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The State of Salary Data Usage in 2018 (New Research)

With competition for top talent more feverish than it has been in recent memory, organizations are revamping their compensation plans to ensure that they’re able to bring in and retain top talent. They’re turning to new salary data sources to help them gain an edge. In light of these dynamics, we decided to conduct new research to explore how the compensation survey landscape is shifting. This blog post features key findings from this research.

To get the full details, download our new whitepaper The Salary Data Brief: How the Compensation Survey Landscape is Shifting in 2018

Getting pay “Right” is getting harder

The job market in the U.S. has been very hot for the past four years. Unemployment rates are at a historical low point. Experienced workers in many professions are often interviewing with and receiving offers from multiple companies. Counteroffers are becoming more common and offer acceptance rates are declining.

In 2018, paying workers competitively is an essential part of acquiring and retaining talent. But getting pay right has become especially challenging for several reasons:

  • For one, organizations’ hiring needs are evolving rapidly; they need to price new jobs that are often hard to find survey data for.
  • Certain jobs are highly volatile in the market. Here at PayScale, we see that workers who have particular skills (e.g. the programming language Go for software engineers) are commanding double-digit pay boosts, and this isn’t just true for those in the tech sector.
  • The market rate for particular skills can swing wildly from year to year. For example, Algorithm Development was the top skill for data scientists — one that gave workers the greatest pay boost — back in the beginning Q3 2017. Twelve months later, this skill has fallen off the list of top 25 skills for data scientists entirely.

To make pay decisions with confidence, organizations need to have the right salary data to keep a pulse on the market. Because PayScale makes compensation and data management software, we’re in a unique position to find out: do modern organizations have the right data to understand the true, competitive nature of all of their positions? 

To answer this expansive question, we decided to find the answers to several related questions, including:

  • How are organizations doing in terms of being able to find data to benchmark their positions?
  • Where are the gaps in survey data? In other words, are there positions that organizations are struggling to price?
  • What percentage of a typical organization’ roles would fall into this bucket?
  • How many surveys are typically incorporated into a compensation model to price a job?

Who’s Included in the Study


Photo by Kayla Harris on Unsplash

We pulled these stats from PayScale’s data management platform. This piece of our technology helps organizations manage a myriad of survey data products, ingesting and normalizing the data to prepare it for salary benchmarking. Currently, more than 900 organizations use these capabilities to make pay decisions for more than 10 million employees. Nearly half of all these organizations have 5,000 or more employees. Another 20 percent have somewhere between 2001 to 5,000 employees, and the remainder have under 2,000 employees.

Our customers come from wide-ranging industries, including Healthcare; Manufacturing; Finance and Insurance; Professional, Scientific and Technical Services; Educational Services, and Information. (The data was collected in August, 2018).

What We Learned

In 2018, we found that many organizations currently using traditional, consultant-lead surveys have significant data gaps. In fact, the typical organization in our dataset is matching just 50 percent of their internal positions to the market data they have licensed.

For context, we know that organizations have licensed salary data from a variety of data providers. More than half of all organizations in our dataset had access to data from Mercer, Willis Towers Watson, and Aon Hewitt. PayScale has relationships with 85 percent of the survey providers in the market, out of the 350 or so survey providers we know about in today’s market.  

Organizations Have Significant Data Gaps  


Photo by Markus Spiske on Unsplash

Although organizations have plenty of data, survey utilization tends to be low. In fact, nearly half of all organizations are using less than 10 percent of the total jobs in the surveys they’ve already purchased. In other words, 90 percent of all jobs in all the purchased surveys were not utilized in job pricing exercises.  

Why is this the case? The problem is that organizations’ jobs are often quite different from the benchmark positions available in salary surveys.   

In our study, we found that PayScale customers are matching on average 50 percent of internal positions with employees in them to survey positions they’ve purchased.

SHRM has said that it’s sound practice for an organization to benchmark between 50 percent and 65 percent of its jobs when using market pricing, and benchmark positions should aim to include at least 70 percent of the employee population. The percentage of jobs that PayScale customers are able to price with market data is within the range of SHRM recommendations.

However, here’s an important point: Our research shows that many compensation pros are struggling to find sufficient data to price their positions. The World at Work organization recommends that organizations use three distinct sources of salary data to price a job. We see that most organizations are not able to achieve this for every position. Part of this may be due to the trend that jobs are becoming more unique and/or more complex, therefore harder to match and price.

Of the positions that have been matched to surveys, we found that 60 percent of jobs were matched to less than three survey matches. For those using a Company-Sourced Match (PayScale’s own compensation survey), in a quarter of all cases, this data source helped users match their position to the 3rd data source.

In addition, 80 percent of all matches made are made to the national or “all” data cut, rather than to specific locations or industries. When matches are only made to the national data, customers may be losing out on valuable information on pay differentials between regions.

What’s the State of Market Pricing In 2018?


Why are organizations struggling in the market pricing process? Is it because they lack sufficient data, don’t have budget to purchase more salary data, is it because they have out-of-date job descriptions, or is a lack of time or something else? To find some answers, we ran a market pricing survey in September 2018.

In the survey, we found that a vast majority of respondents recognize the importance of using market data to price their positions: 98 percent of respondents priced at least some of their positions. Out of this group, the vast majority priced at least 50 percent of all their positions using market data.

Although the number of positions organizations are able to price seems pretty good, the majority of organizations (77 percent of respondents) said that they would like to increase their match rate.

We asked people to tell us the biggest obstacles they face when it comes to increasing the percentage of positions they are able to match to the market.


The most common response was the lack of data (39 percent), followed by lack of budget (20 percent) and poor job description management (19 percent). Additionally, a smaller portion of respondents identified lack of time (13 percent) and organizational strategy (9 percent) as obstacles to market pricing more positions.  

It’s interesting to note that lack of market data was the most frequent response. What’s not captured in our survey but may be salient is that jobs themselves are becoming more complex, more unique, and therefore it’s becoming harder find exact matches for these jobs in traditional survey data sources.

How to Fill in the Data Gaps

To ensure that you’re able to find market data for more of your positions, make sure to consider multiple sources of data. When we say different data sources, we don’t mean adding more employer-sourced surveys. Rather, it’s important to find data that are collected in entirely different ways.

To learn about emerging salary data sources and how you can fill in the data gaps, download the full whitepaper.


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