Supply Chain & Procurement worked example
Lead Time Variability with fastest observed lead time of 2.5 days: a worked example
Suppose fastest observed lead time falls to 2.5 days. This page works the full calculation at that level so you can see exactly which result moves and by how much. Measure lead-time variability for Supply Chain & Procurement from the minimum, maximum, and average lead time.
The inputs for this scenario
- Fastest observed lead time: 2.5 days (the input this scenario stresses; the baseline uses 5)
- Slowest observed lead time: 9 days (held at the documented default)
- Average lead time: 7 days (held at the documented default)
Working through the calculation
- The calculation starts from the formula this tool documents: Lead-time variability = (maximum − minimum) lead time ÷ average lead time × 100.
- Lead-time variability works out to 92.86 % at these inputs, and this is the headline figure for the scenario.
- Spread works out to 6.5 value at these inputs.
- Minimum works out to 2.5 value at these inputs.
- Maximum works out to 9 value at these inputs.
How this compares with the baseline
- Against the tool's baseline example, where fastest observed lead time sits at 5 days and the headline result is 57.14 %, this scenario comes in 62.5% above the baseline at 92.86 %.
- It computes the range between maximum and minimum lead time divided by the average, as a percentage that quantifies delivery inconsistency. When the numbers land here, the stressed input is the lever to work; the walkthrough above shows exactly how much each output recovers as it climbs back toward the baseline.
Results at a glance
- Lead-time variability: 92.86 % (headline result)
- Spread: 6.5 value
- Minimum: 2.5 value
- Maximum: 9 value
Run it with your numbers
- To rerun this with your own numbers, open the live Lead Time Variability calculator, set fastest observed lead time to your actual value, and adjust the remaining inputs to match your operation.
Last reviewed 2026-05-12.