In recent years, the legal industry has witnessed the rise of the law firm Chief Knowledge Officer and, more broadly, a proliferation of research and library professionals within the big firm ranks. Knowledge Management (KM) professionals support law departments’ efficient and effective operation; put simply, KM is about winning and keeping business. KM pros live at the intersection of cost control, quality and speed. It is no wonder, then, that the legal KM community has begun to adopt and tout the benefits of judicial analytics.
I meet weekly with KM department heads and law librarians to discuss the value of judicial analytics platforms like Gavelytics. And one thing I can say for certain is that the demand for a nimble judicial analytics platform is high. In fact, in all honesty, KM pros have been waiting for the legal tech industry to catch up. There is a considerable amount of “collective wisdom” within a law firm, and the greatest challenge faced by KM pros is efficiently harnessing this wisdom to drive business development, reduce costs and bolster client satisfaction.
One of the most obvious fountains of collective wisdom within a law firm is background information regarding a judge. Most attorneys are familiar with the “all firm” emails circulated to hundreds of colleagues seeking any information about a judge to whom a litigator’s case was just assigned. Even basic information can be hard to come by, let alone detailed background on a given judge’s propensity to rule for or against certain parties. This is the sort of inefficient information gathering that is likely to drive a KM Officer crazy. And it is the type of disorganized approach to judicial research that Gavelytics was created to improve upon.
KM plays a critical function in keeping law firms profitable and sustainable, while at the same time promoting transparency. This can be a difficult needle to thread in the competitive, cost-driven marketplace, but one that KM leaders are increasingly able to manage given new machine learning technologies, including judicial analytics.
Fundamentally, KM is about connecting people and information to facilitate successful client outcomes. I often hear that one of the most frustrating data sets in the legal industry is comprised of information regarding judicial behavior, not only because state court systems are traditionally opaque, but also because, to truly be valuable, this data must be extremely granular and divisible by case type. Eyes tend to light up when I tell KM leaders that these sorts of detailed profiles of civil, trial court judges are now achievable.
There are a broad range of legal tech tools now on the market, and KM pros are often tasked with discerning which of these tools carries the greatest value for clients. We are entering an era in which a KM department without judicial analytics capabilities will be unthinkable.