A key ingredient needed to reduce legal cost and improve lawyer performance is missing: research and development.
Let’s start with what we see in the legal market:
- A few general counsels are changing how they manage law practice, both internally and with outside counsel.
- A larger number of GC whine about costs but take little visible action to control them other than demand discounts.
- A bevy of commentators (including me) opine about how the legal market should operate and who should do what.
- A handful of outfits produce empirical data about and benchmark BigLaw but focus more on what is than what might or should be.
What we don’t see is observable, significant R&D to achieve efficiency and cost goals. To be sure, there is some trial and error testing. But that’s a far cry from systematic, controlled study. Let’s first consider the dollars and cents of R&D, and then what a R&D budget might fund.
On the money side, The National Science Foundation reports that non-Federal R&D funding has fluctuated between 0.6% and 1.2% of gross domestic product. Applying the low end of the range to the corporate law market of about $100 billion would mean $600 million on R&D. I’d be surprised if anyone could even identify $6 million of R&D.
Of course, some might argue that it’s appropriate to spend very little on R&D in legal. But consider how much companies spend on legal. Serengeti reports that $10+ bil companies spend about 0.3% on legal. That’s $30mil annually with a lifetime cost (NPV) of $600 million at a 5% cost of capital. That’s big. R&D to lower that legal cost might be a very good investment indeed.
The Chicago School (“whatever is, is right”) might argue that the apparent lack of R&D suggests that the market thinks savings are not possible. I think the better conclusion is that market structural problems make investing in R&D nigh impossible.
If funding were available, promising R&D might include:
- Develop defensible automatic / predictive coding for litigation document review. . We all now that doc review costs are huge. Many e-discovery (EDD) experts believe that computer generated document designations for responsiveness and ultimately privilege are more accurate and reproducible than human review. The computer approach is certainly cheaper than humans. So if I were a GC facing on-going, sizable doc review bills, I would consider R&D to support creating a defensible automated approach. Doing so is not rocket science. More likely, it’s a brute force process, specifically, paying to review document collections twice – once the “traditional” way and once the “new” way – and then comparing. (Ok, perhaps over-simplified but you get the idea).
- Determine the right level of preventive law (including training). The best way to reduce the cost of lawsuits and government investigations is to avoid them. Figure out how much preventive law is worth doing. This will mean data collection, probably some retrospectively but more likely most prospectively.
- Figure out how much contracting is really necessary. America spends a lot on drafting contracts. How much is all this ‘paper’ really worth? Might a term sheet with a simple cover contract suffice? Heresy? We obsess to paper everything because we fear something bad will happen. But where are the data showing that our current cumbersome approach to contracting really minimizes end-to-end cost? Perhaps data analysis would show we really do not need such complicated contracts.
- Go crazy with data that might contain hidden legal signals. I was inspired by Insurers Test Data Profiles to Identify Risky Clients (WSJ, 19 Nov 2010), which describes how some life insurers are using a wide range of personal data to see if it’s possible to avoid medical exams in underwriting policies. They use huge amounts of inexpensive personal data (perhaps raising privacy concerns) as a proxy for what expensive blood tests and physical exams would otherwise show. Is there a moral equivalent in legal? What data would we have to analyze to find risk proxies? To be a little more specific, how many companies analyze the connection between their vast troves of operational data and their legal spending to see if they can find correlations that signal problems.
- Mine the data we already have. GC and law firms are sitting on huge volumes of fee-earner timekeeping data. Do something with it. To make it more useful, R&D may be required to extract automatically from text descriptions an appropriate task code. Once that’s done, pay statisticians, data modelers, and others to figure out what it’s telling us.
I’m not saying that budgeting for or doing research is easy. Only that there is a crying need to at least consider some fundamental research to reduce legal spending. If the GCs with budgets in excess of, say, $100 million are not willing to invest in R&D, who will be? Perhaps the answer is collective action (subject to antitrust considerations).
Readers, what do you think? Would RD pay off? What might it find? And who should do it?
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