A much easier and more reliable approach is to leave the underlying forecast intact and then to carry each business change as a separate overlay that get applied to the forecast, some adding volume and some reducing it.  When outputting a forecast for use in headcount planning, you output the combined forecast of the underlying plus the overlays.  It is helpful to add sales & marketing campaigns into forecasts in this way, too.  Showing adjustments as overlays means that the underlying shape and integrity of the forecast remains intact and that you are more explicit and controlled in how the output forecasts change over time.

The first advantage of this approach is that if any one of those projects moves in scope or timescales, it’s a straightforward task to change that one overlay and re-build the output without having to undo any other work.

For the forecaster, there is another huge benefit of this approach:  Suppose, for example, an initiative was supposed to reduce volumes by 10% from 10,000 per week to 9,000, and that your forecast accuracy was normally very good (less than 2% variance per week).  If, in the week the initiative goes live you receive 9,500 calls, the fact that the forecast remains explicit in terms of individual changes should mean that the forecast variance can be explained in terms of the under-achieving initiative and not as a problem with the forecast per se.  While this is good news for the forecaster’s self esteem, it’s also good business to make sure eyes are focussed on the real source of the problem.  If you have 2, 3, 10 or 20 changes going on at the same time, this analysis can be complicated but it becomes even more valuable.