Traditional demand planning is under pressure. Volatile markets, shifting customer behaviour, and shorter product lifecycles demand more than static forecasts and spreadsheet-driven adjustments.
In this session, we explore how Anaplan transforms demand planning using Machine Learning, AI, advanced statistical forecasting and Connected Planning, enabling planners to move from reactive forecasting to a more intelligent, collaborative and responsive planning process.
In 30 minutes you'll see:
- How statistical forecasting and Machine Learning can improve forecast accuracy through best-fit method selection and predictive analytics
- How causal data, seasonality, outlier management and historical demand patterns can be used to build a stronger baseline forecast
- How planners can move from manual spreadsheet adjustments towards exception-based, collaborative demand planning
- How scenario modelling and consensus planning help teams understand changes in demand and rapidly evaluate alternative outcomes
- How Connected Planning links demand with supply, inventory and financial plans, giving teams greater visibility of downstream volume and value impacts.
Whether you’re looking to improve forecast accuracy, reduce bias, shorten planning cycles, increase planner productivity or modernise your demand planning capability, this session will demonstrate what’s possible with an AI-enabled connected planning platform.
