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Oracle v. Google - Third Damages Report: Arguments and Counter-Motions to Strike |
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Monday, February 27 2012 @ 02:45 PM EST
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It's been months since we have seen the number of filings that were made last Friday, but the squabbling over Oracle's third attempt at an expert damages report from Dr. Cockburn is now fully engaged. Google had its say (Google Moves to Strike Portions of 3rd Oracle Damages Report and Google Takes Exception to Third Damages Report [as text]), and now it is Oracle's turn to respond.
Before heading off through the looking glass, there were a number of other filings that we will address. First, a reminder from the court that the parties are going to be required to disclose the compensation paid to their expert witnesses. (724 [PDF; Text]) It is clear the court wants the jury to be aware these experts have, at a minimum, a financial bias toward their client.
Second, we have the not altogether unexpected order on the issue of patent marking. (725 [PDF; Text]) Since the parties were only able to agree in a single instance on a stipulation with respect to the marking issue, the court is only adopting that single stipulation and throwing all of the so-called contingent stipulations out the window. The parties will have to fight this out at trial. As the court points out, however, this will not result in a longer trial, only a difference in how the time allocated to the parties for the trial will be spent. This will undoubtedly eat into the time available to argue other issues around the patent infringement claims, but then again, given the fact that most of those claims have been found invalid upon reexamination, maybe this will have little impact at all.
In the last of the orders issued by the court on Friday, the court directed the parties to "submit a candid discussion of the impact these rejections will have on the shape of trial," by March 9. The court has also asked whether the trial should be delayed to allow the last of the reexaminations to be completed. This last question may be a moot point as Robert Van Nest, lead counsel for Google, has reminded the court (748 [PDF; Text]) that he will likely be unavailable for trial in the April-June timed frame set aside by the court. That means that the trial will most likely be postponed until the September-December, 2012 timeframe, which should be sufficient time for the USPTO to complete the reexaminations.
In a related matter, Oracle has also asked (732 [PDF; Text]) to be able to file a supplemental expert report with respect to the patent validity issues raised by Google with respect to ’702 and ’205 and information relied upon by the USPTO in its rejection of the claims of these patents during reexamination. (723 [PDF; Text])
Now on to Oracle's response to Google's. Before considering all of the Oracle filings in response to Google's motion to strike portions of the third Oracle damages report, let's review Google's primary objections to the report. Google's objections largely centered on its belief that Dr. Cockburn, Oracle's damages expert, failed to respond to the instructions of the court when the court permitted this third attempt. Google asserts that the primary focus of the third report needed to be the apportionment of valuation between patent claims asserted and those not asserted and between copyright claims asserted and those not asserted. Google believes Dr. Cockburn has failed to address the apportionment issue with his third attempt, and most of its motion to strike (points B-D in the motion) focus on that failure. (See, Google Takes Exception to Third Damages Report [as text]) Apart from that criticism, Google addresses various methodologies which Dr. Cockburn and Dr. Shugan adopted in preparing the third damages report.
Oracle has filed five primary responsive documents, and we include the text of a sixth as exemplary of some of supporting responses provided by Oracle/Sun engineers. The six filings that we provide in text below are:
- Oracle's response to Google's motion to strike portions of the third Cockburn report (737 [PDF; Text])
- Cockburn's declaration in support of Oracle's response (739 [PDF; Text])
- Shugan's declaration in support of Oracle's response (740 [PDF; Text])
- Wong's declaration in support of Oracle's response (745 [PDF; Text])
- Oracle's motion to strike portions of (Google expert) Leonard's supplemental report (criticizing the third Cockburn report) (729 [PDF; Text])
- Oracle's motion to strike portions of (Google expert) Cox's supplemental report (criticizing the third Cockburn report) (734 [PDF; Text])
The two key points of contention are:
- Valuing the copyrights: - According to Google, Cockburn valued the copyrights asserted by estimating the cost to Sun to independently develop a mobile platform. It is hard to understand the relevance of that number as it would have been the costs avoided by Google through access to that code that would better reflect the value. Oracle and Cockburn believe they have used the proper approach; Google disagrees. Oracle believes, if anything, they have overstated the value in Google's favor. But this is really an argument over precision with Google contending Oracle has not achieved the level of precision required by the court and Oracle contending it has.
- Valuing the patents: The differences between the parties' positions on the patent value allocation mirrors that on the copyright side. Google contends Oracle has made no attempt to allocate value on a claim by claim basis with respect to the patent asserted and that Oracle has been imprecise in allocating value among all of the patents that would have been licensed to Google in the 2006 deal. Further, Google argues that the Oracle/Sun engineers engaged to assess the technical merits of the Sun patent portfolio was biased because these are the same engineers called upon to identify the best patents to assert against Google. Oracle, on its part, sees no bias and sees no failure.
Most of the remaining arguments are secondary to these. If the court finds that the apportionment methodologies adopted by Cockburn in this third attempt are plausible (they don't have to be optimal, simply plausible), then I would expect the Google motion to largely fail. If the court agrees with Google that the methodologies are not plausible, then Oracle is toast. I would place the odds in Oracle's favor simply because the court doesn't want to be seen as being too stiff-necked in deciding this matter.
Jump To Comments
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Docket
02/23/2012 - 724 - ORDER
REGARDING EXPERTS' COMPENSATION. Signed by Judge Alsup on February 23,
2012. (whalc1, COURT STAFF) (Filed on 2/23/2012) (Entered: 02/23/2012)
02/24/2012 - 725 - ORDER
REGARDING PATENT MARKING JOINT STATEMENT re 721 Statement filed by
Google Inc., Oracle America, Inc.. Signed by Judge Alsup on February 24,
2012. (whalc1, COURT STAFF) (Filed on 2/24/2012) (Entered: 02/24/2012)
02/24/2012 - 726 - ORDER
REGARDING REEXAMINATIONS re 722 Notice (Other) filed by Google Inc.,
Oracle America, Inc.. Signed by Judge Alsup on February 24, 2012.
(whalc1, COURT STAFF) (Filed on 2/24/2012) (Entered: 02/24/2012)
02/24/2012 - 727 - Administrative Motion to File Under Seal PORTIONS OF MOTION
TO STRIKE PORTIONS OF THE SUPPLEMENTAL EXPERT REPORT OF DR. GREGORY K. LEONARD
filed by Oracle America, Inc.. (Attachments: # 1 Proposed Order)(Holtzman,
Steven) (Filed on 2/24/2012) (Entered: 02/24/2012)
02/24/2012 - 728 - Declaration of ANDREW TEMKIN in Support of 727 Administrative
Motion to File Under Seal PORTIONS OF MOTION TO STRIKE PORTIONS OF THE
SUPPLEMENTAL EXPERT REPORT OF DR. GREGORY K. LEONARD filed byOracle America,
Inc.. (Related document(s) 727 ) (Holtzman, Steven) (Filed on 2/24/2012)
(Entered: 02/24/2012)
02/24/2012 - 729 -
MOTION to Strike PORTIONS OF GREGORY LEONARDS SUPPLEMENTAL REPORT filed by
Oracle America, Inc.. Responses due by 3/2/2012. Replies due by 3/6/2012.
(Holtzman, Steven) (Filed on 2/24/2012) (Entered: 02/24/2012)
02/24/2012 - 730 -
Declaration of IAIN M. COCKBURN in Support of 729 MOTION to Strike PORTIONS OF
GREGORY LEONARDS SUPPLEMENTAL REPORT filed byOracle America, Inc.. (Related
document(s) 729 ) (Holtzman, Steven) (Filed on 2/24/2012) (Entered: 02/24/2012)
02/24/2012 - 731 -
Declaration of BEKO REBLITZ-RICHARDSON in Support of 729 MOTION to Strike
PORTIONS OF GREGORY LEONARDS SUPPLEMENTAL REPORT filed by Oracle America, Inc..
(Attachments: # 1 Exhibit A, # 2 Exhibit B, # 3 Exhibit C, # 4 Exhibit C, # 5 Exhibit E, # 6 Exhibit F, # 7 Exhibit G, # 8 Exhibit H)(Related
document(s) 729 ) (Holtzman, Steven) (Filed on 2/24/2012) (Entered: 02/24/2012)
02/24/2012 - 732 -
RESPONSE to re 723 Letter regarding '702 and '205 invalidity supplementation by
Oracle America, Inc.. (Jacobs, Michael) (Filed on 2/24/2012) (Entered:
02/24/2012)
02/24/2012 - 733 - Administrative Motion to File Under Seal PORTIONS OF ITS
MOTION TO STRIK PORTIONS OF THE SUPPLEMENTAL EXPERT REPORT OF DR. ALAN J. COX
filed by Oracle America, Inc.. (Attachments: # 1 Proposed Order)(Holtzman,
Steven) (Filed on 2/24/2012) (Entered: 02/24/2012)
02/24/2012 - 734 -
MOTION to Strike EXCLUDE PORTIONS OF THE SUPPLEMENTAL EXPERT REPORT OF DR. ALAN
J. COX filed by Oracle America, Inc.. Responses due by 3/2/2012. Replies due by
3/6/2012. (Holtzman, Steven) (Filed on 2/24/2012) (Entered: 02/24/2012)
02/24/2012 - 735 -
Declaration of MEREDITH DEARBORN in Support of 734 MOTION to Strike EXCLUDE
PORTIONS OF THE SUPPLEMENTAL EXPERT REPORT OF DR. ALAN J. COX filed byOracle
America, Inc.. (Attachments: # 1 Exhibit A, # 2 Exhibit B, # 3 Exhibit C)(Related
document(s) 734 ) (Holtzman, Steven) (Filed on 2/24/2012) (Entered: 02/24/2012)
02/24/2012 - 736 - Administrative Motion to File Under Seal PORTIONS OF ITS
OPPOSITION TO GOOGLES DAUBERT MOTION filed by Oracle America, Inc..
(Attachments: # 1 Proposed Order)(Holtzman, Steven) (Filed on 2/24/2012)
(Entered: 02/24/2012)
02/24/2012 - 737 -
RESPONSE (re 718 MOTION to Strike Portions of Third Expert Report by Iain
Cockburn and Expert Report by Steven Shugan; Memorandum of Points and
Authorities in Support Thereof ) filed by Oracle America, Inc.. (Holtzman,
Steven) (Filed on 2/24/2012) (Entered: 02/24/2012)
02/24/2012 - 738 -
Declaration of FRED NORTON in Support of 737 Opposition/Response to Motion,
filed byOracle America, Inc.. (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)(Related
document(s) 737 ) (Holtzman, Steven) (Filed on 2/24/2012) (Entered: 02/24/2012)
02/24/2012 - 739 -
Declaration of IAIN M. COCKBURN in Support of 737 Opposition/Response to Motion,
filed by Oracle America, Inc.. (Attachments: # 1 Exhibit A, # 2 Exhibit B)(Related
document(s) 737 ) (Holtzman, Steven) (Filed on 2/24/2012) (Entered: 02/24/2012)
02/24/2012 - 740 -
Declaration of STEVEN M. SHUGAN in Support of 737 Opposition/Response to Motion,
filed byOracle America, Inc.. (Attachments: # 1 Exhibit A, # 2 Exhibit B)(Related
document(s) 737 ) (Holtzman, Steven) (Filed on 2/24/2012) (Entered: 02/24/2012)
02/24/2012 - 741 -
Declaration of PETER KESSLER in Support of 737 Opposition/Response to Motion,
filed by Oracle America, Inc.. (Related document(s) 737 ) (Holtzman, Steven)
(Filed on 2/24/2012) (Entered: 02/24/2012)
02/24/2012 - 742 -
Declaration of CHRISTOPHER PLUMMER in Support of 737 Opposition/Response to
Motion, filed by Oracle America, Inc.. (Related document(s) 737 ) (Holtzman,
Steven) (Filed on 2/24/2012) (Entered: 02/24/2012)
02/24/2012 - 743 -
Declaration of MARK REINHOLD in Support of 737 Opposition/Response to Motion,
filed by Oracle America, Inc.. (Related document(s) 737 ) (Holtzman, Steven)
(Filed on 2/24/2012) (Entered: 02/24/2012)
02/24/2012 - 744 -
Declaration of JOHN R. ROSE in Support of 737 Opposition/Response to Motion,
filed by Oracle America, Inc.. (Related document(s) 737 ) (Holtzman, Steven)
(Filed on 2/24/2012) (Entered: 02/24/2012)
02/24/2012 - 745 -
Declaration of HINKMOND WONG in Support of 737 Opposition/Response to Motion,
filed by Oracle America, Inc.. (Related document(s) 737 ) (Holtzman, Steven)
(Filed on 2/24/2012) (Entered: 02/24/2012)
02/24/2012 - 746 -
Declaration of GEORGE SIMION in Support of 737 Opposition/Response to Motion,
filed by Oracle America, Inc.. (Related document(s) 737 ) (Holtzman, Steven)
(Filed on 2/24/2012) (Entered: 02/24/2012)
02/24/2012 - 747 - ERRATA re 736 Administrative Motion to File Under Seal
PORTIONS OF ITS OPPOSITION TO GOOGLES DAUBERT MOTION [CORRECTED] PROPOSED ORDER
by Oracle America, Inc.. (Holtzman, Steven) (Filed on 2/24/2012) (Entered:
02/24/2012)
02/24/2012 - 748 -
Letter from Robert A. Van Nest . (Van Nest, Robert) (Filed on 2/24/2012)
(Entered: 02/24/2012)
*******************
Documents
724
IN THE UNITED STATES DISTRICT COURT
FOR THE NORTHERN DISTRICT OF CALIFORNIA
ORACLE AMERICA, INC.,
Plaintiff,
v.
GOOGLE INC.,
Defendant.
No. C 10-03561 WHA
ORDER REGARDING
EXPERTS’ COMPENSATION
At trial, all retained experts must be prepared to testify to the amounts that they and their
firms have received in compensation and expect to receive for work they did up to the end of trial
as well as the billing rate for all personnel involved. Counsel shall instruct the experts to be
prepared on this subject.
Counsel are reminded that they and witnesses must keep the period from April 16 until
late June available for the trial.
IT IS SO ORDERED.
Dated: February 23, 2012.
/s/Williams Alsup
WILLIAM ALSUP
UNITED STATES DISTRICT JUDGE
725
IN THE UNITED STATES DISTRICT COURT
FOR THE NORTHERN DISTRICT OF CALIFORNIA
ORACLE AMERICA, INC.,
Plaintiff,
v.
GOOGLE INC.,
Defendant.
No. C 10-03561 WHA
ORDER REGARDING PATENT
MARKING JOINT STATEMENT
Counsel have filed a supplemental joint statement regarding the Oracle products that
practiced the patents in suit. In this statement, they largely offer points on which they disagree.
That is, while they came close to an agreement, they could not close the deal and agree on the use
that the jury and Court could make of the proposed stipulations.
A stipulation requires full agreement. Until the parties reach a complete agreement on the
evidentiary use of the stipulation, then it is not effective. Both sides are entitled to withhold their
acceptance until they get a full loaf instead of half a loaf. No one will be held to any conditional
stipulation for any purpose until it is fully agreed on as to its use by the Court and jury.
In the Court’s view, the failure to reach this stipulation will require counsel to use their
allotted time to cover what, in most cases, would be easily agreed upon by reasonable counsel.
The conditional stipulations will have no binding effect on anyone.
The foregoing is not true with respect to the ’702 patent and Java OS 1.1 products. This
single unconditional stipulation is hereby binding on the parties.
IT IS SO ORDERED.
Dated: February 24, 2012.
/s/William Alsup
WILLIAM ALSUP
UNITED STATES DISTRICT JUDGE
726
IN THE UNITED STATES DISTRICT COURT
FOR THE NORTHERN DISTRICT OF CALIFORNIA
ORACLE AMERICA, INC.,
Plaintiff,
v.
GOOGLE INC.,
Defendant.
No. C 10-03561 WHA
ORDER REGARDING
REEXAMINATIONS
Based on the recently filed joint statement regarding reexaminations, the parties are
requested to do the following. By NOON ON MARCH 9, the parties shall submit a candid
discussion of the impact these rejections will have on the shape of trial. Please discuss whether in
light of the track record of final rejections, it is best to delay the trial to allow the single remaining
non-final reexamination to run its course.
IT IS SO ORDERED.
Dated: February 24, 2012.
/s/William Alsup
WILLIAM ALSUP
UNITED STATES DISTRICT JUDGE
729
UNITED STATES DISTRICT COURT
NORTHERN DISTRICT OF CALIFORNIA
SAN FRANCISCO DIVISION
ORACLE AMERICA, INC.
Plaintiff,
v.
GOOGLE, INC.
Defendant.
Case No. CV 10-03561 WHA
ORACLE AMERICA, INC.’S MOTION TO
STRIKE PORTIONS OF GREGORY
LEONARD’S SUPPLEMENTAL REPORT
Dept.: Courtroom 8, 19th Floor
Judge: Honorable William H. Alsup
TABLE OF CONTENTS
|
NOTICE OF MOTION AND MOTION TO STRIKE |
iii |
|
MEMORANDUM OF POINTS AND AUTHORITIES |
1 |
I. |
INTRODUCTION |
1 |
II. |
ARGUMENT |
2 |
|
A. |
Dr. Leonard’s Forward Citations Analysis Is Profoundly Flawed And
His Results From That Analysis Are Unreliable And Irrelevant |
2 |
|
B. |
Dr. Leonard Includes Misleading And Irrelevant Calculations Based On
An Accounting Document Prepared For Oracle In 2010 |
5 |
|
C. |
Dr. Leonard’s Claim That Google’s Expected Gains Are Determinative
With Respect To The Amount Of Any Reasonable Royalty Awardable
To Oracle Is Wrong And Improper |
8 |
IV. |
CONCLUSION |
10 |
i
TABLE OF AUTHORITIES
CASES
|
Georgia-Pacific v. U.S. Plywood Corp.,
318 F.Supp. 1116 (S.D.N.Y. 1970) |
8, 9 |
Golight, Inc. v. Wal-Mart Stores, Inc.,
355 F.3d 1327 (Fed. Cir. 2004) |
9 |
Lucent Techs, Inc. v. Gateway, Inc.,
580 F.3d 1301 (Fed. Cir. 2009) |
6 |
Monsanto Co. v. Ralph,
382 F.3d 1374 (Fed. Cir. 2004) |
9 |
Panduit Corp v. Stahlin Bros. Fibre Works, Inc.,
575 F.2d 1152 (6th Cir. 1978) |
9 |
Rite-Hite Corp. v. Kelley Co.,
56 F.3d 1538 (Fed. Cir. 1995) |
9 |
Ticketmaster Corp. v. Tickets.com, Inc.,
No. CV 99-07654 HLH (VBKx), 2003 WL 25781901 (C.D. Cal. Feb. 10, 2003) |
10 |
ii
NOTICE OF MOTION AND MOTION TO STRIKE
PLEASE TAKE NOTICE that Plaintiff Oracle America, Inc. (“Oracle”) hereby moves to
exclude portions of the opinions and testimony of Google, Inc.’s (“Google’s”) patent damages expert
Dr. Gregory K. Leonard. This motion is based on the following memorandum of points and
authorities, the declarations of Beko Reblitz-Richardson and Prof. Iain Cockburn and accompanying
exhibits, the entire record in this matter, and on such evidence as may be presented at any hearing on
this Motion, on a date to be determined by the Court, as well as any other ground the Court deems
just and proper.
DATED: February 24, 2012
BOIES, SCHILLER & FLEXNER LLP
/s/ Steven C. Holtzman
Steven C. Holtzman
Attorneys for Plaintiff
ORACLE AMERICA, INC
iii
MEMORANDUM OF POINTS AND AUTHORITIES
I. INTRODUCTION
Oracle requests that the Court strike three portions of the February 17, 2012 supplemental
report of Google’s patent damages expert, Dr. Gregory Leonard. (See Declaration of Beko Reblitz-
Richardson (“Richardson Decl.”) Exh. A (“Supplemental Leonard Report”).) As explained below,
these portions contain calculations and assertions that are unreliable, irrelevant, and would serve no
purpose other than to mislead and confuse the jury regarding the calculation of damages in this case.
First, Oracle requests that the Court strike Dr. Leonard’s “forward citation” patents analysis.
(Leonard Report at 7.) To calculate the relative value of certain patents owned by Sun, Dr. Leonard
counts the number of times those patents were cited by later-issued patents. Even assuming that
forward citation analysis is a reliable valuation tool, there are two fundamental flaws in Dr. Leonard’s
approach, each of which makes his results unreliable: (1) Dr. Leonard fails to account for the fact
that certain patents (such as the ’104) were re-issued, and fails to include counts for the predecessor
patents; and (2) Dr. Leonard fails to control for the fact that certain patents (such as the ’720) issued
years after the other patents, and therefore naturally would not be cited as frequently as the older
patents. A correction for the first error alone results in the ’104 patent being ranked 1st based on the
total number of citations, not 11th, as Dr. Leonard erroneously claims in his report.
Second, Oracle requests that the Court strike Dr. Leonard’s testimony and calculations based
on a 2010 accounting document prepared for Oracle in connection with its acquisition of Sun.
(Supplemental Leonard Report at 9.) The document on which Dr. Leonard relies reflects an effort to
allocate, purely for bookkeeping purposes, the specific amount that Oracle paid to acquire Sun, not
measure the actual worth of any of the Sun assets, different elements of which possessed varying
characteristics and investment value. The document – and thus Dr. Leonard’s calculations – bears no
relationship to the value of any particular intellectual property to Sun or to Google, let alone the
relative value of the patents-in-suit and the full 2006 Bundle. Dr. Leonard’s calculations are both
misleading and irrelevant, and permitting him to present those calculations to the jury would be
contrary to the Court’s prior rulings in this case, including the Court’s refusal to permit testimony
regarding the amount of the settlement in the earlier Sun v. Microsoft litigation.
1
Third, Oracle requests that the Court strike Dr. Leonard’s suggestion that the reasonable
royalty should be limited to “the value that Google was expecting to receive” from the infringement.
(Supplemental Leonard Report at 2.) It is well-established that a patentee’s expected revenues and
losses should be considered in calculating a reasonable royalty, and that the infringer’s expected
revenue from the infringement does not cap the amount of a reasonable royalty or lost license fee.
Permitting Dr. Leonard to offer contrary testimony would confuse the jury and intrude on the Court’s
role in instructing the jury as to the relevant considerations for calculating a reasonable royalty.
Striking these misleading, inaccurate, and irrelevant portions of Dr. Leonard’s supplemental
report is especially important given the Court’s ruling that “no deposition shall be taken of Google’s
experts, Oracle may not serve a further reply report, and Oracle will not be allowed to present Dr.
Cockburn as a rebuttal witness on the new materials.” (Dkt. 702 at 2.) Opportunities to depose an
expert prior to cross-examination at trial and have another expert rebut those opinions at trial are
important checks on the reliability and relevance of expert testimony. Here, the absence of those
checks creates a greater risk of the jury being misled by Dr. Leonard, with prejudice to Oracle.
II. ARGUMENT
A. Dr. Leonard’s Forward Citations Analysis Is Profoundly Flawed And His Results
From That Analysis Are Unreliable And Irrelevant
In response to Prof. Cockburn’s group and value apportionment analysis, Dr. Leonard offers a
“forward citations” analysis with respect to certain patents included in the 2006 Bundle. (See
Supplemental Leonard Report at p. 7.) The citations analysis consists of counting the number of
times each patent is cited by later patents and using the counts as a proxy for the value of each patent.
Dr. Leonard did not previously refer to forward citations or citation counts in his previous reports or
testimony in this case. Dr. Leonard’s supplemental report contains one paragraph that concerns that
new analysis, which states in full:
[REDACTED]
2
[REDACTED]
(Id. (footnote omitted).)
Prof. Cockburn has worked extensively with patent counts and citations since he wrote his
Ph.D. thesis in the 1980s, and has since conducted substantial research on citations analysis. (See
Richardson Decl. Exh. B (Cockburn Depo. Tr. at 112:10-113:13); Declaration of Iain M. Cockburn in
Support of Oracle America, Inc.’s Motion to Strike Portions of Gregory Leonard’s Supplemental
Report (“Cockburn Leonard Decl.”) at ¶ 3).) As he testified in detail at his deposition, analysis of
forward citations is not a useful way to measure the relative value of the specific patents-in suit in
this case. In particular, Prof. Cockburn testified that
If you count those up in circumstances where it’s meaningful to do so and make
adjustments where necessary, you will find often that that measure will correlate with
other things. . . .
I considered it [citation analysis]. Considered it quite carefully and did not do it for a
couple of reasons. One is a purely practical one, which is most of the patents in this
portfolio are relatively young and that means that not enough patents have been
issued subsequently to be able to have the possibility of citing these patents,
especially once you take into account lags between application and issuance and so
forth.
So a recent cohort of patents is going to be one which is very difficult to assess using
citation analysis just because, if you like, the signal-to-noise ratio buried in the
number of citations that a patent attracts is not favorable. So that’s a practical
problem.
More generally there’s the question of, are these citation types of measures
particularly useful at discriminating at the level of individual patents? Where they
have been shown to be useful, generally speaking, is in the context of statistical
studies with very large sample sizes where much of the noise, if you like, can come
out in the wash or you have sufficient numbers of observations and statistical power
to use the kinds of methodologies which will apply appropriate adjustments so that
you can meaningfully compare one patent to another.
3
Those are the circumstances under which I think citation analysis stands a chance of
working reliably. They don’t apply here.
(Richardson Decl. Exh. B (Cockburn Depo. Tr. at 112:21-114:13).) Dr. Leonard’s report does not
state that he has ever conducted a citation count analysis before, nor does it contain any discussion of
the methodological challenges specifically identified by Prof. Cockburn. But even if a forward
citations analysis were appropriate in this case – and it is not for the reasons identified by Prof.
Cockburn and academic studies1 – Dr. Leonard’s attempt at such an analysis in this case is
fundamentally flawed and misleading.
Dr. Leonard does not disclose any exhibit or calculations that actually show his forward
citation counts or the methods he uses to reach those numbers. However, the backup data that
Google produced following submission of the report reveals that Dr. Leonard’s forward citations
analysis suffers from at least two fundamental flaws, both of which render Dr. Leonard’s analysis and
calculations unreliable, misleading, and inadmissible under the Daubert standard. The backup
spreadsheet with his citation counts is attached as Exhibit C to the Richardson Declaration.
First, Dr. Leonard failed to account for the fact that certain patents were re-issued. For
example, the predecessor to the ’104 is USRE36204E1 (applied for in November 1996 and issued in
April 1999), which has 1 citation. The predecessor to USRE36204E1 is US5367685 (applied for in
December 1992 and issued in November 1994), which has 73 citations. (Cockburn Leonard Decl. ¶
5.) Dr. Leonard failed to attribute the ’204’s one citation to the ’104 and failed to count any of the 73
citations to the ’685 at all. Instead, Dr. Leonard counts only three citations for the ’104 patent. (See
Richardson Decl. Exh. C.) In fact, the ’104 patent and its predecessors have been cited 77 times in
all. (Cockburn Decl. ¶ 6.) Correcting Dr. Leonard’s elementary but substantial counting errors for
re-issued patents changes the rank of the ’104 patent from 11th under Dr. Leonard’s approach to 1st,
___________________________________________
1 See, e.g., Bhaven Sampat & Arvids Ziedonis, “Patent Citations and the Economic Value of
Patents,” Handbook of Quantitative Science and Technology Research 2005, Part 2, p. 295 (“Our
primary finding is that whilst patent citations are good predictors of whether a university patent is
licensed, they are not good predictors of the license revenues earned by technologies conditional
upon its licensing.”).
4
with more than double the number of citations than the next patent. (Id.) The significant change in
ranking among the patents highlights the significance of Dr. Leonard’s error.
Second, in counting forward citations for the top 22 patents in Dr. Cockburn’s analysis, all of
which were issued (or re-issued) between April 27, 1999 and February 1, 2011 (see Richardson Exh.
C), Dr. Leonard treats all citations as equal, disregarding the fact that some patents (such as the ’720)
were issued many years after other patents in the group.
Citations of course take place over time, so newer patents will tend to have been cited fewer
times than older patents, irrespective of value. (See Cockburn Decl. ¶ 7.) In other words, absolute
citation counts are partly (and largely) a function of age, not just a function of value. Dr. Leonard
makes no effort to control for the obvious effect of time. (See id.) As a result, his analysis
systematically understates the value of newer patents. This is particularly relevant to the assessment
of the citations for the patents-in-suit, given that the ’720 was issued on September 16, 2008, making
it the second most recent patent in the list of 22, and that the ’205 patent was issued on June 16, 2005,
also relatively recently. (Id. ¶¶ 9-11.)
