7 Keys to Using Salary Surveys

When the results of salary surveys return, there are mountains of information to sift through. You can spend days reviewing and analyzing the data. A lot depends onhow far down into the details you’re willing to drill andhow granular you want to get. But if you don’t know how to interpret the data correctly, you may end up spinning your wheels, or worse, making ill-informed pay decisions.

To effectively leverage salary surveys, you must familiar- ize yourself with several details and concepts. Here are seven key factors you should consider as you dive into your survey results and begin utilizing them for your or- ganization.


All surveys have an effective date. In most cases, this will be the date the data was collected. Since it takes months to prepare market data for publishing, some publishers may elect to age the data to an effective date that is more current. In any event, note the effective date. You most likely will need to further age the data yourself. For ex- ample, if the effective date of the survey is March 1, 2018 and your salary increases take effective on January 1, 2019, you may want to age the data to the later date. On the other hand, you may want to age it to July 1, 2019, in order to “lead the market”. Age the data to a date that isappropriate for you.


A reputable survey will provide multiple cuts of data based on geography, industry, revenue or company size. For some or all staff, you may want to narrow the scope of data based on one or more of these parameters. You need to be careful not to set the scope too narrow. Al- ways make certain there are enough participants and consider your organization’s anticipated growth.

  • Geography – Think about where you recruit the various levels of staff within your organization. For example, executives are usually recruited from a region of the country, the entire country,or maybe even globally. Whereas lower level staff are usually recruited from the immediate city or region wherein the business operates.
  • Industry – For some positions, it is appropriate to limit the scope to a specific industry, but many jobs are industry agnostic. Many compa- nies using larger surveys will use industry spe-cific data as well as “all participants” or “all in- dustries”.
  • Revenue – This is a key scoping factor. As you can imagine, the larger the revenue, the more complex the job, especially in the leadership and executive positions. If you are a growing company, consider your current revenue as well as future revenue targets.
  • Company size – Generally, larger companies are more complex, just as revenue scope. Again, consider your current number of employees where you anticipate being in the near future.


Each survey position title will have a count of companies and the number of incumbents matched to the job. Look to ensure you have enough matches, either in companies or number of incumbents. Of course, these numbers are relative to the total number of companies participating in the survey and speak, in part, to the reli- ability/validity of the data. Most surveys will only pub- lish data for those jobs with enough reports incumbents to be statistically significant.

Be on the lookout for jobs that typically have a single in- cumbent, such as a Controller. If you should see survey results for a Controller with more incumbents than companies reporting, you can deduce that some compa- nies matched multiple incumbents in this job. Perhaps they have “Divisional” Controllers. So, it’s possible thatthe multiple incumbent data may pull the overall survey numbers down. However, you may be able to test that theory if you can run a report of median or average sal- aries from the survey of larger companies (size or reve- nue) and compare the numbers.


Data anomalies are just a fact of statistical life. They may or may not indicate a problem, but in all cases, you’llwant to make sure you address them. There are two sit- uations where anomalies commonly appear. The first is when the data for one job is inconsistent with that of an- other job within the same job family. For example, you may find that base salary for an Analyst II is very close to or higher than that of an Analyst III. The second is when current year numbers are compared those of the previ- ous year and appear to have increased or decreased dra- matically. Both examples could be the result of a signifi- cant change in market demand, thus affecting salaries. In these instances, you will have to decide to either acceptthe anomalies as is or adjust to “normalize” the data.

When working with large national surveys, you can ex- pect to see fewer anomalies. When you have several hundred or thousands of the same companies participat- ing, the data trends more consistent.


Although you’ve done a good job of matching your jobs to the survey, it’s very possible that some adjustments to the data are warranted. Perhaps some of the survey jobsyou’ve matched to are either “lighter” or “heavier” than your own—i.e., the survey job has greater or less respon- sibility, scope, etc. Another instance is when the survey has five levels of professionals and your organization has four. In this case, the match is not a direct match to the levels. In these instances, you must decide if the differ- ences are significant enough to warrant an adjustment (discount or premium) to the survey data. To assist you to determine how much adjustment is appropriate, you can look at the numbers for the job one level above and the job one level below and make appropriate adjust- ment.


In many organizations, there are some staff members performing multiple jobs. Primarily there are three meth- ods for determining a market rate for that job:

  • Percentage – As you can guess, this approach calculates a rate based upon the percentage of time spent in each role. Each percentage isapplied to the corresponding market rates, and the results are added together to form a blended rate. Keep in mind that this methodmay reduce the individual’s pay instead of pay-ing more for the individual taking over addi- tional responsibilities.
  • Highest Value – This is simply paying the highest value of the different jobs the individual is per- forming. The thought being that you’re alreadypaying for the individual for the Skills, Knowledge and Abilities (KSAs) of the highest paid role and taking on a “lower level” job shouldn’t result in a lesser rate.
  • Premium – In this scenario, you’re putting a pre-mium to the highest rate of pay of the multiple jobs the individual is performing. This is ac- knowledgment that the individual is taking on two jobs and saving you money. Therefore,you’re sharing that savings with the employee.


A salary survey serves as a tool for external comparison.Once you’ve reviewed how your organization compares to the “market” and made any necessary adjustments, you will need to look at how your jobs compare inter- nally. For example, as the result of salary survey, you’venow elevated your Director, Business Development posi- tion to VP, Business Development. However, the organi- zation has valued the Director, Marketing to be equal to Director, Business Development. Changing jobs or em- ployee compensation because of market pressures may upset the internal equity within your organization.


As you consider all these seven factors, use your com-pany’s Compensation Philosophy and/or Strategy to guide you. Some of the decisions you make are broad de- cisions that apply to several jobs. There will be other de- cisions you make that will apply to an individual (involv- ing appropriate personnel). It’s critical that you applythem consistently. At some point, a person does “make the job”. Make sure you involve your legal department,and your rationale is valid. Always keep good notes! It’scritical that you apply them consistently. They will prove valuable as you face similar situations in the future, or should you need to defend your decisions.