The core of the solution
Tested shelf optimization in selected stores with flat files (no heavy integrations) and established the operating model.
Validated space and assortment by size-class assortment groups (77 merchandising groups, 651 classes) so that guidance reached every store.
Modeled category roles, demand potential and constraints to reallocate space where each meter yields the most, with results available in UI + data.
One-off data loads, joint validation workshops, clear scope and cadence; outputs ready to plug into remodeling decisions.
Impacts
Capability for localization
Space is allocated by catchment demand, so assortments can be tuned to capture the full sales and profit potential.
Rolling control, fewer misses
When macro space and micro assortment run on the same model, you reduce out-of-stocks and “shelf warmers.”
Faster, clearer decisions
Shared KPIs and views align store ops, category teams and leadership around the same facts.
Key Take-aways
Localization works when space and assortment are driven by one demand model. The pilots built not only the capability but also the proof that this approach is feasible at chain scale.
Want to see how a two-store macro pilot, linked to chain-wide micro validation, kick-starts the same shift for you? Let’s map your priorities and run.