The problem with ignoring the issue dates of the patents is obvious in Dr. Leonard’s results:
all of the top six patents in Dr. Leonard’s ranking were issued in 2004 or earlier (each receiving over
10 citations), while the three bottom spots in the ranking are occupied by patents issued in 2008 or
later (each receiving zero citations). Dr. Leonard includes a second ranking, but that second ranking
also fails to deal with this issue. (See id. ¶ 8.)
Dr. Leonard’s failure to account in any way for the more than ten-year span covering the
issuance of these 22 patents is a serious methodological flaw that has a substantial impact on the
outcome of the ranking. (Id. ¶¶ 7-12.) Permitting Dr. Leonard to testify about this flawed citation
analysis, particularly without rebuttal testimony by Prof. Cockburn, would mislead and confuse the
jury regarding the relative importance of the patents-in-suit.
B. Dr. Leonard Includes Misleading And Irrelevant Calculations Based On An
Accounting Document Prepared For Oracle In 2010
In his new report, Dr. Leonard improperly relies on a single document, [REDACTED]
5
[REDACTED] It is not a comparable license or a valuation of comparable
intellectual property, and cannot be used as an indicator of the value of the patents and copyrights
that Google infringed. See Lucent Techs, Inc. v. Gateway, Inc., 580 F.3d 1301, 1325-32 (Fed. Cir.
2009).
Dr. Leonard contends that calculations based on the 2010 accounting document show that
Prof. Cockburn’s damages calculations are “unreliable.” (Supplemental Leonard Report at p. 9.) The
full text of the relevant paragraph is:
[REDACTED]
(Id. (emphasis in original, footnotes omitted).)
Dr. Leonard’s purported justification for invoking the $505 million to cap Oracle’s damages
is mere pretext. Dr. Leonard states that he is “[u]sing Dr. Cockburn’s own methodology” for these
calculations. (Id.) But Prof. Cockburn’s methodology does not rely on any accounting valuation of
Oracle’s 2010 acquisition of Sun at all.
Dr. Leonard’s calculations are [REDACTED]
6
[REDACTED]
[REDACTED]
Dr. Leonard not only misconstrues the one document he relies upon; he shuts his eyes to the
substantial evidence that points in the opposite direction. Sun generated hundreds of millions of
__________________________________
2 The full document is 389 pages long, but Dr. Leonard cited only these three pages in footnote 9 of
his report. Oracle has submitted only those three pages with this motion, to try to limit the number of
pages submitted to the Court in connection with these Daubert motions, but will of course supply a
full copy of the document if the Court requests.
7
dollars in revenue each year by licensing its Java technology to third parties. When Oracle
announced that it would acquire Sun for $7.4 billion, Oracle CEO Larry Ellison stated publicly that
“Java is the single most important software asset we have ever acquired.” (Richardson Decl. Exh. F.) [REDACTED] Dr. Leonard ignores all of that evidence.
Dr. Leonard has plucked an irrelevant number from an irrelevant document that was prepared
for an irrelevant purpose almost five years after the hypothetical negotiation. Without reference to
any of the specifics of the hypothetical negotiation or any Georgia Pacific factor, he opines that a
small fraction of that irrelevant number is the maximum reasonable royalty in this case. That
“analysis” has no basis in either law or fact, is not a relevant comparable or benchmark, and is
nothing more than an attempt to prejudice the jury by picking out a low number. Permitting Dr.
Leonard to testify to the jury about these calculations would mislead the jury. Consistent with this
Court’s previous order regarding the dollar figure of the Sun v. Microsoft settlement, it should be
stricken.
C. Dr. Leonard’s Claim That Google’s Expected Gains Are Determinative With
Respect To The Amount Of Any Reasonable Royalty Awardable To Oracle Is
Wrong And Improper
Dr. Leonard opines in his supplemental report:
[REDACTED]
(Supplemental Leonard Report at p. 2 (emphasis added).)
8
The statement that “It is the value that Google was expecting to receive that matters for the
reasonable royalty analysis” is an incorrect statement of the law of patent damages. For example, in
Rite-Hite Corp. v. Kelley Co., 56 F.3d 1538 (Fed. Cir. 1995), the court ruled:
The district court here conducted the hypothetical negotiation analysis. It determined
that Rite-Hite would have been willing to grant a competitor a license to use the ’847
invention only if it received a royalty of no less than one-half of the per unit profits
that it was foregoing. In so determining, the court considered that the ’847 patent was
a “pioneer” patent with manifest commercial success; that Rite-Hite had consistently
followed a policy of exploiting its own patents, rather than licensing to competitors;
and that Rite-Hite would have had to forego a large profit by granting a license to
Kelley because Kelley was a strong competitor and Rite-Hite anticipated being able to
sell a large number of restraints and related products. It was thus not unreasonable for
the district court to find that an unwilling patentee would only license for one-half its
expected lost profits and that such an amount was a reasonable royalty. The fact that
the award was not based on the infringer’s profits did not make it an unreasonable
award.
Id. at 1554-55 (emphasis added and citations omitted); see also Golight, Inc. v. Wal-Mart Stores, Inc.,
355 F.3d 1327, 1338 (Fed. Cir. 2004) (“There is no rule that a royalty be no higher than the
infringer’s net profit margin.”) (citations omitted); Monsanto Co. v. Ralph, 382 F.3d 1374, 1384 (Fed.
Cir. 2004) (“[A]lthough an infringer’s anticipated profit from use of the patented invention is among
the factors to be considered in determining a reasonable royalty, the law does not require that an
infringer be permitted to make a profit.”) (citing Georgia-Pacific v. U.S. Plywood Corp., 318 F.Supp.
1116, 1120 (S.D.N.Y. 1970)) (internal punctuation omitted).
Here, the Court already ruled that “lost convoyed sales also remain relevant to a reasonable
royalty even where the patent owner’s proof is insufficient to show lost profit.” (Dkt. 685 at 6.)
Other courts have confirmed that expected sales by the licensor should be considered. See also
Georgia Pacific, 318 F. Supp. at 1121 (factors include “the anticipated amount of profits that the
prospective licensor reasonably thinks he would lose as a result of licensing the patent as compared to
the anticipated royalty income”); Panduit Corp v. Stahlin Bros. Fibre Works, Inc., 575 F.2d 1152,
1163 (6th Cir. 1978) (“expectant loss is an element to be considered in retroactively determining a
reasonable royalty”). Permitting Dr. Leonard to testify to the contrary would not only confuse the
jury but also potentially create a conflict with the Court’s jury instructions. Such testimony is
impermissible. See, e.g., Ticketmaster Corp. v. Tickets.com, Inc., No. CV 99-07654 HLH (VBKx),
9
2003 WL 25781901, at *1 (C.D. Cal. Feb. 10, 2003) (“the sole source of the law for the jury is the
judge, not the expert witness”).
The Court should strike the paragraph quoted above from Dr. Leonard’s supplemental report
and preclude any testimony or argument that only “the value that Google was expecting to receive”
matters for the reasonable royalty analysis.
III. CONCLUSION
For these reasons, Oracle respectfully requests that the Court preclude Dr. Leonard from
providing any testimony regarding forward citation analysis, the 2010 accounting document, or any
purported limitation of a reasonable royalty or actual damages to “the value that Google was
expecting to receive.” The corresponding portions of Dr. Leonard’s supplemental report should be
stricken.
Dated: February 24, 2012
BOIES, SCHILLER & FLEXNER LLP
By: /s/ Steven C. Holtzman
Steven C. Holtzman
Attorneys for Plaintiff
ORACLE AMERICA, INC.
10
732
[Morrison Foerster letterhead]
February 24, 2012
The Honorable William H. Alsup
United States District Court, Northern District of California
450 Golden Gate Avenue
San Francisco, California 94102
Re: Oracle America, Inc. v. Google Inc., No. 3:10-CV-03561-WHA (N.D. Cal.)
Dear Judge Alsup:
I write in response to Google’s February 22 précis letter requesting leave for the parties to
update their expert reports on the ’702 and ’205 patent validity issues to reflect the recent
PTO actions.
Although Oracle maintains its objection to introducing evidence from an incomplete
reexamination as being more prejudicial than probative under FRE 403, Oracle recognizes
that the Court’s decision on Oracle’s Motion in Limine No. 1 is law of the case, and that the
Court permitted supplementation with respect to the ’520, ’720, and ’476 patents. (ECF No.
676, at 5.)
If the Court were to grant Google’s current request, Oracle requests leave to respond with its
own supplemental expert reports to address any arguments Google newly advances in its
supplemental expert reports.
Respectfully submitted,
/s/ Michael A. Jacobs
Michael A. Jacobs
734
UNITED STATES DISTRICT COURT
NORTHERN DISTRICT OF CALIFORNIA
SAN FRANCISCO DIVISION
ORACLE AMERICA, INC.
Plaintiff,
v.
GOOGLE, INC.
Defendant.
Case No. CV 10-03561 WHA
ORACLE AMERICA, INC.’S NOTICE OF
MOTION AND MOTION TO EXCLUDE
PORTIONS OF THE SUPPLEMENTAL
EXPERT REPORT OF DR. ALAN J. COX
Dept.: Courtroom 8, 19th Floor
Judge: Honorable William H. Alsup
TABLE OF CONTENTS
I. |
INTRODUCTION |
1 |
II. |
COPYRIGHT DAMAGES STANDARD |
2 |
III. |
BACKGROUND |
3 |
|
A. |
Prof. Cockburn’s Copyright Damages Calculations |
3 |
|
B. |
Dr. Cox’s Copyright Damages Calculations |
4 |
IV. |
ARGUMENT |
6 |
|
A. |
Cox’s Changes To His Infringer’s Profits And Lost Profits Calculation
Are Impermissible Under The Court’s Order |
6 |
|
B. |
Dr. Cox’s Application of Prof. Cockburn’s Lowest Apportionment
Percentage To Calculate Infringer’s Profits Does Not Rest On A
Reliable Foundation And Should Be Striken |
8 |
|
C. |
Cox’s Alternative Calculation Of Infringer’s Profits Based On The
Parties’ Revenue Sharing Discussion Should Be Stricken |
10 |
|
D. |
Cox’s Revisions To Lost Profits Do Not Rest On A Reliable
Foundation And Should Be Stricken |
12 |
IV. |
CONCLUSION |
13 |
i
TABLE OF AUTHORITIES
CASES |
On Davis v. The Gap, Inc.,
246 F.3d 152 (2d Cir. 2001) |
12 |
Polar Bear Prods., Inc. v. Timex Corp.,
384 F.3d 700 (9th Cir. 2004) |
2, 3, 10, 11 |
Three Boys Music Corp. v. Bolton,
212 F.3d 477 (9th Cir. 2000) |
3 |
STATUTES |
|
17 U.S.C. § 504(b)17 U.S.C. § 504(b) |
2, 3, 8, 12 |
ii
NOTICE OF MOTION AND MOTION TO STRIKE
PLEASE TAKE NOTICE that Plaintiff Oracle America, Inc. (“Oracle”) hereby moves to
exclude portions of the opinions and testimony of Google, Inc.’s (“Google’s”) copyright damages
expert Dr. Alan Cox. This motion is based on the following memorandum of points and authorities,
the Declaration of Meredith Dearborn and accompanying exhibits, the entire record in this matter,
and on such evidence as may be presented at any hearing on this Motion, on a date to be determined
by the Court, as well as any other ground the Court deems just and proper.
DATED: February 24, 2012
BOIES, SCHILLER & FLEXNER LLP
________________________________
Steven C. Holtzman
Attorneys for Plaintiff
ORACLE AMERICA, INC
1
MEMORANDUM OF POINTS AND AUTHORITIES
I. INTRODUCTION
In October 2011, Google’s copyright damages expert, Dr. Alan Cox, calculated infringer’s
profits at [REDACTED] and lost profits at [REDACTED] In a supplemental report served on February 17, 2012, Dr. Cox [REDACTED] and added an entirely new infringer's profits analysis that estimates recoverable profits at [REDACTED]. With his new report, Dr. Cox has thus [REDACTED]
These revised and new calculations should be stricken.
First, Dr. Cox’s revised and new infringer’s profits and lost profits calculations are
impermissible under the Court’s prior orders. On January 9, 2012, the Court struck Prof. Cockburn’s
reasonable royalty and lost license fee calculations, but did not strike his infringer’s profits or lost
profits calculations. (Dkt. 685 at 9.) On January 20, 2012, the Court entered an order permitting
Prof. Cockburn to revise the stricken calculations and update his discussion of the econometric and
conjoint studies. (Dkt. 702 at 2–3.) The Court permitted Google to serve revised damages reports in
response, but stated: “Only revisions directly responsive to new material by Dr. Cockburn will be
allowed.” (Id.) Prof. Cockburn did not revise his opinions as to infringer’s profits, lost profits, or the
conjoint analysis. Dr. Cox’s revisions to his infringer’s profits and lost profits calculations, and his
entirely new infringer’s profits calculation, are all beyond the scope of what the Court permitted, and
therefore should be stricken.
Second, Dr. Cox’s new calculations should be stricken because they are fundamentally
flawed. For infringer’s profits, the copyright statute requires Dr. Cox to measure the portion of
Android’s real world profits that are attributable to factors other than the copyrighted APIs. Dr. Cox
does not perform that analysis. He does not measure the contributions of the other elements of
Android at all. Instead, he simply assumes that 5.1% of Android’s profits would be attributable to
Google’s copyright infringement. This number comes from the lowest bound of Prof. Cockburn’s
hypothetical license fee determination, in which Prof. Cockburn determined that at least 5.1% of the
value of the 2006 license that Sun offered Google was attributable to the copyrights in suit. Dr. Cox
1
applies the same 5.1% figure to reduce Oracle’s lost profits damages. But the Court has previously
held that there is no relationship between the value of the Bundle and the value of actual Android
profits (or Oracle’s actual lost profits) attributable to the infringed copyrights. (See Dkt. 685 at 7–9.)
Indeed, Google previously accused Prof. Cockburn of mixing apples and oranges by using data
showing the actual value to Android from 2011 to apportion the value of the 2006 Bundle. Dr. Cox
has now done the same thing, only in reverse: by applying a 2006 apportionment to profits and losses
through 2011, he has compared oranges to apples. His analysis must be stricken.
Dr. Cox’s unauthorized and illogical revisions are particularly pernicious given that the Court
has indicated that it will not permit Oracle to depose Dr. Cox about his new opinions or permit Prof.
Cockburn to rebut them at trial. (Dkt. 702 at 2.) Dr. Cox’s opinions that violate the Court’s order
will be highly prejudicial to Oracle and particularly misleading to the jury.
Oracle respectfully requests that the Court strike Sections VIII.B and VIII.D from Dr. Cox’s
supplemental report, which contain Dr. Cox’s improper and flawed revisions to his infringer’s profits
and lost-profits calculations.
II. COPYRIGHT DAMAGES STANDARD
The copyright damages statute provides, in full:
(b) Actual Damages and Profits. — The copyright owner is entitled to recover the actual
damages suffered by him or her as a result of the infringement, and any profits of the infringer
that are attributable to the infringement and are not taken into account in computing the actual
damages. In establishing the infringer’s profits, the copyright owner is required to present proof
only of the infringer’s gross revenue, and the infringer is required to prove his or her deductible
expenses and the elements of profit attributable to factors other than the copyrighted work.
17 U.S.C. § 504(b).
“Congress explicitly provides for two distinct monetary remedies—actual damages and
recovery of wrongful profits. These remedies are two sides of the damages coin—the copyright
holder’s losses and the infringer’s gains.” Polar Bear Prods., Inc. v. Timex Corp., 384 F.3d 700,
707–08 (9th Cir. 2004). “Actual damages are usually determined by the loss in the fair market value
of the copyright, measured by the profits lost due to the infringement or by the value of the use of the
copyrighted work to the infringer.” Id. (quotation marks and citations omitted).
2
This Court recognized this important distinction between actual damages and infringer’s
profits in its November 2011 ruling on Oracle’s Daubert motion concerning the original reports of
Google’s damages experts. In that ruling, the Court held that non-infringing alternatives are
irrelevant to recovery of wrongful profits. (Dkt. 632 at 7.) The Court wrote:
Not acceptable, however, is allowing the existence of non-infringing alternatives to reduce
recovery of wrongful profits. This is a distinct remedy for the purpose of disgorgement.
Non-infringing alternatives have nothing to do with this. The motion to strike portions of Dr.
Cox’s report that opined that non-infringing alternatives would provide a basis for calculating
wrongful profit is GRANTED.
(Id. (emphasis in original).)
The infringer’s profits remedy eliminates incentives for would-be infringers, and prevents
“the infringer from unfairly benefitting from a wrongful act.” Polar Bear, 384 F.3d at 708 (quotation
marks and citation omitted). Pursuant to this policy, Congress expressly provided that apportionment
of infringer’s profits is the defendant’s burden. 17 U.S.C. § 504(b). Oracle “is required to present
proof only of the infringer’s gross revenue,” id., and then Google “bears the burden of apportioning
the profits that were not the result of infringement.” Polar Bear, 384 F.3d at 711. Where there is
“imprecision in the computation of expenses, a court should err on the side of guaranteeing the
plaintiff a full recovery.” Three Boys Music Corp. v. Bolton, 212 F.3d 477, 487 (9th Cir. 2000)
(quotation marks and citation omitted).
III. BACKGROUND
A. Prof. Cockburn’s Copyright Damages Calculations
In his September 2011 report, Prof. Cockburn calculated Google’s gross Android revenue
attributable to its infringement to be [REDACTED] through the end of 2011. This calculation was
based on his review of evidence demonstrating the importance of the copyrighted APIs to attracting
Java developers and the importance of those developers to Android’s success. Any further
apportionment of that [REDACTED] was and is Google’s burden under the Copyright Act.
Prof. Cockburn also calculated lost profits in two ways. [REDACTED]
3
[REDACTED] He calculated that Oracle’s combined lost profits from these
two sources are $136.2 million.
In his February 2012 report, Prof. Cockburn did not revise either the lost profits or the
infringer’s profits calculation. (See Cockburn Report ¶¶ 621–49, 650, 671–94, Ex. 20–22.)1
This
was consistent with the Court’s orders. In its previous Daubert order striking portions of Prof.
Cockburn’s damages analysis, the Court specifically noted that “calculations of copyright unjust
enrichment and copyright lost profits are not stricken.” (Dkt. 685 at 13.) The Court permitted Prof.
Cockburn only to revise “only those items stricken by the recent order” as well as the conjoint and
econometrics analyses. (Dkt. 702 at 2–3.) Neither Prof. Cockburn nor Prof. Shugan revised any
portion of the conjoint analysis; instead, Prof. Cockburn now uses that analysis in a manner that is
consistent with the Court’s orders. (See Cockburn Report ¶¶ 470–79 (discussing conjoint analysis);
id. ¶¶ 416–20 (describing current use of the conjoint analysis); id. Exh. 5.)
B. Dr. Cox’s Copyright Damages Calculations
On October 3, 2011, Google served a copyright damages expert report signed by Dr. Cox. On
October 24, 2011, Google served an errata list with a revised Dr. Cox report. In that revised report,
Dr. Cox responded to Prof. Cockburn’s infringer’s profits calculation and opined that [REDACTED]
in Android revenue is profit attributable to the copyrights-in-suit.
(Declaration of Meredith Dearborn (“Dearborn Decl.”) Ex. A (10/21/2011 Cox Report) at pp. 38–42
and Ex. 3a.) Dr. Cox also included alternative calculations in which he opined that [REDACTED]
(Id. Ex. 2a, 2b.) Dr.
Cox also opined that [REDACTED] (Id. pp. 58.)
Dr. Cox has never offered an affirmative infringer’s profits analysis. In his October 2011
report, Dr. Cox relied—“for the sake of argument” only, despite the fact that Google has the
affirmative burden of proving apportionment—on the conjoint analysis conducted by Dr. Shugan.
(10/21/2011 Cox Report at p. 38, Ex. 3a).) Dr. Shugan’s conjoint survey showed that consumers
__________________________________
1 All references to the Cockburn Report refer to the February 9, 2012 revision to the February 3, 2012
report, which was submitted to the Court.
4
place significant value on the number of applications available, and, if fewer applications were
available, Android’s market share would have declined by at least 8% to 19%, depending on certain
assumptions about the but-for world. (See Cockburn Report ¶ 653.) Ignoring the fact that Dr.
Shugan’s measurements represented a floor, not a ceiling, and also ignoring the fact that Dr. Shugan
measured the incremental benefit of Google’s copyright infringement over the next best alternative,
not the total benefit Google derived from its infringement, Dr. Cox nonetheless borrowed that figure, [REDACTED]
and applied that adjusted figure to his calculation of Google’s Android revenues.
Dr. Cox did not perform any independent analysis that would enable him to apportion Google’s
infringer’s profits.
On February 17, 2012, in “response” to Prof. Cockburn’s February 3 report, Google served a
supplemental damages report by Dr. Cox that significantly changes his analysis as to both infringer’s
profits and lost profits. (Dearborn Decl. Ex. B (Supplemental Expert Report of Dr. Alan J. Cox)
(“Supp. Cox Report”)) ¶¶ 29–44, Ex. 2a, 2b, 4a.)
On infringer’s profits, Dr. Cox substantially reduces the figure that was included in his
October report. He includes two alternative calculations.
First, Dr. Cox, again “for the sake of argument,” uses the lower end of the range of Prof.
Cockburn’s “group and value” copyright apportionment percentage (5.1%) and applies that
percentage to all of Google’s Android revenues, which ultimately yields infringer’s profits of
[REDACTED]” [sic]. (Id. ¶¶ 31, 33.)
Second, Dr. Cox treats Sun’s 2006 proposal to license its intellectual property to Google in
exchange for a 10% revenue share (plus a license fee) as establishing that no more than 10% of real
world Android revenues could be attributable to Sun intellectual property. (Id. ¶¶ 37–39.) Dr. Cox
assumes that only 5.1% of that 10% (or 0.51% of the total) is attributable to the asserted copyrights.
(Id. ¶¶ 39–41.) Thus, he multiplies his estimate of Android’s revenues by 0.51%, and arrives at an
amount of [REDACTED]. (Id. ¶¶ 37–42.) In this alternate approach, Dr. Cox artificially limits the
value of the transaction to the 10% revenue share, disregarding the facts that the 2006 proposal he
relies on (a) would have provided Sun an additional $60 million in license fees, (b) included a grant
to Sun of rights to Google intellectual property, (c) would have required Google to promote the Sun
5
brand for the mobility market, and (d) would have allowed Sun to earn hundreds of millions of
dollars from convoyed sales.
Although both of Dr. Cox’s calculations rely on Prof. Cockburn’s “group and value” lower
bound copyright apportionment percentage, Dr. Cox concedes that percentage expressly applies only
to the 2006 Bundle—not real world Android. (See id. ¶ 36.)
Dr. Cox also revises his lost profits figures, applying the same lower-bound “group and
value” 5.1% figure with no explanation as to why it would be appropriate to use that number. (Id. ¶
44, Ex. 4a.) His new opinion would award [REDACTED]
a substantial reduction from his previous opinion.
IV. ARGUMENT
A. Cox’s Changes To His Infringer’s Profits And Lost Profits Calculation
Are Impermissible Under The Court’s Order
In its order permitting Prof. Cockburn to file a third report, the Court limited the scope of any
reports filed by Google’s experts: “Only revisions directly responsive to new material by Dr.
Cockburn will be allowed.” (Dkt. 702 at 2.) That limitation was important because the Court was
seeking to “streamline” this process. (Id.) Further, the Court’s order limited Oracle’s ability to
challenge any revised reports filed by Google’s experts, stating “no deposition shall be taken of
Google’s experts, Oracle may not serve a further reply report, and Oracle will not be allowed to
present Dr. Cockburn as a rebuttal witness on the new material.” (Id.) These limitations made it
critically important that Google’s experts not stray beyond the scope of Prof. Cockburn’s revised
report, because Oracle would not have a full opportunity to test any new opinions or revised
calculations.
Dr. Cox’s supplemental report violates the Court’s order and prejudices Oracle. The Court
did not permit Prof. Cockburn to make any changes to his infringer’s profits or lost profits
calculations, and Prof. Cockburn did not make any changes to those calculations. (See Dkt. 685 at
12–13; Dkt. 702 at 2–3.) Neither Prof. Cockburn nor Prof. Shugan revised the conjoint analysis.
Nonetheless, Dr. Cox’s supplemental report includes significant changes to his previous infringer’s
profits and lost profits calculations. As described above, those changes [REDACTED]
6
[REDACTED]
Dr. Cox’s arguments for why it was appropriate to make these changes are meritless. Dr. Cox
seeks to bypass the Court’s order by stating: [REDACTED]
(Dearborn Dec. Ex. B (Supp. Cox Report) ¶ 31).) This is nonsense.
Prof. Cockburn revised his apportionment analysis only for the purpose of calculating a reasonable
royalty and lost license fee, and only as to the portion of the 2006 license bundle that Sun offered
Google properly attributable to the intellectual property in suit. Prof. Cockburn offered no
affirmative opinion at all as to the percentage of Android’s profits attributable to the copyrighted
APIs in suit, other than to opine that the copyrighted APIs are a material and indeed very significant
element in Android’s success. Any more is Google’s burden. As discussed below, conflating the
2006 license bundle and Android’s actual profits is precisely what the Court has previously rejected.
Prof. Cockburn does not have a “copyright apportionment analysis” in the sense in which Dr. Cox is
attempting to use that term, and he made no revision to any infringer’s profits analysis that warrants
Dr. Cox’s changes.
Dr. Cox also asserts that [REDACTED]
(Dearborn Decl. Ex. B (Supp. Cox Report) ¶ 36; see also id. ¶ 44 (claiming that revisions to lost
profits are appropriate because [REDACTED]
This is both false and inconsistent with what Google itself repeatedly argues in its Daubert motion—
filed precisely the same day—regarding Prof. Cockburn’s third report. (See Dkt. 720 at 3, 14–15
(arguing that Prof. Cockburn “relies” on the conjoint analysis in multiple respects).) Prof. Cockburn
continues to use the conjoint analysis. (See Cockburn Report ¶¶ 411–12, 416–20, 459, Exs. 5–11,
35–36; see also Dearborn Decl. Ex. C (Excerpts from the 2/10/12 Deposition of Iain M. Cockburn) at
30:15–23, 31:1–32:21.) Prof. Cockburn did not “back away” from the conjoint analysis at all, much
less in any way that justifies Dr. Cox’s modifications to his infringer’s profits or lost profits
calculations. Dr. Shugan’s conjoint analysis has not been changed in any respect at all.
7
But even if Prof. Cockburn completely abandoned conjoint analysis as a basis for his
opinions—or if Google succeeded in its efforts to exclude —that would not justify Dr. Cox’s belated
introduction of a completely new method of measuring infringer’s profits. It has always been
Google’s burden to apportion infringer’s profits. Google decided it would meet that burden by
relying on evidence that it simultaneously argues should never be admitted, and if admitted, should
never be believed by a jury. Now Google faces the consequence of its own cynical tactics, but it
cannot blame that consequence on Prof. Cockburn.
Dr. Cox also offers a “different way” to calculate infringer’s profits in his supplemental
report, which never appeared in his prior report and which is in no way “directly responsive to new
material by Dr. Cockburn.” (Dkt. 702 at 2.) Dr. Cox begins from the license the parties were
actually negotiating in 2006, and he then suggests that the revenue share portion of that license (10%)
was an “implicit proposal” that 90% of revenues would be “available to Google to recover all its
costs and cover any profit attributable to factors other than Sun’s IP.” (Dearborn Decl. Ex. B (Supp.
Cox Report) ¶ 37–39). The only step Prof. Cox takes that is borrowed from Prof. Cockburn’s new
report is to apply the 5.1% lower-bound “group and value” apportionment figure to the 10% of
revenues Sun would have earned. (Id. ¶ 41.) With or without the use of that apportionment figure,
this is an entirely new framework by which Dr. Cox purports to calculate infringer’s profits. It is
fatally flawed, as described below, but it is also a naked attempt to shoehorn a wholly new analysis
into what should have been a narrowly cabined rebuttal report. Like his “revised” infringer’s profits
analysis, this wholly new “different” approach should be stricken as procedurally improper,
particularly in light of the fact that Oracle may not depose Dr. Cox or rebut this wholly new opinion
at trial.
B. Dr. Cox’s Application of Prof. Cockburn’s Lowest Apportionment
Percentage To Calculate Infringer’s Profits Does Not Rest On A Reliable
Foundation And Should Be Stricken
Google’s burden for apportioning infringer’s profits is straightforward: it must prove “the
elements of profit attributable to factors other than the copyrighted work.” 17 U.S.C. § 504(b). Dr.
