A federal judge for the Southern District of California rang in the month of February by ordering plaintiffs in a patent related case to pay a whopping $12 million in attorney fees. The award included more than $2.8 million in “computer assisted” review fees and to add insult to injury, the judge tacked on an additional $64,316.50 in Rule 11 sanctions against defendants’ local counsel. Plaintiffs filed a notice of appeal on February 13th, but regardless of the final outcome, the case is chock-full of important lessons about patent litigation, eDiscovery and the use of predictive coding technology.
In Gabriel Technologies Corp. v. Qualcomm Inc., plaintiffs filed a lawsuit seeking over $1 billion in damages. Among its eleven causes of action were claims for patent infringement and misappropriation of trade secrets. The Court eventually dismissed or granted summary judgment in defendants’ favor as to all of plaintiffs’ claims making defendants the prevailing party and prompting Defendants’ subsequent request for attorneys’ fees.
In response to defendants’ motion for attorney fees, U. S. District Judge Anthony J. Battaglia relied on plaintiffs’ repeated email references to “the utter lack of a case” and their inability to identify the alleged patent inventors to support his finding that their claims were brought in “subjective bad faith” and were “objectively baseless.” Given these findings, Judge Battaglia determined that an award of attorney fees was warranted.
The Attorney Fees Award
The judge then turned to the issue of whether or not defendants’ fee request for $13,465,331.01 was reasonable. He began by considering how defendants itemized their fees which were broken down as follows:
- $10,244,053 for its outside counsel Cooley LLP (“Cooley”);
- $391,928.91 for document review performed by Black Letter Discovery, Inc. (“Black Letter”); and
- $2,829,349.10 for a document review algorithm generated by outside vendor H5.
The court also considered defendants’ request that plaintiffs’ local counsel be held jointly and severally liable for the entire fee award based on the premise that local counsel is required to certify that all pleadings are legally tenable and “well-grounded in fact” under Federal Rule of Civil Procedure 11.
Following a brief analysis, Judge Battaglia found the overall request “reasonable,” but reduced the fee award by $1 million. In lieu of holding local counsel jointly liable, the court chose to sanction local counsel in the amount of $64,316.50 (identical to the amount of local counsel’s fees) for failing to “undertake a reasonable investigation into the merits of the case.”
Three Lessons Learned
The case is important on many fronts. First, the decision makes clear that filing baseless patent claims can lead to financial consequences more severe than many lawyers might expect. If reviewed and upheld on appeal, counsel in the Ninth Circuit accustomed to fending off unsubstantiated patent or misappropriation claims will be armed with an important new tool to ward off would-be patent trolls.
Second, Judge Battaglia’s decision to order Rule 11 sanctions should serve as a wake-up call for local counsel. The ruling reinforces the fact that merely rubber-stamping filings and passively monitoring cases is a risky proposition. Gabriel Technologies illustrates the importance of properly monitoring lead counsel and the consequences of not complying with the mandate of Rule 11 whether serving as lead or local counsel.
The final lesson relates to curbing the costs of eDiscovery and the importance of understanding tools like predictive coding technology. The court left the barn door wide open for plaintiffs to attack defendants’ predictive coding and other fees as “unreasonable,” but plaintiffs didn’t bite. In evaluating H5’s costs, the court determined that Cooley’s review fees were reasonable because Cooley used H5’s “computer-assisted” review services to apparently cull down 12 million documents to a more reasonable number of documents prior to manual review. Although one would expect this approach to be less expensive than paying attorneys to review all 12 million documents, $2,829,349.10 is still an extremely high price to pay for technology that is expected to help cut traditional document review costs by as much as 90 percent.
Plaintiffs were well-positioned to argue that predictive coding technology should be far less expensive because the technology allows a fraction of documents to be reviewed at a fraction of the cost compared to traditional manual review. These savings are possible because a computer is used to evaluate how human reviewers categorize a small subset of documents in order to construct and apply an algorithm that ranks the remaining documents by degree of responsiveness automatically. There are many tools on the market that vary drastically in quality and price, but a price tag approaching $3 million is extravagant and should certainly raise a few eyebrows in today’s predictive coding market. Whether or not plaintiffs missed an opportunity to challenge the reasonableness of defendants’ document review approach may never be known. Stay tuned to see if these and other arguments surface on appeal.