present)
(Associate Editor, Journal of Labor Economics, 2008 – 2012)
(Associate Editor, Labour Economics, 2008 – present)
(Associate Editor, Economics Bulletin, 2005 – July 2010)
(Editorial Board, Industrial and Labor Relations Review, 2006 – present)
Academy of Management Journal, Advances in the Economics of Sport, American Economic
Journal: Applied Economics, American Economic Review, British Journal of Industrial
Relations, Economic Theory, Eastern Economic Review, Economic Inquiry, Economic Journal,
Economics Bulletin, Economics of Education Review, Economics and Politics, Economics
Letters, Education and Finance Policy, Empirical Economics, Explorations in Economic History,
Financial Review, Industrial and Labor Relations Review, Industrial Relations, International
Economic Review, International Journal of Manpower, International Journal of Organizational
Analysis, International Migration Review, International Review of Economics and Finance,
Journal of Business, Journal of Business and Economic Statistics, Journal of Corporate Finance,
Journal of Human Resources, Journal of Economic Psychology, Journal of Finance, Journal of
Industrial Economics, Journal of Labor Economics, Journal of Law Economics and Organization,
Journal of Political Economy, Journal of Public Economics, Journal of Urban Economics, Labour
Economics, The Manchester Review, Nonprofit and Voluntary Sector Quarterly, Nonprofit
Management and Leadership, Quarterly Journal of Business and Economics, Quarterly Journal of
Economics, Quarterly Journal of Economics and Finance, Review of Economics and Statistics
National Science Foundation, Social Science and Humanities Research Council, United States
Census Bureau, Various Publishers

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GRANTS
United States Department of Education, National Institute on Disability and Rehabilitation
Research (NIDRR), Rehabilitation Research Training Center (RRTC) on Employer Practices
Related to Employment Outcomes for Individuals with Disabilities (co-PI, with Susanne Bruyere
and Linda Barrington), $4 million, 2010 – 2015.
Compensation in Asia, (CAHRS), 2011 – 2012.
International Compensation, (CAHRS), 2010- 2011.
Costs of Compensation versus Value to the Organization (CAHRS), 2009 – 2010.
Why Managers Fire Workers and How it Affects the Bottom Line (CAHRS), 2008-2009.
Managing Layoffs, Cornell Center for Human Resource Management (CAHRS), 2007-2008.
Stock Options, (with Craig Olson), Cornell Center for Human Resource Management (CAHRS),
2006-2007.
When and Why Do Firms Make Layoffs?, Alfred P. Sloan Foundation, 2001 - 2003.
The Illinois Historical Salary Study, (with David Card), University of Illinois Campus Research
Board, 2003.
What Happens to Firms When Workers are Let Go?, Illinois Center for Human Resource
Management, 2001-2002.
Stock Options for Employees in Large U.S. Firms, Illinois Center for Human Resource
Management, (with Craig Olson), 2001-2002.
Studies in Executive Compensation, University of Illinois Campus Research Board, 2001-2002.
What Drives Nonprofits? Evidence from Managerial Pay, Performance, and Market Competition
in Nonprofit Hospitals, National Bureau of Economic Research, (with Richard Arnould, and
Marianne Bertrand), 1999-2000.
Computation Problems in Applied Economics, Intel Corporation, (with Lawrence DeBrock
and Roger Koenker), 1998.
Determinants of Managerial Compensation in American Charities, American Compensation
Association, 1997-1998.
Unions and Managerial Pay, American Compensation Association, (with John DiNardo and JornSteffen Pischke), 1997-1998.
How to Make Incentive Pay Programs More Successful: Linking Sales Compensation Plans to
Firm Performance, Center for Human Resource Management, University of Illinois, (with Paul
Oyer), 1997-1998.
Executive Compensation, Firm Layoffs, and Firm Performance, United States Department of
Labor, 1996.
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SEMINARS AND PRESENTATIONS
University of Arizona, Brigham Young University, University of California at Berkeley, University
of California at Santa Barbara, Case Western Reserve University, University of Chicago, ClaremontMcKenna College, Cornell University, Harvard University, University of Illinois at Chicago,
University of Illinois at Urbana-Champaign, Illinois State University, Kansas State University,
University of Konstanz, Marquette University, Massachusetts Institute of Technology, McGill
University, University of Michigan, Michigan State University, University of Missouri, New York
University, Northwestern University, The Ohio State University, Princeton University, University of
Pennsylvania, Indiana University – Purdue University at Indianapolis, Queen’s University, University
of Rochester, Stanford University, Texas A&M University, University of Wisconsin at Madison,
University of Wisconsin at Milwaukee, Yale University
American Economic Association, Econometric Society, European Society of Labour Economists,
Industrial Relations Research Association, Labor and Employment Relations Association, National
Bureau of Economic Research, Society of Labor Economists, WorldatWork

TEACHING
Ph.D.Students advised, department, year of degree, and initial placement (* chair of committee):

Pablo Acosta*, Economics, 2006, World Bank
Ji-Young Ahn, ILIR, Illinois, 2009, Ehwa Women’s College, South Korea
Carole Amidon, Economics, 2002, ERS Group, Florida
Vic Anand, Accounting, 2013 (expected), Emory University
Michelle Arthur, ILIR, 2000, Purdue University
David Balan*, Economics, 2000, Federal Trade Commission
Sherrilyn Billger*, Economics, 2000, Union College
Paul Byrne, Economics, 2003, Wabash College
John Deke*, Economics, 2000, Mathematica Policy Research, Princeton NJ
Emre Ekinci, Economics, 2012, Universidad Carlos III
Todd Fister*, ILIR, 2003, Kimberly-Clark, Atlanta
R. Kaj Gittings, Economics, 2009 expected, Louisiana State University
Lynn Gottschalk, Economics, 2005 Federal Trade Commission
Weishi (Grace) Gu, Economics (current)
Juliana Guimaraes*, Economics, 2001, Universidade Nova de Lisboa, Portugal
John Haggerty, HR Studies, 2010, Cornell University
Dan Hanner, Economics, 2005, Federal Trade Commission
Jeffrey Hemmeter, Economics, 2004, University of California, Davis
Xin Jin, Economics (current)
Kandice Kapinos, ILIR, 2007, St. Olaf College
David Kaplan, ILIR, 2000, James Madison University
GiSeung Kim, Economics, 2001, LG Economics Research Group, Korea.
Elizabeth Kiss, Ag. Economics, 2000, Purdue University
Felice Klein*, HR Studies, 2012, Michigan State University
Nolan Kopkin, Economics (2013), University of Wisconsin, Milwaukee.
Gregory Kordas, Economics, 2000, University of Pennsylvania

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TEACHING (continued)
Fidan Kurtulus*, Economics, 2007, University of Massachusetts at Amherst
Regina Madalozzo*, Economics, 2002, Brazilian Institute of Capital Markets
Farzad Mashayekhi*, Economics, 2003, Moody’s K M V, San Francisco
Catherine McClean, Economics, 2012, University of Pennsylvania
Daniel Morillo, Economics, 2000, PanAgora Asset Management, Boston
Ben Ost, Economics, 2011, University of Illinois at Chicago
Heather Radach, Economics, 2001, Lexecon, Chicago
Clayton Reck*, Economics, 2004, ERS Group, Florida.
Eduardo Ribeiro, Economics, 1995, Universidade Federal do Rio Grande do Sul, Brazil
Laura Ripani*, Economics, 2004, World Bank.
Patricia Simpson, ILIR, 1997, Loyola University, Chicago
Michael Strain*, Economics, 2012, American Enterprise Institute
Mary Taber, ILIR, 1999, Skidmore College
Maria Tannuri, Economics, 2000, Universidade de Brasilia, Brazil
Rosemary Walker, Economics, 2000, Wabash College
Ying Wang, Economics (current)
Douglas Webber, Economics, 2012, Temple University
Leigh Wedenoja, Economics (current)
Olga Yakusheva*, Economics, 2005, Marquette University
Chen Zhao, Economics, 2013, Analysis Group
Courses Taught:
PAY (undergraduate) at Cornell
Managing Compensation (MILR) at Cornell
Executive Compensation (MILR) at Cornell
Job Loss (Undergraduate) at Cornell
Freshman Colloquium (Undergraduate) at Cornell
Finance for Human Resources (M.H.R.I.R.) at Illinois and (MILR) at Cornell
Labor Economics for Managers (M.H.R.I.R.) at Illinois
Managerial Economics (Masters of Science in International Finance) at Illinois
Labor Economics I (Ph.D.) and Labor Economics II (Ph.D.) at Illinois
Applied Econometrics (Masters of Science in Policy Economics) at Illinois
Microeconomic Principles (Undergraduate) at Illinois
Labor Problems (Undergraduate) at Illinois
Labor Economics (Undergraduate) at Illinois and Princeton

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UNIVERSITY SERVICE
2012 – 2013 (Cornell)
Donald C. Opatrny ’74 Chair of the Department of Economics
Director, Institute for Compensation Studies (ICS)
Member, Search Committee for the Dean of the College of Arts and Sciences
Member, Department of Economics Recruiting Committee
Member, Cornell University Council on Mental Health and Welfare
2011 – 2012 (Cornell)
Director, Institute for Compensation Studies (ICS)
Chair, Recruiting Committee, Department of Economics
Associate Chair, Department of Economics
Director of Research and Board Member, Center for Advanced HR Studies (CAHRS)
Member, Cornell University Council on Mental Health and Welfare
2010 – 2011 (Cornell):
Chair, Department of Labor Economics
Director, Institute for Compensation Studies (ICS)
Chair, Recruiting Committee, Department of Labor Economics
Recruiting Committee, Department of Policy Analysis and Management
Recruiting Committee, Department of Human Resource Studies
Director of Research and Board Member, Center for Advanced HR Studies (CAHRS)
Member, Cornell University Council on Mental Health and Welfare
Member, ILR Admissions Committee
2009 – 2010 (Cornell):
Provost’s Budget Model Task Force
Campus Task Group on Student Services
Chair, ILR Task Group on Student Services
Institute for the Advancement of Economics at Cornell
Director, Compensation Research Initiative (CRI)
Labor Economics Recruiting Committee
Director of Research, Center for Advanced Human Resource Studies (CAHRS)
Center for Advanced Human Resource Studies (CAHRS) Board
2008 – 2009 (Cornell):
Cornell University Financial Policy Committee
Institute for the Advancement of Economics at Cornell
Director of Research, Center for Advanced Human Resources Studies (CAHRS)
Undergraduate Committee, ILR School
Center for Advanced Human Resources Studies (CAHRS) Board
2007-2008 (Cornell):
Chair, Cornell University Financial Policies Committee
Economics Field Review Committee
Director of Research, Center for Advanced Human Resource Studies (CAHRS)
Review Panel for Cornell Institute for the Social Sciences
Center for Advanced Human Resource Studies (CAHRS) Board
Undergraduate Committee, ILR School
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UNIVERSITY SERVICE (continued)
2006 – 2007 (Cornell):
Interim-Chair, Human Resource Studies Department, ILR School Cornell (Fall)
Cornell University Financial Policies Committee (2006 – 2009), Co-Chair (2006 - 2007)
Labor Economics Search Committee
Review Panel for Cornell Institute for the Social Sciences
Center for Advanced Human Resource Studies (CAHRS) Board
Undergraduate Committee, ILR School
2005 – 2006 (Cornell):
Campus Financial Policies Committee (Spring)
Committee on Faculty Recruitment and Retention in the Social Sciences
ILR Committee to Evaluate the Math Requirement
Departmental Tenure Review Committee
Center for Advanced Human Resource Studies (CAHRS) Board
2004 – 2005 (Illinois):
ILIR On-Campus Committee, Chair
ILIR Executive Committee
University of Illinois Center for Human Resource Management, Co-Director
2003 – 2004 (Illinois):
Economics Junior Recruiting Committee, Chair
Economics Advisory Committee to the Head
ILIR On-Campus Committee, Chair
University of Illinois Executive Board of Center for Human Resource Management
2002 – 2003: (Illinois) On sabbatical (fall)
ILIR Executive Committee
Economics Search Committee for new Head of Department
University of Illinois Executive Board of Center for Human Resource Management
Campus Admissions Committee
College of Business Educational Policy Committee
2001 – 2002 (Illinois):
ILIR Executive Committee
ILIR Ph.D. Advisory Committee
Economics/LIR Faculty Search Committee
Economics Capricious Grading Committee
Economics Labor Seminar
College of Commerce Educational Policy Committee
College of Commerce Teaching Advancement Board
Campus Admissions Committee
University of Illinois Executive Board of Center for Human Resource Management
2000 – 2001 (Illinois):
ILIR Executive Committee
ILIR On-Campus Committee
Economics/ILIR Faculty Search Committee
Economics Advisory Committee to the Head

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UNIVERSITY SERVICE (continued)
1999 – 2000 (Illinois):
ILIR Ph.D. Advisory Committee
ILIR Speaker-Scholars Committee
Economics Advisory Committee to the Head
Economics Graduate Admissions Committee
Economics Labor Seminar
1998 – 1999: (On Leave all year at Princeton)
Economics/ILIR Faculty Search Committee
1997 – 1998 (Illinois):
ILIR Speaker-Scholars Committee
ILIR Long Distance Learning Committee
ILIR Admissions and Financial Aid Committee
Economics Faculty Search Committee
Economics Labor Seminar
1996 – 1997 (Illinois):
ILIR Ph.D. Advisory Committee
ILIR Speaker-Scholars Committee
ILIR On-Campus Committee
ILIR Computer Classroom Committee
Economics Advisory Committee to the Head
Economics Graduate Programs Committee
Economics Labor Seminar
1995 – 1996 (Illinois):
ILIR On Campus Committee, Speaker-Scholars Committee, Computer Classroom Committee

PROFESSIONAL SOCIETY SERVICE
Member, Board of Directors of the Society of Certified Professionals, WorldatWork, 2012 Member, Board of Directors, WorldatWork, 2009 - 2011
Board Member, WorldatWork Executive Compensation Advisory Board, 2007 - 2009
Member, Strategic Planning Committee, National Academy of Social Insurance, 2007-2008
Member, Awards Committee, Labor and Employment Relations Association, 2006 – 2010

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CONFERENCE ORGANIZATION
Emerging Scholars In Compensation Conference, Spring 2013, Ithaca NY (with Linda
Barrington)
21st Century Human Resource Management Practices and Their Effects on Firms and Workers:
ILIR Alumni Professorship Symposium, Institute of Labor & Industrial Relations,
University of Illinois, November 11-12, 2005 (with Craig Olson and Kathryn Shaw)
Job Loss: Causes, Consequences, and Policy Responses, Federal Reserve Bank of Chicago,
November 18-19, 2004 (with Kristin Butcher and Daniel Sullivan)

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APPENDIX B
Materials Considered Include The Following:
Papers or Books
Adams, J. Stacy, 1965, “Inequity in Social Exchange,” in L. Berkowitz, ed., Advances in
Experimental Social Psychology, 2, 267 – 299.
Card, David, 1999, “The Causal Effect of Education on Earnings,” in Orley Ashenfelter and
David Card, Eds., Handbook of Labor Economics. Volume #a, Elsevier, 1801 – 1863.
Card, David, 2001, “Estimating the Return to Schooling: Progress and Some Persistent
Econometrics Problems,” Econometrica, 69, 1127 – 1160.
Card, David, Alexandre Mas, Enrico Moretti, and Emmanuel Saez, 2012, “Inequality at Work:
The Effect of Peer Salaries on Job Satisfaction,” The American Economic Review, 102(6), 29813003.
Cardinal, Ken and Beth Florin, 2012, Handbook for Conducting Compensation and Benefits
Surveys, WorldatWork Press.
Hallock, Kevin F., 2012, Pay: Why People Earn What They Earn and What You Can Do Now to
Make More, Cambridge University Press.
Hallock, Kevin F. and Judit P. Torok, 2010, The 2010 U.S. Top Executive Pay Report, The
Conference Board, New York, N.Y.
Hungerford, Thomas and Gary Solon, 1987, “Sheepskin Effects in the Return to Education,”
Review of Economics and Statistics, 69(1), February, 175 – 177.
Levine, David I., 1993, “Fairness, Markets, and Ability to Pay: Evidence from Compensation
Executives,” The American Economic Review, 83(5), December, 1241-1259.
Lazear, Edward P. and Rosen, Sherwin. 1986, "Rank-Order Tournaments as Optimum Labor
Contracts”. Journal of Political Economy, 89(5), October 1981, 841-864.
Milkovich, George T. and Philip H. Anderson, 1972, “Management Compensation and Secrecy
Policies,” Personnel Psychology, 25, 293-302.
Milkovich, George T., Gerry M. Newman and Barry Gerhart, 2011, Compensation, 10th
Ediction, McGraw-Hill Irwin.
Milkovich, George T., Gerry M. Newman and Barry Gerhart, 2014, Compensation, 11th
Ediction, McGraw-Hill Irwin.

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93

Rosen, Sherwin S., 1986, “The Theory of Equalizing Differences,” in Orley Ashenfelter and
Richard Layard, Eds., The Handbook of Labor Economics, North Holland, 641 – 592.
Spence, Michael, 1973, “Job Market Signaling,” Quarterly Journal of Economics, 87(3), August,
355-374.
Weiss, Andrew, 1995, “Human Capital vs. Signaling Explanations for Wages,” Journal of
Economic Perspectives, 9(4), 133 – 154.

Data Sources and Other
I was provided access to all deposition transcripts and exhibits in the case. The following are
among the materials I considered:
2009 Croner Animation and Visual Effects Survey, January 8, 2009, PIX00001263, exhibit 119.
Document, HR Global Staffing, Manage Offer Module, Develop External Offer, document
Version 1.3, February 13, 2009, 76579DOC005963, exhibit 398.8.
Document from Intuit, Talent Acquisition Hiring Plan, INTUIT_007866, exhibit 1107.2.
Document, 2009 Salary Increase & LTI ‘Talking Points’, PIX00083585, exhibit, 1307.3
Declaration of Ms. Donna Morris of Adobe Systems, September 13, 2011.
Declaration of Ms. Michelle Maupin, January 17, 2013.
Declaration of Mr. Danny McKell, Intel, September 13, 2011.
Declaration of Ms. Donna Morris, September 13, 2011.
Deposition of Mr. David Alvarez, Apple, March 5, 2013
Deposition of Ms. Rosemary Arriada-Keiper, Adobe, March 28, 2013.
Deposition of Mr. Darrin Baja, Apple, March 1, 2013.
Deposition of Mr. Richard Bechtel, Apple, March 7, 2013.
Deposition of Dr. Shona Brown, January 30, 2013.
Deposition of Mr. Patrick Burke, Apple, February 26, 2013.
Deposition of Mr. Steven Burmeister, Apple, March 15, 2013.
Deposition of Dr. Ed Catmull, January 24, 2013.

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Deposition of Ms. Michelene Chau, Lucasfilm, February 21, 2013.
Deposition of Mr. Bruce Chizen, Adobe, March 15, 2013.
Deposition of Ms. Sharon Coker, LucasFilm, November 1, 2012.
Deposition of Ms. Deborah Conrad, Intel, November 21, 2012.
Deposition of Mr. Alan Eustace, February 27, 2013.
Deposition of Mr. Chris Galy, Intuit, March 20, 2013.
Deposition of Mr. Randall Goodwin, Intel, March 15, 2013.
Deposition of Mr. Digby Horner, Adobe, March 1, 2013.
Deposition of Ms. Renee James, Intel, March 22, 2013.
Deposition of Ms. Danielle Lambert, Apple, October 2, 2013.
Deposition of Mr. Alex Lintner, Intuit, March 25, 2013.
Deposition of Michelle Maupin, February 12, 2013.
Deposition of Ms. Lori McAdams, August 2, 2012.
Deposition of Mr. Daniel McKell, Intel, March 20, 2013.
Deposition of Ms. Jan van der Voort, February 5, 2013.
Deposition of Ms. Donna Morris, August 21, 2012.
Deposition of Ms. Patricia Murray, Intel, February 14, 2013.
Deposition of Mr. Shantanu Narayen, Adobe, February 28, 2013.
Deposition of Mr. Ron Okamoto, Apple, February 27, 2013.
Deposition of Mr. Paul Otellini, Intel, January 29, 2013.
Deposition of Ms. Stephanie Sheehy, Pixar, March 5, 2013.
Deposition of Mr. Brad Smith, Intuit, February 27, 2013.
Deposition of Mr. Mason Stubblefiled, Intuit, March 29, 2013.

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Deposition of Mr. Jeffrey Vijungco, Adobe, October 5, 2012.
Deposition of Mr. Frank Wagner, March 7, 2013.
Deposition of Ms. Sherry Whiteley, Intuit, March 14, 2013.
Email from Ms. Jan van der Voort, July 9, 2007, LUCAS00060705, exhibit 728.1
Email from Ms. Michelle Maupin to Jan van der Voort, May 8, 2008, LUCAS00201069, exhibit
727.3.
Email from Ms. Michelle Maupin, November 4, 2010, LUCAS00198130, exhibit 729.1.
Email from Ms. Donna Morris, Adobe, March 4, 2007, ADOBE_005661, exhibit 1158.
Email from Ms. Donna Morris, Adobe, June 5, 2010, ADOBE_019278, exhibit 1159.
Email of Ms. Donna Morris, Adobe, June 13, 2011, ADOBE_9652, exhibit 1160.
Email of Ms. Donna Morris, Adobe, January 18, 2008, ADOBE_009425, exhibit, 2501.1.
Email of Mr. Shantanu Narayen, Adobe, June 14, 2011, ADOBE_9652, exhibit 1160.
Email from Ms. Vanessa Hall, February 14, 2011, LUCAS00199905-6.
Email from Arnnon Geshuri on Saturday March 15, 2008GOOGLE-High_Tech-00379327,
exhibit 614.
Email from Ms. Lori McAdams on November 17, 2006, LUCAS00184664, Exhibit 122.
Email from Anuj Chandarana, Google, December 2, 2010, exhibit 1629.
Email from Tiffany Wu, September 7, 2007, Goog-High-Tech-00473658, exhibit 1613.
Email from Mr. Chris Galy, Intuit, March 3, 2010, INTUIT_039790, exhibit 2142.1.
Email from Danny McKell, Intel, February 2005, 76657DOC004599, exhibit 2033.
Email from Mr. Ron Okamoto, Apple, September 17, 2010, 231APPLE099371, exhibit 1130.1.
Email from Mr. Paul Otellini, Intel, January 22, 2010, 76616DOC012164, exhibit 478.1.
Email from Ms. Jocelyn Vosburch, Adobe, October 25, 2010, ADOBE_011976-7, exhibit
1250.1-2.

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Email from Mr. Odgen Reid, Intel, April 5, 2005, 76657DOC019264, exhibit, 2035.4.
Email from Mr. Rob York, Apple, on December 17, 2010, 231APPLE039427, exhibit 1376.2.
Google High Tech 00336879 from Deposition of Dr. Shona Brown, January 30, 2013,
referencing exhibit 621.
Great Places to Work website: http://www.greatplacetowork.com/.
Powerpoint, “Recruiting and Human Resources Update,” Board of Directors Meeting, October
19, 2007, LUCAS00013707, exhibit 690.3.
Powerpoint, NPG Human Resources Job Leveling & Pay Equity Review, June 6, 2002,
76583DOC00388, exhibit 392.3.
Powerpoint, NPG Human Resources Job Leveling & Pay Equity Review, June 6, 2002,
76583DOC00388, exhibit 392.5.
Powerpoint on pay design, LUCAS 00188717, exhibit 715.10.
Powerpoint on pay design, LUCAS 00188763, exhibit 715.56.
Powerpoint, Comp Basics for Recruiters, GOOG-HIH-TECH-00036292, exhibit 1606.6.
Powerpoint, Compensation Components Setting a Base Salary, GOOG-HIGH-TECH-00036302,
exhibit, 16016.16.
Powerpoint, Intel Base Pay Comparison Report, Support Overview, WW04 2011,
765825DOC001211, exhibit 400.31.
Powerpoint, Salary Planning 2007, Presentation to Engineering Directors, 29 October 2007,
exhibit, 1609.11.
Powerpoint called FY11 Preliminary Pay lines development update, Intel, May 5, 2010,
76582DOC000004_000004, exhibit 399.4.
Powerpoint, Candidate Generation, Intuit, December 12, 2006, INTUIT_034255, exhibit
2135.25.
Powerpoint, FY ’09 New Hire Equity Guidelines, Intuit, INTUIT_039756, exhibit 2140.4.
Powerpoint, Key Components of Intuit’s Total Rewards Portfolio, Intuit, January 7, 2005,
INTUIT_52803, exhibit 1760.5.
Powerpoint, Leveraging Compensation and Performance, Intuit, January 7, 2005, exhibit
1761.19.

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Powerpoint, INTUIT Total Rewards & Pay Decisions Toolkit, Intuit, May 2005,
INTUIT_043560, exhibit 2739.13.
Powerpoint, Focal Decisions 2005, Communications Session for Senior Managers, June 2005,
Intuit, INTUIT_052841, exhibit 2740.16.
Powerpoint, Lucasfilm Ltd. Compensation Project Status Executive Review, Lucasfilm,
December 7, 2006, LUCAS00027982, exhibit 359.4.
Powerpoint, Global Compensation Project, Lucasfilm Ltd., September 22, 2005, exhibit 944.9.
Powerpoint, PAY FOR PERFORMANCE: 2009 Salary Budget Recommendation, Executive
Review, January 21, 2009, Lucasfilm, LUCAS00189288, exhibit 945.13.
Powerpoint, FSM Pre-Focal Analysis 2007, Intel, January 2007, 76583DOC002007, exhibit
393.13.
Powerpoint, FSM Pre-Focal Analysis 2007, Intel, January 2007, 76583DOC002007, exhibit
393.16.
Powerpoint, FSM Pre-Focal Analysis 2007, Intel, January 2007, 76583DOC002007, exhibit
393.28.
Powerpoint, FSM Pre-Focal Analysis 2007, Intel, January 2007, 76583DOC002007, exhibit
393.19.
Powerpoint, GAM SBS UPDATE, 2/11/09, INTEL, 76579DOC00124_000026, exhibit 396.26.
Powerpoint, TMG Non-Tech Job Audit – HR, Intel, August 25th, 2005,
76583DOC008097_000003, exhibit 397.3.
PowerPoint, Base Pay Comparison Report Support Overview WW 042011, Intel,
765825DOC001211, exhibit 400.17.
Powerpoint, Internal Climate, Intel, 76596DOC017025, exhibit 781.16.
Powerpoint, Base Pay Comparison Report Support Overview WW 04 2011, Intel,
765825DOC001211, exhibit 400.25.
Powerpoint, Adobe, Q1 Workforce Metrics, As of 4 March 2005, Adobe, ADOBE_000622,
exhibit 210.12.
Powerpoint, Retention/Transition Guidelines, Adobe, June 2008, ADOBE_050724, exhibit
216.5.

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Powerpoint, Global Market Analysis, Adobe, exhibit 2486.33.
Powerpoint, 2010 Annual Performance Review, Compensation Training for Managers,
December 2009, ADOBE_100614, exhibit 2487.15.
Powerpoint, Compensation Framework, Insuring Global Consistency, Apple, 231APPLE105345,
exhibit 1856.4
Powerpoint, Total Rewards Planning, FY07, September 2006, Apple, 231APPLE095052, exhibit
1855.107.
Google document, Project Big Bang, Revised Comp Proposal – 9/7/2010, exhibit, 1625.2.
Google document, GOOG-HIGH-TECH-00474908, exhibit 1618.12.
LUCAS00188750-LUCAS00188753, exhibit 959.43-959.46.
Intel spreadsheet printout 76579DOC005152_000017, exhibit 295.17.
Excel spreadsheet, Apple Computer, Inc., 2006 Compensation Analysis, APPLE
231APPLE098912, exhibit 1858.2.
Compensation Analysis and Review Process, Internal Transfer, DRAFT Last Updated 11-23-04,
LUCAS00185312, exhibit 716.
Compensation 201 Instructor Guide, Intel, 76583DOC007693, exhibit 2030.65.
Base Salary Structures, Apple, Effective July 15, 2008, 231APPLE009282, exhibit 268.5.
Worldwide Focal 2001 Questions and Answers Intel Confidential, Rev 13, Feb 26, 2001.
76583DOC003753, exhibit 391.4.
WorldatWork: The Total Rewards Association website:
http://www.worldatwork.org/waw/aboutus/html/aboutus-whatis.html.
Engineering Job Matrix, Pixar, PIX00049042, exhibit 1305.
High-Tech Employee Antitrust Litigation, Consolidated Amended Complaint, September 2,
2011.
Order by Judge Lucy H. Koh, Case5:11-cv-02509-LHK Document382 Filed04/05/13.
Spreadsheet “Employee Type Count by Employer,” provided on February 22, 2013.
Spreadsheet GOOG-HIGH-TECH-00221513.xlsx, tab “Employee Data”.

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GOOG-HIGH-TECH-00625148 Contains a courtesy reproduction of a compensation spreadsheet
titled 2005 Global Ranges - for MQU May-06.xls.
Exhibit 1600.l1 “Google 2004 Salary Ranges”Employer Costs for Employee Compensation –
September 2012, United States Bureau of Labor Statistics,
http://www.bls.gov/news.release/pdf/ecec.pdf.
LUCAS00188913 (Exhibit 711.29) for 2008 Salary Structure.
LUCAS00188912 (exhibit 360) for 2006 Salary Structure.

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APPENDIX C
FIGURES

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101
Figure 1.
Salary Table 2011-DCB
Incorporating a locality payment of 24.22%, Rates Frozen at 2010 Levels
For the locality pay area of Washington-Baltimore-Northern Virginia, DC-MD-VA-WV-PA
Effective January 2011, Annual Rates by Grade and Step
Grade

Step 1

Step 2

Step 3

Step 4

Step 5

Step 6

Step 7

Step 8

Step 9 Step 10

1

22115

22854

23589

24321

25056

25489

26215

26948

26977

27663

2

24865

25456

26279

26977

27280

28082

28885

29687

30490

31292

3

27130

28034

28938

29843

30747

31651

32556

33460

34364

35269

4

30456

31471

32486

33501

34516

35531

36546

37560

38575

39590

5

34075

35210

36346

37481

38616

39752

40887

42022

43158

44293

6

37983

39249

40514

41780

43046

44312

45578

46843

48109

49375

7

42209

43616

45024

46431

47838

49246

50653

52061

53468

54875

8

46745

48303

49861

51418

52976

54534

56092

57649

59207

60765

9

51630

53350

55070

56791

58511

60232

61952

63673

65393

67114

10

56857

58752

60648

62544

64439

66335

68230

70126

72022

73917

11

62467

64548

66630

68712

70794

72876

74958

77040

79122

81204

12

74872

77368

79864

82359

84855

87350

89846

92341

94837

97333

13

89033

92001

94969

97936

100904 103872 106839 109807 112774 115742

14

105211 108717 112224 115731 119238 122744 126251 129758 133264 136771

15

123758 127883 132009 136134 140259 144385 148510 152635 155500 155500

Source: United States Office of Personnel Management: http://www.opm.gov/oca/11tables/pdf/DCB.pdf
See Hallock (2012), p 69.

May 10, 2013

Expert Witness Report of Kevin F. Hallock

668

Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page104 of 120
102
Figure 2.
Example of a Job Evaluation Worksheet
Degree 1

Degree 2

Degree 3

Degree 4

Degree 5

Technical Ability

100

200

300

400

500

Leadership

40

80

120

160

200

Responsibility

30

60

90

120

150

Communications

20

40

60

80

100

Working
Conditions

10

20

30

40

Total

50

See Hallock (2012), page 71.

May 10, 2013

Expert Witness Report of Kevin F. Hallock

669

Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page105 of 120
103
Figure 3.
Example of a Job Evaluation Worksheet for a particular Job

Degree 1

Degree 2

Degree 3

Degree 4

Degree 5

Total

Technical Ability

100

200

300

400

500

400

Leadership

40

80

120

160

200

80

Responsibility

30

60

90

120

150

90

Communications

20

40

60

80

100

60

Working
Conditions

10

20

30

40

50

10

640

Job Evaluation Points
See Hallock (2012), page 72.

May 10, 2013

Expert Witness Report of Kevin F. Hallock

670

Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page106 of 120
104
Figure 4.
Job Evaluation Points

Engineer I
(530 points)

Engineer II
(640 points)

Senior Engineer
(935 points)

Job Evaluation Points
See Hallock (2012), page 72.

May 10, 2013

Expert Witness Report of Kevin F. Hallock

671

Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page107 of 120
105
Figure 5.
Evaluation Points in Different Job Families

Engineer I
(530 points)

Engineer II
(640 points)

Senior Engineer
(935 points)

Job Evaluation Points

Admin I
(211 points)

Admin II
(411points)

Admin Lead
(657 points)

Job Evaluation Points

Legal Assistant
(385 points)

Junior Attorney
(590 points)

Senior Attorney
(895 points)

Job Evaluation Points
See Hallock (2012), page 75.

May 10, 2013

Expert Witness Report of Kevin F. Hallock

672

Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page108 of 120
106

0

100000

200000

300000

400000

Figure 6.
Market Pay Line

200

250

300
350
Job Evaluation Points

Total Compensation

400

450

Fitted values

See Hallock (2012), page 79.

May 10, 2013

Expert Witness Report of Kevin F. Hallock

673

Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page109 of 120
107
Figure 7.
Example of an Internal Structure from Google in 2004

Source: Created from data in spreadsheet GOOG-HIGH-TECH-00221513.xlsx, tab “Employee Data”.

May 10, 2013

Expert Witness Report of Kevin F. Hallock

674

Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page110 of 120
108
Figure 8.
From Apple Proposed FY10 Annual Grant Guidelines

Source: Powerpoint, Apple Inc., Compensation Committee, Apple, August 5, 2009, 231APPLE10067,
exhibit 1854.5.

May 10, 2013

Expert Witness Report of Kevin F. Hallock

675

Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page111 of 120
109
Figure 9.
Apple Salary, Total Cash and Bonus

Source: Excel spreadsheet, Apple Computer, Inc., 2006 Compensation Analysis, APPLE
231APPLE098912, exhibit 1858.2

May 10, 2013

Expert Witness Report of Kevin F. Hallock

676

Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page112 of 120
110
Figure 10.
Apple Salary Structure in Table

Note: Annual Salaries in Thousands.
Source: Base Salary Structures, Apple, Effective July 15, 2008, 231APPLE009282, exhibit 268.5.

May 10, 2013

Expert Witness Report of Kevin F. Hallock

677

Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page113 of 120
111
Figure 11.
Apple Salary Structure in Figure

Source: Base Salary Structures, Apple, Effective July 15, 2008, 231APPLE009282, exhibit 268.5.

May 10, 2013

Expert Witness Report of Kevin F. Hallock

678

Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page114 of 120
112
Figure 12. Google, Merit Increase Matrix

May 10, 2013

Expert Witness Report of Kevin F. Hallock

679

Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page115 of 120
113
Figure 13.
Adobe Salary Increase Matrices, 2009

Source: Powerpoint, 2010 Annual Performance Review, Compensation Training for Managers, December
2009, ADOBE_100614, exhibit 2487.15.

May 10, 2013

Expert Witness Report of Kevin F. Hallock

680

Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page116 of 120
114
Figure 14.
Apple Total Rewards Planning

Source: Powerpoint, Total Rewards Planning, FY07, September 2006, Apple, 231APPLE095052, exhibit,
1855.107.

May 10, 2013

Expert Witness Report of Kevin F. Hallock

681

Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page117 of 120
115
Figure 15.
Excerpts from Adobe Global Market Analysis
Salary Matrices

Source: Powerpoint, Global Market Analysis, Adobe, exhibit 2486.33.