Cox did not try to do that. Instead, he assumed that the percentage of Android’s real world profits
8
attributable to Google’s infringement of copyrighted API specifications must be the same as the
percentage of the 2006 Bundle attributable to copyrighted API specifications.
When the Court struck the apportionment analysis in Prof. Cockburn’s second damages
report, it held that Prof. Cockburn erroneously “failed to account for [the] disconnect” between the
universe of know-how included in Sun’s 2006 offer of a license and the universe of know-how
included in Android during 2008–2011. (Dkt. 685 at 8.) The Court concluded that Prof. Cockburn’s
apportionment of the 2006 Bundle had an “apples-and-oranges problem” because the 2006 Bundle
“does not bear any relationship” to 2008–11 Android revenues, “for all the record shows.” (Id.)
Dr. Cox’s revised calculations are impermissible for the same reasons articulated in the
Court’s order striking Prof. Cockburn’s second report. Dr. Cox borrows the lowest possible bound of
the apportionment percentage from Prof. Cockburn’s analysis of the 2006 license bundle—5.1%, out
of a range of 5.1% to 16.4% (see Cockburn Report ¶ 420)—and applies that apportionment
percentage to actual Android revenues through 2011 to reduce his infringer’s profits calculation to [REDACTED]
(Dearborn Decl. Ex. B (Supp. Cox Report) ¶ 33.) This is not appropriate. The Court
has already rejected the notion that there is a direct correlation between the relative value of the
copyrights to the 2006 license bundle, on the one hand, and the relative value of the copyrights to
revenues generated for Google by Android, on the other hand. (Dkt. 685 at 7–9.) Dr. Cox just
ignores the Court’s ruling.
In fact, Dr. Cox admits that his use of Prof. Cockburn’s apportionment percentage is
inappropriate. Dr. Cox writes:
[REDACTED]
(Dearborn Decl. Ex. B (Supp. Cox Report) ¶ 36) (emphasis in original). Dr. Cox does not explain
why his use of Prof. Cockburn’s apportionment analysis is scientifically or logically sound at all.
Instead, he only claims, without any analysis or explanation, that his use of those percentages [REDACTED]
(Id. ¶ 32.) This is, of course, the same
9
reasoning that the Court previously found inadequate . (See Dkt. 685 at 8 (“It is no answer to say, as
Dr. Cockburn did in his footnote 327, that his approach is ‘conservative.’”).)
Even if Dr. Cox’s use of the 5.1 percentage figure were analytically sound—and it is not—it
could not be conservative. Prof. Cockburn, through the group-and-value approach, measured the
relative value of the copyrights and the patents as compared to the other elements of the 2006 license
bundle. Google’s burden with respect to infringer’s profits, by contrast, is to present some
methodology by which to measure the absolute value that the copyrights provided to Google’s
advertising revenues, to avoid full disgorgement. Anything less would not accomplish the
disgorgement aims of the statute. See Polar Bear, 384 F.3d at 708. Moreover, Prof. Cockburn
determined that the proper apportionment percentage of the 2006 Bundle for the copyrights could be
16.4% or higher. (Cockburn Report ¶ 420.) Dr. Cox has not explained why the lower bound of Prof.
Cockburn’s range is appropriate to use in the context of his infringer’s profits analysis.
C. Cox’s Alternative Calculation Of Infringer’s Profits Based On The
Parties’ Revenue Sharing Discussion Should Be Stricken
Dr. Cox’s new and “different way” to calculate Google’s profits attributable to the
infringement fares no better. In his alternative calculation, Dr. Cox begins with the [REDACTED] in
revenues that he claims Android had earned as of September 2011. Once again, he fails to prove the
elements of profit attributable to factors other than the copyrighted work. Instead, he constructs the
following argument: In 2006, Sun proposed to license its technology to Google in exchange for a
10% royalty. (Dearborn Decl. Ex. B (Supp. Cox Report) ¶ 39.) According to Dr. Cox, that
establishes that no more than 10% of real world Android revenues could be attributable to Sun
intellectual property. (Id.) Dr. Cox once again relies on Prof. Cockburn’s 5.1% lower bound
apportionment figure to assert that no more than 5.1% of the 10% of real world Android revenues
(0.51%) could be attributable to Google’s copyright infringement. Ergo, reasons Dr. Cox, 99.49% of
Android’s real world profits are attributable to factors other than the copyrighted Java API
specifications. (Id.) Thus, he multiplies his estimate of Android’s revenues by 0.51%, and arrives at
an amount of [REDACTED]. (Id. ¶¶ 37–42.)
This method is even more profoundly flawed than Dr. Cox’s first method. No court has ever
10
approved of a defendant using a previously negotiated royalty rate to meet its burden to apportion the
profits it subsequently earned through infringement.
First, this approach suffers from the same problem that undermines his other calculation, as
explained above. The fact that Prof. Cockburn concludes that, at the lowest bound, the copyrighted
APIs represented at least 5.1% of the 2006 license bundle does not permit Dr. Cox to conclude that
the same apportionment percentage applies to Android’s real world revenues.
Second, Dr. Cox’s analysis cannot meet Google’s burden under Section 504(b). Whatever
amounts the parties hypothetically might have agreed on in 2006, that ex ante division of value does
not establish the amount by which Google subsequently actually profited from Android’s
infringement of the Java APIs.
Third, using a royalty rate negotiated ex ante to apportion infringer’s profits will
systematically understate copyright damages. The amount that Google rationally would have been
willing to pay Sun for a license necessarily will be less than the amount Google expected to profit
from that same license. Of course, the point of the infringer’s profits remedy is to deter infringement
by forcing the infringer to disgorge whatever gains it earned as a result of the infringement. Polar
Bear, 384 F.3d at 707–08 (discussing “infringer’s gains”). Dr. Cox’s approach would subvert that
rule. A willful infringer would bargain for the lowest possible royalty, break off negotiations once
favorable terms were proposed, and then deliberately infringe. If the infringer avoided getting
caught, it would pay nothing. If it were caught, it would argue—just as Google does now—that the
infringer’s profits remedy should be no greater than what Google was prepared to pay in the first
place. This is even more brazen than the “Soviet-style negotiation” Google previously advocated,
and the Court rejected. (Dkt. 230 at 10.)
Fourth, even if Dr. Cox’s second approach were sound—and it is not—his use of the 10%
revenue share to cap the value of the copyrights is nonsensical. The 2006 proposal would have
provided Sun with substantial value above and beyond a 10% share of Android revenues, including a
license fee of $60 million for the first three years, rights to Google intellectual property, the
advantage of having Google promote the Java brand in the mobile market, a compatible Android
implementation, and hundreds of millions of dollars from convoyed sales.
11
Dr. Cox’s alternate approach to infringer’s profits is unsound factually, legally, and logically,
and it should be stricken.
D. Cox’s Revisions To Lost Profits Do Not Rest On A Reliable Foundation
And Should Be Stricken
Dr. Cox has revised his lost profits analysis to apply the same 5.1% apportionment
percentage, derived from Prof. Cockburn’s group-and-value apportionment analysis. (Dearborn
Decl. Ex. B (Supp. Cox Report) ¶ 44).) This is unsound for the same reasons described above. Dr.
Cox does not explain why it is appropriate to apply a figure derived from a group-and-value
apportionment exercise to Sun’s lost profits, and there is no basis to do so. On this ground alone, as
well as the fact that Prof. Cockburn made no revisions to his lost profits analysis and Dr. Cox
therefore may not either, the Court should strike Dr. Cox’s supplemental lost profits opinions.
Moreover, the Copyright Act does not provide for any apportionment of lost profits at all. See
17 U.S.C. § 504(b). Prof. Cockburn already accounted for the degree to which Google’s
infringement caused Sun, and now Oracle, harm in calculating the lost-profits figures shown in his
Report. (Cockburn Report ¶¶ 671–94.) [REDACTED]
The Copyright Act provides for “actual damages” to account for the copyright holder’s actual
losses. Lost profits are lost revenue less costs avoided. See On Davis v. The Gap, Inc., 246 F.3d 152,
164–65 (2d Cir. 2001). Prof. Cockburn already deducted avoided costs. (See Cockburn Report Exs.
20 & 21.) Oracle will show at trial that the entirety of the remaining losses are attributable to
Android’s infringement. Google may argue otherwise, but Dr. Cox should not be permitted to
present a misleading and unreliable calculation that mechanically applies an inapposite 5.1%
12
apportionment figure to Oracle’s lost profits with no explanation at all as to why that figure bears any
relationship to the harm caused by Android’s infringement.
V. CONCLUSION
For all these reasons, the revisions in Dr. Cox’s supplemental report to the infringer’s profits
and lost profits figures should be stricken, and Dr. Cox should not be permitted to testify regarding
them.
Dated: February 24, 2012
BOIES, SCHILLER & FLEXNER LLP
By: /s/ Steven C. Holtzman
Steven C. Holtzman
Attorneys for Plaintiff
ORACLE AMERICA, INC.
12
737
UNITED STATES DISTRICT COURT
NORTHERN DISTRICT OF CALIFORNIA
SAN FRANCISCO DIVISION
ORACLE AMERICA, INC.
Plaintiff,
v.
GOOGLE, INC.
Defendant.
Case No. CV 10-03561 WHA
ORACLE AMERICA, INC.’S OPPOSITION
TO GOOGLE’S MOTION TO STRIKE
PORTIONS OF THIRD EXPERT REPORT
BY IAIN COCKBURN AND EXPERT
REPORT BY STEVEN SHUGAN
Dept.: Courtroom 8, 19th Floor
Judge: Honorable William H. Alsup
TABLE OF CONTENTS
I. |
INTRODUCTION |
1 |
II. |
ARGUMENT |
3 |
|
A. |
Prof. Cockburn’s “Independent Significance” Analysis Is Legally And
Factually Sound |
3 |
|
B. |
Prof. Cockburn’s “Group And Value” Analysis Is Reasonable And
Admissible |
7 |
|
|
1. |
Prof. Cockburn’s Consideration Of The Work Performed By
Oracle Engineers Is Appropriate |
8 |
|
|
2. |
Prof. Cockburn’s Consideration Of Industry Studies Reflecting
Patent Value Distributions Is Appropriate |
11 |
|
C. |
Prof. Cockburn Correctly Apportions The Value Of Copyrights In The
2006 Bundle |
15 |
|
D. |
Prof. Cockburn Correctly Considered And Accounted For Claim-By-
Claim Differences Within The Portfolio |
17 |
|
E. |
Professor Shugan’s Conjoint Analysis Is Methodologically Sound |
19 |
|
|
1. |
Conjoint Analysis Is An Appropriate Tool In A Hypothetical
License Analysis |
19 |
|
|
2. |
Prof. Shugan’s Conjoint Survey Was Methodologically Sound |
20 |
|
F. |
Prof. Cockburn’s Econometric Analysis Is Methodologically Sound |
23 |
|
|
1. |
Prof. Cockburn’s Econometric Analysis Is Based On Reliable
Data |
23 |
|
|
2. |
Prof. Cockburn’s Analysis Is Based On Reasonable
Assumptions |
24 |
III. |
CONCLUSION |
25 |
i
TABLE OF AUTHORITIES
CASES |
Arista Records LLC v. Lime Group, LLC,
06 CV5936KMW, 2011 WL 1674796 (S.D.N.Y. May 2, 2011) |
15, 24 |
Boucher v. U.S. Suzuki Motor Corp.,
73 F.3d 18 (2d Cir. 1996) |
24 |
Cornell Univ. v. Hewlett-Packard Co.,
609 F. Supp. 2d 279 (N.D.N.Y. 2009) |
19 |
Daubert v. Merrell Dow Pharms., Inc.,
509 U.S. 579 (1993) |
8, 20, 23 |
Domingo v. T.K.,
289 F.3d 600 (9th Cir. 2002) |
24 |
Faulkner v. Gibbs,
199 F.2d 635 (9th Cir. 1952) |
1, 4 |
Finjan, Inc. v. Secure Computing Corp.,
626 F.3d 1197 (Fed. Cir. 2011) |
2, 4, 5, 6 |
General Electric Co. v. Joiner,
522 U.S. 136 (1997) |
14 |
Hangarter v. Provident Life & Acc. Ins. Co.,
373 F.3d 998 (9th Cir. 2004) |
11 |
i4i Ltd. P'ship v. Microsoft Corp.,
598 F.3d 831 (Fed. Cir. 2010), aff'd, 131 S. Ct. 2238 (2011) |
19 |
In re Katz Interactive Call Processing Patent Litig.,
639 F.3d 1303 (Fed. Cir. 2011) |
19 |
In re Phenylpropanolamine (PPA) Prods. Liab. Litig.,
289 F. Supp. 2d 1230 (W.D. Wash. 2003) |
24 |
Johnson Elec. N. Am. v. Mabuchi Motor Am. Corp,
103 F. Supp. 2d 268 (S.D.N.Y. 2000) |
23 |
Kennedy v. Collagen Corp.,
161 F.3d 1226 (9th Cir. 1998) |
13, 23 |
LG Display Co., Ltd. v. AU Optronics Corp.,
722 F. Supp. 2d 466 (D. Del. 2010) |
8, 11, 13 |
ii
Lucent Technologies, Inc. v. Gateway, Inc.,
580 F.3d 1301 (Fed. Cir. 2009) |
4, 6, 7, 19 |
McLaughlin v. American Tobacco Co.,
522 F.3d 215 (2d Cir. 2008) |
20 |
Medical Instr. & Diagnostics Corp. v. Elekta AB,
No. 97-CV-02271, Dkt. No. 464 |
24 |
Ruiz-Troche v. Pepsi Cola of Puerto Rico Bottling Co.,
161 F.3d 77 (1st Cir. 1998) |
21 |
U.S. Gypsum Co. v. Lafarge N. Am. Inc.,
670 F. Supp. 2d 737 (N.D. Ill. 2009) |
24 |
Uniloc USA, Inc. v. Microsoft Corp.,
632 F.3d 1292 (Fed. Cir. 2011) |
2, 4, 6 |
Veritas Operating Corp. v. Microsoft Corp.,
No. C06-0703-JCC, 2008 WL 7404617 (W.D. Wash. Feb. 26, 2008) |
4 |
iii
I. INTRODUCTION
In his revised damages report (“Report”), Prof. Cockburn applies two new apportionment
methods, both grounded in this Court’s Orders and established case law. In addition, he provides
further explanation of his approach to claim-by-claim and future damages, and minor revisions to his
econometric analysis. Other than that, as required by the Court, his report is unchanged.
Based on the new apportionment methods, and after accounting for any reductions for failure
to mark or for the limitation to only accused products, Prof. Cockburn calculates a range of
minimum reasonable royalty damages for the patent claims ($17.7 to $57.1 million) and the
copyrighted API claims ($34.7 to $111.9 million). (Report ¶¶ 5-6.) The “starting point” for those
calculations is the combination of Sun’s $100 million offer and the $557 million that Sun expected to
earn over three years from a compatible Android, both of which the Court previously ruled could be
used to calculate damages based on a hypothetical negotiation. (Dkt. 685 at 4-7.) Prof. Cockburn’s
copyright lost profits and infringer’s profits calculations and analyses are unchanged.
In its entire brief, Google cites only eight cases (not one of which supports the points Google
advances), an oral argument transcript from a different case, and a losing in limine brief that Google
mischaracterizes as a federal court decision. Google claims that Prof. Cockburn and Prof. Shugan
failed to perform analyses that they did perform and expressly documented. Google makes factual
assertions, and then quotes testimony that negates those assertions. Google speculates that there
might be facts that contradict Prof. Cockburn’s analyses, but offers no evidence to support its
musings. Nothing in Google’s brief justifies exclusion of any expert opinion in this case.
Google first attacks Prof. Cockburn’s “independent significance” approach to apportioning
the value that would have been included in the 2006 transaction (the “2006 Bundle”). In that
approach, Prof. Cockburn considers the available evidence concerning the attributes provided by the
patents and copyrights and the importance of those attributes to Google as of 2006. Google’s attack
has two prongs:
- Google contends Prof. Cockburn’s conclusion that the patents in suit account for at least 25%
of the value of the 2006 Bundle is impermissibly subjective because the figure is not based on
a “quantitative algorithm or formula.” But “[t]here is no mathematical formula for the
determination of a reasonable royalty.” Faulkner v. Gibbs, 199 F.2d 635, 639 (9th Cir.
1952). Prof. Cockburn’s approach is consistent with the Federal Circuit decision in Finjan,
1
Inc. v. Secure Computing Corp., 626 F.3d 1197 (Fed. Cir. 2011). Google ignores Finjan.
- Google argues that Prof. Cockburn’s use of 25% is an improper attempt to rely on the “25%
rule of thumb” royalty rate that the Federal Circuit rejected in Uniloc. But this argument
ignores that the independent significance approach does not calculate a royalty rate; it simply
apportions the 2006 Bundle. Moreover, Prof. Cockburn relies on no rule of thumb; he
examines the specific evidence in this case to determine proper apportionment percentages.
Google next attacks Prof. Cockburn’s “group and value” approach to apportionment. In that
approach, Prof. Cockburn identifies, values, and accounts for all of the elements of the 2006 Bundle
other than the patents and copyrights. He then relies on work done by Oracle’s Chief Architect for
the Java Platform, Dr. Mark Reinhold, and other Java engineers to identify the patents that would be
expected to contribute the greatest technical benefits to a smartphone platform in 2006. Numerous
studies of patent value establish that most of the value of a group of patents is attributable to a very
small number of patents in the group. Those studies calculate curves that allow one to estimate the
percentage of portfolio value attributable to the most significant patents in the portfolio. Prof.
Cockburn uses the engineers’ conclusions that three of the asserted patents are among the most
technically important 4% of the 2006 portfolio to apportion economic value according to these
curves. Google’s arguments in response are unfounded:
- Google argues that the four engineers supporting Dr. Reinhold were biased by their previous
analyses of Sun’s patents for litigation purposes. As this Court has previously made clear, the
claim of bias is a cross-examination point, not a Daubert argument. But there was no bias.
Google fails to mention that the engineers testified under oath that their previous analyses
covered dozens of patents, not just the patents-in-suit.
- Google argues that the engineers’ analysis is too vague because it does not rank each of the
569 patents individually. But false precision does not make for good evidence or good
engineering analysis. Prof. Cockburn appropriately deals with this by having an upper bound
and a lower bound measurement of the value of the patents-in-suit.
- Google speculates that the portfolio of patents identified by the engineers may have a
different value distribution than the patents in the studies that Prof. Cockburn cites. But
Google cannot say whether the distribution really is different, whether any difference is
material, or whether any difference would increase or decrease damages. Prof. Cockburn has
made clear that the distribution of patent value in the studies – across countries, across
industries, and within specific product groups – is the same as for the Sun portfolio and is
consistent with his own observations of single company portfolios.
- Google argues that Prof. Cockburn fails to subtract the full value of copyrighted source code
(not in suit) that Sun would have conferred in the 2006 Bundle. Google is wrong. Prof.
Cockburn identifies all of the relevant copyrighted material. For copyrighted source code not
in suit, he calculates the value to Google of avoiding the expense of writing that code itself.
With respect to code implementations, there is no basis for attributing greater value than the
2
cost of writing them.
- Google argues that Prof. Cockburn failed to account for unasserted claims within the asserted
patents. But the Court’s requirement that Oracle separately calculate damages for the asserted
claims was for purposes of determining a verdict if some asserted claims were more valuable
than others, or if some claims were later found to be invalid. Prof. Cockburn was not required
to calculate a value for every claim, asserted and unasserted, of a patent, particularly when
neither real nor hypothetical negotiators in 2006 would have done so.
Google also argues that Prof. Shugan’s conjoint analysis should be excluded. Google claims
that conjoint analysis is a market research tool, not a way to calculate damages. Google’s argument
that only methods specifically developed for litigation are admissible, while those that are accepted
by academics and professionals as rigorous and reliable are not, contradicts Daubert itself. Market
surveys are routinely used in litigation to calculate damages, and the Federal Circuit has specifically
approved their use to show what parties would have expected at the time of a hypothetical
negotiation. Moreover, conjoint analysis has repeatedly been used in litigation, and many experts,
including Google’s own copyright damages expert, Dr. Cox, have concluded that it is a proper way to
calculate infringement damages. None of Google’s specific attacks on Prof. Shugan’s analysis here
have any merit. Even if they did, those attacks are grounds for cross-examination, not exclusion.
Finally, Google attacks Prof. Cockburn’s econometric analysis. That study uses eBay data
from smartphone auctions to assess the value that consumers would place on the performance
benefits provided by the patents-in-suit (as shown by the benchmarking analyses). Google asserts
that eBay purchasers are unrepresentative, without explaining how or why, while ignoring Prof
Cockburn’s explanation why this is not so. Google also asserts that if Android phones were slower,
their price would drop, mitigating the effect on its own market share. But Google never explains how
it would dictate phone prices to the OEMs and carriers who must build and subsidize those mediocre
phones. Moreover, Google’s assertion concedes that the performance enhancement provided by the
patents in suit is valuable to consumers. Google’s arguments provide no basis for exclusion.
II. ARGUMENT
A. Prof. Cockburn’s “Independent Significance” Analysis Is Legally And Factually Sound
Prof. Cockburn’s independent significance approach evaluates (a) the specific attributes
provided by the patents and copyrights in suit, (b) Google documents that demonstrate the importance
3
to Google of those specific features and functionality, and (c) quantitative measures of the
performance and economic benefits that the parties would have expected from the infringement, as
demonstrated by benchmark performance tests and the input of technical experts and generally
supported by the conjoint survey and econometric data. (Report ¶¶ 421, 459, Exs. 6-11.) Based on
all of that evidence, Prof. Cockburn concludes that at least 25% of the value of the 2006 Bundle
should be attributed to the patents in suit, and at least 12.5% should be attributed to the copyrighted
API specifications in suit. (Id. ¶¶ 5-6, 423, 670.)
Google does not dispute that the speed, memory and applications provided by the patents and
copyrights were and are important to Android. Instead, Google argues that Prof. Cockburn’s
quantification of the value of the property in suit is nothing more than a “subjective guess” derived
“without using any quantitative algorithm or formula” and that Prof. Cockburn’s apportionment
analysis runs afoul of the Federal Circuit’s rejection of the “25% rule of thumb” for a reasonable
royalty in Uniloc. (Dkt. 718 at 1, 4-7.)
Like almost all of the arguments in its motion, Google’s insistence that a reasonable royalty
calculation must be based on some “quantitative algorithm or formula” (Dkt. 718 at 1) rests on
nothing but Google’s own say-so. Google cites no legal authority in support of its argument. To the
contrary, the Ninth Circuit has held that “[t]here is no mathematical formula for the determination of
a reasonable royalty.” Faulkner, 199 F.2d at 639; see also Lucent Tech., Inc. v. Gateway, Inc., 580
F.3d 1301, 1325 (Fed. Cir. 2009) (hypothetical negotiation “necessarily involves an element of
approximation and uncertainty”) (internal quotation and citation omitted); Veritas Operating Corp. v.
Microsoft Corp., No. C06-0703-JCC, 2008 WL 7404617, at *5 (W.D. Wash. Feb. 26, 2008) (denying
motion to exclude expert damages; reasonable royalty calculation does not require “mathematical
formula” or “mathematical precision”).
The Federal Circuit’s decision in Finjan, Inc. v. Secure Computing Corp., 626 F.3d 1197
(Fed. Cir. 2011) squarely supports Prof. Cockburn’s independent significance analysis. In Finjan, the
jury found that defendant Secure Computing infringed three of Finjan’s software patents related to
“proactive scanning” (techniques for defending against computer viruses), and awarded reasonable
royalty damages based on the testimony of Finjan’s expert, Russell Parr. Id. at 1201. On appeal,
4
Secure challenged the damages award on numerous grounds, including the sufficiency of Dr. Parr’s
testimony under Georgia Pacific factors 10 and 13, which concern “the nature of the patented
invention” and “the portion of the realizable profit that should be credited to the invention.” Id. at
1211. Secure argued that Dr. Parr failed to fully account for the other software modules included in
the accused products that also contributed to their profits. Id. The Federal Circuit disagreed:
Parr testified that, based on Secure’s internal documents, proactive scanning was
“fundamentally important to the product,” while Degen [Secure’s expert] agreed after
reviewing Secure and Finjan promotional materials that “[i]t’s important technology.
It was perceived as the next wave.” Those materials included statements emphasizing
Secure’s ability to “proactively protect” customers with “Webwasher Proactive
Scanning.” From this evidence, the jury could infer that a substantial fraction of the
accused products’ profits stemmed from proactive scanning.
Id. (internal record citations omitted). Dr. Parr offered no algorithm or formula for his apportionment
of profits and no quantitative evidence, but nonetheless testified regarding a specific range of
appropriate apportionment values. The Federal Circuit held that the jury was “entitled to hear the
expert testimony” and affirmed the damages award based on that testimony. Id. at 1212. Google
never addresses Finjan, though the Court and Oracle both have previously cited it.
Prof. Cockburn’s conclusion here considers and relies upon far more evidence than Dr. Parr
did in concluding that Finjan’s patents accounted for a “substantial fraction” of the value of Secure’s
virus detection software. Like Dr. Parr, Prof. Cockburn considers Google’s contemporaneous
documents, which repeatedly emphasize the critical importance of the speed and memory that the
asserted patents provide. (Report ¶¶ 63, 441-46, 448, 450.) Google does not try to rebut that
evidence, but rather argues that speed, memory and applications are “obvious features” (Dkt. 718 at
1). But calling features “obvious” does not make them unimportant – indeed, they may be obvious
because they are so critical to the commercial success of a smartphone.
Prof. Cockburn also considers the cost of memory and hardware needed to compensate for a
non-infringing device’s larger footprint (Report ¶¶ 432, 453-55; Exh. 16) and benchmarking evidence
showing the substantial incremental performance improvements provided by the patented technology.
(Id. ¶¶ 425–38.) In addition, he considers the results of the conjoint survey and econometric analyses
of consumer preferences as general quantitative indicators of how important those features are. (Id.
5
Exs. 6-11.)1 Because all of this data is precisely the type of information that could have been
obtained at the time of the hypothetical negotiation (Report ¶¶ 426, 458), it is properly considered to
establish a royalty. Lucent, 580 F.3d at 1333–34; see also Dkt. 718 at 15-16 (Google concession that
conjoint analysis is frequently used when “designing or launching a new product”).)
In short, nothing in Prof. Cockburn’s testimony states or suggests, as Google contends, that
Prof. Cockburn “made up [the 25%] number because it felt right to him.” (Id. at 6.) Instead, even the
testimony Google quotes shows that his quantification is based on objective evidence, not a
“subjective judgment,” as Google asserts. (Dkt. 718 at 7.) Finjan analysis is a “disguised resurrection” of the
“25% rule of thumb” rejected in Uniloc USA, Inc. v. Microsoft Corp., 632 F.3d 1292 (Fed. Cir.
2011). In support of its argument, Google relies only on coincidence: Prof. Cockburn’s patent
apportionment percentage is 25%, and the “rule of thumb” was a 25% royalty. Google’s attempt to
relate the two is off base. First, What Google describes as an impermissible “subjective” analysis is
in fact the approach that the Federal Circuit approved in Finjan. Second, in Uniloc the court rejected
the rule of thumb not because it was “subjective,” but because it was a constant, arbitrary value
unrelated to the facts of the case, see 632 F.3d at 1313-18. In contrast, the independent significance
approach rests upon consideration of the specific evidence in this case, not any generic rule of thumb.
Third, the approach is an apportionment analysis of the percentage of the 2006 Bundle attributable to
the patents and copyrights in suit, not the calculation of a royalty rate. It has nothing at all to do with
the 25% rule of thumb at issue in Uniloc.
Google’s claim Prof. Cockburn “admitted at deposition that he included the caveat ‘at least’ to
preserve his flexibility to argue a much higher percentage to the jury” (Dkt. 718 at 1) is also false.
Google pressed Prof. Cockburn to identify an upper limit for the apportionment percentage for the IP
in suit, and he stated that the percentages could be substantially greater (see id. at 6-7 (quoting
_________________________________
1 Google incorrectly claims that Dr. Cockburn does not discuss the conjoint or econometric analyses
in the independent significance section of his report. (Dkt. 718 at 5.) In fact, paragraph 459 of that
section makes clear that the evidence on which he relies is summarized in Exhibits 6-11 of his report,
which refer to the results of the conjoint and econometrics analyses.
6
testimony)). That testimony in no way undermines his damages calculations, which are based on the
minimum apportionment percentages that he derived based on his review of the evidence, and which
make no adjustment for fragmentation or the litigation premium. Google’s claim that Prof.
