Case Study: Leading Fortune 500 Energy Company reduces inventory holding costs with Mu Sigma's supply chain optimization solution

Building Scalable Supply Chain Through Inventory Optimization

Mu Sigma worked with a leading Fortune 500 energy company’s Innovation and Supply team to tackle a common supply chain challenge: excess inventory driven by uncertain and volatile demand. The customer needed a more data-driven way to anticipate both emergent and non-emergent material needs, reduce overstocking, and improve inventory planning across thousands of materials and facilities.

Mu Sigma built a demand forecasting and inventory optimization solution using historical inventory, purchase order, material request, issuance, and weather data. By testing an ensemble of 150+ time-series model combinations and selecting the best model for each material, Mu Sigma helped the customer reduce stockouts and excess inventory, with the project projected to save $1.6M annually in holding costs for the selected 15 materials.