Solving the Challenge of Accurate Matter Classification for Better Analytics

Sean Monahan | March 22, 2022

Doing more with less has been a refrain in the legal industry for years, becoming even more urgent during the current talent war. Every year, there seems to be more work, less time, and higher pressure to get the work done efficiently and cost-effectively. But as law departments and their law firms alike struggle with finding new ways to streamline their work, the data they need to inform better strategies sits at their fingertips, unused and overlooked. Enter the need for legal analytics. Legal analytics provide the foundation for data-driven, strategic decision making, helping legal organizations advance business objectives.

But meaningful analytics require good data. Law firms typically capture only the data they need to open matters, send bills, pay lawyers, manage taxes, and retain required matter records. If they study their data, the focus is typically on internal pressures, such as determining how to maintain margin while keeping up with client demands for greater predictability and lower spend. Few firms consider how they could leverage their data analytics with their clients, delivering insights that create value and thereby differentiating themselves from the competition.

Meanwhile, in-house counsel are marginally better than outside counsel at collecting matter-related data, but rarely apply a long-term lens to their data collection and curation efforts. That means they have difficulty with the core responsibilities that revolve around determining a company’s potential exposure on a legal matter. To do so, they must assess what a matter might be expected to settle for, what they should offer, what to allocate for reserves, how much to set aside to pay outside counsel, and which outside counsel have the acumen and experience to perform well on a case. Business clients are frustrated by the reactive nature of the law department and seek preventative legal support.

Both law firms and law departments lack useful historical data that could support deeper analysis, allowing them to diagnose problems and predict the future more accurately. In part, this is because neither in-house nor outside counsel correctly classify their legal matters. Accurate classification of matters is the keystone to effective data analysis, but typically relies on inconsistent and unreliable human input.


What does it mean to classify a legal matter?

Each legal matter should be classified in three ways:

  • Area of law: The body of laws and regulations associated with the matter.
  • Subarea of law: A more granular subset of laws, particular to an area of law.
  • Service: How the law department or law firm is assisting a client.

Here are some examples of these taxonomies:

Area of law Subarea of law Service
Banking and finance Commercial finance Loan assumption
Corporate Mergers and acquisitions Private M&A transaction
Intellectual property Patent Patent dispute
Securities Security offerings and capital markets Private securities offering/investment

The goal is to classify matters clearly enough so that when a situation recurs in the future, lawyers can look back and accurately determine which prior matters are most similar to the one currently being assessed.

Unfortunately, every law firm and law department has a different taxonomy—and there are often no guidelines when matter management systems are implemented. Complicating this further is that people are not always consistent in how they classify things. Unfortunately, the people tasked with opening a matter and entering data in the system are often the least connected to the substance of the legal matter. That means they are poorly qualified to designate an area of law, subarea, or service that accurately describes a matter. Perhaps that explains why so often the first item in the matter classification dropdown is chosen, regardless of its applicability.

Accurate and meaningful matter classification information is foundational to legal analytics. If the initial classification is incorrect, it is impossible to have an accurate historical record that can meaningfully inform matter strategy. If matters are haphazardly classified, it is impossible to correctly predict the potential outcome of cases, determine whether to recommend settlement, or decide which law firm is best positioned to handle a matter. From an operational perspective, lawyers relying on analytics from poorly classified matters will not be able to identify trends in spending or problematic developments that may indicate an emerging hotspot that compliance should address. They may not be able to optimize resources, balance their workloads, or share work appropriately with third-party suppliers. And they certainly will not be able to demonstrate their value to their clients.

HBR has developed an approach to auto-generating a taxonomy at the time a new matter is opened. Avoid squandering the value of your data analytics by glossing over matter classification. If you would like to discuss how HBR’s team of former practitioners, data analysts, data visualization experts, and technologists can help assess and advance your firm’s or department’s data analytics capabilities, please feel free to contact Bobbi Basile or Sean Monahan.