In the sphere of law department management, power-law distributions probably describe a variety of distributions of data (See my post of Feb. 24, 2009: background on power laws.).
Expensive lawsuits. Assuming $10 million in costs is the largest, the drop off can be predicted to the number of lawsuits costing $5 million, and the same formula predicts the frequency of $2.5 million cases. For instance, each level down may be four times more common (See my post of Nov.13, 2005: power laws and the ratios of litigation costs.).
Expenditures on specialty law firms. A plausible power-law distribution might see a law department spend about 53 percent of its outside counsel budget in a given legal-service area on its top choice firm, 20 percent on the second choice firm, 13 percent on the third, and 7 percent on the fourth. The decline can be expressed as a polynomial power-law function.
Payments by a large law department to its law firms. Treating each year’s total payment as a single data point, the distribution of payments by a law department likely follows a power-law pattern. To go from $10,000 to $100,000 and from $100,000 to $1 million – a logarithmic increase – will show a pattern of decreasing frequency described by a power-law expression.
The number of attorneys in law departments. A big drop from the largest law department to the second largest, then a sizeable but not as big drop to the third, and so on marks a power-law distribution. In fact, the larger the system (such as all law departments by number of lawyers), the larger the gap between the number-one and the median member of the system.
Total legal spending as a percentage of revenue in a sector. If you sort companies from high to low on total legal spending, the drop off may illustrate a power curve.