Course Code
mrkfct
Duration
14 hours (usually 2 days including breaks)
Requirements
Good Excel or other Spreadsheet knowledge
Solid Maths and Statistics knowledge
Overview
Audience
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.
Description
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 ...)
Course Outline
Problems facing forecasters
- Customer demand planning
- Investor uncertainty
- Economic planning
- Seasonal changes in demand/utilization
- Roles of risk and uncertainty
Time series methods
- Moving average
- Exponential smoothing
- Extrapolation
- Linear prediction
- Trend estimation
- Growth curve
Econometric methods (casual methods)
- Regression analysis using linear regression or non-linear regression
- Autoregressive moving average (ARMA)
- Autoregressive integrated moving average (ARIMA)
- Econometrics
Judgemental methods
- Surveys
- Delphi method
- Scenario building
- Technology forecasting
- Forecast by analogy
Simulation and other methods
- Simulation
- Prediction market
- Probabilistic forecasting and Ensemble forecasting
- Reference class forecasting
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