Articles Posted in Benchmarks

The members of a law department yield many descriptive metric (See my post of Feb. 26, 2009: start of a series on such metrics.). To review, a descriptive metric puts some aspect of a law department in numeric terms, which encompasses traditional benchmarks but goes beyond them to quantify less common features. This post focuses on lawyers, but the same principles apply to all other legal staff.

At the personal level, descriptive metrics arise from various characteristics of lawyers in a department (See my post of Nov. 28, 2007: average tenure of lawyers and years out of law school; Nov. 28, 2005: quality of law school attended; Aug. 29, 2008: LSAT scores and general counsel success; June 26, 2008: lawyer experience correlated with staffing and spending; Sept. 4, 2005: demographics; April 16, 2007: talent index with several descriptive metrics; and Sept. 25, 2005: lawyers work an average 6 years before moving into a company.). Diversity figures are descriptive metrics as are psychometric instruments create them (percentage of ENTJ lawyers in a department!).

Beyond descriptive metrics about personal attributes of the lawyers, many are possible for compensation (See my post of Aug. 27, 2008: compensation by levels with 18 references.). For example, the percentage gap between the highest and lowest paid lawyers of a given compensation band; the proportions of base, bonus, and incentive; and average salary increases over three years. Another could be vacation days (See my post of Feb. 22, 2009: vacations and holidays with 10 references.).

A benchmarking study of law departments in EMEA (Europe, Middle East and Africa) collected data for 2008 from 123 departments. Conducted by Laurence Simons, a leading legal recruitment firm, and this author, the report is available for a nominal cost from Laurence Simons. The report contains recommendations for most of the benchmarks as to how to alter your law department’s metrics.

Four differences stand out between the EMEA and US data.

Higher number of lawyers per staff member than in the US. The difference results partly from the scarcity of paralegals in EMEA.

Someday we will be able to describe with numbers most of the primary characteristics of any law department. Such “descriptive metrics” are numbers that convey something about how a law department operates. For example, concentration of spending on law firms: 75 percent of all spend in a year went to 10 percent of the firms paid. If many law departments use the same cutoff (75%), then we will all have a standard descriptive metric to describe one operating characteristic of all law departments. Another is the average years of a department’s lawyers since graduation from law school.

Benchmarks are descriptive metrics, but I believe there are many, many more. As with XML coding, we need standard ways to define and calculate descriptive metrics. Accordingly, this post begins a series of six posts that explore law department descriptive metrics.

Once descriptive metrics are defined and generally accepted, the next step will be to benchmark them. The final step will be to study the correlations of descriptive metrics with practices and performance indicators (See my post of Feb. 12, 2008: surveys ought to correlate metrics with practices.).

While discussing power laws, the McKinsey Quarterly, 2009, No. 1 at 13, argues that power curves for revenues of businesses (the sorted distribution of revenue, for example) are often a function of “intangible assets — talent, networks, brands, and intellectual property — because those assets can drive increasing returns to scale, generate economies of scope, and help differentiate value propositions.”

Different sectors of the economy show power-curve distributions of inequality in market value. Research shows that the more labor-or capital-intensive sectors, such as chemicals and machinery, have flatter curves than intangible-rich ones, such as software and biotech.

This power-curve pattern may explain variations across industries in lawyers per billion of revenue (See my post of Feb. 19, 2009: compared to revenue per lawyer; and Dec. 14, 2005: legal intensity of regulation.). “Intangible-rich” industries such as telecommunications, software, finance, and biotech have more lawyers per billion of revenue than industries that are less suffused with intangibles. Intangible-based businesses generate more legal work than companies that rely on machines and land, hallmarks of “labor-or capital-intensive sectors.” For example, intangibles require more patents, more licenses, more complicated joint ventures and other agreements than does selling objects. The correlation between intellectual capital and legal intensity may be strong and positive and explain the relationship between lawyers per billion and intangible density among business sectors.

