Regarding normality assumptions for model evaluation I have been told by my supervisor that it is not needed in the case of analyzing but is needed in forecasting only. i am looking for an explanation.
From my understanding, more important than normally distributed variables (prior to modelling) is the normality of model residuals (evaluated from a Q-Q plot, for example) after your model has been fit. Is this relevant to your question? Here is a paper describing this misconception (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5436580/)
Also, more information on your problem would be helpful!