How do we define obsolete consistently?
Written policy: e.g. no movement 12 months, superseded revision, or below forecast with no approved promo plan. Apply same at all sites.
ZBI Business Control Library
Obsolete Inventory %
Obsolete Inventory %: plain-English definition, formula, worked example, how to interpret the result, policy- and trend-based guidance, common mistakes, and management actions in the ZBI Business Control Library.
What is Obsolete Inventory %?
Obsolete inventory percent is the share of inventory value that meets a written obsolete policy—stock that cannot realistically be sold or used at full value. Obsolete is a policy definition (for example: no movement for a defined period, superseded revision, or no approved demand path). Dead stock is related but not identical: obsolete is policy-defined; dead stock usually means no realistic movement path in practice. Treat them as overlapping risk categories, not automatic synonyms.
A warehouse can show healthy turnover on active A-class lines while obsolete and dead-stock value quietly waits for write-off or deep discount. That is why this metric belongs next to turnover—not behind it.
Why Obsolete Inventory % matters
Obsolete stock consumes space, insurance and pick paths while contributing little or nothing to service. Buyers may keep replenishing active lines while superseded or discontinued items block fast-pick locations. Sales promises assortment freshness while finance reserves grow. Every new product launch without a disposition plan for replaced SKUs can increase the obsolete share—even when total inventory looks “under control.”
Formula and variables
Obsolete Inventory % = Obsolete Inventory Value ÷ Total Inventory Value × 100
Obsolete inventory value — stock meeting written obsolete policy at standard or net realizable value per finance rules.
Total inventory value — same valuation basis for all inventory categories in scope.
Excel: =IFERROR(B2/B3*100,0)
Hypothetical example
Hypothetical example — for formula illustration only, not a documented company case.
Suppose obsolete inventory value is EUR 35,000 and total inventory value is EUR 400,000 (same valuation basis).
Obsolete Inventory % = 35,000 ÷ 400,000 × 100 = 8.75%
Use the same valuation basis for both inputs. Change either input and the percent changes; the formula itself does not decide write-off timing.
Real-world experience
How to interpret the result
Obsolete percent measures capital trapped in stock with no viable demand path. Interpretation depends on written company policy, industry and product lifecycle, absolute obsolete value, and trend over time—not on a universal external target.
- Compare the current percent to your written obsolete policy threshold and to prior periods.
- Read the percent together with absolute obsolete euros (or local currency)—a stable percent can still hide a rising absolute exposure.
- Define obsolete the same at every site; otherwise a corporate headline can hide a location with a much higher obsolete share.
- Write-offs improve the percent without fixing launch discipline—track pre-write-off obsolete separately.
- Pair with new product introduction count—launches up but obsolete flat means old SKUs are not cleared.
Policy and trend context
There is no single industry percentage that defines “acceptable” obsolete inventory for every business. Use your written obsolete definition, the absolute value at risk, and the direction of change over consecutive periods. Seasonal or campaign-driven spikes may need separate review from structural SKU proliferation. The hypothetical 8.75% example above is only arithmetic illustration—not a policy threshold.
Red flags
- Obsolete percent rising for two consecutive quarters against the company's written policy threshold—write-offs and/or disposition backlog ahead; gross margin hit when reserves move to P&L.
- Obsolete defined inconsistently by site—corporate headline hides a location with a much higher obsolete or dead-stock share.
- New product introductions up but obsolete percent flat—superseded SKUs not cleared from warehouse.
- Write-offs improve obsolete percent without disposition process—same SKUs reclassified next year.
- Obsolete euros concentrated in one buyer's category—assortment discipline failure, not random slow movers.
Common mistakes
- Obsolete defined differently by site—a corporate headline can hide a warehouse with much higher obsolete share.
- Waiting for annual write-off to 'clean' the metric without monthly obsolete review.
- Classifying superseded revision as active because 'someone might order it' without sales evidence.
- Excluding WIP obsolete—half-finished promo packs count when no demand path exists.
- New product launches without mandatory disposition checklist on replaced SKUs.
What should management do next?
- Apply written obsolete definition consistently; publish percent before and after write-off.
- Monthly obsolete review with engineering sign-off on superseded revisions.
- Set disposition path—discount, scrap, return—and deadline per obsolete band.
- Tie new product launch checklist to obsolete risk on replaced SKUs.
- Board report when obsolete percent exceeds policy threshold two quarters running.
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FAQ
When do we write off versus discount?
Write off when no demand path; discount when channel and margin allow clearance. Finance sets materiality threshold.
Should engineering sign off on the obsolete list?
Yes monthly for FG and WIP—ECO process should feed obsolete review, not only warehouse counts.
Is a high obsolete percent acceptable?
Trend and absolute euros both matter. Set a written policy threshold with board visibility; rising obsolete share over two quarters usually requires disposition action.
Does clearing obsolete hurt turnover metrics?
Yes cosmetically. Track pre-write-off obsolete separately so ops cannot hide buildup behind write-off timing.
Summary
Obsolete inventory percent shows how much stock has no viable demand path. Define obsolete consistently, disposition monthly with engineering input, and tie product launches to clearance of replaced SKUs.
Reviewed by ZBI Business Control Library · Last updated 2026-09-22