ABA Journal

The New Normal

Legal machines give lawyers the structure we need

By D. Casey Flaherty

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D. Casey Flaherty.

Lawyers excel at creating structure. They can weave disparate facts and convoluted laws into a coherent narrative that persuades a judge or a jury. They can merge two unrelated entities while navigating a complex regulatory environment. They can transform inchoate business ideas into a comprehensive contract that covers contingencies that never entered the thoughts of those who negotiated the original terms. Creating structure is important because it is not naturally occurring.

One of the great challenges and opportunities in the modern legal industry is giving structure to unstructured data. The Word document you save to your laptop is unstructured. When you save it to the document management system, it becomes structured (or semi-structured depending on how the system works). In theory, it is not only easier to find structured documents, it is also easier to organize, search, and categorize them.

When data is unstructured—think of all those locally saved Word, Excel, and PowerPoint files stored across a company—it becomes a real pain at scale. A business with a bunch of “loose” contracts has to review each of them to figure out which agreements are up for renewal—a problem that gets worse as the business grows. A business with a good contract life cycle management system (i.e., contracts as structured data) should be able to identify all such agreements in a matter of minutes, no matter how large the company. Most enterprise data is unstructured. Much of the software development in and around contracts, compliance, due diligence, and e-discovery is aimed at bringing structure to unstructured data (recommended: this talk from DLA Piper Chief Information Officer Daniel Pollick).

But structure only goes so far. The usefulness of the structuring data is largely dependent on data integrity. Garbage in, garbage out. One of the great tragedies in the modern legal market is that we are data rich but information poor—information being data organized in a way that is useful for decision-making. Our primary source of historical information for how we work and what we do should be our billing records. But our bills are polluted with garbage data. There have been many attempts at using machines to add more structure to our invoice data. To the extent the objective is finding problems with the data, it works wonderfully. To the extent the purpose is finding meaningful patterns and guiding future action, we still have a long way to go.

As I detailed throughout this series, we are terrible at creating and reviewing invoices. We are terrible, in part, because creating and reviewing invoices is soul-crushing, and we want to spend as little time on it as humanly possible. Given our human disdain for it, I say leave the invoices to the machines.

Moving backwards. Law departments and law firms should be interested in changing behavior. A data-driven approach to changing behavior would include applying analytics to large data sets. In theory, you figure out what work is being done by whom for how long and then measure progress if you decide to change the what, who, or how long. But before you can do that analysis, you need better data. So the algorithms can be deployed to look at each line item and enforce more entry discipline, including firms cleansing the data before it is sent to the client.

While judgmental algorithms might ultimately improve entries, they do not make information-rich entries easier to generate in the first instance. There is, however, no reason why most entries need to be written from scratch or in isolation. The analytics and the algorithms can also be used to help construct well-defined workflows populated with categories and prewritten narratives that can then be supplemented with color commentary via digital dictation or text expansion. The associated time capture can be largely passive—with the machine monitoring open documents, calendars, and phone calls to recommend time allocation.

Making time recording more accurate and more contemporaneous then lends itself to better real-time transparency of work in progress, including project status and performance against budget. Clients and law firms can get past arguing over invoices months after the damage is done. Instead, they have the opportunity to course correct in a collaborative fashion.

The foregoing is a more technologically enabled version of the status quo. It need not be. Again, the objective is to change behavior for the better. The structures, processes, and technologies outlined drive better budgeting, planning, resource allocation, tracking, communication, and after-action reviews. Alleviating work that clients and firms loathe will permit them to focus their energies elsewhere, including re-engineering workflows or moving to, and monitoring, value fees.

We’ve already created a low-trust equilibrium where clients are unwilling to take their lawyers’ word for it and frequently are uncomfortable agreeing to a price without some transparency into costs. Time is a cost that we use as a (poor) proxy for value. Knowing your costs is important. Yet arguing about costs at the subatomic level, line-by-line, invoice-by-invoice, month-after-month, year-after-year is getting us nowhere.

Technology helped create this mess—the introduction of computers is intimately tied to the transition to the billable-hour regime. Technology has a role to play in cleaning it up. But as I end an arc that has tried to gently talk about analytics, algorithms, machine learning, and, finally, structured and unstructured data, let me give my standard caveat: technology is not “the answer.”

Technology is absolutely essential to the modern practice of law. Some technology (email) is simply inescapable. Some technology (e-filing) is required. Some technology (e-discovery, due diligence) is necessitated by the downstream impact of other technology. But being essential and being easy are not the same thing. There is no Easy Button. Technology rarely just works. Buying technology is not coterminous with the complementary training and process redesign necessary to productively integrate it into the delivery of legal services. Human behavior actually has to change. That’s a big topic for another arc.

D. Casey Flaherty is a consultant at Procertas. Casey is an attorney who worked as both outside and inside counsel. He also serves on the advisory board of Nextlaw Labs. He is the primary author of Unless You Ask: A Guide for Law Departments to Get More from External Relationships, written and published in partnership with the ACC Legal Operations Section. Find more of his writing here. Connect with Casey on Twitter and LinkedIn. Or email [email protected].

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