Our demand model's accuracy has dropped over the last few weeks. Should we just retrain it on the latest data?

Not automatically. First I check the input data distributions, then I compare ground truth against predictions to see where it's actually going wrong. If the drift comes from an external extraordinary event we can't account for when predicting, I don't retrain on it.

I flag the predictions while it lasts instead of teaching the model a one-off shock.