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The Future of Work

A New Tool Helps Tackle Tricky Salary Negotiations

Big-data platform Paysa provides market insight to ease the often awkward, sometimes emotional, conversations about compensation.

[Photo: Flickr user Kevin Doncaster]

Employees are usually in the dark about salaries other than their own. Even discussions with close friends and family members can get a little squirrely when paychecks are brought up. But it's tough to effectively negotiate either a raise or a new compensation package without really knowing what other people are earning. So it’s no surprise that Chris Bolte, cofounder/CEO of Paysa, says that the spark for the new platform that provides market salary data was literally to shed light on a shadowy aspect of the workplace.

"I’ve worked in small companies and big companies, interviewed thousands and hired hundreds of people," Bolte tells Fast Company. "It’s been fascinating [to see] how all over the map people are in terms of their compensation." The goal for Paysa was simple, he says. "We wanted to figure out how to help people better understand what their value is in the market, at least to enable them to have a more balanced, data-driven conversation with either a current or future employer."

Paysa’s platform is designed to do just that. Plug in details such as job title, years of experience, company, location, education level, and skill set, and Paysa’s analytics will give you a comprehensive picture of what your worth is in the market.

Of course Paysa isn't the first company to offer this kind of info. They are entering a space dominated by the likes of larger, established players such as Payscale, Glassdoor, and Salary.com, among others. Each draws from a different data pool like the Bureau of Labor Statistics or from existing and former employee reporting. This has limitations, according to Bolte, because it's usually only gathering information on specific companies, locations, or job titles. A resulting search could therefore generate a salary report based on professionals who are similar to the searcher, but earning a very different salary. Why? Because they might be doing some of the same work, but have a whole different skill set, or come from a different educational background.

Bolte says even companies trying to set salary "bands" for groups of employees at specific levels could be at a disadvantage from a data standpoint. For example, Walmart and Google are very different, but both employ software engineers.

Paysa’s founding team are all veterans of the ad tech industry where Bolte says extremely refined personalization reigns supreme. "What we are exceptionally good at is bringing large data sets," he explains, and distilling them to a specific profile. "Now it’s the same thinking, but applying it to the individual," says Bolte.

Millions Of Points Of Data

For example, Bolte says, "Payscale really looks at three things: job, title, and education." He notes that Paysa’s data sets mine 30 million salary points and 90 million career profiles, and break that down to 10,000 variables so that every skill is assigned a value. "You can go as deep as you want," he says. In comparison, Payscale only allows users to select three skills in their searches.

The way it works is that a user can quantify the incremental value of mastering certain skills such as a programming language, or check to see if a graduate degree from a private university will allow them to collect a bigger paycheck than if they earned the same degree at a state school. Even with the same job title at the same company, these two variables could mean a dollar difference in their salaries. Paysa also provides data on other aspects of compensation, such as equity or signing bonuses.

Right now, Paysa is only going deep for software, data science, and IT jobs. The company just came out of a private beta test phase with about 2,000 users and raised $4 million in seed funding. Bolte says that while there is no data on whether these early users went on to negotiate better compensation packages, "They spent quite a bit of time understanding what the drivers were around their own compensation, and what sort of jobs are out there that would match their skills and provide them with the compensation that was fair market value for them."

He says Paysa will expand to include other industries soon, but has no plans to change its revenue model, keeping the platform free to use. "Our focus has been just on a consumer-based business," he says. "But in the next year or so, we have plans where we can get referrals based on jobs or skills, and there are a lot of ways to make that happen, whether it’s online learning or Udacity or Lynda.com, which LinkedIn just bought."

Bottom line, Bolte and company just want to make navigating the often-awkward salary negotiation a bit easier. "It’s very emotional," he contends. "[Paysa] level sets them and gives them real information they can trust."

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