BP Perspective Insights from a Business Partner

What Analytics Means to Law Firms of All Sizes

One of the principal challenges in legal management — both for managing individual associate work and entire law offices — is the inadequacy of the billable hour for measuring internal performance.

While billable hours are a convenient way for firms to assess legal fees for clients, they inherently fail to value productivity gains: If a new technique or technology allows an associate to complete the same work in less time, that associate will bill fewer hours per assignment than an associate using obsolete practices, earning the firm less in fees. As clients demand greater transparency for their legal spend, firms will need to show clients ever-increasing productivity per billable hour to justify their billing rates.


For best practices to evolve and continue to meet more demanding client expectations, firms need more granular metrics to evaluate attorney performance. How quickly does each associate respond to partner emails? How often does she turn in work on time? Does she take less or more time than is typical for similar assignments? Is her work usually acceptable the first time, or do partners often send it back for major revisions?

Some of these factors find their way into performance reviews but are largely based on partners’ subjective impressions.

The problem with this approach is twofold. First, even if the partner is trying to be fair to each associate, the partner’s perception of each associate inevitably will come from anecdotes that may not reflect the associate’s overall performance and are colored by the partner’s unconscious biases. Second, if a problem has been recurring often enough to be noteworthy at a performance evaluation, it means that it has already cost the firm.

But now that attorneys use network-connected software to complete most of their legal work, continuous performance evaluation has finally become practical. Virtually everything attorneys do with software generates metadata, from email timestamps to research site logs to document version control. Most larger law firms can gather and compile this metadata on an ongoing basis without requiring attorneys to do anything outside their normal routines.

Knowing how quickly each associate responds to emails from partners, clients and other associates gives partners much better insight into whether both individual attorneys and the office as a whole are functioning properly.


For example, one of the simplest metrics to compile and analyze is associate email responsiveness. Because attorneys conduct most of their communications via email — and because the volume of emails each attorney sends and receives per day is large enough to generate a meaningful data set over time — firms can use email metadata to get a much better sense of whether their attorneys are communicating effectively.

Knowing how quickly each associate responds to emails from partners, clients and other associates gives partners much better insight into whether both individual attorneys and the office as a whole are functioning properly.

Firms can also use data from their time-tracking software to determine whether associates are working effectively. Using this data, firms can compare how much time associates use to complete similar assignments. Particularly for larger firms generating bigger data sets, algorithms can increase the signal-to-noise ratio to the point where it becomes possible both to track trends in attorneys’ efficiency over time and compare different attorneys’ efficiency. This allows firms not only to determine whether capital investments are bearing fruit, but also increases transparency to clients in showing them how those investments translate into better value per billable hour.

Knowing how much time associates actually need for each assignment also gives law firms more predictability when offering clients alternative billing arrangements, such as flat fees.


The real potential of using analytics based on metrics that more closely reflect day-to-day attorney performance will come not from the obvious ways firms can use them to tinker with policy changes, but from the otherwise invisible patterns that will emerge from the data.

As it happens, Uber was market-testing a side-by-side view of carpooling and individual ride prices in the DC-metro area at the same time ILTACON was happening. For most trips in the area, these cost savings were not significant. But for certain routes, such as passing by Reagan National Airport, the near-certainty of being able to pick up an additional passenger on a quick detour allowed Uber to offer savings of as much as 80 percent, cheaper than even taking the Metro.

Of course, it is impossible to know what kind of dramatic opportunities for attorneys the data will reveal until firms begin to gather them, but we know how to find them. Firms can now analyze the fundamental day-to-day interactions between attorneys in ways that would have been impractical even a few years ago.