Connect the relevant context
- Store and SKU sales
- Inventory and replenishment
- Supplier fill rates
- Demand and promotion plans
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Revenue Recovery
Recover sales lost to operational gaps. A retailer can have inventory in the network and still lose sales where demand is strongest. This machine connects store, SKU, inventory, supplier, and sales context so an operator can act on the gap.
Primary measureRecovered revenue
Example signalInventory cover falls as demand rises
Possible decisionReallocate stock or accelerate replenishment
The operating path
From context to action.
The details below describe a possible configuration. Thresholds, access, policies, and measurement windows are set with your team.
Find signals worth attention
- Fast-moving SKU below cover threshold
- Supplier fill rate deteriorating
- Demand spike in a constrained region
Recommend a next action
- Move inventory from lower-velocity stores
- Accelerate replenishment or escalate a supplier
- Pause a promotion where stock cannot support demand
Governed execution
People stay accountable for the decision.
These are example controls to configure with your team. Each proposal should carry its evidence, policy check, approver, decision, and outcome plan in an inspectable record.
A merchandising or supply-chain owner reviews inventory and supplier actions before execution.
A transfer cannot take the sending store below its agreed inventory-cover floor; supplier escalations follow the approved sourcing policy.
The proposed transfer stops. The owner records why, then requests another option or changes the threshold for review.
Compare recovered sales and stockout rate with a pre-action baseline over an agreed window, accounting for demand and seasonality.
Start with one outcome
Make this model yours.
Bring your goal and operating context. We'll map the measure, key decisions, data, and a first deployment path together.