Manage Forecasts with Metrics, Not Hunches
As part of CSO Insights' 2013 Sales Management Optimization (SMO) study, we asked more than 1,700 firms to identify the ultimate outcome of their forecast deals. As you can see from the chart shown here, the average win rate came in at a very lackluster 44.7 percent.
The fact that more than half of the deals sales teams confidently add to the forecast end up as losses or no decisions is causing Maalox moments not just for chief sales officers, but for chief financial officers and chief executive officers as well. How can you manage your business when you have such poor visibility into what customers will be buying?
A clue to why many companies have major issues regarding forecast accuracy surfaced in the 2013 SMO data. The most common tools sales managers are using to manage their forecasts are spreadsheets and their core CRM systems, neither of which offer the analytics needed to generate metrics that sales managers need to effectively manage their teams.
To deal with this challenge, more firms are turning to two types of CRM 2.0 applications. The first, which is helping sales management make better choices at the beginning of the sales process, is big data platforms. Solution providers such as Birst, Lattice Engines, PROS, and Vendavo can pull data from a variety of internal, and in some cases external, systems.
They analyze the information, looking for key metrics that help predict the profile of a high-quality opportunity. Big data analysis may find that there are certain industries you are more effective at selling to than others, that you relate better to certain types of stakeholders, that you solve certain problems more effectively than others, etc.
Based on these insights, marketing can do a more effective job of interest generation by developing campaigns that target prospects that fit the profile. They can also more precisely score leads as they come in to determine if they are "sales ready." In addition, once the leads are passed on to sales and qualified, sales managers can more effectively coach their salespeople on if and how to pursue the opportunity based on the big data analysis.
What is often seen in benchmarking these types of sales effectiveness initiatives is that there is an initial drop in the size of the pipeline. While that may sound bad, what is actually happening is that sales teams are dropping low probability deals, leaving them more time to work on the higher probability accounts.
Another technology that is helping sales management is sales analytics applications. Solution developers such as C9, Collective[i], and InsightSquared have created applications that integrate directly with a customer's CRM system. They provide sales managers with forecast management dashboards, which generate deeper insights into the status of each forecast deal than they can get from CRM systems alone.
Leveraging these insights, managers don't just have to rely on a gut feel for how each deal in the forecast is doing. Instead, the sales analytics applications constantly monitor and assess the health of each deal. Managers are then provided with real-time metrics that can identify which reps need what type of help on what forecast deals, and then take proactive action to get at-risk deals back on track.
So what is the "size of the prize" for effectively prioritizing which accounts to pursue, and then proactively coaching sales teams on how best to engage customers throughout the sell cycle? In doing an analysis of the 2013 SMO study data, we found that sales organizations that exceeded expectations at these two aspects of sales management won 55.6 percent of the deals they forecast, nearly a 10 percent jump in close rates versus the study average.
By bringing more science to the art of selling, CRM 2.0 solutions can take a lot of the guesswork out of forecast management. In doing so they are generating significant ROIs resulting from often double-digit increases in win rates, which at the end of the day is what selling is all about.
Jim Dickie is a partner with CSO Insights, a research firm that specializes in benchmarking CRM and sales effectiveness initiatives. He can be reached at email@example.com.
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