I'd like to use predictive modeling to identify which programs may lose money in the future. I have monthly data within the FY for hundreds of programs, in categories of actual revenue, actual margin, forecast revenue, forecast margin, etc. Each category is recorded per month, so for actual margin, I have values for January through October, actual revenue Jan - Oct., etc.
What I'd like to do is set up a process by which I run the analysis for all programs, then use the resulting forecast file to see which programs are forecasted to lose money. In the process attached, I filter for Actual Margin, fill any empty months, run the data through the ARIMA tool and then the forecast tool. This gives me usable data when my initial filter also filters by a single program, but meaningless data without the program filter.
Is there a way to run the forecast process iteratively to get results per program? Or, is there a whole better way to approach this?
Thank you!
