Sometime ago, I wondered whether and to what extent plaintiffs’ lawyers, most of whom work on a contingency basis as opposed to by the hour, were adopting technology. After all, it would make sense that any technology that would reduce time spent on a task should be appealing to those who use a business model with which the less time you spend on a project, the more you make.
It has since occurred to me that litigation data analytics would be particularly appealing to contingency fee lawyers since it would enable them to better assess exposure and likely results and the time needed to get to an end resolution. I have written before about the power of these kinds of analytics.
I recently had a chance to talk with Owen Byrd, Chief Evangelist and General Counsel of the data analytics company Lex Machina, about this issue. Lex Machina provides data based insights and analysis on judges, lawyers, law firms, parties, and other critical information across 12 federal practice areas and the Delaware Court of Chancery. (Lex Machina is part of LexisNexis, the global provider of legal, regulatory and business information and analytics). Byrd confirmed that Lex Machina, at least, sees plaintiffs’ lawyers as a significant marketing opportunity and is making a big push to get into the contingency fee market.
Litigation analytics is a great equalizer
Byrd sees litigation analytics as a great equalizer both for plaintiffs’ lawyers facing well heeled defense firms but also among plaintiffs’ firms competing for business with one another. In particular, smaller firms—be they plaintiff or defendant— often don’t have the data that analytical platforms like Lex Machina and its parent LexisNexis offer and don’t have the personnel needed to do the type of hand analytics to match the capabilities of bigger firms. He says that there are a number of smaller firms and solos already using the Lex Machina analytical platforms.
Having access to and, more importantly, using analytics, will be table stakes for any firm competing for business.
Soon, Byrd says, having access to and, more importantly, using analytics, will be table stakes for any firm competing for business. (I agree by the way that this should be the case; it remains to be seen when this will come to pass). Byrd noted some present day differences between how smaller and bigger firms use litigation analytics: big firms use analytics more to pitch getting work; plaintiffs’ firms use analytics to filter the cases they will take.
I will confess that other than a few isolated but (fortunately) financially lucrative opportunities, I have never worked as a plaintiffs’ contingency lawyer. But I have gotten to know a whole lot of them and watched them work and analyze cases. Two big issues for them in evaluating cases are the time necessary to resolve a matter via trial or settlement and how much is realistically at stake. Both go to the heart of being successful as a plaintiffs’ lawyer.
Generally speaking, the really successfully plaintiffs are experienced trial lawyers who have become skilled at getting really high value results. Or they go the other way and know how to move lower value cases quickly and efficiently through the process to get results with the least amount of time invested. (That’s not to say that they don’t do a good job for their clients by the way). In any event, the really good ones have traditionally had the knack of intuitively placing themselves in the shoes of jurors for case valuation purposes-in essence they successfully practice a degree of empathy driven by business related concerns. Most of them get to this point through trial and error.
The less successful ones often misevaluate either the time needed to get to a result or the value of their cases or both. Often these are younger or less experienced lawyers who traditionally have had to learn as they go how to evaluate cases.
Litigation analytics can also get a better read—not on what a jury might do with a case—but on what juries have actually done, substituting intuition with real data
But here is value of data analytics. By accessing and analyzing data, less experienced lawyers can jump start their experience level and compete more effectively with more experienced brethren. They can get a better read on what a judge may with issues of law, whether a case might survive motion practice, and the chances it will get to a jury—all based on actual data. (Getting to the jury is the mother lode for plaintiffs lawyer: it increases the exposure and costs and, frankly, makes it more likely the case will settle sooner). They can also get a better read—not on what a jury might do with a case—but on what juries have actually done, substituting intuition with real data. With the power of analytics, the less experienced lawyers may even be encouraged to confidently take winnable cases that a more experienced lawyer who is not accessing analytics might not. End result: more people with winnable cases may have access to lawyers and have their cases heard in court.
I talked about this with a real plaintiffs’ lawyer, Hans Nilges. Nilges, who practices in Massillon, Ohio uses the Lex Machina analytic tools. He told me that so far he uses analytics to indeed assess a particular judge’s proclivities and to predict how they might deal with legal issues. He thus has a better handle on the chances a case coming in the door will get to a jury. Ultimately, Nilges sees analytics being used to predict legal and jury outcomes in a more evidence based way versus the hunch or intuitive method used by many lawyers today. He compared the use of analytics in law to the use in the medical profession: the medical profession long ago abandoned intuition for an evidence based model. This is one reason younger doctors who receive state of the art training in medical school quickly become skilled and even better practitioners than older physicians. Nilges also told me something interesting: one of his colleagues is using data analytics to predict when a judge may rule on a motion; he then uses that information to exert the maximum settlement pressure at the right time. Hadn’t thought of that but makes sense.
Since obviously not using analytical tools your adversary is using is such a disadvantage, you have to wonder why defense firms are using analytics differently
One last thing Nilges told me: similarly to Byrd, he, too, sees differences in how plaintiff and defense firms use litigation analytic. Nilges thinks defense firms use analytics more for business development purposes than to analyze what might actually happen in a case or map out strategy. Since obviously not using analytical tools your adversary is using is such a disadvantage, you have to wonder why defense firms are using analytics differently. Perhaps it’s because their livelihood is not so much directly at stake from a bad result; a miscalculation by a plaintiffs’ lawyer has much more immediate and direct, bottom line financial repercussions.
I also talked to Ari Treuhaft, the Head of Product of the national plaintiffs’ law firm, Morgan & Morgan. Treuhaft confirmed that Morgan & Morgan also makes extensive use of analytical tools based on both external data but also on the significant internal Morgan & Morgan data. Morgan & Morgan uses analytics to look at predicted outcomes but also to determine process mapping, how long it will take to resolve cases and how to select lawyers for cases and staffing.
So, yes, the better plaintiffs’ firms seem to be using data analytics just as I thought they would be and should be. And, as time goes on, its inevitable that these firms will gain a significant litigation advantage over defense firms that don’t. The big issue is whether and when corporate clients will figure this out and demand better use of analytical tools by their lawyers.
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