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A Lead Time Variability Analysis Playbook measures variance, not just average, across every supplier and surfaces the ones whose unstable delivery windows are the real driver of stockouts and expediting cost.
The Challenge
A supplier with a 14-day average lead time that ranges from 8 to 28 days is more dangerous than a supplier with an 18-day average that never deviates. Planners can absorb a longer lead time if it is predictable. They cannot absorb a 20-day swing without overbuilding safety stock or expediting.
Most procurement scorecards track on-time delivery rate and average lead time. Neither captures variance. A supplier hitting 95% on-time within a 7-day window looks healthy on the scorecard but is causing constant replanning underneath because the 7-day window itself is wide.
Without variability data, safety stock levels are set by intuition or one-size policies. The result is overstock on stable suppliers and stockouts on unstable ones, with no statistical basis for adjusting either.
How eyko Solves It
A Lead Time Variability Analysis Playbook reads purchase order receipts against confirmed dates, calculates the coefficient of variation for every supplier and SKU, and identifies the unstable lead times driving downstream cost. It then recommends safety stock levels sized to actual variance rather than rule-of-thumb.
The Playbook surfaced 6 suppliers with coefficient of variation above 35%, the threshold where variance becomes the dominant risk factor. Supplier D shows lead times ranging from 12 to 41 days against a 22-day average. Lead time variability correlated with 73% of stockout events in the past 12 months. Reducing variance on the top 3 suppliers projects $860K in avoided expediting cost annually.
| Metric | Current | Benchmark | Status |
|---|---|---|---|
| Primary indicator | Flagged | Target | Action needed |
| Secondary indicator | Monitoring | Within range | On track |
| Trend direction | Declining | Stable | Review required |
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FAQ
Everything you need to know about Supplier Variability Risk (Top Offenders).
Lead Time Variability Analysis is an AI-driven analysis of supplier delivery history that measures variance (not just average) at the supplier and SKU level. The output is a ranked list of suppliers whose unstable lead times are driving stockouts, expediting cost, and safety stock overruns, with recommended actions for each.
The Playbook reads from your ERP (purchase orders, receipts, acknowledged dates), warehouse management system (inbound events), and any supplier scorecards you maintain. It also pulls historical stockout events from inventory and order management so it can correlate variability with downstream cost. The richer the receipt-level data, the more precise the variance attribution.
Average lead time tells you the central tendency. Variability tells you the spread. Two suppliers with identical 18-day averages can have completely different risk profiles: one with a 16 to 20 day range is easy to plan against; one with a 9 to 27 day range constantly forces replanning. The Playbook reports coefficient of variation (standard deviation divided by mean) so variance is comparable across suppliers with different average lead times.
Yes. The Playbook recommends safety stock levels sized to the actual variance distribution of each supplier, not a flat policy. Suppliers with CV under 15% get tight safety stock; suppliers with CV above 35% get safety stock sized to absorb the upper-tail lead times. The output includes the projected service level at each safety stock level so the team can choose its risk posture explicitly.
Join the enterprises replacing weeks of manual analysis with a single prompt. See what eyko Playbooks can do with your data.
