Probabilistic Demand Forecasting.
From → To
From the planning pain to probabilistic demand forecasting.
Every forecast ships as a distribution — expected value, P25/P75 (25th to 75th percentile) band, P5/P95 (5th and 95th percentile) tails — calibrated from historical bias and variance per segment. The plan consumes the distribution, not just the mean.
When the plan consumes the distribution rather than the mean, buffer dollars get allocated to the SKUs whose downside variance actually exposes revenue, not spread uniformly across the catalog.
When the plan consumes the distribution rather than the mean, buffer dollars get allocated to the SKUs whose downside variance actually exposes revenue, not spread uniformly across the catalog. Forecast accuracy stops being a vanity metric and becomes a measurable, improving asset, and the inventory-to-revenue ratio improves without trading away service.
- 01Empirical bias and variance calibration per segment
- 02Time-bucketed distributions for seasonality
- 03Forecast-quality drift detection