DDMRP in D365 and Demand Forecasting Fueled by Azure Machine Learning

The supply chain landscape is evolving, and traditional planning methods are no longer enough to keep up with rapid market fluctuations. Demand Driven Material Requirements Planning (DDMRP) offers a modern approach by decoupling supply from demand, allowing businesses to achieve greater inventory control, agility, and efficiency.

In this session, we’ll explore how Azure Machine Learning and advanced forecasting models can transform demand planning by predicting future needs with unprecedented accuracy. Learn how to leverage AI-driven insights, optimize stock levels, and improve supply chain resilience—all within Dynamics 365 Supply Chain Management.

Key Takeaways:

• Demand Forecasting with AI – Learn how to set up Azure Machine Learning Service to generate highly accurate demand forecasts.
• Advanced Statistical Modeling – Understand how Dynamics 365 Supply Chain integrates with Azure pipelines for forecasting models such as ARIMA, ETS, and STL.
• DDMRP & Inventory Control – Implement Decoupling Points and define Coverage Groups to balance stock levels and demand fluctuations.
• Baseline Forecasting & Adjustments – Learn techniques for reviewing, adjusting, and authorizing demand forecasts.
• Data-Driven Stock Optimization – Define Minimum, Reorder, and Maximum points using Average Daily Usage (Past, Future, and Combined) to optimize inventory management.