Articles Posted in Benchmarks

General Counsel Metrics will offer Industry Analyses starting after the second release of its global benchmark survey in July. Each of the 25 Industry Analyses available offers deeper insights than the no-cost, 60-page Standard Report.

I strongly believe that general counsel should look only at benchmark metrics from companies in their own industry (See my post of March 28, 2011: an example of why industry benchmarks provide by far the most useful insights; Dec. 27, 2010: large benchmark surveys can present “sector” data; and Jan. 3, 2011: absolute numbers of staff, even by industry, afford little insight.).

Since my first metapost on industries in relation to benchmarks, I have added the three in the preceding paragraph plus 11 more (See my post of March 2, 2010: industry benchmarks with 8 references.). Some address an index I have created called “legal intensity” (See my post of Aug. 3, 2010: differences in legal intensity of industries do not cause assessments of primary firms to vary much; Dec. 1, 2010: 20 industries ranked by “legal efficiency”; Dec. 31, 2010: rankings of industries by benchmark metrics and participation rates in survey; April 12, 2011: legal intensity and the competitive level in an industry; and Oct. 31, 2011: industry intensity revisited one year later.).

On a pace to exceed 1,000 legal departments, the first release this year of GC Metrics survey of 2011 staffing and spending goes this week to the 332 departments that have submitted their data. The lengthy report focuses on 25 fundamental management metrics, such as lawyers per billion of revenue, for 23 industries. It also provides medians by revenue of company and size of law department and country.

New this year also are optional questions about compensation and contract management software. Participants in the no-cost survey will learn findings about those later this year.

You can get the first release promptly whenever you take the survey. Go to the confidential survey site and provide your identifying information and the six pieces of data asked for. All data is normalized and only medians and quartiles are published in the report.

A ground-breaking report, which combines data on matter management systems (MMS) with benchmark metrics, is now available from General Counsel Metrics, LLC. MMS Insights reports on 130 users of more than 15 matter management systems in Canadian and U.S. legal departments.

Typically, a large share of the spend by a company on outside counsel is captured in its MMS (if it has one). A table in Insights shows for each package the median amount spent per lawyer on external counsel and other vendors. The median stands at $496,000. The U.S. and Canadian medians from this year’s General Counsel Metrics benchmark survey are reasonably close to the medians of this group of law departments.

Broadly speaking, the finding from MMS Insights suggests that $10,000 per week for each in-house lawyer is processed by MMS software. Litigation lawyers account for the largest share of that spending, in the range of 40-50 percent.

The Fortune 500 amassed revenue of close to $10 trillion in 2011. At five lawyers typically for every billion of revenue, they alone would employ something like 50,000 in-house lawyers. What else can we cobble together about the number of law departments in the United States.

With something like 25,000 law departments in the United States (See my post of Sept. 25, 2005: ACCA estimate of 71,000 non-governmental in-house lawyers; Dec. 3, 2006: possible Fortune 500 staff figures; Dec. 31, 2008: oblique data suggests about 21% in-house; March 9, 2009: ABA data and 8% in-house; April 2, 2009 #2: data from 1961 to 1991; June 15, 2009: almost one out of five lawyers in a large survey had gone in-house by their seventh year of practice; Oct. 7, 2010 #1: US has 30,000 companies with 100+ employees; Dec. 31, 2010: clues from subscriptions to trade journals and listings of largest law departments; July 20, 2011: estimates 30,000 departments; and Dec. 20, 2011: closer to 30,000 departments. ), employing at least one lawyer per department – call it 20,000 more. Governmental legal staffs contribute more – a pure guess at 15,000 federal and 20,000 state and local (See my post of May 13, 2012: law departments of government agencies.).

OK, so how can we correlate the estimate of 100,000 in-house lawyers to other facts? There are approximately one million lawyers practicing law in the United States, but 500,000 of them are solo practitioners who do very little corporate work. Take away 100,000 in-house lawyers from the remainder, then that leaves 400,000 in multi-lawyer private practices.

