As mentioned in my last blog post manual forecasting generally produces results whose accuracy is, rather questionable. However it can be of benefit in certain situations. In such situations the overriding factors tends to be that the person doing the forecast has some information that is not currently visible in the data. Good examples of where manual forecast checks and adjustments can be applied are:
- Introductions of products with no previous comparable products lines. Also if there are differences in planned pipeline stock building, forecast adjustments may increase accuracy.
- Planned promotions that are not conveyed to the forecast system with the data. Forecast review is often also good to focus on promotions.
- The wins and losses of very large accounts, if not communicated to the forecasting solution through data.
Forecasts tend to reflect the outlook of the team producing them
There’s also clear evidence that where there’s a responsibility to leave an explanation for the reasons behind forecast corrections, those corrections tend to be more accurate than where corrections go unexplained. Moreover forecasts tend to reflect the outlook of the team producing them. If they are the responsibility of the sales team, increases in the forecast quantities tend to result in a lower level of accuracy, whereas decreases tend to improve accuracy. Who would have believed that there is a positive bias in salespeople’s estimates of future sales?!
The real issue, in almost every instance where manual forecasting is used for exception situations, is that the people doing the forecasting must actually have sufficient time to review those situations properly, to take past data into account and to consider carefully the most likely outcome. In forecasting it is important to move quickly to automate routine forecasting, and then give your forecast analysts the best tools to dig into the more challenging situations!
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