I am trying to solve a problem for a brewery:
A brewery has 50 beer types in total out of which only 8 to 10 beers are available on tap for a single day i.e only 8 to 10 beers will be sold on any given day. The combination were selected randomly as of now. How to find the best beer type combination which will yield maximum sales. And depending on the best combinations(3-4) I want to forecast sales of individual beer to understand the quantity requirement in the future. Also i wanted to know the contribution of individual beer on the total sales forecast. how to find the best combination of products and then forecast sales, and after forecasting again determine the contribution of individual products?
Example of how the data looks like:
Potential problems: I have just 1000 days data. I can forecast total sales as it is continuous, but when dealing with individual beer it has a lot of gaps/intervals in the time series.
Appreciate if you can give an solution/example in r.