Sales forecast accuracy is a chronic issue in most organizations. In a 2019 Gartner survey, 296 sales operations leaders were asked to identify their top 3 areas where they are least effective. Pipeline management and forecasting were among the most common responses. Despite the self-awareness, the resolution seems to be elusive for many sales organizations.
CSOs, along with their heads of sales operations, may recognize these 5 common contributors to forecast accuracy issues:
1 – Lack of Training for Managers
Forecasting is a significant responsibility for most front-line and second-line sales managers. Yet, too few sales organizations train their managers on how to forecast appropriately. Moreover, new sales managers often come from roles without a forecasting mandate. Or, they may come from another industry where forecasting is quite different.
CSOs must partner with sales operations and sales enablement leaders to establish a manager onboarding and continued development in forecasting and data literacy.
2 – Failure to Change/ Adapt
There are many ways to forecast sales results. Some rely on the classic sales funnel stages, while others may use propensity modeling or extrapolated longitudinal trends. Leaders must acknowledge when their methodology is no longer working (or perhaps has never worked).
Related, many CSOs recognize that forecast accuracy issues are partially a symptom of an outdated sales process. Traditionally, sales processes are designed sequentially. Yet, most B2B buying journeys are nonlinear. As a precursor to fixing forecasts, sales processes may need to be redesigned. Then, sellers must be trained to manage opportunities using customer verifiers to track progress through the buying journey.
3 – Over-reliance on Intuition over Data-driven Decision Making
Frequently, there are enough opportunities and data points for sales organizations to leverage advanced analytics and data-driven decision-making. However, we still see most organizations leverage manager judgment to either set or at least “refine” the forecast. People – all people – have a history of making bad judgments. As an aside, I encourage you to read Noise by Daniel Kahneman, Olivier Sibony, and Cass Sunstein. It’s a great book that explores why people make bad judgments and how to make better ones.
While process orientation improves forecast accuracy and transparency, significant gains require data-driven decision-making, specifically using advanced technologies with artificial intelligence.
4 – Inconsistent Discounting or Price Realization
Clearly, it can be hard to know if and when a deal will close. It’s even tougher when the realized prices vary greatly across deals, even for the same product or service. Forecasts must consider:
- Probability of winning
- Approximation of close-date
- Scope and volume of products and services
- Price realization
Process, data, and technology all improve price realization. The process should include deliberate and clear guidance on distributed decision rights related to discounting. Data, especially linked to win/low reviews, help identify when discounts should occur and by how much. Finally, technology – like Configure, Price, Quota (CPQ) platforms improve pricing and forecasting.
5 – Culture of Business Reviews and Forecasting
Two common dynamics stem from the CSO that may need to change.
- First, there is the CSO that prioritizes beating the forecast over forecast accuracy. This is the tale of under-promise and over-deliver. The belief is that it’s better to guide down and beat the estimate as opposed to try to be accurate and miss it (even if just by a little). CSOs should talk to their CFOs to see how finance appreciates a big miss, even if it’s on the plus side. Most CFOs favor accuracy and predictability.
- Second, I’ve heard stories about CSOs that will berate sales managers for being below plan. The learned behavior is to forecast at plan until the last moment where the forecast drops. One sales manager has said to me, “If I’m going to get yelled at, better once at the end of the quarter as opposed to every week that I know I’m going to miss.”
CSOs must be conscious to establish a culture of transparency with a priority on forecast accuracy. Clearly, there are a few things wrong with these examples but to keep it brief, I’m only focusing on the impacts on sales forecasts.
Fixing sales forecasts won’t be easy but there are plenty of opportunities to make incremental, and sometimes better than incremental, improvements. Start by resolving any (and all) of these 5 issues that impact your ability to forecast more accurately.