This session builds on the previous session on " Current state of Demand planning". It explains some of the fundamental obstacles encountered by the traditional approaches and the various approaches that are currently gaining traction with early adopters. The role of academia is covered. Topics will include demand modeling, machine learning, probabilistic forecasting, and so-called demand-driven alternatives.