5 Strategies for More Accurate Sales Forecasting
5. Augment the Art of Forecasting With Science
Use data science to score deals by comparing them to deals you have won in the past.
So many sales forecasts are based on the “gut instinct” of the sales team. There will always be some subjectivity in forecasting, but judgments should be based on objective data. Historical trend data and top-down run rate predictions have some value in forecasting, but in today’s rapidly changing markets a bottom-up, deal-by-deal forecast is essential.
The challenge here is that anecdotal details and personal judgments can dilute the accuracy of the numbers as they are rolled up through the sales organization. Sales managers usually know the right questions to ask, but they often lack the time to inspect every opportunity, so this isn’t the fail-safe that most companies believe it is.
To get around this, I am increasingly seeing companies utilizing data science to score deals by comparing them to deals they have won in the past. This provides an objective data-based view of a deal’s likelihood to close and gives a great benchmark with which finance functions can compare the sales leadership numbers.
Although the accuracy of these data science-based algorithms is shown to outperform human judgment, my advice is to use them to augment human forecasting processes, not replace them.
So, my takeaways are that forecasting has become a painful, time-consuming process. Wasted time cripples everyone and company leaders just don’t have the reliable projections they need to build a predictable business.
It’s time for the sales function to stand up and take accountability for its forecasting and become a real business partner to the finance team. For this to happen, the business also needs to deliver the right tools, processes, and cadence for accurate sales forecasting. Use data and science alongside human insights in every forecasting judgment.
What’s the biggest blocker to accurate forecasting for your company? Share your experience with sales forecasting in the comments section below.
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