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This is a far out idea, so you level-headed types can pass on by.

I unleashed the LinkedIn Labs app for maps on my own network of about 400 people. A nebula blazing with eight colors came back that showed, I think, each contact in my network and their connections to my other contacts. The size of their node indicates how many cross-over contacts I have as in where my contacts overlap. My node sits right in the middle. The map is quite beautiful although I am at a loss to understand why the software grouped people the way it did.

Now, here’s the futuristic part. If a law department tracked when its lawyers called upon any of its law firms, software such as this would vividly depict the law firms that serve the department broadly, the firms that assist only a single lawyer, and everything in between. Over a multi-year period, with color codes to match practice areas, the map of retentions might be insightful. If the thickness of the line corresponded to fees paid, or if the volume of each firm’s node did that – like cities on maps are scaled to their population, even more information would be displayed visually and graphically.

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Eastman Kodak makes hundreds of millions of dollars every year from its patent licenses. Its lucrative portfolio has more than 1,000 patents and in 2010 “it made an estimated $630 million from its licenses, according to Argus Research.” The quote comes from the NY Times, April 29, 2011 at B4, which adds that Kodak expects to generate $250 million to $300 million in revenue each year through 2013 from its licensing agreements (See my post of Dec. 31, 2007: intellectual property licensing with 12 references.)

In part, I was surprised that someone outside a company was able to estimate its patent licensing revenue. How the terms of license deals could be known and aggregated is beyond me (See my post of April 27, 2008: American Express’s patent licensing program; Feb. 24, 2009: primacy of intangibles for lawyers per billion; March 27, 2009: more on patent investors; April 9, 2009: AT&T sale of fallow patents; Sept. 21, 2009: patent trolls and licenses; Nov. 8, 2009: most patents make no money; July 15, 2010: Motorola’s licensing structure; Oct. 18, 2010: create separate corporate licensing team: and Dec. 16, 2010; pruned patents may create licensing work in-house.).

Second, wouldn’t it be good as a benchmark of comparative performance for law departments to know patent license revenue obtained per patent record or per billion dollars of revenue? My slide rule salivates!

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The blog of Lecorpio has post on Jan. 1, 2011 that talks about the hidden costs of software, those costs a law department incurs over and above the license fee. As backup they refer to but do not cite to a government study. “The U.S. Department of Commerce study shows that software purchase expenditures account for only approximately 30 percent of the total. The biggest hidden cost is represented by labor expenditures ranging from 37 percent for support and 33 percent related to software getting the software up and running. The numbers translate to a ratio of 1:2, software license to management/labor costs; and 1:1 license fee to implementation.”

The original text comes from a 2003 paper by Tim Chou. On page 2 Chou writes “In addressing total software related spending, JP Morgan Chase technology analyst Chuck Phillips cites a recent U.S. Department of Commerce study” and the exact quote of Lecorpio follows.

I don’t doubt that the total cost of software for a law department goes far beyond the initial license fee. Still, to cite a study done at least eight years before, years during which the bee hive of software has been buzzing furiously, leaves me wondering about the old research’s current accuracy.

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If a team has to choose a software package from a group of contenders, one way to do that is to choose between package 1 and package 2, then between the winner of that and package 3, then between the winner of the first two competitions and the next package, until you are done. As explained by John D. Barrow, 100 Essential Things You Didn’t Know You Didn’t Know: Math Explains Your World (Norton 2008) at 169-171, this sounds efficient and logical, but maybe it is not fair.

The outcome depends heavily on the order of packages chosen. If the stronger packages eliminate each other in the early stages, paradoxically a weak package can end up selected.

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If you calculate the average billing rate increase of the two law firms you paid the most during 2009 and 2010, and then divide the total of those increases by two, you have the arithmetic mean of those increases. So, Firm A increased 4 percent and firm B increased 6 percent. The arithmetic mean was 5 percent, (4+6)/2.

The geometric mean is more appropriate than the arithmetic mean for describing proportional growth; in business the geometric mean of growth rates is known as the compound annual growth rate (CAGR). The geometric mean of the increases requires a different calculation. In the example, the geometric mean is the square root of each firm’s change multiplied together.

