Analytics versus Intuition:
Human behavior plays a big role in sales forecasting. We have a number to shoot for, and often we try to figure out ways to make it, regardless of the soundness of our reasoning. So we assume deals are going to close even if it means we have to ignore telltale signs of trouble until its too late. Using modeling and analytics to evaluate your company’s position in each deal. The model could tell you the warning signs, because analytics would reveal how closely any deal fit with the model’s known history of success. As with weather forecasting, there would be no value judgement, just a probability of rain. Managers would still need to apply their reasoning, but armed with this kind of knowledge, sales people up and down the organization could evaluate scenarios constructed to make their deals match up with the ideal.
Cloudy With 30 Percent Chance Of Sale
Take a more scientific approach. The sales process stage is one of the variables in the model that the company uses to evaluate deals. More importantly, the busisness applies analytics to the deal data rather than expecting managers to review all of it. Analytics would have no trouble spotting the incomplete deal stage and would downgrade the forecast appropriately. A report then would show the variance between the forecast and the model. If you apply this logic to every deal in the forecast, then you have a range of probabilities similar to those weather people rely on to tell you about Saturday’s conditions. More importantly and unlike a weather report, the forecast is also prescriptive because it shows you how you can improve it. Get that meeting with the decision maker if you want to close the deal. Everyone complains about the weather but no one does anything about it. If you’re tired of complaints about sales forecast accuracy, consider building an accurate model and applying analytics. It works for the weather.