Cockburn’s analysis cannot be “replicated” (id. at 7) is also factually and legally wrong. Google
engineers could have conducted performance tests on Android phones; Google could have hired a
survey expert; Google’s experts could have conducted an econometric study; and Google’s experts
could, like Prof. Cockburn, consider the evidence. But in any event, because expert valuation of
intellectual property, unlike a chemistry experiment, “necessarily involves an element of
approximation and uncertainty,” Lucent, 580 F.3d at 1325, its admissibility cannot hinge on whether
it can be “replicated.” See Kumho Tire Co., Ltd. v. Carmichael, 526 U.S. 137, 150-51 (1999) (expert
testimony that relies on “personal knowledge or experience,” such as valuation of property, may not
be susceptible to scientific standards of reliability); American General Life Ins. Co. v. Schoenthal
Family, LLC, 555 F.3d 1331, 1338 (11th Cir. 2009) (“Standards of scientific reliability, such as
testability and peer review, do not apply to all forms of expert testimony.”).
B. Prof. Cockburn’s “Group And Value” Analysis Is Reasonable And Admissible
In the “group and value” approach, Prof. Cockburn identifies the elements of the 2006 Bundle
and subtracts the value of the elements other than the patents and copyrights in suit. (Report ¶¶ 361-
90.) To help apportion value between the patents in suit and other patents, Dr. Cockburn asked Dr.
Reinhold to evaluate what Sun patents would have been included in the 2006 Bundle and which of
those patents would have been expected to contribute the greatest technical benefit to a smartphone
platform. (Id. ¶¶ 391-97.) Prof. Cockburn considers studies showing that the distribution of value
within a group of patents is highly skewed; that is, a very small number of patents will account for a
very large percentage of the value of a portfolio. Dr. Cockburn applies the engineers’ ranking of the
technical benefits provided by the patents in Sun’s portfolio to the distribution curves described by
the studies, and calculates an apportionment range on that basis. (Id. ¶¶ 403-15.) This method
carefully applies established economic principles to the facts of this case. Indeed, allocating value
within a company’s patent portfolio based on evidence of the asserted patents’ relative value and
established distribution curves has been accepted by other courts. See LG Display Co., Ltd. v. AU
7
Optronics Corp., 722 F. Supp. 2d 466 (D. Del. 2010).
Google challenges Prof. Cockburn’s (a) reliance on Oracle engineers to select and rank the
patents that likely would have been included in the 2006 Bundle; and (b) method of evaluating the
relative economic value of the patents-in-suit based on studies concerning the distribution of value
among patents. (Dkt. 718 at 7-11.) Neither challenge warrants exclusion under Daubert.
The core of Google’s argument is an unreasonable and insupportable notion of what is
required for expert analysis to survive attack under the Daubert standard. Google first takes Dr.
Reinhold to task for not “offer[ing] even a guess as to the ranking [of each individual patent] among
these top 22,” (Dkt. 718 at 9), and then criticizes Prof. Cockburn for applying a well-accepted
economic rationale for attributing value to the patents group-ranked by the engineers. Google would
have this Court require a standard of false precision that lies beyond the ability of engineering and
economics and still further beyond the gate-keeping requirements of the law.
1. Prof. Cockburn’s Consideration Of The Work Performed By Oracle Engineers Is
Appropriate
Google badly mischaracterizes the work that Oracle’s Java engineers performed to assist Dr.
Cockburn. That work is described in detail in the engineers’ depositions and in declarations that each
has submitted.2
All five engineers were Sun employees with over 70 years combined experience in
overlapping elements of the Java language, Java virtual machines, and Java virtual machines on small
embedded devices. All five are the inventors of Java-related patents (none of which are in suit) that
would have been included in the 2006 portfolio. All five are deeply experienced in evaluating and
implementing inventions related to the performance of Java virtual machines. ((Reinhold Decl. ¶¶ 4-
7; Rose Decl. ¶¶ 3-6; Wong Decl. ¶¶ 3-7; Kessler Decl. ¶¶ 3-8; Plummer Decl. ¶¶ 3-7.) One was
directly involved in the 2006 negotiations with Google. (Wong Decl. ¶ 5; Wong Tr. 23:24-25:18.)
Dr. Kessler has also served on Sun’s and Oracle’s Patent Review Committee, in which he assesses
___________________________________
2 Excerpts of the deposition transcripts of the five Oracle engineers are attached to the Norton
declaration as Exhibits F (Dr. Mark Reinhold), G (John Rose), H (Hinkmond Wong), D (Peter
Kessler), and E (Christopher Plummer). We refer to those deposition transcripts and declarations in
this brief by last name (e.g., “Reinhold Tr.” and “Reinhold Decl.”).
8
the technical merit of many Java-related inventions. (Kessler Decl. ¶ 6.)3
The engineers began by applying their experience, as well as the Android Product
Requirements Document that Google gave Sun in 2006, to identify 22 “technology blocks” covered
by Sun’s Java patents in 2006 relevant to a smartphone at that time. (See, e.g., Reinhold Decl. ¶ 10.)
They then ranked those 22 groups, in terms of their importance to a smartphone platform, by
considering their importance to startup time, speed, memory and security – all criteria they regularly
use to judge Sun’s and Oracle’s own Java implementations. (Id. ¶ 19.)
The engineers also reviewed a deliberately over-inclusive list of over 1300 patents issued to
Sun prior to June 30, 2006 that included the term “Java” or “bytecode” anywhere in the patent or
listed James Gosling or Nedim Fresko as an inventor. (Simion Decl. ¶¶ 3-9.) The engineers were
already familiar with the overwhelming majority of these patented inventions, as they were (or knew)
the inventors, were directly or indirectly involved in the implementations of those inventions, [REDACTED]
(Reinhold Decl. ¶¶ 4-7; Rose Decl. ¶¶ 4-8; Wong Decl. ¶¶ 4-7; Kessler Decl. ¶¶ 4-8; Plummer Decl.
¶¶ 4-7; see also footnote 3.) By reviewing the titles, abstracts, inventors, application dates, and where
necessary, the specifications and claims, the engineers were able to evaluate which patents would
have been relevant to the parties’ 2006 smartphone platform negotiations, and to assign the relevant
patents to the appropriate technology blocks. (See, e.g., Reinhold Decl. ¶ 17; Kessler Decl. ¶ 9.) The
engineers confirmed the accuracy of their initial categorization of the patents by reviewing the
patents both together and individually in categories in which they had special expertise. (Reinhold
Decl. ¶ 17.) This process left 569 potentially relevant patents.
The engineers rated the technical importance of each of the 569 patents on a 3-point scale,
considering the patent’s expected contribution to a smartphone platform’s startup, speed, or footprint.
(Id. ¶ 21.) The engineers could provide this ranking in a matter of days because the scale was
____________________________________
3
The engineers each detailed the breadth of their knowledge and experience during their depositions.
(Reinhold Tr. 6:4-8:10, 23:13-23, 48:3-49:16; Rose Tr. 12:22-13:18, 26:22-28:9, 28:18-24, 77:15-
78:11, 80:9-14; Wong Tr. 13:1-12, 15:13-17:22, 39:13-19, 64:17-65:8, 66:17-67:6, 69:4-70:6, 145:4-
146:6, 147:3-148:11, 153:15-154:8; Kessler Tr. 22:2-22, 23:19-24:4, 37:20-38:6; Plummer Tr. 10:10-
11:2, 16:18-17:10, 35:9-36:15, 96:2-19, 97:11-98:5, 99:14-101:17.)
9
manageable, they were already familiar with the patented inventions based on years of experience,
and they had already spent an intensive week examining and discussing the patents. (Reinhold Decl.
¶ 22; Wong Decl. ¶¶ 11-21; Plummer Decl. ¶¶ 11-20; Kessler Decl. ¶¶ 12-21; Rose Decl. ¶¶ 12-21;
Wong Tr. 64:11-66:6, 146:18-148:21; Rose Tr. 77:15-78:11; Plummer Tr. 97:11-98:5.) Each patent’s
rating was independent of the importance of the technology block to which the patent was assigned.
(Reinhold Decl. ¶ 19.) By identifying the patents and blocks rated most highly, the engineers were
able to identify the 22 most important patents of the 569. Three out of six (now five) of the asserted
patents – the ’104, the ’720, and the ’205 – were among the top 22 patents, comprised of patents rated
a “1” on the individual rating scale and assigned to one of the three top-ranked technology blocks.
Google argues that the four engineers who assisted Dr. Reinhold were “biased” [REDACTED]
) There is simply no factual basis for any assertion of bias in favor of the
patents that happen to be at issue in this one lawsuit.
Even were there a factual basis for a claim of bias, it is not cognizable in this motion.
Google’s own damages experts in this case rely heavily on party employees for information, and the
Court has already ruled that they may do so provided that the foundational facts are established at
trial. (Dkt. 632 at 2-3 (“If Oracle is worried about bias, then it should make its arguments on crossexamination.”).)
The same reasoning applies here.
Google also suggests that the engineers had too little time to rate the patents, and should have
conducted “quantitative testing” of all 569. (Dkt. 718 at 7-9.) Each of the engineers has rejected that
contention in sworn testimony. (Reinhold Tr. 41:23-42:11; Wong Decl. ¶ 24; Plummer Decl. ¶ 23;
Kessler Decl. ¶ 24; Rose Decl. ¶ 24.) Google ignores that testimony, as well as the engineers’
10
testimony that they relied on years of experience with implementations of the patents and longstanding
familiarity with many of the inventions to inform their technical assessment of the
engineering benefits of the patents in the portfolio. Google’s arguments at most go to the weight of
the evidence, not admissibility. See Hangarter v. Provident Life & Acc. Ins. Co., 373 F.3d 998, 1017
n.14 (9th Cir. 2004) (factual basis for expert opinion goes to credibility of testimony, not
admissibility; opposing party may examine basis for opinion in cross-examination).
2. Prof. Cockburn’s Consideration Of Industry Studies Reflecting Patent Value
Distributions Is Appropriate
Based on the engineers’ identification of the 22 technically most significant patents that
would have been included in the 2006 Bundle, Prof. Cockburn applied published studies that examine
the distribution of patent value to estimate the percentage of the total portfolio value that would have
been attributed to those top patents. (Report ¶¶ 403-12 & Exs. 34-35.)
This approach was approved in LG Display Co., Ltd. V. AU Optronics Corp., 722 F. Supp. 2d
466 (D. Del. 2010). There, AU Optronics (AUO) asserted that LG Display infringed four patents.
AUO’s damages expert, Jonathan Putnam, reviewed industry portfolio licensing practices to
determine the amount that LG Display would have paid AUO for its entire portfolio. To determine
the value of the four specific patents in suit, Putnam assumed that those four patents were in the top
5% of AUO’s patent portfolio and calculated their likely value based on a distribution curve from a
single paper that examined patent values for the entire electronics industry. (Norton Decl. Exh. A
(Putnam declaration describing analysis) at 7 n.4, 8.) Putnam’s distribution curve showed that the
average patent in the top 5% was worth 29 times more than the average patent in the bottom 95%,
and on that basis he calculated a royalty for the four asserted patents. (Id. at 7–8.) The court found
Putnam’s “testimony and methodology to be credible and consistent with Federal Circuit case law
and the Georgia-Pacific factors, despite LGD’s assertions to the contrary,” and awarded damages
consistent with that testimony. LG Display, 722 F. Supp. 2d at 472.
Prof. Cockburn’s analysis is more rigorous. He does not simply assume the importance of the
patents in suit; he relies on the informed assessments of experienced Java engineers. He does not use
a single distribution curve; he considers three such curves, based on detailed academic studies across
11
countries, industries, and products. He does not simply assume that the Java patent portfolio at issue
here would share a similar distribution; he has the engineers’ own assessment, which confirms that a
relatively small number of the patents would have the greatest technical value, while the majority
would have little importance to a smartphone platform. He also relies on his own experience having
observed the same highly skewed value distribution of single-company patent portfolios. (Report ¶
404; Norton Decl. Exh. B (Cockburn Tr. 107:20-110:19); Cockburn Decl. ¶¶ 4-12.)
Google contends that the three studies cited by Prof. Cockburn have “nothing to do with the
Sun portfolio at issue” and “are likely to have different distributions of value than the Sun portfolio.”
(Dkt. 718 9-10). Notably, Google does not challenge the conclusion that the distribution of value in
the Sun portfolio would be highly skewed, a fact that has been observed, documented, and studied for
decades. (See Cockburn Decl. ¶¶ 4-6.) Instead, Google speculates – without a shred of analysis or
factual support – that superficial differences between the relevant Sun portfolio and the patents in the
studies are “critical” and make it “likely” that the degree of skewness in the Sun portfolio might be
different from the studies. (Dkt. 718 at 10.) Lacking any support for this conjecture, Google does
not even try to argue that the curves really would be different, that the supposed difference would be
material, or that accounting for the supposed difference would actually decrease damages.
First, Google argues that none of the three studies examined distribution of patent value
within a single company’s portfolio. (Dkt. 718 at 10.) But Prof. Cockburn specifically explained at
his deposition why this is not a meaningful distinction:
As I’ve said a few times, it’s striking that these types of studies done for many
different sets of patents and in many different contexts using many different
methodologies all point to a conclusion which I don’t think is controversial, which is
that the value distribution is highly skewed. So based upon that, it is my opinion that I
have no reason to believe that the 569 patents of interest here would have a value
distribution which is any less skewed than that which has been found so many times in
so many different circumstances. . . .
I’m very familiar myself with looking at portfolios of patents held by specific
companies or organizations that I’ve done research projects on which show this
similar degree of skewness. For example, a number of years ago, had a doctoral
student who was studying patents licensed or offered for license by M.I.T. so he could
see the entire portfolio of inventions and worked on – he knew what the licensing
payments were, he was able to come up with a valuation based upon a calculation or a
projection of licensing revenue. And I think that -- I can’t recall the precise number
12
from memory, but I think that portfolio displayed exactly the property that a handful
of patents of the order of 1 or 2 percent constituted 50 percent of the economic value.
More recently I worked on research projects again looking at licensing data collected
for all the patents, several thousand patents in the portfolio which is held by two large
academic medical research centers who prefer to remain nameless but are not a million
miles from here, and I've looked closely at the data on their licensing. And again they
display the same phenomenon: that a large number of the patents are essentially
valueless by the metric of are they able to attract licensing revenue. And even among
those licensed, a handful constitute the vast majority of the value and have been
licensed or sold for very large sums of money. (Norton Decl. Exh B (Cockburn Tr.
107:20-110:19).)
Dr. Cockburn’s conclusion that single-company portfolios exhibit the same distribution of
value as larger populations of patents is supported both by LG Display, 722 F. Supp. 2d at 472
(approving apportionment analysis based on patent value distribution for entire electronics industry)
and the academic literature (Cockburn Decl. ¶¶ 7-12 & Exh. B at 560 (article observing similar
distribution of values for Harvard patent portfolio).) Prof. Cockburn’s explanation of his reasoning is
more than adequate. See Kennedy v. Collagen Corp., 161 F.3d 1226, 1230 (9th Cir. 1998) (refusing
to exclude testimony where expert had “set forth the steps he took in arriving at his conclusion at his
deposition”). Google provides no affirmative basis on which the Court could conclude otherwise.
Second, Google argues that the 569 patents are confined to software patents for smartphone
functionality, unlike the studies cited by Prof. Cockburn. (Dkt. 718 at 10.) Again, Prof. Cockburn
explained why the Sun portfolio at issue here would be expected to show the same distribution as
other patent populations. That conclusion is supported by the published research, which confirms the
same highly skewed distributions for patents limited to specific product areas. (Cockburn Decl. ¶ 8.)
Google provides nothing to show the distinction makes any difference at all, much less a “critical”
one that “means” the distribution here differs from the studies Prof. Cockburn cites.
Third, Google complains that the 569 patents were “selected deliberately for relevance to this
case,” whereas the cited studies looked at randomly selected patents. (Dkt. 718 at 10.) But the
purpose of the “selection” was to identify the entire set of patents that would have been relevant to a
smartphone in 2006, based on objective indicia of relevance. (Reinhold Decl. ¶¶ 17-18.) Google
cites no example of any patent that was improperly excluded.
13
Fourth, Google notes that two of the studies cited by Prof. Cockburn relied on European
patents, whereas one relied on US patents. (Dkt. 718 at 10.) Google tries to argue that “this is not a
trivial difference” because one of the studies observed that citation counts – not distributions of value
– look very different for German patents than US patents. (Id.) On that basis, Google claims that
“the text of one of [Prof. Cockburn’s] source studies refutes” the assumption that the value
distribution is comparable. (Id.) Differences between European and US citation practices have
nothing at all to do with whether there is any difference in the distribution of patent values.
Moreover, as the authors of the study explain immediately after the words Google quotes – but
Google omits from its brief – “applicants at the EPO are not required to supply a full list of prior art”
so they cite far fewer patents than US applicants. (Zimmer Decl. Exh. C (Harhoff study) at 1355.)
In fact, the PatVal survey cited by Prof. Cockburn finds distribution curves to be consistent
across countries. (Cockburn Decl. Exh. A at 45.) To the extent that there is a difference between US
and European patents, the Barney study Prof. Cockburn cites suggests that the value of US patents is
even more skewed, which would tend to increase damages. (Report Exh. 35 (showing damages
ranges for each study’s curve).) Other studies demonstrate that distribution curves are similar across
a sample of German, US, and Harvard patents. (Cockburn Decl. Exh. B at 560.)
Google neither addresses Prof. Cockburn’s explanations, examines the extensive relevant
literature, nor provides any analysis that calls Prof. Cockburn’s conclusions into question. Instead, it
says Prof. Cockburn’s reasoning must be rejected as mere ipse dixit, in conflict with General Electric
Co. v. Joiner, 522 U.S. 136, 146 (1997). As Joiner held and Google concedes, “experts commonly
extrapolate from existing data.” 522 U.S. at 146.4 Numerous decisions confirm that it is reasonable
___________________________________
4
Joiner is of no help to Google. In that case, the Court held that the district court was within its
discretion in excluding expert testimony that the plaintiff’s small cell lung cancer was caused by his
exposure to small quantities of PCBs, rather than his history of smoking. The plaintiff’s expert relied
on inapposite studies that found that (a) infant mice injected directly with massive doses of PCBs
developed a different kind of cancer; (b) factory workers exposed to PCBs had an elevated incidence
of cancer, but there was no basis to find a causal connection; (c) factory workers exposed to PCBs
had a slightly elevated incidence of cancer, but again made no finding of a causal connection; (d) a
study of Norwegian workers exposed to mineral oil, not PCBs, and (e) a study that found a
significant increase in cancer among Japanese workers exposed to PCBs, but those workers had been
exposed to many other carcinogens as well, including “toxic rice oil they had ingested.” Joiner, 522
U.S. at 145-46.
14
for experts to rely on industry studies when calculating damages, provided they apply their judgment
and analysis. See, e.g., Arista Records LLC v. Lime Group, LLC, 06 CV5936KMW, 2011 WL
1674796, at *11 (S.D.N.Y. May 2, 2011) (the “fact that these conclusions are based, in part, upon a
review of surveys and the relevant literature in the area does not render [expert’s] testimony
inadmissible, as long as [he] bases his conclusions on his own expertise and analysis where he
considered both survey evidence, relevant literature, and his expertise to calculate damages”). Prof.
Cockburn uses these studies to inform his analysis and conclusions, and applies his expert judgment
and analysis in doing so. While Google would preclude the application of expertise to interpret
preexisting studies, such application is precisely what the law both contemplates and requires.
C. Prof. Cockburn Correctly Apportions The Value Of Copyrights In The 2006 Bundle
Prof. Cockburn accounts for the value of the copyrights in the 2006 Bundle in three ways.
First, he begins with the draft contract between the parties, which limits the grant of intellectual
property to technology that would be specific to the Android smartphone platform. [REDACTED]
Both calculations likely overstate the cost of
Google’s independent development. Third, Prof. Cockburn values the copyrighted API
specifications, using the independent significance approach. Google’s claim that Prof. Cockburn
“failed to make any attempt to value all of the copyrights that would have been part of the 2006
intellectual property package” (Dkt. 718 at 11) is false.
Google attacks Prof. Cockburn’s analysis by claiming that he “admitted in his deposition that
15
did not even know what Java-related copyrights Sun owned in 2006” (Dkt. 718 at 12). The
deposition testimony Google quotes does not say what Google claims: it simply recites the irrelevant
point that Prof. Cockburn does not know precisely how many copyrights Sun owned for all of Java.
Prof. Cockburn certainly does know, and analyzes, what is relevant: what copyrighted material,
including both the copyrighted APIs in suit and the source code implementations (of both API
libraries and the virtual machine) on which Google now focuses, would have been included in the
2006 Bundle and provided value to Google. (See Report ¶¶ 365-82.)
Google erroneously claims that Prof. Cockburn “made no systematic effort to measure the
value of the millions of lines of code in the API libraries that would have been part of the 2006
bundle” (Dkt. 718 at 13). Prof. Cockburn did account for the value of that copyrighted code. He
quantified the cost incurred by Google to write the code, which it might have otherwise obtained as
part of the 2006 Bundle. As explained below, Prof. Cockburn’s evaluation of those costs tracks the
value that Sun and Google would have assigned to that aspect of the 2006 Bundle. Prof. Cockburn
conducted the same analysis with respect to the development of the Dalvik virtual machine. Google
has not identified any other source code that the parties would have valued as part of the 2006 Bundle
or that would not have been accounted for in Sun’s estimate of $86.15 million in engineering costs.
Google complains that Prof. Cockburn “never had anyone from Oracle examine the code
libraries to determine their value in relation to the API specifications.” (Dkt. 718 at 13.) But Prof.
Cockburn had no need to do so. In calculations Google does not challenge, Prof. Cockburn uses the
amounts Google paid contractors to write source code for the Java class libraries to calculate the
value of all of the Sun class library source code to Google. No further analysis is necessary to
account for the value of the code. Google’s claim that Prof. Cockburn “avoids any specific valuation
of those copyrighted materials at all” (Dkt. 718 at 13) ignores the plain language of the report.
Finally, Google attacks Prof. Cockburn for using Sun’s projected future R&D costs “as a
proxy for the value of Sun’s then-existing intellectual property (the copyrighted class libraries and
source code).” (Dkt. 718 at 13.) Here again, Google misrepresents Prof. Cockburn’s analysis. [REDACTED]
16
[REDACTED] Prof. Cockburn’s analysis also obviates Google’s arguments
about cost versus value and “apples and oranges.” (Dkt. 718 at 13.) Google could have written
source code without infringing, and Google would not place a value on Sun’s code that was greater
than the cost to Google of doing the work itself. Accordingly, the value of that code is no greater
than Google’s saved costs.
In any event, as both Prof. Cockburn and Google's copyright expert, Dr. Astrachan, explain,
Google derived value by including Oracle’s copyrighted API packages to attract the Java developer
community by giving them a familiar development environment. (Report ¶¶ 635-36 (quoting Dr.
Astrachan).) The Android website boasts that, “Android includes a set of core libraries that provides
most of the functionality available in the core libraries of the Java programming language.” (Id. at
479.) Copying Oracle’s source code implementation of the core libraries (API packages) was not
needed to create that familiar development environment because, as Dr. Astrachan points out,
application developers do not care how an API is implemented, as long as it works properly.
(Astrachan Report at p. 56.) [REDACTED]
D. Prof. Cockburn Correctly Considered And Accounted For Claim-By-Claim Differences
Within The Portfolio
Prof. Cockburn’s revised report considers and addresses the issue of calculating damages on a
claim-by-claim basis. (Report ¶¶ 493-533.) Based on input from Prof. Mitchell, Prof. Cockburn
explains how Oracle asserts the same infringement theory for every asserted claim of each patent, and
concludes that each of the asserted claims in any of the patents-in-suit should account for the full
value associated with each of the patents-in-suit. (Id. ¶¶ 494-95.) Prof. Cockburn’s report does not
fail to apportion damages on a claim-by-claim basis, but rather explains, based on the evidence and
17
input from Prof. Mitchell, how damages should be calculated if the jury finds Google liable on some
but not all asserted claims. Notably, Google’s own experts have never argued that damages for one
claim of a patent differ from other claims of that patent. (Report ¶ 496.)
Google now claims that Prof. Cockburn’s apportionment analysis is flawed because he did not
“attribute any value to any of the unasserted claims of the patents-in-suit.” (Dkt. 718 at 14 (emphasis
added).) But neither this Court (nor any other) has ever required such an analysis, and it makes no
sense to do so here. The Court ruled that it was necessary to value the individual asserted claims for
a number of reasons, including the possibility that a jury might find infringement as to some but not
all of the asserted claims. (Dkt. 685 (1/9/12 Order) at 9-10.)
Reducing the value of the patents-in-suit based on the presence of some unasserted claims
makes no sense where the relevant inquiry is one of apportionment – what proportion of the 2006
Bundle value the parties would have assigned to those patents. Parties to an actual licensing
negotiation would not have evaluated every claim – certainly Google and Sun never negotiated over
individual claims – and there is no reason to do so now. (Report ¶¶ 336-37.)
The granular analysis demanded by Google would introduce false precision without
generating more reliable results. The Oracle engineers evaluated each of the 569 patents that might
have been included in the 2006 Bundle by considering, among other things, the patent abstracts and
descriptions, which describe what invention is covered by each of the patents. To the extent asserted
claims deliver the benefits promised by the abstract and description – which they do – they are
entitled to the full value of the patent. No reduction is necessary to account for any unasserted
claims, each of which would be expected to deliver the same benefits promised by the abstracts.
Google suggests that Oracle’s decision to narrow the number of claims in suit somehow
proves that Prof. Cockburn’s analysis is flawed, because Oracle “cannot be heard to argue that those
[no longer asserted] claims have no value to Google.” (Dkt. 718 at 14.) But it is not Oracle’s or Prof.
Cockburn’s position that those claims had no value to Google. Rather, it is Prof. Cockburn’s opinion
that the claims would have no additional value to Google, above and beyond that of the asserted
claims. The evidence indicates that the different claims each address the same functionality.
Finally, requiring some additional reduction to account for the value of unasserted claims
18
would be particularly problematic in this case, where Oracle has been required to drop claims to
narrow this case for trial. If Oracle is forced to reduce damages for the remaining claims based on
the existence of unasserted claims, that would mean that those claims presented unique issues as to
damages, and the Court’s case management orders would be constitutionally suspect. In re Katz
Interactive Call Processing Patent Litig., 639 F.3d 1303, 1312-13 (Fed. Cir. 2011).
E. Professor Shugan’s Conjoint Analysis Is Methodologically Sound
Conjoint analysis is an accepted method of valuing individual product attributes using a
consumer survey. (Report ¶¶ 471; 662; Shugan Report p. 5-6.) By considering multiple attributes
jointly, survey participants make the implicit tradeoffs one would make in real world purchasing
decisions. Comparing respondents’ choices when presented with different feature sets allows for the
estimation of the relative importance of specific features and their effect on market shares.
1. Conjoint Analysis Is An Appropriate Tool In A Hypothetical License Analysis
Google initially attacks the use of conjoint analysis based on the overbroad argument that
such analysis should never be admissible to calculate damages in litigation. (Dkt. 718 at 15.) But it
is settled law that survey-based studies are admissible for just such a purpose. In Lucent, the Federal
Circuit held that an expert may rely on surveys to calculate damages:
Usage (or similar) data may provide information that the parties would frequently have
estimated during the negotiation. . . . Such data might, depending on the case, come from
sales projections based on past sales, consumer surveys, focus group testing, and other
sources. . . . This quantitative information, assuming it meets admissibility requirements,
ought to be given its proper weight, as determined by the circumstances of each case.
Lucent Technologies, Inc. v. Gateway, Inc., 580 F.3d 1301, 1333–34 (Fed. Cir. 2009) (emphasis
added). A conjoint study is precisely the kind of analysis that hypothetical parties could have used
during the 2006 negotiations. The Federal Circuit has also approved of survey evidence to estimate
infringing use, i4i Ltd. P'ship v. Microsoft Corp., 598 F.3d 831, 856 (Fed. Cir. 2010), aff'd, 131 S. Ct.
2238 (2011); ee also Cornell Univ. v. Hewlett-Packard Co., 609 F. Supp. 2d 279, 289 (N.D.N.Y.
2009) (Rader, J.) (faulting plaintiff for failing to produce “customer surveys” that would have backed
“predictive claims” that patent-in-suit was “competitive requirement”).
