What sales preference allows forecast KPIs to be weighted by probability?

The option that indicates how forecast KPIs can be weighted by probability is to calculate forecasts as weighted. This method specifically allows for the assignment of different probabilities to varying sales opportunities, modifying how much each opportunity contributes to the overall forecast based on its likelihood of closing. This is particularly beneficial in forecasting because it creates a more nuanced and realistic prediction of future sales, reflecting the varying degrees of certainty associated with each potential sale.

By using a weighted calculation, organizations can prioritize opportunities that are more likely to convert and thus forecast revenues more accurately. This weighting can be based on factors such as past sales performance, stage in the sales cycle, and external market conditions. The weighted approach helps businesses make informed, strategic decisions based on a more accurate view of potential sales revenue.

In contrast, calculating forecasts as monthly or using transaction totals for forecasting does not factor in the probability of these opportunities occurring, leading to less refined results. Enabling historical sales analysis aids in understanding trends but does not inherently allow for the weighting of forecasts by probability. Thus, the focus on weighted calculations enables a more precise and actionable forecast model.