Fair comparison
A raw leaderboard tells you which stores have the easiest customers. That is not the same as which stores are run well.
Locations are scored against a peer group rather than the whole system, so performance is measured relative to what a store like that should expect. A high-volume urban location with heavy traffic and a suburban location with a regular crowd get judged on their own terms.
The result is a ranking a franchisee will actually accept — which matters more than it sounds, because a ranking operators dismiss as unfair is a ranking that changes nothing.
Raw averages reward circumstance. The store at the top is often the one with the least demanding customers, and a genuinely well-run location in a difficult market can sit near the bottom for years while doing everything right.
That does real damage beyond bad measurement. It makes corporate scorecards a running argument with the field, and it teaches your best operators in hard markets that the numbers are something to explain away rather than something to move.
Underperformance becomes visible where it actually is. A store that looks fine on a raw average but trails every comparable location stops hiding, and a store that looks weak in the system ranking but leads its peer group gets recognized instead of coached.