Here is a classic example of the distorted benchmarks produced by from some small companies. The Graduate Management Admission Council (GMAC) manages the GMAT test taken worldwide for admission to business schools. The current general counsel joined ten years ago as the only lawyer for the non-profit’s 34 employees. Today, the legal department has grown to 9, including 3 more attorneys while the number of employees has tripled to 140.

GMAC’s benchmarks are bizarre. Its 4 lawyers for 140 employees (28 per thousand) blows away typical metrics (See my post of Jan. 31, 2102: median in U.S. of about 2 lawyers per thousand.). Or consider a second common benchmark. The article on this in the ACC Docket, March 2012 at 92, doesn’t give the revenue of GMAC, but its website says that more than 200,000 people took the test last year. At $250 per taker, that revenue would have been around $50 million. Let’s double it because of (presumed) other GMAC services and to be very conservative. That would mean 40 lawyers per $1 billion, which from the General Counsel Metrics survey is eight times higher than the median benchmark.

Small companies haven’t yet grown enough to settle into more typical benchmark metrics for legal departments. For that reason, medians have much more legitimacy than averages.

Here are metaposts on seven domains of mathematics that play a role in legal department management.

Bayesian statistics (See my post of April 5, 2009: Bayesian statistics with 6 references.)

Bell curves and normal distributions (See my post of March 12, 2009: bell curves with 8 references.).

Regular readers of this blog understand, or at least have heard of, distributions of data that look like a bell. Many toward the middle hump; tails of less frequent amounts on either end. Invoice amounts for large law departments follow that pattern, for example. Some readers might even speak comfortably about standard deviations (See my post of March 12, 2009: bell curves with 8 references.).

Along with normal, bell-curves there exist many other mathematical distributions of data, several of which this blog has covered. Legal managers who aspire to sophisticated data analysis should familiarize themselves with these ways to describe and understand data.

For example, a power-law distribution has a dominant number, a significant drop off to the next number, a lesser drop to the third, and on down to the proverbial long tail (See my post of April 27, 2010: power-law distributions with 6 references.).

Nonlinear systems occur when “outputs of a system cannot be expressed in terms of a sum of inputs, each multiplied by a simple constant.” The quote comes from John Brockman, Ed., This Will Make You Smarter (Harper Collins 2012) at 184, a piece on scale analysis. If a formula could capture the output of law departments, life and management would be so much simpler: X times number of lawyers plus Y times number of paralegals and Z times other staff plus A times the dollars spent on outside counsel equals output! For any given law department, its four inputs multiplied by their respective constants would capture it all. Not so, of course.

Law departments are non-linear, with complexity the dominant characteristic: “Unpredictable variability, tipping points, sudden changes in behavior, hysteresis – all are frequent symptoms of a nonlinear world.” We can hold out no hope for a linear function that describes law departments.

The drivers of legal costs are many, but certainly one of them is the pace of change and growth of an industry segment. I would hypothesize that an industry’s pace correlates well with total legal spending. How might research quantify that ferment fomented?

An article on corporate governance published in the Acad. Mgt. Rev., Feb. 2012 at 140, uses a measure for “industry dynamism.” The researcher created the variable by “regressing industry sales over time for the prior five years and using the standard error of the resulting regression coefficient.” I have written the author to find out more about the math and the robustness of this method. It does seem eminently reasonable that the more an industry grew during the five years before a given year, the more “dynamic” it should be deemed. Benchmark metrics on legal spend should rise and fall with industrial dynamism.

In the world of claims management, predictive analytics has blossomed lately, at least according to an article in Lit. Mgt., Spring 2012 at 44. “Predictive analytics is the analysis of data through statistical or mathematical techniques that results in meaningful relationships being identified in the data.” Informed by predictive analytics, claims managers can make better decisions. In the authors’ apt wording, predictive analytics can help claims staff “allocate the right case to the right law firm at the right price.”

Litigation management presents more complexity than claims management, so the tractability of predictive analytics is lower. The return, however, on effective analysis may be higher. At this time, the authors point out, few law firms think in terms of data mining and analysis; worse, the authors don’t even mention law departments as sources of data mining. For predictive analytics to pay off, generous sets of data need to be available and law departments may in fact have an edge.