The Data-Driven Approach to Sales Compensation Design

“We’re in a new world now. There is now academic data based on scientifically tested sales drivers.”

For most organizations, a significant portion of revenue goes to sales compensation. Leaders want to inspire their people to sell product, meet objectives, and hit deadlines. They want them to succeed and to come in the next day and do it again. Yet most companies have little insight into what works and what doesn’t.

“They have a terrible perspective into what’s going on,” says Erik Charles, M.B.A., vice president and solutions evangelist at Xactly Corp. “Eighty percent of them are still writing sales compensation as a spreadsheet, but no one’s actually looking at the calculator to see if it’s working.”

Charles is one of the guest lecturers on the Sales Operations Science certificate course. He takes sales professionals through the practical considerations of designing an effective sales compensation plan and working with them on tactical strategies that impact the business. You need to study the numbers, measure what works, and monitor effectiveness over time.

“We’re in a new world now,” Charles says. “There is now academic data based on scientifically tested sales drivers. A scientific mindset to it is very important to understand the impact of what you’re doing.”

Charles cites numerous drivers for data-based design. Everybody loves a SPIF (sales performance incentive fund), but most people don’t do the hard work of coming back and determining: does it have an impact? Will we make more money?

“We have this ability to apply more and more science to the world of the sales profession and really see what’s going on,” Charles says. “We’re inundated with data, but, if it’s managed right in the right systems, it can give us a preview of what’s just beyond the horizon.”

Stemming Turnover

There are about 50 factors that contribute to a sales rep quitting. It could be pay, or pay in comparison with the team, with peers in the company, in the marketplace. But, it could also be challenges in a territory, in job requirements.

“When you start bringing it all together, you can start predicting who’s updating their LinkedIn profile,” Charles says.

And, the 80-20 rule is real. Eighty percent of the revenue is brought in by 20 percent of the team.

“That’s why you better pay true market rate for the top performers. What accelerators do you put into the plan? You can’t know that without being a data-driven sales executive.”

Sales Goals vs. Corporate Goals

You want to be sure you have clear expectations and goals, that corporate and sales goals are in alignment.

“If the sales incentive plan is to sell more stuff, then you’re not connected,” Charles says. An effective sales comp plan will communicate corporate goals such as pushing more high-margin products without losing sustaining customers. “You may want to implement a two-factor incentive plan.”

Another organization experienced higher costs associated with sales that occurred later in the month so they incentivized sales reps to bring in sales revenue earlier to make more of a profit on each deal.

You could even go ahead and add a third actor, Charles says. But, not a fourth measure. To hit all your measures, you need people to be focused to get it all done. When you add more than three measures into an incentive plan, performance drops.

Activity-Based Payments

The data also tells the story behind small incentives to get paperwork done. Who wants to log their call reports? Nobody in sales certainly. So, how important is it and how do you incentivize sales professionals to get it done?

One company put small incentives behind logging call reports and saw a 4 percent improvement in the completion of that activity. Even more significant was the company experienced an 8 percent uptick in revenue as a result of that incentive.

Clearly it was important for the company to pay for the call logs to get done.

“It’s just basic algebra, but it’s amazing how many companies don’t do it.”

For the Love of Data

Charles fell in love with Excel 1.0 back in the 80s. He had been one of the first to computerize risk quotes for an insurance agency, which, until that point, had been running calculations on paper. It was a big deal back then and made a difference.

“I started realizing what you could do with data sets,” Charles says. “I hate calculators. I wanted to see the data and run the relationships, find correlations and patterns.”

He jumped to a management consulting firm that happened to focus on incentive compensation and started designing incentive plans for some of the biggest corporations in the world. In mergers and acquisitions, his role has been to make sure top sales people were retained.

“This kind of science can be applied to any size firm,” Charles says. “There’s no reason to assume that what General Electric does couldn’t be done by anyone selling products on Main Street.”

UCSC Extension Applied Business Science Program

The Applied Business Science series is a new UCSC Silicon Valley Extension partnership with GreenFig, a market-driven education company that delivers innovative programs to prepare learners for the demands of today’s economy.

Leave a Reply