For years, companies have relied on high-priced consultants to gain access to proprietary data reporting on how much competitors are paying their employees. But the fees charged by consultants to conduct salary surveys forced many businesses to depend on hearsay and hunches when negotiating wages. What’s worse, in a fast-moving economy, the data from these surveys became obsolete almost as soon as it was collected.
Compensation analytics software has changed all that. Vendors such as PayScale, IBM, Oracle and NICE Systems are offering a new breed of software by providing real-time compensation data and services. Companies can now slice and dice market survey data, employee profiles and industry benchmarks to determine how to compensate workers based on job description, experience level and geography in a highly competitive labor market.
According to John Lucker, leader of Deloitte’s advanced analytics and modeling practice, compensation analytics is “becoming increasingly important as management and HR professionals look for better ways to recruit and retain. It’s one of those areas that people are beginning to think more about and focus on. In certain domains, the talent crisis is very real. [Compensation analytics] is only going to get more significant as the demographic bubble ebbs and flows with an aging workforce.”
But while these applications promise to better reward workers, improve retention and ease labor costs, compensation analytics software as a category is much like the workforce it analyzes: subject to growing pains and ripe for training and development. That means companies implementing compensation analytics typically find value in adding their own data—on compensation, job responsibilities and required skills—to the applications to fine tune the applications for specific needs. And practitioners say that it pays to act quickly when data shows trends that are unfavorable to their needs, like when pay rates are not keeping up with market conditions.
Taking Time to Teach the System
Just ask Susan Hollingshead. Chief people and corporate services officer at Sungevity, an Oakland, Calif.-based solar energy company, Hollingshead has relied on PayScale’s compensation analytics software to reward talent since the fall of 2010. At the time, Hollingshead says “hearsay” was the only thing guiding the company’s hiring decisions as it struggled to grow its workforce from a team of 54 employees to its current size of 400. With hard-to-categorize job titles like “remote solar designer,” Hollingshead says it was challenging at first for PayScale’s software to match a job description to its limited database of job titles in order to accurately determine compensation.
Since then, though, PayScale has expanded its database to include more than 14,000 positions. What’s more, Sungevity has played an active role in feeding its compensation analytics system with industry-specific terms and carefully crafted job descriptions like “rebate and interconnection” so that the right salary ranges are linked to the most appropriate employees.
By taking the time to build out and grow its PayScale system, Hollingshead says Sungevity has been able to retain hard-to-find talent—from engineering, software programming and sales—that could have easily been poached by Silicon Valley neighbors like Google. For example, Hollingshead recently discovered that the job responsibilities of one of its teams had become significantly more complicated. Upon entering the group’s new-found duties into the PayScale system, Hollingshead learned that these employees were no longer being paid fair market value. She immediately approved a 3.5 percent salary hike – an increase that she believes prevented half the team from jumping ship.
“We had very good evidence that a new company in the Bay Area had a need for that particular highly developed skill set and were making overtures to everybody in the department,” she says. “That’s a point when you don’t want to be dealing with an annual survey. You want real-time data that tells you what’s going on out there in the market.”
In fact, to this day, Sungevity tests salary ranges for that particular group every three months based on an updated list of job duties.
Another way Hollingshead says the company has grown its compensation analytics system is by “layering on additional levels of sophistication,” such as adding employment trend and global job market data. “It’s kind of like a snap-on model where you can start with the most basic functionality and then layer on many other tools for compensation administration as you get used to the system.”
Transparent Incentives for the Sales Team
F5 Networks, a Seattle-based application delivery networking provider, also relies on compensation analytics to calculate compensation for its 1,000 salespeople worldwide. The IBM Cognos Sales Performance Management system combines data feeds from point-of-sale solutions, human resources tools and Salesforce to calculate compensation as well as “give finance a better understanding of where they’re spending their money,” says Nick Popko, F5 Networks’ senior sales compensation analyst. “Executives can see with a level of granularity how much compensation is costing the business and where the majority of that spend is.”
In turn, by logging into the system each morning, sales representatives can discover how closing a particular deal may have boosted their pay-out and how projects in the pipeline are impacting projected earnings. “The system gives reps more insight into exactly how they’re being paid so it’s not this vague notion,” says Popko.
But rather than rely on current market values to dole out compensation, F5 Networks has configured and trained its system to attribute a value or “weight” to varying products and job titles. For example, the sales of a brand-new product line that F5 Networks is trying to push into the marketplace will be given a higher weighting than one that’s being phased out. By “mixing up the weighting and applying different compensation weights for particular product groups that we’re launching, we can better drive revenue growth and gain traction,” says Popko.
The compensation adjustments can also go down. So if the company’s engineers achieve a staggering quota attainment, such as 150 percent, resulting in an off-the-charts payout, F5 Networks will go back into the system and adjust weighting so that the compensation model is more on par with other job positions.
“We’ve had a couple of instances where projected earnings showed particular reps at 700 percent attainment for the quarter,” says Popko. “That really allowed us to identify issues with our compensation plan set-up as opposed to a more theoretical account.”
Fortunately for F5 Networks, the company’s corporate bean counters aren’t the only ones satisfied with its compensation analytics system. The tool recently received a 90 percent approval rating from employees for its ease of use.
Cloud and On-Premise Systems in Play
If PayScale’s recent revenue report is any indication, compensation analytics software is well on its way to the cloud. As of October 2013, the provider of cloud-based compensation data and software added 677 new subscription customers and increased revenue by 43 percent in last 12 months. Like many of the tools populating today’s human capital management software category—a market projected to hit $11 billion in 2016 according to IDC—software as a service (SaaS) applications are delivering the kind of ease of use, affordability and fast deployment that drives adoption.
That’s not to suggest, however, that there isn’t a place for on-premise compensation analytics tools in today’s market. Vendors such as NICE Systems and IBM offer both on-premise and cloud-based models. In fact, some companies see a distinct advantage in using in-house models.
Take, F5 Networks, for example. The Seattle-based application delivery networking provider relies on an on-premise version of the IBM Cognos Sales Performance Management system to calculate its sales teams’ pay-out. “[Our on-premise] tool is a phenomenally stable system for us,” says Nick Popko, F5 Networks’ senior sales compensation analyst. Moreover, by being able to better control and customize the crunching of its data, Popko says, “the speed of calculating compensation is quicker.”
Cindy Waxer, a contributing editor who covers workforce analytics and other topics for Data Informed, 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.