Individual trade-area know-how turned into standard data
“The same candidate site got a different grade depending on who evaluated it.”
Problem
When reviewing a new or relocated store, regional supervisors evaluated the trade area from field experience and their own materials. The criteria were spread across spreadsheets, documents and personal experience, and because the reasoning was never captured as standard data, it could not be reproduced or reviewed afterward.
- Scattered criteria — spread across spreadsheets, documents and experience
- Evaluator variance — the same site draws different grades
- Not reproducible — the reasoning is never captured as standard data
What BeSir did
Standardize evaluation of new and relocated store sites, until now dependent on individual experience, onto shared organizational data and criteria.
- Consolidates the trade-area materials and criteria supervisors were using into one shared evaluation framework
- Connects real trade-area data — foot traffic, nearby facilities, catchment demand — to each candidate site
- Structures separate criteria for dine-in demand and delivery demand as an ontology
- Derives an S/A/B/C grade automatically from the two scores
- Validates the criteria and weights by comparing derived grades against supervisors’ existing evaluations
Results
- PoC
Automatic grading engine built on real store data
- Target
Scattered trade-area criteria turned into a standard asset
- Target
Consistent, reproducible site evaluation
- Target
Less evaluator variance, data-driven site selection
No quantitative performance figures are presented.
Verified confirmed in the operating environment · PoC confirmed within PoC scope · Target a target set on work in progress · Estimate calculated from the stated assumptions