Examples
Examples
Try the starting example
- Observed lead-time demand scenarios (inventory units)
- 20,25,30,40,50
- Desired empirical coverage quantile (0<q≤1)
- 0.8
- Empirical reorder demand (units)
- 40
- Mean observed demand (units)
- 33
- Buffer above mean (units)
- 7
Try another scenario
- Observed lead-time demand scenarios (inventory units)
- 20,25,30,40,50
- Desired empirical coverage quantile (0<q≤1)
- 1
- Empirical reorder demand (units)
- 50
- Mean observed demand (units)
- 33
- Buffer above mean (units)
- 17
Calculation method
Calculation method
Empirical reorder demand (units)
Sorted observation at rank ceil(q×n), with ranks starting at one.
Mean observed demand (units)
Arithmetic mean of supplied scenarios.
Buffer above mean (units)
max(0,empirical reorder demand − mean).
Symbols and units
- a
- Observed lead-time demand scenarios (inventory units)
- b
- Desired empirical coverage quantile (0<q≤1)
Use the units shown. A list keeps the order in which you enter its values. The symbol ^ means “raised to the power of”.
Assumptions & limits
Assumptions & limits
- Empirical nearest-rank coverage across observed lead-time-demand scenarios; no normality assumption or future service guarantee. Supported limits: Nonempty finite nonnegative scenarios. Quantile strictly positive and ≤1.
Are these inputs private?
These calculations run in your browser. A shared link contains the values you choose to share. Only questions submitted to the separate AI finder are sent to OpenAI.