The Impact of Machine Learning on Demand Planning Precision

The traditional approach to product demand forecasting struggles to capture many of today’s complex market dynamics and is plagued with bias, human error, waste and inefficiency. Fortunately, advanced analytics and intelligent automation are laying the foundation for a powerful new model that can improve demand planning processes and increase forecast accuracy, leading to significant cost savings for consumer goods organizations.

This white paper, developed collaboratively by Path to Purchase Institute and SAS, examines the impact that machine learning and other automation tools are having on success at forward-thinking consumer goods organizations. And leaders from Nestle, Georgia-Pacific and Kellogg's will share their insights on the importance of these new technologies on their business.