How to Account for Manual Adjustments
All companies allow planners to make manual adjustments to the statistical forecast. How this process is managed is one of the most important in terms of the quality of the final forecast. More often than not this process is very poorly managed because many people in the field do not understand the importance of removing forecast bias, and secondly, because many people who know better are not interested in fighting the political battle that is necessary in order to keep to a structured approach as to how the manual overrides are maintained, measured and controlled for. This issues applies equally to consensus based forecasting as to statistical forecasting. The common misimpression of consensus based forecasting is that if everyone has a say, the forecast will be improved. This is a false belief, and those experienced with consensus and statistical techniques know that managing the bias, and ultimately removing bias is the most important factor in improving the overall forecast.
How Not to Do It
At my client, they did not keep separate fields for the statistically generated forecast and the manual override or adjustments. Since I did not want the manual override to interfere with the statistical forecast, I had them remove any product that had received a manual override. That worked ok for the short-term, although it greatly reduced the number of projects that we could measure the forecast error for. However, an additional recommendation I made was to begin to record and archive much more information about the manual overrides. This included the following:
- Separate fields for the final statistical forecast and the manual change
- Multiple fields for the manual change so that the date and the person could be tied to the change
What this allowed the company to do was to isolate the manual change to individuals and departments, and then to being to look for bias. Without this data, it is not possible to reduce bias because it is not possible to know from where and from who the bias is coming from. This is particularly problematic for some clients that do a poor job of restricting access to the forecasts, and where multiple people can change the forecast. This is a sure signal of a forecasting problem, a lack of appropriate control over permissions. Generally, control over the manual overrides must be tied to accountability for the forecast. Without this, forecasts become extremely poor, as no one declares ultimate ownership for the forecast, and everyone can blame everyone else for a poor forecast. I have seen several clients that manage their forecast like this, and this situation devolves to this every time. Once there is an institutional acceptance for poor role management, it becomes difficult to re-install discipline, so this is very much a situation to be careful of. Unfortunately it is the position that most companies seem to find themselves in.
Conclusion
Manual adjustments to the forecast are important, and the software selected needs to make manual adjustments easy to do. However, not that many applications do. To see more on different ways to perform manual adjustment in one system in a way which I think is a best practice, see this post below.
