If more past values are available than the system requires or is to use for model initialization (refer to "Number of historical values" and "Initialization periods" in Forecast Parameters: Independent of the Forecast Model), then the system will carry out an ex-post forecast. In order to do this, the system divides the time series of past values into two groups. The first group with the older values is used for initialization. The system carries out an ex-post forecast using the second group as it is best to adapt the parameters to the most recent developments.
Furthermore, you can monitor the forecast model during the initialization phase by comparing the forecast values from the ex-post forecast with the actual consumption values.
The ex-post forecast does not only play an important role in the initial forecast. It is also significant for subsequent forecasts. It is, therefore, possible to omit periods during the forecast calculation. This means that you can determine, for example, daily forecast values for a material even if you only execute a weekly forecast run for this particular material. The system forecasts the missing periods in retrospect. The ex-post forecast is only possible for models with the exponential smoothing procedure.