The geometric mean, however, is 4 times 6 raised to the ½ power (since you have two numbers and the exponent is 1/n), which is 4.9 percent (it is always less than the arithmetic mean). In the US the Labor Bureau calculates the Consumer Price Index with geometric means. More generally, the geometric mean of n quantities is the nth root of their product, according to John D. Barrow, 100 Essential Things You Didn’t Know You Didn’t Know: Math Explains Your World (Norton 2008) at 236. So, if you had changes in billing rates for five law firms, you would multiply all five of their percentage changes and raise it to the 1/5 (.2) power (the fifth root).

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Nero AG’s law department, headquartered in Germany and with legal offices in the US and Asia, set up a wiki three years ago. As Frank Fletcher, the General Counsel of Nero, explains in ACC Docket, April 2011 at 16,, “a wiki is software that allows you to make a site of internally linked webpages that can be easily edited.” ffletcher@nero.com

Fletcher writes that his wiki is easy to use – a one-page tutorial is all that is needed – and that IT does not need to be involved – unlike intranet sites, which in my experience usually require some technical support. The law department has posted photos of its members, listed areas of responsibility, provided template agreements, and done much more. He notes that they have put on the wiki “directions on how to work effectively with legal,” for example, as well as lists of trademarks and how to use them correctly.

Almost anything that helps clients and members of the law department locate and use resources could be fodder for the wiki (See my post of Sept. 1, 2008: wikis with 8 references; and Dec. 31, 2007: Wikipedia and law department management.)

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The ACC Docket, April 2011 at 14, states a finding from the 2010 Managing Outside Counsel Survey: “The median number of US law firms used by law departments during 2009 was 12.” A dozen seems too low. If a law departments has a couple of law suits during the year, a firm to review issues in each of a handful of specialty areas, local counsel, etc. it is be easy to hire more than a dozen, so to find that half of the companies in the survey use fewer needs some backup.

The summary offers one sentence more. “The average number of US law firms used by small law departments (2 or fewer lawyers) was five firms; medium law departments (3-10 lawyers) was 12 firms; and large law departments (more than 10 lawyers) was 60 firms.”

When the finding one year for large departments was 20 firms, I challenged it as too low (See my post of April 18, 2009: 2009 Serengeti survey gave 20 law firms.). This fuller set of data does not seem right to me either. The average of 12 means there had to have been mostly smallish law departments in the survey. Or perhaps if a department did not give a number the analysts treated it as zero firms? Did the phrasing of the question lead to an undercount?

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I admire Boris Groysberg’s book, Chasing Stars: The Myth of Talent and the Portability of Performance (Princeton Univ. 2010). He exhaustively studied equity research analysts who were top-ranked by Institutional Investor. The first chapter condenses a huge amount of research on innate performance drivers and acquired performance drivers, and his book adds one..

On the side of what people seem born with, the pre-eminent one is general intelligence, sometimes called “g” by psychologists (See my post of Jan. 6, 2009: high g’s are healthier.). He also points out emotional intelligence – an array of attributes including self-awareness, self-regulation, motivation and empathy (See my post of Sept. 20, 2010: lawyers and their brains.). He includes deep motivational structures such as those studied by David McClelland), including the need for achievement and for socialized power. Also deeply internal to people, part of their innate makeup, are personality and temperamental attributes such as energy, persistence, and a low anxiety threshold. For law departments, hiring decisions seem quite sensitive to these factors as they pore over resumes, schools attended, and higher degrees.

Genetic inheritance, however, is not destiny. Others who study professional excellence focus on acquired skills. The most fertile discipline that espouses this view is human capital theory (See my post of Aug. 14, 2009: human capital with 10 references.). Adherents to this view see education, experience, and skills acquired lead to higher productivity. Continuing legal education, HIPO programs, lunch-and-learns, and other efforts by law departments build human capital and past work experience embodies it.

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I wrote a set of propositions about new ideas in relation to law departments. The National Law Journal published them on April 11th and I invite readers to

here.

More, I urge readers to leave a comment here or email me with something they have done that some other readers might think of as new: “Hey, we should try that out!”

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  1. Canadian law departments, Canada (See my post of April 14, 2011: law departments in Canada with 28 references.).

  2. Capitalized expenses and hidden (See my post of April 20, 2011: capitalized expenses with 7 references.).

  3. Administrative time demands (See my post of July 22, 2009: administrative time with 3 references and 18 metaposts.).