E-Discovery Software

Last year, The Wall Street Journal reported on a BTI Consulting Group survey indicating that large companies intend to spend more than 7% of their litigation budget on e-discovery this year.

The ABA Journal cited the article, noting that:

"The right software can help reduce the number of documents needing attorney review, helping save money..."

For example, Morgan, Lewis & Bockius used “predictive coding” software made by Recommind Inc. to review millions of pages of documents in less than a month.

Cisco recently started utilizing the same software.

As Recommind explains, Predictive Coding is "a patent-pending technology and workflow which automatically analyzes, prioritizes and codes all documents in a collection as part of litigation or regulatory or internal investigations."

However, as the Recommind site also explains, predictive coding is not a replacement for attorneys.

It is simply a more efficient addition to the sorting component of the workflow and documentation process -- a process that still requires attorney review and analysis, which is itself an area abundant with potential added efficiencies and cost savings.

Moneyball for Lawyers?

The November issue of National Jurist featured an article by University of Indiana law professor William Henderson advocating big changes in the way law firms assess which candidates to hire and train, and that article has prompted quite a bit of discussion.

The Wall Street Journal says that Mr. Henderson "pokes a variety of holes in the way big law firms have gone about their hiring for decades and decades — essentially luring the folks with the highest GPAs at the top 15 or so law schools."

The ABA Journal reports that Henderson's company, Lawyer Metrics, will apply a "Moneyball" approach to help quantify what qualities partners seek in an associate (referencing the best selling book about Oakland A's General Manager Billy Beane, who introduced a revolutionary statistical-based method of evaluating baseball prospects).

Henderson himself writes as an example that, "In 2007 and 2008, 46 percent of all entry-level associates at an AmLaw 100 firm were graduates of a Top 14 law school . . . Yet, during this same period, 39 percent of lawyers promoted to partner were from Top 14 schools. Further, as of 2009, only 35 percent of general counsels for a Fortune 500 company had graduated from a Top 14 school. This suggests that the advantage of higher test scores and academic pedigree diminishes rather than compounds over time — at least for partnership or general counsel positions."

Steven Harper at AmLaw Daly voices concern that Henderson's data-driven approach won't account for "politics and luck."


The Moneyball analogy is apt if Henderson is taking a bottom-up approach -- since Billy Beane first looked solely at unbiased statistical data and then taught managers and scouts a new way of assessing talent based on the data.

However, if as AmLaw Daly reports, Henderson's approach includes asking partners "about what values and traits they want in their lawyers", then his method is a top-down approach that is the exact opposite of Moneyball.

The goal should not be to assess the data in light of what partners already think they want.

If Henderson really wants to act as Billy Beane would, he needs to assess the data and then tell partners what they should want, even if what they should want is very different than what they think they want.