Reduce inventories by more than $112 Million

Reduce inventories by more than


We delivered an automated forecasting capability that reduced the forecast error on average by 10.5% for the key categories. Expected reduction in inventory from this project was in excess of $112 Million.

The challenge

Our client is a large supermarket chain with sales more than $25 Billion. Poor forecasting for imports and general merchandise was leading to significant excess inventory for the customer while facing stock-outs at the store level.

Our solution

CoreCompete deployed a forecasting solution (from SAS), that was capable of forecasting at higher levels to support forecasting for product transitions.

Scorecards were built that made it easy to objectively compare forecast performance over time at different levels of the merchandise hierarchy.

The entire process from the weekly data upload to the integration of the forecast into the replenishment process was automated using a parameter driven data integration process.

The solution was developed and went live for the first phase in 13 weeks.

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