Preventing Stockouts on Fast-Moving Pharmaceutical SKUs
A pharmaceutical distributor supplying 900 pharmacies holds inventory against a forecast maintained in spreadsheets and updated monthly.
Run on Sanchay · Supply Chain Resilience
The challenge
Fast-moving SKUs stock out between forecast refreshes, sending pharmacies to competing distributors.
Safety stock is set by habit at a flat percentage rather than by demand variability per SKU.
Nobody measures forecast accuracy, so the forecast is never corrected.
How Sanchay solves it
Per-SKU Forecasting
Demand is projected per SKU using its own history and seasonality rather than a category average.
Variability-Based Safety Stock
Safety stock is set from measured demand variability and supplier lead time, not from a flat rule.
Accuracy Tracking
Every forecast is scored against what actually happened, so the model is corrected continuously.
Stockout Alerting
Projected stockouts are flagged with enough lead time to place an order rather than an expedite.
Reorder Recommendation
Reorder quantities and timings are recommended against forecast, lead time, and shelf life.
The outcome
Stockouts on fast-moving SKUs caught before they occur rather than after.
Safety stock sized per SKU rather than by a single blanket percentage.
Forecast accuracy measured and improving rather than assumed.
Representative scenario: a modelled industry situation showing how this accelerator applies. Figures are projections, not a named client result.
Capabilities used
Every accelerator is assembled from the same capability layer, so a workflow you adopt here shares its foundation with the rest of the portfolio.
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