Every law firm needs a legal data strategy. This was the keynote topic discussed by our own Chief Strategy Officer Daniel Martin Katz at the recent MaRS Discovery District for the Emerging Legal Technology Forum on September 20th in Toronto.
We say it. We mean it. Data strategy is the future of law, and having one can open up a whole realm of advantages. A data strategy can help to measure, monitor, and manage resources and service providers; model and improve processes; allocate tasks across internal and external resources; allocate tasks across risk management strategies (such as ADR); assess cost and quality of services; and provide a clear picture of a firm’s performance to its board and clients.
But what is a data strategy? Today, we’re taking a slight detour from our usual blog posts in order to answer that question.
Defining Data Strategy
When we talk about data strategy, we’re talking about a comprehensive, top-down approach that delves into an organization’s data in order to effect all kinds of improvement. We want data on our firm’s cases and clients, data on personnel and communication, data about resources, and data about risk management and uncertainty. Any record of fact that we have, we can use to elevate and improve a firm. Once we collect data, we can observe the kinds of patterns that develop, make an interpretation of that information, and make inferences and plan for the future with as much skillful preparation as possible. Critically, tools like LexSemble can help you crowd-source data from your human capital and experience.
When Is Data Valuable?
Sometimes it’s hard to know what data is valuable and what isn’t. We typically place high value on events that happen frequently with relatively low impact, and events that happen infrequently but have a high impact. Something that is a small factor present every day, like a routine meeting or report, versus a big one-time event, like the completion of a big case that’s taken most of a year to execute. Too often, we view these different aspects of an operation as discrete entities not inherently related. Without a data strategy, we may miss tiny patterns in the operation of a firm that could be having a larger impact than one might at first suspect.
The goal of a law firm or corporate legal department is to facilitate business activities and transactions and to help manage and value risk. The focus of a legal data strategy, then, is to develop data collection and capabilities in order to improve the quality and efficiency of a firm’s tasks. Our data strategy needs to find anything and everything that may have an impact on how these tasks are completed.
Types of Data
There are two types of data: structured, and unstructured. Examples of structured legal data include billing records, docket records, or litigation outcomes. This data already possesses a semblance of organization. Unstructured data, on the other hand, probably doesn’t. Examples of unstructured data include court filings, contracts, deposition transcripts, etc. These are documents considered mainly for their internal content, but not often collected and considered as separate data points in a set. We have to ask questions about these separate documents and processes. In an ADR case, for example, do we know our chances of winning? Do we know what our liability might be? How successful is ADR in the first place? We can’t find this answer in a pile of documents. The answer may lie in the unstructured data floating around, but it’s ineffective as a predictive tool in its current state. This is where we need a model, and where having a data strategy can fill in the answer to those questions and many more.
Starting a Data Strategy
How do we start a data strategy, though? The best way to start is to use small projects that are easily repeatable in order to design and build predictive models. We need a data set large enough to train a predictive model using machine learning.
In our post next Monday, we will delve deeper into machine learning and the various processes that it entails. LexPredict is at the forefront of developing machine learning for use in legal data strategy. Legal teams need to take advantage of these technological tools. Law is a client-centered business, and in a competitive field, clients are going to demand the very best cutting-edge technologies.
The data is on your side. And LexPredict can help you learn how to use it.