The Future of Sales Forecasting

As Anthony says, "organizations are trying to predict revenue blindfolded." Forrester research shows that 79% of organizations miss their forecast by more than 10%. But why is this happening?

Companies who significantly miss their forecast are typically heavily reliant on their sellers to determine which deals will close, and when. This process is largely judgment-based, and as a result, it is highly inaccurate and prone to bias.

The next evolution of sales forecasting introduces historical data and digital interactions as forecast factors. This "augmented" forecast uses data and probability scoring to supplement manager and sellers opinions with insights to increase accuracy. 

Finally, in the new age of forecasting, Anthony introduces the prescriptive forecast. The prescriptive forecast uses deep AI to interpret unstructured data and large data sets. This changes the focus of forecasting from predicting outcomes to optimizing them.

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This has several implications, namely:

  • Greater organizational responsiveness
  • A more dynamic sales process
  • Bias reduction
  • Blindspot reduction
  • Increased buyer/market insight
  • Management culture shift
  • Broader organizational success ownership

Of course, forecasting is not one-size-fits-all. Different organizations require different approaches to forecasting. 

Best Practices from Forecasting 3.0

In short, the larger and more complex your sales cycle, the more complex your forecasting process will be. One of the best things a team can do is use artificial intelligence to analyze the massive amount of data available for forecasting. AI will become increasingly useful, effective, and beneficial as the complexity of your forecasting increases.

When it comes to driving forecast accuracy within your organization, Matt suggests three simple foundational principles: where, what, and then.

Leaders should understand where inputs to the forecast are coming from, and what their attributes are. They should understand what happens to that specific input source, and then what the implications are on that input.

Matt provides a visualization of lead sources and the amount of paying customers from each source. While it may seem simple, he says, "this level of insight takes quite a bit of focus, instrumentation, and time."

As data gets increasingly complex and available, so does the analysis of it. With multiple inputs, numerous sources, and hundreds of ways to analyze any given variable, AI plays a valuable role in decreasing the workload on your team. 

Benefits of AI Forecasting

As Anthony previously mentioned, Christine says that the best way to understand your forecast, and meet it, is to uncover the "why behind the what."

This means that teams must:

  • Uncover deal risks
  • Understand buyer interactions
  • Interpret sales activities
  • Analyze trends and insights
  • Measure success and create a repeatable process

To do this, Christine uses BoostUp. The insights provided by BoostUp's AI forecasting have granted the entire team at Degreed with many benefits, namely:

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What AI is Right for You?

When it comes to AI, Sharad believes there are two types, arrogant and servant.

Arrogant AI is a black box. It generates a number without fully explaining the why. It is also very autonomous, it pretends to know your data and often assumes it is clean. Further, it does not provide many benefits and does little to alleviate the work for ops or even tries to replace their judgment-making capabilities. 

Servant AI is a transparent box. It shows the metrics and calculations in an easy-to-understand way. It also takes your command and applies the metrics you care about to accomplish what you need it to. Finally, it is a servant. It automates the tiring job of data aggregation and leaves humans to make judgments.

This aggregation of data is the crux of forecasting 3.0, and gives teams the information they need to make accurate and informed decisions. In BoostUp, it looks like the image below:

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Teams should look not for the AI that takes aware their judgment, but the one that gives them the ability to focus on making better decisions. Servant AI provides us with all the data we need to make an accurate and informed decision about forecasts. 

To watch this roundtable in its entirety, click the link below.

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