May 10, 2013

Expert Witness Report of Kevin F. Hallock

682

Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page118 of 120
116
Figure 16.
From Intel “Applying Pay Report to Focal Decisions”

Source: PowerPoint, Base Pay Comparison Report Support Overview WW 042011, 765825DOC001211,
exhibit 400.17.

May 10, 2013

Expert Witness Report of Kevin F. Hallock

683

Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page119 of 120
117
Figure 17
Google Data

May 10, 2013

Expert Witness Report of Kevin F. Hallock

684

Case5:11-cv-02509-LHK Document424-1 Filed05/17/13 Page120 of 120
118
Figure 18

May 10, 2013

Expert Witness Report of Kevin F. Hallock

685

Case5:11-cv-02509-LHK Document188-10 Filed10/01/12 Page1 of 29

Exhibit 71
686

Case5:11-cv-02509-LHK Document188-10Filed 09/24/10 Page 1 of 22
Case 1:10-cv-01629-RBW Document 2
Filed10/01/12 Page2 of 29

687

Case5:11-cv-02509-LHK Document188-10Filed 09/24/10 Page 2 of 22
Case 1:10-cv-01629-RBW Document 2
Filed10/01/12 Page3 of 29

688

Case5:11-cv-02509-LHK Document188-10Filed 09/24/10 Page 3 of 22
Case 1:10-cv-01629-RBW Document 2
Filed10/01/12 Page4 of 29

689

Case5:11-cv-02509-LHK Document188-10Filed 09/24/10 Page 4 of 22
Case 1:10-cv-01629-RBW Document 2
Filed10/01/12 Page5 of 29

690

Case5:11-cv-02509-LHK Document188-10Filed 09/24/10 Page 5 of 22
Case 1:10-cv-01629-RBW Document 2
Filed10/01/12 Page6 of 29

691

Case5:11-cv-02509-LHK Document188-10Filed 09/24/10 Page 6 of 22
Case 1:10-cv-01629-RBW Document 2
Filed10/01/12 Page7 of 29

692

Case5:11-cv-02509-LHK Document188-10Filed 09/24/10 Page 7 of 22
Case 1:10-cv-01629-RBW Document 2
Filed10/01/12 Page8 of 29

693

Case5:11-cv-02509-LHK Document188-10Filed 09/24/10 Page 8 of 22
Case 1:10-cv-01629-RBW Document 2
Filed10/01/12 Page9 of 29

694

Case5:11-cv-02509-LHK Document188-10 Filed 09/24/10 Page 9 ofof 29
Case 1:10-cv-01629-RBW Document 2
Filed10/01/12 Page10 22

695

Case5:11-cv-02509-LHK Document188-10Filed 09/24/10 Page 10 of 22
Case 1:10-cv-01629-RBW Document 2
Filed10/01/12 Page11 of 29

696

Case5:11-cv-02509-LHK Document188-10Filed 09/24/10 Page 11 of 22
Case 1:10-cv-01629-RBW Document 2
Filed10/01/12 Page12 of 29

697

Case5:11-cv-02509-LHK Document188-10Filed 09/24/10 Page 12 of 22
Case 1:10-cv-01629-RBW Document 2
Filed10/01/12 Page13 of 29

698

Case5:11-cv-02509-LHK Document188-10Filed 09/24/10 Page 13 of 22
Case 1:10-cv-01629-RBW Document 2
Filed10/01/12 Page14 of 29

699

Case5:11-cv-02509-LHK Document188-10Filed 09/24/10 Page 14 of 22
Case 1:10-cv-01629-RBW Document 2
Filed10/01/12 Page15 of 29

700

Case5:11-cv-02509-LHK Document188-10Filed 09/24/10 Page 15 of 22
Case 1:10-cv-01629-RBW Document 2
Filed10/01/12 Page16 of 29

701

Case5:11-cv-02509-LHK Document188-10Filed 09/24/10 Page 16 of 22
Case 1:10-cv-01629-RBW Document 2
Filed10/01/12 Page17 of 29

702

Case5:11-cv-02509-LHK Document188-10Filed 09/24/10 Page 17 of 22
Case 1:10-cv-01629-RBW Document 2
Filed10/01/12 Page18 of 29

703

Case5:11-cv-02509-LHK Document188-10Filed 09/24/10 Page 18 of 22
Case 1:10-cv-01629-RBW Document 2
Filed10/01/12 Page19 of 29

704

Case5:11-cv-02509-LHK Document188-10Filed 09/24/10 Page 19 of 22
Case 1:10-cv-01629-RBW Document 2
Filed10/01/12 Page20 of 29

705

Case5:11-cv-02509-LHK Document188-10Filed 09/24/10 Page 20 of 22
Case 1:10-cv-01629-RBW Document 2
Filed10/01/12 Page21 of 29

706

Case5:11-cv-02509-LHK Document188-10Filed 09/24/10 Page 21 of 22
Case 1:10-cv-01629-RBW Document 2
Filed10/01/12 Page22 of 29

707

Case5:11-cv-02509-LHK Document188-10Filed 09/24/10 Page 22 of 22
Case 1:10-cv-01629-RBW Document 2
Filed10/01/12 Page23 of 29

708

Case5:11-cv-02509-LHK Document188-10 Filed10/01/12 Page24 of 29
Case 1:10-cv-01629-RBW Document 2-1 Filed 09/24/10 Page 1 6

709

Case5:11-cv-02509-LHK Document188-10 Filed10/01/12 Page25 of 29
Case 1:10-cv-01629-RBW Document 2-1 Filed 09/24/10 Page 2 6

710

Case5:11-cv-02509-LHK Document188-10 Filed10/01/12 Page26 of 29
Case 1:10-cv-01629-RBW Document 2-1 Filed 09/24/10 Page 3 6

711

Case5:11-cv-02509-LHK Document188-10 Filed10/01/12 Page27 of 29
Case 1:10-cv-01629-RBW Document 2-1 Filed 09/24/10 Page 4 6

712

Case5:11-cv-02509-LHK Document188-10 Filed10/01/12 Page28 of 29
Case 1:10-cv-01629-RBW Document 2-1 Filed 09/24/10 Page 5 6

713

Case5:11-cv-02509-LHK Document188-10 Filed10/01/12 Page29 of 29
Case 1:10-cv-01629-RBW Document 2-1 Filed 09/24/10 Page 6 6

714

Case5:11-cv-02509-LHK Document209 Filed11/12/12 Page1 of 32

715

Case5:11-cv-02509-LHK Document209 Filed11/12/12 Page29 of 32

716

Case5:11-cv-02509-LHK Document209 Filed11/12/12 Page30 of 32

717

Case: 12-80188

01/16/2013

ID: 8475821

DktEntry: 5

Page: 1 of 1

FILED
UNITED STATES COURT OF APPEALS
FOR THE NINTH CIRCUIT

SHIRLEY RAE ELLIS, on behalf of
herself and all others similarly situated,
and LEAH HORSTMAN,
Plaintiffs - Respondents,

JAN 16 2013
MOLLY C. DWYER, CLERK
U .S. C O U R T OF APPE ALS

No. 12-80188
D.C. No. 3:04-cv-03341-MHP
Northern District of California,
San Francisco

v.
ORDER
COSTCO WHOLESALE
CORPORATION,
Defendant - Petitioner.

Before: CLIFTON and N.R. SMITH, Circuit Judges.
The court, in its discretion, denies the petition for permission to appeal the
district court’s September 25, 2012 order granting class action certification. See
Fed. R. Civ. P. 23(f); Chamberlan v. Ford Motor Co., 402 F.3d 952 (9th Cir. 2005)
(per curiam).

KS/MOATT

718

SUPPLEMENTAL EXCERPTS OF RECORD
SUBMITTED UNDER SEAL
Pages 719-1128

ADRMOP,CONSOL,E-Filing,PRVADR,RELATE

U.S. District Court
California Northern District (San Jose)
CIVIL DOCKET FOR CASE #: 5:11-cv-02509-LHK
In re: High-Tech Employee Antitrust Litigation
Assigned to: Hon. Lucy H. Koh
Referred to: Magistrate Judge Paul Singh Grewal
Relate Case Case: 5:12-cv-01262-LHK
Case in other court: Alameda County Superior Court, RG 11574066
Cause: 28:1441 Petition for Removal

Date Filed: 05/23/2011
Jury Demand: Both
Nature of Suit: 442 Civil Rights: Jobs
Jurisdiction: Federal Question

In Re
Attorney Palm Inc.
Non-Parties

Plaintiff
Siddharth Hariharan
individually and on behalf of all others
similarly situated

represented by Benjamin Patrick Smith
Morgan, Lewis & Bockius, LLP
One Market, Spear Street Tower
San Francisco, CA 94105
415-442-1000
Fax: [phone]
Email: [e-mail]
LEAD ATTORNEY
ATTORNEY TO BE NOTICED
represented by Anne Brackett Shaver
Lieff, Cabraser, Heimann & Bernstein LLP
275 Battery Street.
29th Floor
San Francisco, CA 94111
415-956-1000
Fax: [phone]
Email: [e-mail]
ATTORNEY TO BE NOTICED
Brendan Patrick Glackin
Lieff, Cabraser, Heimann & Bernstein LLP
275 Battery Street
29th Floor
San Francisco, CA 94111-3339
415-956-1000
Fax: [phone]
Email: [e-mail]
ATTORNEY TO BE NOTICED
Dean Michael Harvey
Lieff, Cabraser, Heimann & Bernstein, LLP
275 Battery Street
29th Floor
San Francisco, CA 94111-3339
415-956-1000
Email: [e-mail]
ATTORNEY TO BE NOTICED
Eric L. Cramer

1129

Berger & Montague, P.C.
1622 Locust Street
Philadelphia, PA 19103
215-875-3000
Fax: [phone]
Email: [e-mail]
PRO HAC VICE
ATTORNEY TO BE NOTICED
Eric B. Fastiff
Lieff, Cabraser, Heimann & Bernstein,LLP
275 Battery Street
29th Floor
San Francisco, CA 94111-3339
415-956-1000
Fax: [phone]
Email: [e-mail]
ATTORNEY TO BE NOTICED
James Gerard Beebe Dallal
Joseph Saveri Law Firm
255 California Street, Suite 450
San Francisco, CA 94111
[phone]
Email: [e-mail]
ATTORNEY TO BE NOTICED
John D. Radice
Grant & Eisenhofer P.A.
485 Lexington Avenue
29th Floor
New York, NY 10017
646-722-8500
Fax: [phone]
TERMINATED: 06/14/2012
ATTORNEY TO BE NOTICED
Joseph Peter Forderer
Leiff Cabraser Heimann Bernstein LLP
275 Battery Street
29th Floor
San Francisco, CA 94111-3339
415-956-1000
Email: [e-mail]
ATTORNEY TO BE NOTICED
Joseph R. Saveri
Joseph Saveri Law Firm, Inc.
505 Montgomery Street
Suite 625
San Francisco, CA 94111
[phone]
Fax: [phone]
Email: [e-mail]
ATTORNEY TO BE NOTICED
Joshua P. Davis

1130

University of San Francisco School of Law
2130 Fulton Street
San Francisco, CA 94117
415-422-6223
Email: [e-mail]
ATTORNEY TO BE NOTICED
Katherine M Lehe
Law Foundation of Silicon Valley
Fair Housing Law Project
152 N. Third St.
3rd Floor
San Jose, CA 95112
408-280-2458
Fax: [phone]
Email: [e-mail]
TERMINATED: 03/23/2012
ATTORNEY TO BE NOTICED
Kelly M. Dermody
Leiff Cabraser Heimann & Bernstein LLP
275 Battery Street, 29th Floor
San Francisco, CA 94111-3339
415-956-1000
Fax: [phone]
Email: [e-mail]
ATTORNEY TO BE NOTICED
Kevin Edward Rayhill
Joseph Saveri Law Firm, Inc.
505 Montgomery Street
Suite 625
San Francisco, CA 94111
[phone]
Fax: [phone]
Email: [e-mail]
ATTORNEY TO BE NOTICED
Linda Phyllis Nussbaum
Grant & Eisenhofer P.A.
485 Lexington Avenue
29th Floor
New York, NY 10017
646-722-8500
Fax: [phone]
Email: [e-mail]
PRO HAC VICE
ATTORNEY TO BE NOTICED
Lisa Janine Cisneros
Lieff, Cabraser, Heimann and Bernstein, LLP
275 Battery Street, 29th Floor
San Francisco, CA 94111-3339
415-956-1000
Email: [e-mail]
ATTORNEY TO BE NOTICED

1131

Peter A. Barile , III
Grant & Eisenhofer, P.C.
485 Lexington Avenue
New York, NY 10017
[phone]
Fax: [phone]
Email: [e-mail]
PRO HAC VICE
ATTORNEY TO BE NOTICED
Richard Martin Heimann
Lieff Cabraser Heimann & Bernstein
275 Battery Street, 30th Floor
San Francisco, CA 94111-3339
415-956-1000
Email: [e-mail]
ATTORNEY TO BE NOTICED
Sarah Rebecca Schalman-Bergen
Berger and Montague, P.C.
1622 Locust Street
Philadelphia, PA 19103
215-875-3053
Fax: [phone]
Email: [e-mail]
PRO HAC VICE
ATTORNEY TO BE NOTICED
Shanon Jude Carson
Berger & Montague, P.C.
1622 Locust Street
Philadelphia, PA 19103
215-875-4656
Fax: [phone]
Email: [e-mail]
PRO HAC VICE
ATTORNEY TO BE NOTICED
Plaintiff
Brandon Marshall

represented by Anne Brackett Shaver
(See above for address)
ATTORNEY TO BE NOTICED
Brendan Patrick Glackin
(See above for address)
ATTORNEY TO BE NOTICED
Dean Michael Harvey
(See above for address)
ATTORNEY TO BE NOTICED
Eric L. Cramer
(See above for address)
PRO HAC VICE
ATTORNEY TO BE NOTICED
Eric B. Fastiff

1132

(See above for address)
ATTORNEY TO BE NOTICED
James Gerard Beebe Dallal
(See above for address)
ATTORNEY TO BE NOTICED
John D. Radice
(See above for address)
TERMINATED: 06/14/2012
ATTORNEY TO BE NOTICED
Joseph Peter Forderer
(See above for address)
ATTORNEY TO BE NOTICED
Joseph R. Saveri
(See above for address)
ATTORNEY TO BE NOTICED
Joshua P. Davis
(See above for address)
ATTORNEY TO BE NOTICED
Katherine M Lehe
(See above for address)
TERMINATED: 03/23/2012
ATTORNEY TO BE NOTICED
Kelly M. Dermody
(See above for address)
ATTORNEY TO BE NOTICED
Kevin Edward Rayhill
(See above for address)
ATTORNEY TO BE NOTICED
Linda Phyllis Nussbaum
(See above for address)
PRO HAC VICE
ATTORNEY TO BE NOTICED
Lisa Janine Cisneros
(See above for address)
ATTORNEY TO BE NOTICED
Peter A. Barile , III
(See above for address)
PRO HAC VICE
ATTORNEY TO BE NOTICED
Richard Martin Heimann
(See above for address)
ATTORNEY TO BE NOTICED
Sarah Rebecca Schalman-Bergen
1133
(See above for address)

PRO HAC VICE
ATTORNEY TO BE NOTICED
Shanon Jude Carson
(See above for address)
PRO HAC VICE
ATTORNEY TO BE NOTICED
Plaintiff
Michael Devine

represented by Anne Brackett Shaver
(See above for address)
ATTORNEY TO BE NOTICED
Brendan Patrick Glackin
(See above for address)
ATTORNEY TO BE NOTICED
Dean Michael Harvey
(See above for address)
ATTORNEY TO BE NOTICED
Eric L. Cramer
(See above for address)
PRO HAC VICE
ATTORNEY TO BE NOTICED
Eric B. Fastiff
(See above for address)
ATTORNEY TO BE NOTICED
James Gerard Beebe Dallal
(See above for address)
ATTORNEY TO BE NOTICED
John D. Radice
(See above for address)
TERMINATED: 06/14/2012
ATTORNEY TO BE NOTICED
Joseph Peter Forderer
(See above for address)
ATTORNEY TO BE NOTICED
Joseph R. Saveri
(See above for address)
ATTORNEY TO BE NOTICED
Joshua P. Davis
(See above for address)
ATTORNEY TO BE NOTICED
Katherine M Lehe
(See above for address)
TERMINATED: 03/23/2012
ATTORNEY TO BE NOTICED
Kelly M. Dermody

1134

(See above for address)
ATTORNEY TO BE NOTICED
Kevin Edward Rayhill
(See above for address)
ATTORNEY TO BE NOTICED
Linda Phyllis Nussbaum
(See above for address)
PRO HAC VICE
ATTORNEY TO BE NOTICED
Lisa Janine Cisneros
(See above for address)
ATTORNEY TO BE NOTICED
Lisa Jennifer Leebove
Joseph Saveri Law Firm
255 California Street
Suite 450
San Francisco, CA 94111
415 500 6800
Fax: [phone]
Email: [e-mail]
ATTORNEY TO BE NOTICED
Peter A. Barile , III
(See above for address)
PRO HAC VICE
ATTORNEY TO BE NOTICED
Richard Martin Heimann
(See above for address)
ATTORNEY TO BE NOTICED
Sarah Rebecca Schalman-Bergen
(See above for address)
PRO HAC VICE
ATTORNEY TO BE NOTICED
Shanon Jude Carson
(See above for address)
PRO HAC VICE
ATTORNEY TO BE NOTICED
Plaintiff
Mark Fichtner

represented by Anne Brackett Shaver
(See above for address)
ATTORNEY TO BE NOTICED
Brendan Patrick Glackin
(See above for address)
ATTORNEY TO BE NOTICED
Dean Michael Harvey
(See above for address)
1135
ATTORNEY TO BE NOTICED

Eric L. Cramer
(See above for address)
PRO HAC VICE
ATTORNEY TO BE NOTICED
Eric B. Fastiff
(See above for address)
ATTORNEY TO BE NOTICED
James Gerard Beebe Dallal
(See above for address)
ATTORNEY TO BE NOTICED
John D. Radice
(See above for address)
TERMINATED: 06/14/2012
ATTORNEY TO BE NOTICED
Joseph Peter Forderer
(See above for address)
ATTORNEY TO BE NOTICED
Joseph R. Saveri
(See above for address)
ATTORNEY TO BE NOTICED
Joshua P. Davis
(See above for address)
ATTORNEY TO BE NOTICED
Katherine M Lehe
(See above for address)
TERMINATED: 03/23/2012
ATTORNEY TO BE NOTICED
Kelly M. Dermody
(See above for address)
ATTORNEY TO BE NOTICED
Kevin Edward Rayhill
(See above for address)
ATTORNEY TO BE NOTICED
Linda Phyllis Nussbaum
(See above for address)
PRO HAC VICE
ATTORNEY TO BE NOTICED
Lisa Janine Cisneros
(See above for address)
ATTORNEY TO BE NOTICED
Peter A. Barile , III
(See above for address)
PRO HAC VICE
1136
ATTORNEY TO BE NOTICED

Richard Martin Heimann
(See above for address)
ATTORNEY TO BE NOTICED
Sarah Rebecca Schalman-Bergen
(See above for address)
PRO HAC VICE
ATTORNEY TO BE NOTICED
Shanon Jude Carson
(See above for address)
PRO HAC VICE
ATTORNEY TO BE NOTICED
Plaintiff
Daniel Stover

represented by Anne Brackett Shaver
(See above for address)
ATTORNEY TO BE NOTICED
Brendan Patrick Glackin
(See above for address)
ATTORNEY TO BE NOTICED
Dean Michael Harvey
(See above for address)
ATTORNEY TO BE NOTICED
Eric L. Cramer
(See above for address)
PRO HAC VICE
ATTORNEY TO BE NOTICED
Eric B. Fastiff
(See above for address)
ATTORNEY TO BE NOTICED
James Gerard Beebe Dallal
(See above for address)
ATTORNEY TO BE NOTICED
John D. Radice
(See above for address)
TERMINATED: 06/14/2012
ATTORNEY TO BE NOTICED
Joseph Peter Forderer
(See above for address)
ATTORNEY TO BE NOTICED
Joseph R. Saveri
(See above for address)
ATTORNEY TO BE NOTICED
Joshua P. Davis
(See above for address)
1137
ATTORNEY TO BE NOTICED

Katherine M Lehe
(See above for address)
TERMINATED: 03/23/2012
ATTORNEY TO BE NOTICED
Kelly M. Dermody
(See above for address)
ATTORNEY TO BE NOTICED
Kevin Edward Rayhill
(See above for address)
ATTORNEY TO BE NOTICED
Linda Phyllis Nussbaum
(See above for address)
PRO HAC VICE
ATTORNEY TO BE NOTICED
Lisa Janine Cisneros
(See above for address)
ATTORNEY TO BE NOTICED
Peter A. Barile , III
(See above for address)
PRO HAC VICE
ATTORNEY TO BE NOTICED
Richard Martin Heimann
(See above for address)
ATTORNEY TO BE NOTICED
Sarah Rebecca Schalman-Bergen
(See above for address)
PRO HAC VICE
ATTORNEY TO BE NOTICED
Shanon Jude Carson
(See above for address)
PRO HAC VICE
ATTORNEY TO BE NOTICED
Plaintiff
UNITED STATES OF AMERICA

V.

represented by Anna Tryon Pletcher
Department of Justice
Antitrust Division
450 Golden Gate Avenue
Box 36046
Room 10-0101
San Francisco, CA 94102
415-436-6727
Fax: [phone]
Email: [e-mail]
ATTORNEY TO BE NOTICED

1138

Defendant
Adobe Systems Inc.

represented by Robert Addy Van Nest
Keker & Van Nest LLP
633 Battery Street
San Francisco, CA 94111-1809
415-391-5400
Fax: [phone]
Email: [e-mail]
LEAD ATTORNEY
ATTORNEY TO BE NOTICED
Craig Andrew Waldman
Jones Day
555 California Street
26th Floor
San Francisco, CA 94104
415-626-3939
Fax: [phone]
Email: [e-mail]
ATTORNEY TO BE NOTICED
David Craig Kiernan
Jones Day
555 California Street, 26th Floor
San Francisco, CA 94104
[phone]
Fax: [phone]
Email: [e-mail]
ATTORNEY TO BE NOTICED
Robert Allan Mittelstaedt
Jones Day
555 California Street, 26th Floor
San Francisco, CA 94104
[phone]
Fax: [phone]
Email: [e-mail]
ATTORNEY TO BE NOTICED
Lin W. Kahn
Jones Day
555 California Street, 26th Floor
San Francisco, CA 94104
[phone]
Fax: [phone]
Email: [e-mail]
ATTORNEY TO BE NOTICED

Defendant
Apple Inc.

represented by George A. Riley
O'Melveny & Myers LLP
2 Embarcadero Center
28th Floor
San Francisco, CA 94111
415/984-8741
Fax: [phone]

1139

Email: [e-mail]
LEAD ATTORNEY
ATTORNEY TO BE NOTICED
Robert Addy Van Nest
(See above for address)
LEAD ATTORNEY
ATTORNEY TO BE NOTICED
Amanda R. Conley
O'Melveny and Myers
Two Embarcadero Center
28th Floor
San Francisco, CA 94111
415-984-8829
Email: [e-mail]
ATTORNEY TO BE NOTICED
Christina Joanne Brown
O'Melveny & Myers
Two Embarcadero Center, 28th Floor
San Francisco, CA 94111-3823
415-984-8979
Fax: [phone]
Email: [e-mail]
ATTORNEY TO BE NOTICED
Flora F Vigo
O'Melveny & Myers LLP
Two Embarcadero Center
28th Floor
San Francisco, CA 94111
415.984.8700
Fax: [phone]
Email: [e-mail]
ATTORNEY TO BE NOTICED
George Riley
O'Melveny Myers LLP
Two Embarcadero Center
28th Floor
San Francisco, CA 94111-3823
415-984-8741
Fax: [phone]
Email: [e-mail]
PRO HAC VICE
ATTORNEY TO BE NOTICED
Michael Frederick Tubach
O'Melveny & Myers LLP
Two Embarcadero Center
28th Floor
San Francisco, CA 94111-3305
415-984-8700
Fax: [phone]
Email: [e-mail]
1140
ATTORNEY TO BE NOTICED

Defendant
Google Inc.

represented by Anne M Selin
Mayer Brown LLP
Two Palo Alto Square
Suite 300
3000 El Camino Real
Palo Alto, CA 94306
650-331-2000
Fax: [phone]
Email: [e-mail]
ATTORNEY TO BE NOTICED
Daniel Edward Purcell
Keker & Van Nest LLP
633 Battery Street
San Francisco, CA 94111-1809
415-391-5400
Fax: [phone]
Email: [e-mail]
ATTORNEY TO BE NOTICED
Donald M. Falk
Mayer Brown LLP
Two Palo Alto Square
Suite 300
Palo Alto, CA 94306-2112
650-331-2030
Fax: [phone]
Email: [e-mail]
ATTORNEY TO BE NOTICED
Edward D. Johnson
Mayer Brown LLP
Two Palo Alto Square
Suite 300
Palo Alto, CA 94306-2112
650-331-2000
Fax: [phone]
Email: [e-mail]
ATTORNEY TO BE NOTICED
Eric Evans
Mayer Brown LLP
Two Palo Alto Square, Suite 300
3000 El Camino Real
Palo Alto, CA 94306-2112
650-331-2000
Fax: [phone]
Email: [e-mail]
ATTORNEY TO BE NOTICED
Eugene Morris Paige
Keker & Van Nest LLP
633 Battery Street
San Francisco, CA 94111-1809
415-391-5400
1141

Fax: [phone]
Email: [e-mail]
ATTORNEY TO BE NOTICED
Justina Kahn Sessions
Keker & Van Nest LLP
633 Battery Street
San Francisco, CA 94111
415-391-5400
Fax: [phone]
Email: [e-mail]
ATTORNEY TO BE NOTICED
Lee H. Rubin
Mayer Brown LLP
Two Palo Alto Square
Suite 300
Palo Alto, CA 94306-2112
(650-331-2000
Fax: [phone]
Email: [e-mail]
ATTORNEY TO BE NOTICED
Robert Addy Van Nest
(See above for address)
ATTORNEY TO BE NOTICED
Defendant
Intel Corp.

represented by Gregory P. Stone
Munger Tolles & Olson LLP
355 South Grand Avenue
35th Floor
Los Angeles, CA 90071-1560
213-683-9100
Fax: [phone]
Email: [e-mail]
LEAD ATTORNEY
ATTORNEY TO BE NOTICED
Robert Addy Van Nest
(See above for address)
LEAD ATTORNEY
ATTORNEY TO BE NOTICED
Angela Marie Munoz
Bingham McCutchen
3 Embarcadero Center
SF, CA 94111
415-393-2370
Fax: [phone]
Email: [e-mail]
TERMINATED: 04/26/2012
ATTORNEY TO BE NOTICED
Bradley S. Phillips
Munger Tolles & Olson LLP
1142
355 S. Grand Avenue

35th Floor
Los Angeles, CA 90071-1569
213-683-9100
Fax: [phone]
Email: [e-mail]
ATTORNEY TO BE NOTICED
Donn P. Pickett
Bingham McCutchen , LLP
Three Embarcadero Center
San Francisco, CA 94111-4067
415-393-2000
Fax: [phone]
Email: [e-mail]
TERMINATED: 10/20/2013
ATTORNEY TO BE NOTICED
Frank H Busch
Bingham McCutchen
Three Embarcadero Center
San Francisco, Ca 94111
United Sta
415-393-2074
Fax: [phone]
Email: [e-mail]
TERMINATED: 10/20/2013
ATTORNEY TO BE NOTICED
Frank Hinman
Bingham McCutchen LLP
Three Embarcadero Center, 18th Floor
San Francisco, CA 94111
415-393-2462
Fax: [phone]
Email: [e-mail]
TERMINATED: 10/20/2013
ATTORNEY TO BE NOTICED
Gregory M Sergi
Munger Tolles & Olson LLP
355 South Grand Avenue
Suite 3500
Los Angeles, CA 90071
213-683-9100
ATTORNEY TO BE NOTICED
Holly A. House
Paul Hastings LLP
55 Second Street
Twenty-Fourth Floor
San Francisco, CA 94105
415-856-7217
Fax: [phone]
Email: [e-mail]
TERMINATED: 09/27/2011
ATTORNEY TO BE NOTICED

1143

John P Mittelbach
Munger Tolles Olson LLP
355 S. Grand Ave
35th Floor
Los Angeles, CA 90071
213-683-9166
Email: [e-mail]
ATTORNEY TO BE NOTICED
Sujal Shah
Bingham McCutchen LLP
Three Embarcadero Center
San Francisco, CA 94111-4067
[phone]
Fax: [phone]
Email: [e-mail]
TERMINATED: 10/20/2013
ATTORNEY TO BE NOTICED
Zachary J. Alinder
Bingham McCutchen, LLP
Three Embarcadero Center
San Francisco, CA 94111
[phone]
Fax: [phone]
Email: [e-mail]
TERMINATED: 04/26/2012
ATTORNEY TO BE NOTICED
Krystal N. Bowen
Bingham McCutchen
Three Embarcadero Center
San Francisco, CA 94611
415-393-2760
Fax: [phone]
Email: [e-mail]
TERMINATED: 10/20/2013
ATTORNEY TO BE NOTICED
Defendant
Intuit Inc.

represented by Catherine Tara Zeng
Jones Day
1755 Embarcadero Rd
Palo Alto, CA 94303
650-739-3939
Fax: [phone]
Email: [e-mail]
ATTORNEY TO BE NOTICED
Craig Ellsworth Stewart
Jones Day
555 California Street, 26th Floor
San Francisco, CA 94104
[phone]
Fax: [phone]
Email: [e-mail]
1144
ATTORNEY TO BE NOTICED

David Craig Kiernan
(See above for address)
ATTORNEY TO BE NOTICED
Robert Allan Mittelstaedt
(See above for address)
ATTORNEY TO BE NOTICED
Defendant
Lucasfilm Ltd.

represented by Chinue Turner Richardson
1201 Pennsylvania Ave NW
Washington, DC 20004
United Sta
202-662-5766
Fax: [phone]
Email: [e-mail]
ATTORNEY TO BE NOTICED
Cody Shawn Harris
Keker and Van Nest LLP
633 Battery Street
San Francisco, CA 94111-1809
415-391-5400
Fax: [phone]
Email: [e-mail]
ATTORNEY TO BE NOTICED
Daniel Edward Purcell
(See above for address)
TERMINATED: 07/24/2013
ATTORNEY TO BE NOTICED
Deborah A. Garza
Covington and Burling LLP
1201 Pennsylvania Avenue, NW
Washington, DC 20004
202-662-5146
Fax: [phone]
Email: [e-mail]
ATTORNEY TO BE NOTICED
Emily Johnson Henn
Covington & Burling LLP
333 Twin Dolphin Drive
Suite 700
Redwood Shores, CA 94065
650-632-4700
Email: [e-mail]
ATTORNEY TO BE NOTICED
Eugene Morris Paige
(See above for address)
TERMINATED: 07/24/2013
ATTORNEY TO BE NOTICED
John Watkins Keker

1145

Keker & Van Nest LLP
633 Battery Street
San Francisco, CA 94111-1809
415/391-5400
Fax: [phone]
Email: [e-mail]
TERMINATED: 07/24/2013
ATTORNEY TO BE NOTICED
John W. Nields , Jr.
Covington and Burling LLC
1201 Pennsylvania Avenue, N.W.
Washington, DC 20004
202-662-5058
Email: [e-mail]
ATTORNEY TO BE NOTICED
Justina Kahn Sessions
(See above for address)
TERMINATED: 07/24/2013
ATTORNEY TO BE NOTICED
Paula Lenore Blizzard
Keker & Van Nest LLP
633 Battery Street
San Francisco, CA 94111
[phone]
Fax: [phone]
Email: [e-mail]
ATTORNEY TO BE NOTICED
Thomas A. Isaacson
Covington & Burling LLP
3600
1201 Pennsylvania Avenue, N.W.
Washington, DC 20004
202-783-0800
Fax: [phone]
Email: [e-mail]
ATTORNEY TO BE NOTICED
Defendant
Pixar

represented by Robert T. Haslam , III
Covington & Burling LLP
333 Twin Dolphin Drive
Suite 700
Redwood Shores, CA 94065
[phone]
Fax: [phone]
Email: [e-mail]
TERMINATED: 05/14/2013
LEAD ATTORNEY
ATTORNEY TO BE NOTICED
Chinue Turner Richardson
(See above for address)
1146
PRO HAC VICE

ATTORNEY TO BE NOTICED
Deborah A. Garza ,
Covington and Burling LLP
1201 Pennsylvania Avenue, NW
Washington, DC 20004
202-662-5146
Fax: [phone]
Email: [e-mail]
PRO HAC VICE
ATTORNEY TO BE NOTICED
Emily Johnson Henn
Covington & Burling LLP
333 Twin Dolphin Drive
Suite 700
Redwood Shores, CA 94065
650-632-4700
Email: [e-mail]
ATTORNEY TO BE NOTICED
John W. Nields , Jr.
(See above for address)
PRO HAC VICE
ATTORNEY TO BE NOTICED
Jonathan A D Herczeg ,
Convington Burling LLP
1201 Pennsylvania Avenue, NW
Washington, DC 20004
202-662-5052
Fax:
Email: [e-mail]
TERMINATED: 11/21/2012
PRO HAC VICE
ATTORNEY TO BE NOTICED
Thomas A. Isaacson
Howrey LLP
3600
1299 Pennsylvania Avenue, N.W.
Washington, DC 20004
202-783-0800
Fax: [phone]
Email: [e-mail]
PRO HAC VICE
ATTORNEY TO BE NOTICED
Date Filed

#

Docket Text

05/23/2011

1

JOINT NOTICE OF REMOVAL of Action from State Court; No Process from Alameda
County Superior Court. Their case number is RG11574066. (Filing fee $350.00 receipt
number 34611060153). Filed by Intel Corp., Apple Inc., Intuit Inc., Adobe Systems Inc.,
Pixar, Google Inc., Lucasfilm Ltd.. (Attachments: # 1 Civil Cover Sheet) (gba, COURT
STAFF) (Filed on 5/23/2011) (Entered: 05/24/2011)

1147

05/23/2011

2

Declaration of Cody Harris in Support of 1 Notice of Removal (Alameda County Superior
Court Complaint attach) filed by Lucasfilm Ltd.. (Related document(s) 1 ) (gba, COURT
STAFF) (Filed on 5/23/2011) (Entered: 05/24/2011)

05/23/2011

3

Declaration of David Anderman in Support of 1 Notice of Removal, filed by Lucasfilm Ltd..
(Related document(s) 1 ) (gba, COURT STAFF) (Filed on 5/23/2011) (Entered: 05/24/2011)

05/23/2011

4

Declaration of Rhonda Hjort in Support of 1 Notice of Removal, filed by Lucasfilm Ltd..
(Related document(s) 1 ) (gba, COURT STAFF) (Filed on 5/23/2011) (Entered: 05/24/2011)

05/23/2011

5

Declaration of Jack Gilmore in Support of 1 Notice of Removal, filed by Adobe Systems,
Inc. (Related document(s) 1 ) (gba, COURT STAFF) (Filed on 5/23/2011) (Entered:
05/24/2011)

05/23/2011

6

Declaration of Joel Pdolyny in Support of 1 Notice of Removal, filed by Apple Inc. (Related
document(s) 1 ) (gba, COURT STAFF) (Filed on 5/23/2011) (Entered: 05/24/2011)

05/23/2011

7

Declaration of Tadhg Bourke in Support of 1 Notice of Removal, filed by Google Inc.
(Related document(s) 1 ) (gba, COURT STAFF) (Filed on 5/23/2011) (Entered: 05/24/2011)

