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Eisenhower said what's urgent is rarely important, and what's important is rarely urgent. Until recently, this was the problem with efforts to standardize legal data—it was easier to kick the can down the road than get everybody on the same page. But today, 87% of corporate law departments are subject to demands that they become more data-driven, which is hard to do if people define the same thing differently.

A number of forces are coming to the rescue. A high-profile industry group is pulling in new data to supplement the existing Uniform Task-Based Management System (UTBMS) codes Second, a new type of professional is poised to play a critical role in taking legal data where it needs to go. Finally, new artificial intelligence tools have come to market that greatly increase the value of quality legal data and provide a greater incentive to ensure it is standardized and clean.

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Legal Data 2.0

In May 2017, a group of leading law firms, corporate law departments, legal technology companies, and others established the SALI initiative, which aims to standardize the reporting of legal work based on the type of problem solved, rather than the effort expended to solve it. SALI released the most recent version of its standard in early 2020.

Let's say a public healthcare company based in the UK is buying a German LLC in the nursing and residential care industry for $40M Singapore dollars. SALI codes can capture all those details in a standard way and allow legal organizations to identify comparable matters from their own data or in anonymized, aggregated databases. Those comps can then inform pricing and other legal ops-type conversations. Think Zillow for legal matters.

However, Zillow for legal matters isn't going to work if your data quality is poor. We cannot depend on lawyers and paralegals, by themselves, to take responsibility for data quality. It isn't what they want to do, are trained to do, or get rewarded for.

We should take a cue from the medical field, which has over 180,000 professionals dedicated to ensuring medical procedures are coded and invoiced properly. These legal data specialists already exist at a few leading law firms and will probably start cropping up in corporate legal departments (CLDs) soon. Since they don't have to handle legal problems, legal data specialists can focus on their core mission: improving data quality and policies and procedures around it.

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Why Not Start Now?

Data quality often sounds like an abstract goal, but AI is helping to realize a concrete payoff. AI products which predict litigation costs, settlements, cycle times, and outcomes, can help establish case budgets, alternative fee arrangements, milestones, settlement strategies, and other key decisions in legal project management.

The catch: Only law departments that have quality data will be able to take full advantage of these tools. AI can't spot patterns in data that doesn't exist and will provide less accurate predictions where underlying data is inaccurate. AI-driven tools will only continue to mature and make more tasks easier—yet another reason for CLDs to get their data ducks in a row.

There are more reasons than ever to create institutional structures that improve and maintain the quality of legal data. So why aren't more CLDs doing it? For many, the prospect is overwhelming, until they realize they can start small. Pick just a few data points and standardize those first.

If you have 500 data fields, you will extract the bulk of the value from a fraction of them—about 80% of value from 100 fields, and 80% of that subset's value from just 20 fields. That's 64% of the value in just 20 fields. The fact that you will likely want to do more in the future is no reason to forego quick wins now. Get your department into the discipline of making data quality a true priority at even a small scale now, and you'll be prepared to reap major rewards.

Nathan Cemenska, JD/MBA, is the Director of Legal Operations and Industry Insights at Wolters Kluwer's ELM Solutions. He previously worked in management consultancy helping GC's improve law department performance and has prior experience as a legal operations business analyst. In past lives, Nathan owned and operated a small law firm and wrote two books about election law. He holds degrees from Northwestern University, Ohio State University and Cleveland State University.