A leading alcoholic beverages company operating across more than one hundred thirty countries struggled to accurately estimate market share and predict demand using limited datasets and rigid monolithic code that hindered micro and macro forecasting across two hundred thousand time series. To resolve this challenge, Sigmoid deployed a scalable machine learning-based demand forecasting solution. Sigmoid’s advanced software automated complex data modeling, seamlessly processing massive time series while accounting for diverse exogenous factors. By streamlining supply chain operations and eliminating manual bottlenecks, Sigmoid’s intelligent platform dramatically improved forecast accuracy, optimized inventory management, and successfully reduced overall operational costs by a factor of five.

Join for free to read