05/23/2011

8

Declaration of James M. Kennedy in Support of 1 Notice of Removal, filed by Pixar.
(Related document(s) 1 ) (gba, COURT STAFF) (Filed on 5/23/2011) (Entered: 05/24/2011)

05/23/2011

9

Declaration of Debbie R. Oldham-Auker in Support of 1 Notice of Removal, filed by Intel
Corp.. (Related document(s) 1 ) (gba, COURT STAFF) (Filed on 5/23/2011) (Entered:
05/24/2011)

05/23/2011

10

Certificate of Interested Entities by Lucasfilm Ltd. (gba, COURT STAFF) (Filed on
5/23/2011) (Entered: 05/24/2011)

05/23/2011

11

NOTICE of Corporate Disclosure Statement by Apple Inc. (gba, COURT STAFF) (Filed on
5/23/2011) (Entered: 05/24/2011)

05/23/2011

12

NOTICE of Corporate Disclosure Statement by Adobe Systems Inc. (gba, COURT STAFF)
(Filed on 5/23/2011) (Entered: 05/24/2011)

05/23/2011

13

NOTICE of Corporate Disclosure Statement by Google Inc. (gba, COURT STAFF) (Filed on
5/23/2011) (Entered: 05/24/2011)

05/23/2011

14

NOTICE of Corporate Disclosure Statement by Intuit Inc. (gba, COURT STAFF) (Filed on
5/23/2011) (Entered: 05/24/2011)

05/23/2011

15

NOTICE of Corporate Disclosure Statement by Pixar (gba, COURT STAFF) (Filed on
5/23/2011) (Entered: 05/24/2011)

05/23/2011

16

ADR SCHEDULING ORDER: Case Management Statement due by 8/26/2011. Case
Management Conference set for 9/2/2011 01:30 PM in Courtroom A, 15th Floor, San
Francisco. (gba, COURT STAFF) (Filed on 5/23/2011) (Entered: 05/24/2011)

05/23/2011

CASE DESIGNATED for Electronic Filing. (gba, COURT STAFF) (Filed on 5/23/2011)
(Entered: 05/24/2011)

05/24/2011

18

AMENDED Declaration of Cody Harris in Support of 1 Notice of Removal, filed by
Lucasfilm Ltd.. (Related document(s) 1 ) (gba, COURT STAFF) (Filed on 5/24/2011)
(Entered: 05/26/2011)

05/24/2011

19

NOTICE of Corporate Disclosure Statement by Intel Corp. (gba, COURT STAFF) (Filed on
5/24/2011) (Entered: 05/26/2011)

05/24/2011

20

CERTIFICATE OF SERVICE by Lucasfilm Ltd. re 7 Declaration in Support, 14 Notice
(Other), 15 Notice (Other), 11 Notice (Other), 6 Declaration in Support, 1 Notice of
Removal, 10 Certificate of Interested Entities, 3 Declaration in Support, 12 Notice (Other), 4

1148

Declaration in Support, 5 Declaration in Support, 9 Declaration in Support, 8 Declaration in
Support, 13 Notice (Other), 2 Declaration in Support, 16 ADR Scheduling Order (gba,
COURT STAFF) (Filed on 5/24/2011) (Entered: 05/26/2011)
05/24/2011

21

CERTIFICATE OF SERVICE by Lucasfilm Ltd. re 18 Declaration in Support, 19 Notice
(Other) (gba, COURT STAFF) (Filed on 5/24/2011) (Entered: 05/26/2011)

05/26/2011

17

STIPULATION /Extending Time To Respond To Complaint by Adobe Systems Inc., Apple
Inc., Google Inc., Siddharth Hariharan, Intel Corp., Intuit Inc., Lucasfilm Ltd., Pixar.
(Tubach, Michael) (Filed on 5/26/2011) (Entered: 05/26/2011)

05/27/2011

22

Declination to Proceed Before a U.S. Magistrate Judge by Siddharth Hariharan. (Harvey,
Dean) (Filed on 5/27/2011) (Entered: 05/27/2011)

05/31/2011

23

CLERK'S NOTICE of Impending Reassignment to U.S. District Judge (klhS, COURT
STAFF) (Filed on 5/31/2011) (Entered: 05/31/2011)

06/01/2011

24

ORDER REASSIGNING CASE. Case reassigned to Judge Hon. Saundra Brown Armstrong
for all further proceedings. Judge Magistrate Judge Joseph C. Spero no longer assigned to the
case.. Signed by Executive Committee on 6/1/11. (as, COURT STAFF) (Filed on 6/1/2011)
(Entered: 06/01/2011)

06/16/2011

25

MOTION for leave to appear in Pro Hac Vice for Deborah A. Garza ( Filing fee $ 275,
receipt number 44611007160.) filed by Pixar. (Attachments: # 1 Proposed Order)(jlm,
COURT STAFF) (Filed on 6/16/2011) (Entered: 06/17/2011)

06/16/2011

26

MOTION for leave to appear in Pro Hac Vice for Jonathan Herczeg ( Filing fee $ 275,
receipt number 44611007160.) filed by Pixar. (Attachments: # 1 Proposed Order)(jlm,
COURT STAFF) (Filed on 6/16/2011) (Entered: 06/17/2011)

06/20/2011

27

CASE MANAGEMENT SCHEDULING ORDER: Case Management Conference set for
9/15/2011 03:00 PM., via Telephone. Signed by Judge Saundra Brown Armstrong, on
6/20/11. (lrc, COURT STAFF) (Filed on 6/20/2011) Modified on 6/21/2011 (jlm, COURT
STAFF). (Entered: 06/20/2011)

06/21/2011

28

ORDER by Judge Saundra Brown Armstrong GRANTING 25 Motion for Pro Hac Vice for
Deborah A. Garza (jlm, COURT STAFF) (Filed on 6/21/2011) (Entered: 06/23/2011)

06/21/2011

29

ORDER by Judge Saundra Brown Armstrong GRANTING 26 Motion for Pro Hac Vice for
Jonathan Herczeg (jlm, COURT STAFF) (Filed on 6/21/2011) (Entered: 06/23/2011)

06/28/2011

30

NOTICE of Filing of Declaration of Kumud Kokal in Support re 1 Notice of Removal, filed
by Lucasfilm Ltd.. (Purcell, Daniel) (Filed on 6/28/2011) Modified on 6/30/2011 (jlm,
COURT STAFF). (Entered: 06/28/2011)

06/28/2011

31

Declaration of Daniel Purcell in Support re 1 Notice of Removal filed by Lucasfilm Ltd..
(Attachments: # 1 Exhibit)(Purcell, Daniel) (Filed on 6/28/2011) Modified on 6/30/2011
(jlm, COURT STAFF). (Entered: 06/28/2011)

06/29/2011

32

NOTICE of Pendency of other Actions or Proceedings, filed by Siddharth Hariharan
(Harvey, Dean) (Filed on 6/29/2011) Modified on 6/30/2011 (jlm, COURT STAFF).
(Entered: 06/29/2011)

06/29/2011

33

Declaration of Dean M. Harvey in Support of 32 Notice of Pendency of Other Actions or
Proceedings filed by Siddharth Hariharan. (Attachments: # 1 Exhibit A, # 2 Exhibit B)
(Related document(s) 32 ) (Harvey, Dean) (Filed on 6/29/2011) Modified on 6/30/2011 (jlm,
COURT STAFF). (Entered: 06/29/2011)

06/30/2011

34

Certificate of Interested Entities by Siddharth Hariharan (Harvey, Dean) (Filed on 6/30/2011)
(Entered: 06/30/2011)

06/30/2011

35

1149
Second NOTICE of Pendency of Other Actions or Proceedings, filed by Siddharth Hariharan

(Harvey, Dean) (Filed on 6/30/2011) Modified on 7/1/2011 (jlm, COURT STAFF). (Entered:
06/30/2011)
06/30/2011

36

Declaration of Dean M. Harvey in Support of 35 Second Notice of Pendency of Other Actions
or Proceedings filed by Siddharth Hariharan. (Attachments: # 1 Exhibit A)(Related
document(s) 35 ) (Harvey, Dean) (Filed on 6/30/2011) Modified on 7/1/2011 (jlm, COURT
STAFF). (Entered: 06/30/2011)

07/06/2011

37

MOTION for leave to appear in Pro Hac Vice for John D. Radice ( Filing fee $ 275, receipt
number 34611061838.) filed by Siddharth Hariharan. (Attachments: # 1 Proposed Order)
(jlm, COURT STAFF) (Filed on 7/6/2011) (Entered: 07/08/2011)

07/06/2011

38

MOTION for leave to appear in Pro Hac Vice for Linda P. Nussbaum ( Filing fee $ 275,
receipt number 34611061839.), filed by Siddharth Hariharan. (Attachments: # 1 Proposed
Order)(jlm, COURT STAFF) (Filed on 7/6/2011) (Entered: 07/08/2011)

07/13/2011

39

ORDER by Judge Saundra Brown Armstrong GRANTING 37 Motion for Pro Hac Vice for
John D. Radice (jlm, COURT STAFF) (Filed on 7/13/2011) (Entered: 07/14/2011)

07/13/2011

40

ORDER by Judge Saundra Brown Armstrong GRANTING 38 Motion for Pro Hac Vice for
Linda P. Nussbaum (jlm, COURT STAFF) (Filed on 7/13/2011) (Entered: 07/14/2011)

07/19/2011

41

MOTION to Relate Cases: C-11-3539-HRL; C-11-3538-HRL; C-11-3540-PSG; C-11-3541PSG, filed by Intuit Inc.. (Broderick, Catherine) (Filed on 7/19/2011) Modified on 7/20/2011
(jlm, COURT STAFF). (Entered: 07/19/2011)

07/19/2011

42

Declaration of Catherine T. Broderick in Support of 41 Motion to Relate Cases filed by Intuit
Inc.. (Related document(s) 41 ) (Broderick, Catherine) (Filed on 7/19/2011) Modified on
7/20/2011 (jlm, COURT STAFF). (Entered: 07/19/2011)

07/19/2011

43

EXHIBITS to 42 Declaration in Support of Catherine T. Broderick filed by Intuit Inc..
(Attachments: # 1 Exhibit Exhibit A, # 2 Exhibit Exhibit B, # 3 Exhibit Exhibit C, # 4
Exhibit Exhibit D)(Related document(s) 42 ) (Broderick, Catherine) (Filed on 7/19/2011)
Modified on 7/20/2011 (jlm, COURT STAFF). (Entered: 07/19/2011)

07/20/2011

44

RESPONSE re 41 Motion to Relate Cases filed by Siddharth Hariharan. (Harvey, Dean)
(Filed on 7/20/2011) Modified on 7/21/2011 (jlm, COURT STAFF). (Entered: 07/20/2011)

07/20/2011

45

Declaration of Dean M. Harvey in Support of 44 Response to Motion to Relate Cases, filed
by Siddharth Hariharan. (Attachments: # 1 Exhibit A, # 2 Exhibit B, # 3 Exhibit C)(Related
document(s) 44 ) (Harvey, Dean) (Filed on 7/20/2011) Modified on 7/21/2011 (jlm, COURT
STAFF). (Entered: 07/20/2011)

07/20/2011

46

Proposed Order re 32 , 35 Notice of Pendency of other Actions or Proceedings, by Siddharth
Hariharan. (Harvey, Dean) (Filed on 7/20/2011) Modified on 7/21/2011 (jlm, COURT
STAFF). (Entered: 07/20/2011)

07/20/2011

47

CERTIFICATE OF SERVICE by Intuit Inc. re 41 MOTION to Relate Case (Broderick,
Catherine) (Filed on 7/20/2011) (Entered: 07/20/2011)

07/22/2011

48

STIPULATION Extending Time to Respond to Complaint, filed by Apple Inc., Adobe
Systems Inc., Siddharth Hariharan, Lucasfilm Ltd., Google Inc., Intel Corp., Intuit Inc.,
Pixar. (Tubach, Michael) (Filed on 7/22/2011) Modified on 7/25/2011 (jlm, COURT
STAFF). (Entered: 07/22/2011)

07/26/2011

49

MOTION for leave to appear in Pro Hac Vice for Sarah R. Schalman-Bergen ( Filing fee $
275, receipt number 44611007340.) filed by Siddharth Hariharan. (Attachments: # 1
Proposed Order)(jlm, COURT STAFF) (Filed on 7/26/2011) (Entered: 07/26/2011)

07/26/2011

50

MOTION for leave to appear in Pro Hac Vice for Shanon J. Carson ( Filing fee $ 275, receipt
number 44611007340.) filed by Siddharth Hariharan. (Attachments: # 1 Proposed Order)

1150

(jlm, COURT STAFF) (Filed on 7/26/2011) (Entered: 07/26/2011)
07/26/2011

51

MOTION for leave to appear in Pro Hac Vice for Eric L. Cramer ( Filing fee $ 275, receipt
number 44611007340.) filed by Siddharth Hariharan. (Attachments: # 1 Proposed Order)
(jlm, COURT STAFF) (Filed on 7/26/2011) (Entered: 07/26/2011)

07/27/2011

52

ORDER by Judge Saundra Brown Armstrong GRANTING 41 Motion to Relate Cases: C-113539-HRL; C-11-3538-HRL; C-11-3540-PSG; C-11-3541-PSG. Signed by Judge Saundra
Brown Armstrong, on 07/25/11 (lrc, COURT STAFF) (Filed on 7/27/2011) Modified on
7/28/2011 (jlm, COURT STAFF). (Entered: 07/27/2011)

07/28/2011

53

ORDER by Judge Saundra Brown Armstrong GRANTING 51 Motion for Pro Hac Vice for
Eric L. Cramer (jlm, COURT STAFF) (Filed on 7/28/2011) (Entered: 07/28/2011)

07/28/2011

54

ORDER by Judge Saundra Brown Armstrong GRANTING 50 Motion for Pro Hac Vice for
Shanon J. Carson (jlm, COURT STAFF) (Filed on 7/28/2011) (Entered: 07/28/2011)

07/28/2011

55

ORDER by Judge Saundra Brown Armstrong GRANTING 49 Motion for Pro Hac Vice for
Sarah R. Schalman-Bergen (jlm, COURT STAFF) (Filed on 7/28/2011) (Entered:
07/28/2011)

08/02/2011

56

MOTION to Transfer Case to the San Jose Division, filed by Siddharth Hariharan. Responses
due by 8/8/2011. (Attachments: # 1 Proposed Order)(Fastiff, Eric) (Filed on 8/2/2011)
Modified on 8/3/2011 (jlm, COURT STAFF). (Entered: 08/02/2011)

08/02/2011

57

Declaration of Eric B. Fastiff in Support of 56 Motion to Transfer Actions to the San Jose
Division filed by Siddharth Hariharan. (Related document(s) 56 ) (Fastiff, Eric) (Filed on
8/2/2011) Modified on 8/3/2011 (jlm, COURT STAFF). (Entered: 08/02/2011)

08/04/2011

58

ORDER: That case numbers C-11-2509-SBA, C-11-3538-SBA, C-11-3539-SBA, C-113540-SBA and C-11-3541-SBA be TRANSFERRED to the San Jose Division re 35 Notice
and 56 Motion to Transfer Case. Signed by Judge Saundra Brown Armstrong, on 7/28/11.
(lrc, COURT STAFF) (Filed on 8/4/2011) Modified on 8/5/2011 (jlm, COURT STAFF).
(Entered: 08/04/2011)

08/05/2011

59

NOTICE of Change of Address by Daniel Edward Purcell (Purcell, Daniel) (Filed on
8/5/2011) (Entered: 08/05/2011)

08/05/2011

60

ORDER REASSIGNING CASE. Case reassigned to Judge Hon. Lucy H. Koh for all further
proceedings. Judge Hon. Saundra Brown Armstrong no longer assigned to the case. Signed
by The Executive Committee, on 08/05/2011. (jlm, COURT STAFF) (Filed on 8/5/2011)
(Entered: 08/05/2011)

08/08/2011

61

CLERKS NOTICE SETTING CASE MANAGEMENT CONFERENCE AFTER
REASSIGNMENT Case Management Statement due by 10/19/2011. Case Management
Conference set for 10/26/2011 02:00 PM in Courtroom 8, 4th Floor, San Jose. (mpb, COURT
STAFF) (Filed on 8/8/2011) (Entered: 08/08/2011)

08/08/2011

62

CERTIFICATE OF SERVICE by Siddharth Hariharan of Standing Order Regarding Case
Management In Civil Cases For The Northern District Of California, San Jose Division
(Harvey, Dean) (Filed on 8/8/2011) (Entered: 08/08/2011)

08/11/2011

Case Assigned to Magistrate Judge Howard R. Lloyd for all discovery matters. (tsh, COURT
STAFF) (Filed on 8/11/2011) (Entered: 08/11/2011)

09/06/2011

63

Proposed Pretrial Order Number 1 by Adobe Systems Inc., Intel Corp., Siddharth Hariharan,
Pixar, Lucasfilm Ltd., Google Inc., Apple Inc., Intuit Inc.. (Harvey, Dean) (Filed on
9/6/2011) (Entered: 09/06/2011)

09/12/2011

64

ORDER re 21 in 5:11-cv-03541-LHK: Adopting, as modified, Proposed Pretrial Order No. 1.
Signed by Judge Koh on 9/12/2011. Case Numbers 11-CV-3538, 11-CV-3539, 11-CV-3540

1151

and 11-CV-3541 are hereby CONSOLIDATED under MASTER FILE No. 11-CV-2509
LHK. All docket entries regarding the Consolidated Action shall be docketed under Master
File Number 11-CV-2509. If a document pertains to only one or some of the consolidated
cases, it will be docketed on the Master Docket with the notation in the docket text as to the
case number(s) to which it pertains. (lhklc3, COURT STAFF) (Filed on 9/12/2011) Modified
text on 9/13/2011 (dhm, COURT STAFF). (Entered: 09/12/2011)
09/13/2011

65

AMENDED COMPLAINT Consolidated against Adobe Systems Inc., Apple Inc., Google
Inc., Intel Corp., Intuit Inc., Lucasfilm Ltd., Pixar. Filed bySiddharth Hariharan. (Saveri,
Joseph) (Filed on 9/13/2011) (Entered: 09/13/2011)

09/22/2011

66

MOTION for Leave to File DEFENDANT LUCASFILM LTD.'S MOTION FOR
ADMINISTRATIVE RELIEF REQUESTING LEAVE TO FILE A SEPARATE MOTION TO
DISMISS; DECLARATION OF DANIEL PURCELL IN SUPPORT filed by Lucasfilm Ltd..
(Attachments: # 1 Proposed Order)(Purcell, Daniel) (Filed on 9/22/2011) (Entered:
09/22/2011)

09/26/2011

67

OPPOSITION to ( 66 MOTION for Administrative Relief Requesting Leave to File a
Separate Motion to Dismiss ) ; Declaration of Eric B. Fastiff in Opposition, filed by Michael
Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Harvey,
Dean) (Filed on 9/26/2011) Modified text on 9/27/2011 (dhm, COURT STAFF). (Entered:
09/26/2011)

09/27/2011

68

NOTICE of Substitution of Counsel by Frank Hinman substituting in for Holly A. House as
counsel for Intel Corporation (Hinman, Frank) (Filed on 9/27/2011) (Entered: 09/27/2011)

09/28/2011

69

Order by Hon. Lucy H. Koh granting in part and denying in part 66 Motion for Leave to File.
(lhklc1, COURT STAFF) (Filed on 9/28/2011) (Entered: 09/28/2011)

10/04/2011

70

ADR Certification (ADR L.R. 3-5 b) of discussion of ADR options (Kiernan, David) (Filed
on 10/4/2011) (Entered: 10/04/2011)

10/04/2011

71

ADR Certification (ADR L.R. 3-5 b) of discussion of ADR options (Broderick, Catherine)
(Filed on 10/4/2011) (Entered: 10/04/2011)

10/05/2011

72

ADR Certification (ADR L.R. 3-5 b) of discussion of ADR options (Harvey, Dean) (Filed on
10/5/2011) (Entered: 10/05/2011)

10/05/2011

73

ADR Certification (ADR L.R. 3-5 b) of discussion of ADR options (Alinder, Zachary) (Filed
on 10/5/2011) (Entered: 10/05/2011)

10/06/2011

74

ADR Certification (ADR L.R. 3-5 b) of discussion of ADR options (Tubach, Michael) (Filed
on 10/6/2011) (Entered: 10/06/2011)

10/12/2011

75

ADR Certification (ADR L.R. 3-5 b) of discussion of ADR options by Henn and Kennedy for
Pixar (Henn, Emily) (Filed on 10/12/2011) (Entered: 10/12/2011)

10/13/2011

76

Statement DISCOVERY DISPUTE JOINT REPORT #1 by Adobe Systems Inc., Apple Inc.,
Michael Devine, Mark Fichtner, Google Inc., Siddharth Hariharan, Intel Corp., Intuit Inc.,
Lucasfilm Ltd., Brandon Marshall, Pixar, Daniel Stover. (Saveri, Joseph) (Filed on
10/13/2011) (Entered: 10/13/2011)

10/13/2011

77

MOTION to Dismiss filed by Lucasfilm Ltd.. Motion Hearing set for 1/19/2012 09:00 AM in
Courtroom 8, 4th Floor, San Jose before Hon. Lucy H. Koh. Responses due by 10/27/2011.
Replies due by 11/3/2011. (Purcell, Daniel) (Filed on 10/13/2011) (Entered: 10/13/2011)

10/13/2011

78

Proposed Order re 77 Motion to Dismiss, by Lucasfilm Ltd.. (Purcell, Daniel) (Filed on
10/13/2011) Modified on 10/14/2011 linking entry to document #77 (dhm, COURT STAFF).
(Entered: 10/13/2011)

10/13/2011

79

MOTION to Dismiss Consolidated Amended Complaint filed by Apple Inc.. Motion Hearing

1152

set for 1/19/2012 01:30 PM in Courtroom 8, 4th Floor, San Jose before Hon. Lucy H. Koh.
Responses due by 11/4/2011. Replies due by 12/2/2011. (Attachments: # 1 Declaration, # 2
Proposed Order)(Tubach, Michael) (Filed on 10/13/2011) (Entered: 10/13/2011)
10/13/2011

80

Joint MOTION to Stay Discovery filed by Google Inc.. Motion Hearing set for 12/8/2011
01:30 PM in Courtroom 8, 4th Floor, San Jose before Hon. Lucy H. Koh. Responses due by
10/27/2011. Replies due by 11/3/2011. (Attachments: # 1 Declaration of Lee H. Rubin, # 2
Exhibit A, # 3 Exhibit B, # 4 Proposed Order)(Rubin, Lee) (Filed on 10/13/2011) (Entered:
10/13/2011)

10/14/2011

81

CERTIFICATE OF SERVICE by Apple Inc. re 79 MOTION to Dismiss Consolidated
Amended Complaint (Tubach, Michael) (Filed on 10/14/2011) (Entered: 10/14/2011)

10/14/2011

82

CLERKS NOTICE Continuing Motion Hearing, Set/Reset Deadlines as to 79 MOTION to
Dismiss Consolidated Amended Complaint, 77 MOTION to Dismiss. Motion Hearing set for
1/26/2012 01:30 PM in Courtroom 8, 4th Floor, San Jose before Hon. Lucy H. Koh. (mpb,
COURT STAFF) (Filed on 10/14/2011) (Entered: 10/14/2011)

10/17/2011

83

Amended MOTION to Dismiss filed by Lucasfilm Ltd.. Motion Hearing set for 1/26/2012
01:30 PM in Courtroom 8, 4th Floor, San Jose before Hon. Lucy H. Koh. Responses due by
10/27/2011. Replies due by 11/3/2011. (Purcell, Daniel) (Filed on 10/17/2011) (Entered:
10/17/2011)

10/19/2011

84

JOINT CASE MANAGEMENT STATEMENT filed by Adobe Systems Inc., Apple Inc.,
Michael Devine, Mark Fichtner, Google Inc., Siddharth Hariharan, Intel Corp., Intuit Inc.,
Lucasfilm Ltd., Brandon Marshall, Pixar, Daniel Stover. (Shaver, Anne) (Filed on
10/19/2011) (Entered: 10/19/2011)

10/20/2011

85

JOINT CASE MANAGEMENT STATEMENT Amended Joint Case Management
Conference Statement filed by Adobe Systems Inc., Apple Inc., Michael Devine, Mark
Fichtner, Google Inc., Siddharth Hariharan, Intel Corp., Intuit Inc., Lucasfilm Ltd., Brandon
Marshall, Pixar, Daniel Stover. (Shaver, Anne) (Filed on 10/20/2011) (Entered: 10/20/2011)

10/25/2011

86

ADR Certification (ADR L.R. 3-5 b) of discussion of ADR options of Google Inc. (Rubin,
Lee) (Filed on 10/25/2011) (Entered: 10/25/2011)

10/25/2011

87

ADR Certification (ADR L.R. 3-5 b) of discussion of ADR options (Harris, Cody) (Filed on
10/25/2011) (Entered: 10/25/2011)

10/26/2011

88

Minute Entry and Case Management Order: Initial Case Management Conference held on
10/26/2011 before Judge Lucy H. Koh (Date Filed: 10/26/2011). Further Case Management
Conference set for 1/26/2012 01:30 PM in Courtroom 8, 4th Floor, San Jose. Jury Selection
set for 6/10/2013 09:00 AM in Courtroom 8, 4th Floor, San Jose before Hon. Lucy H. Koh.
Jury Trial set for 6/10/2013 09:00 AM in Courtroom 8, 4th Floor, San Jose before Hon. Lucy
H. Koh. Pretrial Conference set for 5/15/2013 02:00 PM in Courtroom 8, 4th Floor, San Jose
before Hon. Lucy H. Koh. (Court Reporter Lee-Anne Shortridge.) (mpb, COURT STAFF)
(Date Filed: 10/26/2011) (Entered: 10/28/2011)

11/03/2011

89

NOTICE by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel
Stover re 65 Amended Complaint [NOTICE OF WITHDRAWAL OF PRAYER FOR
INJUNCTIVE RELIEF] (Glackin, Brendan) (Filed on 11/3/2011) (Entered: 11/03/2011)

11/04/2011

90

STATUS REPORT Regarding Voluntary Dismissal of Related Case, Pursuant To The
Courts October 26, 2011 Minute Order and Case Management Order (Dkt. 88) by Michael
Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Lehe,
Katherine) (Filed on 11/4/2011) (Entered: 11/04/2011)

11/04/2011

91

OPPOSITION to ( 83 AMENDED MOTION to Dismiss ) filed by Michael Devine, Mark
Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Saveri, Joseph) (Filed on
11/4/2011) Modified text on 11/7/2011 (dhm, COURT STAFF). (Entered: 11/04/2011)

1153

11/04/2011

92

OPPOSITION to ( 79 JOINT MOTION to Dismiss Consolidated Amended Complaint ) filed
by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover.
(Saveri, Joseph) (Filed on 11/4/2011) Modified text on 11/7/2011 (dhm, COURT STAFF).
(Entered: 11/04/2011)

11/04/2011

93

DECLARATION of Dean M. Harvey in Opposition to 79 MOTION to Dismiss Consolidated
Amended Complaint filed byMichael Devine, Mark Fichtner, Siddharth Hariharan, Brandon
Marshall, Daniel Stover. (Attachments: # 1 Exhibit A, # 2 Exhibit B, # 3 Exhibit C, # 4
Exhibit D, # 5 Exhibit E, # 6 Exhibit F)(Related document(s) 79 ) (Harvey, Dean) (Filed on
11/4/2011) (Entered: 11/04/2011)

11/07/2011

94

Transcript of Proceedings held on 10-27-11, before Judge Lucy H. Koh. Court
Reporter/Transcriber Lee-Anne Shortridge, Telephone number 408-287-4580. Per General
Order No. 59 and Judicial Conference policy, this transcript may be viewed only at the
Clerks Office public terminal or may be purchased through the Court Reporter/Transcriber
until the deadline for the Release of Transcript Restriction.After that date it may be obtained
through PACER. Any Notice of Intent to Request Redaction, if required, is due no later than
5 business days from date of this filing. Release of Transcript Restriction set for 2/6/2012.
(las, ) (Filed on 11/7/2011) (Entered: 11/07/2011)

11/30/2011

95

STIPULATION Stipulated [Proposed] Protective Order by Adobe Systems Inc., Apple Inc.,
Michael Devine, Mark Fichtner, Google Inc., Siddharth Hariharan, Intel Corp., Intuit Inc.,
Lucasfilm Ltd., Brandon Marshall, Pixar, Daniel Stover. (Harvey, Dean) (Filed on
11/30/2011) (Entered: 11/30/2011)

12/01/2011

CLERKS NOTICE: The parties are advised to take notice of the new Standing Order
Regarding Motions to File Under Seal in Civil Actions before U.S. District Judge Lucy H.
Koh.THIS IS A TEXT ONLY DOCKET ENTRY, THERE IS NO DOCUMENT
ASSOCIATED WITH THIS NOTICE (mpb, COURT STAFF) (Filed on 12/1/2011)
(Entered: 12/01/2011)

12/01/2011

CLERKS NOTICE: The parties are advised to take notice of the new Standing Order
Regarding Motions to File Under Seal in Civil Actions before U.S. District Judge Lucy H.
Koh.THIS IS A TEXT ONLY DOCKET ENTRY, THERE IS NO DOCUMENT
ASSOCIATED WITH THIS NOTICE. (mpb, COURT STAFF) (Filed on 12/1/2011)
(Entered: 12/01/2011)

12/02/2011

96

REPLY (re 83 Amended MOTION to Dismiss ) DEFENDANT LUCASFILM LTD.'S REPLY
IN SUPPORT OF MOTION TO DISMISS PLAINTIFFS' CONSOLIDATED AMENDED
COMPLAINT filed byLucasfilm Ltd.. (Purcell, Daniel) (Filed on 12/2/2011) (Entered:
12/02/2011)

12/02/2011

97

REPLY (re 79 MOTION to Dismiss Consolidated Amended Complaint ) filed byApple Inc..
(Tubach, Michael) (Filed on 12/2/2011) (Entered: 12/02/2011)

12/05/2011

98

CERTIFICATE OF SERVICE by Apple Inc. re 97 Reply to Opposition/Response (Tubach,
Michael) (Filed on 12/5/2011) (Entered: 12/05/2011)

12/05/2011

99

STIPULATION and [Proposed] Order Concerning Testifying Expert Discovery by Intuit
Inc.. (Attachments: # 1 Certificate/Proof of Service Proof of Service by U.S. Mail)
(Broderick, Catherine) (Filed on 12/5/2011) (Entered: 12/05/2011)

01/05/2012

100

NOTICE by Intuit Inc. of Attorney Name and Email Change (Broderick, Catherine) (Filed on
1/5/2012) (Entered: 01/05/2012)

01/18/2012

101

NOTICE of Appearance by Joshua P. Davis (Davis, Joshua) (Filed on 1/18/2012) (Entered:
01/18/2012)

01/19/2012

102

Administrative Motion to File Under Seal Joint Case Management Conference Statement
filed by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel

1154

Stover. (Attachments: # 1 Exhibit Joint Case Management Conference Statement (Proposed
Public Redacted Version))(Harvey, Dean) (Filed on 1/19/2012) (Entered: 01/19/2012)
01/19/2012

103

CERTIFICATE OF SERVICE by Michael Devine, Mark Fichtner, Siddharth Hariharan,
Brandon Marshall, Daniel Stover re 102 Administrative Motion to File Under Seal Joint
Case Management Conference Statement (Harvey, Dean) (Filed on 1/19/2012) (Entered:
01/19/2012)

01/23/2012

104

ORDER Concerning Testifying Expert Discovery. Signed by Judge Lucy H. Koh on
1/23/2012. (lhklc1, COURT STAFF) (Filed on 1/23/2012) (Entered: 01/23/2012)

01/24/2012

105

REQUEST by Apple Inc. to Bring Electronic Equipment into the Courtroom (Attachments: #
1 Proposed Order)(Brown, Christina) (Filed on 1/24/2012) Modified text on 1/25/2012 (dhm,
COURT STAFF). (Entered: 01/24/2012)

01/24/2012

106

ORDER Granting 105 Request to Bring Electronic Equipment into the Courtroom, filed by
Apple Inc.. Signed by Judge Lucy H. Koh on 1/24/12. (mpb, COURT STAFF) (Filed on
1/24/2012) Modified text on 1/25/2012 (dhm, COURT STAFF). (Entered: 01/24/2012)

01/24/2012

107

STIPULATION AND ORDER (MODIFIED BY THE COURT) re 95 . Signed by Magistrate
Judge Howard R. Lloyd on 1/24/12. (hrllc1, COURT STAFF) (Filed on 1/24/2012) (Entered:
01/24/2012)

01/26/2012

108

Minute Entry and Case Management Order: Further Case Management Conference held on
1/26/2012 before Judge Lucy H. Koh (Date Filed: 1/26/2012). Further Case Management
Conference set for 4/18/2012 02:00 PM in Courtroom 8, 4th Floor, San Jose. (Court Reporter
Lee-Anne Shortridge.) (mpb, COURT STAFF) (Date Filed: 1/26/2012) (Entered:
01/27/2012)

01/26/2012

110

Minute Entry: Motion Hearing held on 1/26/2012 before Judge Lucy H. Koh (Date Filed:
1/26/2012) re 83 Amended MOTION to Dismiss filed by Lucasfilm Ltd., 79 MOTION to
Dismiss Consolidated Amended Complaint filed by Apple Inc.. (Court Reporter Lee-Anne
Shortridge.) (mpb, COURT STAFF) (Date Filed: 1/26/2012) (Entered: 01/27/2012)

01/27/2012

109

JOINT CASE MANAGEMENT STATEMENT filed by Michael Devine, Mark Fichtner,
Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Harvey, Dean) (Filed on 1/27/2012)
(Entered: 01/27/2012)

01/30/2012

111

STATUS REPORT PLAINTIFFS STATUS REPORT REGARDING DISMISSAL WITHOUT
PREJUDICE OF PRAYER FOR DECLARATORY RELIEF AND CAL. BUS. & PROF.
CODE § 16600 CLAIM, PURSUANT TO THE COURTS JANUARY 26, 2012 MINUTE
ORDER AND CASE MANAGEMENT ORDER (Dkt. 108) by Michael Devine, Mark Fichtner,
Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Lehe, Katherine) (Filed on
1/30/2012) (Entered: 01/30/2012)

01/31/2012

112

Transcript of Proceedings held on 1-26-12, before Judge Lucy H. Koh. Court
Reporter/Transcriber Lee-Anne Shortridge, Telephone number 408-287-4580. Per General
Order No. 59 and Judicial Conference policy, this transcript may be viewed only at the
Clerks Office public terminal or may be purchased through the Court Reporter/Transcriber
until the deadline for the Release of Transcript Restriction.After that date it may be obtained
through PACER. Any Notice of Intent to Request Redaction, if required, is due no later than
5 business days from date of this filing. Release of Transcript Restriction set for 4/30/2012.
(las, ) (Filed on 1/31/2012) (Entered: 01/31/2012)

03/23/2012

113

MOTION to Withdraw as Attorney Motion for Leave to Withdraw as Counsel filed by
Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover.
Responses due by 4/6/2012. Replies due by 4/13/2012. (Attachments: # 1 Proposed Order)
(Lehe, Katherine) (Filed on 3/23/2012) (Entered: 03/23/2012)

03/30/2012

114

STIPULATION re: Production Format of Electronically Stored Information filed by Apple

1155

Inc.. (Brown, Christina) (Filed on 3/30/2012) (Entered: 03/30/2012)
04/11/2012

115

JOINT CASE MANAGEMENT STATEMENT filed by Michael Devine, Mark Fichtner,
Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Harvey, Dean) (Filed on 4/11/2012)
(Entered: 04/11/2012)

