PayScale: Bringing data to compensation

PayScale combines crowdsourced data and analytics to develop market insights and bring clarity to employee compensation for both consumers and businesses in a “B2B2C” model.

PayScale is the largest salary database in the world, utilizing a “B2B2C” model to create and capture value for consumers and businesses. PayScale has effectively developed a two-sided marketplace utilizing crowdsourcing to develop a comprehensive analysis of salaries across a variety of jobs and occupations. They help consumers understand how much they are worth at no cost, and help businesses identify how much they should be paying their employees for a cloud-based subscription service. Through its disruptive crowdsourced data-collection model, PayScale has made compensation insights widely available. This is a stark contrast to the status quo just a few years ago, where traditionally these insights were only determined via third-party consultants hired by companies to better understand what they should be paying their workers.

 

How PayScale serves consumers

PayScale offers consumers accurate compensation benchmarks to answer the question, “What am I worth?” When a new user decides to use the platform, they complete a survey asking for detailed professional information including level of education, past and current employment, compensation, location, etc. PayScale then uses this data to add to existing database of over 54M individual salary profiles, as well as to provide the user with an assessment of how their compensation stacks up against industry norms. While this basic service is free to consumers, PayScale also offers more premium features such as a Career Path Explorer, where users can see what career path opportunities are available to them based on what others have done, and other services such as a negotiations guides, reports on the ROI of education, and other resources to help consumers understand how to make better compensation decisions.

 

How PayScale serves businesses

For businesses, PayScale provides a subscription-based SaaS offering allowing companies to benchmark their own compensation packages against the market data which PayScale has collected from its users, breaking away from the traditional use of consultants to gather this data, which could take 6-12 months and lead to lagged data. PayScale’s model offers the benefits of up-to-date data refreshed frequently, coupled with the ability to spot trends for specific industries or positions. PayScale charges businesses for its SaaS offering products though exact prices are not public and likely vary company to company. PayScale state they have over 3500 customers including companies like Zappos, H&M, Warby Parker, and Bloomberg.

 

Data collection methodology

As mentioned previously, PayScale’s data is all user-generated by consumers seeking compensation benchmarking. However, PayScale also vets the data through a multi-step process to ensure its accuracy. They remove any obvious outliers and also checks against the volume of data coming from any one individual to weed out fake entries. Additionally, PayScale has also developed technology to help standardize titles and ensure accurate matching, e.g. understanding that “programmer” and “developer” likely refer to the same type of job. Given the scale of data they have collected over time, they are able to continuously iterate this process as well to ensure all incoming data meets expectations.

 

Using data beyond compensation benchmarking

PayScale has been able to utilize its data to develop broader insights around the marketplace beyond standard compensation comparisons. Most recently, PayScale has been featured across multiple popular media sites for its report around pay gaps between men and women. They have also developed a series of assessments around the ROI of different colleges, majors, and career paths based on information that has been collected from users. PayScale’s breadth of geographic information has also allowed them to develop insights around location-specific trends and pay variations, and they have been able to utilize predictive analytics to fill in gaps for specific compensation scenarios they may not actually have real data on (e.g. “How much should a computer programmer with six years of experience based in Ames, Iowa make?”). Through their collection of data, PayScale has found a way to remain relevant in the broader employment space and also maintain its positioning and branding as the leader of compensation insights and analysis.

 

Is the model sustainable?

Despite being anonymous, salary data is one of the more personal data points we have about ourselves. This potentially limits what PayScale can reasonably acquire from users. For example, how many of us at HBS would be willing to go through the process of contributing salary information to PayScale? Furthermore, given user-generated data, there is always the concern around quality perception. Even though PayScale claims to conduct accuracy tests, a simple Google search will yield pages of results of posts by skeptical consumers citing whether sites like PayScale, Glassdoor, and others can be trusted. The user-generated data point leads to other concerns around data concentration around specific industries. It’s likely much more difficult to properly assess complicated offers, such as an financial services or investment management, executive compensation, or start-up compensation schemes, which have many more components beyond simple base salary and annual bonus.

Additionally, when evaluating PayScale’s revenue sources, they largely make money by selling their data to businesses. If salary data becomes more transparent through other sources or if penetration starts to saturate, where does PayScale go next? Their publications on broader, market-wide concerns such as gender pay gaps is a way to maintain relevancy, but as companies such as LinkedIn become more expansive in the recruiting space, there is potential for them to build up a similar compensation data base over time as well and distribute to a much larger, more global consumer base (LinkedIn recently announced 400M users globally).

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Student comments on PayScale: Bringing data to compensation

  1. Interesting! A significant portion of the graduating HBS class gives HBS data on its compensation, but I wonder how many would be willing to give that up to an entity with which they have little to no affiliation. However, I think/hope there’s a general trend towards greater transparency in compensation, hopefully this will help. An example, Buffer follows ‘radical transparency’ and makes all salaries public as well as their equity formula, revenue, fundraising details, and on and on: https://buffer.com/transparency

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