The product that moved down
A delivery needs space, so the priority line drops to the bottom shelf. The bay still looks full.
Every trading day moves the shelf a little further from the plan.
Not all at once. One facing, one delivery, one busy shift at a time.
One bay, three weeks after a reset
Day 0 · reset complete
- Priority line
- Fast seller
- New serum
- Promotion
Four ordinary days
Each for a good reason. Each hidden by a tidy bay.
The facing that disappeared
A neighbour spreads into the gap. The best seller comes back to less space, and runs out again.
The launch nobody encountered
The launch waits behind the range. Weak early sales then cut its support.
The promotion that became storage
Overflow cartons fill the end-cap while the leaflet still advertises the offer.
Small errors, repeated daily, add up. Put your own numbers on it in the shelf gap model.
Open the modelA correct reset doesn’t stay correct
Every usual check sees part of the picture. None sees the shelf between visits.
- Manual audits
- See one moment, not the weeks between.
- Sales data
- Can’t tell a moved product from an unwanted one.
- Vendor reps
- See their own portfolio, not the whole bay.
- Store managers
- Have the whole store to run.
Between inspections
The five changes from the bay above. Choose how often someone looks.
In pharmacy and beauty, a near miss matters
- Suitability
- The pack next door is not always an acceptable swap.
- Launches
- A launch out of sight is judged on sales it couldn’t make.
- Category balance
- It erodes one substitution at a time, while the shelf looks full.
- Not a compliance claim
- Plan adherence is a merchandising measure, never regulatory evidence.
A current view of the shelf
You need a mirror, not another audit: a current view of the shelf your shopper sees, and which differences matter.
See your shelf gapFair questions
We already do manual audits. Isn’t that enough?
Audits are useful for checking standards and correcting problems. The question is what happens between visits. Judge your coverage against how quickly shelves change and how long commercially important errors remain undetected. Audits and a current view of the shelf answer different questions; many teams need both.
Wouldn’t our POS data tell us if something was wrong?
It can flag unusual sales patterns. It cannot directly show that a product moved shelves or lost its facings. Physical context helps distinguish weak demand from weak execution. Read together, sales data and shelf evidence tell you more than either alone.
Our managers adapt the layout to local demand. Is that a problem?
Local adaptation can improve the plan. Record it as an approved exception so intentional choices remain distinguishable from accidental drift. An exception that works locally may be worth adopting in the plan itself.
If shoppers buy another brand, haven’t we kept the sale?
Often you have. That is why the model does not count every execution error as lost revenue. Substitution may preserve the sale, change its margin, or fail to meet the shopper’s particular need. In the model, severity is the share of exposed sales that is actually lost.
How do you know the new product isn’t simply a poor seller?
You do not know from low sales alone. Check availability and placement alongside price, demand, and repeat purchase. Correct execution makes the sales result more interpretable; it does not guarantee success.