MLR Profile

In the profile for multiple linear regression (MLR profile) in Demand Planning (DP), two methods are available:

In the MLR profile, you can make settings for each forecasting method.

You have created a master forecast profile. For more information on how to create a master forecast profile, see Creating a Master Forecast Profile.

For the MLR standard method, enter the following:

Key figure for the historical values of the dependent variable (Y)
Independent variables (X_i), either as indicators or as time series
If you use key figures, you can define a time shift between cause and effect.

Example
The demand for a consumer product may depend on the income tax rate. However, since most employee are paid at the end of the month, it takes at least one month until the effect of a reduction in the tax rate can be seen.

End of the example.

For more information on how to create a time series for MLR, see Creating a Time Series Variable.
Method used to measure the error in the historical values
Assumptions on how the error is distributed
If you want the system to generate alerts when measures of fit are not reached or exceeded, enter a diagnosis group. For more information, see Measures of Fit.
Time shifts between dependent and independent variables

For the MLR forecast with POS data, enter the following:

Key figure for historical data
Key figure for POS data
Statistical forecast model
Diagnosis group, which determines the upper limit for the mean absolute percentage error (MAPE)
You create the diagnosis group specifically for the MLR forecast with POS data. You cannot use this diagnosis group in the MLR standard forecast.
Key figure, in which the inventory fluctuations calculated are saved
Determination of whether or not the system is to consider null value in the historical data and in the POS data

In the master forecast profile, choose the MLR Profile tab, and then choose the required forecasting method.