I am working on a forecasting problem for generic drug launch and the only data I have is past sales for branded drugs, unit cost of branded drugs, and other categorical variables such as drug category(chronic, wellness etc.), drug form(tablet, solution etc).
The major problem: Generics are launched once the patent of branded drugs expire. And so, I do not have any past data for generic drugs. I am trying to forecast the demand of generics for inventory optimization.
Secondly, can you also suggest some other significant factors which I should look upon to design the model?
Finally, if the distribution is highly skewed, what would be the most apt data transformation that I can use?