David Jones has a stockout problem running in the opposite direction from the usual one. As of November 15, 2026, the receivers appointed on November 5 say foot traffic and online sales across the department store are at record levels, and they have ordered replenishment from some suppliers. At the same time, some stockists have been pulling products off the shop floor, and the receivers plan to close roughly half of the 38-store network. High demand, thinning shelves and a shrinking footprint in the same week is exactly the condition that breaks on-shelf availability reporting.
Why availability data goes wrong in a receivership
Availability normally measures whether a product can be bought. In a distressed retail situation it measures something else: whether a supplier is still willing to ship. When a brand pulls its stock, the SKU does not become unavailable because of demand, it becomes unavailable because of a commercial decision. A dashboard that only counts zero-on-hand will read this as a demand spike and trigger exactly the wrong response, such as pulling forward reorders that nobody will fulfil.
Three signals to separate
The practical fix is to split availability into three states and report them separately. The table below is the minimum needed to tell a demand problem from a supply problem during a period when the store network itself is changing.
| State | What it means | Where to read it | Typical false reading |
|---|---|---|---|
| On shelf, own stock | Retailer holds inventory and can sell | Store inventory feed | Counted as available while a transfer is pending |
| On shelf, concession | Brand-owned stock sold through the store | Concession agreement and brand feed | Disappears from the feed with no reason code |
| Delisted | Supplier withdrew or store is closing | Withdrawal notices, closure list | Looks identical to a stockout |
Once these three states are separated, the weekly review changes shape. Instead of asking why one store is out of stock, the team asks how many SKUs moved from state one to state three, and whether that movement is concentrated in stores on the closure list. That is a question a category manager can act on; a single availability percentage is not.
The closure list changes distribution coverage
Coverage is not a national number
Losing about 19 stores out of 38 does not halve national distribution coverage evenly. Coverage in a trade area falls to zero for shoppers who used a single store, while nearby stores absorb the rest. Any coverage report that stays at the national level will look stable for weeks after the local reality has changed.
Replenishment orders need a destination
The receivers have ordered stock from some suppliers, which is a reasonable move while traffic is high. The complication is that the same period includes store closures, so part of that replenishment has to be routed to stores that will still be trading in January. Without a store-level cover model, replenishment improves the average and worsens the tail.
A weekly routine that survives the period
This is not a moment for a new platform. It is a moment for a fixed weekly extract that a small team can maintain while the situation moves. The steps below are deliberately manual; they are meant to be reproducible rather than clever.
Record traffic during a receivership is not a recovery signal, and empty shelves are not automatically a demand signal. The only reliable way through the period is to keep the three availability states apart and to report coverage where shoppers actually are.
FAQ
Does record footfall mean the network is safe?
No. Traffic and sales can rise while a store closure programme runs in parallel; the two numbers answer different questions and should be reported separately.
How should withdrawn stock be treated in availability reporting?
As a separate state, not as a stockout. Withdrawal is a commercial decision, and treating it as demand-driven leads to reorders that cannot be fulfilled.
What is the minimum data needed weekly?
Store-level inventory for high-turn SKUs, a withdrawal list, and the closure list. Three inputs are enough to separate demand from supply.
