I am working for a large food retail company and we are using ML models to predict the demand of certain products for the weeks to come.
Of course, looking at the sales distribution, 2020 was a completely irregular year and therefore, it really messes with our forecasting model.
Are you also experiencing this in the data you are analysing? I am really interested how you adapt your data analytics solutions to this situation. Do you exchange features? Do you exclude certain time periods?