6×2 hoursWhere every team starts
Demand Planning
What demand forecasting should be about, how to measure planning success, and how to achieve it
- Demand versus sales: unconstrained demand, and the difference between forecasts, plans, budgets and targets
- The right granularity and horizon for your supply decisions
- Accuracy and bias, with metrics weighted by value instead of MAPE
- Forecast Value Added: what each step of your process adds
- Demand drivers, statistical models and machine learning
- When planners should enrich the forecast, which products to review first, and how to avoid biases
- New products, outliers, and five case studies: data errors, prices, shortages, promotions and Covid
- The Beer Game, then your team assesses its own maturity in data, metrics, models and enrichment


Two pages of the course. Forecast Value Added, step by step, and how to choose your forecasting metrics.






Data Science for Supply Chain Forecasting
Inventory Optimization: Models and Simulations
Demand Forecasting Best Practices