04/17/2012

116

MOTION to Relate Case filed by Google Inc.. (Attachments: # 1 Proposed Order)(Rubin,
Lee) (Filed on 4/17/2012) (Entered: 04/17/2012)

04/17/2012

117

Declaration of Lee H. Rubin in Support of 116 MOTION to Relate Case filed byGoogle Inc..
(Attachments: # 1 Exhibit A)(Related document(s) 116 ) (Rubin, Lee) (Filed on 4/17/2012)
(Entered: 04/17/2012)

04/17/2012

118

Declaration of Lee H. Rubin in Support of 116 MOTION to Relate Case With Corrected
Exhibit A filed byGoogle Inc.. (Attachments: # 1 Exhibit A)(Related document(s) 116 )
(Rubin, Lee) (Filed on 4/17/2012) (Entered: 04/17/2012)

04/18/2012

119

ORDER by Judge Lucy H. Koh granting in part and denying in part (79) Motion to Dismiss;
denying (83) Motion to Dismiss in case 5:11-cv-02509-LHK. (lhklc1, COURT STAFF)
(Filed on 4/18/2012) (Entered: 04/18/2012)

04/18/2012

120

Minute Entry and Case Management Order: Further Case Management Conference held on
4/18/2012 before Judge Lucy H. Koh (Date Filed: 4/18/2012). Further Case Management
Conference set for 5/31/2012 01:30 PM in Courtroom 8, 4th Floor, San Jose. (Court Reporter
Christine Bedard.) (mpb, COURT STAFF) (Date Filed: 4/18/2012) (Entered: 04/23/2012)

04/25/2012

121

Order by Hon. Lucy H. Koh granting (116) Motion to Relate Case in case 5:11-cv-02509LHK. Related Case: 5:12-cv-1262-LHK (lhklc1, COURT STAFF) (Filed on 4/25/2012)
Modified on 4/26/2012 (dhm, COURT STAFF). (Entered: 04/25/2012)

04/26/2012

122

NOTICE of Substitution of Counsel by Frank H Busch and Sujal J. Shah (Busch, Frank)
(Filed on 4/26/2012) (Entered: 04/26/2012)

05/01/2012

123

STIPULATION Extending Time to Answer Consolidated Amended Complaint filed by
Adobe Systems Inc., Apple Inc., Michael Devine, Mark Fichtner, Google Inc., Siddharth
Hariharan, Intel Corp., Intuit Inc., Lucasfilm Ltd., Brandon Marshall, Pixar, Daniel Stover.
(Busch, Frank) (Filed on 5/1/2012) (Entered: 05/01/2012)

05/16/2012

124

NOTICE of Appearance by Richard Martin Heimann (Heimann, Richard) (Filed on
5/16/2012) (Entered: 05/16/2012)

05/16/2012

125

NOTICE of Appearance by Kelly M. Dermody (Dermody, Kelly) (Filed on 5/16/2012)
(Entered: 05/16/2012)

05/21/2012

126

ANSWER to Amended Complaint byIntel Corp.. (Pickett, Donn) (Filed on 5/21/2012)
(Entered: 05/21/2012)

05/21/2012

127

Defendant Adobe Systems Inc.'s ANSWER to Amended Complaint byAdobe Systems Inc..
(Attachments: # 1 Certificate/Proof of Service)(Kiernan, David) (Filed on 5/21/2012)
(Entered: 05/21/2012)

05/21/2012

128

Defendant Intuit Inc's ANSWER to Amended Complaint (Jury Demand) byIntuit Inc..
(Attachments: # 1 Certificate/Proof of Service)(Stewart, Craig) (Filed on 5/21/2012)
(Entered: 05/21/2012)

05/21/2012

129

ANSWER to Amended Complaint byPixar. (Henn, Emily) (Filed on 5/21/2012) (Entered:
05/21/2012)

05/21/2012

130

ANSWER to Amended Complaint byLucasfilm Ltd.. (Purcell, Daniel) (Filed on 5/21/2012)
(Entered: 05/21/2012)

05/21/2012

131

ANSWER to Amended Complaint byGoogle Inc.. (Rubin, Lee) (Filed on 5/21/2012)
1156

(Entered: 05/21/2012)
05/21/2012

132

ANSWER to Amended Complaint byApple Inc.. (Tubach, Michael) (Filed on 5/21/2012)
(Entered: 05/21/2012)

05/22/2012

133

CERTIFICATE OF SERVICE by Apple Inc. re 132 Answer to Amended Complaint
(Tubach, Michael) (Filed on 5/22/2012) (Entered: 05/22/2012)

05/23/2012

134

STIPULATION WITH PROPOSED ORDER [Extending Case Management Conference]
filed by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel
Stover. (Harvey, Dean) (Filed on 5/23/2012) (Entered: 05/23/2012)

05/24/2012

135

Order by Hon. Lucy H. Koh denying (134) Stipulation in case 5:11-cv-02509LHK.Associated Cases: 5:11-cv-02509-LHK, 5:11-cv-03538-LHK, 5:11-cv-03539-LHK,
5:11-cv-03540-LHK, 5:11-cv-03541-LHK, 5:12-cv-01262-LHK(lhklc1, COURT STAFF)
(Filed on 5/24/2012) (Entered: 05/24/2012)

05/24/2012

Set/Reset Hearing re 135 Order on Stipulation, Further Case Management Conference set for
7/25/2012 02:00 PM in Courtroom 8, 4th Floor, San Jose. (mpb, COURT STAFF) (Filed on
5/24/2012) (Entered: 05/24/2012)

05/25/2012

136

ASSOCIATION of Counsel Joseph R. Saveri, Saveri Law Firm by Michael Devine, Mark
Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Shaver, Anne) (Filed on
5/25/2012) (Entered: 05/25/2012)

05/25/2012

137

MOTION for Extension of Time to File Plaintiffs' Motion for Class Certification Pursuant to
Civil Local Rule 6-3 filed by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon
Marshall, Daniel Stover. (Shaver, Anne) (Filed on 5/25/2012) (Entered: 05/25/2012)

05/25/2012

138

Declaration of Ann B. Shaver in Support of 137 MOTION for Extension of Time to File
Plaintiffs' Motion for Class Certification Pursuant to Civil Local Rule 6-3 filed byMichael
Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover.
(Attachments: # 1 Exhibit A, # 2 Exhibit B, # 3 Exhibit C, # 4 Exhibit D, # 5 Exhibit E, # 6
Exhibit F, # 7 Exhibit G, # 8 Exhibit H, # 9 Exhibit I, # 10 Exhibit J, # 11 Exhibit K, # 12
Exhibit L, # 13 Exhibit M, # 14 Exhibit N, # 15 Exhibit O, # 16 Exhibit P, # 17 Exhibit Q, #
18 Exhibit R, # 19 Exhibit S, # 20 Exhibit T, # 21 Exhibit U, # 22 Exhibit 1, # 23 Exhibit 2)
(Related document(s) 137 ) (Shaver, Anne) (Filed on 5/25/2012) (Entered: 05/25/2012)

05/25/2012

139

Proposed Order re 137 MOTION for Extension of Time to File Plaintiffs' Motion for Class
Certification Pursuant to Civil Local Rule 6-3 by Michael Devine, Mark Fichtner, Siddharth
Hariharan, Brandon Marshall, Daniel Stover. (Shaver, Anne) (Filed on 5/25/2012) (Entered:
05/25/2012)

05/29/2012

140

Order by Hon. Lucy H. Koh denying (137) Motion for Extension of Time to File in case
5:11-cv-02509-LHK. Associated Cases: 5:11-cv-02509-LHK, 5:11-cv-03538-LHK, 5:11-cv03539-LHK, 5:11-cv-03540-LHK, 5:11-cv-03541-LHK, 5:12-cv-01262-LHK(lhklc1,
COURT STAFF) (Filed on 5/29/2012) (Entered: 05/29/2012)

05/29/2012

Set/Reset Hearing re 140 Order on Motion for Extension of Time to File, Further Case
Management Conference set for 6/4/2012 02:30 PM in Courtroom 8, 4th Floor, San Jose.
(mpb, COURT STAFF) (Filed on 5/29/2012) (Entered: 05/29/2012)

05/29/2012

141

Discovery Dispute Joint Report #2 by Apple Inc., Michael Devine, Mark Fichtner, Siddharth
Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Exhibit A)(Tubach, Michael)
(Filed on 5/29/2012) Modified text on 5/30/2012 (dhm, COURT STAFF). (Entered:
05/29/2012)

06/01/2012

142

JOINT CASE MANAGEMENT STATEMENT filed by Adobe Systems Inc., Apple Inc.,
Michael Devine, Mark Fichtner, Google Inc., Siddharth Hariharan, Intel Corp., Intuit Inc.,
Lucasfilm Ltd., Brandon Marshall, Pixar, Daniel Stover. (Harvey, Dean) (Filed on 6/1/2012)
1157
(Entered: 06/01/2012)

06/01/2012

143

NOTICE of Appearance by Joseph R. Saveri (Saveri, Joseph) (Filed on 6/1/2012) (Entered:
06/01/2012)

06/03/2012

144

UNOPPOSED ADMINISTRATIVE MOTION to Amend Pretrial Order No. 1 filed by
Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover.
Responses due by 6/18/2012. Replies due by 6/25/2012. (Attachments: # 1 Exhibit Exhibit A
to Motion - [Proposed Order])(Shaver, Anne) (Filed on 6/3/2012) Modified text on 6/4/2012
(dhm, COURT STAFF). (Entered: 06/03/2012)

06/03/2012

145

Declaration of Anne B. Shaver in Support of 144 MOTION to Amend/Correct Plaintiffs
Unopposed Administrative Motion to Amend Pretrial Order No. 1 filed byMichael Devine,
Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1
Exhibit A to Shaver Declaration - Firm Resume)(Related document(s) 144 ) (Shaver, Anne)
(Filed on 6/3/2012) (Entered: 06/03/2012)

06/03/2012

146

Declaration of Joseph R. Saveri in Support of 144 MOTION to Amend/Correct Plaintiffs
Unopposed Administrative Motion to Amend Pretrial Order No. 1 filed byMichael Devine,
Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Related document(s)
144 ) (Shaver, Anne) (Filed on 6/3/2012) (Entered: 06/03/2012)

06/04/2012

147

Order by Hon. Lucy H. Koh granting (144) Motion to Amend/Correct. Associated Cases:
5:11-cv-02509-LHK, 5:11-cv-03538-LHK, 5:11-cv-03539-LHK, 5:11-cv-03540-LHK, 5:11cv-03541-LHK, 5:12-cv-01262-LHK(lhklc1, COURT STAFF) (Filed on 6/4/2012) (Entered:
06/04/2012)

06/04/2012

149

Minute Entry: Further Case Management Conference held on 6/4/2012 before Judge Lucy H.
Koh (Date Filed: 6/4/2012). Further Case Management Conference set for 9/12/2012 02:00
PM in Courtroom 8, 4th Floor, San Jose. (Court Reporter Lee-Anne Shortridge.) (mpb,
COURT STAFF) (Date Filed: 6/4/2012) (Entered: 06/05/2012)

06/05/2012

148

Case Management Order; Referral of Discovery; Further Case Management Order. ***
Counsel is advised that this Order contains new dates in addition to the dates discussed
at the June 4, 2012 Case Management Conference.***
. Signed by Judge Lucy H. Koh on 6/5/2012. (lhklc1, COURT STAFF) (Filed on 6/5/2012)
(Entered: 06/05/2012)

06/12/2012

Pursuant to Signed Order ( 148 ). Case Reassigned to Magistrate Judge Paul Singh Grewal
for all further discovery disputes. Magistrate Judge Howard R. Lloyd no longer assigned to
the case. (tsh, COURT STAFF) (Filed on 6/12/2012) (Entered: 06/12/2012)

06/14/2012

150

NOTICE by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel
Stover of withdrawal of Attorney John Radice (Nussbaum, Linda) (Filed on 6/14/2012)
(Entered: 06/14/2012)

06/14/2012

151

STIPULATION WITH PROPOSED ORDER Regarding Amending Answers and Affirmative
Defenses filed by Pixar. (Henn, Emily) (Filed on 6/14/2012) (Entered: 06/14/2012)

06/15/2012

152

Stipulation and Order Regarding Amending Answers and Affirmative Defenses by Hon.
Lucy H. Koh granting (151) Stipulation in case 5:11-cv-02509-LHK. Associated Cases:
5:11-cv-02509-LHK, 5:11-cv-03538-LHK, 5:11-cv-03539-LHK, 5:11-cv-03540-LHK, 5:11cv-03541-LHK, 5:12-cv-01262-LHK (lhklc1, COURT STAFF) (Filed on 6/15/2012)
Modified text on 6/18/2012 (dhm, COURT STAFF). (Entered: 06/15/2012)

06/18/2012

153

NOTICE of Compliance with the Courts June 5, 2012 Case Management Order by Michael
Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover (Attachments:
# 1 Declaration of Dean M. Harvey Regarding Plaintiffs Compliance with the Courts June 5,
2012 Case Management Order, # 2 Declaration of Joseph R. Saveri Regarding Compliance
with the Courts June 5, 2012 Case Management Order)(Harvey, Dean) (Filed on 6/18/2012)
Modified text on 6/19/2012 (dhm, COURT STAFF). (Entered: 06/18/2012) 1158

06/18/2012

154

Declaration of Eric B. Evans regarding Compliance with 148 June 5, 2012 Case Management
Order by Google Inc.. (Evans, Eric) (Filed on 6/18/2012) Modified text on 6/19/2012 (dhm,
COURT STAFF). (Entered: 06/18/2012)

06/18/2012

155

Declaration of Catherine T. Zeng re 148 Order Regarding Defendant Intuit Inc.'s Production
of Data and Documents by Intuit Inc.. (Zeng, Catherine) (Filed on 6/18/2012) Modified text
on 6/19/2012 (dhm, COURT STAFF). (Entered: 06/18/2012)

06/18/2012

156

Declaration of David C. Kiernan re 148 Order Regarding Defendant Adobe Systems
Incorporateds Production of Data and Documents by Adobe Systems Inc.. (Kiernan, David)
(Filed on 6/18/2012) Modified text on 6/19/2012 (dhm, COURT STAFF). (Entered:
06/18/2012)

06/18/2012

157

Declaration of Jonathan Herczeg re 148 Order Regarding Pixar's Production of Documents
and Data by Pixar. (Henn, Emily) (Filed on 6/18/2012) Modified text on 6/19/2012 (dhm,
COURT STAFF). (Entered: 06/18/2012)

06/18/2012

158

Declaration of Frank M. Hinman re 148 Order Regarding Intel's Production of Data and
Documents by Intel Corp.. (Hinman, Frank) (Filed on 6/18/2012) Modified text on 6/19/2012
(dhm, COURT STAFF). (Entered: 06/18/2012)

06/18/2012

159

Declaration of Christina Brown re 148 Order Regarding Apple Inc.'s Document and Data
Productions by Apple Inc.. (Brown, Christina) (Filed on 6/18/2012) Modified text on
6/19/2012 (dhm, COURT STAFF). (Entered: 06/18/2012)

06/18/2012

160

Declaration of Justina K. Sessions re 148 Regarding Lucasfilm's Document and Data
Production filed by Lucasfilm Ltd.. (Sessions, Justina) (Filed on 6/18/2012) Modified on
6/19/2012 linking entry to entry #148 (dhm, COURT STAFF). (Entered: 06/18/2012)

06/21/2012

161

MOTION for leave to appear in Pro Hac Vice of Peter A. Barile III ( Filing fee $ 305, receipt
number 0971-6911874.) filed by Michael Devine, Mark Fichtner, Siddharth Hariharan,
Brandon Marshall, Daniel Stover. (Attachments: # 1 Proposed Order)(Barile, Peter) (Filed on
6/21/2012) (Entered: 06/21/2012)

07/02/2012

162

STATUS REPORT REGARDING REVIEW OF DOCUMENTS AND DATA by Michael
Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover.
(Attachments: # 1 Exhibit A)(Dermody, Kelly) (Filed on 7/2/2012) (Entered: 07/02/2012)

07/02/2012

163

Order by Hon. Lucy H. Koh granting 161 Motion for Pro Hac Vice.(lhklc1, COURT STAFF)
(Filed on 7/2/2012) (Entered: 07/02/2012)

07/02/2012

164

ORDER re Discovery. Signed by Judge Lucy H. Koh on 6/28/2012. (lhklc1, COURT
STAFF) (Filed on 7/2/2012) (Entered: 07/02/2012)

07/02/2012

165

ORDER re Case Schedule. Signed by Judge Lucy H. Koh on 7/2/2012. (lhklc1, COURT
STAFF) (Filed on 7/2/2012) (Entered: 07/02/2012)

07/03/2012

166

NOTICE of Appearance by Kevin Edward Rayhill (Rayhill, Kevin) (Filed on 7/3/2012)
(Entered: 07/03/2012)

07/05/2012

167

NOTICE of Appearance by Lisa Jennifer Leebove (Leebove, Lisa) (Filed on 7/5/2012)
(Entered: 07/05/2012)

07/05/2012

168

AMENDED ANSWER to 65 Consolidated Amended Complaint byLucasfilm Ltd.. (Purcell,
Daniel) (Filed on 7/5/2012) Modified on 7/6/2012 (gm, COURT STAFF). (Entered:
07/05/2012)

07/05/2012

169

Amended ANSWER to 65 Amended Complaint byIntel Corp.. (Pickett, Donn) (Filed on
7/5/2012) Modified on 7/6/2012 (gm, COURT STAFF). (Entered: 07/05/2012)

07/05/2012

170

AMENDED ANSWER to 65 AMENDED COMPLAINT byAdobe Systems Inc.. (Kiernan,
1159
David) (Filed on 7/5/2012) Modified on 7/6/2012 (gm, COURT STAFF). (Entered:

07/05/2012)
07/05/2012

171

AMENDED ANSWER to Plaintiffs' 65 Consolidated Amended Complaint byIntuit Inc..
(Zeng, Catherine) (Filed on 7/5/2012) Modified on 7/6/2012 (gm, COURT STAFF).
(Entered: 07/05/2012)

07/05/2012

172

AMENDED ANSWER to 65 Amended Complaint byPixar. (Henn, Emily) (Filed on
7/5/2012) Modified on 7/6/2012 (gm, COURT STAFF). (Entered: 07/05/2012)

07/05/2012

173

AMENDED ANSWER to 65 Amended Complaint byGoogle Inc.. (Rubin, Lee) (Filed on
7/5/2012) Modified on 7/6/2012 (gm, COURT STAFF). (Entered: 07/05/2012)

07/05/2012

174

AMENDED ANSWER to Plaintiffs' 65 Consolidated Amended Complaint byApple Inc..
(Tubach, Michael) (Filed on 7/5/2012) Modified on 7/6/2012 (gm, COURT STAFF).
(Entered: 07/05/2012)

07/09/2012

175

STIPULATION WITH PROPOSED ORDER AMENDING CASE SCHEDULE filed by
Adobe Systems Inc., Apple Inc., Michael Devine, Mark Fichtner, Google Inc., Siddharth
Hariharan, Intel Corp., Intuit Inc., Lucasfilm Ltd., Brandon Marshall, Pixar, Daniel Stover.
(Harvey, Dean) (Filed on 7/9/2012) (Entered: 07/09/2012)

07/10/2012

176

Order by Hon. Lucy H. Koh granting (175) Stipulation in case 5:11-cv-02509-LHK.
Associated Cases: 5:11-cv-02509-LHK, 5:11-cv-03538-LHK, 5:11-cv-03539-LHK, 5:11-cv03540-LHK, 5:11-cv-03541-LHK, 5:12-cv-01262-LHK(lhklc1, COURT STAFF) (Filed on
7/10/2012) (Entered: 07/10/2012)

07/10/2012

Set Deadlines/Hearings: Fact Discovery Cutoff 1/29/13; Expert Discovery Cutoff 3/26/2013.
Final Pretrial Conference set for 7/31/2013 02:00 PM in Courtroom 8, 4th Floor, San Jose.
Jury Selection set for 8/27/2013 09:00 AM in Courtroom 8, 4th Floor, San Jose before Hon.
Lucy H. Koh. Jury Trial set for 8/27/2013 09:00 AM in Courtroom 8, 4th Floor, San Jose
before Hon. Lucy H. Koh. (mpb, COURT STAFF) (Filed on 7/10/2012) (Entered:
07/18/2012)

07/10/2012

Set/Reset Hearing re 176 Order on Stipulation, Hearing re Class Certification Motion set for
12/13/2012 01:30 PM in Courtroom 8, 4th Floor, San Jose before Hon. Lucy H. Koh. (mpb,
COURT STAFF) (Filed on 7/10/2012) (Entered: 08/28/2012)

07/19/2012

177

CLERKS NOTICE AMENDING TRIAL SCHEDULE (CHANGING DATE FOR
COMMENCEMENT OF TRIAL) Jury Selection set for 8/26/2013 09:00 AM in Courtroom
8, 4th Floor, San Jose before Hon. Lucy H. Koh. Jury Trial set for 8/26/2013 09:00 AM in
Courtroom 8, 4th Floor, San Jose before Hon. Lucy H. Koh. (mpb, COURT STAFF) (Filed
on 7/19/2012) (Entered: 07/19/2012)

07/23/2012

178

ORDER to Show Cause Why Case No. 5:12-CV-01262-LHK Should Not Be Dismissed for
Failure to Prosecute. Signed by Judge Lucy H. Koh on 7/23/2012. (lhklc1S, COURT
STAFF) (Filed on 7/23/2012) Modified on 7/23/2012 (lhklc1S, COURT STAFF). (Entered:
07/23/2012)

09/06/2012

179

JOINT CASE MANAGEMENT STATEMENT filed by Michael Devine. (Leebove, Lisa)
(Filed on 9/6/2012) (Entered: 09/06/2012)

09/06/2012

180

NOTICE of Appearance by Joseph Peter Forderer (Forderer, Joseph) (Filed on 9/6/2012)
(Entered: 09/06/2012)

09/11/2012

181

CASE MANAGEMENT STATEMENT (SUPPLEMENTAL) filed by Michael Devine, Mark
Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Dermody, Kelly) (Filed on
9/11/2012) (Entered: 09/11/2012)

09/12/2012

182

RESPONSE to 181 Plaintiffs' Supplemental Case Management Statement by Google Inc..
(Rubin, Lee) (Filed on 9/12/2012) Modified text on 9/13/2012 (dhmS, COURT STAFF).
(Entered: 09/12/2012)
1160

09/12/2012

183

09/12/2012

Minute Entry and Case Management Order: Further Case Management Conference held on
9/12/2012 before Judge Lucy H. Koh (Date Filed: 9/12/2012). Final Pretrial Conference set
for 10/31/2013 01:30 PM in Courtroom 8, 4th Floor, San Jose. Jury Selection set for
11/12/2013 09:00 AM in Courtroom 8, 4th Floor, San Jose before Hon. Lucy H. Koh. Jury
Trial set for 11/12/2013 09:00 AM in Courtroom 8, 4th Floor, San Jose before Hon. Lucy H.
Koh. Motion Hearing set for 1/17/2013 01:30 PM in Courtroom 8, 4th Floor, San Jose before
Hon. Lucy H. Koh. (Court Reporter Lee-Anne Shortridge.) (mpb, COURT STAFF) (Date
Filed: 9/12/2012) (Entered: 09/13/2012)
Set/Reset Hearing re 183 Case Management Conference - Further, Set Hearings
(Inadvertently not calendared when Case Management Order was docketed) Further Case
Management Conference set for 12/12/2012 02:00 PM in Courtroom 8, 4th Floor, San Jose.
(mpb, COURT STAFF) (Filed on 9/12/2012) (Entered: 10/16/2012)

09/18/2012

184

Transcript of Proceedings held on 09-12-12, before Judge Lucy H. Koh. Court
Reporter/Transcriber Lee-Anne Shortridge, Telephone number 408-287-4580. Per General
Order No. 59 and Judicial Conference policy, this transcript may be viewed only at the
Clerks Office public terminal or may be purchased through the Court Reporter/Transcriber
until the deadline for the Release of Transcript Restriction.After that date it may be obtained
through PACER. Any Notice of Intent to Request Redaction, if required, is due no later than
5 business days from date of this filing. Release of Transcript Restriction set for 12/17/2012.
(las, ) (Filed on 9/18/2012) (Entered: 09/18/2012)

09/19/2012

185

NOTICE of Appearance by James Gerard Beebe Dallal (Dallal, James) (Filed on 9/19/2012)
(Entered: 09/19/2012)

10/01/2012

186

Administrative Motion to File Under Seal filed by Michael Devine, Mark Fichtner, Siddharth
Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Declaration of Joseph P.
Forderer, # 2 Proposed Order, # 3 Exhibit Class Certification Brief (Redacted), # 4 Exhibit
Colligan Declaration (Redacted), # 5 Exhibit Expert Report (Redacted), # 6 Exhibit Exhibits
to Shaver Declaration (Redacted), # 7 Exhibit Exhibits to Colligan Declaration (Redacted))
(Shaver, Anne) (Filed on 10/1/2012) (Entered: 10/01/2012)

10/01/2012

187

MOTION to Certify Class and Memorandum of Points and Authorities filed by Michael
Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. Motion
Hearing set for 1/17/2013 01:30 PM in Courtroom 8, 4th Floor, San Jose before Hon. Lucy
H. Koh. Responses due by 11/12/2012. Replies due by 12/10/2012. (Attachments: # 1
Proposed Order)(Shaver, Anne) (Filed on 10/1/2012) (Entered: 10/01/2012)

10/01/2012

188

Declaration of Ann B. Shaver in Support of 187 MOTION to Certify Class and
Memorandum of Points and Authorities filed byMichael Devine, Mark Fichtner, Siddharth
Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Exhibit 6, # 2 Exhibit 7, # 3
Exhibit 8, # 4 Exhibit 9, # 5 Exhibit 10, # 6 Exhibit 1-5, 11-55, 58-68, and 70, # 7 Exhibit 56,
# 8 Exhibit 57, # 9 Exhibit 69, # 10 Exhibit 71)(Related document(s) 187 ) (Shaver, Anne)
(Filed on 10/1/2012) (Entered: 10/01/2012)

10/01/2012

189

Declaration of Edward Colligan in Support of 187 MOTION to Certify Class and
Memorandum of Points and Authorities filed byMichael Devine, Mark Fichtner, Siddharth
Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Exhibit A & B)(Related
document(s) 187 ) (Shaver, Anne) (Filed on 10/1/2012) (Entered: 10/01/2012)

10/01/2012

190

Declaration of Edward E. Leamer, Ph.D. in Support of 187 MOTION to Certify Class and
Memorandum of Points and Authorities filed byMichael Devine, Mark Fichtner, Siddharth
Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Exhibit 1, # 2 Exhibit 2, # 3
Exhibit 3)(Related document(s) 187 ) (Shaver, Anne) (Filed on 10/1/2012) (Entered:
10/01/2012)

10/01/2012

191

CERTIFICATE OF SERVICE by Michael Devine, Mark Fichtner, Siddharth Hariharan,
Brandon Marshall, Daniel Stover re 188 Declaration in Support,, 189 Declaration in Support,
1161
186 Administrative Motion to File Under Seal , 190 Declaration in Support, 187 MOTION to

Certify Class and Memorandum of Points and Authorities (Shaver, Anne) (Filed on
10/1/2012) (Entered: 10/01/2012)
10/08/2012

192

Declaration of Robert Booth In Support of Plaintiffs' Administrative Motion to File Under
Seal filed byPalm Inc.. (Smith, Benjamin) (Filed on 10/8/2012) (Entered: 10/08/2012)

10/08/2012

193

Proposed Order re 192 Declaration in Support of Granting Plaintiffs' Administrative Motion
to File Under Seal by Palm Inc.. (Smith, Benjamin) (Filed on 10/8/2012) (Entered:
10/08/2012)

10/08/2012

194

MOTION to Withdraw as Attorney Jonathan Herczeg filed by Pixar. Responses due by
10/22/2012. Replies due by 10/29/2012. (Attachments: # 1 Proposed Order)(Henn, Emily)
(Filed on 10/8/2012) (Entered: 10/08/2012)

10/09/2012

195

Defendants' Joint Response to 186 Plaintiffs' Administrative Motion to Seal filed by Adobe
Systems Inc., Apple Inc., Lucasfilm Ltd., Intuit Inc., Google Inc., Intel Corp., Pixar.
(Attachments: # 1 Exhibit A)(Kiernan, David) (Filed on 10/9/2012) Modified on 10/10/2012
counsel posted document incorrectly as a motion and failed to link entry to document
#186 (dhmS, COURT STAFF). (Entered: 10/09/2012)

10/09/2012

196

Declaration of Donna Morris in Support of 195 Joint Response to Plaintiffs' Administrative
Motion to Seal filed byAdobe Systems Inc.. (Related document(s) 195 ) (Kiernan, David)
(Filed on 10/9/2012) Modified text on 10/10/2012 (dhmS, COURT STAFF). (Entered:
10/09/2012)

10/09/2012

197

Declaration of Lisa Borgeson in Support of 186 Plaintiffs' Administrative Motion to File
Under Seal filed byIntuit Inc.. (Related document(s) 195 ) (Kiernan, David) (Filed on
10/9/2012) Modified text on 10/10/2012 to conform with caption of document (dhmS,
COURT STAFF). (Entered: 10/09/2012)

10/09/2012

198

Proposed Order Granting 186 Plaintiffs' Administrative Motion to File Under Seal by Adobe
Systems Inc.. (Attachments: # 1 Exhibit A (Plaintiffs Notice of Motion and Motion for Class
Cert_Proposed Redactions), # 2 Exhibit B (Expert Report of Edward E. Leamer, Ph.D. With
Proposed Redactions), # 3 Exhibit C (Exhibits With Proposed Redactions))(Kiernan, David)
(Filed on 10/9/2012) Modified text on 10/10/2012 to conform with caption of document
(dhmS, COURT STAFF). (Entered: 10/09/2012)

10/09/2012

199

Declaration of DAVID J. ANDERMAN in Support of 195 Joint Response to Plaintiffs'
Administrative Motion to Seal filed by Lucasfilm Ltd.. (Related document(s) 195 ) (Purcell,
Daniel) (Filed on 10/9/2012) Modified text on 10/10/2012 (dhmS, COURT STAFF).
(Entered: 10/09/2012)

10/09/2012

200

Declaration of Alan Eustace in Support of 195 Administrative Motion to File Under Seal
filed by Google Inc.. (Related document(s) 195 ) (Evans, Eric) (Filed on 10/9/2012)
Modified text on 10/10/2012 to conform with caption of document (dhmS, COURT STAFF).
(Entered: 10/09/2012)

10/09/2012

201

Declaration of Frank Wagner in Support of 195 Administrative Motion to File Under Seal
filed by Google Inc.. (Related document(s) 195 ) (Evans, Eric) (Filed on 10/9/2012)
Modified text on 10/10/2012 to conform with caption of document (dhmS, COURT STAFF).
(Entered: 10/09/2012)

10/09/2012

202

Declaration of James M. Kennedy Pursuant to Civil Local Rule 79-5(d) Submitted in Support
of 195 Plaintiffs' Administrative Motion to File Under Seal filed by Pixar. (Related document
(s) 195 ) (Henn, Emily) (Filed on 10/9/2012) Modified text on 10/10/2012 to conform with
caption of document (dhmS, COURT STAFF). (Entered: 10/09/2012)

10/09/2012

203

Declaration of Tina M. Evangelista in Support of 195 Plaintiffs' Administrative Motion to
File Under Seal Plaintiffs' Notice of Motion and Motion for Class Certification and
Memorandum of Law in Support filed by Intel Corp.. (Related document(s) 195 ) (Busch,

1162

Frank) (Filed on 10/9/2012) Modified text on 10/10/2012 to conform with caption of
document (dhmS, COURT STAFF). (Entered: 10/09/2012)
10/09/2012

204

Declaration of Mark Bentley Pursuant to Civil Local Rule 79-5(d) in Support of 195
Administrative Motion to File Under Seal filed by Apple Inc.. (Related document(s) 195 )
(Brown, Christina) (Filed on 10/9/2012) Modified text on 10/10/2012 to conform with
caption of document (dhmS, COURT STAFF). (Entered: 10/09/2012)

10/10/2012

205

MOTION for leave to appear in Pro Hac Vice Chinue T. Richardson ( Filing fee $ 305,
receipt number 0971-7189136.) filed by Pixar. (Attachments: # 1 Certificate/Proof of Service
Certificate of Good Standing)(Richardson, Chinue) (Filed on 10/10/2012) (Entered:
10/10/2012)

10/11/2012

206

Order by Hon. Lucy H. Koh granting 205 Motion for Pro Hac Vice.(lhklc1, COURT STAFF)
(Filed on 10/11/2012) (Entered: 10/11/2012)

10/16/2012

207

MOTION for leave to appear in Pro Hac Vice Thomas A. Isaacson ( Filing fee $ 305, receipt
number 0971-7203150.) filed by Pixar. (Attachments: # 1 Certificate/Proof of Service
Certificate of Good Standing)(Isaacson, Thomas) (Filed on 10/16/2012) (Entered:
10/16/2012)

10/17/2012

208

Order by Hon. Lucy H. Koh granting (207) Motion for Pro Hac Vice in case 5:11-cv-02509LHK.Associated Cases: 5:11-cv-02509-LHK, 5:11-cv-03538-LHK, 5:11-cv-03539-LHK,
5:11-cv-03540-LHK, 5:11-cv-03541-LHK(lhklc3, COURT STAFF) (Filed on 10/17/2012)
(Entered: 10/17/2012)

11/12/2012

209

OPPOSITION to ( 187 MOTION for Class Certification ) filed by Apple Inc.. (Tubach,
Michael) (Filed on 11/12/2012) Modified text on 11/13/2012 (dhmS, COURT STAFF).
(Entered: 11/12/2012)

11/12/2012

210

MOTION to Strike the Report of Dr. Edward E. Leamer filed by Adobe Systems Inc., Apple
Inc., Google Inc., Intel Corp., Intuit Inc., Lucasfilm Ltd., Pixar. Motion Hearing set for
1/17/2013 01:30 PM in Courtroom 8, 4th Floor, San Jose before Hon. Lucy H. Koh.
Responses due by 11/26/2012. Replies due by 12/3/2012. (Attachments: # 1 Declaration of
Susan J. Welch, # 2 Exhibit)(Hinman, Frank) (Filed on 11/12/2012) (Entered: 11/12/2012)

11/12/2012

211

Administrative Motion to File Under Seal filed by Adobe Systems Inc.. (Kiernan, David)
(Filed on 11/12/2012) (Entered: 11/12/2012)

11/12/2012

212

*** FILED IN ERROR. DOCUMENT LOCKED. PLEASE SEE DOCKET # 230 . ***
Expert Report of Prefessor Kevin M. Murphy in Support of 209 Opposition/Response to
Motion for Class Certification filed by Adobe Systems Inc., Apple Inc., Google Inc., Intel
Corp., Intuit Inc., Lucasfilm Ltd., Pixar. (Related document(s) 209 ) (Hinman, Frank) (Filed
on 11/12/2012) Modified text on 11/14/2012 (dhmS, COURT STAFF). Modified on
11/14/2012 (wv, COURT STAFF). (Entered: 11/12/2012)

11/12/2012

213

MOTION for an Evidentiary Hearing on Class Certification Issues filed by Adobe Systems
Inc., Apple Inc., Google Inc., Intel Corp., Intuit Inc., Lucasfilm Ltd., Pixar. (Purcell, Daniel)
(Filed on 11/12/2012) Modified text on 11/14/2012 (dhmS, COURT STAFF). (Entered:
11/12/2012)

11/12/2012

214

Declaration of Catherine T. Zeng in Support of 211 joint Administrative Motion to File
Under Seal filed by Intuit Inc.. (Related document(s) 211 ) (Zeng, Catherine) (Filed on
11/12/2012) Modified text on 11/14/2012 (dhmS, COURT STAFF). (Entered: 11/12/2012)

