publication of the International Legal Technology Association
Issue link: https://epubs.iltanet.org/i/355985
ILTA WHITE PAPER: JULY 2014 WWW.ILTANET.ORG 35 Even with good data, the promise to win work is built on an assumption that lawyers either obtain work in this fashion or that they will change the way they pursue work along the lines of the technology. This is not how lawyers work. In fact, this idea runs counter to how many of them develop and manage client relationships. They have economic motivations driving them in the opposite direction. First, they protect their client relationships in order to maintain their billing attorney status with a client. Second, introducing new partners to a relationship can jeopardize the relationship, especially if the new partner does not manage the relationship well. Of course, lawyers should be doing it the way the CRM demo suggests. That would be best for the firm and eventually for them. But, for the most part, they don't and they won't until compensation systems change. Why go down such a tortured path? It is a good lesson for legal KM professionals. Perfect data and great technology are not enough, even when both are dedicated to solving a clear problem. Project management (PM) as a discipline has words of wisdom for KM teams: people, process and technology. More specifically, PM addresses these needs in that order. Technology should follow the needs of the people and then the process they use. These same people should always be improving their processes, driving the need for new technology. Many law firms have approached KM challenges in the opposite order, putting technology first and expecting people and process to follow. THE MORAL The moral of this story is not that legal KM professionals should avoid data analytics. The real moral is that they should understand customers' needs, behaviors and processes before developing data analytics solutions. KM should be laser-focused on solving lawyers' practice challenges, and there are many of them. They should also learn from the past in order to avoid repeating it, especially now that the KM stakes are growing so much higher. A good question to ask your partners is: What is keeping you up a night? An answer you will probably get is: Figuring out pricing that helps me win work. TASK CODE CONSIDERATIONS I can tell you from experience that many times the topic of pricing leads to a discussion about task codes and comments such as "If we only had task codes, we would know how much past matters cost and thus know what to charge for a given piece of work." Let's follow that path of layering in data analytics and applying task codes. One seemingly obvious place to apply data analytics would be with a firm's financial information. This is high-value knowledge typically poorly structured. Pricing people struggle daily with how to find value and leverage financial knowledge to improve the firm's chance of winning work and enhancing profitability. It also seems obvious that firms need better financial detail on the work they perform. Doesn't it make sense to find a solution that would programmatically code all of a firm's time entries with task codes? This firm would have a competitive advantage for sure. WHAT IF THE DATA WERE PERFECT? So let's apply our "what if the data were perfect" magic wand. What if a firm had perfect knowledge about the task codes for every time entry in the system? I believe this firm would face a situation similar to the CRM scenario. This approach presumes lawyers will change and use this knowledge and any related systems to win work. The fact is they probably won't. Programmatically coding time entries is an advanced version of data analytics, and many people express interest in it. Utilizing technology similar to predictive coding as applied in discovery, the text of documents are "read," and the nature of the content is predicted. Some providers are claiming they have the ability to perform this type of analytics on time entries. One example is LegalBill.