Moving at the Speed of Business: Lex Machina, Data, and Dedicated Business Courts

By: Clint Westbrook

The business world changes rapidly, and if lawyers want to stay above water, they must change rapidly too. Unfortunately, some lawyers are trying to make their horses faster, when they really need to be building cars. In a previous post, Jay Lonick described the advent of business courts in Michigan and the importance of lawyers fully engaging in a changing legal market. Specifically, he described the purpose of the business courts and their impact in a market that now asks for data-supported legal conclusions. In this post, I intend to expand on those ideas by advocating for improvements to a new, though quite powerful, analytical tool: Lex Machina.

When one opens the homepage of Lex Machina, the user sees a simple interface with graphically represented data. At the time of writing, the home page displays analytics on 92,546 cases from 2007–2014. The cases are charted on an intuitive line graph in the middle of the page with four categories represented: patent, trademark, antitrust, and trademark. These intellectual property cases are the lifeblood of Lex Machina. The system is designed to give searchable, filterable data on the world of IP law, and it does so quite well. If a lawyer is faced with a patent suit in the Eastern District of Texas, for example, the lawyer may drill down to “Patent” in the “Courts and Judges” tab of the interface and see all 5,432 patent cases decided in that district. By applying filters, one can see which judges found for the plaintiff and how many times, how certain motions were most often decided, and by some savvy deduction, how best to proceed to increase the chances of a favorable verdict or settlement.

Unfortunately, though, the usefulness of the system is limited by its subject matter. As noted above, Lex Machina represents four types of only IP cases. With the changing legal landscape, though, lawyers will be expected to provide similarly in-depth data for every field of law. The diligent lawyer can deduce a much more accurate expected value for a client by accessing data about venue, judge, and damages awarded in any kind of case. Presumably, Lex Machina decided to begin with IP cases because such clients are more often data driven; one would expect Apple to be much more concerned with the data in a patent case than dear Aunt Ethel might be in her probate dispute.

Notwithstanding that general conclusion, though, Lex Machina will provide a better service by broadening its market base. The business courts now found in many states, like Michigan, provide a useful starting point. As Jay’s post indicated, Michigan’s Business Court statute provides for resolution of disputes arising out of “information technology, internal affairs of businesses and the rights of participants therein, and perhaps most broadly, actions ‘arising out of contractual agreements or other business dealings.’” Though this seems to be impossibly broad, business transactions may be reduced to categories much like Lex Machina’s categories for IP cases. This new business branch of analytics might offer data on cases involving: (1) mergers and acquisitions; (2) stockholders rights; (3) breaches of fiduciary duties; (4) partnership and incorporation disputes; and (5) breaches of contract.

While the claims, ideas, and legal principles within these categories are extensive, Lex Machina’s business interface, like its IP interface, would be designed to give the user access to compiled summary data. In the current IP system, if one drills down to determine how Judge James Rodney Gilstrap in the Eastern District of Texas decides IP cases, one will find that, from 2001 to 2015, Judge Gilstrap awarded attorney’s fees in only three cases. If a lawyer is representing a plaintiff before Judge Gilstrap and that plaintiff is seeking attorney’s fees, the lawyer would be wise to properly set his clients expectations—attorney’s fees are unlikely. Lex Machina does not offer, nor does it promise to offer, information about the facts in those three cases, give the rules of law established in each, or explain exactly why Judge Gilstrap does not often award attorneys fees.

But Lex Machina is not designed around such information. The interface is meant to provide summary analytics that give IP lawyers an easy-to-access basis for sound personal judgment in particular cases. Lex Machina does provide a link to each of those cases in the Eastern District, but it does not, and does not purport to, offer legal conclusions. Even the broad nature of business-court cases, then, should not deter Lex Machina, or any other summary analytics provider, from wading into the depths of the state-business courts. If they did so, the legal-analytics industry would see rapid growth as lawyers could access data on thousands of business-court cases through a user-friendly, intuitive interface.

Legal analytics, then, should not be only for the technological whizzes in the world of IP law. When lawyers can use data to inform themselves and their clients, everyone wins. Clients feel more informed, lawyers feel more confident, and the system has less waste by reducing frivolous motions before particular judges. By expanding their scope and data pool, companies like Lex Machina could reach into every area of law and drastically change the way that lawyers think about cases; maybe lawyers will even stop promising clients that Judge Gilstrap will award their attorney’s fees.