This course has been created for analysts, forecasters wanting to introduce or improve forecasting which can be related to sale forecasting, economic forecasting, technology forecasting, supply chain management and demand or supply forecasting.
This course guides delegates through series of methodologies, frameworks and algorithms which are useful when choosing how to predict the future based on historical data.
It uses standard tools like Microsoft Excel or some Open Source programs (notably R project).
The principles covered in this course can be implemented by any software (e.g. SAS, SPSS, Statistica, MINITAB ...)
Problems facing forecasters
Customer demand planning
Seasonal changes in demand/utilization
Roles of risk and uncertainty
Time series methods
Econometric methods (casual methods)
Regression analysis using linear regression or non-linear regression
Autoregressive moving average (ARMA)
Autoregressive integrated moving average (ARIMA)
Forecast by analogy
Simulation and other methods
Probabilistic forecasting and Ensemble forecasting
Reference class forecasting