Case Study: Leading Home Improvement Retailer Improves Product Availability with Mu Sigma

Built a scalable analytics framework to anticipate effects of weather on sales for a leading home improvement retailer

Mu Sigma worked with a leading home improvement retailer, a Fortune 500 company operating more than 1,500 stores across multiple countries, to address weather-driven fluctuations in sales. The retailer needed a better way to anticipate demand across 200+ micro-regions and 5,000+ product categories per region to reduce stock-outs and overstocks while managing huge data volumes and tight time and cost constraints.

Mu Sigma built a scalable analytics framework using a hypothesis-driven forecasting approach and cloud computing on AWS, including EMR with distributed tools like Spark and Hadoop. The solution identified significant weather-sales relationships and improved fulfillment forecasting, resulting in a 12% reduction in stock-outs, lower stock holding costs, and a stable, scalable framework that could be deployed across geographies with minimal cost.