The business platitude “data is the new oil” has proven its worth in spades over the last decade. The country’s biggest companies, groups like Google, Facebook and Amazon, trade primarily in data; organizations across industries have invested heavily in business analytics, developers and analysts; and “data scientist” roles have become some of the most lucrative jobs on the market. Yet law firms, for the most part, haven’t quite caught up. But that might be changing. A growing number of law firms are attempting to navigate the Big Data age by appointing data “leaders” under a few different titles—chief data scientist, head of data analytics and chief innovation officer, to name a few. As the variance in names may indicate, the industry is still fairly new to data work, leaving law firm data science leaders with a tall task: figuring out how to make law firm data valuable and profitable, and doing it quickly enough to keep pace with the business community. Finding Ground Data science found its first foothold in the legal community through e-discovery. Because the volume of client data has ballooned over the last decade, both law firms and vendors in the e-discovery space have increasingly developed and honed analytics and predictive modeling methods to help manage e-discovery. Tess Blair, a partner at Morgan, Lewis & Bockius and head of the firm’s e-data practice, got her start with analytics and data management as an associate managing e-discovery matters at the firm. The firm saw value and earnings potential in her work and sought to build it out. These days, she leads a team of 50 technologists, over 20 legal staff and a contingent workforce of about 400 people across all of Morgan Lewis’ global offices. Since the group’s inception, Blair has seen data become just as important to internal strategy as it has to client-facing work. “We are much wiser and much more data- and process-driven than we were back then,” Blair says. Nowadays, “the solution is not always to hire more people and assign more reviewers.” Rather, Blair finds it’s often more prudent to “look at the data” to figure out how and where to assign more human resources. Blair’s team is increasingly looking beyond e-discovery to think about other potential ways the firm can leverage client data and serve it back to clients. “Currently, our typical problems are litigation-oriented, or it’s a due diligence exercise,” she notes of the e-data practice, adding that clients are now beginning to ask how technology can be used to solve more complex problems, like regulatory compliance, such as for the European Union’s General Data Protection Regulation (GDPR) set to go into effect in May. Bennett Borden, partner and chief data scientist at Drinker Biddle & Reath, has overseen similar conversations at his firm. For years, Borden was the sole unique example of an attorney-data scientist, boasting both a tenure in the intelligence community using data to predict potential human behavior and a graduate degree in business analytics. Although his skill set remains fairly uncommon, he’s seen other firms add legal-based data science roles like his at an increasing clip. “If you look at this role, there have been people at law firms who have data science backgrounds, who are looking at data and analytics, but most of them are inward-facing,” he says. “They’re looking at the firm and how the firm does business.” Borden does deal with many internal firm analytics, but the work that he sees the most potential in is client-facing. Borden advises clients on issues in their business analytics models, things like algorithmic bias and potential ethical concerns, but also develops machine learning and predictive data models with client data to help them navigate business decisions, be it modeling potential litigation outcomes or merger and acquisition data. “Pretty much everyone will do this before too long. It’s just inevitable,” Borden says of his data science work in law. Lawyers, he says, “fundamentally deal in information. In the information age, that information is overwhelmingly electronic. The way you get at insight in large piles of data is through analytics and data science. It’s just inevitable. It’s just also crazy cool.” Mining Data for Meaning Data science may be inevitable in law firms, but the industry may not have a great sense of how to really make use of and respond to data quite yet. “In general, firms are thinking, ‘We have to use data, and we have to use analytics,’ and it’s being applied in a way that’s not how it’s applied in other spaces,” Littler Mendelson’s former head of global data analytics Zev Eigen tells The American Lawyer. Eigen has now co-founded HR monitoring and compliance startup Syndio. At Littler, Eigen found himself primarily tasked with questions from firm leaders about pricing and predictions—how things can and should be budgeted, and how to predict potential outcomes. He also worked a lot on data projects requested by clients. “We’re scraping data sources or amalgamating data sources external to the firm. Sometimes we