11/12/2012

215

Declaration of Christina J. Brown in Support of 209 Opposition to Motion for Class
Certification filed by Apple Inc. PUBLIC REDACTED VERSION. (Attachments: # 1 Ex. 16, # 2 Ex. 7, # 3 Ex. 8-15, # 4 Ex. 16, # 5 Ex. 17, # 6 Ex. 18, # 7 Ex. 19-22, # 8 Ex. 23, # 9
Ex. 24, # 10 Ex. 25-27)(Related document(s) 209 ) (Brown, Christina) (Filed on 11/12/2012)
Modified text on 11/14/2012 (dhmS, COURT STAFF). (Entered: 11/12/2012)

1163

11/12/2012

216

Proposed Order re 213 ADMINISTRATIVE MOTION for an Evidentiary Hearing on Class
Certification Issues by Adobe Systems Inc., Apple Inc., Google Inc., Intel Corp., Intuit Inc.,
Lucasfilm Ltd., Pixar. (Purcell, Daniel) (Filed on 11/12/2012) Modified text on 11/14/2012
(dhmS, COURT STAFF). (Entered: 11/12/2012)

11/12/2012

217

Declaration of Lin W. Kahn in Support of 211 Administrative Motion to File Under Seal
filed byAdobe Systems Inc.. (Related document(s) 211 ) (Mittelstaedt, Robert) (Filed on
11/12/2012) (Entered: 11/12/2012)

11/12/2012

218

Declaration of James M. Kennedy in Support of 211 Administrative Motion to File Under
Seal filed byPixar. (Related document(s) 211 ) (Henn, Emily) (Filed on 11/12/2012)
(Entered: 11/12/2012)

11/12/2012

219

Declaration of Justina K. Sessions in Support of 211 Administrative Motion to File Under
Seal filed byLucasfilm Ltd.. (Related document(s) 211 ) (Sessions, Justina) (Filed on
11/12/2012) (Entered: 11/12/2012)

11/12/2012

220

Declaration of Frank Busch in Support of 211 Administrative Motion to File Under Seal filed
byIntel Corp.. (Related document(s) 211 ) (Busch, Frank) (Filed on 11/12/2012) (Entered:
11/12/2012)

11/12/2012

221

Declaration of Frank Wagner in Support of 211 Administrative Motion to File Under Seal
filed byGoogle Inc.. (Related document(s) 211 ) (Evans, Eric) (Filed on 11/12/2012)
(Entered: 11/12/2012)

11/12/2012

222

Declaration of Christina J. Brown in Support of 211 Administrative Motion to File Under
Seal filed byApple Inc.. (Related document(s) 211 ) (Brown, Christina) (Filed on
11/12/2012) (Entered: 11/12/2012)

11/12/2012

223

EXHIBITS re 211 Administrative Motion to File Under Seal filed byAdobe Systems Inc..
(Attachments: # 1 Exhibit A (Opp), # 2 Exhibit B, # 3 Exhibit C, # 4 Exhibit D, # 5 Exhibit
E)(Related document(s) 211 ) (Kiernan, David) (Filed on 11/12/2012) (Entered: 11/12/2012)

11/13/2012

224

Proposed Order re 211 Administrative Motion to File Under Seal by Adobe Systems Inc..
(Kiernan, David) (Filed on 11/13/2012) (Entered: 11/13/2012)

11/13/2012

225

Proposed Order re 210 MOTION to Strike the Report of Dr. Edward E. Leamer by Adobe
Systems Inc., Apple Inc., Google Inc., Intel Corp., Intuit Inc., Lucasfilm Ltd., Pixar. (Busch,
Frank) (Filed on 11/13/2012) (Entered: 11/13/2012)

11/13/2012

226

Transcript of Proceedings held on 06-04-12, before Judge Lucy H. Koh. Court
Reporter/Transcriber Lee-Anne Shortridge, Telephone number 408-287-4580. Per General
Order No. 59 and Judicial Conference policy, this transcript may be viewed only at the
Clerks Office public terminal or may be purchased through the Court Reporter/Transcriber
until the deadline for the Release of Transcript Restriction.After that date it may be obtained
through PACER. Any Notice of Intent to Request Redaction, if required, is due no later than
5 business days from date of this filing. Release of Transcript Restriction set for 2/11/2013.
(las, ) (Filed on 11/13/2012) (Entered: 11/13/2012)

11/13/2012

227

CERTIFICATE OF SERVICE by Intel Corp. re 212 Declaration in Support, 210 MOTION
to Strike the Report of Dr. Edward E. Leamer, 215 Declaration in Support, (Busch, Frank)
(Filed on 11/13/2012) (Entered: 11/13/2012)

11/13/2012

228

CERTIFICATE OF SERVICE by Apple Inc. re 209 Opposition/Response to Motion, 215
Declaration in Support, (Brown, Christina) (Filed on 11/13/2012) (Entered: 11/13/2012)

11/14/2012

229

Proposed Order re 224 Proposed Order Revised Proposed Order re 211 Administrative
Motion to File Under Seal by Adobe Systems Inc.. (Kiernan, David) (Filed on 11/14/2012)
(Entered: 11/14/2012)

11/14/2012

230

Expert Report of Professor Kevin M. Murphy in Support of 209 Opposition/Response to
1164

Motion CORRECTION OF DOCKET # 212 , filed byAdobe Systems Inc., Apple Inc., Google
Inc., Intel Corp., Intuit Inc., Lucasfilm Ltd., Pixar. (Related document(s) 209 ) (Hinman,
Frank) (Filed on 11/14/2012) Modified text on 11/19/2012 (dhmS, COURT STAFF).
(Entered: 11/14/2012)
11/15/2012

231

NOTICE of Appearance Google Inc. (Rubin, Lee) (Filed on 11/15/2012) (Entered:
11/15/2012)

11/15/2012

232

MOTION Administrative Motion for Order Compelling Defendants to Comply with Civil
Local Rules 7-3(a) and 3-4(c)(2) filed by Michael Devine, Mark Fichtner, Siddharth
Hariharan, Brandon Marshall, Daniel Stover. Responses due by 11/29/2012. Replies due by
12/6/2012. (Shaver, Anne) (Filed on 11/15/2012) (Entered: 11/15/2012)

11/15/2012

233

Declaration of Brendan P. Glackin in Support of 232 MOTION Administrative Motion for
Order Compelling Defendants to Comply with Civil Local Rules 7-3(a) and 3-4(c)(2) filed by
Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover.
(Attachments: # 1 Exhibit A , # 2 Exhibit B)(Related document(s) 232 ) (Shaver, Anne)
(Filed on 11/15/2012) Modified on 11/16/2012 (ewn, COURT STAFF). Modified on
11/16/2012 (ewn, COURT STAFF). Modified on 11/28/2012 PURSUANT TO ORDER
(DOC. #242) THE GLACKIN DECLARATION IS PERMANENTLY LOCKED
(dhmS, COURT STAFF). (Entered: 11/15/2012)

11/15/2012

234

Proposed Order re 232 MOTION Administrative Motion for Order Compelling Defendants
to Comply with Civil Local Rules 7-3(a) and 3-4(c)(2) by Michael Devine, Mark Fichtner,
Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Shaver, Anne) (Filed on
11/15/2012) (Entered: 11/15/2012)

11/16/2012

235

MOTION to Remove Incorrectly Filed Document filed by Michael Devine, Mark Fichtner,
Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Proposed Order)
(Glackin, Brendan) (Filed on 11/16/2012) (Entered: 11/16/2012)

11/16/2012

236

Amended Declaration of Brendan P. Glackin in Support of 232 MOTION Administrative
Motion for Order Compelling Defendants to Comply with Civil Local Rules 7-3(a) and 3-4
(c)(2) CORRECTION OF DOCKET # 233 . filed byMichael Devine, Mark Fichtner,
Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Exhibit A, # 2
Exhibit B)(Related document(s) 232 ) (Glackin, Brendan) (Filed on 11/16/2012) Modified
text on 11/19/2012 (dhmS, COURT STAFF). (Entered: 11/16/2012)

11/16/2012

237

OPPOSITION to ( 213 MOTION for an Evidentiary Hearing on Class Certification Issues )
filed byMichael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel
Stover. (Attachments: # 1 Proposed Order Denying Defendants' Administrative Motion)
(Glackin, Brendan) (Filed on 11/16/2012) Modified text on 11/19/2012 (dhmS, COURT
STAFF). (Entered: 11/16/2012)

11/19/2012

238

OPPOSITION to ( 232 MOTION Administrative Motion for Order Compelling Defendants
to Comply with Civil Local Rules 7-3(a) and 3-4(c)(2) ) filed by Adobe Systems Inc., Apple
Inc., Google Inc., Intel Corp., Intuit Inc., Lucasfilm Ltd., Pixar. (Attachments: # 1 Proposed
Order)(Hinman, Frank) (Filed on 11/19/2012) Modified text on 11/20/2012 (dhmS, COURT
STAFF). (Entered: 11/19/2012)

11/19/2012

239

Declaration of Frank M. Hinman in Support of 238 Opposition to Motion, filed by Adobe
Systems Inc., Apple Inc., Google Inc., Intel Corp., Intuit Inc., Lucasfilm Ltd., Pixar.
(Attachments: # 1 Exhibit A-E)(Related document(s) 238 ) (Hinman, Frank) (Filed on
11/19/2012) Modified text on 11/20/2012 (dhmS, COURT STAFF). (Entered: 11/19/2012)

11/19/2012

240

Declaration of JOSEPH P. FORDERER in Support of 211 Administrative Motion to File
Under Seal AS TO INFORMATION DESIGNATED CONFIDENTIAL BY PLAINTIFFS filed
byMichael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover.
(Related document(s) 211 ) (Forderer, Joseph) (Filed on 11/19/2012) (Entered: 11/19/2012)

1165

11/19/2012

241

Proposed Order re 240 Declaration in Support, 211 Administrative Motion to File Under Seal
AS TO INFORMATION DESIGNATED CONFIDENTIAL BY PLAINTIFFS by Michael
Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover.
(Attachments: # 1 Exhibit A (Opposition to Plaintiffs Motion for Class Certification:
Plaintiffs Proposed Redactions), # 2 Exhibit B (Exhibits to the Declaration of Christina
Brown: Plaintiffs Proposed Redactions), # 3 Exhibit C (Exhibits to the Declaration of Susan
J. Welch: Plaintiffs Proposed Redactions))(Forderer, Joseph) (Filed on 11/19/2012) (Entered:
11/19/2012)

11/21/2012

242

ORDER by Judge Lucy H. Koh denying (213) Motion for Hearing; granting in part and
denying in part (232) Motion ; granting (235) Motion to Remove Incorrectly Filed Document
in case 5:11-cv-02509-LHK (lhklc1, COURT STAFF) (Filed on 11/21/2012) (Entered:
11/21/2012)

11/21/2012

243

Order by Hon. Lucy H. Koh granting 194 Motion to Withdraw as Attorney. Attorney
Jonathan A D Herczeg terminated.(lhklc1, COURT STAFF) (Filed on 11/21/2012) (Entered:
11/21/2012)

11/26/2012

244

Order by Hon. Lucy H. Koh granting 113 Motion to Withdraw as Attorney Katerine M Lehe.
(lhklc1, COURT STAFF) (Filed on 11/26/2012) (Entered: 11/26/2012)

12/05/2012

245

JOINT CASE MANAGEMENT STATEMENT filed by Adobe Systems Inc., Apple Inc.,
Michael Devine, Mark Fichtner, Google Inc., Siddharth Hariharan, Intel Corp., Intuit Inc.,
Lucasfilm Ltd., Brandon Marshall, Palm Inc., Pixar, Daniel Stover. (Shaver, Anne) (Filed on
12/5/2012) (Entered: 12/05/2012)

12/10/2012

246

Administrative Motion to File Under Seal filed by Michael Devine, Mark Fichtner, Siddharth
Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Declaration of Anne Shaver,
# 2 Proposed Order, # 3 Exhibit Redacted Reply Class Certification, # 4 Exhibit Redacted
Reply Report Edward Leamer, # 5 Exhibit Exhibits Under Seal)(Shaver, Anne) (Filed on
12/10/2012) (Entered: 12/10/2012)

12/10/2012

247

REPLY (re 187 MOTION to Certify Class and Memorandum of Points and Authorities, 210
MOTION to Strike the Report of Dr. Edward E. Leamer ) filed byMichael Devine, Mark
Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Shaver, Anne) (Filed on
12/10/2012) (Entered: 12/10/2012)

12/10/2012

248

Declaration of Dean M. Harvey in Support of 247 Reply to Opposition/Response, filed
byMichael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover.
(Attachments: # 1 Exhibit Exhibits Filed Under Seal, # 2 Exhibit 7, # 3 Exhibit 8, # 4 Exhibit
9, # 5 Exhibit 10, # 6 Exhibit 11, # 7 Exhibit 31, # 8 Exhibit 32, # 9 Exhibit 33, # 10 Exhibit
34)(Related document(s) 247 ) (Shaver, Anne) (Filed on 12/10/2012) (Entered: 12/10/2012)

12/10/2012

249

Declaration of Edward E. Leamer in Support of 247 Reply to Opposition/Response, filed
byMichael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover.
(Related document(s) 247 ) (Shaver, Anne) (Filed on 12/10/2012) (Entered: 12/10/2012)

12/10/2012

250

CERTIFICATE OF SERVICE by Michael Devine, Mark Fichtner, Siddharth Hariharan,
Brandon Marshall, Daniel Stover re 247 Reply to Opposition/Response, (Shaver, Anne)
(Filed on 12/10/2012) (Entered: 12/10/2012)

12/11/2012

251

CLERKS NOTICE CONTINUING FURTHER CASE MANAGEMENT CONFERENCE
TO DATE OF MOTION HEARING Further Case Management Conference set for
1/17/2013 01:30 PM in Courtroom 8, 4th Floor, San Jose. ****THIS IS A TEXT-ONLY
ENTRY. THERE IS NO DOCUMENT ASSOCIATED WITH THIS DOCKET ENTRY****
(mpb, COURT STAFF) (Filed on 12/11/2012) (Entered: 12/11/2012)

12/12/2012

252

Administrative Motion to File Under Seal LETTER RE CORRECTION TO
CONSOLIDATED REPLY IN SUPPORT OF MOTION FOR CLASS CERTIFICATION AND
IN OPPOSITION TO DEFENDANTS MOTION TO STRIKE THE REPORT OF DR.
1166

EDWARD E. LEAMER, AND REPLY EXPERT REPORT OF EDWARD E. LEAMER, PH.D.
filed by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel
Stover. (Attachments: # 1 Proposed Order, # 2 Exhibit Redacted Letter)(Harvey, Dean)
(Filed on 12/12/2012) (Entered: 12/12/2012)
12/12/2012

253

Letter from Brendan P. Glackin RE CORRECTION TO CONSOLIDATED REPLY IN
SUPPORT OF MOTION FOR CLASS CERTIFICATION AND IN OPPOSITION TO
DEFENDANTS MOTION TO STRIKE THE REPORT OF DR. EDWARD E. LEAMER, AND
REPLY EXPERT REPORT OF EDWARD E. LEAMER, PH.D.. (Harvey, Dean) (Filed on
12/12/2012) (Entered: 12/12/2012)

12/17/2012

254

Joint Administrative Motion to File Under Seal filed by Google Inc.. (Attachments: # 1
Appendix Appendix A, # 2 Exhibit Exhibits A-C, # 3 Proposed Order)(Evans, Eric) (Filed on
12/17/2012) (Entered: 12/17/2012)

12/17/2012

255

Declaration of Susan J. Welch in Support of 254 Joint Administrative Motion to File Under
Seal filed byIntel Corp.. (Related document(s) 254 ) (Welch, Susan) (Filed on 12/17/2012)
(Entered: 12/17/2012)

12/17/2012

256

Declaration of Catherine T. Zeng in Support of 254 Joint Administrative Motion to File
Under Seal filed byIntuit Inc.. (Related document(s) 254 ) (Zeng, Catherine) (Filed on
12/17/2012) (Entered: 12/17/2012)

12/17/2012

257

Declaration of Lin W. Kahn in Support of 254 Joint Administrative Motion to File Under
Seal filed byAdobe Systems Inc.. (Related document(s) 254 ) (Wang, Lin) (Filed on
12/17/2012) (Entered: 12/17/2012)

12/17/2012

258

Declaration of Christina Brown in Support of 254 Joint Administrative Motion to File Under
Seal filed byApple Inc.. (Related document(s) 254 ) (Brown, Christina) (Filed on
12/17/2012) (Entered: 12/17/2012)

12/17/2012

259

Declaration of James M. Kennedy in Support of 254 Joint Administrative Motion to File
Under Seal filed byPixar. (Related document(s) 254 ) (Richardson, Chinue) (Filed on
12/17/2012) (Entered: 12/17/2012)

12/18/2012

260

Declaration of Justina K. Sessions in Support of 254 Joint Administrative Motion to File
Under Seal filed byLucasfilm Ltd.. (Related document(s) 254 ) (Sessions, Justina) (Filed on
12/18/2012) (Entered: 12/18/2012)

12/18/2012

261

Declaration of Frank Wagner in Support of 254 Joint Administrative Motion to File Under
Seal filed byGoogle Inc.. (Related document(s) 254 ) (Selin, Anne) (Filed on 12/18/2012)
(Entered: 12/18/2012)

01/09/2013

262

NOTICE of Change of Address by James Gerard Beebe Dallal for Joseph Saveri Law Firm
(Dallal, James) (Filed on 1/9/2013) (Entered: 01/09/2013)

01/09/2013

263

JOINT ADMINISTRATIVE MOTION for Leave to Supplement the Record in Support of
Defendants' Opposition to Plaintiffs' Motion for Class Certification; Declaration of Eric B.
Evans; Supplemental Declaration of Kevin Murphy; Proposed Order filed by Google Inc..
(Attachments: # 1 Declaration of Eric B. Evans, # 2 Exhibit A to Evans Decl., # 3
Declaration of Kevin Murphy, # 4 Proposed Order)(Evans, Eric) (Filed on 1/9/2013)
Modified text on 1/10/2013 (dhmS, COURT STAFF). (Entered: 01/09/2013)

01/09/2013

264

Administrative Motion to File Under Seal filed by Google Inc.. (Attachments: # 1 Exhibit A
to Administrative Motion to Seal, # 2 Exhibit B to Administrative Motion to Seal, # 3 Exhibit
C to Administrative Motion to Seal, # 4 Declaration of Anne Selin, # 5 Proposed Order)
(Evans, Eric) (Filed on 1/9/2013) (Entered: 01/09/2013)

01/09/2013

265

Declaration of Frank Busch in Support of 264 Administrative Motion to File Under Seal filed
byIntel Corp.. (Related document(s) 264 ) (Busch, Frank) (Filed on 1/9/2013) (Entered:
1167
01/09/2013)

01/09/2013

266

Declaration of Christina Brown in Support of 264 Administrative Motion to File Under Seal
filed byApple Inc.. (Related document(s) 264 ) (Brown, Christina) (Filed on 1/9/2013)
(Entered: 01/09/2013)

01/10/2013

267

NOTICE of Appearance by Lisa Janine Cisneros (Cisneros, Lisa) (Filed on 1/10/2013)
(Entered: 01/10/2013)

01/10/2013

268

JOINT CASE MANAGEMENT STATEMENT filed by Adobe Systems Inc., Apple Inc.,
Michael Devine, Mark Fichtner, Google Inc., Siddharth Hariharan, Intel Corp., Intuit Inc.,
Lucasfilm Ltd., Brandon Marshall, Pixar, Daniel Stover. (Harvey, Dean) (Filed on
1/10/2013) (Entered: 01/10/2013)

01/11/2013

269

ORDER Re: Motions to Seal. Signed by Judge Lucy H. Koh on 1/11/2013. (lhklc3, COURT
STAFF) (Filed on 1/11/2013) (Entered: 01/11/2013)

01/14/2013

270

OPPOSITION to ( 263 JOINT ADMINISTRATIVE MOTION for Leave to Supplement the
Record in Support of Defendants' Opposition to Plaintiffs' Motion for Class Certification )
and ( 210 MOTION to Strike the Report of Dr. Edward E. Leamer ) [REDACTED] filed by
Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover.
(Attachments: # 1 Declaration of Dr. Edward E. Leamer in Opposition to Defendants'
Administrative Motion)(Harvey, Dean) (Filed on 1/14/2013) Modified text on 1/16/2013
(dhmS, COURT STAFF). (Entered: 01/14/2013)

01/14/2013

271

Administrative Motion to File Under Seal filed by Michael Devine, Mark Fichtner, Siddharth
Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Exhibit A [Plaintiffs'
Opposition to Defendants' Administrative Motion - Redacted], # 2 Exhibit B [Declaration of
Dr. Edward E. Leamer in Opposition to Defendants' Administrative Motion - Redacted], # 3
Exhibit C [Plaintiffs' Opposition to Defendants' Administrative Motion - Redactions
Highlighted], # 4 Exhibit D [Declaration of Dr. Edward E. Leamer in Opposition to
Defendants' Administrative Motion - Redactions Highlighted])(Harvey, Dean) (Filed on
1/14/2013) (Entered: 01/14/2013)

01/15/2013

272

NOTICE by Intuit Inc. of Request to Bring Electronic Equipment into the Courtroom
(Attachments: # 1 Proposed Order)(Zeng, Catherine) (Filed on 1/15/2013) Modified on
1/16/2013 COUNSEL POSTED DOCUMENT INCORRECTLY AS A NOTICE (dhmS,
COURT STAFF). (Entered: 01/15/2013)

01/15/2013

273

ORDER by Judge Lucy H. Koh granting in part and denying in part (186) Administrative
Motion to File Under Seal Documents Related to Plaintiffs' Motion for Class Certification;
granting in part and denying in part (211) Administrative Motion to File Under Seal
Documents Related to Defendants' Opposition to Class Certification; granting in part and
denying in part (246) Administrative Motion to File Under Seal Documents Related to
Plaintiffs' Consolidated Reply in Support of its Motion for Class Certification and Opposition
to Defendants' Motion to Strike; granting (252) Administrative Motion to File Under Seal
Portion of Glackin Letter; granting in part and denying in part (254) Defendants' Joint
Administrative Motion to File Under Seal in case 5:11-cv-02509-LHK (lhklc3, COURT
STAFF) (Filed on 1/15/2013) (Entered: 01/15/2013)

01/16/2013

274

ERRATA re 215 Declaration in Support, by Apple Inc.. (Brown, Christina) (Filed on
1/16/2013) (Entered: 01/16/2013)

01/16/2013

275

CLERKS NOTICE re Deficiency (dhmS, COURT STAFF) (Filed on 1/16/2013) (Entered:
01/16/2013)

01/16/2013

276

ERRATA re 222 Declaration in Support, 221 Declaration in Support of Joint Administrative
Motion to Seal dated Nov. 12, 2012 by Google Inc.. (Selin, Anne) (Filed on 1/16/2013)
(Entered: 01/16/2013)

01/16/2013

277

ORDER TO BRING EQUIPMENT INTO COURTROOM re 272 Notice (Other), filed by
Intuit Inc.. Signed by Judge Lucy H. Koh on 1/16/13. (mpb, COURT STAFF) (Filed on
1168

1/16/2013) (Entered: 01/16/2013)
01/16/2013

278

MOTION to Compel Google Documents [REDACTED] filed by Michael Devine, Mark
Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. Motion Hearing set for
2/26/2013 10:00 AM in Courtroom 5, 4th Floor, San Jose before Magistrate Judge Paul
Singh Grewal. Responses due by 1/30/2013. Replies due by 2/6/2013. (Attachments: # 1
Declaration of Dean M. Harvey in Support of Plaintiffs Motion to Compel and Plaintiffs
Motion to Shorten Time, Exhibits A-O [REDACTED], # 2 Proposed Order Granting
Plaintiffs' Motion to Compel Google Documents)(Harvey, Dean) (Filed on 1/16/2013)
(Entered: 01/16/2013)

01/16/2013

279

Administrative Motion to File Under Seal , Pursuant to Civil Local Rule 79-5(d), Portions of
Plaintiffs' Motion to Compel Google Documents and the Declaration of Dean M. Harvey in
Support Thereof filed by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon
Marshall, Daniel Stover. (Attachments: # 1 Exhibit A: Plaintiffs' Motion to Compel Google
Documents [Redacted], # 2 Exhibit B: Declaration of Dean M. Harvey in Support Thereof
with Exhibits A-O [Redacted], # 3 Exhibit C: Highlighted Version of Plaintiffs' Motion To
Compel Google Documents, # 4 Exhibit D: Declaration of Dean M. Harvey in Support
Thereof)(Harvey, Dean) (Filed on 1/16/2013) (Entered: 01/16/2013)

01/16/2013

280

MOTION to Shorten Time on Plaintiffs' Motion to Compel filed by Michael Devine, Mark
Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Proposed
Order Granting Plaintiffs' Motion to Shorten Time on Plaintiffs' Motion to Compel)(Harvey,
Dean) (Filed on 1/16/2013) (Entered: 01/16/2013)

01/17/2013

281

Minute Entry: Motion Hearing held on 1/17/2013 before Judge Lucy H. Koh (Date Filed:
1/17/2013) re 187 MOTION to Certify Class and Memorandum of Points and Authorities
filed by Michael Devine, Siddharth Hariharan, Mark Fichtner, Daniel Stover, Brandon
Marshall. (Court Reporter Lee-Anne Shortridge.) (mpb, COURT STAFF) (Date Filed:
1/17/2013) (Entered: 01/22/2013)

01/17/2013

282

Minute Entry and Case Management Order: Further Case Management Conference held on
1/17/2013 before Judge Lucy H. Koh (Date Filed: 1/17/2013). Further Case Management
Conference set for 3/13/2013 02:00 PM in Courtroom 8, 4th Floor, San Jose. (Court Reporter
Lee-Anne Shortridge.) (mpb, COURT STAFF) (Date Filed: 1/17/2013) (Entered:
01/22/2013)

01/22/2013

283

Administrative Motion to File Under Seal filed by Adobe Systems Inc.. (Attachments: # 1
Exhibit, # 2 Exhibit A, # 3 Exhibit B, # 4 Exhibit C, # 5 Exhibit D, # 6 Exhibit E, # 7 Exhibit
F, # 8 Exhibit G, # 9 Proposed Order Granting Renewed Administrative Motion to File
Under Seal)(Kiernan, David) (Filed on 1/22/2013) (Entered: 01/22/2013)

01/22/2013

284

Declaration of Donna Morris in Support of 283 Administrative Motion to File Under Seal
filed byAdobe Systems Inc.. (Related document(s) 283 ) (Kiernan, David) (Filed on
1/22/2013) (Entered: 01/22/2013)

01/22/2013

285

Declaration of Lisa K. Borgeson in Support of 283 Administrative Motion to File Under Seal
filed byIntuit Inc.. (Related document(s) 283 ) (Kiernan, David) (Filed on 1/22/2013)
(Entered: 01/22/2013)

01/22/2013

286

Letter from Eric Evans to Honorable Paul S. Grewal. (Evans, Eric) (Filed on 1/22/2013)
(Entered: 01/22/2013)

01/22/2013

287

Declaration of Tina M. Evangelista in Support of 283 Administrative Motion to File Under
Seal filed byIntel Corp.. (Related document(s) 283 ) (Busch, Frank) (Filed on 1/22/2013)
(Entered: 01/22/2013)

01/22/2013

288

Declaration of Frank Wagner in Support of 283 Administrative Motion to File Under Seal
filed byGoogle Inc.. (Related document(s) 283 ) (Selin, Anne) (Filed on 1/22/2013) (Entered:
01/22/2013)
1169

01/22/2013

289

NOTICE of Compliance with 273 Court's January 15, 2013 Order re Motions to Seal by
Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover
(Harvey, Dean) (Filed on 1/22/2013) Modified text on 1/23/2013 (dhmS, COURT STAFF).
(Entered: 01/22/2013)

01/22/2013

290

REDACTION to PLAINTIFFS' NOTICE OF MOTION AND MOTION FOR CLASS
CERTIFICATION, AND MEMORANDUM OF LAW IN SUPPORT in compliance with the
Court's January 15, 2013 Order 273 by Daniel Stover, Siddharth Hariharan, Michael Devine,
Mark Fichtner, Brandon Marshall. (Harvey, Dean) (Filed on 1/22/2013) (Entered:
01/22/2013)

01/22/2013

291

REDACTION to DECLARATION OF ANNE B. SHAVER IN SUPPORT OF PLAINTIFFS'
MOTION FOR CLASS CERTIFICATION in compliance with the Court's January 15, 2013
Order 273 by Daniel Stover, Siddharth Hariharan, Michael Devine, Mark Fichtner, Brandon
Marshall. (Attachments: # 1 Exhibit 1, # 2 Exhibit 2, # 3 Exhibit 3, # 4 Exhibit 4 (redacted),
# 5 Exhibit 5, # 6 Exhibit 6, # 7 Exhibit 7, # 8 Exhibit 8, # 9 Exhibit 9, # 10 Exhibit 10, # 11
Exhibit 11, # 12 Exhibit 12, # 13 Exhibit 13, # 14 Exhibit 14 (redacted), # 15 Exhibit 16, #
16 Exhibit 17, # 17 Exhibit 18, # 18 Exhibit 19, # 19 Exhibit 20, # 20 Exhibit 21 (redacted),
# 21 Exhibit 22, # 22 Exhibit 23, # 23 Exhibit 24 (redacted), # 24 Exhibit 25 (redacted), # 25
Exhibit 26, # 26 Exhibit 27, # 27 Exhibit 28, # 28 Exhibit 29 (redacted), # 29 Exhibit 30, #
30 Exhibit 31, # 31 Exhibit 32 (redacted), # 32 Exhibit 33, # 33 Exhibit 34 (redacted), # 34
Exhibit 35, # 35 Exhibit 36, # 36 Exhibit 37 (redacted), # 37 Exhibit 38, # 38 Exhibit 39
(redacted), # 39 Exhibit 40 (redacted), # 40 Exhibit 41, # 41 Exhibit 42 (redacted), # 42
Exhibit 50, # 43 Exhibit 51, # 44 Exhibit 52, # 45 Exhibit 53, # 46 Exhibit 55, # 47 Exhibit
56, # 48 Exhibit 57, # 49 Exhibit 58, # 50 Exhibit 60, # 51 Exhibit 61, # 52 Exhibit 62
(redacted), # 53 Exhibit 63 (redacted), # 54 Exhibit 64, # 55 Exhibit 65, # 56 Exhibit 66, # 57
Exhibit 67 (redacted), # 58 Exhibit 68 (redacted), # 59 Exhibit 69, # 60 Exhibit 70, # 61
Exhibit 71)(Harvey, Dean) (Filed on 1/22/2013) (Entered: 01/22/2013)

01/22/2013

292

Joint Administrative Motion to File Under Seal Defendants Joint Response in Support of
Plaintiffs Administrative Motion to Seal filed by Adobe Systems Inc., Apple Inc., Google
Inc., Intel Corp., Intuit Inc., Lucasfilm Ltd., Pixar. (Attachments: # 1 Proposed Order, # 2
Exhibit Opposition [REDACTED], # 3 Exhibit Declaration [REDACTED], # 4 Opposition
[highlighted], # 5 Declaration [highlighted])(Busch, Frank) (Filed on 1/22/2013) (Entered:
01/22/2013)

01/22/2013

293

AFFIDAVIT OF EDWARD T. COLLIGAN AND EXHIBITS A AND B in compliance with the
Court's January 15, 2013 Order 273 by Michael Devine, Mark Fichtner, Siddharth
Hariharan, Brandon Marshall, Daniel Stover. (Harvey, Dean) (Filed on 1/22/2013) (Entered:
01/22/2013)

01/22/2013

294

Declaration of Frank Busch in Support of 292 Joint Administrative Motion to File Under
Seal Defendants Joint Response in Support of Plaintiffs Administrative Motion to Seal filed
byIntel Corp.. (Related document(s) 292 ) (Busch, Frank) (Filed on 1/22/2013) (Entered:
01/22/2013)

01/22/2013

295

Declaration of Catherine T. Zeng in Support of 292 Joint Administrative Motion to File
Under Seal Defendants Joint Response in Support of Plaintiffs Administrative Motion to Seal
filed byIntuit Inc.. (Related document(s) 292 ) (Zeng, Catherine) (Filed on 1/22/2013)
(Entered: 01/22/2013)

01/22/2013

296

DOCUMENT E-FILED UNDER SEAL re 273 Order on Administrative Motion to File
Under Seal,,,,,,,,,,,,,,,,,,, PLAINTIFFS' NOTICE OF MOTION AND MOTION FOR CLASS
CERTIFICATION, AND MEMORANDUM OF LAW IN SUPPORT by Michael Devine, Mark
Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1
Declaration of Anne B. Shaver in Support of Plaintiffs' Motion for Class Certification, # 2
Exhibit 4, # 3 Exhibit 14, # 4 Exhibit 15, # 5 Exhibit 21, # 6 Exhibit 24, # 7 Exhibit 25, # 8
Exhibit 29, # 9 Exhibit 32, # 10 Exhibit 34, # 11 Exhibit 37, # 12 Exhibit 39, # 13 Exhibit 40,
# 14 Exhibit 42, # 15 Exhibit 43, # 16 Exhibit 44, # 17 Exhibit 45, # 18 Exhibit 46, # 19
1170

Exhibit 47, # 20 Exhibit 48, # 21 Exhibit 49, # 22 Exhibit 54, # 23 Exhibit 59, # 24 Exhibit
62, # 25 Exhibit 63, # 26 Exhibit 67, # 27 Exhibit 68)(Harvey, Dean) (Filed on 1/22/2013)
(Entered: 01/22/2013)
01/22/2013

297

REDACTION to PLAINTIFFS' CONSOLIDATED REPLY IN SUPPORT OF MOTION FOR
CLASS CERTIFICATION AND IN OPPOSITION TO MOTION TO STRIKE in compliance
with the Court's January 15, 2013 Order 273 by Daniel Stover, Siddharth Hariharan,
Michael Devine, Mark Fichtner, Brandon Marshall. (Attachments: # 1 Declaration of Dean
M. Harvey, # 2 Exhibit 1 (redacted), # 3 Exhibit 2 (redacted), # 4 Exhibit 3, # 5 Exhibit 4
(redacted), # 6 Exhibit 5, # 7 Exhibit 6, # 8 Exhibit 7, # 9 Exhibit 8, # 10 Exhibit 9, # 11
Exhibit 10 (redacted), # 12 Exhibit 11, # 13 Exhibit 12, # 14 Exhibit 13 (redacted), # 15
Exhibit 14, # 16 Exhibit 21, # 17 Exhibit 26 (redacted), # 18 Exhibit 27 (redacted), # 19
Exhibit 28, # 20 Exhibit 29 (redacted), # 21 Exhibit 31, # 22 Exhibit 32, # 23 Exhibit 33, #
24 Exhibit 34)(Harvey, Dean) (Filed on 1/22/2013) (Entered: 01/22/2013)

01/22/2013

298

DOCUMENT E-FILED UNDER SEAL re 273 Order on Administrative Motion to File
Under Seal,,,,,,,,,,,,,,,,,,, PLAINTIFFS' CONSOLIDATED REPLY IN SUPPORT OF MOTION
FOR CLASS CERTIFICATION AND IN OPPOSITION TO MOTION TO STRIKE in
compliance with the Court's January 15, 2013 Order by Michael Devine, Mark Fichtner,
Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Declaration of
Dean M. Harvey, # 2 Exhibit 1, # 3 Exhibit 2, # 4 Exhibit 4, # 5 Exhibit 10, # 6 Exhibit 13, #
7 Exhibit 15, # 8 Exhibit 16, # 9 Exhibit 17, # 10 Exhibit 18, # 11 Exhibit 19, # 12 Exhibit
20, # 13 Exhibit 22, # 14 Exhibit 23, # 15 Exhibit 24, # 16 Exhibit 25, # 17 Exhibit 26, # 18
Exhibit 27, # 19 Exhibit 29, # 20 Exhibit 30)(Harvey, Dean) (Filed on 1/22/2013) (Entered:
01/22/2013)

