Legal Analytics involves the use of data to make predictions that inform decisions made in both the business of law (law firm marketing and law department operations/outside counsel selection) and the practice of law (litigation and transactions).
I believe data-centric lawyering represents the biggest change in law since research moved from books to computers. I like to call this shift to a data-based approach “Moneyball for lawyers,” a reference to Michael Lewis’s popular book (and the movie) of the same name. In my view, analytics is changing law just as dramatically as rigorous statistical analysis has changed the way baseball teams evaluate and field talent.
Legal Analytics brings objective rigor to the traditionally subjective business and practice of law.
Increased availability of litigation data, including dockets and documents, makes Legal Analytics possible. Sources include the US Public Access to Court Electronic Records (PACER) system, the International Trade Commission’s (ITC) EDIS platform and the United States Patent and Trademark Office (USPTO) Patent Trial and Appeal Board.
Data from these and other sources enables lawyers to make data-driven decisions that were previously based on what I call “anecdata.”
Legal Analytics can influence every step of the dispute resolution process, helping companies select and manage outside counsel, law firms land clients, and attorneys from both camps craft successful case strategy and drive results. The data sources currently available make analytical approaches especially useful for IP litigation, and these approaches are particularly powerful in the early stages of litigation, where there are many unknowns that can complicate decision-making.
Evaluating the behavior of adversaries
Before a demand letter is ever drafted, plaintiffs and their attorneys must analyze not only who has caused the harm and who has the deepest pockets, but also how prospective defendants will react to a claim. One obvious measure is the prior litigation behavior of a defendant. A good Legal Analytics platform can easily provide that information and reveal meaningful patterns to provide important insights. But it’s always possible the defendant has never before been sued, at least about the subject matter of the plaintiff’s claim. Legal Analytics allows lawyers to quantify and analyze the behavior of similar defendants faced with similar claims. For example, a patent holder asserting a claim of infringement about a patent that has never before been litigated—and/or against a party that has never before been sued for infringement—can extract predictive insights out of the litigation behavior of similar parties in similar patent lawsuits. That can give the plaintiff a decisive advantage.
Similarly, defendants and their attorneys can look to data to inform their response to a demand letter or complaint. Data about the behavior of peer companies in similar litigation can confirm or cause adjustments to a litigant’s behavior. Perhaps the plaintiff has brought other similar lawsuits. If so, how did the plaintiff behave at each stage of litigation? What was the outcome? How have other defendants responded to the plaintiff or similar plaintiffs with similar claims or behaviors, and what were the outcomes in those cases? Legal Analytics can provide fact-based answers to each of these questions, providing the starting point for a winning case strategy.
Legal data can even be the basis for a proactive strategy for companies who desire a better view of their standing in relation to competitors. One large technology company known for its aggressive responses to patent lawsuits commissioned a comparative study of its patent litigation behavior and the behavior of 15 of its peers. Subjects studied included case volumes, case types, products at issue, venues, settlement volumes, case phase at settlement, settlement rates, chances of early settlement, number of cases stayed pending re-examination of the patent at issue by the USPTO, overall case outcomes, win/ loss rates and damages awarded. The results showed a wide variety of behaviors and outcomes, even in response to similar claims by similar plaintiffs. Some companies settled early. Others fought every claim to the bitter end. But the bottom line is that the data revealed an optimized combination of spending and tactics that would otherwise have been impossible to know and deploy.
Analyzing venues and judges
Once litigation is under way, every step in the process can be informed by data that improves a party’s chances of winning, while at the same time minimizing unnecessary legal spending. For plaintiffs, establishing jurisdiction by a court with both a measurable track record favoring plaintiffs with similar claims, as well as one that moves faster and more often to a jury trial, can have more impact on the outcome of litigation than any subsequent tactics. For a defendant moving for transfer of venue, quantifying the arguments that have succeeded in the past with a specific judge can propel the case out of an unfriendly environment and into one where similar defendants more frequently prevail.
In fact, a close look at the behavior of specific judges based on data can inform important tactical decisions that can turn a case early in the process. For example, in-house attorneys for a large pharmaceutical company had heard anecdotally that the judge presiding over their patent case often ruled on claim construction solely on the briefs, without holding a hearing, but couldn’t be sure the anecdotes were true. Before designing and executing its claim construction strategy, they obtained data revealing the judge did indeed rule on claim construction without a hearing more than 80 percent of the time in pharma patent litigation. Knowing that, the company could confidently decide to include all of its arguments in its brief, holding nothing back for a hearing that was likely never to happen.
Analysis of judges can also involve assessments of trial time and preparation for trial. Facing a non-practicing entity (NPE) matter in a particular district, a large technology firm already knew that trial time would be relatively short, so time would have to be carefully divided between direct examination of its own witnesses and cross-examination of opposing witnesses. Using Legal Analytics, the company found a number of prior orders from the judge and used that information to calculate the likely trial time the judge would give for the case, and thus was able to make an informed decision in advance about how to split that time with the plaintiff and co-defendants. Similarly, judge- or venue-specific data about average time to termination and time to trial can help legal teams estimate legal costs and the time counsel will invest in a case.
The day is close at hand when statistics for the players and teams in the legal game will be as ubiquitous and impactful as statistics for ballplayers and sports teams. A lawyer’s track record on judgment calls in advising clients is no longer a mystery, and likewise a firm’s track record in specific kinds of cases and particular venues is becoming knowable and subject to analytical insight. Lawyers and law firms, parties and their law departments, and districts and judges will all be subject to statistical analysis and performance rankings. All these players will, in turn, use Legal Analytics to compete more vigorously with each other.
The legal profession will become more economically efficient and transparent, delivering better results for those most in need of legal services. While some traditionalist lawyers may resist the application of Legal Analytics to law, those who embrace it, especially today’s early adopters, are likely to gain significant and lasting competitive advantage. While they may not win the Commissioner’s Trophy, they will win the client, transaction or case – the ultimate goal of every lawyer.