Many experts have concluded that conjoint analysis is a proper way to calculate intellectual
property damages. (Shugan Decl. ¶¶ 10–18 (listing sources).) Indeed, Google’s damages expert Dr.
19
Cox has described conjoint analysis as a “rigorous” method of calculating damages.5 Conjoint
analysis has been used extensively in litigation. (Shugan Decl. ¶¶ 15-16 (listing cases); Green, P.E.
and V. Srinivasan, “Conjoint Analysis in Marketing: New Developments with Implications for
Research and Practice,” Journal of Marketing, October 1990, pp. 3-19 (article published over 20
years ago, noting increasing use of conjoint analysis in litigation).)
Seeking some disapproval of conjoint analysis, Google mischaracterizes a footnote in
McLaughlin v. American Tobacco Co., 522 F.3d 215 (2d Cir. 2008). (Dkt. 718 at 15-16.)
McLaughlin says absolutely nothing about the admissibility of conjoint analysis, much less its
application to patent damages.6 Google provides no legal basis on which to exclude conjoint
analysis, and it is wrong to claim that a “dearth of opinions” suggests that such analysis is
inadmissible. Daubert does not require that a methodology first be accepted by other courts to be
admissible. To so hold would be to return to the “general acceptance” test that Daubert expressly
rejected. Daubert v. Merrell Dow Pharms., Inc., 509 U.S. 579, 597 (1993).
2. Prof. Shugan’s Conjoint Survey Was Methodologically Sound
Google next presents a series of specific challenges to the reliability of Prof. Shugan’s
conjoint analysis. (Dkt. 718 at 17-20.) Google made every one of these arguments in its opposition
____________________________________
5 Norton Decl. Exh. I (Dr. Alan Cox, “A Better Consumer Survey for Better Damages,” IP Value
Commentator (April 2003), http://www.nera.com/extImage/5958.pdf (“In a choice modeling
exercise, survey respondents compare the features of a product and report their preferences for a
particular combination of features. The results can be translated into monetary values. . . . This
willingness-to-pay and predicted market penetration can then be used to develop a damage
estimate.”)); id. Exh. J (Dr. Alan Cox & Louis Guth, Survey Techniques for Rigorous Measurement
of Damages in Trade Dress Confusion Cases, NERA (Jan. 8, 2007),
http://www.nera.com/67_4876.htm (choice modeling is a “widely accepted, testable technique that
has been peer reviewed, has known rates of error and which is often used in market research -- not
merely in litigation.”)).
6 McLaughlin concerned an effort to extend a presumption of class-wide reliance to a RICO class
action alleging that class members had relied on statements about the health benefits of “light”
cigarettes. 522 F.3d at 223-25. Although plaintiffs had offered a conjoint analysis in the trial court,
that analysis was not at issue on the appeal. Rather, in the course of explaining why it would not
import a presumption of reliance into RICO cases, the Second Circuit observed in a footnote that the
plaintiffs also had difficulty coming up with direct proof of class-wide reliance. Id. at 225 n.6.
Google incorrectly suggests that the Second Circuit found the study inadequate to prove damages
“with sufficient precision to allow a jury award.” (Dkt. 718 at 16.) The Second Circuit was not
commenting on the adequacy of the studies; it was holding that the plaintiffs’ overall approach to
damages – a “fluid recovery” that relied on [r]oughly estimating the gross damages to the class as a
whole and only subsequently allowing for the processing of individual claims” – would expose
defendants to excess damages and violate due process. McLaughlin, 522 F.3d at 231.
20
to Oracle’s Daubert motion to preclude Google’s patent damages expert from testifying about the
conjoint analysis. (Dkt. No. 581 at 14-17; Leonard Decl. (Dkt. No. 581-1) ¶¶ 26-46, 64, 66, 73.) At
that time, Google emphasized that these challenges were “a dispute between experts” and “factual
disputes or disagreements between experts are not grounds for striking expert testimony.” (Dkt. No.
581 at 17.) The Court instructed Oracle to “save its critiques” of Dr. Leonard “for trial.” (Dkt. No.
632 at 7.) The same result should apply now. See Ruiz-Troche v. Pepsi Cola of Puerto Rico Bottling
Co., 161 F.3d 77, 85 (1st Cir. 1998) (“As long as the expert’s scientific testimony rests upon ‘good
grounds, based on what is known,’” it should be permitted “rather than excluded from jurors’ scrutiny
for fear that they will not grasp its complexities or satisfactorily weigh its inadequacies.”). But
Google’s Daubert arguments are not only misplaced jury arguments. They are also wrong.
First, Google claims that Prof. Shugan’s selection of features to be tested was driven by
litigation. This argument is both false and irrelevant. Before including any of the features relevant to
this litigation, Prof. Shugan first confirmed that the features were actually relevant to consumer
choice, through interviews, market research, a focus group, industry analyst reports and buyers’
guides, as he explained in his deposition. (Shugan Decl. ¶¶ 22–24; Shugan Report p. 7–8, App’x D at
5–6.) After he identified 36 features that real-world consumers said mattered in making a purchasing
decision, Prof. Shugan did include features in his survey that were not at issue in this litigation,
including brand and price. It is not necessary in conjoint analysis to test every distinguishing feature
that may matter to consumers, because conjoint assesses relative importance. (Shugan Decl. ¶ 25.)
Second, Google complains that some of the tested features were “spoonfed” to Prof. Shugan
by Prof. Cockburn. (Dkt. 718 at 18.) By that Google means that Prof. Cockburn told Prof. Shugan
which infringement-enhanced features had to be tested. These are the same features that Google calls
“obvious.” (Id. at 1.) That is not a flaw in the study. It is the point of the study.
Third, Google claims that Prof. Shugan erred by assessing the value of features “rather than
the incremental benefit to those features allegedly enabled by the technology at issue.” (Id. at 18.)
This argument is nonsense. The measurements that Prof. Shugan took were of the incremental
benefits provided by the patents and copyrights as they affect features, measured by the benchmark
tests upheld by the Court. Prof. Shugan measured, for example, how much market shares would shift
21
if applications opened in 0.2 versus 2.0 versus 4.0 seconds – the precise differences demonstrated by
the benchmarking. (Shugan Report Exh. 3a–f; Report Exh. 5 (showing benchmarking results).) Prof.
Shugan could have measured nothing more granular. (Shugan Decl. ¶¶ 28–32.)
Fourth, Google argues that Prof. Shugan’s instruction that survey respondents assume that
any feature not listed was the same for all phones “undermines the survey’s ability to predict realworld
behavior” because “all phones are not the same in the real world” (Dkt. 718 at 16, 18). Google
further claims consumers in fact did not hold constant all unnamed features, as is supposedly shown
by the purported fact that 24% of respondents “prefer a smartphone costing $200 to a putatively
identical one costing $100.” (Id. at 19). As Prof. Shugan explained in his October reply report,
Google misinterprets his data. A proper reading indicates that 8.8%, not 24%, of respondents were
insensitive to the $100 price increase. (Shugan Decl. ¶ 39, Exh. A (Shugan Reply Report at 19).)
But even that 8.8% does not give substance to Google’s claims. As Prof. Shugan explains, the ability
of a Bayesian model to predict aggregate consumer behavior is not tested by focusing on individual
outlier cases. (Id. ¶ 41-42.) In any event, it is widely recognized that consumers may associate a
higher price with prestige in a conspicuously consumed item like a smartphone, or with durability.
(Dkt. No. 595 (11/1/11 Shugan Decl.) at 10.) Google’s complaint is that when it reads the data the
wrong way, the study results do not conform to Google’s uninformed assumptions about consumer
behavior. Google’s mistakes say nothing about the reliability of Prof. Shugan’s work.
Fifth, Google argues that Prof. Shugan “conceded” that respondents did not hold nonspecified
features constant because some implicitly associated prestige or durability with price. This
argument misconstrues Prof. Shugan’s testimony. (Shugan Decl. ¶ 33.) Prof. Shugan explains:
When respondents implicitly attribute aspects of other attributes to price or brand name,
that is not inconsistent with holding constant all other variables that are not included in
the conjoint study. There is no reason to believe that respondents who do enrich the
value of the price or brand with variables not included in the conjoint study vary their
evaluation of price or brand between the 16 choice sets from which they choose their
preferred smartphones. Therefore, even if respondents enrich the value of price or
brand, I am still able to isolate the incremental benefit of the features at issue accurately.
(Id. ¶ 33.) In other words, the meaning of price and brand may differ slightly for some consumers,
but each individual consumer can be expected to have a constant view of the meaning of price and
brand. That is all that this survey requires.
22
Finally, Google claims that “[c]ourts routinely recognize that a ‘common sense’
understanding of real-world consumer behavior is an important check against the reliability of
surveys,” (Dkt. 718 at 20, citing Johnson Elec. N. Am. v. Mabuchi Motor Am. Corp., 103 F. Supp. 2d
268, 286 (S.D.N.Y. 2000)), but does not cite a single case where a court actually did so. Johnson
Electric involved no survey at all, contrary to Google’s representations. Even so, a rule that
admissibility of expert testimony depends on the court’s “common sense” reaction to the results
violates the principle that Daubert does not test results, but methods. Daubert, 509 U.S. at 595 (court
must focus “solely on principles and methodology, not on the conclusions that they generate”). More
importantly, if properly understood, nothing about the conjoint analysis here offends common sense.
F. Prof. Cockburn’s Econometric Analysis Is Methodologically Sound
Prof. Cockburn’s econometric analysis uses eBay smartphone auction data to determine how
likely it is that consumers would switch to a different phone if Android lacked the performance
benefits provided by the patents-in-suit. Even if Google’s arguments to exclude this evidence had
any merit, which they do not, they would at most go to the study’s credibility. Indeed, as explained
in the attached Cockburn Declaration, Google’s expert Dr. Leonard makes grievous errors in his
treatment of the eBay data. (See, e.g., Cockburn Decl. ¶ 34–40 (explaining that Dr. Leonard, inter
alia, improperly drops variables, misunderstands collinearity, and applies linear tests to nonlinear
models).) This conflict among the experts should be reserved for trial.
1. Prof. Cockburn’s Econometric Analysis Is Based On Reliable Data.
Google argues that the preferences of people who buy used smartphones on eBay are not
representative of purchasers of new phones bundled with a service agreement (Dkt. 718 at 22), but
provides no reason to believe that the two groups value incremental performance gains differently.
(See Cockburn Decl. ¶¶ 9–11.) See Kennedy, 161 F.3d at 1230–31 (defendant failed to introduce any
evidence that extrapolation at issue was not scientifically valid). Economics and business literature
teaches that there are strong relationships between new and used goods. (Cockburn Decl. ¶ 11.)
Google’s own Chief Economist, Hal Varian, has emphasized how useful eBay data is for
understanding consumers’ willingness to pay for products they demand, stating that “Online auctions
offer a wonderful laboratory for experimental economists.” (Cockburn Decl. ¶ 20.)
23
Extrapolation is acceptable science. “Studies involving similar but not identical situations
may be helpful, so long as an expert sets forth the steps used to reach the conclusion that the research
is applicable.” In re Phenylpropanolamine (PPA) Prods. Liab. Litig., 289 F. Supp. 2d 1230, 1245
(W.D. Wash. 2003) (quoting Domingo v. T.K., M.D., 289 F.3d 600, 605–06 (9th Cir. 2002) (internal
punctuation omitted)). Contrary to Google’s claims, Prof. Cockburn did explain why online
consumers of used phones could be expected to behave similarly to brick-and-mortar purchasers of
new phones (Report App’x C ¶¶ 9–11), and did control for possible difference between new and used
phones. (Id. ¶ 29; see also Cockburn Decl. ¶ 11.) His analysis is sound.
2. Prof. Cockburn’s Analysis Is Based On Reasonable Assumptions.
Google next challenges two aspects of Prof. Cockburn’s econometrics analysis: his
assumption that poorly performing, non-infringing Android phones would be sold at the same price
as real world Android phones, and his use of a ten-day window to observe data for each bidder.
“[C]laims that ‘the assumptions relied on by an expert are unfounded is generally an argument
that goes to the weight rather than the admissibility of the evidence.’”. Arista Records, 2011 WL
1674796, at *3. See also U.S. Gypsum Co. v. Lafarge N. Am. Inc., 670 F. Supp. 2d 737, 740–41
(N.D. Ill. 2009) (rejecting Daubert motion where infringers took issue “not with Davis’s subsequent
calculations, but with her initial assumptions;” holding that “the jury will decide whether to accept or
reject that factual predicate.”) Google’s two “authorities” for the proposition that Daubert excludes
assumptions do not help it. The first emphasizes that testimony is excludable only if the assumptions
are “so unrealistic and contradictory as to suggest bad faith.” Boucher v. U.S. Suzuki Motor Corp., 73
F.3d 18, 21 (2d Cir. 1996). The second is not an opinion at all. Google quotes and cites the
defendant’s losing brief on a motion in limine – a motion that the court denied. (Norton Decl. Exh.
C (Medical Instr. & Diagnostics Corp. v. Elekta AB, No. 97-CV-02271, Dkt. No. 464, at 14–15).)
Google argues that in a world in which Android phones performed more poorly, the price of
Android phones would have declined, blunting the effect on its market share. But with the exception
of a small number of Nexus One phones that Google sold directly, Google would have no influence
over the price at which OEMs sold phones or the extent to which carriers subsidized them. Google
cites no evidence to the contrary. Indeed, Prof. Cockburn will testify that the more likely scenario is
24
that Android would have failed if Google required OEMs or carriers to sell (or subsidize) poorly
performing phones at a lower prices, while still facing the same costs. (Cockburn Decl. ¶¶ 13–16.)
Consequently, Prof. Cockburn’s assumption does not inflate damages; it understates them. Indeed,
the conclusion Google assumes – that poorer-performing Android phones would command a lower
price – corroborates the conclusion of a significant reasonable royalty in this case.
Nor does Prof. Cockburn’s choice of a ten-day window to observe bids overestimate the
number of people who would not purchase a smartphone. The number of buyers who would switch
away from Android phones is not tied to a particular auction; the analysis compares successful
bidders’ revealed valuations to the average prices for the phones on which they bid during the year
the auction took place. (Cockburn Decl. ¶¶ 17–20.) Google merely asserts that if the data shows that
15% of prospective purchasers would have decided not to buy a smartphone in the but-for world, the
data must be wrong. Google does not support that assertion or explain why that result is so
surprising. In fact, in 2009, almost 80% of U.S. wireless subscribers used feature phones, not
smartphones, and the majority of US phones today still are feature phones. (Cockburn Decl. ¶ 32.)
Moreover, any supposed bias in Prof. Cockburn’s assumption is mitigated, if not eliminated, by Prof.
Cockburn’s conservative assumption that Android did not increase the overall size of the smartphone
market. (Id.) Google’s argument is at most a cross-examination point.
III. CONCLUSION
Oracle respectfully requests that the Court deny Google’s motion to strike.
Dated: February 24, 2012
BOIES, SCHILLER & FLEXNER LLP
By: /s/ Steven C. Holtzman
Steven C. Holtzman
Attorneys for Plaintiff
ORACLE AMERICA, INC.
25
739
UNITED STATES DISTRICT COURT
NORTHERN DISTRICT OF CALIFORNIA
SAN FRANCISCO DIVISION
ORACLE AMERICA, INC.
Plaintiff,
v.
GOOGLE, INC.
Defendant.
Case No. CV 10-03561 WHA
DECLARATION OF IAIN M. COCKBURN
IN SUPPORT OF ORACLE AMERICA,
INC.’S OPPOSITION TO GOOGLE’S
MOTION TO STRIKE
Dept.: Courtroom 8, 19th Floor
Judge: Honorable William H. Alsup
I, IAIN M. COCKBURN, declare as follows:
1. I have been retained by Oracle America, Inc. (“Oracle”) as an expert in this matter. In
this declaration, at the request of counsel for Oracle, I address certain issues raised in Google’s
Motion to Strike Portions Of Third Expert Report By Iain Cockburn And Expert Report By Steven
Shugan (“Motion to Strike”) (Dkt. No. 720).
2. My background and qualifications, the terms of my retention, and the documents I
have reviewed are set forth in the report I submitted in this matter on February 3, 2012 (as revised
February 9, 2012) (“Cockburn Report”), and I incorporate them herein by reference. (See Cockburn
Report ¶¶ 8–10; App’x A, B.)
My Use Of Certain Patent Value Distribution Curves In Connection With My “Group
And Value” Apportionment Analysis Was Reasonable
3. Google claims that the three studies I used to evaluate the expected distribution of
value among the 569 patents included in the 2006 Bundle—the Harhoff,1
Barney,2
and PatVal3 studies—are inapplicable because they “have nothing to do with the Sun portfolio at issue” and “are
likely to have different distributions of value than the Sun portfolio.” (Motion to Strike at 9–10.) In
my opinion, Google’s criticisms are misplaced, and my use of these studies in my analysis was
appropriate.
4. As I explained at my deposition, it is my opinion that the distribution of value among
the 569 patents included in the 2006 Bundle would have been similar to the value distribution
reflected in these studies, which is also consistent with a number of other studies and my own
experience evaluating different patent portfolios, both in my academic work and in connection with
various licensing negotiations.
__________________________________
1 Harhoff D., F. Scherer, K. Vopel, "Citations, family size, opposition and the value of patent rights"
Research Policy 32, October, 2002, pp. 1343-1363 (“Harhoff”).
2 Barney, J. A., "A Study of Patent Mortality Rates: Using Statistical Survival Analysis to Rate and
Value Patent Assets," AIPLA Quarterly Journal, Vol. 30, No. 3, Summer 2002. (“Barney”).
3 Gambardella A., P. Giuri, and M. Mariani, "The Value of European Patents - Evidence from a
Survey of European Inventors," Final Report of the PatVal EU Project, January 2005 (“PatVal”).
1
5. It is well-established and widely recognized that patent values are generally highly
skewed, with a relatively small number of patents having significantly greater value. The three
studies that I cited in my report each recognize this principle, and cite to other studies that confirm
this same principle:
- “Consistently with previous findings in the literature, the economic value (measured in
monetary terms) of the PatVal-EU patents is skewed: a small share of patents yields
very high economic returns.” (PatVal, 2005, p. 5 (true and correct copy of article
attached to this declaration as Exhibit A).);
- “The task of assessing the value of patent rights is a particularly difficult one, since the
distribution of these values is highly skew. The skewness property has been discussed
by numerous authors, e.g. Scherer (1965), Pakes and Schankerman (1984, p 79), Pakes
(1986), and Griliches, 1990.” (Harhoff, 2003, p. 1344.);
- “[T]he model supports the view, long held by many in the field, that patent values are
highly skewed. A relatively large number of patents appear to be worth little or
nothing while a relatively small number appear to be worth a great deal.” (Barney,
2002, p. 329.).
6. Many other studies reinforce this conclusion
- “[T]he distribution of the value of patented innovations is known to be extremely skew
implying that a few patents are very valuable, and many are worth almost nothing.”
(Hall, 1999, p. 14.4
);
- “This paper draws implications for technology policy from evidence on the size
distribution of returns from eight sets of data on inventions and innovations
attributable to private sector firms and universities. The distributions are all highly
skew; the top 10% of sample members captured from 48 to 93 percent of total sample
returns.” (Scherer, 2000 (true and correct copy of this article attached to this
declaration as Exhibit B).5
);
- "[I]n 1980 the top 10% of licensed technologies account for 95% of total gross
income, and in 1990 the top 10% account for 88%. This feature of the distribution -
that outlying tail values account for a large proportion of cumulative revenue - is
consistent with previous evidence on the distribution of returns from industrial
innovations (see Scherer and Harhoff 2000 for an excellent review), and university
__________________________________
4 Bronwyn Hall, “Innovation and Market Value,” NBER Working paper 6984, 1999.
5 Scherer, F. M. and D. Harhoff, “Technology policy for a world of skew-distributed outcomes,”
Research Policy, v. 29, 2000, pp. 559-566.
2
inventions (Mowery et al. 2001; Mowery and Sampat 2001).” (Sampat and Ziedonis,
2005, pp. 285-286.6
);
- “The distribution of the private value of patent rights is sharply skewed in all
technology fields, with most of the value concentrated in a relatively small number of
patents in the tail of the distribution.” (Schankerman, 19987
).
7. Google’s contention that a single-firm portfolio, such as the portfolio that I considered
in this case, is “likely” to have a different distribution curve (Motion to Strike at p. __) is, in my
opinion, incorrect. Google has not cited any study or paper in support of this proposition, and I know
of none. In contrast, one study from 2000 shows that the patents of a single firm (Harvard) have a
similar degree of skewness as the patents shown in the broader studies of both German and US
patents, with the top 10 percent of each set capturing more than 80 percent of the value of that set.8
8. There have been a number of studies that focus on the distribution of value across
various different patent populations, and they all come up with similar distribution curves. That
includes published research that confirms the same highly skewed distribution for patents limited to
specific product areas.9
Every paper I have reviewed suggests that the distribution of value of patent
is highly skewed, and they confirm that the distribution curves that I used in my analysis for this case
are reasonable.10
I would expect such similar distribution curves to apply to single-firm portfolios,
including the one that I evaluated in this case.
9. My opinion in this respect is reinforced by the work that I did with a doctoral student,
Ajay Agarwal, at University of British Columbia, who was studying patents licensed or offered for
____________________________________
6 Bhaven Sampat and Arvids Ziedonis, “Patent Citations and the Economic Value of Patents,”
Handbook of Quantitative Science and Technology Research 2005, Part 2, 277-298.
7 M. Schankerman, “How Valuable is Patent Protection? Estimates by Technology Field,” Rand
Journal of Economics, Vol. 29, 1998, pp. 77-107.
8 Scherer, F. M. and D. Harhoff, “Technology policy for a world of skew-distributed outcomes,”
Research Policy, v. 29, 2000, pp. 559-566.
9 Harhoff D., F. Scherer, K. Vopel, “Citations, family size, opposition and the value of patent rights”
Research Policy 32, 2003, pp. 1343-1363.
10 See also, e.g., Gambardella A., P. Giuri, and M. Mariani, “The Value of European Patents -
Evidence from a Survey of European Inventors,” Final Report of the PatVal EU Project, January
2005.)
3
license by the Massachusetts Institute of Technology. As I explained in my deposition, Dr. Agarwal
studied licensing payments received by MIT for all of the patents in its portfolio. Such payments
provide a basis for economic valuation based on received or projected licensing revenue, and the
distribution of value within that single portfolio displayed the same property that I rely on in my
report: a very small number of patents, 1-2%, commanded more than 50% of the value of the
portfolio. That work is consistent with the Scherer article, and confirms that single-firm portfolios
demonstrate similar value distributions as the larger samples reflected in other studies.11
10. Additionally, as I explained in my deposition, I recently worked on a research project
in which I reviewed licensing data collected for several thousand patents held by two large medical
research centers. These portfolios owned by a specific institution again display the same
phenomenon that is described in the Harhoff, PatVal, and Barney papers: the distribution of value in
these single-company portfolios was highly skewed, in that a small number of patents had a
substantially greater value that the rest of the patents. Even among those patents that were licensed, a
handful constitute the vast majority of the value, and have been licensed or sold at a premium.
11. Based on my conversation with Alfonso Gambardella, the author of the PatVal study,
the distribution of the value within the portfolios of individual companies is very similar to the
distribution of value within the larger sample of patents in the published paper.
12. This phenomenon has been repeatedly described to me in the course of conversations
and research interviews with licensing executives for large US-based technology companies,
including IBM, United Technologies, and Pitney Bowes.
My Calculation Of The Value of Copyrights Included In The 2006 Bundle Other Than
The Infringed APIs Was Reasonable
13. Google claims that I confuse cost with value based on my analysis of the copyrighted
materials at issue in the 2006 Bundle, and argues that my analysis is therefore inadequate. (Motion to
Strike at 13.) Google is wrong. The “millions of lines of code” that Google claims would have been
__________________________________
11 Bhaven Sampat and Arvids Ziedonis, “Patent Citations and the Economic Value of Patents,”
Handbook of Quantitative Science and Technology Research 2005, Part 2, 277-298
4
copyrighted in 2006 would not have any value to Google separate and apart from the code itself,
which I have fully accounted for in my assessment of the cost to write that code. As explained in my
report, I fully accounted for the copyrighted materials included in the 2006 Bundle but which are not
in-suit by calculating the full cost of developing that copyrighted code.
14. Google’s patent damages expert, Dr. Leonard, uses the same proxy as I do to calculate
value. In Dr. Leonard’s October 2011 report, he also used the cost of writing a certain amount of
code—the cost of building a virtual machine—which he pegs at approximately $11 million. If there
is significant “value” on top of the pure code of a virtual machine, Dr. Leonard should have
accounted for such value in this calculation.
15. I have not confused cost and value. If there had been an agreement between the
parties, it might have cost Sun next to nothing to provide Google some of the source code Google
wanted for the Java virtual machine and associated libraries. However, given that all these items
provide value to Google, I calculate the value to Google as the cost of writing that code from scratch.
Effectively, the value is the avoided cost. By calculating the cost to Google of writing that source
code, I have fully accounted for the value to Google.
The Conjoint Analysis
16. I understand that Prof. Steven Shugan, who conducted a conjoint study to evaluate the
enhancements enabled by the use of the copyrights and patents that Google is alleged to have
infringed, has submitted a declaration in support of Oracle’s opposition to Google’s motion in which
he explains how Google’s critiques of the conjoint analysis are badly misinformed. I have reviewed
Prof. Shugan’s critiques, and I agree with them.
The Econometrics Analysis
17. Google claims that my econometric analysis should be excluded for two reasons.
First, Google claims that my analysis is based on unrepresentative data. Second, Google claims that
my calculation of market share is based on unreasonable assumptions about price and consumer
choices. Google is wrong on both points.
A. My calculations are based on representative data.
5
18. Google claims that eBay purchasers are not representative of purchasers in brick-and-mortar
stores. Google’s position that online sales data do not provide meaningful information about
consumer preferences is contrary to Google’s own practices. As a company, Google makes money
by analyzing online consumer behavior and selling that information to firms interested in reaching
potential consumers. 12
19. Google has emphasized that it uses data from online purchases, rather than brick-and-mortar
stores.
- Google has proposed a Google Price Index (GPI) based on online prices as an improved
way of tracking inflation. Rather than waiting for answers from brick and mortar stores
(as the U.S. government does in producing the CPI), GPI tracks inflation through online
prices. Generally, Google’s index and the U.S. Government’s index closely track one
another.13
An independent effort to use online price information to track pricing and
inflation has found very similar results. MIT’s Billion Prices Project’s (BPP) uses online
prices to construct a measure of inflation that tracks the Bureau of Labor Statistic’s
measure of the CPI very closely, suggesting that online prices have a close
correspondence to those observed in traditional retail outlets.14
- Google Shopper searches the web (including the websites of both online and brick-and-mortar
stores) to deliver the best prices for keyword-searched goods. It is difficult to
reconcile Google’s claim that consumers who buy their phones from eBay versus mobile
carriers and brick and mortar stores are not linked when Google, itself, provides a shopper
that allows consumers to compare prices between the two.15
- When Google commissions studies to better understand purchasing behavior, it has, itself,
looked at eBay data. For example, eBay was among the sites analyzed in a study
__________________________________
12 Firms that advertise on Google include both brick and mortar and online firms.
13 See, e.g., Robin Harding, Google to map inflation using web data, Financial Times, ft.com (Oct.
11, 2010), available at http://www.ft.com/intl/cms/s/2/deeb985e-d55f-11df-8e86-
00144feabdc0.html#axzz1mvc6HBDa; Alexis Madrigal, Google Price Index Highlights Slowness of
Economic Data Collection, The Atlantic, (Oct. 12, 2010), available at
http://www.theatlantic.com/technology/archive/2010/10/
google-price-index-highlights-slowness-ofeconomic-
data-collection/64393/; Tavia Grant, Google eyes trends as economic indicators, The
Globe And Mail, (Oct. 12, 2010), available at http://www.theglobeandmail.com/report-onbusiness/
economy/google-eyes-trends-as-economic-indicators/article1754248/.
14 http://bpp.mit.edu/usa/
15 See, e.g., http://www.google.com/mobile/shopper/
6
commissioned by Google to better understand consumer purchases of e-readers, netbooks,
tablets, and laptops.16
20. Google’s Chief Economist, Hal Varian, has even emphasized how useful eBay data
could be for economic use. Indeed, as the two examples below make clear, Dr. Varian clearly
endorses the use of eBay data to understand consumers’ willingness to pay for products they demand.
Dr. Varian’s biggest concern appears to be that because bidders seem reluctant to use eBay’s
automated “bidding agent” that is intended to eliminate any incentive for late bidding, eBay data
leads to an underestimate of consumers’ willingness to pay (e.g., Dr. Varian seems to believe that my
econometric analysis is an appropriate way to conservatively estimate consumers’ willingness to
pay).