01/22/2013

299

DOCUMENT E-FILED UNDER SEAL re 273 Order on Administrative Motion to File
Under Seal,,,,,,,,,,,,,,,,,,, Letter from Brendan P. Glackin RE CORRECTION TO
CONSOLIDATED REPLY IN SUPPORT OF MOTION FOR CLASS CERTIFICATION AND
IN OPPOSITION TO MOTION TO STRIKE, AND REPLY EXPERT REPORT OF EDWARD
E. LEAMER, PH.D. by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon
Marshall, Daniel Stover. (Harvey, Dean) (Filed on 1/22/2013) (Entered: 01/22/2013)

01/22/2013

300

Declaration of Christina Brown in Support of 292 Joint Administrative Motion to File Under
Seal Defendants Joint Response in Support of Plaintiffs Administrative Motion to Seal filed
byApple Inc.. (Related document(s) 292 ) (Brown, Christina) (Filed on 1/22/2013) (Entered:
01/22/2013)

01/22/2013

301

REDACTION to 210 MOTION to Strike the Report of Dr. Edward E. Leamer in compliance
with the Court's January 15, 2013 Order 273 by Intel Corp., Apple Inc., Intuit Inc., Adobe
Systems Inc., Pixar, Google Inc., Lucasfilm Ltd.. (Attachments: # 1 Exhibit to Welch
Declaration in Support)(Busch, Frank) (Filed on 1/22/2013) (Entered: 01/22/2013)

01/22/2013

302

DOCUMENT E-FILED UNDER SEAL re 273 Order on Administrative Motion to File
Under Seal,,,,,,,,,,,,,,,,,,, Motion to Strike the Report of Dr. Edward E. Leamer 210 by Adobe
Systems Inc., Apple Inc., Google Inc., Intel Corp., Intuit Inc., Lucasfilm Ltd., Pixar.
(Attachments: # 1 Declaration of Susan J. Welch, # 2 Exhibit to Welch Declaration)(Busch,
Frank) (Filed on 1/22/2013) (Entered: 01/22/2013)

01/22/2013

303

Declaration of Justina K. Sessions in Support of Defendants' Renewed Administrative Motion
to Seal filed byLucasfilm Ltd.. (Sessions, Justina) (Filed on 1/22/2013) (Entered:
01/22/2013)

01/22/2013

304

REDACTION OPPOSITION TO PLAINTIFFS MOTION FOR CLASS CERTIFICATION by
Intel Corp., Apple Inc., Intuit Inc., Adobe Systems Inc., Pixar, Google Inc., Lucasfilm Ltd..
(Brown, Christina) (Filed on 1/22/2013) (Entered: 01/22/2013)

01/22/2013

305

Declaration of Anne M. Selin in Support of Defendants' Renewed Motion to Seal filed
byGoogle Inc.. (Selin, Anne) (Filed on 1/22/2013) (Entered: 01/22/2013)

1171

01/23/2013

306

Declaration of Christina J. Brown in Support of 307 Renewed Administrative Motion to Seal
filed by Apple Inc.. (Brown, Christina) (Filed on 1/23/2013) Modified on 1/28/2013 linking
entry to document #307 (dhmS, COURT STAFF). (Entered: 01/23/2013)

01/23/2013

307

Renewed Administrative Motion to File Under Seal filed by Apple Inc.. (Attachments: # 1
Proposed Order)(Brown, Christina) (Filed on 1/23/2013) Modified text on 1/28/2013 (dhmS,
COURT STAFF). (Entered: 01/23/2013)

01/23/2013

308

REDACTION to 304 Redacted Document by Intel Corp., Apple Inc., Intuit Inc., Adobe
Systems Inc., Pixar, Google Inc., Lucasfilm Ltd.. (Attachments: # 1 Exhibit 1, # 2 Exhibit 2,
# 3 Exhibit 3, # 4 Exhibit 4, # 5 Exhibit 5, # 6 Exhibit 6, # 7 Exhibit 7, # 8 Exhibit 8, # 9
Exhibit 9, # 10 Exhibit 10, # 11 Exhibit 11, # 12 Exhibit 12, # 13 Exhibit 13, # 14 Exhibit
14a, # 15 Exhibit 14b, # 16 Exhibit 14c, # 17 Exhibit 14d, # 18 Exhibit 14e, # 19 Exhibit 14f,
# 20 Proposed Order 15, # 21 Exhibit 16, # 22 Exhibit 17, # 23 Exhibit 18, # 24 Exhibit 19, #
25 Exhibit 20, # 26 Exhibit 21, # 27 Exhibit 22a,*** PURSUANT TO ORDER 317 ,
DOCUMENT REMOVED. DOCUMENT TO BE REFILED LATER. ***
# 28 Exhibit 22b, # 29 Exhibit 22c, # 30 Exhibit 23, # 31 Exhibit 24, # 32 Exhibit 25, # 33
Exhibit 26, # 34 Exhibit 27)(Brown, Christina) (Filed on 1/23/2013) Modified on 1/23/2013
(fff, COURT STAFF). (Attachment 27 replaced on 1/31/2013) (sp, COURT STAFF).
Modified on 1/31/2013 (sp, COURT STAFF). (Entered: 01/23/2013)

01/23/2013

309

EXHIBITS re 307 Administrative Motion to File Under Seal filed byAdobe Systems Inc.,
Apple Inc., Google Inc., Intel Corp., Intuit Inc., Lucasfilm Ltd., Pixar. (Attachments: # 1
Exhibit A-1b, # 2 Exhibit A-1c, # 3 Exhibit A-1d, # 4 Exhibit A-1e, # 5 Exhibit A-1f, # 6
Exhibit B-1, # 7 Exhibit C-1, # 8 Exhibit D-1, # 9 Exhibit E-1, # 10 Exhibit F-1, # 11 Exhibit
G-1a,*** PURSUANT TO ORDER 317 , DOCUMENT REMOVED. DOCUMENT TO
BE REFILED LATER. ***
# 12 Exhibit G-1b, # 13 Exhibit G-1c, # 14 Exhibit H-1, # 15 Exhibit I-1, # 16 Exhibit J-1, #
17 Exhibit K-1)(Related document(s) 307 ) (Brown, Christina) (Filed on 1/23/2013)
Modified on 1/23/2013 (fff, COURT STAFF). (Attachment 11 replaced on 1/31/2013) (sp,
COURT STAFF). Modified on 1/31/2013 (sp, COURT STAFF). (Entered: 01/23/2013)

01/23/2013

310

MOTION to Remove Incorrectly Filed Document filed by Lucasfilm Ltd.. (Sessions, Justina)
(Filed on 1/23/2013) (Entered: 01/23/2013)

01/23/2013

311

Proposed Order re 310 MOTION to Remove Incorrectly Filed Document by Lucasfilm Ltd..
(Sessions, Justina) (Filed on 1/23/2013) (Entered: 01/23/2013)

01/23/2013

312

EXHIBITS re 308 Redacted Document,,,, Exhibit 22a to Declaration of Christina Brown
filed byLucasfilm Ltd.. (Related document(s) 308 ) (Sessions, Justina) (Filed on 1/23/2013)
(Entered: 01/23/2013)

01/23/2013

313

Administrative Motion to File Under Seal Google's Response In Support of Plaintiffs'
Administrative Motion to Seal Portions of Plaintiffs' Motion to Compel Google Documents
and the Declaration of Dean M. Harvey In Support Thereof filed by Google Inc..
(Attachments: # 1 Exhibit Exhibit 1, # 2 Exhibit Exhibit 2, # 3 Exhibit Exhibit 3, # 4
Proposed Order, # 5 Declaration Declaration of Anne M. Selin, # 6 Exhibit, # 7 Exhibit, # 8
Exhibit)(Selin, Anne) (Filed on 1/23/2013) (Entered: 01/23/2013)

01/23/2013

314

EXHIBITS G1-a to 307 Defendant's Renewed Administrative Motion filed by Lucasfilm
Ltd.. (Sessions, Justina) (Filed on 1/23/2013) Modified on 1/28/2013 linking entry to
document #307 (dhmS, COURT STAFF). (Entered: 01/23/2013)

01/23/2013

315

ORDER DENYING MOTION TO SHORTEN TIME by Judge Paul S. Grewal, denying 280
Motion to Shorten Time. (ofr, COURT STAFF) (Filed on 1/23/2013) (Entered: 01/24/2013)

01/24/2013

316

STATUS REPORT by Apple Inc., Michael Devine, Mark Fichtner, Siddharth Hariharan,
Brandon Marshall, Daniel Stover. (Tubach, Michael) (Filed on 1/24/2013) (Entered:
01/24/2013)

1172

01/25/2013

317

Order by Hon. Lucy H. Koh granting (310) Motion to Remove Incorrectly Filed Document in
case 5:11-cv-02509-LHK.Associated Cases: 5:11-cv-02509-LHK, 5:11-cv-03538-LHK,
5:11-cv-03539-LHK, 5:11-cv-03540-LHK, 5:11-cv-03541-LHK, 5:12-cv-01262-LHK
(lhklc1, COURT STAFF) (Filed on 1/25/2013) (Entered: 01/25/2013)

01/25/2013

318

OPPOSITION to ( 278 MOTION to Compel Google Documents [REDACTED] ) filed
byGoogle Inc.. (Attachments: # 1 Declaration of Lee H. Rubin, # 2 Declaration of Alan
Eustace)(Evans, Eric) (Filed on 1/25/2013) Modified text on 1/28/2013 (dhmS, COURT
STAFF). (Entered: 01/25/2013)

01/25/2013

319

Administrative Motion to File Under Seal re Google's Opposition to Plaintiffs' Motion to
Compel and Supporting Documents filed by Google Inc.. (Attachments: # 1 Exhibit 1, # 2
Exhibit 2, # 3 Declaration of Laszlo Bock, # 4 Declaration of Eric B. Evans, # 5 Proposed
Order)(Evans, Eric) (Filed on 1/25/2013) (Entered: 01/25/2013)

02/01/2013

320

Statement JOINT DISCOVERY STATUS REPORT by Adobe Systems Inc., Apple Inc.,
Michael Devine, Mark Fichtner, Google Inc., Siddharth Hariharan, Intel Corp., Intuit Inc.,
Lucasfilm Ltd., Brandon Marshall, Pixar, Daniel Stover. (Dermody, Kelly) (Filed on
2/1/2013) (Entered: 02/01/2013)

02/05/2013

321

Transcript of Proceedings held on 01-17-13, before Judge Lucy H. Koh. Court
Reporter/Transcriber Lee-Anne Shortridge, Telephone number 408-287-4580. Per General
Order No. 59 and Judicial Conference policy, this transcript may be viewed only at the
Clerks Office public terminal or may be purchased through the Court Reporter/Transcriber
until the deadline for the Release of Transcript Restriction.After that date it may be obtained
through PACER. Any Notice of Intent to Request Redaction, if required, is due no later than
5 business days from date of this filing. Release of Transcript Restriction set for 5/6/2013.
(las, ) (Filed on 2/5/2013) (Entered: 02/05/2013)

02/05/2013

322

ORDER REGARDING JOINT DISCOVERY STATUS REPORT TO THE COURT. Signed
by Judge Lucy H. Koh on 2/05/2013. (lhklc3, COURT STAFF) (Filed on 2/5/2013) (Entered:
02/05/2013)

02/08/2013

323

STIPULATION WITH PROPOSED ORDER Permiting Supplemental Briefing Regarding
Plaintiffs Motion to Compel Google Documents filed by Michael Devine, Mark Fichtner,
Google Inc., Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Harvey, Dean) (Filed
on 2/8/2013) (Entered: 02/08/2013)

02/11/2013

324

STIPULATION AND ORDER PERMITTING SUPPLEMENTAL BRIEFING
REGARDING PLAINTIFFS' MOTION TO COMPEL GOOGLE DOCUMENTS by Judge
Paul S. Grewal, granting 323 . (ofr, COURT STAFF) (Filed on 2/11/2013) (Entered:
02/12/2013)

02/13/2013

325

Supplemental Brief re 278 MOTION to Compel Google Documents [REDACTED] filed
byMichael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover.
(Attachments: # 1 Declaration (Supplemental) of Dean M. Harvey in Support of Plaintiffs'
Motion to Compel [Redacted])(Related document(s) 278 ) (Harvey, Dean) (Filed on
2/13/2013) (Entered: 02/13/2013)

02/13/2013

326

Administrative Motion to File Under Seal Portions of Plaintiffs' Supplement Regarding
Motion to Compel Google Documents filed by Michael Devine, Mark Fichtner, Siddharth
Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Exhibit A, # 2 Exhibit B, # 3
Exhibit C, # 4 Exhibit D)(Harvey, Dean) (Filed on 2/13/2013) (Entered: 02/13/2013)

02/15/2013

327

STATUS REPORT Joint Discovery Status Report by Adobe Systems Inc., Apple Inc.,
Michael Devine, Mark Fichtner, Google Inc., Siddharth Hariharan, Intel Corp., Intuit Inc.,
Lucasfilm Ltd., Brandon Marshall, Pixar, Daniel Stover. (Shaver, Anne) (Filed on 2/15/2013)
(Entered: 02/15/2013)

02/18/2013

328

RESPONSE (re 278 MOTION to Compel Google Documents [REDACTED] 1173
) Supplement

regarding Plaintiffs' Motion to Compel filed byGoogle Inc.. (Attachments: # 1 Declaration of
Eric B. Evans)(Evans, Eric) (Filed on 2/18/2013) (Entered: 02/18/2013)
02/18/2013

329

Administrative Motion to File Under Seal filed by Google Inc.. (Attachments: # 1 Exhibit 1,
# 2 Exhibit 2, # 3 Declaration of Eric B. Evans, # 4 Proposed Order)(Evans, Eric) (Filed on
2/18/2013) (Entered: 02/18/2013)

02/20/2013

330

ORDER RE Privilege Logs. Signed by Judge Lucy H. Koh on 2/20/2013. (lhklc3, COURT
STAFF) (Filed on 2/20/2013) (Entered: 02/20/2013)

02/20/2013

331

Administrative Motion to File Under Seal filed by Google Inc.. (Attachments: # 1 Exhibit A,
# 2 Exhibit B, # 3 Exhibit C, # 4 Exhibit D, # 5 Declaration of Eric B. Evans, # 6 Proposed
Order)(Evans, Eric) (Filed on 2/20/2013) (Entered: 02/20/2013)

02/26/2013

332

Minute Entry: Motion Hearing held on 2/26/2013 before Magistrate Judge Paul S. Grewal re
278 MOTION to Compel: The court takes matter under submission; written order after
hearing to be issued. (Court Reporter: Summer Fisher.) (ofr, COURT STAFF) (Date Filed:
2/26/2013) (Entered: 02/26/2013)

02/28/2013

333

ORDER GRANTING-IN-PART SEALING MOTIONS by Judge Paul S. Grewal granting
313 Administrative Motion to File Under Seal; granting in part and denying in part 319
Administrative Motion to File Under Seal; granting in part and denying in part 326
Administrative Motion to File Under Seal; granting in part and denying in part 329
Administrative Motion to File Under Seal; granting in part and denying in part 331
Administrative Motion to File Under Seal; granting 279 Administrative Motion to File Under
Seal (psglc2, COURT STAFF) (Filed on 2/28/2013) (Entered: 02/28/2013)

02/28/2013

334

ORDER RE PLAINTIFFS' MOTION TO COMPEL PRODUCTION by Judge Paul S.
Grewal denying 278 Motion to Compel (psglc2, COURT STAFF) (Filed on 2/28/2013)
(Entered: 02/28/2013)

03/02/2013

335

Administrative Motion to File Under Seal Exhibits 1 and 2 to the March 1, 2013 Joint
Discovery Status Report filed by Michael Devine, Mark Fichtner, Siddharth Hariharan,
Brandon Marshall, Daniel Stover. (Attachments: # 1 Exhibit Exhibits 1 and 2)(Cisneros,
Lisa) (Filed on 3/2/2013) (Entered: 03/02/2013)

03/02/2013

336

JOINT DISCOVERY STATUS REPORT by Adobe Systems Inc., Apple Inc., Michael
Devine, Mark Fichtner, Google Inc., Siddharth Hariharan, Intel Corp., Intuit Inc., Lucasfilm
Ltd., Brandon Marshall, Pixar, Daniel Stover. (Attachments: # 1 Exhibit A to Joint Discovery
Status Report, # 2 Slip Sheet)(Cisneros, Lisa) (Filed on 3/2/2013) Modified text on 3/4/2013
(dhmS, COURT STAFF). (Entered: 03/02/2013)

03/02/2013

337

Declaration of Lisa J. Cisneros Regarding Late Filing on 3/2/2013 Statement re 335
Administrative Motion to File Under Seal Exhibits 1 and 2 to the March 1, 2013 Joint
Discovery Status Report, 336 Status Report, by Michael Devine, Mark Fichtner, Siddharth
Hariharan, Brandon Marshall, Daniel Stover. (Cisneros, Lisa) (Filed on 3/2/2013) Modified
text on 3/4/2013 (dhmS, COURT STAFF). (Entered: 03/02/2013)

03/04/2013

338

NOTICE OF REQUEST for In Camera Review by Michael Devine, Mark Fichtner,
Siddharth Hariharan, Brandon Marshall, Daniel Stover (Attachments: # 1 Exhibit A)(Shaver,
Anne) (Filed on 3/4/2013) Modified text on 3/5/2013 (dhmS, COURT STAFF). (Entered:
03/04/2013)

03/04/2013

339

MOTION for Leave to File Statement of Recent Decision filed by Michael Devine, Mark
Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1
Supplement, # 2 Declaration, # 3 Proposed Order)(Dallal, James) (Filed on 3/4/2013)
(Entered: 03/04/2013)

03/06/2013

340

JOINT CASE MANAGEMENT STATEMENT filed by Adobe Systems Inc., Apple Inc.,
Michael Devine, Mark Fichtner, Google Inc., Siddharth Hariharan, Intel Corp., Intuit Inc.,

1174

Lucasfilm Ltd., Brandon Marshall, Pixar, Daniel Stover. (Brown, Christina) (Filed on
3/6/2013) Modified text on 3/8/2013 (dhmS, COURT STAFF). (Entered: 03/07/2013)
03/08/2013

341

NOTICE by Google Inc. re 334 Order on Motion to Compel Notice of Compliance with
February 27, 2013 Order (Evans, Eric) (Filed on 3/8/2013) (Entered: 03/08/2013)

03/08/2013

342

ORDER RE: DEPOSITION OBJECTIONS. Signed by Judge Lucy H. Koh on March 8,
2013. (lhklc1, COURT STAFF) (Filed on 3/8/2013) (Entered: 03/08/2013)

03/08/2013

343

MOTION for Leave to File Statement of Recent Decision filed by Lucasfilm Ltd..
(Attachments: # 1 *** EXHIBIT 1 FILED IN ERROR, REFER TO DOCUMENT 345 .
***
Exhibit 1, # 2 Proposed Order)(Sessions, Justina) (Filed on 3/8/2013) Modified on 3/11/2013
(fff, COURT STAFF). (Entered: 03/08/2013)

03/08/2013

344

CORRECTIONS to 340 Joint Case Management Statement, by Lucasfilm Ltd.. (Sessions,
Justina) (Filed on 3/8/2013) Modified text on 3/11/2013 (dhmS, COURT STAFF). (Entered:
03/08/2013)

03/08/2013

345

ERRATA re 343 MOTION for Leave to File Statement of Recent Decision CORRECTION
OF DOCKET #, 343 [343-1] by Lucasfilm Ltd.. (Sessions, Justina) (Filed on 3/8/2013)
(Entered: 03/08/2013)

03/08/2013

346

Administrative Motion to File Under Seal filed by Google Inc.. (Attachments: # 1
Declaration of Eric B. Evans, # 2 Signature Page (Declarations/Stipulations))(Evans, Eric)
(Filed on 3/8/2013) (Entered: 03/09/2013)

03/12/2013

347

Administrative Motion to File Under Seal Pursuant to February 28, 2013 Sealing Order filed
by Google Inc.. (Attachments: # 1 Declaration, # 2 Proposed Order, # 3 Exhibit, # 4 Exhibit,
# 5 Exhibit, # 6 Exhibit, # 7 Exhibit, # 8 Exhibit, # 9 Exhibit, # 10 Exhibit)(Selin, Anne)
(Filed on 3/12/2013) (Entered: 03/12/2013)

03/13/2013

348

MOTION for leave to appear in Pro Hac Vice ( Filing fee $ 305, receipt number 09717545843.) filed by Pixar. (Nields, John) (Filed on 3/13/2013) (Entered: 03/13/2013)

03/13/2013

349

Order by Hon. Lucy H. Koh granting (348) Motion for Pro Hac Vice in case 5:11-cv-02509LHK for Nields.Associated Cases: 5:11-cv-02509-LHK, 5:11-cv-03538-LHK, 5:11-cv03539-LHK, 5:11-cv-03540-LHK, 5:11-cv-03541-LHK, 5:12-cv-01262-LHK(lhklc3,
COURT STAFF) (Filed on 3/13/2013) (Entered: 03/13/2013)

03/13/2013

350

CASE MANAGEMENT ORDER. Signed by Judge Lucy H. Koh on March 13, 2013.
(lhklc1, COURT STAFF) (Filed on 3/13/2013) (Entered: 03/13/2013)

03/13/2013

357

Minute Entry: Further Case Management Conference held on 3/13/2013 before Judge Lucy
H. Koh (Date Filed: 3/13/2013). Further Case Management Conference set for 4/2/2013
02:00 PM in Courtroom 8, 4th Floor, San Jose. (Court Reporter Lee-Anne Shortridge.) (mpb,
COURT STAFF) (Date Filed: 3/13/2013) (Entered: 03/15/2013)

03/14/2013

351

Statement Regarding Document Redactions by Pixar. (Henn, Emily) (Filed on 3/14/2013)
(Entered: 03/14/2013)

03/14/2013

352

Statement re 350 Order Statement regarding Redactions by Google Inc.. (Evans, Eric) (Filed
on 3/14/2013) (Entered: 03/14/2013)

03/14/2013

353

Statement re 350 Order Defendants Adobe Systems Inc. and Intuit Inc.'s Statements
Regarding Redactions by Adobe Systems Inc., Intuit Inc.. (Mittelstaedt, Robert) (Filed on
3/14/2013) (Entered: 03/14/2013)

03/14/2013

354

Statement re 350 Order Regarding Redactions by Lucasfilm Ltd.. (Sessions, Justina) (Filed
on 3/14/2013) (Entered: 03/14/2013)

03/14/2013

355

1175
Statement Regarding Document Redactions by Apple Inc.. (Tubach, Michael) (Filed on

3/14/2013) (Entered: 03/14/2013)
03/14/2013

356

Statement Regarding Document Redactions by Intel Corp.. (Shah, Sujal) (Filed on
3/14/2013) (Entered: 03/14/2013)

03/15/2013

358

NOTICE of Change In Counsel by Cody Shawn Harris NOTICE OF WITHDRAWAL OF
COUNSEL (Harris, Cody) (Filed on 3/15/2013) (Entered: 03/15/2013)

03/15/2013

359

ORDER RE: REDACTIONS FOR LACK OF RELEVANCE AND/OR
RESPONSIVENESS. Signed by Judge Lucy H. Koh on March 15, 2013. (lhklc1, COURT
STAFF) (Filed on 3/15/2013) (Entered: 03/15/2013)

03/15/2013

360

STATUS REPORT Joint Discovery Status Report by Adobe Systems Inc., Apple Inc.,
Michael Devine, Mark Fichtner, Google Inc., Siddharth Hariharan, Intel Corp., Intuit Inc.,
Lucasfilm Ltd., Brandon Marshall, Pixar, Daniel Stover. (Harvey, Dean) (Filed on
3/15/2013) (Entered: 03/15/2013)

03/18/2013

361

ORDER GRANTING DEFENDANT GOOGLE INC.'S RENEWED ADMINISTRATIVE
MOTION TO FILE UNDER SEAL PURSUANT TO FEBRUARY 28, 2013 SEALING
ORDER by Judge Paul S. Grewal, granting 347 . (ofr, COURT STAFF) (Filed on 3/18/2013)
(Entered: 03/18/2013)

03/18/2013

362

ORDER RE: MARCH 15, 2013 STATUS REPORT. Signed by Judge Lucy H. Koh on
March 18, 2013. (lhklc1, COURT STAFF) (Filed on 3/18/2013) (Entered: 03/18/2013)

03/19/2013

363

TRANSCRIPT ORDER by Apple Inc. from Court Reporter Lee-Anne Shortridge. (Brown,
Christina) (Filed on 3/19/2013) (Entered: 03/19/2013)

03/21/2013

364

NOTICE of Appearance by Amanda R. Conley (Conley, Amanda) (Filed on 3/21/2013)
(Entered: 03/21/2013)

03/22/2013

365

Joint Discovery Status Report by Google Inc.. (Selin, Anne) (Filed on 3/22/2013) Modified
text on 3/25/2013 (dhmS, COURT STAFF). (Entered: 03/22/2013)

03/26/2013

366

Transcript of Proceedings held on 3-13-13, before Judge Lucy H. Koh. Court
Reporter/Transcriber Lee-Anne Shortridge, Telephone number 408-287-4580 email: [e-mail]. Per General Order No. 59 and Judicial Conference
policy, this transcript may be viewed only at the Clerks Office public terminal or may be
purchased through the Court Reporter/Transcriber until the deadline for the Release of
Transcript Restriction.After that date it may be obtained through PACER. Any Notice of
Intent to Request Redaction, if required, is due no later than 5 business days from date of this
filing. Release of Transcript Restriction set for 6/24/2013. (Related documents(s) 363 ) (las, )
(Filed on 3/26/2013) (Entered: 03/26/2013)

03/26/2013

367

TRANSCRIPT ORDER by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon
Marshall, Daniel Stover for Court Reporter Lee-Anne Shortridge. (Cisneros, Lisa) (Filed on
3/26/2013) (Entered: 03/26/2013)

03/27/2013

368

MOTION for Leave to File Statement of Recent Decision filed by Intuit Inc.. (Attachments: #
1 Exhibit 1, # 2 Exhibit A, # 3 Proposed Order)(Zeng, Catherine) (Filed on 3/27/2013)
(Entered: 03/27/2013)

03/28/2013

369

TRANSCRIPT ORDER by Intel Corp. for Court Reporter Lee-Anne Shortridge. (Busch,
Frank) (Filed on 3/28/2013) (Entered: 03/28/2013)

03/28/2013

370

MOTION to Withdraw as Attorney filed by Pixar. Responses due by 4/11/2013. Replies due
by 4/18/2013. (Attachments: # 1 Proposed Order)(Haslam, Robert) (Filed on 3/28/2013)
(Entered: 03/28/2013)

03/28/2013

371

STIPULATION WITH PROPOSED ORDER Regarding Document Admissibility and
Authentication filed by Adobe Systems Inc.. (Mittelstaedt, Robert) (Filed on 3/28/2013)

1176

(Entered: 03/28/2013)
03/29/2013

372

Order by Hon. Lucy H. Koh granting 368 Motion for Leave to File.(lhklc3, COURT STAFF)
(Filed on 3/29/2013) (Entered: 03/29/2013)

03/29/2013

373

Order by Hon. Lucy H. Koh granting 343 Motion for Leave to File Recent Decision.(lhklc3,
COURT STAFF) (Filed on 3/29/2013) (Entered: 03/29/2013)

03/29/2013

374

Order by Hon. Lucy H. Koh granting 339 Motion for Leave to File Recent Decision.(lhklc3,
COURT STAFF) (Filed on 3/29/2013) (Entered: 03/29/2013)

03/29/2013

375

Supplemental Brief re 361 Order on Administrative Motion to File Under Seal filed pursuant
to Order dkt. no. 361 filed byGoogle Inc.. (Related document(s) 361 ) (Evans, Eric) (Filed on
3/29/2013) (Entered: 03/29/2013)

03/29/2013

376

Declaration of D. Harvey in Support of 361 Order on Administrative Motion to File Under
Seal pursuant to Order dkt. no. 361 filed byGoogle Inc.. (Related document(s) 361 ) (Evans,
Eric) (Filed on 3/29/2013) (Entered: 03/29/2013)

03/29/2013

377

OPPOSITION to 361 Order on Administrative Motion to File Under Seal pursuant to Order
dkt. no. 361 by Google Inc.. (Evans, Eric) (Filed on 3/29/2013) Modified text on 4/1/2013
(dhmS, COURT STAFF). (Entered: 03/29/2013)

03/29/2013

378

DECLARATION of Eric B. Evans in Opposition to 361 Order on Administrative Motion to
File Under Seal pursuant to Order dkt. no. 361 filed byGoogle Inc.. (Related document(s)
361 ) (Evans, Eric) (Filed on 3/29/2013) (Entered: 03/29/2013)

03/29/2013

379

Joint Discovery Status Report by Adobe Systems Inc., Apple Inc., Michael Devine, Mark
Fichtner, Google Inc., Siddharth Hariharan, Intel Corp., Intuit Inc., Lucasfilm Ltd., Brandon
Marshall, Pixar, Daniel Stover. (Harvey, Dean) (Filed on 3/29/2013) Modified text on
4/1/2013 (dhmS, COURT STAFF). (Entered: 03/29/2013)

04/01/2013

380

ORDER REGARDING DISCOVERY. Signed by Judge Lucy H. Koh on 4/01/2013. (lhklc3,
COURT STAFF) (Filed on 4/1/2013) (Entered: 04/01/2013)

04/02/2013

381

CLERKS NOTICE CONTINUING FURTHER CASE MANAGEMENT CONFERENCE
Further Case Management Conference set for 4/8/2013 10:00 AM in Courtroom 8, 4th Floor,
San Jose. *****THIS IS A TEXT ONLY NOTICE. THERE IS NO DOCUMENT
ASSOCIATED WITH THIS DOCKET ENTRY***** (mpb, COURT STAFF) (Filed on
4/2/2013) (Entered: 04/02/2013)

04/05/2013

382

ORDER by Judge Lucy H. Koh granting in part and denying in part (187) Motion to Certify
Class; denying (210) Motion to Strike ; denying (263) Motion for Leave to File in case 5:11cv-02509-LHK (lhklc3, COURT STAFF) (Filed on 4/5/2013) (Entered: 04/05/2013)

04/05/2013

383

DOCUMENT E-FILED UNDER SEAL by Court Staff. (lhklc3, COURT STAFF) (Filed on
4/5/2013) (Additional attachment(s) added on 4/5/2013: # 1 Certificate/Proof of Service)
(mpbS, COURT STAFF). (Entered: 04/05/2013)

04/05/2013

384

ORDER RE: JOINT CASE MANAGEMENT STATEMENT. Signed by Judge Lucy H. Koh
on April 5, 2013. (lhklc1, COURT STAFF) (Filed on 4/5/2013) (Entered: 04/05/2013)

04/05/2013

385

STATUS REPORT Joint Discovery Status Report by Michael Devine, Mark Fichtner,
Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Cisneros, Lisa) (Filed on 4/5/2013)
(Entered: 04/05/2013)

04/08/2013

386

JOINT CASE MANAGEMENT STATEMENT filed by Adobe Systems Inc.. (Kiernan,
David) (Filed on 4/8/2013) Modified text on 4/9/2013 (dhmS, COURT STAFF). (Entered:
04/08/2013)

04/08/2013

387

TRANSCRIPT ORDER by Lucasfilm Ltd. for Court Reporter Lee-Anne Shortridge. (Paige,
1177
Eugene) (Filed on 4/8/2013) (Entered: 04/08/2013)

04/08/2013

388

04/08/2013

Minute Entry and Case Management Order: Further Case Management Conference held on
4/8/2013 before Judge Lucy H. Koh (Date Filed: 4/8/2013). Further Case Management
Conference set for 5/15/2013 02:00 PM in Courtroom 8, 4th Floor, San Jose. Final Pretrial
Conference set for 5/8/2014 01:30 PM in Courtroom 8, 4th Floor, San Jose. Jury Selection
set for 5/27/2014 09:00 AM in Courtroom 8, 4th Floor, San Jose before Hon. Lucy H. Koh.
Jury Trial set for 5/27/2014 09:00 AM in Courtroom 8, 4th Floor, San Jose before Hon. Lucy
H. Koh. (Court Reporter Lee-Anne Shortridge.) (mpb, COURT STAFF) (Date Filed:
4/8/2013) (Entered: 04/08/2013)
Set/Reset Hearing re 388 Case Management Conference - Further, Set Hearings Final Pretrial
Conference set for 5/8/2014 01:30 PM in Courtroom 8, 4th Floor, San Jose. (mpb, COURT
STAFF) (Filed on 4/8/2013) (Entered: 04/08/2013)

04/08/2013

389

TRANSCRIPT ORDER by Apple Inc. for Court Reporter Lee-Anne Shortridge. (Brown,
Christina) (Filed on 4/8/2013) (Entered: 04/08/2013)

04/09/2013

390

NOTICE by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel
Stover OF WITHDRAWAL REGARDING DKT. NOS. 186 AND 246 (Harvey, Dean) (Filed
on 4/9/2013) (Entered: 04/09/2013)

04/09/2013

391

Notice of Withdrawal of Motion Regarding Dkt. Nos. 195 , 211 , 254 , 264 , and 292
(Hinman, Frank) (Filed on 4/9/2013) (Entered: 04/09/2013)

04/12/2013

392

Transcript of Proceedings held on 4-8-13, before Judge Lucy H. Koh. Court
Reporter/Transcriber Lee-Anne Shortridge, Telephone number 408-287-4580 email: [e-mail]. Per General Order No. 59 and Judicial Conference
policy, this transcript may be viewed only at the Clerks Office public terminal or may be
purchased through the Court Reporter/Transcriber until the deadline for the Release of
Transcript Restriction.After that date it may be obtained through PACER. Any Notice of
Intent to Request Redaction, if required, is due no later than 5 business days from date of this
filing. Release of Transcript Restriction set for 7/11/2013. (Related documents(s) 387 ) (las, )
(Filed on 4/12/2013) (Entered: 04/12/2013)

04/12/2013

393

Joint Discovery Status Report by Michael Devine, Mark Fichtner, Siddharth Hariharan,
Brandon Marshall, Daniel Stover. (Cisneros, Lisa) (Filed on 4/12/2013) Modified text on
4/15/2013 (dhmS, COURT STAFF). (Entered: 04/12/2013)

04/12/2013

394

Joint Renewed Administrative Motion to File Under Seal Portions of the Expert Reports of
Dr. Leamer and Dr. Murphy filed by Adobe Systems Inc., Apple Inc., Google Inc., Intel
Corp., Intuit Inc., Lucasfilm Ltd., Pixar. (Attachments: # 1 Exhibit A-1, # 2 Exhibit B-1 (part
1), # 3 Exhibit B-1 (part 2), # 4 Exhibit B-1 (part 3), # 5 Exhibit C-1, # 6 Exhibit D-1, # 7
Exhibit E-1, # 8 Exhibit F-1, # 9 Exhibit G-1, # 10 Exhibit A-2 (highlighted), # 11 Exhibit B2 (highlighted), # 12 Exhibit C-2 (highlighted), # 13 Exhibit D-2 (highlighted), # 14 Exhibit
E-2 (highlighted), # 15 Exhibit F-2 (highlighted), # 16 Exhibit G-2 (highlighted), # 17
Proposed Order)(Brown, Christina) (Filed on 4/12/2013) Modified text on 4/15/2013 (dhmS,
COURT STAFF). (Entered: 04/12/2013)

