Demand Forecasting for a Medical Devices Company

  • January 30th, 2020

Demand forecasting using near real-time data is crucial to optimize your supply chain

One of the largest medical technology companies in the world was looking to revamp its existing supply chain model. At the macro-level, the client wanted:
• Improve the accuracy of its demand forecasting model to increase supply chain efficiency
• Create a framework that can forecast at acceptable high-levels of accuracy which was currently not possible due to demand-stream volatility.

Mu Sigma created an advanced analytical framework aimed at improving the client’s demand forecasting. We followed a comprehensive methodology to enhance existing forecast accuracy to ensure short term accuracy and long-term volume alignment.

Mu Sigma helped improve accuracy of forecasting from previous 53% to 70% with nearly 95% accuracy across stable segments. The solution also stabilized overall process efficiency.

Download the case study to know more.

« Previous

Decoding Consumer Behavior using Agent-Based Modeling

Mu Sigma is enabling next-level consumer insights through Agent-Based Modeling (ABM) – a predictive-prescriptive technique to observe consumer behavior in a simulation of their market environment and predict demand accurately.

Next »

Transforming Customer Experience for a Fortune 50 Bank

A global bank approached Mu Sigma to transform the way their customers perceived them. They were looking to offer a seamless omnichannel customer relationship, build customer loyalty, and enhance the Net Promoter Score (NPS).