Last month we explored the concept of a compensation philosophy and why it is an important guide to an organization. This month we are looking at survey data. Next month we’ll tie things together by looking at how a compensation philosophy influences what specific survey data will be useful to an organization.
You’ve participated in surveys, bought the report (or received one from MRA as part of your membership), and are now the proud owner of a treasure trove of data. Is it a pot of gold or the data equivalent of your kitchen junk drawer? Actually, the answer could be either—depending on how you use it.
Salary surveys typically contain a lot of information expressed in numbers such as average, weighted average, market 25th percentile, market 50th percentile (also known as the median), and market 75th percentile. All of these numbers work together to help you develop a picture of the market rate for a job.
Start with the market 50th percentile data point, the rate that falls in the middle of the set of reported rates which are sorted from highest to lowest. This measure of central tendency, rather than the mean or average, eliminates very high and very low numbers that can skew the results. Many compensation professionals use this data point to evaluate survey findings.
Next, look at the average. If it is drastically different from the market 50th percentile, this indicates that the data set contains some extreme high or low values, making the market 50th a better representation of the market pay for the job, especially if the sample size is relatively small.
Why should you also look at the market 25th and market 75th percentile values? If they are close to the market 50th, this tells you that there is not much variation of pay in the market for that job. If your organization establishes a range for a job with the midpoint at the market 50th percentile, you will likely have a hard time recruiting someone by offering a rate at the bottom of the range if the market 25th, 50th, and 75th are very close together.
Finally, consider your sample size. Surveys generally provide the number of companies and the number of incumbents reported in each scope cut. A large sample size will give you numbers that are less likely to be influenced by a few unusual rates in the reported data. Sample size isn’t the only consideration, though. Next month we’ll discuss other important factors in survey data: "Matchmaking and the Market."
MRA’s Total Rewards team encompassing Compensation, Surveys, and Benefits is here for you to create your strategy, build the business case, interpret data, conduct custom research, or facilitate and partner regarding many other essential steps for a comprehensive Total Rewards approach.
This is the second of a three-part series of articles focused on compensation and salary surveys, designed to launch and reinforce your journey through:
- Candid discussions and succinct documentation of your company’s compensation philosophy;
- Reviewing your company’s existing compensation philosophy;
- Using reliable data to make decisions impacting company costs and employee pay; and
- Applying current, credible data for compensation decisions.
Source: Jane Crane, Compensation Specialist, MRA - The Management Association