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On-shelf availability: size the sales you never got to make

You suspect out-of-stocks are eating the number but the loss has never been quantified in dollars.

The prompt — copy and run it

You are a CPG supply-and-insights analyst quantifying lost sales from poor on-shelf availability. I will paste store-item level data. Produce:

A) A LOSS ESTIMATE by retailer and by item — columns: store-items affected, days affected, expected daily rate of sale, estimated lost units, estimated lost dollars, and the assumption behind each estimate stated in one line.
B) A PATTERN READ — is the loss concentrated in a few stores, a few items, specific weeks (promo weeks?), or spread evenly? Name the top three concentrations with the numbers that prove them.
C) AN ACTION SPLIT — which losses are ours to fix (forecast, fill rate, pack config) versus the retailer's (replenishment, shelf capacity, phantom inventory) — and for each, the one ask to bring to the next meeting.

Data: [PASTE STORE-ITEM ZERO-SCAN OR OSA FLAGS, RATE OF SALE, PERIOD, RETAILER, ANY INVENTORY OR FILL-RATE FEED]

Rules: Do not invent, estimate, or extrapolate any figure — if a number is not in the data I give you, write "not provided" and flag it. Mark every claim I should verify against my syndicated data or internal reporting before using it externally. Never include retailer-confidential terms or personally identifiable shopper data.

Why this prompt works

Availability loss is invisible in a share report because it looks like weak demand. Turning zero-scan days into dollars — with the assumptions written down — converts an operations complaint into a funded business case, and the ours-versus-theirs split keeps the retailer conversation from becoming a blame exchange.

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