The key points from this module are:
A forecast is a prediction of some event or events.
Forecasting problems occur in many fields. For example, business and industry, in the
area of economics, finance, environmental science, social science, political science,
Forecasting is the basis for all planning decisions used for both push and pull processes
in a supply network.
A forecast is just a forecast it cannot be 100 percent accurate.
Observed demand= systematic component + Random component
There are three ways to calculate systematic component
multiplicative- S= level*trend*seasonal factor
additive- S=level + trend + seasonal factor
Mixed- S=(level + trend) * seasonal factor
Adaptive forecasting is a term used to describe several different methods of determining the likelihood of events occurring based on statistical data and variable analysis.
The most simple adaptive forecasting methods is the moving average method. This moving average method is used when the demand has no observable trend or
Single exponential smoothing model is used when there is no observable trend or seasonality.
MAD stands for mean average Mean Absolute Deviation.
MAD measures the total error in a forecast without regard to sign.
Cumulative Forecast Error; it measures any bias in the forecast,
A tracking signal is a measure that indicates whether a method of forecasting is
accurately predicting the actual changes in demand; that means, whether the forecasting system is stable and consistent or not.
Croston's model is the prediction of mean time between demands and the magnitude of demand whenever such kind of demand occurs
Croston's Model has two components:
Predicting mean time between demands
The magnitude of demand whenever such demand occurs
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