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Shelf-life waste surfaces when product hits the expiration date and gets written off. A Shelf Life Prediction Playbook reads lot-level inventory positions, demand velocity, and product-specific shelf-life data to forecast expiration exhaustion early, with time to redistribute, discount, or donate before the loss locks in.
The Challenge
Warehouse systems track expiration dates per lot, but the operating teams that could redistribute or discount short-dated inventory rarely have a view by lot until the product is already inside the at-risk window. By then the action options have narrowed.
A lot may have plenty of shelf life if demand at that location matches the on-hand quantity, but if velocity has slowed, the same lot will expire. Without joining demand velocity to lot-level inventory, the risk only surfaces when expiration is imminent.
Short-dated inventory can be moved to a higher-velocity location, discounted, or donated, but each option has a window. Slow detection means the window closes and the only remaining option is write-off, which is the most expensive outcome.
How eyko Solves It
A Shelf Life Prediction Playbook reads lot-level inventory positions, expiration dates, demand velocity per SKU and location, and product-specific shelf-life characteristics to forecast expiration risk per lot. It surfaces lots at risk with enough lead time for redistribution, discounting, or donation, sizes the dollar exposure per lot, and recommends specific actions ranked by recovery value vs write-off cost.
The Playbook analyzed lot-level inventory across 18 perishable categories and 84,000 lots. 1,840 lots at elevated expiration risk in the next 90 days, representing $3.2M in inventory value at risk. 480 lots are within a 14-day redistribution window where moving inventory to higher-velocity locations would prevent the write-off entirely. The remaining lots need discount or donation programs to recover residual value.
| Metric | Current | Benchmark | Status |
|---|---|---|---|
| Primary indicator | Flagged | Target | Action needed |
| Secondary indicator | Monitoring | Within range | On track |
| Trend direction | Declining | Stable | Review required |
Shelf Life Prediction forecasts expiration risk per lot using lot-level inventory positions, expiration dates, demand velocity per SKU and location, and product-specific shelf-life characteristics. The Playbook surfaces lots at risk with enough lead time for redistribution, discounting, or donation, sizes the dollar exposure per lot, and recommends specific actions ranked by recovery value vs write-off cost so the perishable inventory program runs against forecast rather than calendar.
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FAQ
Everything you need to know about Shelf Life Risk Map.
Shelf Life Prediction is an AI-driven forecast of expiration risk per lot using lot-level inventory positions, expiration dates, demand velocity per SKU and location, and product-specific shelf-life characteristics. The Playbook surfaces lots at risk with enough lead time for redistribution, discounting, or donation, sizes the dollar exposure per lot, and recommends specific actions ranked by recovery value vs write-off cost.
The Playbook reads from your warehouse management system (lot-level inventory positions, expiration dates, location data), ERP or sales system (demand velocity per SKU per location), product master data (product-specific shelf-life characteristics, allowed redistribution paths), and historical write-off and recovery records. At least 12 months of paired lot-and-outcome data anchors the prediction.
An expiration date report lists lots sorted by date. Shelf Life Prediction forecasts expiration exhaustion by combining lot quantity with demand velocity at the holding location, surfacing lots that will expire before they sell even when the calendar date is weeks away. The two are complementary, but the velocity-aware forecast is what produces actionable redistribution decisions rather than just a sorted date list.
Yes. For each at-risk lot the Playbook recommends a specific recovery action: redistribute to higher-velocity locations on lots inside the redistribution window, discount-driven sell-through on lots where redistribution is not viable, and donation or controlled disposal on lots past those windows. Each recommendation projects recovery value vs write-off cost so operations leadership prioritizes the highest-yield moves first.
Join the enterprises replacing weeks of manual analysis with a single prompt. See what eyko Playbooks can do with your data.
