Store profiling 101: the attributes that actually drive allocation

Before a single quantity can be computed, you need to know your stores. Not in the vague “we have 1,200 locations” sense, but in structured detail: the traits that determine how much of each asset a store can use. This is store profiling, and getting it right is the foundation everything else rests on.

Start with the attributes that change the answer

It is tempting to capture everything about a location. Resist that. The useful question is narrower: which attributes actually change how many of an asset a store needs? Those are the ones worth modeling first.

A workable starting set for most fleets:

• Format and size — supercenter, standard, express; square footage bands.
• Fixture counts — number of endcaps, window bays, checkout lanes, display zones.
• Department presence — deli, pharmacy, garden, electronics; present or not.
• Traffic and demographics — the context that scales certain assets up or down.

If an attribute would never appear in a rule, it does not need to be in the profile yet. You can always add it later.

Make it a living record, not a one-time survey

Stores change. A location adds a pharmacy, a format gets remodeled, fixtures get pulled. A profile that was accurate at launch and never updated slowly drifts back toward the same guesswork flat allocation gave you. The fix is to treat the profile as a record you maintain, with bulk updates when the fleet shifts, rather than a spreadsheet someone built once.

Custom attributes are the point

No two retail operations model their stores the same way, and a rigid, fixed schema forces you to distort your fleet to fit the tool. The profile should bend to your operation — custom attributes let you capture the traits that are specific to how you plan, which is exactly what your rules will read from.

The payoff

A good profile is quietly powerful. Once it exists, allocation stops being a negotiation and becomes a computation. You are no longer arguing about how many kits a “typical” store needs — you are looking up what this store has and letting the rule do the arithmetic. That is the whole game: precise inputs make precise outputs possible.