Lex Machina Arms Corporate Leaders and Patent Attorneys with Predictive Analytics

by   |   June 6, 2012 11:50 am   |   0 Comments

Joshua Walker, a co-founder of Lex Machina Inc., likes to call what his company does “the Moneyball of intellectual property litigation.”

Just as Oakland Athletics’ General Manager Billy Beane, made famous by Michael Lewis’s book and the Brad Pitt movie, analyzed sabermetrics statistics to field winning baseball teams, Lex Machina customers can look at stats on courts, judges, attorneys and patent rulings to put together a better legal offense or defense in the high-stakes game of patent litigation—instead of relying on their experience and instincts.

A spin-out of Stanford University, Lex Machina has developed an analytical reference for IP lawsuits by painstakingly collecting and analyzing data on court cases. It sells risk advisory consulting services to clients, which include law firms, corporate general counsels and technology companies. For example, a client may be considering bringing a patent infringement lawsuit and want to know its chances of winning. Alternatively, it may be trying to determine what it will cost to defend itself against such a lawsuit, or evaluate an acquisition target’s patent portfolio during merger talks.

“We’ve done a number of use cases where we’ve [looked at] settlement patterns and win rates for companies,” says Walker. By looking at what’s happened in similar cases, it gives the client a good idea of its chances. It’s similar to the actuarial calculations done by insurance companies, he notes.

Patent Protection a Hot Button Issue in Tech Sector

Developed in the heart of Silicon Valley, Lex Machina’s capabilities could be particularly relevant to nearby technology companies who have been waging a legal battle through patents. The ownership of innovations in mobile communications is a major front in the conflict. Last June, the defunct Nortel Networks sold more than 6,000 telecommunications-related patents to a group that included Apple, EMC, Ericsson, Microsoft, Research in Motion and Sony for $4.5 billion. In August, Google cited the protection Motorola Mobility’s patents afforded Android mobile phones when it agreed to buy the company for $12.5 billion.

The issue has reached the point that in April Twitter published the draft of an “Innovator’s Patent Agreement,” stating the company’s concern that “we sometimes worry that [patents] may be used to impede the innovations of others” and declaring: “We will not use the patents from employees’ inventions in offensive litigation without their permission.”

Twitter’s statement does not mean the issue will subside any time soon. At last month’s AllThingsD technology conference, attendees reacted frostily to Nathan Myrhvold, the CEO of Intellectual Ventures, a company known for litigating its patent portfolio. Myrhvold defended his company as a protector of innovators, adding: “The part I find ironic, the question about animosity [toward me], is that this I the year when all the biggest and most important companies in Silicon Valley are doing exactly what I do.”

Lex Machina’s Stanford Roots
The company grew out of Stanford’s IP Litigation Clearinghouse (IPLC). The original plan for IPLC was to create a database similar to what Stanford had done with securities law. Just like securities litigation in the past, patent litigation has become very costly for technology companies, but there is little well-organized data on it. Unlike securities law, however, collecting and analyzing data on patent lawsuits is much more difficult, says Walker, who was recruited by Stanford IP Law Professor Mark Lemley to head the IPLC project.

Patent cases are more numerous than securities cases, says Walker, who serves as executive vice president of law and business development at Lex Machina. A recent study by PricewaterhouseCoopers found that patent holders brought 2,892 infringement lawsuits in 2010, reflecting a compound annual growth rate of 4.9 percent since 1991.   That compares to about 250 cases a year in securities lawsuits, according to Walker.

Patent cases also are more complex, coming in many shades of gray. The IPLC has information on more than 100,000 cases, 134,000 attorneys, 1,399 judges, 63,000 law firms and 64,042 parties, he says, and new ones are added every day. Each case can have any of 8,000 different events associated with it, such as the type of IP case it is and what counterclaims are associated with it. Add to that the fact that sometimes the courts don’t even categorize case outcomes correctly—and it’s a far cry from clean data.

Legal Data Run Through a Heavy Rinse Cycle
Walker recruited advisors from Stanford’s Artificial Intelligence Lab to help make the legal data usable. They start with the raw data in the IPLC, which comes from an online database called the Public Access to Court Electronic Records (PACER)/Case Management/ElectronicCase Files (CM/ECF) project. Lex Machina then applies proprietary AI processes and incorporates the expertise of legal scholars, practicing IP attorneys, federal judges and others. It’s taken a lot of human analysis and coding to make the data useful.

“The PACER data is like raw iron ore,” says Walker. “But we’re trying to build a Prius engine. The most valuable thing we’ve done is to clean up the data and make it useable. That’s a hugely difficult task.” Walker says the outcome coding by the administrative office of the U.S. courts was wrong more than half the time, and many cases were miscategorized. Others, such as trade secret cases, did not have a federal code or related data tags. Cleaning this data takes a lawyer and an AI engineer working together, he says. “Part of the secret sauce is not what we’re doing but how accurate we can make it, how legally rigorous we can make it,” he adds.

Lex Machina won’t discuss its customers or pricing for its service. As a Stanford spin-out, Lex Machina makes the database available for free to certain public-interest entities, including the courts, academics, government policymakers and media outlets.

A Frontier in Legal Analytics
Daniel Katz, assistant professor of law at Michigan State University, is an expert in the emerging field of quantitative legal prediction. Katz thinks Lex Machina has chosen a good market for the application of legal analytics. Patent litigation is a murky and very expensive area for corporations. “Those cases are so massive,” he says. “Your company can hang in the balance.”

According to a 2010 analysis by the Federal Judicial Center, IP litigation costs are about 62 percent higher than other legal matters and the average cost of taking a patent case to trial can be as high as $5 million per patent. Today, corporations rely on the experience and instincts of top IP law firms and attorneys for advice. But even the best of them have seen maybe tens of cases that are similar to the clients. “Humans are limited—people haven’t seen 10,000 cases or a 100,000 cases—a human can’t hold that kind of information,” Katz says. That’s what Lex Machina’s database provides.

Lawyers in general may be slow to warm up to analytics. Not only does it threaten their livelihood, but the legal profession is notoriously slow in adopting technology.  More likely, corporate general counsels will be the early adopters, says Katz.

Walker thinks this type legal analytics will transform how CFOs view IP litigation. In fact, a large part of his client base is business people, not attorneys. He notes that patent litigation impacts how Wall Street views public companies, and that CFOs need quantification of the potential risks and benefits.  The database can also be used to do patent portfolio valuation, including gauging how strongly the patents would stand up in court if challenged, says Walker.  The value of patent portfolios is becoming a key piece of information in mergers and acquisitions, notes Katz.

“Increasingly CFOs need this predictive modeling information,” he says. Today, attorneys tend to judge their chances in a patent case by gut feel. “The state of the art is outside counsel putting their thumb in the air and feeling which way the wind’s blowing,” says Walker.  “Moneyball is a great supplement to the expert’s gut.”

Tam Harbert is a freelance writer based in Washington, D.C. She can be contacted through her website.

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