Dead Stock Identification
Every warehouse accumulates stock that's functionally dead — no sales in months, no open orders, no forecasted demand — but it sits in the system mixed in with genuinely slow-but-healthy SKUs, and nobody runs the analysis to tell the two apart because it means manually cross-referencing sales history, open orders and forecast against every low-velocity SKU. The dead stock keeps taking up warehouse space and tying up capital, and by the time someone finally does the analysis — usually during an annual write-off review — items that could have recovered real value through early liquidation have aged into something only a salvage buyer wants.
STARTING PRICE
From €299
Standard tier · Multi-step workflow with AI extraction/decisioning and 2-3 integrations.
Get a quote →Saves roughly 3-5 hrs/week for an inventory or merchandising team.
How the automation works
We continuously score SKUs against a genuine dead-stock definition — no sales velocity, no open customer orders, no forecasted demand, and no active promotional or seasonal explanation for the lull — rather than flagging anything simply below a velocity threshold, which would catch legitimately slow but healthy items too. Confirmed dead-stock candidates get a recommended disposition based on quantity, condition and category: return-to-vendor where the agreement allows it, liquidation channel (B2B liquidator, outlet, marketplace) with an estimated recovery value, or write-off where recovery isn't realistic. The scoring runs on a recurring schedule so items get flagged as they cross into dead-stock territory rather than accumulating for a year before anyone looks.
Process flow
- 01
Sales, order and forecast data syncs trigger
Sales velocity, open customer orders and demand forecast per SKU sync in on a recurring schedule from the inventory and order management systems.
- 02
Score against dead-stock definition ai
Each SKU is scored against a genuine dead-stock definition — sustained zero or near-zero velocity, no open orders, no forecasted demand, no seasonal explanation — not a single velocity threshold.
- 03
Filter out false positives ai
SKUs with a plausible non-dead explanation — new launch still ramping, known seasonal item currently off-season, active promotional hold — are filtered out before candidates are finalized.
- 04
Estimate recovery value ai
Confirmed candidates get an estimated recovery value per disposition path (return-to-vendor, liquidation channel, write-off) based on quantity, condition and category comparables.
- 05
Recommend disposition output
A ranked disposition recommendation is generated per candidate — the path with the best estimated recovery given the item's condition and vendor agreement terms.
- 06
Route for approval output
Recommendations route to the appropriate approver based on dollar value, with the underlying data attached so the decision doesn't require re-running the analysis manually.
Inputs
- SKU sales velocity history
- Open customer order data
- Demand forecast per SKU
- Vendor return agreement terms
- Known seasonal/promotional calendar
Outputs
- Confirmed dead-stock candidate list
- Recommended disposition path per SKU
- Estimated recovery value
- Approval-routed liquidation packet
Works with
Prefer a fully custom build instead of an off-the-shelf integration? We scope both options during your free consultation — most jobs like this one work fine on standard connectors, but higher-volume or non-standard systems sometimes need bespoke API work, reflected in the complex tier.
Where this goes wrong if you get it wrong
- Flagging anything below a flat velocity threshold as dead stock catches legitimately slow-but-healthy SKUs — a specialty item that sells five units a year at high margin isn't dead, and treating it that way pushes good inventory into liquidation it doesn't need.
- A new product launch that's still ramping looks identical to dead stock on raw velocity alone — the scoring needs a launch-date check and grace period, or every new SKU gets flagged as dead in its first quarter.
- Return-to-vendor terms have real constraints (return windows, restocking fees, condition requirements) that a recovery estimate has to account for — recommending RTV on stock that's past the vendor's return window or in non-returnable condition wastes the effort of routing it for approval.
- Recommending liquidation for stock that still has open customer backorders or is committed to a future promotion destroys real, already-committed demand — the dead-stock check has to cross-reference open orders and promotional calendars before a SKU is confirmed as a candidate, not just check recent sales velocity.
Frequently asked questions
How is dead stock different from slow-moving stock?
Dead stock has no sales velocity, no open orders and no forecasted demand with no plausible explanation like seasonality; slow-moving stock still sells, just infrequently, and isn't flagged as a candidate.
Does this account for vendor return windows?
Yes — return-to-vendor is only recommended where the vendor agreement's return window and condition requirements are actually still met; otherwise a liquidation channel or write-off is recommended instead.
How does it avoid flagging new products as dead stock?
New SKUs get a grace period based on launch date before they're eligible to be scored as dead-stock candidates, so early low velocity on a ramping product isn't mistaken for a dead item.
What recovery value estimate accuracy should we expect?
Estimates are based on category and condition comparables from prior liquidation outcomes and are directional for prioritization — actual recovery depends on the liquidation channel and negotiation at time of sale.