The Next Generation of Forecast Accuracy

I once closed a $450,000 deal in seven business days. A company wanted to upgrade from an old version of our product to the new version. They had budget, and they wanted to move on it. I learned this in my first sales call with them.

I did not forecast it.

My manager and I weighed the pros and cons of raising visibility on the deal. We still needed to bring in resources for a series of demos, some upfront training, a proposal for the solution and implementation services, and the contract reviewed and signed. But we wanted to keep this in our hip-pocket and become the heroes of the quarter.

I wonder now if we did the right thing from our executive’s point of view. Was it better to potentially bring in some extra, outside-the-forecast revenue, or were we just protecting ourselves in case the deal couldn’t make it through our legal team or their signature process in time? We ended up looking good, but we may have made leadership look like they didn’t really know their own numbers.

Organizations still struggle today with forecast accuracy. Our 2017 World-Class Sales Practices Study showed that the win rate of forecasted deals is 46.9% – less than half. On top of that, when deals do close in their predicted quarter, they usually don’t close as they were forecasted. According to that study, the average percentage of deals that closed as originally forecast is only 48.2%.

With numbers like these, what does forecast accuracy even mean?

There’s an actual calculation metric for Forecast Accuracy, which is: (actual – forecast)/actual*100. And this will give you a percentage that you can track every quarter, if you want. But this calculation doesn’t tell the whole story.

If you’re interested in trying to apply more science to your team’s selling, consider tracking your forecast accuracy in in these additional ways:

  • Revenue Accuracy – is the revenue amount for each deal closing as forecasted? If not, what’s the variance between the prediction and actuals?
  • Product Mix Accuracy – are forecasted deals closing with the proposed solution mix as expected? Are components dropping off or being “thrown in” at the end? What is the variance between “booked” products and “forecasted” products?
  • Quantity of Forecasted Deals – how many deals were included in the forecast and how many “blue birds” popped up? Are sellers holding out or are they successfully moving deals forward?
  • Win/Loss/No Decision Rate of Forecasted Deals – how many deals are your team winning? How many are pushed out? How many are we actually losing? Understanding this mix can be especially insightful for managing the risk inherent in your projected forecasts.


Executives are under more pressure than ever to understand the pulse of their business. Shareholders and board members alike don’t really want surprises (good or bad); they want to see controlled and managed performance from their executive team. Analyzing your forecast accuracy at one more level of detail may highlight selling issues, personnel issues, or negotiating issues, which, once fixed, should help your organization continue to improve your forecast accuracy.


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