Case Study: Largest Medical Device Manufacturer improves demand forecast accuracy with Mu Sigma

Demand Forecasting in The Time of COVID-19: Navigating Demand Volatility using Advanced Analytics

Largest Medical Device Manufacturer faced major demand forecasting disruption when COVID-19 made its existing planning processes unreliable across multiple product lines. The company needed a way to identify which parts of the portfolio were affected, estimate product-level impact and recovery timing, and compare demand sensing forecasts against baseline forecasts.

Mu Sigma developed a self-serve COVID-19 Forecast Simulator using statistical modeling, machine learning, and business inputs to create a demand sensing framework. The solution included a web-based UI, data preparation and modeling layers, and the ability for users to simulate scenarios and download forecasts, resulting in a 35–40% improvement in forecast accuracy and a more resilient supply chain.