use internal firm data as well, but we’re looking for data and trying to find ways of answering questions on behalf of clients” with data, he notes. Many of these client-facing projects centered on litigation risk assessment. “If you can get ahead of that risk and fix problems before they materialize into very, very costly and time-consuming litigation, that’s great. Clients in that circumstance are willing to pay a lot for high-quality analytic work to get ahead of that risk,” Eigen says. Notably, some practice areas may be better equipped to adopt broader data resources and projects than others. “Labor and employment is a more fertile ground for this to happen than, say, mergers and acquisitions, because L&E is commodity work, and there’s a lot of competition,” Eigen notes. But instead of using data to change inefficient firm practices or advise clients differently, as businesses and technologists often tout of their analytics investments, Eigen is seeing firms primarily leverage data for narrow competitive uses that can help them develop slight advantages over other Big Law firms. Data practices that today seem cutting edge could easily be undercut without more structural changes to attorneys’ relationships to data. For example, Eigen has seen some clients starting data-based legal risk modeling that his team does itself. “It’s likely to change over time,” he says. Likewise, Borden says that firms don’t often value their data teams appropriately until they see that their efforts produce direct profit. “The big challenge is turning the position into a money-making one. In a law firm, the world is divided into those that make money and those that eat money,” he says. Thorny ethical issues can arise, however, when looking to depersonalize client data for sale to other clients. “The question of who owns the data [and] what you’re permitted to do with it, those are questions we’re all grappling with,” Blair says. Winning the ‘War for Talent’ While client-facing data analysis can certainly be a way to generate revenue, those efforts require data scientists, an expertise and skill set not often found among the legal community. Making matters more difficult is that data scientists sit among the most highly sought after workers in any industry right now. “I think this is going to be a new war for talent,” Morgan Lewis’ Blair says. “It’s really, really hard to compete in that space,” Eigen says of this war for talent. Strong data scientists are typically wooed by the pay and work culture of technology companies. Law firms often don’t know where to look to find data scientists. Even when they do, Eigen sees firms post job descriptions requiring law firm experience. “That’s really not the right criteria at all,” he notes. Blair says that while attracting talent is a challenge, the novelty and gravity of legal data can be a somewhat successful pull for data scientists. “We are in such early days that they will have an enormous role in shaping what this practice area is going to look like in the future,” Blair says. Access to data is part of how Borden has attracted his data science talent as well. “We’re working on problems that no one has been able to work on before,” he says. Firms that bring data scientists on board sometimes struggle to get those people really plugged into the legal needs at the firm. “The real trouble is, how do you bridge the gap between people who know how to do stuff and people who know what needs to be done?” Borden says. Eigen, however, pushes for firms to partner with technology companies that have the data talent and technological capabilities firms need. “Firms that partner with startups, that’s the best kind of step forward. You don’t have to be innovative. You have all these other really innovative, great companies all around you.” Seyfarth Shaw partner Brett Bartlett has engaged in a hybrid approach. Bartlett teamed up with Georgia State University College of Law professor Charlotte Alexander in the school’s new Legal Analytics Lab on a project to analyze hundreds of thousands of labor and employment cases for predictive analyses. “[Alexander] is able with her team to build a more granular assessment of what factors influence outcomes that we simply don’t have the ability to do at a law firm,” Bartlett says. Several “data heads” on Bartlett’s team will work with Alexander on the project and build out their skills. In return, Bartlett can offer Alexander access to firm clients who may be of use to her in further projects. The partnership also provides something of a pipeline of new law students experienced in handling data in ways the firm can leverage as it starts to bring some of these skills in-house. “We’ll be looking to hire lawyers out of law school who work in these spaces,” he says. The firm has hired statisticians and economists in the past, but Bartlett thinks such law firm roles are likely to be dominated by data scientists in the future. “I think those are the types of slots we’ll be filling with technologists who are engaged in Big Data.” Email: ghernandez@alm.com.