Re-imagining Civil Litigation with Judicial Analytics

BY

Nicole Clark

Artificial intelligence (AI) has brought a new level of transparency to the legal profession. Using machine learning and natural language processing, legal analytics platforms like Trellis Research, Ravel Law, and Premonition have remapped the ways in which attorneys conduct legal research. These three companies have curated their own archives of state trial court records, compiling and synthesizing data from multiple counties and multiple states in ways that allow attorneys to collect information about the judges assigned to their cases.

Ten years ago, there was no simple way for an attorney to illustrate the patterns and the tendencies of their assigned judge. Things are different now. With AI-backed legal analytics, attorneys can interact with charts, graphs, and other easy-to-grasp visualizations in order to understand how their judge has previously handled the cases assigned to his or her dockets. An attorney can know—in a single glance—with whom a judge tends to side in different types of motions and matters. They can also know how long those decisions typically take. Here’s just a sampling of use cases.

 

Judge Dashboard

It all starts with a judge dashboard. This is the place where attorneys can study an assigned judge’s caseload, with charts indicating the number of cases they have active as well as the average duration and the type of practice area of those cases. These figures, culled from thousands of data points from court dockets, enable attorneys to get a sense for how fast cases move through a particular judge’s court. In the Los Angeles County Superior Court, the average case length is 463 days. Knowing where a judge sits in relation to this average, as well as the number of cases (s)he has on deck, can help litigators anticipate the likely pace of their case.

 

Judge Grant Rates for Different Motions

That’s just the beginning. Judicial analytics can also provide information about grant rates for different types of motions. The AI that guides these analytics platforms use a judge’s past rulings to model how (s)he is likely to respond to motions filed by plaintiffs and defendants in the future. We can quickly see, for example, that the Hon. Kevin C. Brazile of the Los Angeles County Superior Court favors plaintiffs in labor and employment disputes and defendants in property disputes, granting 43 percent of demurrers for the former and 85 percent for the latter. This is crucial information to have when formulating settlement strategies. As one attorney from Locke Lord explained, “[i]t also helps me predict, based on prior rulings, how the judge may rule on the motion. The information gives me a sense of who has leverage during settlement negotiations.”

Case Outcomes Broken Down by Practice Area

Judicial analytics can also offer information about case outcomes broken down by practice area. This is particularly helpful at the start of litigation, when an attorney is tasked with deciding which court will be best for their client’s specific claim; an attorney can quickly get a sense for how local judges have handled similar cases in the past. Returning to Judge Brazile, we learn that he has dismissed 233 (out of 290) of the wrongful termination cases assigned to him. He has, in contrast, presided over far fewer unlawful detainers, dismissing 36 (out of 53). This data can be used to assess a judge’s experience with different issues. If the judge presides over a specific type of issue often, an attorney can spend less time discussing the particulars of the law and move straight towards the facts of the case.

 

Milestone Analyses

And, finally, attorneys can perform milestone analyses. It takes only a second to learn that, on average, Judge Brazile cycles through property cases 43 days faster than his peers on the bench. This information is critical when it comes to the logistical side of litigation, helping litigators provide accurate timelines and budgets for their clients.

The insights from judicial analytics feel endless. However, reaching these insights requires attorneys to adopt a paradigm shift. They must combine new kinds of information in new ways, juxtaposing the data gleaned from state trial court records with the controlling authorities found in statutes and tentative rulings. Much of this territory is still uncharted. What will you do with it?

 

about the author

Nicole Clark is a business litigation and labor and employment attorney who has handled litigation in both state and federal courts. She’s worked at a variety of law firms ranging from mid-size litigation boutiques to large firms, and is licensed to practice law in three states. Additionally, Nicole is the CEO and co-founder of Trellis Research, a legal analytics platform that uses AI and machine learning to provide litigators with strategic legal intelligence and judicial analytics. Nicole has an intuitive understanding of technology and is deeply committed to helping lawyers leverage technology to gain a competitive advantage and achieve a more favorable outcome for their clients.

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