The Scenario
A multi-aisle retailer relies on manual shelf checks to manage stock. Staff do walk-throughs at set intervals, but coverage is inconsistent — especially during peak hours when the same staff are handling customers. Out-of-stocks are often discovered by customers first. Planogram compliance is checked sporadically, and reset corrections happen days after drift occurs. Shrinkage is identified at inventory count, not in real time.
How It Would Work
Cameras covering store aisles — many of which are already in place for loss prevention — are connected to a vision pipeline that monitors shelf state continuously. The model is trained on the expected shelf layout for each section: which products belong where, what a full facing looks like, what an empty bay or misplaced item looks like.
When the system detects low stock, a facing below threshold, or a planogram deviation, it sends a directed task to the nearest available staff member: "Aisle 4, shelf 2 — juice facings low." The event is logged with a timestamp and image. At end of day, the manager receives a summary of stock events, response times, and recurring gaps.
What You Would Get
- Continuous aisle monitoring without requiring additional staff walk-throughs
- Staff directed to the right aisle at the right time — before customers notice
- Planogram compliance tracked automatically, with flagged deviations logged
- End-of-day summary showing stock events, response times, and repeat gap locations
- Loss prevention visibility integrated with operational stock monitoring
Why It Matters
Out-of-stocks and planogram drift are usually discovered too late — at the end of a shift, during a count, or by a customer complaint. Continuous camera-based monitoring closes that gap by making shelf state visible in real time. Staff spend less time on scheduled walk-throughs and more time responding to specific, directed tasks. The retailer also builds a daily record of shelf state that supports supplier conversations and promotional planning.