Case Study: Enhancing Demand Forecasting with Machine Learning

A leading retail company struggled with outdated demand forecasting models that led to overstocking, lost sales, and operational inefficiencies. Traditional methods couldn’t adapt to shifting consumer behaviors or market conditions. Learn how applying machine learning transformed their forecasting process, improving forecast accuracy by 30%, reducing excess inventory by 18%, and boosting supply chain responsiveness—positioning them for sustained growth and customer satisfaction.