Data and Analytics: Will Change Finally Come to Law?

For years, legal commentators, technologists and consulting gurus of various sorts have bemoaned the slow adoption by lawyers of technology, innovation, and efficiency. And it’s true: fueled by a business model—the billable hour—that reward inefficiencies, lawyers have been notoriously slow to do things differently.

These same gurus have also predicted with the introduction of each new technology and innovation that the sea change in the legal profession was finally coming. This tool or this new approach would finally be the proverbial straw that broke the camel’s back. Each time, they have been (more or less) wrong.

However, significant change may finally be in the offing, and it could come from an unexpected source: big data and the ability to slice and dice it multiple ways. The availability and ability afforded by data analytics will lead inevitably to something sorely lacking in the legal profession: transparency. It is transparency that may finally drive some fundamental changes.

Why Now?

Without question, I think we are moving from a world of intuition and reputation to a data-based evidence-based model for all sorts of decisions, in business and ultimately in the legal profession.

This is occurring now for three reasons. First, computer processing power has increased to where computers can find more and more hidden patterns in our data. While some people question whether Moore’s law—which holds that computer chip capacity doubles every year—is still valid, the processing power of today’s computers do allow us to analyze and evaluate data in an infinite number of ways. Our computers can take seemingly unrelated data and look for patterns in things humans might never see.

Second, the amount of data available has exploded and is increasing exponentially. In 2013, 2.5 trillion terabytes of data were in existence. By 2020, a few short months from now, we can expect over 40 zeta bytes of data, a number almost incomprehensible to most of us. Many devices continuously generate data, and in many ways: IoT devices, video cameras, and wearables are just the tip of the iceberg.

While some of this data is structured—data that is easily searchable—most of it is unstructured data or semi-structured data, like emails, spreadsheets, videos, slide presentations, and social media data. Unstructured and semi-structured data do not easily fit into a relational database; to make sense of it, you need to understand the context. For computers to understand this unstructured and semi-structured data, they must be able to learn; and our computers are finally powerful enough to understand much of this context and nuance.

This power opens up such things as court cases, the language in decisions and briefs, and even internal data like law firm bills to computer analytical analysis in new ways, and to assess what was previously not measurable.

Finally, the analytics developed by software engineers for our computers have become much more user-friendly and inexpensive, not only for developers but also for lawyers and law firms. More open-source free opportunities are available than ever before. These opportunities will spur competition among the developers, which will result in even more software and analytics that we can all better use and understand.

Why is this important? If we can use analytical software more intuitively, we can better understand what the machines can make possible. Think back to word processing. When we had to use command keys to do anything, few lawyers used the tool. But when word processing became more user-friendly, lawyers recognized the value of the tool and, in turn, adopted it widely. This recognition and adoption then spurred the development of even more user-friendly and sophisticated processing tools.

What Does Improved Analytics Mean?

For years, lawyers and law firms operated behind a veil of mystery. Who really knew what outside lawyers were doing and billing for? Who knew which lawyers were really good? Who knew if a particular lawyer was efficient? How could you determine as an in-house counsel if the work your lawyers were doing was legal work, or work that could be done by people who didn’t have or need a law degree? Combined with a protective regulatory framework, the lack of ability to measure and assess what lawyers were doing allowed lawyers to function with little real scrutiny.

Data and data analytics have the power to disrupt all that. Take an area I am familiar with: litigation. Analytics will let people—lawyers or other legal professionals—do more and more with legal cases and opinions.

In the past, understanding decisions and holdings required understanding context and nuance, and only humans were capable of doing that. Moreover, we had no way to determine if the value of human time spent on legal research was appropriate to the task. No more. Legal research data analytics tools can now understand nuance. These tools can provide a baseline for how long it takes to do a job and how much it costs, in real-time. Research software not only does legal research thoroughly but also much more efficiently than before. Case law is now just data, which can be mined like any other database.

But that’s not all litigation analytics can do. Litigation analytical programs can mine information in seconds that an army of lawyers and legal professionals used to spend hours of (billable) time doing. Knowing this will again enable clients to look hard at work being done, and determine how inefficiently and incompletely it is done without analytics.

Analytics can reveal in seconds such things as what decisions a particular judge likes to rely on, and even what language he or she often cite in ruling on motions. From this, it’s a short step to fashioning the arguments that will resonate most strongly with a particular judge.

Analytics can tell you with a snap of the proverbial fingers what cases your opponent may have missed in their brief. Or it can tell you what you may have missed on your own. You can discover how often a judge tries a case, how often that judge’s opinions are reversed, how experienced the judge is in an area of law (so that you can understand if you needed to educate him or her). Moreover, analytics is not limited to judges and lawyers. Analytics can give you a vast amount of information about experts, including how often they have testified and the results, and how often they have been disqualified or faced challenges. Analytics can help evaluate what discovery is essential and vital to a successful and efficient resolution of a case, and how to best get it. All of this can be done in a fraction of the time it used to take to get even the most basic information.

