Forecasting Strategy feasibility.

Hi All,
I need to check feasibility of one particular scenario.
I have 100 Materials for which I need to Forecast. I need to calculate best Forecast strategy for all Material with calculation of Forecasting Error.
Correct me if I am wrong: We can get the Best Forecasting Strategy by adding all the Univariate Profile with different Forecasting Strategy in the Composite Profile Tab.
Now my requirement:
1. I have 100 SKUs. Each individual SKU has different historical data. Now I cant run Univariate Profile for each individual SKU separately and also run the Composite Profile to find out the best Forecast.  I need to find is there a way to run the Forecasting Strategy for all SKUs separately something like mass run together?
To be very precises i need to run Forecast Strategy for all 100 SKUs for their individuals Historical Data simultaneously.
Thanks,
Best Regards,
Bhaskar

To comment on the statement: If you are looking at performance at Go-Live you might be better off with Auto 1. Auto 2 takes more time
some more ideas if you want to explore them
your final solution will depend on the weightage of the performance of the forecast run vs the accuracy of it
If you are focussing on the performance use Auto 1 during go live. It will definitely be faster.
If you are looking at accuracy go for Auto 2
You also dont have to use a one-size- fits-all  solution for the million CVCs.
Also your forecasting level will make a difference. You might notice dont have to forecast at the most detailed level or for all the million CVCs all the time. Check if all the characteristic levels are pertinent to your forecasting.
You can also forecast at a aggregate level depending on the product characteristics. epending on the business you should look whether a top-down forecasting approach can be adopted vs a bottom-up approach that you are looking at. You can use KF disaggregation to let the forecast take its proportions
You need to be able to group your products at least into 2. You might also use the other characteristics to group these
examples of Group 1:
Critical Products were forecast accuracy matters
Products with Trend, Seasonality
Products which will have an immediate visible effect post go-live
High value products
Regions where not going out-of-stock might be important
use Auto 2 on Group 1
Group 2:
Rest of the products
Use Auto 1

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