Analytics & Smart Compensation: Expanding the Sales Manager’s Toolkit
The old saw states that a poor workman blames his tools. These days, it could also be said that a successful sales manager credits his tools for guiding his success.
But, to use the tools available to them, sales managers. Manual systems for managing commissions and other sales processes don’t capture data in a form that allows fast analysis. These systems act as repositories of historical data about sales. This gives sales managers unprecedented visibility into sales behaviors; combining that data with next-generation analytics results in the tools that can make sales managers more successful through improved motivation techniques, comp plans more focused on business priorities, and more precise and effective coaching.
Analytics is helping to identify sales behaviors that help close deals today and set the stage for additional sales in the future, giving sales managers more levers to pull to make their teams more successful. Next-generation analytics platforms are making it easier for managers to do this analysis themselves through simplified interfaces and correlate data sets from various sales systems beyond compensation management, including configure price quote (CPQ), sales enablement, contract lifecycle management (CLM), and training solutions. Access to these data—and to tools that enable managers to find insight in them—can fundamentally change the way sales teams are incentivized and managed.
For example, a detailed examination of the data allowed California-based Sunrun, the largest dedicated residential solar company in the United States, to uncover areas for improvement in how its sales is motivated. “[Our] biggest shift in approach in recent years has been related to sales vs. realized sales,” said Joe Miller, senior manager, compensation at Sunrun. “In our business, we have a lengthy time between initial sale agreement and the product being installed—two to three months on average. But sometimes it can take nearly a year, and cancellations often occur after the initial sale agreement.”
Wringing those cancellations out was critical in translating closed deals into real revenues. “In our prior plans, we heavily incentivized the initial sale agreement volumes, which drove a lot of ‘bad behavior’ of signing up customers that had a high propensity to cancel,” Miller said. “This not only incentivized the wrong behavior but took up time across the entire organization for sales that didn’t provide any benefit to the company. We have since moved the incentives, and the differentiator between top performers and low performers, to installed activity and realized sales.”
Major shifts in motivation like Sunrun’s require careful examination of the data and an educated prediction of how those changes will affect results—especially since comp plan managers only have so many opportunities to use comp to influence behavior.
“Three is about the right amount of behaviors to incentivize with monetary compensation at the ‘front line,’” Miller said. “Too many behaviors will cause a lack of focus on the important behaviors and will most likely create a less-than-stellar experience for the customer. The higher in the organization structure you go, the more you can add, but five would be about the max before it becomes unfocused and unbalanced.”
Attempting to use commissions payments to motivate too many behaviors may also have the exact opposite impact of what managers intend. “If a plan is not easily understood, then sales will not be able to give it the proper amount of consideration while they conduct their selling process,” Miller said. “Instead of the clear this-for-that, action equals outcome, sales will instead look at their plan as a surprise bonus—‘I guess you’ll pay me whatever you pay me.’ That doesn’t help achieve any of the desired goals.”
This need to keep compensation simple runs head on into the many revelations that come out of increasingly powerful analysis, which can reveal several layers of sales behaviors that managers may want to encourage, reinforce, or change. This requires managers to add their expertise to what the data reveals and to prioritize behaviors based on their impact on sales, revenue, margin, or any other goals set by the organization.
That doesn’t mean that the behaviors that don’t crack the top of the priority list must be ignored. Modern incentives can go beyond the commission check to less formal systems of motivation driven by gamification technology. This can be a formal part of the comp plan or a technique employed to tackle tactical, short-term issues.
While gamification is often thought of in almost light-hearted terms—think leader boards, virtual trophies and badges—the ideas behind it can be used to drive competition around serious aspects of the selling process.
“Something we have done that is more of a behind-the-scenes gamification is a more thoughtful approach on who gets opportunities,” said Miller. “If you want more opportunities, you need to convert the opportunities you have received. Opportunities are a costly piece to our business and we do not want to continue to give these to [salespeople] that do not convert them.”
The ability to use data to mold the comp plan to business objectives and to better understand sales priorities are powerful on their own. But data gives managers one more important new tool in his or her arsenal: the ability to use data as a motivating tool.
“We use data to shine a light on those that are successful in delivering on the goals and expectations we have set,” said Miller. “Oftentimes when we ‘raise the bar,’ many have the initial reaction that the bar is set too high and it can’t be done. By showing those that aren’t achieving it those that are achieving it, they begin to shift from an ‘it can’t be done’ attitude. Giving underperformers multiple examples of what can be done and those who are doing it can be a resource for them to emulate.”
The next step is predictive analytics, which draws upon the data within Commissions and other systems to project future results down to the level of the individual salesperson. In this scenario, the sales manager has the ability to challenge salespeople about their future performance—“the data says you’ll do this, but I think you can do better than that with some coaching and training.” Predictive analytics will help in other areas as well—such as in establishing the most effective sales territories—and do so in a way that results in fewer manager-salesperson conflicts, since decisions are based on data, not on managers’ assumptions.
Analytics can also help with sales talent retention by revealing which salespeople show a pattern consistent with behavior that precedes a departure from the business. It can reveal how effective training and coaching initiatives are—not on a macro level but on a more granular level, something critically important for businesses with long sales cycles. And it can expose which sales content is working and which content is simply taking up space in the enablement system.
The sales manager’s toolkit has more effective tools, and more of them, than ever before—but, without a software infrastructure to capture data and analytical tools to give managers insight into how to use that data, many of these tools are going unused. With analytics and the smart use of compensation, sales managers can fine-tune sales behaviors, drive better results, and make changes with greater certainty of success.
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