After reading up on cardinality, another couple of questions occurred to me:

- Does the density/distribution of salesperson-region relationships have high cardinality (salespeople strongly associated with one or two regions), or low (salespeople working across many regions)?

- Does the density of those relationships better match the old optimizer assumption, or the new one (exponential)?

In that case, an alternative might be to plot three densities: your empirical density, the previously-assumed density (uniform?), and the new density (exponential?). There are a few examples here, but tons more on the web: https://heuristically.wordpress.com/2012/06/13/comparing-continuous-distributions-with-r/

After that, there are a whole slew of goodness-of-fit tests for checking whether your data fit a given distribution or not; off the top of my head, you could probably start fitdistr() from the MASS package.

No clue how you'd go about generating all of those densities, though!