Maybe this is six of one, half a dozen of the other. I think that lawyers per billion lets someone more quickly compare their metric to another company’s metric or a benchmark survey. “If the figure is 5 per billion and we are 2 billion, we should have 10 lawyers (2 times 5).”

However, revenue per lawyer is more grounded in reality and seems more tangible. “If the metric is 200 million per lawyer, and we are at 250 million per lawyer, we are a bit ahead of the benchmark group.”

You pays your £€¥$ and you takes your choice.

Lloyds TSB paid roughly $18 billion to take over HBOS but the merged financial giant decided to keep the HBOS general counsel as its top lawyer. As disclosed in Corp. Counsel, Vol. 16, Feb. 2009 at 52, Lloyds has a team of about 25 lawyers in its London headquarters while HBOS had some 50 lawyers when the rescue took place. Typically, the acquirer’s general counsel takes over the merged legal department (See my post of Jan. 30, 2009: Bank of New York acquired Mellon.).

On a side note, the article added that the estimated annual legal spend of HBOS was about $44 million. Note the closeness of that ratio (about $808,000 total legal spend per lawyer) to the rule-of-thumb number of about $1 million in TLS per inside lawyer.

The Small Law Department Compensation Survey, conducted in the summer of 2008 by ACC and Empsight, collected responses from 337 organizations. The average revenue of the companies was $500 million with the median revenue of $152 million. A year or so ago I published an article about these three metrics.

Staff: Even among this smaller size group, where there is at least one attorney the ratio of one lawyer to one non-lawyer holds. Most law departments hit a balance of approximately equal staff numbers.

Revenue Supported: Attorneys per $100 million of revenue is equal to 1.1 (median) which works out to 4.4 lawyers per billion. This benchmark metric (plus or minus a lawyer) holds fairly well for most law departments.

An excellent way to portray data from a collection is the box-and-whisker plot. The box in the middle shows by its top line the third quartile figure in the collection, where 25 percent of the data points in the sample are higher than this value. Above it, a line extends upward to another line parallel to the top of the box, which marks the maximum value in the collection. That is the top whisker.

Somewhere inside the box a hyphenated line shows the median. The bottom line of the box shows the first quartile figure. A line extending down that goes to another perpendicular line that shows the minimum value in a sample., where half of the data points in the sample or higher and half are lower.

Thus from the top down the box-and-whisker shows the maximum value, the third quartile, the median, the first quartile, and the minimum value. An excellent tool for data visualization (See my post of May 7, 2008: methods to portray data with 9 references and 22 cited in one of them.).

When I think of benchmark metrics, I think of a sizable number of law departments each contributing similar data, and a presentation visually or with the quartiles and averages of those numbers. Then each participating law department can compare its own figure with the benchmark figures, such as technology spending per legal staff member.

When I think of performance metrics, I think of a single law department’s measures of activity or output. For example, a law department that closed 15 cases in the past year has identified a performance metric. Another performance metric is the number of law firms paid by a law department during a year.

So much for definitions. The relationship between performance and benchmark metrics is that benchmark results come from aggregations of performance metrics described in graphs or statistical terms.

Many surveys of law departments – such as those from Altman Weil, Thomson Hildebrandt, and Empsight – compare current metrics to the previous year’s metrics. What the survey reports do not do is show how a metric has endured over a period of five years or more.

I believe that many benchmark metrics that get wide publicity remain quite stable over the years, if you look at reasonably comparable populations and medians. A number of my posts have started to explore the longevity of basic performance benchmarks (See my post of July 20, 2008: Altman Weil data over four years; Dec. 5, 2007: stability of a ratio over a decade; Dec. 21, 2008: lawyers per billion trending down; Dec. 21, 2008: outside counsel spend trending down; July 20, 2008: comparative data over five years; July 21, 2008: five year’s data on internal spending; July 21, 2008: comp and benefits spend over five years; and Aug. 4, 2008: a mashup of data over five years.).