How Judicial Analytics Can Guide Motion Practice

The primary aim of predictive analytics (of which judicial analytics is a leading example) is to help users anticipate potential outcomes and modify behavior accordingly. No amount of artificial intelligence or machine learning is going to engage and excite a busy litigator unless such technological tools can be harnessed in such a way as to provide tangible, valuable guidance. There is no better example of this than how litigators use judicial analytics to guide motion practice.

Gavelytics, one of the top judicial analytics platforms on the market, and the only technology that comprehensively analyzes California Superior Court litigation data, offers a Motion Analyzer, which educates litigators regarding how each judge tends to rule on over 100 different types of motions compared to the average judge in the jurisdiction. Let’s explore how judicial analytics can inform motion practice, through three different hypotheticals, involving: 1) Demurrers; 2) Motions to Compel; and 3) Motions for Summary Judgment.

Hypothetical #1: Demurrer

A demurrer is a written response to a complaint most commonly made on the grounds that the complaint fails to state facts sufficient to constitute a valid cause of action (CCP § 430.10(e)). Imagine, for example, that you are a litigator defending your client in an employment lawsuit that alleges workplace discrimination, and are considering filing a demurrer challenging one of plaintiff’s causes of action.

You use Gavelytics to research your judge — the hypothetical Judge Jones. You learn that Judge Jones grants demurrers in employment litigation matters 22% more often than her peers, a substantial difference in your favor. You then use the Motion Analyzer, select “Employment,” and click on the “Demurrer to Complaint” category, where you notice that Judge Jones has only a “Medium” volume of employment demurrers (meaning between 16 and 49 filings) over the last 7 years, indicating that she does not see very many demurrers in the employment context.

Armed with the knowledge that (1) Judge Jones tends to grant employment demurrers, but (2) she may not see many of them, you decide to adjust the legal standard section of your brief to more carefully walk Judge Jones through the relevant case law since she may not be as familiar with some of the legal nuances as compared to other judges. Similarly, you could adjust the introduction section of your brief to more carefully lay out the relevant issues.

Hypothetical #2: Motion to Compel

A motion to compel asks the court to order the opposing party to take some action, usually during the discovery phase of a lawsuit. This sort of motion is usually filed when a party has propounded discovery to the opposing party and contends that the discovery responses are insufficient or incomplete. Let’s say you are representing a plaintiff in a real estate dispute, and are contemplating a motion to compel the production of certain key documents.

You use Gavelytics to research your judge — the hypothetical Judge Gomez. You use the Motion Analyzer, select “Real Property,” and examine the judge’s tendencies in 4 different categories of discovery motions to compel. You notice that Judge Gomez has seen a very high volume (meaning over 100) of motions to compel written discovery in real estate matters over the last seven years, and the judge grants such plaintiff-filed motions 36% more often than the county average. Knowing that Judge Gomez is the type of judge who will regularly grant a motion to compel, you are more aggressive in your demands during the meet and confer process. When it comes time to file the motion, you need not worry about methodically explaining the legal standard to the judge given the high volume of such filings before Judge Gomez.

Hypothetical #3: Summary Judgment

Summary judgment, generally, is a pre-trial remedy sought where, based upon facts not in dispute, and an application of the law to those facts, a party is entitled to a judgment on a claim. If you are defending a personal injury action, and use the Motion Analyzer to see how the hypothetical Judge Yu usually rules on motions for summary judgment brought by defendants in personal injury actions, you learn that she is 41% less likely than the county average to grant such defendant-filed motions across a very high (100+) volume of filings.

Looking at the judge’s Gavelscore, the Judge Summary and at other motions in the Motion Analyzer, you detect a noticeable pattern of Judge Yu ruling significantly less often for defendants in personal injury cases. This is a problem! Since you’re well-past the CCP § 170.6 stage, your only choice is to adjust, based on your experience, the way you write and argue your brief, knowing in advance that the judge is likely to be hostile to your motion. If you have strong grounds for filing, you probably should. But if the motion is less than a slam dunk, you could strongly consider saving your client the money to be spent on the brief, not file it at all, and head towards settlement (and ask for increased settlement authority when informing your client.)

One of the most effective uses of judicial analytics is in the crafting (or shelving, as it were) of key motions, depending upon the tendencies of one’s assigned judge. When you are in the trenches, litigating a significant matter, and need to demonstrate to your client the value of certain discovery and motion strategies, judicial analytics is an essential tool for the litigator’s toolbox.

Like what you read? Give Rick Merrill a round of applause.

From a quick cheer to a standing ovation, clap to show how much you enjoyed this story.