Skip to content
AI Demand Forecasting for Multi-Region Retail
← All case studies

AI Demand Forecasting for Multi-Region Retail

Cedar & Stone Retail Group

Implemented machine-learning forecasts across 340 stores to improve inventory planning and reduce stockouts.

AIForecastingRetail
AI Demand Forecasting for Multi-Region Retail

Overview

Problem

Manual spreadsheet forecasting caused frequent stockouts on fast-moving items and overstock in seasonal categories.

Solution

  • Built store-SKU forecasting models with weather, promotion, and local-event signals
  • Added planner override workflows with impact simulation
  • Delivered confidence intervals and replenishment recommendations

Outcome

  • 24% reduction in stockouts
  • 17% reduction in aged inventory
  • 11-point increase in forecast accuracy (MAPE)

“Forecast reliability finally gave our planners room to focus on strategy.”

Elise Romero, Director of Merchandising, Cedar & Stone

Related resources

Explore service details and additional implementation insights.