Niels Bohr, the physics Nobel Prize laureate, is quoted as saying, “Prediction is very difficult, especially if it’s about the future!” While there is some dispute to the Danish origin of the quote, there is no dispute that forecasting is a challenge. Add in increased accountability to those numbers from other business stakeholders, so they can deliver on their commitments, and you’ve got a forecasting nightmare that impedes business growth. However, advanced digital technology is helping address the challenge. Tools can bring the power of artificial intelligence (AI) and machine learning (ML) to improve forecasting.

As it turns out, sales leaders can use some help. Varicent just completed a survey of 300 sales leaders and found that only 21% are satisfied with the success of their sales forecasts. According to the survey results, sales forecasting success requires:

1. Revenue intelligence tools
2. Sales forecasting experience
3. A business structure focused on a large number of small transaction and services offerings

Among the 20% of the respondents who use revenue intelligence tools, 47% are satisfied with their sales forecast, which is more than 2X the satisfaction rate of the broader sample.

Longer tenured sales leaders also have greater sales forecasting success. Nearly two-thirds of the sales leaders who responded to the survey have been in their role for more than two years. These more experienced sales leaders have an above average 24% sales forecasting satisfaction rate. By contrast, sales leaders who have been in their role for less than 12 months have half the satisfaction rate—only 12%—as their more experienced colleagues.

Sales leaders learn that their career success is, in part, determined by their ability to manage sales volumes with certainty. Conversely, sales forecasting success creates assurance with senior leaders that the business is under control, further contributing to sales leadership tenure with longer time in role. It works both ways. Longer tenure contributes to sales forecasting success, and sales forecasting success contributes to longer tenure.

Successful sales forecasting is also a function of the business situation sales leaders find themselves in—the hand they are dealt. Businesses that have large volumes of small transactions, with lots of high-volume data, offer an easier forecasting challenge. Similarly, businesses that are more services oriented, with service contracts covering extending periods, are also easier to forecast. Unfortunately, most businesses are more complex with smaller volumes of larger transactions and product sales that reoccur, irregularly, each quarter. As a result, the use of more advanced analytics is needed to paint a more accurate picture of the future.

As we take a closer look at a subset of survey respondents who face the greatest challenges, we can see that those in the technology and life sciences industries—40% of total—have a sales forecasting satisfaction rate of only 13%. By contrast, manufacturing industry respondents have a satisfaction rate of 33%. Further, those in large (500 or more employees) technology and life sciences firms have only single digit satisfaction—6%.

Sales forecasting in these technology-related industries is a much greater challenge than elsewhere because transactions are larger, more product oriented, focused on expansion revenue, and targeting new logo clients. To address such challenges, these technology-related firms have very high usage of CRM and BI tools and above average usage of revenue intelligence tools. Nonetheless, it is the use of advanced analytics that leads to success. Even in these very difficult to forecast businesses, the 19% of the respondents using predictive analytics tools have a 39% satisfaction rate—3X the industry average—and the 16% of respondents using prescriptive analytics tools have a 47% satisfaction rate. So, with enough analytics skill and the use of AI and ML tools, success is possible, even in these difficult to forecast situations.

Increasingly, products like Varicent’s Symon.AI will improve AI and ML tool ease– of– use, enable more effective data integration, and provide much greater success for today’s sales leaders. Dive deeper into the survey results to see how your sales forecasting and analytics tools and processes stack up against your peers in The State of Revenue Forecasting eBook.