Using analytics can save time and money and get a better result. The more clients understand this, the more they will demand it.

Here’s something else: Analytics can tell in-house counsel how often a potential outside counsel has taken a case to verdict, the types of cases they have tried and the results. It can tell an in-house hiring counsel how often the lawyer has appeared before the judge in a new case, and how frequently they may have litigated cases against the opposing counsel. Lawyer track records will be exposed for all to see.

All of this will revolutionize the way clients hire counsel and how lawyers can and should market themselves. No more relying on reputation or what lawyers vying for business say in their marketing spiels. Data analytics will keep lawyers honest in what they say and in what they do.

Clients can also access information and make informed decisions about the anticipated costs and length of cases based on historical data. They can prepare more accurate budgets and monitor performance against those budgets. Analytics will enable our clients and us to better predict costs based on this knowledge, and determine exposure and make better strategic decisions about litigation. They can compare the time and costs of cases and their components against what their lawyers are doing on an industry and case-type basis. They can assess the performance of lawyers based not on subjective determinations, but objective evidence.

Many of these tools are available today for matters in the federal court system and several states. Companies like Lexis Nexis and its subsidiary Lex Machina, Thompson Reuters and FastCase are offering sophisticated and robust products to do many of the things described above.

Let’s face it: non-transparency is dead: you can no longer fake it till you make it. Transparency exposes inefficiencies and spurs the demand for improvement.

Time and Billing

Another potent and, for some, scary use of data is to analyze bills. More and more, clients will be mining their own lawyers’ data by taking a hard and analytical look at their bills and their internal data. Today’s billing software products are sophisticated and robust. They can determine such things as how long it takes lawyers to do specific tasks, and by looking across industry-wide data, the most effective way to process the work and who is using those processes.

Today’s programs can determine if billing guidelines are being met and kick out entries that don’t meet them. They can take billing data and develop more accurate budgets, and then better monitor how lawyers are doing against those budgets as cases progress. They can quickly determine why a matter is off-budget and where the problem billers are. Again, they can look at and measure the effectiveness of their lawyers: who does things better and quicker, and why.

Analytics will drive better lawyer-to-lawyer comparisons and a better understanding of what lawyers are doing and who is doing it. It will lead to a better understanding of the best work process flows. This understanding can lead to the development of data-based best practices, and a mandate that those practices be used by any lawyer who represents that client.

Clients are already engaging third-party services that run analytics on matters handled by several law firms for different clients. This kind of analysis leads to benchmarking to get not just at rate comparisons, but also industry-wide staffing models and efficiencies. Billing analysis won’t just be looking at my firm’s bills; it will be comparing my firm’s bills to other firms to identify high-performing firms.

For in-house counsel, similar analytical programs can evaluate her or his efficiencies and workflows. Ultimately, the C-suite will require in house counsel use these tools and impose them on outside counsel.

Non-transparency is dead. Once information flows freely, the change will be demanded. As a representative of a billing software company recently told me, “We can ferret out the stuff you guys have been getting away with for years.”

Competition and Unbundling

Data analytics and the ability to determine who works better, faster and cheaper inevitably leads to more competition between law firms, and between law firms and alternative legal service providers (ALSPs). Using analytics, in-house counsel can determine what work can be better done not by lawyers and law firms, but by ASLPs, based on hard analytical evidence. Data-based decision-making will lead inevitably to the splitting up or unbundling of work to get the best and cheapest result. Law firms will no longer own and bill for working a complete case, but will be forced to work with other providers.

ALSPs already compete with law firms in the marketplace. These are pure stand-alone providers and even the Big 4 accounting firms. ALSPs are making strong plays to take away from law firms work that may not require a lawyer, but that law firms have traditionally done. ALSPs use technology, process flow principles, and corporate business models to do this work better and cheaper than lawyers have in the past.

The numbers are already eye-popping. According to a Thomson Reuters 2019 Study, in two years, the ALSP industry has grown from revenues of $8.4 billion to $10.7 billion, a growth rate of about 13%. According to the study, corporations are already splintering litigation work in individual cases between ALSPs and law firms, with ASLPS doing things like litigation and investigation support, legal research, document review, eDiscovery and regularly risk and compliance. And they will be doing more sophisticated stuff all the time.

So, clients are looking hard at the data and based on that data, making smart and well-grounded decisions. As analytics improve and data increases, the efficiencies of unbundling work, and sending components of a case to the best and most efficient providers will become apparent.


Analytics will tear the curtain back for in-house counsel and C-suite leaders to finally see what is going on, and help them make more informed decisions than before. Inevitably, this will lead them to demand greater efficiencies and change across the board.

About the Author

Stephen Embry is an attorney and frequent speaker, blogger, and writer. He publishes TechLaw Crossroads, a blog devoted to law, innovation and technology. He is co-chair of the Legal Technology Resource Center of the ABA’s Law Practice Division and is a member of the Board of Editors of Law Practice Today. Contact him on Twitter @stephenembryJD.

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