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Big data analytics technologies are becoming omnipresent in many industries, and the legal sector is no exception.
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Put simply, legal analytics is the science of drawing insights from large volumes of data. In practice, legal analytics tools are helping lawyers make data-driven decisions on which to build their legal strategies. That could mean things like knowing the probability of a specific motion outcome, how seemingly unrelated cases connect or how much a settlement award could be.
(As an aside, you’ve probably noticed that new technologies often incorporate their own specialized dictionary of industry jargon. We created this handy glossary of 8 Legal Analytics Terms You Should Know to help you decipher it.)
As mentioned above, legal analytics helps attorneys incorporate data into their decision making. But that’s a pretty broad statement, so to better understand what that means, let’s explore some specifics.
Truth is, there’s not a single resource that encompasses all of the analytics capabilities now available to attorneys. That means a lawyer can pick from a menu of analytics tools, allowing them to find the one (or ones) that will best suit the needs of their practice area and legal concentration.
So then, how exactly do these legal analytics benefit a law practice?
Predictive analytics, for example, can help lawyers forecast the future. Or more accurately, it helps legal professionals make educated guesses on things like how long a case will take to reach a decision or how an expert witness may fare under scrutiny.
It’s also important to note that “big data” is often a core component of related technologies, encompassing breakthroughs in machine learning, cognitive computing and artificial intelligence. That means those innovations can fall under the umbrella of analytics too.
And, while it may sound like the realm of science fiction, artificial intelligence is already impacting the legal profession. For example, this technology can help a lawyer conduct research by “understanding” what their intended search path is and suggesting relevant documents to help support it.
Using machine learning techniques, analytics engines have been taught how to recognize natural language patterns. That improves a computer’s ability to quickly pinpoint precise words and phrases—finding key information that could take a human several hours (if not weeks, months or years) to find. This is especially handy for something like, say, judicial language.
A tool that uses language analytics, for instance, can scour countless lines of court text to locate (and extract) key phrases that may be beneficial to your argument. That means you could literally use the judge’s own words in your case strategy—which should make it easy to make a compelling argument for them. If that kind of advantage piques your interest, you can learn more about language analytics here.
Regardless of the application, analytics tools typically share a common thread: reliance on massive data sets (AKA big data). And massive is no exaggeration—these analytics engines often pore through petabytes of information.
As a general rule, the more data in a data pool, the more accurate the insights can be. So, it pays to have your legal analytics engines fueled by a robust database of reliable information.
And it’s important to note the use of the word reliable, as any powerful analytics resource not only needs a lot of data, it needs a lot of “clean” data. Since analytics is often considered a GIGO system, the insights you draw will only be as trustworthy as the data that drives them.
Ergo, when selecting a legal analytics provider, make sure to ask detailed questions about where the data comes from and how it is being vetted.
To an attorney, legal analytics software can offer some pretty powerful insight. As alluded to above, that insight could be something like the probability of a motion outcome or a rough dollar amount of a verdict or settlement.
But the value of legal analytics goes way, way deeper than that.
Powerful visualization tools can incorporate data analysis to reveal hidden connections between entities or uncover valuable links to citing cases. Many visualization tools are also incredibly helpful in improving the way lawyers scan and interpret search results to speed up their research time.
The concept of value can manifest itself in several ways—from basic factors like general time savings to more abstract benefits like enhanced strategic decision making.
Specifically speaking, the ability to assess whether it makes financial sense to take a case or to better budget resources for a particular client can be pretty valuable for a lawyer in a small to midsize firm.
Regardless of the specific application, attorneys are finding significant value in the capabilities that legal analytics unlock.
Not likely. Or at least, not anytime soon. What legal analytics is doing though, is encouraging lawyers take a more data-based approach to their decision making. That could mean that the image of the prototypical attorney may be changing.
Historically speaking, law schools were often populated with students grounded in the humanities, writing, philosophy, etc. But now it’s not uncommon to see students with a more diverse background encompassing data sciences like math, engineering and technology.
As the legal profession evolves in the information age, it shows nothing but promise to both attorneys and their clients. Leveraging vast amounts of data has already proven useful in many scenarios, which ultimately means better outcomes for those involved.
While shiny suit-clad robolawyers may be a ways off, data analytics is already helping lawyers make smarter, data-driven decisions—and helping them do it faster. That tells us that the proliferation of related analytics technologies will only accelerate in the future.
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