- Dr. Varian has used online data from eBay to test his own theories. In a New York Times
article,17
he wrote: “Online auctions offer a wonderful laboratory for experimental
economists: the participants are intelligent adults, spending real money, who hope to
purchase goods in which they have an intense interest. This is a far cry from the reluctant
sophomores whom experimentalists have had to rely on in the past to test economic
theories. Analysis of online auction data has yielded a wealth of insights, and a few
puzzles. A particularly intriguing puzzle has been the tendency for ‘late bids.’ In a
representative sample of eBay auctions, researchers found that 37 percent of them
exhibited bids in the last minute and 12 percent had bids in the last 10 seconds. These data
understate the actual number of bids submitted in the closing seconds of the auction, since
bids that arrived at eBay after the auction had closed were not counted. The late-bid
puzzle is particularly interesting, since eBay offers an automated ''bidding agent'' that is
intended to eliminate any incentive for late bidding. I only need to tell my bidding agent
the most I am willing to pay for an item, along with my initial bid. If someone bids more,
my agent will automatically increase my bid by the minimal bid increment, as long as this
doesn't raise my bid over my maximum. In theory, each bidder should report his true
maximum willingness to pay and let the agent do the work of bidding. In the end, the
person with the highest willingness to pay for the item will win the auction, paying a price
equal to the second-highest willingness to pay plus the bid increment.”
___________________________________
16 See, e.g., Google.com, Portable PC Shopper, October 2010, available at
http://www.thinkwithgoogle.com/insights/library/studies/portable-pc-shopper/ Among the paper’s
conclusions are that shoppers looking for e-readers, netbooks, tablets, and laptops check the
following different sites when shopping: Amazon, eBay, Sam‘s Club, Best Buy, Fry’s, Staples,
Circuit City, Newegg, Target, Comp USA, Office Depot, Tiger Direct, Costco, Office Max, Walmart,
CDW, Radio Shack. See id. at p. 38.
17
Hal Varian, Online auctions as a laboratory for economists to test their theories,
New York Times (Nov 16, 2000), available at
http://people.ischool.berkeley.edu/~hal/people/hal/NYTimes/2000-11-16.html
7
- Dr. Varian has also written a chapter in a microeconomics textbook discussing auction
design that discusses how in a Vickrey auction (which eBay’s proxy bidder system
effectively is), it is in the bidder’s interest to submit his or her true willingness to pay.8
21. In addition to being contrary to its own business practices, Google’s suggestion that
the econometric analysis is based on unrepresentative data is incorrect for a number of reasons.
22. First, this criticism misunderstands the purpose of the econometric analysis. I
analyzed eBay data not to model the price at which OEMs or mobile carriers sell smartphones to their
customers, nor to measure the discount that a used or unlocked smartphone sells at compared to a
new smartphone. In either of these scenarios, the difference in price point between an unlocked, used
phone and a new phone bundled with a carrier plan might have some significance, because the
analysis would be sensitive to differences between the two populations. However, that was not the
purpose of my analysis. Instead, I measured how consumers value the incremental benefit of
features, particularly performance and speed. I therefore tested an eBay purchaser’s incremental
willingness to pay for an incrementally faster phone against the same population’s incremental
willingness to pay for an incrementally slower phone. The difference is important, because the
population I analyzed was held constant. The only question one needs to ask is whether there is any
reason to suppose the incremental value that online purchasers place on these features is any more or
less than the incremental value of purchasers who buy in traditional in-store sales outlets. There is, in
fact, no reason to suppose there are any meaningful differences, nor have I seen Google offer any
evidence to the opposite.
23. Second, Google’s criticism of the representativeness of eBay data ignores the role of
resellers in the eBay data. Resellers, who either purchase their stock on eBay or use eBay as a outlet
to sell stock purchased elsewhere, provide a link between eBay and other channels for purchase.
These resellers, in order to make a profit, must reflect end consumers’ preferences. It is a wellestablished
proposition in economics that the ability to arbitrage across customer subgroups makes it
__________________________________
18
Varian, H. R., Intermediate Microeconomics: A Modern Approach, Seventh Edition, pp. 315-316.
8
impossible for firms to differentially price across the subgroups.19
In other words, this ability (and
potential for) arbitrage leads to one price, regardless of where or how a consumer purchases a
product.20
Google fails to understand this fundamental link. Instead, Google suggests that my
results are unreliable because I base them on data which includes resellers. Thus, Google’s
criticisms—on the one hand, criticizing eBay data for being unrepresentative and on the other hand,
criticizing the inclusion of resellers—are inconsistent and show little understanding of how markets
work.21
24. Third, Google’s concerns regarding the inclusion of used phones in the eBay data is
not well-grounded. Google fails to recognize the important economic relationship between new and
used goods. Exactly the same models of phones are sold on eBay as are sold in physical stores,
whether in new condition, used, factory reconditioned, or otherwise. There is a long literature in
economics and business that teaches us that there are strong relationships between new and used
goods.22
This is true whether new and used goods are sold in the same channels or through different
___________________________________
19
“Under arbitrage, a consumer who is offered a lower price for a good by a firm purchases an
excess quantity of the good and resells the good to consumers who are denied the lower price by the
firm. Under perfect arbitrage, the firm would be forced to sell all its output at the lowest price to
consumers offered the lowest price, who would then resell to other consumers. Thus, arbitrage
effectively turns price discrimination into offering a single price.” Preston MacAfee, “Price
Discrimination,” Issues in Competition Law and Policy, Volume I (ABA Section of Antitrust Law
2008), p. 467. See also: Hal Varian, “Price Discrimination,” Chapter 10, Handbook of Industrial
Organization, Volume I, Edited by R. Schmalensee and R.D. Willig , Elsevier Science Publishers
B.V., 1989, p. 599 and Jean Tirole, The Theory of Industrial Organization, MIT Press, 1988, pp. 134-
135.
20
In economics, this is referred to as the “Law of One Price” – which demonstrates that in a
competitive market, all transactions between buyers and sellers occur at a single, common market
price. Preston MacAfee, Price Discrimination, Issues in Competition Law and Policy, Volume I
(ABA Section of Antitrust Law 2008), p. 467. See also: David Besanko and Ronald R. Braeutigam,
Microeconomics (4th edition), Wiley, 2010, at p. 331.
21
As Dr. Leonard noted, several bidders bid on many auctions – probably with the objective to resell
these phones. Furthermore, many sellers on eBay operate on several electronic stores– such as eBay,
Amazon Marketplace, and Buy.com. Some eBay sellers operate both in their own electronic stores or
in brick-and-mortar stores. The evidence of the many linkages between eBay and more traditional
distribution channels – electronic or not – can only lead to one conclusion: the law of one price will
prevail thanks to arbitrage.
22
See, for example, “Exploring the Relationship between the Markets for New and Used Durable
Goods: The Case of Automobiles. Devavrat Purohit. Marketing Science Vol. 11, No. 2 (Spring,
1992), pp. 154-167. ; Benjamin D, Kormendi R. “The Interrelationship between Markets for New and
Used Durable Goods,” Journal of Law and Economics, October 1974, 17(2):381-401.
9
channels, as they are in this case.23
Google also claims that whether or not a phone is locked to a
particular carrier is a significant issue. Again, it is important to note that the same models of phone
are sold locked and unlocked in traditional outlets as well as on-line, and purchasers can always
unlock the phone themselves or have this done for them at a nominal fee. Prices of locked and
unlocked phones are therefore closely related. In any case, although there may be some differences
between the prices of new versus used or locked versus unlocked phones, Google fails to recognize
that my econometric analysis explicitly accounts for whether a phone is new or used and whether a
phone is locked or unlocked.24
The econometric modeling will absorb any systematic differences, if
they exist. Yet, Google fails to acknowledge these facts.
B. My calculations are not based on any unreasonable assumptions.
25. Google claims that my calculation of market share is based on unreasonable
assumptions about price and consumer choices. First, Google claims that contrary to my assumption,
the price of Android phones wouldn’t have remained unchanged in a but-for world in which Android
phones would be slower. Second, Google claims that my choice of a ten-day window to observe bids
leads to an overestimate of the number of people who would not have bought the slower Android
phone. Neither one of these critiques has merit.
1. The assumption that the price of Android would remain constant is reasonable.
26. Google claims that my assumption that the price of Android phones would have
remained unchanged in a but-for world is incorrect and that it leads to an overestimate of damages.
Google’s apparent logic is that in a world in which Android phones were slower and performed more
poorly, the price of Android phones would have declined. This is an alternative assumption to the
way I conduct my primary analysis. In making this argument, Dr. Leonard and Google completely
ignore the obvious implication that any decline in prices of Android phones due to the reduced
_______________________________
23
Again, we expect the law of one price to hold, regardless of channel. See, for example, Shulman,
Jeffrey D., Coughlan, Anne T. “Used goods, not used bads: Profitable secondary market sales for
durable goods channel,” Quant Market Econ, (2007) 5:191–210, June 5, 2007.
24
As I explained in Appendix C to my February 3, 2012 report, I include controls for whether a
phone is used or new, and whether a phone is locked or unlocked.
10
quality of the operating system itself is not irrelevant in measuring the reasonable royalty due to Sun.
Quite the opposite – this price decline itself is one such measure.
27. I have considered and discussed this possibility in my report. In Exhibits 6-9 I have
discussed the change in users’ willingness-to-pay for Android phones with diminished performance.
For example, I have determined that disabling the ‘104 patent would translate into a decrease in
users’ willingness-to-pay of $24-$29 (Exhibit 6). Presumably, if the price of Android phones
decreased by that amount in the absence of features enabled by the ‘104 patent, sales of Android
phones would remain unchanged.
28. In that case, one has to consider how this price differential would be financed. The
wireless industry is intensely competitive. Android OEMs and carriers compete with very similar
products and therefore likely earn small margins. If these companies were forced to reduce price by
$24-$29 to compensate for lower quality of the Android OS , they would require Google to
compensate them, for example through additional technical assistance or (increased) revenue sharing
or both. In the end, it would be Google’s burden to absorb the majority, if not all, of the price
decline, or face the likely failure of Android. Therefore, I conclude that Google would have been
willing to pay a patent royalty to Sun in the amount up to the decrease in the users’ willingness-topay.
For the case of the ‘104 patent, Google would be willing to pay Sun up to $29 per unit. The
upper bound of my calculated royalty rate for the ‘104 patent is just $2.36 (see Exhibit 12b) – over 10
times less than this measure of Google’s willingness-to-pay for that technology. This confirms that
my analysis of royalty rates is reasonable and conservative.
2. My assumption that the ten-day window to observe bids is representative is
reasonable.
29. Google next claims that my choice of a ten-day window to observed bids leads to
overestimate the number of people who would not purchase a smartphone. This claim is wrong. It
betrays a fundamental misunderstanding of my model.
30. Google ignores the fact that the computation of the number of buyers who would
switch away from Android phones is not tied to a particular auction, but compares bidders’ revealed
valuations to the prevailing average prices for the phones on which they bid.
11
31. In my model, individual bidders’ valuations of the slower phones are compared to the
average price of that phone. If the price is higher than the bidder’s valuation he simply doesn’t buy
that phone. Contrary to what Google claims, this bidder will not go to AT&T or Verizon to buy the
same phone: that slower phone is simply too expensive relative to that bidder’s valuation for them to
be willing to buy it, whether it is sold on eBay, by a wireless carrier, or in a brick-and-mortar store.
32. Finally, Google contests my conclusion that 15% of Android phone buyers in 2010
wouldn’t have acquired a smartphone at all if the Android phones had been dramatically slower.
Google’s critique is unrealistic, misguided and shows a fundamental misunderstanding of my market
share calculations. In fact, in 2009, almost 80% of wireless subscribers in the United States used
feature phones, not smartphones, and the majority of US phones today still are feature phones.25
Stated differently, my results imply that, if Android phones had performed less well, consumers
would have been slower to switch from their cell phones to smartphones, or alternatively, would have
been slower to upgrade their smartphone to a newer model. This is hardly a surprising finding. To
put it in context, in the but-for world I construct, I find that the sales of smartphones in the United
States would have increased from 46 to 101 million units between 2009 and 2011, instead of the
actual increase from 46 to 107 million units, a reduction of 5.5% of overall smartphone sales. My
model estimates that sales of Android smartphones in the but-for world would still have increased
from 4 to 22 million units instead of the actual increase of 4 to 46 million units. My model is also
conservative based on my assumption that Android did not increase the overall size of the
smartphone market. These estimates are hardly “unreasonable” as Google alleges.
C. Google’s own expert, Dr. Leonard, makes elementary errors in his econometric
analysis.
33. Upon close analysis, it is Google’s expert Dr. Leonard, not I, who has made
elementary mistakes in his econometric analysis. I only describe those errors briefly here, but it is
_________________________________
25
See http://blog.nielsen.com/nielsenwire/consumer/smartphones-to-overtake-feature-phones-in-u-sby-
2011/; http://gigaom.com/2011/09/01/four-in-ten-u-s-phones-are-now-smartphones/
12
my opinion that his analysis is flawed and unreliable, and his criticisms of my approach
fundamentally erroneous.
34. First, Dr. Leonard falsely insists that the results from his Android-only model are
meaningful. Yet, Dr. Leonard must know that by restricting his sample to only the 13 Android phone
models he is unable to estimate the impact of more than twenty different smartphone features, as he
claims to do. Mathematically, one simply cannot do this. The problem arises because there is
insufficient variation in these features across the small number of phone models in Dr. Leonard’s
restricted sample. Dr. Leonard’s “work-around” is to rely on the econometrics software package to
arbitrarily drop certain features from the analysis. One result of this “work-around” is that the
contribution of these omitted features to valuation “loads” on features that are retained, making those
estimates unreliable. Furthermore, the result of this “work-around” is that Dr. Leonard’s model is
nearly collinear, and displays the familiar symptoms of near collinearity.26 In these circumstances,
his estimated coefficients are not reliable and are economically meaningless. Further, Dr. Leonard’s
“results” are not based on the variability in phone features (which would provide meaningful results);
rather, his “results” are based on the different timing of auctions (which does not provide meaningful
results).
35. Second, Dr. Leonard wrongly insists that multicollinearity only affects standard errors.
27
This is nonsense; multicollinearity or near multicollinearity is generally recognized to also make
_______________________________
26
Greene provides an excellent summary of the current understanding of near-multicollinearity:
“When the regressors are highly correlated, we often observe the following problems:
- Small changes in the data can produce wide swings in the parameter estimates.
- Coefficients may have very high standard errors and low significance levels even
though they are jointly highly significant and the R2 in the regression is quite high.
- Coefficients will have the wrong sign or an implausible magnitude”.
(Greene, William H. (1997): Econometric Analysis, 3rd edition, London, Prentice Hall, p. 420).
27
Note that I do not calculate standard errors formulaically from the regression estimates, but instead
report “boot-strapped” standard errors which are much less sensitive to the impact of
multicollinearity.
13
parameter estimates highly sensitive to small changes in sample or specification.28
This is
particularly true in non-linear models which are estimated here.
36. Third, Dr. Leonard insinuates that he ran a “Chow test.” I note that the Chow test per
se is only appropriate for use on linear models; yet, both my model and Dr. Leonard’s version of my
model are nonlinear models. If Dr. Leonard, in fact, used an analogue appropriate to this context, he
has cited the wrong paper.29
37. Fourth, Dr. Leonard makes deceptive claims about the stability of estimated
coefficients in different subsets of the data. Because the specification of the model, that is to say the
list of explanatory variables, is not held constant across the different subsets of the data that Dr.
Leonard considers (there is no or insufficient variation in some variables within subsets of the data),
his analysis conflates the effect, if any, of variation over time in the economic relationship between
valuations and the explanatory variables with the effect of changing the set of explanatory variables.
For example, Dr. Leonard claims to observe variation in the Linpack coefficient for different time
periods. Yet, the evidence Dr. Leonard presents is generated from models which severely limit the
size of the sample used and therefore the set of models present in each subset. As it happens, in some
of Dr. Leonard’s monthly regressions, there are simply no Android phones; in others there are only a
_______________________________
28
There are two types of near-multicollinearity. The first results from high correlation among
regressors (structural issue.) The second is numerical. The regressor data matrix is ill-conditioned.
This problem gives rise to erratic volatility. As Spanos and Guirk explain:
The presence of ill-conditioning in (XTX) indicates that the sample information is ‘nearlyinsufficient’
for reliable inference concerning X. In such a case the modeler should answer the
question whether he/she can live with the potential erratic volatility as quantified by the norm
bounds. If not, the only obvious way to proceed is to ameliorate the sample information in an
attempt to render the data matrix well-conditioned. In the case of observational data this
amounts to changing the units of measurement and/or getting additional or better quality data;
see Silvey (1969). In the case of experimental data repeating or re-designing the experiment
are additional potential options. (Spanos, A. and McGuirk A. (2002): The Problem of Near-
Multicollinearity Revisited: Erratic vs Systematic Volatility, Journal of Econometrics, Vol.
108, pp. 365-393.)
Dr. Leonard’s analysis violates this well-established principle. Rather than using the existing welldesigned
and acceptable sample, he divides the sample into sub-samples that suffer from erratic
volatility.
29
Again, by reducing the sample artificially, Dr. Leonard generates subsamples with ill-conditioned
regressor matrices. The fact that his so-called Chow test concludes that the subsamples are not
identical only proves that the subsamples are unreliable.
14
few smartphones overall. During the time period covered by my analysis, many new models were
introduced, and during any specific month not all models will be present in the data. Further, Dr.
Leonard should know to attempt to measure 11 unique phone features in a month in which there are
data for only five phones is impossible. As with his analysis of an Android-only subset of the data,
by reducing the sample artificially, Dr. Leonard again generates subsamples with ill-conditioned
regressor matrices, which, in turn, lead to unreliable and highly unstable estimates. Contrary to Dr.
Leonard’s claim, his results simply do not support his claim that my requiring coefficients be equal
across months is incorrect.
38. Fifth, Dr. Leonard wrongly claims that any bias in some coefficient estimates is
necessarily transmitted to other coefficient estimates. The extent of any such “contamination” is an
empirical question. Dr. Leonard offers no evidence to this point.
39. Sixth, Dr. Leonard further alleges that I made a comparison between his Android-only
model and my revised Android-only specifications based on the Schwartz criterion (Dr. Leonard
supplemental report, p. 12). I made no such comparison in my report. Dr. Leonard focuses on this
imaginary comparison instead of addressing the very valid concerns I presented related to collinearity
in both my rebuttal and 3rd damages report. On these substantive issues Dr. Leonard remains silent.
I declare under penalty of perjury that the foregoing is true and correct and that this
declaration was executed on February 24th, 2012 at Boston, Massachusetts.
DATED: February 24, 2012
/s/ Iain M. Cockburn
IAIN M. COCKBURN
15
ATTESTATION OF FILER
I, Steven C. Holtzman, have obtained Dr. Iain Cockburn’s concurrence to file this document
on his behalf.
Dated: February 24, 2012
BOIES, SCHILLER & FLEXNER LLP
By: /s/ Steven C. Holtzman
Steven C. Holtzman
Attorneys for Plaintiff
ORACLE AMERICA, INC.
16
740
UNITED STATES DISTRICT COURT
NORTHERN DISTRICT OF CALIFORNIA
SAN FRANCISCO DIVISION
ORACLE AMERICA, INC.
Plaintiff,
v.
GOOGLE, INC.
Defendant.
Case No. CV 10-03561 WHA
DECLARATION OF STEVEN M.
SHUGAN IN SUPPORT OF OPPOSITION
TO GOOGLE’S THIRD DAUBERT
MOTION
Dept.: Courtroom 8, 19th Floor
Judge: Honorable William H. Alsup
I, STEVEN M. SHUGAN, declare as follows:
1. I have been retained by Oracle America, Inc. (“Oracle”) as an expert in this matter.
My background and qualifications, the terms of my retention, and the documents I have reviewed are
set forth in the Expert Report I submitted in this matter on September 12, 2011, and in declarations I
submitted on October 21, 2011, and November 1, 2011; I incorporate those documents herein by
reference. (See Expert Report of Professor Steven M. Shugan (Sept. 12, 2011) (“Shugan Report”) p.
1–2; App’x A, B, C; Declaration of Steven M. Shugan In Support Of Oracle America, Inc.’s Motion
to Exclude The Expert Reports Of Gregory K. Leonard and Alan J. Cox (Dkt. No. 560); Declaration
in Support of Oracle America, Inc.’s Reply To Google, Inc.’s Opposition to Motion to Exclude
Portions of the Expert Reports of Gregory K. Leonard and Alan J. Cox, November 1, 2011, p. 8-10.
(Dkt. No. 595.) In addition to these materials, I submitted a Reply Report in this matter on October
10, 2011 (Expert Reply Report of Professor Steven M. Shugan (“Reply Report”)), which I am
providing to the Court as Exhibit A to this Declaration. I incorporate by reference all of the analyses
I performed in each of the four documents referenced in this paragraph, for completeness.
2. To review my qualifications in brief, I am currently the McKethan-Matherly Eminent
Scholar and Professor at the University of Florida, where I teach multivariate statistics, marketing
models and advanced marketing management. I hold a Ph.D. in Managerial Economics from
Northwestern University and my research includes services marketing (integrating operations),
statistics, metrics, entertainment marketing, advance-selling, normative methods for modeling
competition, markets for evaluative information, and models of selling and product policy. I was
formerly a full professor at the University of Chicago for 13 years, and I have taught marketing,
econometrics, statistics, and computer science at various universities.
3. I was editor-in-chief of Marketing Science for six years, editor of Journal of Business
and associate editor of Management Science, and I served on over 10 editorial boards including the
Journal of Consumer Research, Journal of Marketing and Journal of Marketing Research. I have
numerous publications (including 27 editorials and commentaries) and have made over one hundred
professional presentations in more than 22 countries. Much of my work involves the evaluation of
marketing research tools including surveys.
1
4. My fields of specialization within marketing include marketing strategy, marketing
research, quantitative models, and consumer decision making. In the course of my scholarly research,
teaching, editorial work, and consulting work, I have studied issues of marketing research, product
design, product and feature development, branding, and pricing, and their roles in consumer
preferences and choice. During my career, I have taught managers, M.B.A. students, and doctoral
students about, written textbook chapters on, evaluated articles for publication on, and conducted
conjoint analysis.
5. I was asked by counsel for Oracle to evaluate consumer preferences for certain
smartphone features. Specifically, Prof. Iain Cockburn, on behalf of Oracle, asked me to conduct a
conjoint study that evaluates the effect of particular features on the demand for smartphones,
including those devices that run the Android operating system. (Shugan Report p. 3.) I conducted
the survey at his direction, and reported the results of the survey and my analysis thereof in the
Shugan Report, which I filed on September 12, 2011. I submitted a Reply Report on October 10,
2011, responding to certain critiques from Google’s damages expert, Dr. Gregory Leonard. I have
not revised either report since then.
6. I understand that Google has moved to exclude the conjoint analysis, claiming that the
analysis is unfit for litigation and had certain methodological flaws. (Google’s Motion to Strike
Portions of Third Expert Report by Iain Cockburn And Expert Report by Steven Shugan. (Dkt. No.
720).) At the request of counsel for Oracle, I address certain issues raised by Google in that motion.
A. Google misunderstands the market share analysis I performed.
7. Google claims that “Dr. Shugan essentially converts the consumers’ preference share
into projected market shares—essentially, he concludes that, if 20% of consumers value application
start time more than other tested features, an increase in application start time on Android phones
would mean a 20% drop in Android market share.”1
____________________________________
1
Google’s Notice of Motion and Motion to Strike Portions of Third Expert Report by Iain Cockburn
and Expert Report by Steven Shugan; Memorandum of Points and Authorities in Support
Thereof, Oracle America, Inc. v. Google, Inc., Case No. 3:10-cv-3561-WHA, N.D. Cal, San
Francisco Division, February 17, 2012 (“Google’s Motion to Strike”), p. 15.
2
8. Google’s assertion is incorrect. It demonstrates a lack of knowledge of the analysis
that I undertook and, more generally, of how conjoint studies are typically used to evaluate new
products and features. Google misunderstands and mischaracterizes my standard market share
analysis. Exhibit 3a to the Shugan Report concludes that an incremental change to the application
start time on an Android device from two to four seconds would decrease sales by 20 percent. This
20 percent change is the result of estimating, based on the choices respondents made in the study, the
number of buyers who would select a different phone when the start up time is changed by two
seconds. Thus, the analysis estimates preference share movements when changing from one level to
another within one feature, holding all other features and levels constant. It is nonsensical to
conclude that this result occurs because 20 percent of consumers value application start time “more
than other tested features,” when those “other features” are held constant within the model.
9. Contrary to Google’s assertions, my conjoint study does not simply convert feature
importance into preference share changes. It relies on the expected distribution of respondent choices
given that a particular set of profiles were available in the market place. Each respondent’s set of
preferences in the various scenarios is evaluated such that the most preferred profile, characterized by
all seven features, including application start time, is identified for that respondent. By summing
these selections for all respondents under the two scenarios, with different start times for Android
devices, holding all else equal, I am able to evaluate the expected loss in market share using standard
analyses with standard software.
B. Conjoint analysis has been accepted by marketing professionals, academics, and
courts.
10. Conjoint analysis is a combination of data collection through surveys and analysis of
the data provided by respondents using standard, well-tested methods relied upon by academics and
commercial entities for more than 40 years.
11. Specifically, conjoint analysis employs a two-step procedure, both of which have been
widely employed in litigation. In the first step, data are collected using standard survey methods.
Consumers are simply asked to choose among different sets of “products” defined by different
features levels. In the second step, the data is analyzed using a standard choice modeling technique,
3
using commercially available and publicly tested software, to analyze survey data. In this case for
the data analysis, I used a logit model, which is a type of regression model, in a software package
developed by Sawtooth Software Inc. (“Sawtooth Software”).
12. Sawtooth Software is a leading provider of software packages used by marketing
researchers and ultimately relied upon by corporations for making numerous product development
and marketing decisions. Sawtooth Software developed the most commonly used software to
conduct conjoint analysis. The software package was created with the assistance of leading
academics in the field of Bayesian analysis and is constantly being improved and enriched in its
capabilities based on the input that Sawtooth Software receives from academics and practitioners
during seminars and conferences that the firm organizes.2 Because of Sawtooth Software’s close
connection to the academic world, the software is highly reliable and provides accurate results.
13. Software developed by Sawtooth Software has been used in litigation matters before
and specifically for the assessment of damages. Bryan Orme, the current President of Sawtooth
Software, states in his introductory book on conjoint analysis that conjoint analysis is used in the
assessment of damages in litigation matters.3
14. Well-known academics have also noted the use of conjoint surveys in litigation
matters: “In addition to the use of conjoint analysis for marketing and strategic analysis, its
applications are becoming increasingly diverse. One area of growing interest is litigation. Recently,
conjoint studies provided primary input to the settlement of disputes in the telecommunications
(foreign dumping of equipment in the U.S.), Pharmaceuticals (lost profits through misleading
competitive product claims), and airline (alleged brand position bias in travel agents’ reservation
computer screens) industries.”4
_________________________________
2
Bryan Orme, “Getting Started with Conjoint Analysis: Strategies for Product Design and Pricing
Research,” Second Edition, Research Publishers LLC, 2010, pp. 29-37.
3
Bryan Orme, “Getting Started with Conjoint Analysis: Strategies for Product Design and Pricing
Research,” Second Edition, Research Publishers LLC, 2010, p. 137.
4
Green, P.E. and V. Srinivasan, “Conjoint Analysis in Marketing: New Developments with
Implications for Research and Practice,” Journal of Marketing, October 1990, pp. 3-19 at 15.
4
15. According to Green, Krieger, and Wind, conjoint analysis has been used in the
following cases:5
- Antidumping litigation – AT&T vs. Pacific-rim manufacturers legal dispute regarding
small business telephone equipment; case adjudicated in AT&T’s favor
- Intermittent windshield wipers litigation – study to determine consumer evaluations of
the derived “willingness to pay” for the intermittent wiper feature
- Continental vs. American Airlines litigation – conjoint study of travel agents’ tradeoffs
among airline flight selections
- TiVo v. EchoStar, in the Eastern District of Texas
- U-Haul Int’l v. Jartran Inc., in the District of Arizona
- Robert Kearns v. Ford Motor Co, in the Eastern District of Michigan
16. Furthermore, conjoint analysis has also been used in reports that were submitted to
Congress and used by the U.S. Navy: 6
- Health maintenance plans: study conducted by the American Association of Retired
Persons; results submitted to Congress
- U.S. Navy benefit packages for reenlistment: conjoint used to develop menu of new
reenlistment plans based on individual differences in types of duties, health needs, and
sign-over bonuses.
