I am working on a time series forecasting model to create projections on HR demographics data over a 10 year horizon.
We have certain diversity targets. eg. say 50% women in headcount at the end of the period. right now the model is giving a lower number, thus showing a gap between forecasted number and target number.
I am looking to make adjustments to the model with changes in hiring rates and reduced attrition rates and figure out the optimal combination to achieve targets. what would be the best way to incorporate this?
So it sounds like the demographics/diversity targets at your company are not the result of natural change, but is dependent on active management (e.g. adjusting hiring rates and reducing attrition), therefore I think time series models may not be the best choice here.
Would it make more sense for you to take a regression approach? And the data you need might look like this: