For years, organizations have lived by the credo that the more carrots you dangle in front of a sales team, the more products and services they’ll be incented to sell. So you can imagine GlobalEnglish’s surprise when the California-based maker of English language learning software for enterprises actually lowered its annual compensation spend by four percentage points only to witness its sales reps’ revenues increase nearly 10 percent.
“As long as your salespeople are being well compensated, a company’s [compensation plan] can still be cost effective,” says Inga Pedersen, GlobalEnglish’s director of sales operations.
It’s a number-crunching approach to compensation only recently made possible by today’s data-driven compensation software programs. Compensation planning tools have been around for decades, helping companies calculate salaries and bonuses with paper-based ledgers and Excel spreadsheets. But data analytics is breathing new life into this age-old practice by converting staid tracking tools into powerful predictive models.
Rather than compare salaries against industry benchmarks, these suites, from vendors including Xactly, SumTotal Systems and Workday, gather information on everything from revenue per sales rep to percentage hikes in compensation plans. Computer models are then populated with this data. Next, using sophisticated algorithms, these models spit out predictions such as the exact percentage of pay hike needed to dissuade a top performer from quitting, the impact of compensation reductions on employee productivity and the consequences of changes in compensation plans.
“Being able to leverage a lot of the key data across a business is not only driving performance but better enabling organizations to target their [compensation] spend,” says Stacey Cadigan, global talent solutions leader at Aon Hewitt, a human resources consultancy.
For example, GlobalEnglish once ran a double-pay incentive program that rewarded both members of a two-person sales team a 100-percent closing credit and a 100-percent commission fee for every sale made on a particular enterprise product. However, using Xactly Incent helped Pedersen “come to the conclusion that the program wasn’t worth” the expense.
“Every year we look at how much we paid out [in compensation] on new business earned, how much we paid out on enterprise sales, how much we paid out on bonuses – any granular level that we want,” says Pedersen. “Salespeople want to make money but, from a financial perspective, you also want to control costs so there’s a balance. Every year we see what works and what we’re going to change.”
In addition to crunching historical compensation data, compensation software lets GlobalEnglish model and simulate the financial impact of salary and compensation plans. For example, a user can change a two-week incentive plan for junior sales reps into a year-long incentive strategy for sales managers and test how such a tweak will influence sales and productivity levels compared to previous months.
“We can make business decisions on whether it makes financial sense to run a certain kind of incentive,” says Medha Gerhardt, GlobalEnglish’s senior sales operations analyst, noting that the company experiments with everything from commission structures to the length of an incentive plan.
New Tools Require Integration with Sales Force Management, CRM Systems
Despite its evolution from spreadsheet days, compensation management is hardly a flip-the-switch kind of technology. For one, it needs to be integrated with other data sources such as customer relationship management and salesforce automation systems to be truly effective. In the case of GlobalEnglish, sales reps can log into Xactly Incent via Salesforce.com to see where they stand in terms of bonuses and how sealing a particular deal might impact their commission. Without this strategic integration and real-time visibility, sales reps would be kept guessing about their potential compensation earnings.
“The ability to analyze and consolidate all the data across the enterprise is definitely key to offering sales professionals better insight and accountability,” says Cadigan of Aon Hewitt. “[Companies] need to start to care more about integration than just pure functionality.”
Another roadblock to optimizing the value of compensation management software is knowing what to do with the data. According to a recent study of 560 organizations by the nonprofit HR association WorldatWork and Mercer, 95 percent of compensation professionals use benchmarking to make pay decisions, while only 43 percent rely on more sophisticated techniques such as predictive modeling despite the widespread availability of this technology.
“If I look at leveraging data and making strategic decisions, I’d say the vast majority of companies are still at the 101 level,” says Shawn Rossi, a sales performance principal at management consulting firm Mercer. “There are some early adopters, like software companies, but the next emerging opportunity is to maximize the ROI of these solutions.”
The problem, says Rossi, is that many companies “try to boil the ocean and get reports for every stakeholder instead of focusing on what questions you’re trying to answer.” For instance, rather than generate hundreds of reports on what every single sales rep in the company stands to earn in commission in the next three months, Rossi says companies would gain “more incremental value” from focusing on a single demographic, such as top performers, or modeling a selection of incentive plans.
Compensation management software can also present a steep learning curve. That’s because today’s systems require users to come up with sophisticated rules or formulas to calculate different incentive rates for varying products, geographies and sales divisions. For this reason, GlobalEnglish relies on a systems integrator to help with custom coding and to generate the right rules. “In order to create compensation plans, there are a lot of rules to be written and lots of ins and outs,” says Pedersen. In the end, though, she says, “It’s worth it to pay that extra money.”
Cindy Waxer is a Toronto-based freelance journalist and a contributor to publications including The Economist and MIT Technology Review. She can be reached at firstname.lastname@example.org or via Twitter @Cwaxer.