[guest author: Rachel Bailey]

As a special feature of our blog—guest postings by experts, clients, and other professionals—please enjoy this blog entry from Rachel Bailey, a Legal Data Expert for Lex Machina.

You may have previously read Seyfarth Shaw’s excellent analysis of Lex Machina’s Trade Secret Litigation Report. There are some big picture trends in the report that reflect the trade secret litigation landscape in the federal district courts. A common misconception is that Lex Machina is a reports company. While we do create reports using our data, ultimately we are a platform that updates daily with analytics that allow users to make data-driven decisions for litigation strategy, business development, risk assessment, and other uses.

As the author of the report and Lex Machina’s trade secret data expert, I do a lot of the day-to-day work to make sure the data is as clean and useful as possible. This is called data integrity.

What goes into making sure the data is as accurate and consistent as possible?

We start with data from PACER (Public Access to Court Electronic Records) including case metadata, docket entry text, and certain documents. Because PACER charges a fee to download documents, it is financially infeasible to download every available document. Lex Machina automatically downloads documents for docket entries identified to be significant, including pleadings and certain orders.

While PACER has a Cause of Action (COA) code for trade secret cases (18:1836), it may be underinclusive if not included by the person filing the pleading or overinclusive if chosen by accident. We use machine learning and technology-assisted attorney review to tag cases beyond those filed with the specific COA code. Lex Machina’s Algorithms Team tags cases based on machine learning that have trade secrets claims or counterclaims. With attorney-assisted review, we are able to curate the tag as well.

We define “Trade Secret” cases as those with trade secret misappropriation claims. The pleading must indicate two elements: 1) the information at issue is protected as a trade secret and 2) some form of misappropriation, including various synonyms for acquisition, use, or disclosure. Therefore, cases with allegations of trade secrets in the fact patterns that do not later plead some sort of misappropriation are not included in our data set.

Beyond finding the trade secret cases, Lex Machina supplements and corrects primary data from PACER in a variety of ways, including:

• correcting errors ranging from spelling mistakes to complex data problems
• normalizing data on judges, parties, law firms, and attorneys
• extracting records of law firms and attorneys not found in docket reports
• annotating case resolutions, damages, and dispositive rulings

I spend time thinking about how the data reflects real-world trends and how to count things that are often qualitative, such as a judge’s ruling on whether a plaintiff properly identified a trade secret or whether a defendant acquired, used, or disclosed a trade secret. With nearly 15,000 trade secret cases in our system, there are a variety of fact patterns, pleadings, and related claims. Using big data to get a sense of the litigation landscape is useful, and the report has some examples of how to do that.

What about my specific case?

Overall trends are interesting from a research and current events standpoint, but legal analytics can also answer questions attorneys want to know about their ongoing litigation. By looking at data that is relevant to a particular case, more insights are unlocked. The analytics are particularly helpful when using two or more metrics to find that relevant data. Let’s take a look at some specific examples:

• How long does it take a trade secret case to reach summary judgment in my district?
• What happened in trade secret cases where opposing counsel appeared?
• Has my judge ever approved default judgment damages, and if so, what was the amount?

How long does it take a trade secret case to reach summary judgment in my district?

Looking at the report in the figure above, the median time to summary judgment is 587 days based on all trade secret cases filed in federal district court between 2010 and 2019. The median time to trial is 791 days. The screenshot below shows that in the Central District of California it takes a median of 471 days to reach summary judgment in trade secret cases, nearly 100 days less. The time to trial is a bit shorter with a median of 741 days. This information can be used for budgeting and planning. Additionally, practitioners can compare to other districts where jurisdiction may be proper for deciding where to file or preparing a motion to transfer. For example, the Southern District of New York has a median 622 days to summary judgment and 621 days to trial in trade secret cases, with a larger variance in the time to trial in that district.

What happened in trade secret cases where opposing counsel appeared?

Legal analytics can be used to gain opposing counsel’s statistics or to size up firms that may be competing for a potential matter. Users can explore the specific cases to see whether they have similar fact patterns or parties involved. For example, you received a call from a potential corporate client who hired an employee that previously worked for a competitor and now both their company and the employee are being sued for trade secret misappropriation.

Looking up the opposing counsel, you see that they have appeared on nearly 300 trade secret cases in the last 10 years. They have gone to trial 24 times in trade secret cases but never in your district. With a good number of cases that resolved at trial and summary judgment, this law firm does not necessarily plan to settle. In looking at these cases and comparing the fact patterns, you find out they generally litigate trade secret cases claiming it is intellectual property, rather than likening the fact pattern to a torts or contracts dispute. This quickly gives you strategy information you can pass along to the potential client and prepare them.

Has my judge ever approved default judgment damages, and if so, what was the amount?

Let’s say you represent a plaintiff in the Central District of California, were assigned a judge, and the defendant never appeared. In strategizing for your motion for default judgment, you want to know how much your judge has typically approved in damages. Looking at the statistics, you can quickly see that this judge has overseen 13 trade secret cases in their courtroom and one case resolved on default with an award of nearly $300,000 in reasonable royalty damages. Quickly finding this information is significant because reasonable royalty damages are relatively rare and you can then review the filings in that case to find out more information, such as the type of proof required and what arguments the judge found persuasive. Plaintiffs can also explore other default damages awards in the district, which go up to an $8 million award in Sirona Dental Systems, Inc. v. Jian Lu et al. that includes actual damages/lost profits and attorneys’ fees and costs.

Trade secret litigation is a complex intersection of various areas of the law. Having current data that allows users to see the most relevant information to their own cases allows them to strategize faster and plan better in a landscape that is more competitive than ever.