Digital White Papers

46 WWW.ILTANET.ORG | ILTA WHITE PAPER KNOWLEDGE MANAGEMENT Revolutionizing the Practice of Law through Data Science Today the most agile lawyers in the ediscovery space direct projects where millions or tens of millions of documents are loaded on a platform, where through the use of machine learning soware we can quickly dig deep to find "a signal in the noise" - a paern in the documents comprising a narrative that can be pulled together so a client can understand its own position and the position of its adversaries with immediacy and accuracy. The ability to figure out what happened and why with both absolute certainty and unbelievable speed is unparalleled in legal history. And judges, especially since 2012, have been approving the use of machine learning techniques in ediscovery as a way to put into practice the aspirational goal of Rule 1 of the Federal Rules of Civil Procedure, which calls for the "just, speedy, and inexpensive" determination of every legal action and proceeding. Finding the Facts in Edata Ediscovery is only the beginning, however, for the use of data science in law. As a fundamental maer, the practice of law is based on identifying key facts and insights. The client's position, how that position relates to the law, what risks are involved—all of it comes down to finding the facts. And in the information age those facts are almost exclusively contained within electronic data. As lawyers we can now go a long way towards understanding our client's conduct by analyzing the digital trail that employees leave, and there are massive strategic advantages in our ability to get the right information with certainty and immediacy. This has enormous implications across the wide spectrum of legal practice groups at our firms: providing analytical capabilities positively impacts not only litigation, but also maers involving mergers and acquisitions, due diligence and employment law, among many others. For example, the same analytics tools we use in ediscovery have proved immensely helpful in investigating an acquisition's value and risks during due diligence. The target of an acquisition can use such tools to prepare for a sale by identifying valuable information and providing reliable data to demonstrate its value objectively. An acquisition target can also use these tools to clean up its datascape, much like cleaning a house before it goes on the market, so that the acquirer takes possession of just the information that is key to the target's business operations. Generally in the practice of law, the amount of work that goes into something like a merger—finding contracts, identifying parties, digging into historical business information—has been a time- consuming, complex manual process. Leveraging analytics makes a big difference in cuing costs and time. There are many more examples where data science principles can be applied to the practice of law. Every practice group has repetitive tasks that are largely manual. Process optimization and data science can make these processes more efficient, saving time and increasing uniformity. For example, one of our clients relies on our firm to review thousands of contracts each year, comparing them to model contract terms and making conforming edits so that key terms are uniform across similar types of contracts. Historically this was a terribly manual process where an aorney read the proposed contract, compared it to model clauses, edited it and delivered it back to the vendor or supplier. Versions of each contract were manually tracked. This was a cumbersome process that took a great deal of time. Our data The ability to figure out what happened and why with both absolute certainty and unbelievable speed is unparalleled in legal history.

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