Hi @Volker.
I’m developing a demand model now where multiple items have sporadic, outlier type demand.
We first correct the outliers and use corrected demand to model normal sales patterns. Then we develop models to account for fluctuations in actual demand with the target being the difference between the actual demand and the predicted normal sales demand (residuals).
So we can model promotions, price changes etc by taking the residual prediction and adding it to the normal sales pattern prediction.
Does that make sense?