Sales forecasts have been misleading companies for years. The wildly different numbers that they present from one period to the next should be analyzed with care, as they are more likely to be numbers that lie than actual reliable predictions. But why is it so difficult to come up with accurate forecasts and reliable performance data?

Consider the following scenario: You currently use a CRM system, but the standard reports are poor at best, so you pay a consultant to develop custom reports that will then be run by your sales reps for every forecast report. That report is then exported to a custom Excel sheet with tons of columns, rows, tabs, pivot tables, and everything but the kitchen sink. In the report, the reps alter the data to make the numbers work in their favor. They change deal stages, values, commit levels and create a forecast. After this point, each rep sends that spreadsheet to their managers. The managers combine all forecasts into one forecast. From there, they change up the data and make the numbers work in their favor to create a forecast. The managers send their forecasts to the next level of managers who have an admin or a sales operations person combine all the Excel sheets into one master sheet. Finally, this sales leader switches up the data to work in his or her favor, and voila!, the sales forecast is born for the CFO, CEO and the board.

What’s wrong with this picture? The original forecast submitted by the reps now no longer looks even remotely the same as the forecast submitted to C-level management. Nevertheless, it’s considered accurate. Just ask any sales leader who does this and they will tell you they are spot on. Dig a little deeper and you’ll typically find that is not actually the case.

In their 2013 Sales Performance Optimization Study, CSO Insights stated that forecast accuracy is at an all-time low of 46.5%. Less than half of opportunities in the companies they surveyed are properly forecasted. In a world of big data and big BI technology, should this not be getting better?

To find the answers, you need not look any further than your frontline sales managers and sales reps. Improve forecasting by attacking the sales behaviors that erode the accuracy at the ground level. Secondly, stop taking your data out of your CRM system. Once sales reps improve the quality of their forecasting, then you can use a forecast report that is produced and visualized right inside of your CRM system. This way, you can track the history of the changes that are made and answer key performance questions. If your CRM system can’t do it, there are several really solid reporting tools on the market that can help.

Here are some of the behaviors that you should be tracking and correcting, which will improve your forecasting accuracy:

  • Not properly following your sales process.
  • Not properly following your sales methodology.
  • Not being able to select correct close dates which causes deal pushing.
  • Not logging key activity (validation) to prove a deal has the right to be in a particular stage.
  • Valuating deals poorly (including sandbagging deal sizes).

By tracking these activities and reporting them at the sales rep level, a frontline manager can attack the problem where it needs to be addressed – at the sales rep level. Holding yourself, your sales managers and your sales reps accountable for their behaviors will dramatically improve your forecasting.