Case Study: Huffy improves forecast accuracy and inventory planning with QueBIT

Huffy Bicycles relies on predictive demand planning to increase forecast accuracy

Huffy, a bicycle manufacturer and distributor, faced major forecasting and inventory planning challenges because of 90-120 day bicycle lead times, high carrying costs, and a manual process that relied heavily on sales intuition instead of analytics. QueBIT helped Huffy address this issue with an IBM-based predictive demand planning solution using IBM SPSS Modeler, IBM Cognos TM1, and IBM Cognos BI.

QueBIT built a customized forecasting platform that automated demand planning, used predictive and ensemble modeling to improve forecast accuracy, supported new-item forecasting, and integrated approved forecasts directly into Huffy’s order management system. The result was reduced workload for sales associates, better visibility into demand and inventory, improved forecast accuracy, fewer inventory shortfalls, and better cash flow through lower overstock levels.

Huffy

Dan Carlascio

CIO/Director of Global IT