Ask Dr. Paola: Choosing the Best Pathway for Big Data — Using Prescriptive and Predictive Analytics

Topics: Artificial Intelligence, Data Analytics, Efficiency, Law Firm Profitability, Law Firms, Legal Innovation, Talent Development

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The Legal Executive Institute blog is honored to be working with Dr. Paola Cecchi-Dimeglio, a behavioral economist and senior research fellow for Harvard Law School’s Center on the Legal Profession and the Harvard Kennedy School, on a monthly column.

Each month, Dr. Cecchi-Dimeglio will be answering questions about how law firms and legal service firms can navigate a dramatically changing legal environment by using data analytics and behavioral science to create incentives for law firms and their lawyers to change behavior. (You can follow her on twitter at @HLSPaola.)

On to this month’s question…

Ask Dr. Paola: At my law firm, I must admit that sometimes I am intimidated by the prospect of big data. What’s the best way to wrap my mind around big data and what it can do for me?

Dr. Cecchi-Dimeglio: I think one way of getting to that point  is to remember that data always has a story to tell. However, you need to know what you want to achieve for your lawyers or your firm. You need to know why you want to use big data in order to understand what type of pathway or modeling is best.

It’s a foundational process that you need to have — you have to understand what data to look at, from which you will generate reports and structures of data in a way that is useful for you, and then analyze the findings to understand what needs to happen and what changes you can make at your firm or in your lawyers’ behavior. But understanding big data is always something that needs to happen before you can use it. You have to ask yourself, what is the end goal of whatever I want to do? It is also crucial to understand the importance of having experts guide your firm through this process correctly and effectively.

Previously I wrote about the four main types of big data analytics, which are: prescriptive, predictive, diagnostic and descriptive. Today, I want to take a deeper look at what two of those — prescriptive and predictive — can do for your law firm.

 You have to understand what data to look at, from which you will generate reports and structures of data in a way that is useful for you, and then analyze the findings to understand what needs to happen and what changes you can make at your firm or in your lawyers’ behavior.

Both deal with different ways of looking forward, based on past actions or activities and allow you to ask questions about future outcomes. For example, with prescriptive analytics, you can develop a preliminary view of the probable success of a transaction or a legal case. And as new information becomes available over time — from either publically available sources or new data information that is populated by your firm’s case management system based on all the firm’s clients and the variety of cases they’ve worked — it can all be fed into the model to adjust the prediction. It allows you to optimize the model and at the same time improve its accuracy to determine the probable success of a specific case or legal strategy.

For example, it could show you the best legal team or individual lawyer who would have the best chance for success, or even what type of template or document is more likely to lead to a positive outcome. This information is then generated at the perfect time for your lawyer to make a better decision. Simply put, the more you know about your firm and how people have decided things in your firm or the actions they’ve previously taken, the more prescriptive analytics can show you how to increase the probability of success.

Dr. Paola Cecchi-Dimeglio

And when you go the next level, you can look at predictive data, which is really running a different scenario, in which you are analyzing which of these probable scenarios might happen, given what’s happened in the past. In short, you identify the pattern to predict the future.

So predictive analytics allow you to gain an in-depth value of the market, and how you and your firm behave compared to others. Imagine in a litigation case, for example —we know that through machine learning and artificial intelligence we can now scan millions of documents almost instantly — and we can search for an important concept that is described or used in those documents. Predictive analytics allows you to go even beyond that and extract a subset of data that focuses on answering questions such as: what are the best scenarios in cases such as these? Should we go to litigation? Should we arbitrate the case, or should we mediate the case? What has worked best in the past?

And the questions can go further than that  — what is the best jurisdiction for success in cases like these? What judges have the best track record for giving us the outcome we want? Your analysis can present you with the likelihood of success as well as the risks associated with each of those legal outcomes you could pursue.

I want to similarly describe diagnostic and descriptive analytics of big data in my next column, but, as I said, it is important to avoid becoming intimated by big data and its uses, and to understand that there are tools and experts that will help you find ways of looking at your end goal to determine the data strategy you will want to use, and the type of modeling that you should use to get the best insight into your firm’s behavior, allowing for better decision-making.