Agile Medical Device Demand Planning

Situation

A leading medical device manufacturer struggled to forecast demand accurately across multiple product lines as the COVID-19 pandemic disrupted traditional forecasting models. Their existing processes were unequipped to handle the magnitude of uncertainty and rapid market shifts caused by the global crisis.

Challenge

The client faced:

• Significant disruptions in supply chain planning due to COVID-19-related uncertainties.
• An urgent need for a scalable tool to accommodate the dynamic nature of pandemic-related impacts.
• A lack of integration between demand forecasts and supply chain systems.

Approach

Through Advanced Simulation and Modeling, Mu Sigma integrated statistical modeling with machine learning techniques and domain-specific expertise to create a user-friendly simulation tool. Our initiative incorporated dynamic variables related to COVID-19 as inputs to the model, thereby enhancing its capability to adapt to evolving real-world scenarios and providing a robust platform for strategic planning.

In terms of Data Optimization and Visualization, a comprehensive data warehouse was established to serve as a centralized repository for all relevant data, thus supporting an extensive visualization layer. Additionally, a web application was designed to allow users to tailor features according to their needs, visualize the impact of various scenarios, and access downloadable forecasts for further strategic integration. To ensure long-term operational resilience, Mu Sigma implemented a quality control framework for maintaining data integrity and developed a scalable framework designed to foresee and manage future shock events, fostering an antifragile supply chain.

Impact

• 40% improvement in demand forecasting accuracy.
• Significantly boosted supply chain agility, enabling antifragility during volatile market conditions.