C. Conjoint analysis is frequently used in practice to model consumer behavior.
17. Google claims that “[c]onjoint analysis measures consumer preference for product
features; it does not capture how consumers actually behave when purchasing a product. Consumers’
stated preference for a given feature may be one of many factors a company considers in designing or
launching a new product, but they are not a proxy for market share.”7 In fact, conjoint analysis has
_________________________________
5
Green, P.E., A.M. Krieger, and Y. Wind, “Thirty Years of Conjoint Analysis: Reflections and
Prospects,” Interfaces, Vol. 31, No. 3, Part 2 of 2, May-June 2001, pp. S56-S73 at S67.
6
Green, P.E., A.M. Krieger, and Y. Wind, “Thirty Years of Conjoint Analysis: Reflections and
Prospects,” Interfaces, Vol. 31, No. 3, Part 2 of 2, May-June 2001, pp. S56-S73 at S67.
7
Google’s Motion to Strike, p. 16.
5
been used by firms and other organizations in deciding the specific design features of multi-million
dollar projects as it is widely recognized as a reliable tool for predicting consumer behavior:
- Marriott used conjoint analysis to design Courtyard Marriott hotels, “an ‘optimal’
hotel chain catering primarily to business travelers who had no need for many of the
features provided by up-scale hotels, such as Marriott and Hyatt.”8 Most of the design
recommendations from the conjoint analysis were used to create the Courtyard
Marriott and by 2001, there were 450 Courtyard Marriott locations worldwide “with
annual sales in the billions of dollars.”9 Marriott has continued to use conjoint
analysis in other projects, such as “designing time-share vacation units and in room
and amenities pricing.”10
- General Motors Corporation has used conjoint analysis since the early 1970s.
Conjoint analysis has been used for “products such as the Cadillac Northstar engine,
OnStar, XM Radio, Bumper to Bumper warranty, as well as many vehicles, such as
the Chevrolet Avalanche.”11
- Boeing Employees Credit Union, which is the fifth largest credit union in the United
States with 385,000 members, used conjoint analysis to estimate members’ preference
for money market accounts versus regular saving accounts.12
18. Additionally, the external validity of conjoint analysis has been demonstrated in
several circumstances. Several applications in industry, in which conjoint analysis has been applied,
____________________________________
8
Green, P.E., A.M. Krieger, and Y. Wind, “Thirty Years of Conjoint Analysis: Reflections and
Prospects,” Interfaces, Vol. 31, No. 3, Part 2 of 2, May-June 2001, pp. S56-S73 at S67.
9
Green, P.E., A.M. Krieger, and Y. Wind, “Thirty Years of Conjoint Analysis: Reflections and
Prospects,” Interfaces, Vol. 31, No. 3, Part 2 of 2, May-June 2001, pp. S56-S73 at S68.
10
Green, P.E., A.M. Krieger, and Y. Wind, “Thirty Years of Conjoint Analysis: Reflections and
Prospects,” Interfaces, Vol. 31, No. 3, Part 2 of 2, May-June 2001, pp. S56-S73 at S68.
11
Orme, B., Getting Started with Conjoint Analysis: Strategies for Product Design and Pricing
Research , Second Edition, Research Publishers LLC, 2010, p. 130.
12
Orme, B., Getting Started with Conjoint Analysis: Strategies for Product Design and Pricing
Research , Second Edition, Research Publishers LLC, 2010, p. 132.
6
have confirmed ex-post that the predictions from conjoint analyses were close to how the market
actually behaved after the respective products had been introduced:
- EZ-Pass toll collection project used conjoint analysis to determine how EZ-Pass
should be configured and what level of resources should be allocated to its
implementation: “The overall (at equilibrium) forecast made in 1992 of ‘take rate’ was
49-percent usage. The actual take rate (seven years later) was 44 percent; future usage
is expected to be higher than 49 percent.”13
- “Robinson (1980) reports a multinational conjoint study of North Atlantic air travel
involving airfares, discounts, and travel restrictions. His results indicate that conjoint
analysis had a substantial ability to predict market shares. Srinivasan et al. (1981)
describe a conjoint study of individually computed conjoint functions that are used to
predict work-trip modes (auto, public transit, and car pool). Travel mode shifts were
forecasted for various policy-level gasoline tax surcharges. The authors’ forecasted
results were roughly consistent with the actual subsequent increase in transit ridership
resulting from a serendipitous rise in the price of gasoline. Benbenisty (1983)
describes a conjoint study involving AT&T’s entry into the data terminal market. The
simulator forecasted a share of 8% for AT&T four years after launch. The actual share
was just under 8%.”14
- Sunbeam Appliance Co. used conjoint analysis in conjunction with market research
and product line simulations in redesigning its product lines. “The correlation
between the predicted brand shares and the reported shares was very high (r = .96),
which builds confidence in the quality of the market share predictions produced from
the conjoint based simulations.”15
__________________________________
13
Green, P.E., A.M. Krieger, and Y. Wind, “Thirty Years of Conjoint Analysis: Reflections and
Prospects,” Interfaces, Vol. 31, No. 3, Part 2 of 2, May-June 2001, pp. S56-S73 at S68.
14
Green, P.E. and V. Srinivasan, “Conjoint Analysis in Marketing: New Developments with
Implications for Research and Practice,” Journal of Marketing, October 1990, pp. 3-19 at 13.
15
Page, Albert L. and Harold F. Rosenbaum, “Redesigning Product Lines With Conjoint Analysis: How Sunbeam Does
It,” Journal of Product Innovation Management, Vol. 4, 1987, pp. 120-137 at 120.
7
D. Google misunderstands the design of my survey.
19. Google claims that “Dr. Shugan used respondents’ selections to rank and measure the
relative importance of the seven features to consumers. He then plugged these ranked values—
referred to in conjoint parlance as ‘partworths’—into a statistical software program in order to assess
general consumer preference for an Android phone lacking the application volume, startup time, and
multitasking capabilities allegedly provided by the patents- and copyrights-in-suit.” 16
20. Google misunderstands and misstates the analysis that I conducted. I calculated
partworths using the most widely recognized and used regression-based statistical model for
evaluating respondent choices in the framework of choice-based-conjoint. These partworths are not
“ranked values,” rather they are coefficients from the Hierarchical Bayes regression estimation based
on the actual “choices” respondents made in the conjoint exercise. This misstatement further
demonstrates that Google’s counsel and experts do not understand the fundamentals of choice-based
conjoint analysis. The “partworths” are not plugged “into any statistical software,” they are the
coefficient estimates generated through regression analysis based on the data from the choices made
by respondents over 16 choice tasks. They are not generated from simple rankings or from the
assignment of points to various features or feature levels. Conjoint analysis is used because it allows
one to analyze how features contribute to actual decision making when the relevant set of features are
considered jointly.17
E. The selection of features for the conjoint survey was methodologically proper.
21. Google attacks the choice of features in my survey. Google’s attack mischaracterizes
my analysis and misses the point of conjoint analysis.
22. First, Google falsely characterizes my description of how I selected the features and
feature levels to be included in my 2011 Smartphone Survey. While I clearly included the features
that were relevant to Oracle’s case and to Professor Cockburn’s analyses, I first confirmed that these
__________________________________
16
Google’s Motion to Strike, p. 17.
17
Green, Paul E., Abba M. Krieger, Yoram Wind, “Thirty Years of Conjoint Analysis: Reflections
and Prospects,” Interfaces, Vol. 31, No. 3, Part 2 of 2, 2001, pp. S56-S73.
8
features were relevant to consumer choice. I testified in deposition that I relied upon several sources
in making his decision of which features and feature levels to include:
Q. Do you recall who communicated to you specific features that ought to be included
in the conjoint analysis?
A. Well, the -- your question is not really clear in the sense that there are different
features in the analysis. Now, some of the features were communicated to me through
Analysis Group that they were required features and need to be there. Other features I
decided should be there, and there were other features that Cockburn decided needed
to be there. And then in the end, I put it all together and decided which ones to
actually include in the analysis. So the -- there wasn’t one source where all of the
features came from.18 (emphasis added.)
23. Second, as I explained in the Shugan Report, Reply Report, and deposition, in addition
to speaking with Professor Cockburn, I considered interviews, market research, and a focus group to
identify the relevant features and their levels to be included in his 2011 Smartphone Survey.
Exploratory interviews determined what product characteristics matter to consumers’ smartphone
selections and the appropriate vocabulary for the questionnaire. I explained the purpose of the
exploratory interviews in deposition:
Q. BY MR. PURCELL Did you formulate a list of questions that then went into the
one-on-one interviews?
A. Yeah, basically the major use of that research was to identify the features that
consumers would likely use in choosing between smartphones. And specifically
my goal in this was to try at the end of the process to come up with the most
important features so that we could identify the relative importance of the
features involved in the case, that is, the ones involved in the patent and
copyright infringement and how those -- important those would be compared to
the important features. We wouldn’t be really that concerned about how important
_______________________________
18
Deposition of Steven M. Shugan, Ph.D., September 26, 2011, p. 29.
9
they were compared to the unimportant features, but important to the relevant features,
and then be sure to include the least to most important of the features in the conjoint
analysis, mainly, as I say, to explain variants and decrease the variability of the
estimates more than it is to change the estimates. The other objective, the main
objective was to -- in the focus groups, to be able to provide aided recall measures,
where you actually tell people -- I think we had -- in different categories, we had
people that, you know, that we asked them, you know, if you were considering this
phone, would you consider the attribute, and then if you were a purchasing decision,
would that be something that would be involved in a purchase decision. And then the
aided recall requires certain -- you go into the focus group with sort of some attributes
that you could cue people on. But first they were asked the unaided before the aided.19
(emphasis added.)
24. I complemented this qualitative research with a review and analysis of third-party
sources that provided further information about the attributes that consumers consider when selecting
a smartphone and confirmed that the feature enhancements enabled by the patents-in-suit and the
Java copyrights are relevant to their decisions. Specifically, I reviewed industry analyst reports and
buyers’ guides to determine how manufacturers differentiated their smartphones and underlying
operating systems and which product features were emphasized in product reviews.20
Q. What was done to prepare for the conduct of that focus group?
A. To prepare for the focus group, there was background research done by
myself and Analysis Group looking at the literature and publicly available
information on smartphone purchases, specifically looking for the attributes that
________________________________
19
Deposition of Steven M. Shugan, Ph.D., September 26, 2011, pp. 40-42.
20
See for example, “J.D. Power and Associates Reports: Average Length of Time Wireless
Customers Keep Their Mobile Phones Increases Notably,” J.D. Power and Associates, September
23, 2010; and “Top Reasons for Choosing Device – Smartphone vs. Feature Phone: What Were
the Top 3 Reasons for Selecting Your Current Cell Phone?” The Nielsen Company, 2011,
http://www.fiercemobilecontent.com/pages/nielsen-top-reasonschoosing-device-smartphone-vsfeature-
phone.
10
were identified by either reviewers of smartphones, manufacturers of
smartphones in their advertising, the consumers, any surveys that have taken
place, and I believe it was also some quality -- companies that were looking at the
qualities of various phones, the information, or a good sample of that
information, including expert report. And then I also had some personal knowledge,
as other people did, of smartphones, given that the category is a fairly common one.
And then the focus group was set up. It was also -- before the focus group, it was done
one-on-one in reviews with customers to sort of look at their purchasing decision.
People who have recently purchased phones and what attributes they considered. I
think there were seven one-on-one decisions within six people in the focus group. The
focus -- the one-on-one decisions and focus group decisions are complementary in the
sense that their goal was to identify an exhaustive set of features with aided and
unaided recall, unaided recall being consumers just being asked what they considered,
and aided recall being here are some features, which ones of these did you consider.
And then that was sort of the preparation for the focus group.21 (emphasis added.)
25. Additionally, I did, in fact, include several features in my survey that are not at issue
in this litigation. Importantly, it is not necessary in conjoint analysis to test every feature that may
matter to consumers, because conjoint analysis assesses relative importance. I took this additional
step to estimate a well-specified model. After I identified 36 features that real-world consumers said
were important in making a purchasing decision, I intentionally, and conservatively, included in my
survey the two features that consumers cared about most: brand and price, among other features
consumers in the focus groups indicated that they required. This approach is methodologically
sound, as I included the two most critical features that generally derive the greatest value in any
estimation and that capture the benefits of Google’s reputation. Further, including brand in 2011 is
conservative, as it allows Google to benefit from Android’s reputation for feature-rich devices with
___________________________________
21
Deposition of Steven M. Shugan, Ph.D., September 26, 2011, pp. 39-40.
11
broad applicability (i.e., wide availability of applications) built, in part, off of its infringement of the
patents and copyrights in suit.
F. Google does not understand the difference between choice-based conjoint and self-
explicated
approaches.
26. Google quotes a comment made by Judge Posner in the Apple v. Motorola case
regarding the use of consumer surveys to measure the value of a patent. The approach that Judge
Posner was commenting on is referred to as a self-explicated approach, where respondents are asked
to evaluate the levels of each feature one-by-one and then asked to allocate a number of points, e.g.,
100, across all features to represent their relative importance to the respondent. In contrast, the
choice-based conjoint approach uses choice exercises that ask a respondent to perform repeated
choice tasks. In each choice task, respondents are asked to choose their most preferred product from
among several products (i.e., a set of products) where each product is described in terms of the
product’s features. I did not use the approach that Judge Posner objected to in the Apple v. Motorola
case. In fact, I testified in deposition that I considered using a self-explicated approach, but I dropped
the approach in favor of using the choice-based conjoint approach.22 As noted above, a choice-based-
conjoint study is optimal for this type of analyses, as it avoids the artificial “focus” that a selfexplicated
method may require. By presenting product profiles characterized by both the features
that are relevant to the copyright and patent allegations in this case and features that are generally
considered by consumers when making decisions (e.g., brand and price), I did not draw specific
attention to the features at issue in this case. They are presented as part of a broader product profile.
_____________________________________
22
Deposition of Steven M. Shugan, Ph.D., September 26, 2011, pp. 24-25.
12
G. I did evaluate the “incremental benefit” of phone features.
27. Google claims that my study “measures the value consumers place on certain phone
features as a whole, rather than the incremental benefit to those features allegedly enabled by the
technology at issue.” 23 (emphasis in original.) This statement is false.
28. Again, Google has failed to understand how my data and analyses function. The
conjoint study created a “set of utilities or part-worths that quantify respondents’ preferences for each
level of each attribute.”24 With this data on individuals’ partworths, I utilized a market simulator to
simulate respondents’ market choices among a set of defined products characterized by both product
features and the differentiated feature levels.25
29. Using the market simulator tool, I evaluated how preference shares for an Android
device changed depending on whether the patented technologies were enabled (“Base case”) or
disabled (“Scenario 1,” “Scenario 2,” and “Scenario 3”). (See Exhibit 3a to the Shugan Report.) By
altering the levels of only one or two features at a time, the preference shares between the base case
and various alternative scenarios could be compared to measure precisely the incremental benefit (or
cost) of those feature level changes.26 According to Bryan Orme, this “one-attribute-at-a-time
___________________________________
23
Google’s Motion to Strike, pp. 18-19.
24
Orme, B., Getting Started with Conjoint Analysis: Strategies for Product Design and Pricing
Research, Second Edition, Research Publishers LLC, 2010, p. 89.
25
“The simulator is used to convert raw conjoint (part-worth utility) data into something much more
managerially useful: simulated market choices. Products can be introduced within a simulated
market scenario and the simulator reports the percentage of respondents projected to choose each
product. A market simulator lets an analyst or manager conduct what-if games to investigate
issues such as new product design, product positioning, and pricing strategy.” (Orme, B., Getting
Started with Conjoint Analysis: Strategies for Product Design and Pricing Research, Second
Edition, Research Publishers LLC, 2010, pp. 89 and 91.)
26
“Conducting sensitivity analysis starts by simulating shares of choice among products in a base
case market. Then, we change product characteristics one level at a time (holding all other
attributes constant at base case levels). We run the market simulation repeatedly to capture the
incremental effect of each attribute level upon product choice.” (Orme, B., Getting Started with
Conjoint Analysis: Strategies for Product Design and Pricing Research, Second Edition, Research
Publishers LLC, 2010, p. 81.)
13
approach to sensitivity analysis provides a good way to assess relative preferences of product
attributes.”27
30. Contrary to Google’s assertions, the simulation results presented in my report, on
which I understand Prof. Cockburn relied, do not measure the benefit of the at-issue features as a
whole, as I do not consider Android phones with and without applications – I consider Android
phones with varying speeds of application launch times and varying numbers of available
applications.
31. Google may have confused the simulation results reported in Exhibits 3a – 4c of my
Expert Report (on which I understand Prof. Cockburn relied) and the results reported in Exhibit 5 of
my Expert Report which measure the relative importance of each feature as a whole. This particular
analysis was not created for the purpose of estimating preference shares but rather to demonstrate
stability across sample sensitivities; I understand that these results are not relied upon by Prof.
Cockburn in his analysis.
H. I never “conceded” that the survey respondents did not hold levels constant.
32. Google claims that my instruction to survey respondents to “[a]ssume any features not
listed are the same for all alternatives” “undermines the survey’s ability to predict real-world
behavior.”28 This critique is not valid as researchers have found that respondents are able to consider
such hypotheticals.29
33. Google argues that survey respondents did not hold constant those variables that were
not part of the conjoint analysis’s choice task. Google misconstrues the following excerpt from my
Reply Report to support its argument: “For example, respondents will tend to implicitly attribute to
____________________________________
27
Orme, B., Getting Started with Conjoint Analysis: Strategies for Product Design and Pricing
Research, Second Edition, Research Publishers LLC, 2010, p. 84.
28
Expert Report of Steven M. Shugan, Appendix E, p. E-19; and Google’s Motion to Strike, p. 18.
29
See for example Wilhelm, W.B., “Encouraging Sustainable Consumption through Product
Lifetime Extension: The Case of Mobile Phones,” International Journal of Business and Social
Science, Vol. 3, No. 3, February 2012, pp. 17-32 at 22.
14
the brand name any excluded attributes.”30 Google mistakenly characterizes this statement as a
concession that, contrary to the survey instructions, participants in my survey did not hold constant
the non-included features that might be relevant to a smartphone purchase. That is not the case.
When respondents implicitly attribute aspects of other attributes to brand name it is not inconsistent
with holding constant all other variables that are not included in the conjoint study. There is no
reason to believe that respondents who do enrich the value of the brand name with variables not
included in the conjoint study vary their evaluation of brand between the 16 choice sets from which
they choose their preferred smartphones. Therefore, even if respondents enrich the value of brand, I
am still able to isolate the incremental benefit of the features at issue accurately. In other words, the
meaning of price and brand may differ slightly for some consumers, but each individual consumer
will have a constant view of the meaning of price and brand as they make their choices in the survey.
Moreover, as I explained in my Reply Report, some of the value intrinsic to the patents and
copyrights at issue as well as variables not included in the conjoint study may likely be captured in
the Android brand feature level and would lead to my estimates of the value intrinsic to the patents
and copyrights at issue to be understated.31 The same rationale applies to the price feature: should
price capture any other attributes, such as quality, my market share simulation would lead to my
estimates of the value intrinsic to the patents and copyrights at issue to be understated.
I. Google fails to show that respondents did not follow my instruction to hold constant
all unnamed features.
34. Google presents no support to demonstrate that survey respondents did not follow my
instruction to hold any features not listed constant. In fact, the stability of my results and the accurate
representation of real-world market shares by my preference shares in the base case is a strong signal
_______________________________
30
“Such an effect would increase the value of the Android brand name, and so such biases would
reduce the value of the relevant features.” (Reply Report, Exhibit A, pp. 17.)
31
Shugan Report, pp. 16-17.
15
that the data was collected without deviating from scientific standards and resulted in reliable
estimates.32
35. Google ignores this external validation, however, and instead states that “almost one
quarter of all respondents claimed that they would prefer a smartphone costing $200 to a
putatively identical smartphone costing $100.”33 (emphasis added.) What Google offers as “proof
in the pudding”34 is not only technically wrong, but it is also a gross misstatement of my survey.
First, I did not use any open-ended question that would have allowed respondents to express their
preferences directly. Consequently, no respondent “claimed” to prefer a smartphone costing $200 to
a similar one that costs $100. Second, my survey purposefully avoids statements in which
respondents explain their preferences, opinions, or perceptions. Instead, respondents’ choices are
used in a statistical, regression-based model to generate a distribution of partworths that finally – in
their entirety – are used to predict preference shares in a simulated market. Notably, such preference
shares have been shown in many cases to reflect market shares; and if they do so, they offer a
statistically valid and reliable description of a market in either the real world or in a but-for world. In
this case, the market shares were within a rounding error of the real world market shares, suggesting
that respondents understood the instructions and were able to “hold all else constant.” The evidence
Google supposedly provides is based on flawed analyses and flawed logic.
36. Google claims that “[n]o rational person, much less 24% of all rational people, would
prefer to pay $200 for a phone they could have for $100.”35 I responded to this argument in my
___________________________________
32
Kellogg, Don, “In U.S. Market, New Smartphone Buyers Increasingly Embracing Android,” NielsenWire, September
26, 2011, http://blog.nielsen.com/nielsenwire/online_mobile/in-u-s-market-new-smartphone-buyersincreasinglyembracing-
android/; and Exhibit 3a to Expert Report of Professor Steven M. Shugan. “One, I forecasted or predicted
what the actual market shares could be from the conjoint analysis and found that the observed shares in the market
were very close to what the conjoint analysis predicts they should be.” (Deposition of Steven M. Shugan, Ph.D.,
September 26, 2011, p. 115).
33
Google’s Motion to Strike, p. 19.
34
Despite claiming to present a proof, Google presents a proposition that indicates a lack of
understanding not only of the concept of (scientific) proof, but also of the estimation and the
interpretation of the estimation of partworths in a choice model. (Google’s Motion to Strike, p.
19.)
35
Google’s Motion to Strike, p. 19.
16
declaration from November 1, 2011, as well as in my Reply Report, and I incorporate those
documents herein by reference. (See Exhibit A.)
37. In the declaration to which I responded in November 2011, Dr. Leonard pointed out
that some individual utility functions contradict what he touts as rational preferences.36 In doing so,
Dr. Leonard errs in four ways.
38. First, it is critical to note that Dr. Leonard is confusing estimated parameters with
actual data and is then making false inferences about estimated parameters rather than analyzing
actual respondent choices.
39. Second, for the majority of the 24 percent of respondents the estimates for the two
prices are so close that that a diligent statistician would consider the difference to be zero, rather than
representing some form of irrationality. As explained in my Reply Report, I excluded respondents
with utilities associated with $100 and $200 that are within one standard deviation of the difference
in utilities between levels as a sensitivity analysis. When these respondents with such utility
comparisons are excluded from the analysis, only 8.8 percent of respondents, not 24 percent, prefer a
price of $200 over a price of $100.37
40. Third, what Dr. Leonard touts as “irrational,” is, in fact, commonly accepted in
marketing and consumer research: Some consumers display a tendency to shy away from a cheaper
product in favor for a higher price; they are price-insensitive within a reasonable range of prices.38
This fact is well documented in the literature and represents kinks in the demand curve.39
41. Fourth, the most crucial argument in the discussion of so-called irrational preferences,
Google’s experts misunderstand how the Bayesian approach informs individual estimates based on
____________________________________
36
Declaration in Support of Google’s Opposition to Motion to Exclude Portions of the Expert
Reports of Gregory K. Leonard and Alan J. Cox, October 28, 2011, p. 24.
37
See Reply Report, p. 19.
38
See, for example, Mohr, Jakki, J., Sanjit Sengupta, and Stanley F. Slater, Marketing of High-Technology Products
and Innovations, Third Edition, New Jersey: Pearson Prentice Hall, 2010; and “Smartphones: Building Profitability
and Loyalty in the Mass-market,” WDSGlobal, 2010,
http://www.wds.co/enlightened/smartphone_profitability/smartphone_profitability_and_loyalty_wdsglobal.pdf.
39
Lambert, Z.V., “Product Perception: An Important Variable in Price Strategy,” The Journal of
Marketing, Vol. 34, No. 4, October 1970, pp. 68-71, pp. 68-71.
17
aggregate population parameters during the multi-stage estimation process and that one should not
evaluate isolated respondent estimates, as these methods are intended to characterize populations, not
individuals. In these critiques, Google’s experts are emphasizing outliers (which have little weight in
the analysis), rather than recognizing the close approximation or fit of my results with actual market
data.
42. By using such examples from individual respondents, Google’s experts purposefully
focus on individual parameters, and therefore ignore the idea behind a Hierarchical Bayesian model,
such as the one that I use for my estimations. Specifically, Google’s experts forget or ignore that
while one could very well estimate individual parameters by fitting the individual respondent’s
preferences, the aggregate results would almost always suffer from overfitting of the data.40 To
avoid this overfitting in favor of precise aggregate results, the chosen Hierarchical Bayes approach
allows individual parameters to be influenced by information from the whole sample. Hence, while
some individual parameters might reflect small amounts of statistical noise, the aggregate estimation
outcome is precise; in fact, it is considered the gold-standard in choice modeling by many marketing
experts.41 I have stated in deposition that it is the aggregate outcome of the sample, not individual
values, that matters for my analysis: “[t]he analysis was done at the sample level, and so we looked at
all the – the estimation of all the individual responses of all the individual respondents. I didn’t
examine individual questionnaires.”42
43. Furthermore, given that this is an issue involving estimation and not the quality of the
data, it can easily be eliminated by modifying the estimation. If one tried to account for Dr.
Leonard’s erroneous proposition that “No rational person, much less 24% of all rational people,
____________________________________
40
Overfitting describes a model’s characteristic to fit particular data too precisely and therefore lose
its predictive power.
41
Allenby, G. and P.E. Rossi, “Perspectives Based on 10 Years of HB in Marketing Research,
Sawtooth Software Research Paper Series, 2003,
http://www.sawtoothsoftware.com/download/techpap/allenby.pdf.
42
Deposition of Steven M. Shugan, Ph.D., September 26, 2011, pp. 138-139.
18
would prefer to pay $200 for a phone they could have for $100,”43 the outcome of a model using
monotonic preferences for price yields similar results to those reported in the Shugan Report.44
44. Finally, it is not scientific to conclude that my survey is flawed simply because its
results do not confirm Google’s assumptions about consumer behavior. I have pointed out this flaw
in Dr. Leonard’s reasoning before. It is axiomatic in science that one should not substitute one’s own
view of what is correct for what the data show.45
DATED: February 24, 2012
/s/ Steven M. Shugan
STEVEN M. SHUGAN
____________________________________
43
Google’s Motion to Strike, p. 20.
44
“According to these results, Android sales but-for the feature enhancements enabled by the
patents-in-suit and the Java copyrights would have been at least 7.6 (instead of 7.9) percent lower
if availability of applications was reduced and at least 20.0 (instead of 19.9) percent lower if
application startup time was increased. Collectively, Android sales would have been at least 25.7
(compared to 25.7) percent lower but-for these infringements.” (Reply Report, p. 20.)
45
Lehmann, D.R., S. Gupta, and J.H. Steckel, Marketing Research, Massachusetts, Addison Wesley,
1998, p. 68.
19
ATTESTATION OF FILER
I, Steven C. Holtzman, have obtained Dr. Steven Shugan’s concurrence to file this document
on his behalf.
Dated: February 24, 2012
BOIES, SCHILLER & FLEXNER LLP
By: /s/ Steven C. Holtzman
Steven C. Holtzman
Attorneys for Plaintiff
ORACLE AMERICA, INC.
20
745
UNITED STATES DISTRICT COURT
NORTHERN DISTRICT OF CALIFORNIA
SAN FRANCISCO DIVISION
ORACLE AMERICA, INC.
Plaintiff,
v.
GOOGLE, INC.
Defendant.
Case No. CV 10-03561 WHA
DECLARATION OF HINKMOND WONG
IN SUPPORT OF ORACLE AMERICA,
INC.’S OPPOSITION TO GOOGLE’S
MOTION TO STRIKE PORTIONS OF
THIRD EXPERT REPORT
Dept.: Courtroom 8, 19th Floor
Judge: Honorable William H. Alsup
I, HINKMOND WONG declare as follows:
1. I am an employee of Oracle America, Inc. (“Oracle”). My title is Consulting Member
of the Technical Staff.
2. I have personal knowledge of the facts set forth herein. If called upon to testify, I
could and would testify as follows.
