Is computer vision on the shelf worth it for a 40-store chain?

Worth it for a specific problem, like shelf-out on the fastest movers or expiry control, not as surveillance of the whole store. The camera is the cheap part. The real cost is ground truth and the process that acts on what it detects.

The math closes when three things are true. The problem has a narrow address, twenty critical items in one section, not “the store”. Someone is there to act on the alert in minutes, not in next week’s report. And you can measure the gain against a baseline, in OSA at the shelf, not in system stock.

The most common exception sinks the whole project. In a small, low-velocity store, manual auditing is cheap, and the camera solves a problem the clerk already solved by walking the aisle. There the technology replaces work that cost little, and the return disappears. Computer vision pays when what it sees is expensive to see another way, and when the demand peak hides the gap from the human eye.

What you can do this week needs no camera. Take the section with the most shelf-out and time it: when an item hits zero, how long until someone notices and restocks? If the answer is hours, that is the number computer vision attacks, and the same bottleneck that becomes an expensive, slow POC when the scope is too wide. Without that number, the project is faith in the demo, not a decision.

If you are in this evaluation and want a second read, send me the shape of your case in one sentence, store count and the problem the camera would solve. I will reply within a business day with a paragraph: worth it, not worth it, or “worth it, if the scope is this”. No calendar, no call.