Fast fashion retailer cut overstock by 50%
With Pecan’s models, they saw a reduction of up to 50% in overstock amounts, and an uplift of 10-25% in sales due to increased product availability
increased sales from
Previously used aggressive discounts to keep pace with fast fashion
Traditional forecasting methods made it almost impossible for the retailer to ensure that supply at stores meets consumer demand resulting in sub-optimal financial performance and mediocre customer experience. The inability to accurately forecast demand at a store and SKU level led to significant revenue losses due to stock-outs, lower margins due to aggressive discounts, and overall high operational costs related to inventory holding and reverse logistics.
SKU-level predictions to forecast demand at the speed of shopping
Pecan generates sales forecasts at a granular level on a per SKU, per week/day, per store basis. With the Pecan platform, Retailers can build a demand forecasting model using past transactional (sales/usage) data, operational data, inventory data, and external data enrichments provided by Pecan.
50% reduction in overstock amounts
Reduction of up to 50% in overstock amounts, achieving 10-25% additional sales (fewer stockouts), and maintaining an ongoing precision rate of 80-95% in sales prediction.