Theoretically we can describe every legal department with a single index figure. The figure captures for each department its four fundamentals of metrical benchmarks: number of legal staff, amount of legal spend, size of corporate revenue, and category of industry. Calculations can then show how every other legal department compares to every other department, and how closely.
A department with 30 total staff (lawyers, paralegals, and other staff) would be 30S. If its spend both inside and outside were $30 million it would be 60$ (in millions). The revenue of the company would be $6 billion, expressed as 6R (in billions) and its industry would be manufacturing 8I (it is eighth on an alphabetical list of industries).
Software could match every legal department to every other legal department on these four dimensions and calculate the degree of closeness. With an improvement, each fundamental metric would be weighted with a different degree of importance during the matching process. Thus, the I metric (industry) needs to match exactly; the R number (revenue) can calculate the difference from any other company’s R and by my lights would be weighted next. Both S (total staff) and $ (total spend) would have the same importance and the software would calculate the difference.
With those four figures, then, you can numerically compare any legal department to any other legal department with a single calculation of weighted degree of match.