What if there were a better way to hire lawyers?

The College of Law Practice Management recently announced its 2012 InnovAction Award Winners. The InnovAction Awards recognize outstanding innovation in the delivery of legal services. The College conveniently not only declared a winner, but helpfully made available all the entries received. There are some excellent projects here (not surprisingly, many of them incorporate some aspect of knowledge management and/or legal project management).

One entry which caught my eye (and kind of scared me) is from LawyerMetrics, which claims to have developed a “Data-Driven Lawyer Hiring Method”.  I’m not entirely clear on what this (it sounds suspiciously like math) but because I just spent a week slogging through over 200 articling student applications to winnow the field down to one eventual hire, I was intrigued. Imagine – enter all the info into LawyerMetrics blackbox program and – voila!- your perfect lawyer.

The company says it uses a “Moneyball analysis” to…well, here, let them tell you how it works:

Research shows that the most popular hiring tool in law firms―the one-on-one interview―ranks only slightly above a coin-toss in its ability to separate good from poor prospects [really? I could have just flipped a coin??]. Simply hiring someone because of a shared favorite sports team works just as well. Using a data-driven, scientific method called a Biographical Inventory, Lawyer Metrics increases a law firm’s ability to identify high performers and weed out low performers during the interview process. Also known as a “Moneyball” analysis, this methodology examines the pre-hire traits such as grades, clerkships, and pre-law work that can be used to predict a candidate’s likelihood of success at a particular law firm. Other industries have proven similar hiring methods to be three times more effective than one-on-one interviews. By adapting the methodology to the legal industry, Lawyer Metrics has helped several law firms increase their probability of identifying A players by 10-33% and eliminating C players by 50-60%. By leveraging a law firm’s own talent data, Lawyer Metrics enables the firm’s leadership to hire and retain the lawyers who are best suited to service the needs of their clients….

Fascinating. Call me old-fashioned, but I’m still wedded to the face-to-face interview – even though I can’t muster any scientific or statistical analysis to support my preference. I suspect it has something to do with the fact that billions of dollars of business are done every year over lunch….which suggests to me that there might be some merit in this vague and sloppy method. On the other hand, data-driven selection might have the advantage of curbing the most egregious incidents of discrimination (“Really? You went to Old Money U., too? And a cottage on the same lake as well…..you’ll fit in just fine!”).

 

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About InfoLawyer

I'm an cybersecurity, data protection and privacy lawyer lawyer at the Toronto law firm of McCarthy Tetrault. When not writing here, I am writing restaurant reviews for Precedent legal magazine or using the backs of restaurant napkins to work out the odds of whether I can be replaced by an artificially intelligent machine (this week's odds are 70:30).
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