04/12/2013

395

Declaration of Frank Busch in Support of 394 Joint Administrative Motion to File Under
Seal Portions of the Expert Reports of Dr. Leamer and Dr. Murphy filed byIntel Corp..
(Related document(s) 394 ) (Busch, Frank) (Filed on 4/12/2013) (Entered: 04/12/2013)

04/12/2013

396

Declaration of Anne M. Selin in Support of 394 Joint Administrative Motion to File Under
Seal Portions of the Expert Reports of Dr. Leamer and Dr. Murphy filed byGoogle Inc..
(Related document(s) 394 ) (Selin, Anne) (Filed on 4/12/2013) (Entered: 04/12/2013)

04/12/2013

397

Declaration of Catherine T. Zeng in Support of 394 Joint Administrative Motion to File
Under Seal Portions of the Expert Reports of Dr. Leamer and Dr. Murphy filed byIntuit Inc..
(Related document(s) 394 ) (Zeng, Catherine) (Filed on 4/12/2013) (Entered: 04/12/2013)

04/12/2013

398

Declaration of Christina Brown in Support of 394 Joint Administrative Motion to File Under
1178

Seal Portions of the Expert Reports of Dr. Leamer and Dr. Murphy filed byApple Inc..
(Related document(s) 394 ) (Brown, Christina) (Filed on 4/12/2013) (Entered: 04/12/2013)
04/12/2013

399

Declaration of Lin Kahn in Support of 394 Joint Administrative Motion to File Under Seal
Portions of the Expert Reports of Dr. Leamer and Dr. Murphy filed byAdobe Systems Inc..
(Related document(s) 394 ) (Kahn, Lin) (Filed on 4/12/2013) (Entered: 04/12/2013)

04/12/2013

400

Declaration of James M. Kennedy in Support of 394 Defendants' Renewed Motion to Seal
filed by Pixar. (Richardson, Chinue) (Filed on 4/12/2013) Modified on 4/15/2013 linking
entry to document #394 (dhmS, COURT STAFF). (Entered: 04/13/2013)

04/13/2013

401

Declaration of Justina K. Sessions in Support of 394 Joint Administrative Motion to File
Under Seal Portions of the Expert Reports of Dr. Leamer and Dr. Murphy filed byLucasfilm
Ltd.. (Related document(s) 394 ) (Sessions, Justina) (Filed on 4/13/2013) (Entered:
04/13/2013)

04/15/2013

402

ORDER Regarding April 12, 2013 Joint Discovery Status Report. Signed by Judge
Lucy H. Koh on 4/15/2013. (lhklc3, COURT STAFF) (Filed on 4/15/2013) (Entered:
04/15/2013)

04/15/2013

403

TRANSCRIPT ORDER by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon
Marshall, Daniel Stover for Court Reporter Lee-Anne Shortridge. (Cisneros, Lisa) (Filed on
4/15/2013) (Entered: 04/15/2013)

04/19/2013

404

Joint Discovery Status Report by Adobe Systems Inc., Apple Inc., Michael Devine, Mark
Fichtner, Google Inc., Siddharth Hariharan, Intel Corp., Intuit Inc., Lucasfilm Ltd., Brandon
Marshall, Pixar, Daniel Stover. (Dallal, James) (Filed on 4/19/2013) Modified text on
4/22/2013 (dhmS, COURT STAFF). (Entered: 04/19/2013)

04/25/2013

405

Declaration of Thomas Henry Intuit's In-House counsel filed byIntuit Inc.. (Kiernan, David)
(Filed on 4/25/2013) (Entered: 04/25/2013)

04/25/2013

406

Declaration of Adobe's In-House Counsel Karen Robinson filed byAdobe Systems Inc..
(Kiernan, David) (Filed on 4/25/2013) (Entered: 04/25/2013)

04/25/2013

407

Declaration of William G. Berry Re 402 April 15, 2013 Order filed by Google Inc.. (Selin,
Anne) (Filed on 4/25/2013) Modified on 4/26/2013 linking entry to document #402 (dhmS,
COURT STAFF). (Entered: 04/25/2013)

04/25/2013

408

Declaration of James M. Kennedy on behalf of Pixar pursuant tp 402 Court's April 15, 2013
Order filed by Pixar. (Richardson, Chinue) (Filed on 4/25/2013) Modified on 4/26/2013
linking entry to document #402 (dhmS, COURT STAFF). (Entered: 04/25/2013)

04/25/2013

409

Declaration of Joy C. Sherrod Regarding Intel's Production Of Compensation Related
Discovery Materials filed byIntel Corp.. (Shah, Sujal) (Filed on 4/25/2013) (Entered:
04/25/2013)

04/25/2013

410

Declaration of Thomas M. Jeon in Support of 402 Order dated April 15, 2013 filed
byLucasfilm Ltd.. (Attachments: # 1 Signature Attestation)(Related document(s) 402 )
(Purcell, Daniel) (Filed on 4/25/2013) (Entered: 04/25/2013)

04/25/2013

411

Declaration of Heather Moser Grenier filed byApple Inc.. (Attachments: # 1 Exhibit A)
(Tubach, Michael) (Filed on 4/25/2013) (Entered: 04/25/2013)

04/26/2013

412

TRANSCRIPT ORDER by UNITED STATES OF AMERICA for Court Reporter Lee-Anne
Shortridge. (Pletcher, Anna) (Filed on 4/26/2013) (Entered: 04/26/2013)

04/26/2013

413

JOINT DISCOVERY STATUS REPORT by Adobe Systems Inc., Apple Inc., Michael
Devine, Mark Fichtner, Google Inc., Siddharth Hariharan, Intel Corp., Intuit Inc., Lucasfilm
Ltd., Brandon Marshall, Pixar, Daniel Stover. (Dallal, James) (Filed on 4/26/2013) Modified
text on 4/29/2013 (dhmS, COURT STAFF). (Entered: 04/26/2013)

1179

05/03/2013

414

Joint Discovery Status Report by Adobe Systems Inc., Apple Inc., Michael Devine, Mark
Fichtner, Google Inc., Siddharth Hariharan, Intel Corp., Intuit Inc., Lucasfilm Ltd., Brandon
Marshall, Pixar, Daniel Stover. (Dallal, James) (Filed on 5/3/2013) Modified text on
5/6/2013 (dhmS, COURT STAFF). (Entered: 05/03/2013)

05/08/2013

415

JOINT CASE MANAGEMENT CONFERENCE STATEMENT filed by Michael Devine,
Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Cisneros, Lisa)
(Filed on 5/8/2013) Modified text on 5/9/2013 (dhmS, COURT STAFF). (Entered:
05/08/2013)

05/10/2013

416

JOINT DISCOVERY STATUS REPORT by Adobe Systems Inc., Apple Inc., Michael
Devine, Mark Fichtner, Google Inc., Siddharth Hariharan, Intel Corp., Intuit Inc., Lucasfilm
Ltd., Brandon Marshall, Pixar, Daniel Stover. (Dallal, James) (Filed on 5/10/2013) Modified
text on 5/13/2013 (dhmS, COURT STAFF). (Entered: 05/10/2013)

05/10/2013

417

Administrative Motion to File Under Seal filed by Michael Devine, Mark Fichtner, Siddharth
Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Exhibit 1:Redacted
Supplemental Class Certification Motion, # 2 Exhibit 2:Redacted Expert Report of Kevin
Hallock, # 3 Exhibit 3: Redacted Report of Edward Leamer, # 4 Proposed Order)(Harvey,
Dean) (Filed on 5/10/2013) (Entered: 05/10/2013)

05/10/2013

418

SUPPLEMENTAL MOTION to Certify Class and Brief in Support of Class Certification
filed by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel
Stover. Motion Hearing set for 8/8/2013 01:30 PM in Courtroom 8, 4th Floor, San Jose
before Hon. Lucy H. Koh. Responses due by 6/21/2013. Replies due by 7/12/2013.
(Attachments: # 1 Declaration Dean Harvey, # 2 Declaration Lisa Cisneros, # 3 Exhibit
Redacted Expert Report of Kevin Hallock, # 4 Exhibit Redacted Expert Report of Edward
Leamer, # 5 Proposed Order)(Harvey, Dean) (Filed on 5/10/2013) Modified text on
5/13/2013 (dhmS, COURT STAFF). (Entered: 05/10/2013)

05/14/2013

419

Order by Hon. Lucy H. Koh granting 370 Motion to Withdraw as Attorney. Attorney
Robert T. Haslam, III terminated.(lhklc3, COURT STAFF) (Filed on 5/14/2013)
(Entered: 05/14/2013)

05/14/2013

420

Order by Hon. Lucy H. Koh granting 371 Stipulation Regarding Document
Admissibility and Authentication.(lhklc3, COURT STAFF) (Filed on 5/14/2013)
(Entered: 05/14/2013)

05/15/2013

421

CASE MANAGEMENT ORDER. Signed by Judge Lucy H. Koh on 5/15/2013. (lhklc3,
COURT STAFF) (Filed on 5/15/2013) (Entered: 05/15/2013)

05/15/2013

422

Minute Entry: Further Case Management Conference held on 5/15/2013 before Judge Lucy
H. Koh (Date Filed: 5/15/2013). Further Case Management Conference set for 8/8/2013
01:30 PM in Courtroom 8, 4th Floor, San Jose. (Court Reporter Raynee Mercado.) (mpb,
COURT STAFF) (Date Filed: 5/15/2013) (Entered: 05/16/2013)

05/17/2013

423

JOINT DISCOVERY STATUS REPORT by Michael Devine, Mark Fichtner, Siddharth
Hariharan, Brandon Marshall, Daniel Stover. (Cisneros, Lisa) (Filed on 5/17/2013) Modified
text on 5/20/2013 (dhmS, COURT STAFF). (Entered: 05/17/2013)

05/17/2013

424

Joint Response to Administrative Motion to File Under Seal Plaintiffs' Supplemental Motion
in Support of Class Certification and Related Documents filed by Adobe Systems Inc..
(Attachments: # 1 Exhibit Expert Witness Report of Kevin Hallock - REDACTED, # 2
Exhibit Supplemental Expert Report of Edward E. Leamer, Ph.D. - REDACTED, # 3 Exhibit
Plaintiffs' Supplemental Motion and Brief in Support of Class Certification - REDACTED, #
4 Proposed Order, # 5 Certificate/Proof of Service POS of Documents Lodged Under Seal)
(Kiernan, David) (Filed on 5/17/2013) Modified text on 5/20/2013 (dhmS, COURT STAFF).
(Entered: 05/17/2013)

05/17/2013

425

Declaration of Catherine T. Zeng in Support of 424 Response to Administrative Motion to
1180

File Under Seal Plaintiffs' Supplemental Motion in Support of Class Certification and
Related Documents filed by Intuit Inc.. (Attachments: # 1 Exhibit EE, # 2 Exhibit FF, # 3
Exhibit GG, # 4 Exhibit HH, # 5 Exhibit II, # 6 Exhibit JJ, # 7 Exhibit 912, # 8 Exhibit 914, #
9 Exhibit 1107, # 10 Exhibit 1760, # 11 Exhibit 1761, # 12 Exhibit 2135, # 13 Exhibit 2140,
# 14 Exhibit 2142, # 15 Exhibit 2738, # 16 Exhibit 2739 Part 1, # 17 Exhibit 2739 Part 2, #
18 Exhibit 2739 Part 3, # 19 Exhibit 2740 Part 1, # 20 Exhibit 2740 Part 2, # 21 Exhibit
2743, # 22 Exhibit 2744, # 23 Certificate/Proof of Service)(Related document(s) 424 ) (Zeng,
Catherine) (Filed on 5/17/2013) Modified text on 5/20/2013 (dhmS, COURT STAFF).
(Entered: 05/17/2013)
05/17/2013

426

Declaration of Justina K. Sessions in Support of 424 Joint Response to Administrative
Motion to File Under Seal Plaintiffs' Supplemental Motion in Support of Class Certification
and Related Documents filed by Lucasfilm Ltd.. (Attachments: # 1 Exhibit 17, # 2 Exhibit 8,
# 3 Exhibit 112, # 4 Envelope 359, # 5 Exhibit 360, # 6 Exhibit 690, # 7 Exhibit 710, # 8
Exhibit 711, # 9 Exhibit 715, # 10 Exhibit 716, # 11 Exhibit 727, # 12 Exhibit 728, # 13
Exhibit 729, # 14 Exhibit 730, # 15 Exhibit 944, # 16 Exhibit 945, # 17 Exhibit 959, # 18
Exhibit 2002, # 19 Exhibit 2084, # 20 Exhibit 2088, # 21 Exhibit 2094, # 22 Exhibit 2096, #
23 Exhibit 2100, # 24 Exhibit KK, # 25 Exhibit LL, # 26 Exhibit MM, # 27 Exhibit NN, # 28
Exhibit OO, # 29 Exhibit PP)(Related document(s) 424 ) (Sessions, Justina) (Filed on
5/17/2013) Modified text on 5/20/2013 (dhmS, COURT STAFF). (Entered: 05/17/2013)

05/17/2013

427

Declaration of Eric B. Evans in Support of 424 Joint Response to Administrative Motion to
File Under Seal Plaintiffs' Administrative Motion to File Under Seal Plaintiffs' Supplemental
Motion in Support of Class Certification and Related Documents filed by Google Inc..
(Attachments: # 1 Exhibit Q, # 2 Exhibit R, # 3 Exhibit S, # 4 Exhibit T, # 5 Exhibit V, # 6
Exhibit W, # 7 Exhibit X, # 8 Exhibit EE)(Related document(s) 424 ) (Evans, Eric) (Filed on
5/17/2013) Modified text on 5/20/2013 (dhmS, COURT STAFF). (Entered: 05/17/2013)

05/17/2013

428

EXHIBITS re 418 SUPPLEMENTAL MOTION to Certify Class Public Exhibits to Cisneros
Declaration, Exhibit U filed byGoogle Inc.. (Attachments: # 1 Exhibit 175, # 2 Exhibit 186,
# 3 Exhibit 192, # 4 Exhibit 557, # 5 Exhibit 597, # 6 Exhibit 648, # 7 Exhibit 650, # 8
Exhibit 651, # 9 Exhibit 653, # 10 Exhibit 661, # 11 Exhibit 872, # 12 Exhibit 1868, # 13
Exhibit 1869, # 14 Exhibit 1870, # 15 Exhibit 1871, # 16 Exhibit 1872, # 17 Exhibit 2735)
(Related document(s) 418 ) (Evans, Eric) (Filed on 5/17/2013) (Entered: 05/17/2013)

05/17/2013

429

Declaration of Lin W. Kahn in Support of 424 Joint Response to Administrative Motion to
File Under Seal Plaintiffs' Administrative Motion to File Under Seal Plaintiffs' Supplemental
Motion in Support of Class Certification and Related Documents filed by Adobe Systems
Inc.. (Attachments: # 1 Exhibit A-D, F, # 2 Exhibit 11, # 3 Exhibit 12, # 4 Exhibit 210, # 5
Exhibit 216, # 6 Exhibit 300, # 7 Exhibit 416, # 8 Errata 1158, # 9 Exhibit 1159, # 10 Exhibit
1160, # 11 Exhibit 1250, # 12 Exhibit 2486-1, # 13 Exhibit 2486-2, # 14 Exhibit 2486-3, #
15 Exhibit 2487, # 16 Exhibit 2501, # 17 Exhibit 2800, # 18 Certificate/Proof of Service)
(Related document(s) 424 ) (Kahn, Lin) (Filed on 5/17/2013) Modified text on 5/20/2013
(dhmS, COURT STAFF). (Entered: 05/17/2013)

05/17/2013

430

REDACTION Declaration of Krystal N. Bowen in Support of 424 Joint Administrative
Motion to File Under Seal Plaintiffs' Supplemental Motion in Support of Class Certification
and Related Documents by Intel Corp.. (Attachments: # 1 Exhibit 9, # 2 Exhibit 10, # 3
Exhibit Y, # 4 Exhibit Z, # 5 Exhibit AA, # 6 Exhibit BB, # 7 Exhibit CC, # 8 Exhibit DD, #
9 Exhibit 391, # 10 Exhibit 392, # 11 Exhibit 393, # 12 Exhibit 397, # 13 Exhibit 398, # 14
Exhibit 399, # 15 Exhibit 400, # 16 Exhibit 478, # 17 Exhibit 781, # 18 Exhibit 2030, # 19
Exhibit 2033, # 20 Exhibit 2035)(Bowen, Krystal) (Filed on 5/17/2013) Modified text on
5/20/2013 (dhmS, COURT STAFF). (Entered: 05/17/2013)

05/17/2013

431

Declaration of James M. Kennedy in Support of 424 Joint Response to Administrative
Motion to File Under Seal Plaintiffs' Supplemental Motion in Support of Class Certification
and Related Documents filed by Pixar. (Attachments: # 1 Cisneros Ex. 129, # 2 Cisneros Ex.
137, # 3 Cisneros Ex. 420, # 4 Cisneros Ex. 424, # 5 Cisneros Ex. 1306, # 6 Cisneros Ex.
1308, # 7 Cisneros Ex. 1309, # 8 Cisneros Ex. QQ, # 9 Cisneros Ex. RR, # 101181
Cisneros Ex.

SS, # 11 Cisneros Ex. TT, # 12 Cisneros Ex. UU, # 13 Cisneros Ex. VV)(Related document
(s) 424 ) (Richardson, Chinue) (Filed on 5/17/2013) Modified text on 5/20/2013 (dhmS,
COURT STAFF). (Entered: 05/17/2013)
05/17/2013

432

Declaration of Christina Brown in Support of 424 Joint Response to Administrative Motion
to File Under Seal Plaintiffs' Supplemental Motion in Support of Class Certification and
Related Documents filed by Apple Inc.. (Related document(s) 424 ) (Brown, Christina)
(Filed on 5/17/2013) Modified text on 5/20/2013 (dhmS, COURT STAFF). (Entered:
05/17/2013)

05/17/2013

433

EXHIBITS re 432 Declaration in Support, Declaration of Christina Brown in Support of
Defendants' Joint Response to Plaintiffs' Administrative Motion to File Under Seal Plaintiffs'
Supplemental Motion in Support of Class Certification and Related Documents, Exhibits 1-8
filed byApple Inc.. (Attachments: # 1 Exhibit H, # 2 Exhibit I, # 3 Exhibit J, # 4 Exhibit K, #
5 Exhibit L, # 6 Exhibit M, # 7 Exhibit N, # 8 Exhibit O, # 9 Exhibit P, # 10 Exhibit 268, #
11 Exhibit 278, # 12 Exhibit 279, # 13 Exhibit 1130, # 14 Exhibit 1376, # 15 Exhibit 1854, #
16 Exhibit 1855 (part 1), # 17 Exhibit 1855 (part 2), # 18 Exhibit 1855 (part 3), # 19 Exhibit
1856, # 20 Exhibit 1858, # 21 Exhibit 1859)(Related document(s) 432 ) (Brown, Christina)
(Filed on 5/17/2013) (Entered: 05/18/2013)

05/20/2013

434

TRANSCRIPT ORDER by Apple Inc. for Court Reporter Raynee Mercado. (Brown,
Christina) (Filed on 5/20/2013) (Entered: 05/20/2013)

05/22/2013

435

MEDIATION STATUS REPORT by Michael Devine, Mark Fichtner, Siddharth Hariharan,
Brandon Marshall, Daniel Stover. (Cisneros, Lisa) (Filed on 5/22/2013) Modified text on
5/23/2013 (dhmS, COURT STAFF). (Entered: 05/22/2013)

05/28/2013

436

STATUS REPORT Joint Discovery Status Report by Adobe Systems Inc., Apple Inc.,
Michael Devine, Mark Fichtner, Google Inc., Siddharth Hariharan, Intel Corp., Intuit Inc.,
Lucasfilm Ltd., Brandon Marshall, Pixar, Daniel Stover. (Attachments: # 1 Declaration of
James G. Dallal re: Extension of Time to File Due to Technical Failure Pursuant to Civil
Local Rule 5-1(e)(5))(Dallal, James) (Filed on 5/28/2013) (Entered: 05/28/2013)

05/30/2013

437

ORDER RE: DISCOVERY STATUS REPORTS. Signed by Judge Lucy H. Koh on
May 30, 2013. (lhklc1, COURT STAFF) (Filed on 5/30/2013) (Entered: 05/30/2013)

05/31/2013

438

Transcript of Proceedings held on May 15, 2013, before Judge Lucy H. Koh. Court Reporter
Raynee H. Mercado, CSR, Telephone number 510-451-7530, [e-mail],
[e-mail]. Per General Order No. 59 and Judicial Conference
policy, this transcript may be viewed only at the Clerks Office public terminal or may be
purchased through the Court Reporter until the deadline for the Release of Transcript
Restriction.After that date it may be obtained through PACER. Any Notice of Intent to
Request Redaction, if required, is due no later than 5 business days from date of this filing.
Release of Transcript Restriction set for 8/29/2013. (Related documents(s) 434 ) (rhm) (Filed
on 5/31/2013) (Entered: 05/31/2013)

06/21/2013

439

OPPOSITION to ( 418 SUPPLEMENTAL MOTION to Certify Class ) filed by Adobe
Systems Inc., Apple Inc., Google Inc., Intel Corp., Intuit Inc., Lucasfilm Ltd., Pixar. (Brown,
Christina) (Filed on 6/21/2013) Modified text on 6/25/2013 (dhmS, COURT STAFF).
(Entered: 06/21/2013)

06/21/2013

440

Supplemental Expert Report of Professor Kevin M. Murphy in Support of 439 Opposition to
Motion filed by Adobe Systems Inc., Apple Inc., Google Inc., Intel Corp., Intuit Inc.,
Lucasfilm Ltd., Pixar. (Attachments: # 1 Exhibit, # 2 Appendix)(Related document(s) 439 )
(Busch, Frank) (Filed on 6/21/2013) Modified text on 6/25/2013 (dhmS, COURT STAFF).
(Entered: 06/21/2013)

06/21/2013

441

Declaration of Christina Brown in Support of 450 Defendants' Joint Adminstrative Motion to
File Under Seal Defendants' Opposition to Plaintiffs' Supplemental Motion in Support of
Class Certification and Related Documents filed by Apple Inc.. (Brown, Christina) (Filed on
1182

6/21/2013) Modified on 6/25/2013 linking entry to document #450 (dhmS, COURT STAFF).
(Entered: 06/22/2013)
06/21/2013

443

Declaration of Anne M. Selin In Support of 450 Defendants' Joint Administrative Motion to
Seal Defendants' Opposition to Plaintiffs' Supplemental Motion in Support of Class
Certification and Related Document filed by Google Inc.. (Selin, Anne) (Filed on 6/21/2013)
Modified on 6/25/2013 linking entry to document #450 (dhmS, COURT STAFF). (Entered:
06/22/2013)

06/21/2013

444

Declaration of James M. Kennedy in Support of 450 Defendants' Joint Administrative
Motion to Seal Defendants' Opposition to Plaintiffs' Supplemental Motion in Support of
Class Certification and Related Document filed by Pixar. (Richardson, Chinue) (Filed on
6/21/2013) Modified on 6/25/2013 linking entry to document #450 (dhmS, COURT STAFF).
(Entered: 06/22/2013)

06/22/2013

442

EXHIBIT Expert Report of Kathryn Shaw, Ph.D re 439 Opposition to Motion filed by Adobe
Systems Inc.. (Related document(s) 439 ) (Kahn, Lin) (Filed on 6/22/2013) Modified text on
6/25/2013 (dhmS, COURT STAFF). (Entered: 06/22/2013)

06/22/2013

445

Declaration of Christina Brown in Support of 439 Opposition to Supplemental Class
Certification Motion filed by Adobe Systems Inc., Apple Inc., Google Inc., Intel Corp., Intuit
Inc., Lucasfilm Ltd., Pixar. (Attachments: # 1 Exhibit 1, # 2 Exhibit 2, # 3 Exhibit 3, # 4
Exhibit 4, # 5 Exhibit 5, # 6 Exhibit 6, # 7 Exhibit 7, # 8 Exhibit 8, # 9 Exhibit 9, # 10
Exhibit 10)(Related document(s) 439 ) (Brown, Christina) (Filed on 6/22/2013) Modified
text on 6/25/2013 (dhmS, COURT STAFF). (Entered: 06/22/2013)

06/22/2013

446

DECLARATION of Lin W. Kahn in Support of 439 Opposition to Supplemental to Motion
for Class Certification filed by Adobe Systems Inc.. (Attachments: # 1 Exhibit 1-10, part 1, #
2 Exhibit 1-10, part 2, # 3 Errata 11-20, # 4 Exhibit 21-27, # 5 Errata 28-30, part 1, # 6
Exhibit 28-30, part 2)(Related document(s) 439 ) (Kahn, Lin) (Filed on 6/22/2013) Modified
text on 6/25/2013 (dhmS, COURT STAFF). (Entered: 06/22/2013)

06/22/2013

447

Declaration of Lin W. Kahn in Support of 450 Joint Administrative Motion to File Under
Seal Defendants' Opposition to Plaintiffs' Supplemental Motion in Support of Class
Certification and Related Documents filed by Adobe Systems Inc.. (Related document(s)
450 ) (Kahn, Lin) (Filed on 6/22/2013) Modified on 6/25/2013 linking entry to document
#450 (dhmS, COURT STAFF). (Entered: 06/22/2013)

06/22/2013

448

Declaration of Catherine T. Zeng in Support of 450 Administrative Motion to File Under
Seal filed by Intuit Inc.. (Related document(s) 450 ) (Zeng, Catherine) (Filed on 6/22/2013)
Modified on 6/25/2013 linking entry to document #450 (dhmS, COURT STAFF). (Entered:
06/22/2013)

06/22/2013

449

Declaration of Frank Busch in Support of 450 Defendants Joint Administrative Motion to
File Under Seal filed by Intel Corp.. (Busch, Frank) (Filed on 6/22/2013) Modified on
6/25/2013 linking entry to document #450 (dhmS, COURT STAFF). (Entered: 06/22/2013)

06/22/2013

450

Joint Administrative Motion to File Under Seal Defendants' Opposition to Plaiintiffs'
Supplemental Moiton in Support of Class Certification and Related Documents filed by
Lucasfilm Ltd.. (Attachments: # 1 Exhibit 1, # 2 Exhibit 2, # 3 Exhibit 3, # 4 Exhibit 4)
(Sessions, Justina) (Filed on 6/22/2013) Modified text on 6/25/2013 (dhmS, COURT
STAFF). (Entered: 06/22/2013)

06/22/2013

451

Declaration of JUSTINA K. SESSIONS in Support of 450 Joint Administrative Motion to
File Under Seal Defendants' Opposition to Plaintiffs' Supplemental Motion in Support of
Class Certification and Related Documents filed by Lucasfilm Ltd.. (Related document(s)
450 ) (Sessions, Justina) (Filed on 6/22/2013) Modified on 6/25/2013 (dhmS, COURT
STAFF). (Entered: 06/22/2013)

06/27/2013

452

NOTICE OF ERRATA to 439 Opposition to Supplemental Class Certification Motion and
1183

440 Supplemental Expert Report of Professor Kevin M. Murphy by Adobe Systems Inc.,
Apple Inc., Google Inc., Intel Corp., Intuit Inc., Lucasfilm Ltd., Pixar. (Attachments: # 1
Corrected Exhibit 7)(Brown, Christina) (Filed on 6/27/2013) Modified text on 6/28/2013
(dhmS, COURT STAFF). (Entered: 06/27/2013)
07/12/2013

453

Letter from Co-Lead Class Counsel re Notice of Settlement. (Harvey, Dean) (Filed on
7/12/2013) (Entered: 07/12/2013)

07/12/2013

454

Administrative Motion to File Under Seal filed by Michael Devine, Mark Fichtner, Siddharth
Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Declaration of Anne B.
Shaver, # 2 Proposed Order, # 3 Exhibit, # 4 Exhibit, # 5 Exhibit, # 6 Exhibit)(Shaver, Anne)
(Filed on 7/12/2013) (Entered: 07/12/2013)

07/12/2013

455

REPLY in Support of ( 418 SUPPLEMENTAL MOTION to Certify Class ) [REDACTED]
filed by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel
Stover. (Shaver, Anne) (Filed on 7/12/2013) Modified text on 7/15/2013 (dhmS, COURT
STAFF). (Entered: 07/12/2013)

07/12/2013

456

Declaration of Anne B. Shaver in Support of 455 Plaintiffs' Reply in Support of
Supplemental Class Certification Motion filed by Michael Devine, Mark Fichtner, Siddharth
Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Exhibit, # 2 Exhibit, # 3
Exhibit)(Related document(s) 455 ) (Shaver, Anne) (Filed on 7/12/2013) Modified text on
7/15/2013 (dhmS, COURT STAFF). (Entered: 07/12/2013)

07/12/2013

457

Declaration of Edward E. Leamer in Support of 455 Reply to Opposition/Response
[REDACTED] filed byMichael Devine, Mark Fichtner, Siddharth Hariharan, Brandon
Marshall, Daniel Stover. (Related document(s) 455 ) (Shaver, Anne) (Filed on 7/12/2013)
(Entered: 07/12/2013)

07/12/2013

458

Declaration of Non-Party Sheryl Sandberg in Support of 455 Reply to Opposition/Response
[REDACTED] filed byMichael Devine, Mark Fichtner, Siddharth Hariharan, Brandon
Marshall, Daniel Stover. (Related document(s) 455 ) (Shaver, Anne) (Filed on 7/12/2013)
(Entered: 07/12/2013)

07/12/2013

459

CERTIFICATE OF SERVICE by Michael Devine, Mark Fichtner, Siddharth Hariharan,
Brandon Marshall, Daniel Stover re 457 Declaration in Support, 456 Declaration in Support,
455 Reply to Opposition/Response, 458 Declaration in Support, (Shaver, Anne) (Filed on
7/12/2013) (Entered: 07/12/2013)

07/14/2013

460

ORDER REGARDING JULY 12, 2013 NOTICE OF SETTLEMENT LETTER. Signed
by Judge Lucy H. Koh on 7/14/2013. (lhklc3, COURT STAFF) (Filed on 7/14/2013)
(Entered: 07/14/2013)

07/19/2013

461

RESPONSE to ( 454 PLAINTIFFS ADMINISTRATIVE MOTION TO FILE UNDER
SEAL PLAINTIFFS REPLY IN SUPPORT OF SUPPLEMENTAL MOTION FOR CLASS
CERTIFICATION filed by Lucasfilm Ltd.. (Attachments: # 1 Exhibit A, # 2 Exhibit B, # 3
Exhibit C, # 4 Exhibit D, # 5 Exhibit E)(Sessions, Justina) (Filed on 7/19/2013) Modified
text on 7/23/2013 (dhmS, COURT STAFF). (Entered: 07/19/2013)

07/19/2013

462

JOINT RESPONSE to 454 Plaintiffs Administrative Motion To File Under Seal filed by
Adobe Systems Inc., Apple Inc., Google Inc., Intel Corp., Intuit Inc.. (Busch, Frank) (Filed
on 7/19/2013) Modified on 7/23/2013 counsel posted document incorrectly as a motion and
failed to link entry to related document (dhmS, COURT STAFF). (Entered: 07/19/2013)

07/19/2013

463

Declaration of Lin W. Kahn in Support of 462 Defendants Joint Response To Plaintiffs
Administrative Motion To File Under Seal filed by Adobe Systems Inc.. (Related document
(s) 462 ) (Kahn, Lin) (Filed on 7/19/2013) Modified text on 7/23/2013 (dhmS, COURT
STAFF). (Entered: 07/19/2013)

07/19/2013

464

Declaration of Rowan T. Mason in Support of 462 Defendants Joint Response To Plaintiffs

1184

Administrative Motion To File Under Seal filed by Intuit Inc.. (Related document(s) 462 )
(Mason, Rowan) (Filed on 7/19/2013) Modified text on 7/23/2013 (dhmS, COURT STAFF).
(Entered: 07/19/2013)
07/19/2013

465

Declaration of Anne M. Selin in Support of 462 Defendants Joint Response To Plaintiffs
Administrative Motion To File Under Seal filed by Google Inc.. (Related document(s) 462 )
(Selin, Anne) (Filed on 7/19/2013) Modified text on 7/23/2013 (dhmS, COURT STAFF).
(Entered: 07/19/2013)

07/19/2013

466

Declaration of Frank Busch in Support of 462 Defendants Joint Response To Plaintiffs
Administrative Motion To File Under Seal filed by Intel Corp.. (Related document(s) 462 )
(Busch, Frank) (Filed on 7/19/2013) Modified text on 7/23/2013 (dhmS, COURT STAFF).
(Entered: 07/19/2013)

07/19/2013

467

Proposed Order re 462 Defendants Joint Response To Plaintiffs Administrative Motion To
File Under Seal by Adobe Systems Inc., Apple Inc., Google Inc., Intel Corp., Intuit Inc..
(Busch, Frank) (Filed on 7/19/2013) Modified text on 7/23/2013 (dhmS, COURT STAFF).
(Entered: 07/19/2013)

07/19/2013

468

STATUS REPORT re Mediation by Adobe Systems Inc., Apple Inc., Michael Devine, Mark
Fichtner, Google Inc., Siddharth Hariharan, Intel Corp., Intuit Inc., Lucasfilm Ltd., Brandon
Marshall, Pixar, Daniel Stover. (Brown, Christina) (Filed on 7/19/2013) (Entered:
07/19/2013)

07/19/2013

469

OBJECTIONS to Evidence in Plaintiffs' Reply in Support of Supplemental Class
Certification Motion and Rebuttal Supplemental Expert Report of Edward E. Leamer, Ph.D.
re 457 Declaration of Edward E. Leamer , 455 Reply to Opposition/Response, by Adobe
Systems Inc., Apple Inc., Google Inc., Intel Corp., Intuit Inc.. (Brown, Christina) (Filed on
7/19/2013) Modified text on 7/23/2013 (dhmS, COURT STAFF). (Entered: 07/19/2013)

07/19/2013

470

REPLY in Support of 418 Supplemental Class Certification MOTION filed by Adobe
Systems Inc., Apple Inc., Google Inc., Intel Corp., Intuit Inc.. (Attachments: # 1 Exhibit
Leamer)(Related document(s) 462 ) (Busch, Frank) (Filed on 7/19/2013) Modified on
7/23/2013 incorrect event type selected when posting document. Entry linked to document
#418 (dhmS, COURT STAFF). (Entered: 07/19/2013)

07/19/2013

471

Declaration of Christina Brown in Support of 469 Objection to Reply Evidence filed
byAdobe Systems Inc., Apple Inc., Google Inc., Intel Corp., Intuit Inc.. (Attachments: # 1
Exhibit A, # 2 Exhibit B)(Related document(s) 469 ) (Brown, Christina) (Filed on 7/19/2013)
(Entered: 07/19/2013)

07/19/2013

472

EXHIBITS re 462 Defendants Joint Response To Plaintiffs Administrative Motion To File
Under Seal filed by Adobe Systems Inc., Apple Inc., Google Inc., Intel Corp., Intuit Inc..
(Attachments: # 1 Exhibit B, # 2 Exhibit C, # 3 Exhibit D)(Related document(s) 462 )
(Busch, Frank) (Filed on 7/19/2013) Modified text on 7/23/2013 (dhmS, COURT STAFF).
(Entered: 07/19/2013)

07/19/2013

473

EXHIBITS re 462 Defendants Joint Response To Plaintiffs Administrative Motion To File
Under Seal filed by Adobe Systems Inc., Apple Inc., Google Inc., Intel Corp., Intuit Inc..
(Attachments: # 1 Exhibit F, # 2 Exhibit G, # 3 Exhibit H, # 4 Exhibit J, # 5 Exhibit K, # 6
Exhibit L, # 7 Exhibit M, # 8 Exhibit N, # 9 Exhibit O)(Related document(s) 462 ) (Busch,
Frank) (Filed on 7/19/2013) Modified text on 7/23/2013 (dhmS, COURT STAFF). (Entered:
07/19/2013)

