Much of this blog post is taken from a more comprehensive white paper, The Legal Professional’s Competitive Survival Guide. Click here to view it.

The more we know about the past, the easier it is to predict the future. That’s the idea behind data analytics and predictive technology. And just think of the many ways it’s making your everyday personal life more convenient …  

Weather forecasts are more accurate than they were a decade ago because there is so much more detailed data to pull from. You have a better idea of how long it will take to get from point A to point B thanks to real-time traffic data on your GPS/map navigation app. Heck, your phone predicts what you’re going to type before you even type it based on your previous text history.  

But what about your professional life? Are you fully leveraging data analytics and predictive technology in your small law firm? Consider the following examples of how data can fundamentally improve some common predictions lawyers are asked to make.

1. Litigation Planning and Strategy: Understanding the likelihood of success on a motion or a judge’s tendency to rule on a specific type of matter can be key to litigation. Certain judges take longer to rule, and tend to rule in a certain way. Lawyers may draw on their own experiences or colleagues’ anecdotes when predicting outcomes, but these sources of information don’t paint a full picture.

Today’s legal analytics tools offer the capability to mine the entire body of a judge’s rulings, or to create comparisons using data sets that can be quite robust. Once docket data is cleaned up and normalized, lawyers can rely on statistical evidence of certain trends and outcomes, instead of anecdotes, to base their case predictions and legal strategy. This is one way big data can improve legal research processes.

2. Document Review: The digitalization of documents has turned document review into an electronic process. At the core of that process is a prediction: Which of these millions of documents are likely to be responsive to a discovery request?

Where that review process used to require lawyers to manually read every document and code for relevancy, today’s ediscovery tools can be trained to look for significant patterns in all that electronic data, and to issue predictions on the likelihood of a given document’s relevance to the training set.

3. Pricing and Budgeting: How much will it cost? That’s certainly one of the questions of utmost importance to clients. Many traditional lawyers answer that question in terms of expected inputs – if they are billing by the hour, they know from experience how long a matter is likely to take, and that experience becomes the basis for a prediction. But that sort of experience-based prediction can lead to all sorts of conflicts and disappointments when a matter deviates from the norm.

Today, however, when law firm practice management and financial systems collect all kinds of data about matters and their pricing, there are significantly better ways to use that data to make more firm predictions about pricing, and even to support fixed fees for certain services, cutting the risk of deviations to both the client and the lawyer.

Embrace the data-driven mindset

For lawyers, practicing with a data-driven mindset does not require lawyers to somehow become data scientists or software engineers. Nor does it mean data science or software engineering are equally central to the practice of law as experience and expertise with legal matters. And it’s certainly not limited to large firms. It’s mostly about being open to injecting data into processes and decisions where it can be the most useful, and treating data as an asset with value which must be maximized.

Portions of this blog post come from the white paper: The Legal Professional’s Competitive Survival Guide, which also includes Adopting a data-driven practice in five steps.

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David Curle, Director, Technology and Innovation Platform supports Thomson Reuters’ Legal business with research and thought leadership about the legal technology and innovation ecosystem, and the changing legal services industry.  Prior to joining Thomson Reuters in 2013, he led coverage of the global legal information market for the research and analysis firm Outsell, Inc., tracking industry performance and trends.  He is a regular contributor to the Legal Executive Institute blog and speaker at legal industry events.  He has a JD from the University of Minnesota Law School and a BA in History from Lawrence University.