Dead stock share
The share of your stock value that has stopped moving, computed from when things actually last sold rather than from what the stock sheet claims.
Also called Slow-moving stock, Obsolete inventory, Aged stock.
What it is
Dead stock share is the proportion of inventory value tied up in products that are no longer selling. It matters because that value is cash, and the decision it drives is what to discount and by how much to release it.
value of stock with no sale in N months ÷ total stock value
- no sale in N months
- Measured from the order lines, not from a last-sold column
- stock value
- Units on hand at landed cost, excluding stock in transit and samples
- N
- Set from your own replenishment cycle, commonly 6, 9 or 12 months
The part the formula leaves out
The stock file lies about ageing, and it lies in one direction. A `last_sold` column is maintained by whichever process last touched the record, which includes stock counts, transfers and returns. In the worked example the sheet's own column disagrees with the order lines for 312 SKUs and would have classified $47,000 of dead stock as active.
Seasonality has to be handled before anything is condemned. A SKU that sold in the same month last year is having a quiet summer rather than dying, and treating the two alike produces a clearance list that destroys next season's margin. The exclusion belongs on the page, with the SKUs it applied to, so it can be argued with.
The interesting question is not which stock is dead but why it was bought. Half the dead value in the example arrived on four purchase orders where the quantity was set by a supplier's minimum rather than by demand, one of them 480 units of a product that has sold 96 in fourteen months. That is the finding; the ageing report is the input to it.
How it is usually computed wrongly
01
Trusting the last-sold column
It is maintained by processes that are not sales, and it is stale in the direction that makes the report look better.
Rebuild ageing from the order lines and report how far the two disagree, since that gap is itself a data quality finding.
02
Condemning seasonal stock
A nine-month window in August marks every winter line as dead, and clearing them is the most expensive possible response.
Exclude SKUs with a sale in the same month of the previous year, list the exclusions, and let someone disagree with them.
03
Measuring in units rather than value
A thousand dead units of something cheap is a shelf-space problem. Forty dead units of something expensive is a cash problem, and only one of them is worth a discount campaign.
Rank by the cash that clearing each line would release, at landed cost.
04
Ignoring the stockouts on the other side
Dead stock and stockouts are usually the same decision seen twice, since the cash tied up in one is the cash that was not available for the other.
Report stockouts alongside dead stock. A stockout leaves no rows, so it has to be reconstructed from zero-stock windows in the movement history.
What your file needs
- A stock file with quantities and costs
- Sales history at the order line, for real ageing
- Movement history, if stockouts are to be measured
- Purchase orders, to trace dead stock back to the decision
Anything missing is reported as unavailable rather than substituted with something weaker computed on worse evidence.
Compute it on your own file
No account needed to start. You only pay when you like what you see.