Store Performance Command Center — example input brief

Purpose: build a store-performance diagnosis, action and review workspace.
This is a tutorial input brief, not a complete data export or production dataset.
Project: https://ac29d2f4418941e3bc83afdb5911549b.prod.enterapp.pro/

Input tables: Stores; Daily Performance; Targets; Exceptions; Action Plans; Tasks; Reviews; Users.
Daily fields: date, store_id, gross_sales, discounts, returns, transactions, foot_traffic, gross_profit, labor_hours.
Rules: net_sales = gross_sales - discounts - returns; conversion = transactions / foot_traffic; gross_margin_rate = gross_profit / net_sales. Handle zero denominators explicitly. Always show period and data freshness.
Workflow: store KPI gap -> evidence-backed diagnosis -> owned action plan -> measured result and review decision.
Roles: Manager, Regional Manager, Store Operator. Restrict store scope and review authority.

Observed example, 2026-09-11: Minneapolis Nicollet Mall; EXC-WIL-001 -> AP-WIL-001 -> RV-WIL-001. Current store gross margin 37.8%; store target 44.0%. Action baseline 38.5%, action target 43.0%, tasks 3/3 completed, review pending. These different targets and time windows must remain labelled. Completion does not imply success.
If additional demo data is needed, generate clearly labelled synthetic records with consistent IDs and dates.