publication of the International Legal Technology Association
Issue link: https://epubs.iltanet.org/i/355985
ILTA WHITE PAPER: JULY 2014 WWW.ILTANET.ORG 36 To illustrate this, we will assume lawyers will now have access to the average cost of a deposition. For argument's sake, we will set this at $25,000. What good is this information? Lawyers don't sell depositions, and clients don't buy them. True, the benchmark might be useful in a situation where a client needs to decide how aggressive they want to be in litigation and where the number of depositions is an issue. But, even then, it is only a high-level benchmark. The actual cost of a given deposition will vary significantly from the average. At best, your data will serve as a starting point for a discussion about the price of a task (not the matter or even a phase), but not as a reasonable price for all depositions. Knowing past fees for depositions to calculate an average will have little impact on how lawyers sell their services. To further test my presumption, consider if we knew the fees for a phase. Surely, that would be useful! For this example, let's set a discovery price at $200,000. We could pitch this as a price for the discovery phase of litigation. What type of litigation are we talking about? Now we are back where we started. The range of past fees for this phase will vary significantly depending on the type of litigation. We have just gone back down our CRM path. I am not saying we will not eventually want to know this level of detail in the cost of services firms provide. What I am saying is we need to be very thoughtful in the way we apply data analytics to KM, especially with financial information. Task codes were designed with a specific purpose in mind. Clients primarily want to be able to filter out effort they do not see value in and eliminate it from their bills (e.g., online legal research services). Task codes were not designed to help you understand the cost per unit of services firms provide. Promising firm partners that these task codes will answer their pricing needs is not a good idea. Today, when a lawyer has a pricing need, it is most often at the matter level. Many times it is not even a price they need, but merely a budget. This might be a better area in which to apply data analytics. BEGIN WITH SCOPE TO BUILD BUDGETS What lawyers really want is a magic button they can push that will generate a budget to present to the client. Putting aside the fact that the magic button doesn't exist, let's start with the problem — determining scope. There is some value in past financial information in determining budgets, but budgets are built, not pulled from a bucket. When you take your car to the mechanic, they assess the situation and then come back with the scope of the problem. As the client, you then decide how much of the scope and cost presented to you meet your value proposition. An added level of difficulty for legal is that every case is unique. Depositions are depositions; they all have the same basic steps. However, each deposition brings a different value proposition to a case. This brings us back to scope. Without knowing the scope and value proposition for the client, deciding on a budget for every deposition is like shooting in the dark. THE TAKEAWAY FOR KM Where does this leave KM? I would say, in a better place. Starting with a good understanding of the problem brings focus to how KM can help law firms adapt to change. What lawyers really need are budget-building tools. They need to be able to define and understand scope in a relatively simple fashion. They will then need simple tools to construct budgets around the scope. With a budget draft in hand, they can assess the profitability of the budget. While it is helpful to compare costs against past work as a benchmark, those benchmarks will need to have similar scope. Data analytics can help in this process, but asking what if the data were perfect might be a good way to start in assessing how to best deploy your strategy. WHAT IF THE DATA WERE PERFECT?