Case Study · Retail
Derimod stock analytics: lost sales, size-run breaks, idle stock and the success of every shipment
The layer that measures whether Optail's decisions work. We defined lost sales, size-run breaks and non-selling stock and tied them to weekly dashboards; made stock in warehouses and stores and every product movement — in transit, on dispatch order, incoming — visible; computed the sell-through of initial allocation, replenishment and transfer with a first-in–first-out link. In one season footwear lost sales fell from 14% to 10% and size-run breaks from 10.6% to 8.4%.
- 14% → 10%
- Lost sales
- 10.6% → 8.4%
- Size-run breaks
- 21% → 11%
- Bags lost sales
- 1
- Success definition
Footwear, summer 2025 vs the year before
Footwear, same period
Summer 2025
First inbound movement → first outbound movement
Problem
When you build a distribution system two questions follow: are the decisions right, and what state is stock in today? Answering either needs definitions first. If everyone understands something different by “lost sales”, the figure on the dashboard gets argued over and trusted by no one. At Derimod those definitions did not exist; broken sizes, idle product and stock-outs lived in the planners’ intuition.
Three definitions
| Metric | Definition | Where it is used |
|---|---|---|
| Size-run break | For an option–store pair, sizes in stock / total sizes; an option that cannot form an assortment is “broken” | Weekly size-run dashboard; sender selection in the consolidation transfer |
| Lost sales | Sales missed because of stock-outs: when an option is selling in a store and a size or unit runs out, the gap between the sales expected from the rate of sale and the actual | Availability – stock-out report; replenishment priority |
| Non-selling (idle) stock | Product in stock that has produced no sales for a set period — by store and option | Idle stock report; input to transfer and markdown decisions |
The definitions were written into SQL procedures, computed weekly from the data warehouse and tied to the dashboard catalogue. The same definition is used both in the reports and in Optail’s algorithms; what the report calls “broken”, the algorithm calls “broken”.
The success of every shipment
Did a shipment work? We set the definition up front: the first inbound movement is linked to the first outbound movement. Every unit arriving at a store is matched to the first sale in that store; the share sold within a set window — 21 days for transfer — is that shipment’s success. 2 went, 1 sold: 50%.
This measurement is made separately for initial allocation, replenishment and transfer; separately for Optail and manual; and for the same period last year (LFL). The result is presented to the board at the end of every season, and the rates on the replenishment and transfer pages come from here.
Where the stock is
A decision needs stock not only in the store but at every point of the chain:
- Store — actual stock, final stock, option capacity, number of unbroken options, cover and 28-day cover.
- Warehouse — actual, final, available and returns stock; by season and subgroup; goods-in KPIs; dispatched versus waiting in the warehouse.
- In transit — on dispatch order, on the road and incoming. Store + transit enters the fill calculation; goods in transit are not sent twice.
Every product movement — initial allocation, replenishment, transfer, return — is recorded with its source and destination; which stores an option passed through over the season can be traced. This visibility paid off on the e-commerce side too: the share of orders shipped in parts from more than one warehouse fell in one season by about a fifth across all warehouses, and by more than half at the main e-commerce warehouse.
Outcome
Measurement became Optail’s justification. In the summer 2025 season, footwear lost sales fell from 14% to 10% and size-run breaks from 10.6% to 8.4% against the year before; bags lost sales from 21% to 11%. In the winter season footwear lost sales fell from 24% to 20% and size-run breaks from 39% to 34% — while footfall declined. Unit sales growing despite the monthly fall in footfall was reported as the effect of the right product being in the right place.
The 2026 roadmap has two analytics projects: the lost-sales tree — a structure that automatically separates the root causes of stock-out losses (not in the warehouse, in transit, broken in store, off plan) — and size analysis.
Why this way
- Definition before report. Had size-run breaks and lost sales gone onto a dashboard before being written in SQL, every team would defend its own definition.
- The same definition both measures and decides. Report and algorithm read the same procedure; the two agree.
- Success per shipment. Total sales growth depends on many things; the first-in–first-out link isolates the result of a single decision.