07/19/2013

474

EXHIBITS re 462 Defendants Joint Response To Plaintiffs Administrative Motion To File
Under Seal filed by Adobe Systems Inc., Apple Inc., Google Inc., Intel Corp., Intuit Inc..
(Attachments: # 1 Exhibit 2738, # 2 Exhibit 2739 (Part 1), # 3 Exhibit 2739 (Part 2), # 4
Exhibit 2739 (Part 3))(Related document(s) 462 ) (Busch, Frank) (Filed on 7/19/2013)
Modified text on 7/23/2013 (dhmS, COURT STAFF). (Entered: 07/19/2013)

1185

07/19/2013

475

Declaration of Christina Brown in Support of 462 Defendants Joint Response To Plaintiffs
Administrative Motion To File Under Seal filed by Apple Inc.. (Related document(s) 462 )
(Brown, Christina) (Filed on 7/19/2013) Modified text on 7/23/2013 (dhmS, COURT
STAFF). (Entered: 07/19/2013)

07/20/2013

476

Proposed Order re 462 Defendants Joint Response To Plaintiffs Administrative Motion To
File Under Seal CORRECTION OF DOCKET # 467 . by Adobe Systems Inc., Apple Inc.,
Google Inc., Intel Corp., Intuit Inc.. (Busch, Frank) (Filed on 7/20/2013) Modified text on
7/23/2013 (dhmS, COURT STAFF). (Entered: 07/20/2013)

07/22/2013

477

STIPULATION WITH PROPOSED ORDER Substituting Counsel by Lucasfilm and Pixar
filed by Pixar. (Henn, Emily) (Filed on 7/22/2013) (Entered: 07/22/2013)

07/22/2013

478

TRANSCRIPT ORDER by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon
Marshall, Daniel Stover for Court Reporter Raynee Mercado. (Harvey, Dean) (Filed on
7/22/2013) (Entered: 07/22/2013)

07/23/2013

479

MOTION TO ENFORCE LOCAL RULE 7-3(d)(1) AND STRIKE DEFENDANTS'
IMPROPER SUR REPLY filed by Michael Devine, Mark Fichtner, Siddharth Hariharan,
Brandon Marshall, Daniel Stover. Responses due by 7/29/2013. (Attachments: # 1 Proposed
Order)(Harvey, Dean) (Filed on 7/23/2013) (Entered: 07/23/2013)

07/23/2013

480

Declaration of DEAN M. HARVEY in Support of 479 MOTION TO ENFORCE LOCAL
RULE 7-3(d)(1) AND STRIKE DEFENDANTS' IMPROPER SUR REPLY filed byMichael
Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover.
(Attachments: # 1 Exhibit A, # 2 Exhibit B, # 3 Exhibit C, # 4 Exhibit D, # 5 Exhibit E)
(Related document(s) 479 ) (Harvey, Dean) (Filed on 7/23/2013) (Entered: 07/23/2013)

07/24/2013

481

Order by Hon. Lucy H. Koh granting 477 Stipulation to Permit Keker & Van Nest LLP
to Withdraw as Counsel for Lucasfilm.(lhklc3, COURT STAFF) (Filed on 7/24/2013)
(Entered: 07/24/2013)

07/25/2013

482

NOTICE of Appearance by Robert Addy Van Nest Daniel Purcell, Eugene M. Paige, Justina
K. Sessions (Van Nest, Robert) (Filed on 7/25/2013) (Entered: 07/25/2013)

07/26/2013

483

BRIEF Regarding the Impact of the Proposed Settlement on Plaintiffs' Supplemental Motion
for Class Certification re 460 Order by Michael Devine, Mark Fichtner, Siddharth Hariharan,
Brandon Marshall, Daniel Stover. (Harvey, Dean) (Filed on 7/26/2013) Modified text on
7/29/2013 (dhmS, COURT STAFF). (Entered: 07/26/2013)

07/26/2013

484

JOINT BRIEF Regarding the Impact of the Proposed Pixar and Lucasfilm Settlements on the
Supplemental Class Certification Motion re 460 Order by Adobe Systems Inc., Apple Inc.,
Google Inc., Intel Corp., Intuit Inc.. (Brown, Christina) (Filed on 7/26/2013) Modified text
on 7/29/2013 (dhmS, COURT STAFF). (Entered: 07/26/2013)

07/28/2013

485

OPPOSITION to ( 479 MOTION TO ENFORCE LOCAL RULE 7-3(d)(1) AND STRIKE
DEFENDANTS' IMPROPER SUR REPLY )filed by Adobe Systems Inc., Apple Inc.,
Google Inc., Intel Corp., Intuit Inc.. (Attachments: # 1 Proposed Order)(Brown, Christina)
(Filed on 7/28/2013) Modified text on 7/29/2013 (dhmS, COURT STAFF). (Entered:
07/28/2013)

07/29/2013

486

NOTICE of Appearance by Daniel Edward Purcell (Purcell, Daniel) (Filed on 7/29/2013)
(Entered: 07/29/2013)

07/29/2013

487

NOTICE of Appearance by Eugene Morris Paige (Paige, Eugene) (Filed on 7/29/2013)
(Entered: 07/29/2013)

07/29/2013

488

NOTICE of Appearance by Justina Kahn Sessions (Sessions, Justina) (Filed on 7/29/2013)
(Entered: 07/29/2013)

07/30/2013

489

Letter from Co-Lead Class Counsel re Notice of Settlement. (Harvey, Dean) (Filed on
1186

7/30/2013) (Entered: 07/30/2013)
08/01/2013

490

CASE MANAGEMENT STATEMENT filed by Michael Devine, Mark Fichtner, Siddharth
Hariharan, Brandon Marshall, Daniel Stover. (Cisneros, Lisa) (Filed on 8/1/2013) (Entered:
08/01/2013)

08/08/2013

495

Minute Entry: Motion Hearing held on 8/8/2013 before Judge Lucy H. Koh (Date Filed:
8/8/2013) re 418 SUPPLEMENTAL MOTION to Certify Class filed by Michael Devine,
Siddharth Hariharan, Mark Fichtner, Daniel Stover, Brandon Marshall, Further Case
Management Conference held on 8/8/2013 before Judge Lucy H. Koh (Date Filed: 8/8/2013),
Case referred to Private ADR.. Further Case Management Conference set for 10/3/2013
01:30 PM in Courtroom 8, 4th Floor, San Jose. (Court Reporter Lee-Anne Shortridge.) (mpb,
COURT STAFF) (Date Filed: 8/8/2013) (Entered: 08/19/2013)

08/09/2013

491

MOTION for Leave to File Statement of Recent Decision filed by Apple Inc.. (Attachments:
# 1 Exhibit 1 - Statement of Recent Decision, # 2 Proposed Order and Stipulation)(Riley,
George) (Filed on 8/9/2013) (Entered: 08/09/2013)

08/12/2013

492

TRANSCRIPT ORDER by Apple Inc. for Court Reporter Lee-Anne Shortridge. (Brown,
Christina) (Filed on 8/12/2013) (Entered: 08/12/2013)

08/12/2013

493

TRANSCRIPT ORDER by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon
Marshall, Daniel Stover for Court Reporter Lee-Anne Shortridge. (Cisneros, Lisa) (Filed on
8/12/2013) (Entered: 08/12/2013)

08/19/2013

494

Transcript of Proceedings held on 8-8-13, before Judge Lucy H. Koh. Court
Reporter/Transcriber Lee-Anne Shortridge, Telephone number 408-287-4580 email: [e-mail]. Per General Order No. 59 and Judicial Conference
policy, this transcript may be viewed only at the Clerks Office public terminal or may be
purchased through the Court Reporter/Transcriber until the deadline for the Release of
Transcript Restriction.After that date it may be obtained through PACER. Any Notice of
Intent to Request Redaction, if required, is due no later than 5 business days from date of this
filing. Release of Transcript Restriction set for 11/18/2013. (Related documents(s) 492 )
(las, ) (Filed on 8/19/2013) (Entered: 08/19/2013)

08/23/2013

496

MOTION for Leave to File Statement of Recent Decision filed by Michael Devine, Mark
Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Exhibit 1
- Statement of Recent Decision, # 2 Proposed Order and Stipulation)(Harvey, Dean) (Filed
on 8/23/2013) (Entered: 08/23/2013)

08/27/2013

497

CHART Related to 424 Defendants' Joint Response to Plaintiffs' Administrative Motion to
File Under Seal and Suporting Declarations Filed on May 17, 2013 filed by Adobe Systems
Inc., Apple Inc., Google Inc., Intel Corp., Intuit Inc., Lucasfilm Ltd., Pixar. (Related
document(s) 424 ) (Selin, Anne) (Filed on 8/27/2013) Modified text on 8/28/2013 (dhmS,
COURT STAFF). (Entered: 08/27/2013)

08/30/2013

498

MOTION for Leave to File Statement of Recent Decision filed by Michael Devine, Mark
Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Exhibit
1, # 2 Proposed Order)(Harvey, Dean) (Filed on 8/30/2013) (Entered: 08/30/2013)

09/19/2013

499

MOTION for Leave to File Statement of Recent Decision filed by Michael Devine, Mark
Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Exhibit,
# 2 Proposed Order)(Dallal, James) (Filed on 9/19/2013) (Entered: 09/19/2013)

09/19/2013

500

Letter from Co-Lead Class Counsel and Counsel for Settling Defendants re Motion for
Preliminary Approval of Class Action Settlements. (Harvey, Dean) (Filed on 9/19/2013)
(Entered: 09/19/2013)

09/21/2013

501

MOTION for Preliminary Approval of Class Action Settlements; Memorandum of Points
and Authorities in Support Thereof [REDACTED] filed by Michael Devine, Mark Fichtner,

1187

Siddharth Hariharan, Brandon Marshall, Daniel Stover. Motion Hearing set for 10/3/2013
01:30 PM in Courtroom 8, 4th Floor, San Jose before Hon. Lucy H. Koh. Responses due by
10/7/2013. Replies due by 10/15/2013. (Attachments: # 1 Proposed Order Granting Plaintiffs
Motion for Conditional Class Certification and Preliminary Approval of Class Action
Settlements with Defendants Intuit Inc., Lucasfilm, Ltd., and Pixar)(Cisneros, Lisa) (Filed on
9/21/2013) Modified text on 9/23/2013 (dhmS, COURT STAFF). (Entered: 09/21/2013)
09/21/2013

502

Declaration of Kelly M. Dermody in Support of 501 MOTION for Preliminary Approval
[REDACTED] filed by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon
Marshall, Daniel Stover. (Attachments: # 1 Exhibit 1, # 2 Exhibit 2, # 3 Exhibit 3, # 4
Exhibit 4, # 5 Exhibit 5, # 6 Exhibit 6)(Related document(s) 501 ) (Cisneros, Lisa) (Filed on
9/21/2013) Modified text on 9/23/2013 (dhmS, COURT STAFF). (Entered: 09/21/2013)

09/21/2013

503

Declaration of Joseph R. Saveri in Support of 501 MOTION for Preminary Approval of
Class Action Settlement [REDACTED] filed by Michael Devine, Mark Fichtner, Siddharth
Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Exhibit 1)(Related document
(s) 501 ) (Cisneros, Lisa) (Filed on 9/21/2013) Modified text on 9/23/2013 (dhmS, COURT
STAFF). (Entered: 09/21/2013)

09/21/2013

504

Administrative Motion to File Under Seal Portions of Plaintiffs' Motion for Preliminary
Approval of Class Settlements filed by Michael Devine, Mark Fichtner, Siddharth Hariharan,
Brandon Marshall, Daniel Stover. (Attachments: # 1 Exhibit 1, # 2 Exhibit 2, # 3 Exhibit 3, #
4 Exhibit 4, # 5 Exhibit 5, # 6 Exhibit 6, # 7 Declaration Dean M. Harvey, # 8 Proposed
Order)(Cisneros, Lisa) (Filed on 9/21/2013) (Entered: 09/21/2013)

09/25/2013

505

MOTION for Leave to File Statement of Recent Decision filed by Michael Devine, Mark
Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Exhibit
1, # 2 Proposed Order and Stipulation)(Cisneros, Lisa) (Filed on 9/25/2013) (Entered:
09/25/2013)

09/25/2013

506

NOTICE by Lucasfilm Ltd., Pixar of Letter to Attorneys General (Attachments: # 1 Letter)
(Henn, Emily) (Filed on 9/25/2013) (Entered: 09/25/2013)

09/25/2013

507

NOTICE by Intuit Inc. of Mailing of Letter to Attorneys General Pursuant to 28 U.S.C.
Section 1715 (Attachments: # 1 Exhibit)(Kiernan, David) (Filed on 9/25/2013) (Entered:
09/25/2013)

09/26/2013

508

JOINT CASE MANAGEMENT STATEMENT filed by Adobe Systems Inc., Apple Inc.,
Michael Devine, Mark Fichtner, Google Inc., Siddharth Hariharan, Intel Corp., Brandon
Marshall, Daniel Stover. (Sessions, Justina) (Filed on 9/26/2013) Modified text on 9/30/2013
(dhmS, COURT STAFF). (Entered: 09/26/2013)

09/30/2013

509

ORDER by Judge Lucy H. Koh granting in part and denying in part (307)
Administrative Motion to File Under Seal; granting in part and denying in part (335)
Administrative Motion to File Under Seal; granting in part and denying in part (346)
Administrative Motion to File Under Seal; granting in part and denying in part (394)
Administrative Motion to File Under Seal; granting in part and denying in part (271)
Administrative Motion to File Under Seal; granting in part and denying in part (283)
Administrative Motion to File Under Seal in case 5:11-cv-02509-LHK (lhklc4, COURT
STAFF) (Filed on 9/30/2013) (Entered: 09/30/2013)

09/30/2013

510

ORDER by Judge Lucy H. Koh granting 491 Motion for Leave to File; granting 496
Motion for Leave to File; granting 498 Motion for Leave to File; granting 499 Motion
for Leave to File; granting 505 Motion for Leave to File. ****THIS IS A TEXT-ONLY
ENTRY. THERE IS NO DOCUMENT ASSOCIATED WITH THIS DOCKET
ENTRY**** (lhklc1, COURT STAFF) (Filed on 9/30/2013) (Entered: 09/30/2013)

10/01/2013

511

CLERKS NOTICE CONTINUING FURTHER CASE MANAGEMENT CONFERENCE
AND MOTION FOR PRELIMINARY APPROVAL Further Case Management Conference
set for 10/21/2013 02:00 PM in Courtroom 8, 4th Floor, San Jose. Motion Hearing set for
1188

10/21/2013 02:00 PM in Courtroom 8, 4th Floor, San Jose before Hon. Lucy H. Koh.
*****THIS IS A TEXT-ONLY NOTICE. THERE IS NO DOCUMENT ASSOCIATED
WITH THIS DOCKET ENTRY***** (mpb, COURT STAFF) (Filed on 10/1/2013)
(Entered: 10/01/2013)
10/01/2013

Set/Reset Hearing re 511 Clerks Notice, Clerks Notice Continuing Motion Hearing, Set
Motion and Deadlines/Hearings,,, (mpb, COURT STAFF) (Filed on 10/1/2013) (Entered:
10/01/2013)

10/07/2013

512

DOCUMENT E-FILED UNDER SEAL re 509 Order on Administrative Motion to File
Under Seal,,,,,,,,,,,,,,,,, Expert Report of Professor Kevin M. Murphy by Adobe Systems Inc.,
Apple Inc., Google Inc., Intel Corp., Intuit Inc., Lucasfilm Ltd., Pixar. (Brown, Christina)
(Filed on 10/7/2013) (Entered: 10/07/2013)

10/07/2013

513

DOCUMENT E-FILED UNDER SEAL re 509 Order on Administrative Motion to File
Under Seal,,,,,,,,,,,,,,,,, Defendants' Joint Administrative Motion for Leave to Supplement the
Record by Adobe Systems Inc., Apple Inc., Google Inc., Intel Corp., Intuit Inc., Lucasfilm
Ltd., Pixar. (Attachments: # 1 Supplemental Declaration of Professor Kevin M. Murphy)
(Brown, Christina) (Filed on 10/7/2013) (Entered: 10/07/2013)

10/07/2013

514

REDACTION to 509 Order on Administrative Motion to File Under Seal,,,,,,,,,,,,,,,,, by
Adobe Systems Inc.. (Attachments: # 1 Plaintiffs Motion for Class Certification, # 2 Exhibit
14 to Declaration of Ann B. Shaver in Support of Plaintiffs Motion for Class Certification, #
3 Exhibit 4 to Declaration of Dean Harvey in Support of Plaintiffs Reply, # 4 Exhibit 26 to
Harvey Decl., # 5 Exhibit 29 to Harvey Decl.)(Kahn, Lin) (Filed on 10/7/2013) (Entered:
10/07/2013)

10/07/2013

515

REDACTION to 509 Order on Administrative Motion to File Under Seal,,,,,,,,,,,,,,,,, by
Google Inc.. (Attachments: # 1 Exhibit Exhibit A to March 1, 2013 Joint Discovery Status
Report)(Selin, Anne) (Filed on 10/7/2013) (Entered: 10/07/2013)

10/07/2013

516

REDACTION to 509 Order on Administrative Motion to File Under Seal,,,,,,,,,,,,,,,,, by
Google Inc.. (Attachments: # 1 Exhibit 14 to Brown Declaration in Support of Defendants'
Opposition to Plaintiffs' Motion for Class Certification (Part 1), # 2 Exhibit 14 to Brown
Declaration in Support of Defendants' Opposition to Plaintiffs' Motion for Class Certification
(Part 2), # 3 Exhibit 14 to Brown Declaration in Support of Defendants' Opposition to
Plaintiffs' Motion for Class Certification (Part 3), # 4 Exhibit 14 to Brown Declaration in
Support of Defendants' Opposition to Plaintiffs' Motion for Class Certification (Part 4), # 5
Exhibit 19 to Brown Declaration in Support of Defendants' Opposition to Plaintiffs' Motion
for Class Certification, # 6 Exhibit 21 to Brown Declaration in Support of Defendants'
Opposition to Plaintiffs' Motion for Class Certification, # 7 Exhibit 25 to Brown Declaration
in Support of Defendants' Opposition to Plaintiffs' Motion for Class Certification, # 8 Exhibit
26 to Brown Declaration in Support of Defendants' Opposition to Plaintiffs' Motion for Class
Certification, # 9 Exhibit 27 to Brown Declaration in Support of Defendants' Opposition to
Plaintiffs' Motion for Class Certification, # 10 Motion to Strike Leamer Report)(Selin, Anne)
(Filed on 10/7/2013) (Entered: 10/07/2013)

10/07/2013

517

DOCUMENT E-FILED UNDER SEAL re 509 Order on Administrative Motion to File
Under Seal,,,,,,,,,,,,,,,,, 273 Order on Administrative Motion to File Under Seal,,,,,,,,,,,,,,,,,,,
Defendants' Opposition to Plaintiffs' Motion for Class Certification by Adobe Systems Inc.,
Apple Inc., Google Inc., Intel Corp., Intuit Inc., Lucasfilm Ltd., Pixar. (Attachments: # 1
Declaration of Christina Brown in Support of Defendants' Opposition to Plaintiffs' Motion
for Class Certification, # 2 Exhibit 1, # 3 Exhibit 2, # 4 Exhibit 3, # 5 Exhibit 4, # 6 Exhibit
5, # 7 Exhibit 6, # 8 Exhibit 9, # 9 Exhibit 10, # 10 Exhibit 11, # 11 Exhibit 12, # 12 Exhibit
13, # 13 Exhibit 14 (part 1), # 14 Exhibit 14 (part 2), # 15 Exhibit 15, # 16 Exhibit 16, # 17
Exhibit 17 (part 1), # 18 Exhibit 17 (part 2), # 19 Exhibit 17 (part 3), # 20 Exhibit 18 (part 1),
# 21 Exhibit 18 (part 2), # 22 Exhibit 19, # 23 Exhibit 20, # 24 Exhibit 21, # 25 Exhibit 22, #
26 Exhibit 23, # 27 Exhibit 25, # 28 Exhibit 26, # 29 Exhibit 27)(Brown, Christina) (Filed on
10/7/2013) (Entered: 10/07/2013)
1189

10/07/2013

518

REDACTION to 509 Order on Administrative Motion to File Under Seal,,,,,,,,,,,,,,,,, by Intel
Corp., Apple Inc., Intuit Inc., Adobe Systems Inc., Pixar, Google Inc., Lucasfilm Ltd..
(Attachments: # 1 Expert Report of Edward E. Leamer, Ph.D., # 2 Expert Report of Professor
Kevin M. Murphy (part 1), # 3 Expert Report of Professor Kevin M. Murphy (part 2), # 4
Expert Report of Professor Kevin M. Murphy (part 3), # 5 Reply Expert Report of Edward E.
Leamer, Ph.D.)(Brown, Christina) (Filed on 10/7/2013) (Entered: 10/07/2013)

10/07/2013

519

DOCUMENT E-FILED UNDER SEAL re 509 Order on Administrative Motion to File
Under Seal,,,,,,,,,,,,,,,,, EXPERT REPORT OF EDWARD E. LEAMER, PH.D ISO October 1,
2012 Motion to Certify Class (redacted version at Docket No. 190) by Michael Devine, Mark
Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Cisneros, Lisa) (Filed on
10/7/2013) (Entered: 10/07/2013)

10/07/2013

520

DOCUMENT E-FILED UNDER SEAL re 509 Order on Administrative Motion to File
Under Seal,,,,,,,,,,,,,,,,, REPLY EXPERT REPORT OF EDWARD E. LEAMER, PH.D ISO
December 10, 2012 Reply Brief (redacted version at Docket No. 249) by Michael Devine,
Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Cisneros, Lisa)
(Filed on 10/7/2013) (Entered: 10/07/2013)

10/07/2013

521

DOCUMENT E-FILED UNDER SEAL re 509 Order on Administrative Motion to File
Under Seal,,,,,,,,,,,,,,,,, PLAINTIFFS' OPPOSITION TO DEFENDANTS' JOINT ADMIN.
MOT. FOR LEAVE TO SUPPLEMENT THE RECORD ISO THEIR OPPOSITION TO THE
MOT. FOR CLASS CERT. AND MOT. TO STRIKE DR. LEAMER'S EXPERT REPORT,
Docket No. (redacted version at Docket No. 270) by Michael Devine, Mark Fichtner,
Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Declaration
DECLARATION OF EDWARD E. LEAMER IN OPPOSITION TO DEFENDANTS
ADMINISTRATIVE MOTION, Docket No. (redacted version at Docket No. 270-1))
(Cisneros, Lisa) (Filed on 10/7/2013) (Entered: 10/07/2013)

10/17/2013

522

NOTICE of Substitution of Counsel by Gregory P. Stone AND CONSENT ORDER (Stone,
Gregory) (Filed on 10/17/2013) (Entered: 10/17/2013)

10/17/2013

523

CASE MANAGEMENT STATEMENT [UPDATED] filed by Adobe Systems Inc., Apple
Inc., Google Inc., Intel Corp.. (Van Nest, Robert) (Filed on 10/17/2013) (Entered:
10/17/2013)

10/18/2013

524

STIPULATION WITH PROPOSED ORDER Regarding Substitution of Counsel for Intel
Corporation filed by Intel Corp.. (Stone, Gregory) (Filed on 10/18/2013) (Entered:
10/18/2013)

10/20/2013

525

RESPONSE to 523 the Non-Settling Defendants' Unauthorized Supplemental Filing of
Updated Case Management Statement by Michael Devine, Mark Fichtner, Siddharth
Hariharan, Brandon Marshall, Daniel Stover. (Attachments: # 1 Exhibit A, # 2 Exhibit B, # 3
Exhibit C, # 4 Exhibit D)(Dermody, Kelly) (Filed on 10/20/2013) Modified text on
10/21/2013 (dhmS, COURT STAFF). (Entered: 10/20/2013)

10/20/2013

526

Order by Hon. Lucy H. Koh granting (524) Stipulation in case 5:11-cv-02509LHK.Associated Cases: 5:11-cv-02509-LHK, 5:11-cv-03538-LHK, 5:11-cv-03539-LHK,
5:11-cv-03540-LHK, 5:11-cv-03541-LHK, 5:12-cv-01262-LHK(lhklc1, COURT STAFF)
(Filed on 10/20/2013) (Entered: 10/20/2013)

10/21/2013

527

Case Management Order by Hon. Lucy H. Koh; Order granting in part and denying in
part (504) Administrative Motion to File Under Seal in case 5:11-cv-02509-LHK.
Associated Cases: 5:11-cv-02509-LHK, 5:11-cv-03538-LHK, 5:11-cv-03539-LHK, 5:11cv-03540-LHK, 5:11-cv-03541-LHK, 5:12-cv-01262-LHK (lhklc1, COURT STAFF)
(Filed on 10/21/2013) (Entered: 10/21/2013)

10/21/2013

534

Minute Entry: Motion Hearing held on 10/21/2013 before Judge Lucy H. Koh (Date Filed:
10/21/2013) re 501 MOTION for Preliminary Approval of Class Action Settlements
[REDACTED] filed by Michael Devine, Siddharth Hariharan, Mark Fichtner,1190 Stover,
Daniel

Brandon Marshall, Further Case Management Conference held on 10/21/2013 before Judge
Lucy H. Koh (Date Filed: 10/21/2013). Further Case Management Conference set for
12/18/2013 02:00 PM in Courtroom 8, 4th Floor, San Jose. (Court Reporter Lee-Anne
Shortridge.) (mpb, COURT STAFF) (Date Filed: 10/21/2013) (Entered: 10/28/2013)
10/22/2013

528

TRANSCRIPT ORDER by Apple Inc. for Court Reporter Lee-Anne Shortridge. (Brown,
Christina) (Filed on 10/22/2013) (Entered: 10/22/2013)

10/22/2013

529

TRANSCRIPT ORDER by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon
Marshall, Daniel Stover for Court Reporter Lee-Anne Shortridge. (Cisneros, Lisa) (Filed on
10/22/2013) (Entered: 10/22/2013)

10/22/2013

530

TRANSCRIPT ORDER by Intel Corp. for Court Reporter Lee-Anne Shortridge. (Stone,
Gregory) (Filed on 10/22/2013) (Entered: 10/22/2013)

10/24/2013

531

ORDER by Judge Lucy H. Koh granting 418 Motion to Certify Class (lhklc1, COURT
STAFF) (Filed on 10/24/2013) (Entered: 10/24/2013)

10/25/2013

532

DOCUMENT E-FILED UNDER SEAL by Court Staff. (Attachments: # 1 Certificate/Proof
of Service)(lhklc1, COURT STAFF) (Filed on 10/25/2013) (Entered: 10/25/2013)

10/25/2013

533

NOTICE by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel
Stover re 501 MOTION for Preliminary Approval of Class Action Settlements
[REDACTED] Notice Of Filing Revised And Supplemental Settlement Documents
(Attachments: # 1 Exhibit A, # 2 Exhibit B, # 3 Exhibit C, # 4 Exhibit D, # 5 Exhibit E, # 6
Exhibit F, # 7 Exhibit G)(Dermody, Kelly) (Filed on 10/25/2013) (Entered: 10/25/2013)

10/28/2013

535

NOTICE by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel
Stover re 501 MOTION for Preliminary Approval of Class Action Settlements
[REDACTED] Notice of Filing Pursuant to October 21, 2013 Case Management Order
(Attachments: # 1 Exhibit 1, # 2 Exhibit 2, # 3 Exhibit 3)(Cisneros, Lisa) (Filed on
10/28/2013) (Entered: 10/28/2013)

10/28/2013

536

DOCUMENT E-FILED UNDER SEAL re 527 Order on Administrative Motion to File
Under Seal, Attachment D to Plaintiffs' Settlement Agreement with Intuit by Michael Devine,
Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel Stover. (Cisneros, Lisa)
(Filed on 10/28/2013) (Entered: 10/28/2013)

10/28/2013

537

NOTICE by Michael Devine, Mark Fichtner, Siddharth Hariharan, Brandon Marshall, Daniel
Stover re 527 Order on Administrative Motion to File Under Seal, Second Notice of Filing
Pursuant to the Court's October 21, 2013 Case Management Order (Attachments: # 1
Exhibit 1)(Cisneros, Lisa) (Filed on 10/28/2013) (Entered: 10/29/2013)

10/30/2013

538

NOTICE by Intel Corp. re 430 Redacted Document,, OF FILING REVISED REDACTED
INTEL CORP. DOCUMENTS FILED IN RESPONSE TO PLAINTIFFS' ADMINISTRATIVE
MOTION TO FILE UNDER SEAL PLAINTIFFS' MOTION IN SUPPORT OF CLASS
CERTIFICATION AND RELATED DOCUMENTS (Attachments: # 1 Declaration OF
BRADLEY S. PHILLIPS IN SUPPORT, # 2 Exhibit A, # 3 Exhibit B (Part 1 of 10), # 4
Exhibit B (Part 2 of 10), # 5 Exhibit B (Part 3 of 10), # 6 Exhibit B (Part 4 of 10), # 7 Exhibit
B (Part 5 of 10), # 8 Exhibit B (Part 6 of 10), # 9 Exhibit B (Part 7 of 10), # 10 Exhibit B
(Part 8 of 10), # 11 Exhibit B (Part 9 of 10), # 12 Exhibit B (Part 10 of 10))(Phillips,
Bradley) (Filed on 10/30/2013) (Entered: 10/30/2013)

10/30/2013

539

Transcript of Proceedings held on 10-21-13, before Judge Lucy H. Koh. Court
Reporter/Transcriber Lee-Anne Shortridge, Telephone number 408-287-4580 email: [e-mail]. Per General Order No. 59 and Judicial Conference
policy, this transcript may be viewed only at the Clerks Office public terminal or may be
purchased through the Court Reporter/Transcriber until the deadline for the Release of
Transcript Restriction.After that date it may be obtained through PACER. Any Notice of
Intent to Request Redaction, if required, is due no later than 5 business days from date of this
1191

filing. Release of Transcript Restriction set for 1/28/2014. (Related documents(s) 528 ) (las, )
(Filed on 10/30/2013) (Entered: 10/30/2013)
10/30/2013

10/31/2013

540

Order by Hon. Lucy H. Koh granting 501 Motion for Settlement. (Attachments: # 1
Claim Form, # 2 Notice)(lhklc1, COURT STAFF) (Filed on 10/30/2013) (Entered:
10/30/2013)
Set/Reset Hearing re 540 Order on Motion for Settlement Final Approval Hearing re Pixar,
Lucasfilms & Intuit set for 5/1/2014 01:30 PM in Courtroom 8, 4th Floor, San Jose before
Hon. Lucy H. Koh. (mpb, COURT STAFF) (Filed on 10/31/2013) (Entered: 11/01/2013)

PACER Service Center
Transaction Receipt
11/17/2013 20:28:22
PACER Login: lc0019
Description:

Client Code:

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Docket Report Search Criteria: 5:11-cv-02509-LHK

Billable Pages: 30

Cost:

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1192

No. 13-80223
In the

United States Court Of Appeals
For the

Ninth Circuit
__________________________

IN RE HIGH-TECH EMPLOYEE ANTITRUST LITIGATION

_________________________
Petition for permission to appeal
from the United States District Court
Northern District of California
The Honorable Lucy H. Koh, Presiding
Case No. 5:11-2509-LHK
PLAINTIFFS-RESPONDENTS’ CERTIFICATE OF SERVICE
LIEFF CABRASER HEIMANN
& BERNSTEIN, LLP
Kelly M. Dermody
Brendan P. Glackin
Dean M. Harvey
275 Battery Street, 29th Floor
San Francisco, CA 94111-3339
Telephone: [phone]
Facsimile: [phone]

JOSEPH SAVERI LAW FIRM
Joseph R. Saveri
Joshua P. Davis
Lisa J. Leebove
James G. Dallal
505 Montgomery Street, Suite 625
San Francisco, CA 94111
Telephone: [phone]
Facsimile: [phone]

Co-Lead Class Counsel

1141607.1

CERTIFICATE OF SERVICE
I hereby certify that on November 18, 2013, I electronically filed the
documents noted below with the Clerk of the Court for the United States
Court of Appeals for the Ninth Circuit by using the appellate CM/ECF
system. I certify that all particpants in the case are registered CM/ECF users
and that service will be acomplished by the appellate CM/ECF system. The
documents served via the Ninth Circuit’s CM/ECF system include:
1. PLAINTIFFS’ RESPONSE TO PETITION FOR LEAVE TO
APPEAL A CLASS CERTIFICATION ORDER PURSUANT TO
FEDERAL RULE OF CIVIL PROCEDURE 23(f);
2. SUPPLEMENTAL EXCERPTS OF RECORD, VOLS. I-IV
(Public Portions); and
3. PLAINTIFFS-RESPONDENTS’ MOTION TO SEAL
PORTIONS OF THEIR SUPPLEMENTAL EXCERPTS OF
RECORD
In addition, I hereby certify that on November 18, 2013, I served via
electronic mail and overnight delivery through a third party commercial
carrier the following documents to counsel noted in the accompanying
service list:
1. SUPPLEMENTAL EXCERPTS OF RECORD, VOLS. I-VI
(Public and Provisionally Sealed Portions);

1141607.1

-1-

Dated: November 18, 2013

LIEFF CABRASER HEIMANN
& BERNSTEIN, LLP
By:

/s/ Brendan P. Glackin

LIEFF CABRASER HEIMANN
& BERNSTEIN, LLP
Kelly M. Dermody
Brendan P. Glackin
Dean M. Harvey
275 Battery Street, 29th Floor
San Francisco, CA 94111-3339
Telephone: [phone]
Facsimile: 415.956.1008

1141607.1

-2-

SERVICE LIST
Robert A. Mittelstaedt
George Riley
Craig A. Waldman
Michael F. Tubach
David Kiernan
Lisa Chen
JONES DAY
Christina J. Brown
555 California Street, 26th Floor
O'MELVENY & MYERS LLP
San Francisco, CA 94104
Two Embarcadero Center, 28th Floor
[e-mail]
San Francisco, CA 94111
[e-mail]
[e-mail]
[e-mail]
[e-mail]
Tel.: [phone]
[e-mail]
Fax: [phone]
[e-mail]
Tel.: [phone]
Counsel for Defendant Adobe Systems Inc. Fax: [phone]
Counsel for Defendant Apple Inc.
Robert Addy Van Nest
Eugene M. Paige
Daniel Purcell
Justina Sessions
KEKER & VAN NEST
633 Battery Street
San Francisco, CA 94111-1809
[e-mail]
[e-mail]
[e-mail]
[e-mail]
Tel.: [phone]
Fax: [phone]

Gregory P. Stone
Bradley S. Phillips
Gregory M. Sergi
John P. Mittelbach
MUNGER, TOLLES & OLSON LLP
355 South Grand Avenue, 35th Floor
[e-mail]
[e-mail]
[e-mail]
[e-mail]
Los Angeles, California 90071-1560
Telephone: [phone]
Facsimile: [phone]

Lee H. Rubin
Edward D. Johnson
MAYER BROWN LLP
Two Palo Alto Square
3000 El Camino Real, Suite 300
Palo Alto, CA 94306-2112
[e-mail]
[e-mail]
Tel.: [phone]
Fax: [phone]

Counsel for Defendant Intel Corp.

Kristen A. Rowse
MAYER BROWN LLP
350 South Grand Avenue, 25th Floor
Los Angeles, CA 90071-2112
[e-mail]
Tel.: [phone]
Fax: [phone]
Counsel for Defendant Google Inc.

1141607.1

-3-