eyko Ideas

Which SKUs will stock out before the next replenishment lands?

Stockouts surface as customer-facing failures with the cost already baked in. A Stockout Probability Scoring Playbook reads inventory positions, demand variability, lead-time risk, and replenishment-in-flight data to forecast stockout probability per SKU and location with enough lead time for expedite, redistribute, or substitute action.

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The Challenge

Stockouts surface as failures, not as warnings

  • Days-of-supply reports describe state, not risk

    A days-of-supply dashboard shows current cover. It does not project whether demand variability and lead-time risk will produce a stockout before the next replenishment lands. Operations sees the cover number, assumes it is fine, and discovers the stockout only when it happens.

  • Single-location risk obscures network-level options

    A SKU may be at stockout risk at location A while location B holds excess. Without a network view of risk, the redistribution opportunity is invisible and both locations end up with the wrong inventory positions for their actual demand.

  • Replenishment-in-flight gets treated as guaranteed

    Open POs and inbound shipments get counted as on-hand-equivalent. When the inbound is late or partial, the stockout risk materializes despite the open PO. Without joining inbound risk to stockout scoring, the team relies on POs that are not guaranteed to land on time.

How eyko Solves It

Score the risk, intervene with time

A Stockout Probability Scoring Playbook reads inventory positions per SKU and location, demand variability, lead-time risk on open POs, network-level inventory availability, and substitute-product options to score stockout probability with a days-to-stockout horizon. It surfaces the highest-risk SKU-location combinations, sizes the revenue and customer-experience exposure, and recommends specific actions (expedite, redistribute from another location, substitute) ranked by recovery value.

Stockout Risk Forecast | What
Executive Summary

The Playbook scored 4,200 SKUs across 4 DCs and identified 240 SKU-location combinations at elevated stockout risk in the next 30 days. 84 have viable redistribution paths from sister locations holding excess. 38 require expedited inbound to prevent the stockout. The total revenue exposure is $2.4M; targeted action across all three intervention types projects $1.6M in protected revenue.

Stockout Risk Drivers
Demand spike on variability
42%
Inbound replenishment late
32%
Allocation mismatch
18%
Lead-time variability widening
8%
Substitute unavailable
4%
MetricCurrentBenchmarkStatus
Primary indicatorFlaggedTargetAction needed
Secondary indicatorMonitoringWithin rangeOn track
Trend directionDecliningStableReview required
Recommendations
1The Playbook scored 4,200 SKUs across 4 DCs and identified 240 SKU-location combinations at elevated stockout risk in the next 30 days.
2Full analysis available across all connected data sources.

Stockout Probability Scoring scores each SKU-location combination on stockout probability with a days-to-stockout horizon. The Playbook reads inventory positions, demand variability, lead-time risk on open POs, network-level availability, and substitute options to surface the highest-risk combinations, size the revenue exposure, and recommend specific actions (expedite, redistribute, substitute) ranked by recovery value so operations acts before the failure rather than after.

FAQ

Frequently asked questions

Everything you need to know about Stockout Risk Forecast.

Stockout Probability Scoring is an AI-driven score on each SKU-location combination that predicts stockout probability with a days-to-stockout horizon. The Playbook reads inventory positions, demand variability, lead-time risk on open POs, network-level availability, and substitute options to surface the highest-risk combinations, size the revenue exposure, and recommend specific actions ranked by recovery value.

The Playbook reads from your warehouse and ERP system (inventory positions per SKU per location), demand history (variability and forecast), open PO data (inbound quantities and expected dates), transportation management system (inbound lane reliability), and product master data (substitute-product spec compatibility). At least 12 months of paired inventory-and-outcome data anchors the prediction.

A days-of-supply dashboard reports current cover. Stockout Probability Scoring forecasts whether demand variability and lead-time risk will produce a stockout before the next replenishment lands, with a probability score and days-to-stockout horizon. The two are complementary, but the probability score is what triggers intervention before the failure rather than after.

Yes. For each at-risk combination the Playbook recommends a specific move: redistribute from sister locations on viable network options, expedite inbound on late-replenishment cases, activate substitute recommendations where spec-compatible, and proactively communicate to affected customers where the stockout cannot be prevented. Each recommendation projects protected revenue.

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