A more accurate sales forecast means more money in your pocket. According to just-published report, “Better Sales Forecasting Through Process and Technology,” authored by Peter Ostrow, a vice president and group director at research technology firm Aberdeen Group, best-in-class companies averaged 17.8 percent year-over-year revenue growth using sales forecasting technologies, when compared with industry average companies, at 8.4 percent growth, and laggard companies, which only experienced 0.2 percent growth.
Out of the 144 end-user organizations that Aberdeen surveyed about sales forecasting effectiveness, best-in-class companies shared some of these attributes: 81 percent use performance dashboards to track goal vs. actual sales data; 78 percent have a formal definition of progressive sales stages to weigh sales forecasts; and 75 percent add external social media content to the forecasting process.
When respondents were asked what the greatest barrier to accurate sales pipeline predictions was, it had a lot to do with data. The top challenge was insufficiently entering data and information into their CRM system. While most of the sales organizations reported using CRM systems to track current opportunities in their pipeline, the best performers used those historical benchmarks to increasingly factor in additional weighting measures, and had also come up with formal definitions for sales stage progression, ie. prospect, opportunity, etc.
According to Dublin-based Nimble Apps, a publisher of online professional software, sales teams are far too optimistic when it comes to their pipelines. After studying 144,817 closed opportunities with sales cycles of 75 to 250 days over the course of five years, it was found that on average, it takes 22 percent longer for sales teams to win an opportunity than originally expected.
In order to improve sales forecast accuracy, managers must be able to leverage historical data found in their CRM to develop a more accurate forecast. But, as the Aberdeen report points out, best-in-class companies are also looking to external social data and its effects on the forecast process, which, relatively speaking, is still an emergent area for sales organizations.
“Using the data generated by social media to refine sales forecasts is enticing,” comments Nimble Apps CEO Thomas Oriol. “It is also very difficult in the context of B2B dialogues, where understatements can be as valuable as raw content. We are exploring selected ways to use social media traffic for forecasting purposes, but we think there are lower hanging fruits, like the historical data already stored in CRM software.”
In order for B2B companies to produce more accurate sales forecasts, Nimble Apps says it’s important to focus on the right sales performance indicators and to identify meaningful early warning signs. It’s also key to measure your pipeline dynamic, the company says, by determining pipeline stage durations and closing probabilities by pipeline stage, in addition to calculating your daily closing rate. Likewise, Aberdeen noted that it’s important to provide leaders in marketing, service, supply chain, human resources, and other lines-of-business with access to data and information surrounding the sales forecast.