3. I hold a bachelor’s degree in electrical engineering from the University of Michigan
and a master’s degree in computer engineering from Santa Clara University. I have been working as
a software engineer since 1989.
4. I have been employed as an engineer with Sun Microsystems, Inc. (“Sun”), now
Oracle, since approximately 1994. Through my years of working at Sun, I have become very familiar
with the Java technology, and I have helped to design and improve the Java platform as part of my
regular work responsibilities at various points throughout my tenure at Sun, now Oracle. I now work
primarily with Java ME technology, including the editions of Java that run on smartphones, cell
phones, and embedded devices. I am the inventor of several patents related to Java technology. In
addition, my work at Sun and now Oracle has included development of a smartphone platform for a
third party customer. As a result of my work over the years, I am quite familiar with and
knowledgeable about the technical requirements of mobile devices in general and smartphones in
particular.
5. For example, in addition to my ordinary work with Java ME, I was one of the
engineers involved in the actual Sun-Google negotiations in the 2005–2006 time frame, when I was
involved in planning the technical specifications, as well as estimating the work effort involved for
some of the tasks that were required, for the mobile platform that the parties jointly considered
developing and marketing. At that time, I was also responsible for advising Sun executives on the
technical components that Sun could offer and that were essential to a smartphone platform such as
Android. In the course of those negotiations, I participated in technical meetings with Google
engineers to determine what Google’s requirements were for the Android platform and what portions
of Sun’s Java technologies would be important in that effort. I also participated in face to face
meetings with Google’s Andy Rubin concerning the negotiations.
1
6. I was therefore employed at Sun, and knowledgeable about the Java technology, in the
2006 time frame, when Sun and Google were actually negotiating for a Java license for Android.
7. In addition to the experience I outlined above, I have direct experience with a number
of Java patents, and have direct experience with the performance benefits that certain Java patents
provide. I have ranked patents in terms of their engineering performance before.
8. I, along with four of my colleagues at Oracle, was asked by counsel for Oracle to
conduct an analysis of certain patents held by Sun Microsystems, Inc. in the spring of 2006.
Specifically, counsel requested that we determine which of Sun’s Java patents would have been
potentially relevant to a smartphone platform in 2006, and then determine which of those patents
would have been expected, from an engineering perspective, to provide the greatest benefits to such a
platform.
9. Along with the other engineers, I concluded that we could provide the analysis
requested by counsel through the following steps:
- Identify relevant “blocks” of technology corresponding to functions that would be
expected to be useful to a smartphone platform in 2006;
- Identify what subset of Sun’s patent portfolio would have been useful to a smartphone
platform in 2006;
- Assign those potentially relevant patents to the technology blocks;
- Rank the relative importance of those technology blocks; and
- Rate each of the patents on a three-point scale.
10. I was not asked to provide any economic valuation of the patents in suit. Instead, my
analysis of “value” was confined to the engineering benefit that the patents would be expected to
provide a smartphone platform.
11. Throughout the process, I understood that Dr. Mark Reinhold was the leader of the
team. I understood that he would make all final decisions, and that I was helping him to review the
patents in the interest of time and to ensure that the final analysis was as accurate and comprehensive
as possible.
2
12. Dr. Reinhold asked me to begin working on this project on or about January 24, 2012.
I had not done any work for Prof. Cockburn prior to that date.
13. At the outset of the process, I understand that George Simion of Oracle ran searches
through Sun’s patent databases to acquire a list of over 1,300 Java related patents that we were to
review. I reviewed this list to make sure that it included all of the patents that I would expect to see,
and confirmed that it did.
14. In the first step of the process, our team, led by Dr. Reinhold, identified 22 technology
blocks that would have been relevant to a smartphone platform in 2006. We brainstormed the list of
logical functional components on or about January 24, 2012; over the course of the next few days, we
refined that list to come up with the final list of 22 blocks.
15. In order to contribute to this exercise, I used my personal experience, expertise,
understanding of Google’s objectives in 2006 based on a Product Requirements Document that I
understand Google provided to Sun in 2006, and knowledge of the Java platform. I am confident that
the 22 technology blocks that we identified represent the full range of Java technology that would
have been relevant to a smartphone in 2006.
16. In the second step of the process, our team as a whole, led by Dr. Reinhold, reviewed
every one of the patents in the list of 1,300+ patents captured by the searches discussed above to
determine which patents would have been relevant to a smartphone platform in 2006.
- Our team divided up the group of 1,300+ patents to ensure that every patent was
evaluated by at least one person. We could not all look at every patent because of
limitations on time. I personally looked at each patent I was assigned to evaluate with
care, and I have no reason to believe my colleagues did not do the same.
- We reviewed the patents by looking at the titles, abstracts, descriptions, application
dates, and inventor names. When we believed it would be useful to do so, we also
reviewed the specifications and the claims by retrieving the patent from the USPTO
web site. This is a reasonable way to ascertain a patent’s rough usefulness in a
smartphone, because, in my experience, the abstract and description are written by
engineers, will provide the most useful information to another engineer, and will
3
explain the general purpose of a patent and its claimed invention with enough
specificity to understand its scope, application, and potential advantages. In contrast,
in my experience information in the claims is less useful.
- Although reviewing and categorizing the patents was time-consuming, it was not hard.
Patents filed by Java engineers relating to improvements in Java technology use
familiar terms, and in many cases I myself or another member of the team had direct
experience with the invention or implementations of the invention.
- I finished reviewing my portion of the 1,300+ patents on or about January 26, 2012.
- When we had finished classifying each patent we were assigned to review, the
members of the team who had special expertise with one or more of the technology
blocks reviewed and confirmed the accuracy of our categorization. We discussed any
inconsistently classified patents, and discussed any patents that I or one of my
colleagues had indicated needed further attention or discussion.
17. At the end of this part of the process, I again reviewed the final list of all patents that
could have been relevant in a smartphone platform in 2006. The final responsibility for deciding on
the list of potentially relevant patents fell to Dr. Reinhold. After this process, Dr. Reinhold
determined, and I agreed, that 569 patents out of the original 1,300+ would, in fact, be potentially
relevant to a smartphone platform in 2006, and had classified each of those patents into one of the 22
groups.
18. In the third step of the process, our team, led by Dr. Reinhold, ranked the 22
technology groups. We distinguished among them by determining the benefits they would be
expected to provide a smartphone platform in terms of speed, startup, footprint (i.e. memory
requirements), and security.
- We determined that these four criteria were reasonable criteria on which to rank the
patents because software patents in the Java portfolio are almost always designed to
provide one of these benefits. In my experience, and based on my knowledge of the Java
platform, if I were to consider what benefits I would want to provide a Java-based
4
smartphone in 2006, these are the criteria I would choose. These are the criteria that we
routinely used at Sun and now at Oracle to evaluate our own Java implementations.
- We ranked these groups independent of the patents that were contained within them.
- Based on our ranking system, two or more groups occasionally tied.
19. We had completed this process on or about January 31, 2012.
20. In the fourth step of the process, our team, led by Dr. Reinhold, reviewed the specific
patents, and evaluated each patent on a three-point scale, in which the best score was a 1. The ratings
reflected the benefit that our team, led by Dr. Reinhold, would have expected the patented inventions
to provide a smartphone platform in 2006. The top rating, a 1, was reserved for those patents that
were either required by the Java platform specification for compatibility, or that would bring an order
of magnitude improvement to the key metrics of speed, startup, footprint, or security. The middle
rating, 2, was assigned to patents that would bring a significant improvement to the key metrics of
speed, startup, footprint, or security. The bottom rating, 3, was assigned to patents that would have
been relevant but would not have provided the benefits of a 1 or 2 rated patent.
21. By the time we began to rate the patents, we had reviewed many of them multiple
times, in addition to our pre-existing familiarity with the underlying inventions. Again, I am
confident that we had sufficient information to make an informed engineering assessment of the
likely benefits of each patent. I and other senior engineers at Oracle, including each of the other four
engineers on this assignment, regularly are called upon to make assessments of proposed innovations
and improvements to Java technology. I and other engineers frequently make those assessments
using information that is no more detailed than what is disclosed in the patent abstracts and
descriptions. In addition, I was able to apply my own knowledge of how the inventions had been
implemented, and the engineering benefits (or lack thereof) that resulted. The other engineers often
had similar experiences that they shared with the team as we reviewed the patents and that informed
our collective assessment. I agreed with all of the ratings that we settled on as a group.
22. In summary, we concluded:
- A group of 569 patents would be relevant to a smartphone in 2006.
- Those 569 patents fit into 22 technology groups.
5
- The most important technology group is the Boot group.
- There were seven patents ranked as 1 in the Boot group.
- The second most important technology group is the JIT group.
- There were twelve patents ranked as 1 in the JIT group.
- The third most important technology group is the interpreter group.
- There were three patents ranked as 1 in the interpreter group.
- It would not be possible, based solely on engineering considerations that would be
knowable in 2006, to say which of the 22 patents we identified in the top three groups
was the most or least valuable to a smartphone platform such as Android.
23. I believe that both the process we employed, and the results we came to, are
reasonable and accurate. If I were on a team assigned to design a Java-based smartphone platform in
2006, the three most important groups of technology in terms of startup, speed, and footprint would
have been boot, JIT, and interpreter.
24. I am confident that the team had sufficient time and information to ascertain the
correct rating for each patent, and that we had the collective expertise with the Java platform to
understand the relative importance of every one of the technology groups in a smartphone platform in
2006 and every one of the patents in the list of 569. I do not believe that there is anyone at Oracle
that we could have added to the team who would have improved the accuracy of the process or the
results.
25. Although I have some knowledge of the Android platform, and I have assisted lawyers
in analyses to determine whether Android infringes Oracle’s patents, neither aspect of that work had
any effect on my work for this assignment. My assistance in that regard was not confined to the
seven patents on which Oracle has sued Google – I had looked at numerous other Java patents as
well. I understand that Google has also claimed in papers filed with the Court I and my colleagues
are “the very engineers who selected litigation patents at the outset.” I know that statement to be
false with respect to me. I have never selected any patents for this litigation or any other.
26. I understand that Google has also claimed in papers filed with the Court that I and my
colleagues “admitted in deposition that they spent next to no time compiling their rankings and were
6
influenced by their prior work in this case.” I understand that Google also asserts in its papers that I
and my colleagues “favor[ed] the patents they had already analyzed as part of this case.” I know that
all of those assertions are entirely untrue with regard to me, and are contrary to everything I observed
as I watched my colleagues perform their work alongside me. Together we spent significant time
categorizing, evaluating, and rating the patents, and applied decades of directly relevant engineering
experience to do so. There was sufficient time to do the analysis that we were asked to do, and to do
so in a reliable and responsible manner. I did not “favor” any of the asserted patents for any reason
related to the litigation, and I was not “influenced” by my prior work in the litigation. The assistance
I provided to help determine whether Android infringes Java patents did not cause me to miscategorize
any patent, nor did it cause me to rate any patent higher or lower than its technical merits
warranted. I considered each patent and technology group based on the objective engineering benefit
I would have expected it to provide to a smartphone platform in 2006, in light of my engineering
experience and my knowledge of Java technology as described above.
I declare under penalty of perjury that the foregoing is true and correct.
DATED: February 23, 2012
/s/ Hinkmond Wong
HINKMOND WONG
7
ATTESTATION OF FILER
I, Steven C. Holtzman, have obtained Hinkmond Wong’s concurrence to file this document
on his behalf.
Dated: February 24, 2012
BOIES, SCHILLER & FLEXNER LLP
By: /s/ Steven C. Holtzman
Steven C. Holtzman
Attorneys for Plaintiff
ORACLE AMERICA, INC.
8
748
[Keker & Van Nest LLP letterhead]
February 24, 2012
VIA ECF
Honorable William Alsup
U.S. District Court, Northern District of
California
Courtroom 8 - 19th Fl.
450 Golden Gate Avenue
San Francisco, CA 94102
Re: Oracle America, Inc. v. Google Inc., No. 3:10-cv-03561 WHA
Dear Judge Alsup:
In light of yesterday's order instructing counsel to keep the period from April 16 until late June available for trial, I am writing to re-notify Your Honor of two conflicting federal trial commitments on my schedule during that period. Both trials were set prior to the December 21, 2011 pretrial conference in this case, and they were set forth in the joint pretrial statement and discussed at the pretrial conference. In understand from Your Honor's remarks during th hearing that I am to notify the Court of any changes in this schedule.
I am presently scheduled to commence trial in Commonwealth Scientific and Industrial Research Organisation v. Lenovo, Inc. et al., Case No 6:09-cv-399 LED (Hon. Leonard Davis) on April 2, 2012. The trial is expected to last for approximately three weeks, and the pretrial conference is set to occur on March 22.
I am also set for trial in Genentech v. The Trustees of the University of Pennsylvania, 5:10-cv-02037 LHK (PSG) (Hon. Lucy Koh) on June 11, 2012. Judge Koh recently advised us that she expects the trial to last through the end of June, and she has scheduled a bench trial concerning certain issues on June 29, 2012. The pretiral conference in that case is schedule for May 30.
I am also planning to be out of the country from April 26 through May 12, but I understand from Your Honor's remarks during the pretrial conference that, if my conflicting trial commitments are vacated or reschedule, you might insist that trial proceed notwithstanding.
Honorable William Alsup
February 24, 2012
Page 2
I will notify the Court of any changes in this schedule, and I am continuing to hold the period September - December available, as Your Honor requested. In the meantime, if I have misunderstood Your Honor's instructions, please let me know.
Sincerely,
KEKER & VAN NEXT LLP
Robert A. Van Nest
Robert A. Van Nest
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Authored by: complex_number on Monday, February 27 2012 @ 03:15 PM EST |
no 'on topic' posts please.
---
Ubuntu & 'apt-get' are not the answer to Life, The Universe & Everything which
is of course, "42" or is it 1.618?
[ Reply to This | # ]
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Authored by: complex_number on Monday, February 27 2012 @ 03:18 PM EST |
Don't forget to add a click to the original post.
You will need to change your post mode to HTML!
---
Ubuntu & 'apt-get' are not the answer to Life, The Universe & Everything which
is of course, "42" or is it 1.618?
[ Reply to This | # ]
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Authored by: complex_number on Monday, February 27 2012 @ 03:20 PM EST |
Please post the 'before' and 'after' so that the corrections can be made to thr
article.
---
Ubuntu & 'apt-get' are not the answer to Life, The Universe & Everything which
is of course, "42" or is it 1.618?
[ Reply to This | # ]
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Authored by: complex_number on Monday, February 27 2012 @ 03:22 PM EST |
Keep up the good work.
Instructions on how to do the work are contained in the link on the left.
---
Ubuntu & 'apt-get' are not the answer to Life, The Universe & Everything which
is of course, "42" or is it 1.618?
[ Reply to This | # ]
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Authored by: Anonymous on Monday, February 27 2012 @ 03:24 PM EST |
35. Google ignores this external validation, however, and instead states that
“almost one quarter of all respondents claimed that they would prefer a
smartphone costing $200 to a putatively identical smartphone costing
$100.” (emphasis added.) What Google offers as “proof in the pudding” is not
only technically wrong, but it is also a gross misstatement of my
survey.
39. ........ When these respondents with such utility
comparisons are excluded from the analysis, only 8.8 percent of respondents, not
24 percent, prefer a price of $200 over a price of
$100.
Dr. Shugan: My report is only slightly less absurd than
what Google said!
[ Reply to This | # ]
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Authored by: designerfx on Monday, February 27 2012 @ 03:39 PM EST |
after the whole blog from Hinkmond saying Android is not Java,
they basically gutted his testimony almost entirely.
Coincidence?[ Reply to This | # ]
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Authored by: Anonymous on Monday, February 27 2012 @ 04:29 PM EST |
.... Prof. Cockburn explains how Oracle asserts the same infringement theory
for every asserted claim of each patent, and concludes that each of the asserted
claims in any of the patents-in-suit should account for the full value
associated with each of the patents-in-suit.
Prof. Cockburn’s
report does not fail to apportion damages on a claim-by-claim basis
....
How can Oracle possibly get away with blatantly lying in a
court document like this?
They specifically say that each claim accounts
for the full value, and then turn around and say that they have apportioned
value claim by claim!!!
Here is the full paragraph so you can judge for
yourself:
Prof. Cockburn’s revised report considers and addresses the
issue of calculating damages on a claim-by-claim basis. (Report ¶¶ 493-533.)
Based on input from Prof. Mitchell, Prof. Cockburn explains how Oracle asserts
the same infringement theory for every asserted claim of each patent, and
concludes that each of the asserted claims in any of the patents-in-suit should
account for the full value associated with each of the patents-in-suit. (Id. ¶¶
494-95.) Prof. Cockburn’s report does not fail to apportion damages on a
claim-by-claim basis, but rather explains, based on the evidence and input from
Prof. Mitchell, how damages should be calculated if the jury finds Google liable
on some but not all asserted claims.
[ Reply to This | # ]
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Authored by: Anonymous on Monday, February 27 2012 @ 04:44 PM EST |
Given that nobody can tell for sure what the patent describes, how can you tell
its value? Even Oracle cannot tell whether the patent is for: a) a method, b) a
machine or c) a computer-readable medium. It seems that, because they could not
figure out which description would be most likely to pass the subject-matter
eligibility test, they wrote it down in all three ways, betting that at least
one of the descriptions would be found eligible by a trier of fact.
I think they knew full well that what they were patenting was not patent
eligible subject matter and that the only way to get a patent was to obfuscate
that fact by claiming a, b or c.
So in a sense, there is no intrinsic value to these patents and the damage
experts should tell the court. Would take a lot less paper than what they are
doing now.[ Reply to This | # ]
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Authored by: Anonymous on Monday, February 27 2012 @ 07:16 PM EST |
If the copyright value is subsumed by the future development effort of Sun,
then doesn't that mean that Oracle is claiming no damages due for their
copyright portion? Since they only have a handful of claims left and each
claim is worth 100% of the patent, then those claims that failed diminish the
damages for that patent 100%. Have more claims been invalidated then have
survived? Then this means that Oracle owes Google those damages? (OK,
fantasy world of logic.)
(P.s. title is reference to old US commercial by a hamberger joint when an
old lady opens the bun and proclams "Where's the beef?")[ Reply to This | # ]
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Authored by: Anonymous on Monday, February 27 2012 @ 10:16 PM EST |
- Google contends Prof. Cockburn’s conclusion that the patents
in suit account for at least 25% of the value of the 2006 Bundle is
impermissibly subjective because the figure is not based on a “quantitative
algorithm or formula.” But “[t]here is no mathematical formula for the
determination of a reasonable royalty.”
- Google argues that Prof.
Cockburn’s use of 25% is an improper attempt to rely on the “25% rule of thumb”
royalty rate that the Federal Circuit rejected in Uniloc. But this argument
ignores that the independent significance approach does not calculate a
royalty rate; it simply apportions the 2006 Bundle. Moreover, Prof.
Cockburn relies on no rule of thumb; he examines the specific evidence in this
case to determine proper apportionment
percentages.
So... the professor examines the evidence,
then thinks "25% sounds about right, I like that number", and then puts down
that number? I am with Google there, he should at least try to come up
with a number that he can explain.[ Reply to This | # ]
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Authored by: Anonymous on Monday, February 27 2012 @ 10:39 PM EST |
First, Google claims that Prof. Shugan’s selection of features to be
tested was driven by litigation. This argument is both false and irrelevant.
Before including any of the features relevant to this litigation, Prof. Shugan
first confirmed that the features were actually relevant to consumer choice,
through interviews, market research, a focus group, industry analyst reports and
buyers’ guides, as he explained in his deposition. (Shugan Decl. ¶¶ 22–24;
Shugan Report p. 7–8, App’x D at 5–6.) After he identified 36 features that
real-world consumers said mattered in making a purchasing decision, Prof. Shugan
did include features in his survey that were not at issue in this litigation,
including brand and price. It is not necessary in conjoint analysis to test
every distinguishing feature that may matter to consumers, because conjoint
assesses relative importance. (Shugan Decl. ¶
25.)
So:
- Prof. Shugan selects smartphone features based on
litigation (at least 36)
- He then cuts down the list to 36 consumer- and
litigation-relevant features
- He then adds a few (two mentioned) features in
the mix, and uses this 36+x feature list as a basis (x=2?)
IANAL, but
somebody explain to me how this makes the feature list selection
not driven by litigation?[ Reply to This | # ]
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Authored by: Ian Al on Tuesday, February 28 2012 @ 04:23 AM EST |
There are many versions of Java currently documented by Oracle:
Java SE 7
Java SE 6
J2SE 5.0
J2SE 1.4.2
J2SE 1.3.1
Java EE 6
Java EE 5
J2EE 1.4
J2EE 1.3
J2EE 1.2.1
Java ME
Of these only J2SE 1.4 and Java 2 Standard Edition Version 5 are asserted in the
case (Exhibit H in Oracle's Amended Complaint). One might have expected the ME
version to have been asserted as this is the Java system for mobile devices.
----------------------------
Certificate of Registration
TITLE OF THIS WORK
Java 2 Standard Edition 1.4
PREVIOUS OR ALTERNATIVE TITLES
J2SE 1,4m Java 2 Platform, Standard Edition, v 1.4, Java 2 Standard Edition
Software Development Kit 1.4, SDK 1.4
... NATURE OF AUTHORSHIP
New and revised computer code and accompanying documentation and manuals
DERIVATIVE WORK OR COMPILATION
Prior works by claimant and licensed-in components.
----------------------------
Certificate of Registration
TITLE OF THIS WORK
Java 2 Standard Edition Version 5
PREVIOUS OR ALTERNATIVE TITLES
J2SE 5.0 Java 2 Platform, Standard Edition, Version 5.0 Java 2 Standard Edition
5.0 Software Development Kit, J2SE Development Kit, JDK 5.0
... NATURE OF AUTHORSHIP
New and revised computer code and accompanying documentation and manuals
DERIVATIVE WORK OR COMPILATION
Prior works by claimant and licensed-in components.
----------------------------
The copyright registrations encompass every part of the Java system including
the Software Development Kit in which the APIs for the version are documented.
Google have not infringed on the registered copyrights because they have not
copied one or more of the entire registered distributions.
My thoughts are that the literally copied lines and files are not included in
the registrations because they are not formally part of the Java system. Apart
from these, the asserted copyrights are 'elements of the 37 Java API design
specifications [copied] into Android software or documentation' out of a total
of around 160 to 200 packages. Those 37 'design specifications' are packages
containing thousands of individual APIs.
So, the asserted copyrights are a tiny proportion of the total API's in the
asserted packages, but Oracle are using the value of the entire registered
copyrights in two of the versions of Java as the starting point to damages. Do
all of the versions have the same total value? Is the ME versions that might be
appropriate to Android less or more valuable? Why is the value of the Standard
Editions relevant to the Android mobile devices?
Oracle should remember that each entire registration only relates to an entire
version of Java. The individual components are individually copyrighted and
those copyrights are not registered.
Is there a single copyrighted document for each package? We don't know because
Oracle have destroyed the website that they claim was copied. Does one copyright
apply to every html document on a website or only on the copyright marked html
document (aka, web page)? I think it only applies to one web page. Only when
several pages are published as a book or magazine or newspaper can one copyright
apply because they are single publications.
So, Oracle are accusing Google of copying a few out of tens of thousands of API
definitions. The API definitions are only a small part of the API because the
API includes the copyright source code. The complete API is still only a tiny
portion of the whole registered Java platform and Oracle only assert two out of
11 currently supported Java platforms, and the wrong ones, at that.
An honest evaluation of the value of the actual, alleged, copied materials as a
proportion of the entire Java SE system would be vanishingly small. It's is not
worth the effort of calculation. Google copied the Apache-licensed, Harmony
copyrighted materials.
---
Regards
Ian Al
Software Patents: It's the disclosed functions in the patent, stupid![ Reply to This | # ]
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Authored by: NigelWhitley on Tuesday, February 28 2012 @ 12:45 PM EST |
Three paragraphs from Oracle's Opposition
Top of page 3
"Google argues that Prof. Cockburn failed to account for unasserted claims
within the asserted patents. But the Court’s requirement that Oracle separately
calculate damages for the asserted claims was for purposes of determining a
verdict if some asserted claims were more valuable than others, or if some
claims were later found to be invalid. Prof. Cockburn was not required to
calculate a value for every claim, asserted and unasserted, of a patent,
particularly when neither real nor hypothetical negotiators in 2006 would have
done so."
page 18
"Reducing the value of the patents-in-suit based on the presence of some
unasserted claims makes no sense where the relevant inquiry is one of
apportionment – what proportion of the 2006 Bundle value the parties would have
assigned to those patents. Parties to an actual licensing negotiation would not
have evaluated every claim – certainly Google and Sun never negotiated over
individual claims – and there is no reason to do so now. (Report ¶¶
336-37.)"
and later on that page
"Google suggests that Oracle’s decision to narrow the number of claims in
suit somehow proves that Prof. Cockburn’s analysis is flawed, because Oracle
“cannot be heard to argue that those [no longer asserted] claims have no value
to Google.” (Dkt. 718 at 14.) But it is not Oracle’s or Prof. Cockburn’s
position that those claims had no value to Google. Rather, it is Prof.
Cockburn’s opinion that the claims would have no additional value to Google,
above and beyond that of the asserted claims. The evidence indicates that the
different claims each address the same functionality."
We have previously seen BSF's skill at tap dancing to cover up the deficiencies
in their case. IANAL and nor am I a Java engineer but I find these quoted
paragraphs perplexing. A little background first
IMHO Oracle's description of the process they followed in selecting the patents
to litigate appears to be
i) decide what features/technologies would be relevant to a smartphone in 2006
ii) search through Sun's Java patents from that time which related to those
features/technologies
iii) pick the best patents they had ie the must-have elements of a 2006
smartphone which used Java.
As to evaluating them in economic terms, according to Hinkmond Wong,
"It would not be possible, based solely on engineering considerations that
would be knowable in 2006, to say which of the 22 patents we identified in the
top three groups was the most or least valuable to a smartphone platform such as
Android."
In other words, the engineers could not rationally apportion value between these
patents. So, Dr Cockburn doesn't know the tech and the tech guys say they
couldn't provide a relative worth to the patents they helped choose to sue over.
Which leads us to the question, what could Dr Cockburn base his apportionment
on?
I think the three paragraphs I have quoted confirm that Dr Cockburn had nothing
to base it on and so he couldn't do any sensible apportionment. He is left
trying to stand up for Oracle's headline grabbing numbers, when the facts he's
standing on keep falling away. The BSF/Cockburn line seems to be that the
patent claims all do the same thing (which I believe they would describe as
"techy stuff") and you can't do any Java smartphone thingy unless you
have all of it, so there. Let me expound.
The first and second quotes say that Prof Cockburn ignored unasserted claims in
the patents, that his valuation based on all the claims is the same as that of
just the asserted claims. So either Sun was producing patents in which sections
of their patents had no value ie were worthless, or Dr Cockburn believes that
1+1=1. We shall be generous to Dr Cockburn and assume he can do basic
artithmetic. Therefore Sun was relying on patents (and these are the best they
could find, remember) where claims were worthless or at least duplicative. This
is supported by the third quote where Oracle state that the current and earlier
claims "each address the same functionality". But an entire patent has
been lost from the case and yet Oracle/Cockburn state that no functionality has
been lost. That means that the experienced, expert engineers who evaluated the
patents, who used their intimate knowledge of the area to help pick out the most
suitable patents to cover the important features/technologies, apparently failed
to notice that one those seven patents was merely a duplicate of the others.
They could pore over 1300 patents in a few days, sorting the wheat from the
chaff, but couldn't look through seven patents and see one was simply a waste of
everybody's time. Seriously? Not one of the four expert engineers or their
super-expert boss, who talked directly to Dr Cockburn, seems to have realised
that one of their magnificent seven patents was Brad Dexter and not really
needed.
So do all the remaining claims do the same thing too? The rate at which Oracle
are shedding patent claims from PTO challenges suggests that they may have to
hope that the few left standing are actually super-claims which cover the other
100+ claims the expert, experienced engineers said they absolutely, definitely
needed for a Java smartphone too. Because no matter how many of Oracle's
valuable, critical, innovative patent claims get tossed out of the case, Dr
Cockburn seems to think it does not diminish the money they are due. The Judge
seems determined to give Oracle enough rope to hang itself - I just wonder if he
has the resolve to kick away the chair.
----------------
Nigel Whitley[ Reply to This | # ]
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- Translation - Authored by: Anonymous on Wednesday, February 29 2012 @ 03:16 PM EST
- Dancing on air - Authored by: Anonymous on Friday, March 02 2012 @ 04:41 AM EST
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