Sales Forecast Accuracy: The Holy Grail

It has been widely quoted that 79% of sales organisations regularly miss their revenue targets by more than 10%.   In this first part of a three-part series, we’ll discuss what needs to be done to improve forecasting, and in the second and third parts, we will outline how to achieve it.

For sales leaders today, there are generally two elements to consider when creating a sales forecast. There’s the “science” - using data to create mathematical or AI models, for example, and the “art” - knowing what questions to ask to understand whether a forecast could be met or not.

The best forecasts, of course, apply both art and science. Mathematical models provide a foundation or starting point, and AI models today offer a benchmark value against which to compare your analysis. That foundation, however, will begin to crumble if it isn’t paired with intimate knowledge of both the deals you’re making and the people that will be buying from you.

It’s the marriage of art and science that helps to create accurate forecasts.

Many (many) years ago, when supply chain management was getting started, we addressed this issue by using mathematical approaches to get a baseline (the “turn” business) and then applying human insight to handle the one-time deals (spikes).

The turn business typically represented many small deals that, when aggregated, showed a repeatable pattern. Having historical data was important. New product introductions were forecasted by comparing an existing product to the new product and using that forecast (unless proven otherwise).

This baseline was often highly predictable. The spikes were more complex to predict and carried a higher risk. The forecast was simply the sum of both the turn business and the spikes.

Getting the forecast right was critical in any business, but especially in an environment like manufacturing. Raw material or component procurement and equipment scheduling were dependent on accurate forecasts to meet demand. An inaccurate forecast could result in losing customers due to not having enough resources to fulfil a deal, or wasted money on resources that never end up being used.

In today’s world, much of what we sell (software, in particular) doesn’t depend on physical constraints, except concerning application quality and availability. While experienced salespeople can “sell sand at the beach”, most companies do not have the luxury or the budget for an entire team of elite performers. Therefore, we require a straightforward approach that is easy to manage and consistently executed.

To generate accurate forecasts, there are five critical elements we need to master:

• Documented Sales Process – the sales process informs us of our current deal status, with every stage documented to ensure we have a clear picture of exactly where the deal is in the cycle.
  
  
• Utilised Sales Methodology – a robust sales methodology provides a consistent framework that every deal can be aligned with for consistent execution
  
  
• Deal Reviews – sitting down and reviewing the status of your deals is an important sanity check, offering the opportunity to zoom out and realistically assess the progress of your deals and determine how likely they are to move forwards
  
  
• Management Cadence – implementing a consistent cadence of meetings between sellers and sales managers helps outline how our pipelines and forecast revenues should be developed, keeping everyone on the same page
  
  
• Accurate and Adaptable Analytics – analytics enable us to cut through the noise and ensure that we’re on the right track, but only as long as the data we use is both accurate and adaptable

Over the next two posts, we will cover each of these elements in more detail.  In the meantime, I encourage you to review how effectively your business has been applying each of these five approaches over the past 12 months.