As published by workspan magazine – September 2013
By Theresa M. Worman, Compdata Surveys, and Greg J. Wolf, Compdata Consulting
The proper selection, use and interpretation of salary survey data can significantly contribute to the success of the compensation planning and review processes. Whether using data for planning purposes or fulfilling a request from management, these important steps can lead to success. Prior to consulting survey resources, identify with whom the data will be shared. It is also critical to ascertain the goals of the department or manager making the request to establish a clear understanding of what an audience is looking to gain. If the goal is unclear or unknown, ask questions. It’s essential to understand audience members and what they expect.
Know the Goal
1. Are there internal or external equity issues to address? Or both? When dealing with external equity issues, pay close attention to the types of companies that participated in the survey and be sure to have the right mix of participants. It also may be helpful if the survey contains weighted averages so the impact of competing larger employers can be seen. However, when dealing with internal equity issues, the depth of the data points contained in the survey may be more important. For example, a survey that includes positions at multiple levels and contains a wide range of percentiles may be useful, as well as reported ranges and hire-on rates.
2. Are recommendations being made for a department or an individual position? This question can help determine if this is the first of many compensation decisions in a series of changes for a department, or if there is an individual issue to resolve. The approach to internal equity issues could vary dramatically if there are multiple changes on the horizon.
3. Who is the competition for labor in this situation? An obvious statement to make is that a compensation plan should take into account the labor market. However, employers often get caught up in the idea that their competition is only defined one way. The competition for labor varies by occupation and should determine the selection of survey data. A local survey may provide appropriate data when looking at entry level or hourly positions, but would not likely include the industry data needed for more specialized, industry-specific positions.
4. Within which industry is the competition for labor? To illustrate the importance of this, consider the question, “Does a hospital compete with a casino for labor?” The answer can be “YES!” when considering food service or housekeeping positions. Once the competition for labor is evaluated, consider their industry and decide if it matters. If the survey source does not include data from the competing industry, companies may need to seek data from additional surveys, as pay can vary dramatically across industries.
5. Is the position crucial to the success of the organization or the project? If the position makes a critical contribution to the overall business, companies should be prepared to pay a premium. For example, a nationally known toy company hires designers from the fashion industry to create outfits for a particularly popular doll they sell. The challenge is how to determine pay after being repeatedly denied access to fashion industry data. Because it is critical the position be filled, the solution may be to collect salary history and expectations from all applicants and use that information in lieu of traditional salary data.
6. Has a decision about the pay already been made? HR professionals should determine if they are being asked to support a decision that has already been made, or if their role is to introduce new information. This determination can assure that the data presented does not contradict the decision that has already been made. Likewise, if the criterion for the data requested does not produce a report that accurately represents the true market value for the position, consider providing multiple breakouts that paint a more complete picture. The recommendation is to prepare a draft report and share it with the person who made the data request, so he/she can also see any discrepancies.
Avoid Common Mistakes
Mistake 1: Not asking enough questions before making a purchase. There are so many survey providers and so many surveys available; it can be detrimental to the process to make assumptions about what data will be included in the survey. Prior to purchasing, clearly define the following:
- Job titles needed — industry-specific, general office and benchmark, or executive
- Data points needed — average base rates, weighted averages, percentiles, total compensation, weighted total compensation, ranges or hire-on rates
- Geographic breakouts needed — local, state, regional, national or international
- Appropriate participant profile — participants in future surveys can never be guaranteed; however, a survey provider should be able to share its track record by providing previous participant lists.
Whenever possible, obtain a sample report to see how the data points are presented. It is important to understand that no single survey is likely to have it all, so look for the resources that do the most. Identify what is required and which could be labeled as wish-list items.
Mistake 2: Not knowing the antitrust guidelines and/or using data that does not satisfy the guidelines. To remain within safe-harbor guidelines, the U.S. Department of Justice and Federal Trade Commission stipulate that:
- The survey must be managed by a third party.
- The information provided by survey participants is based on data at least three months old.
- There are at least five providers reporting data upon which each disseminated statistic is based, and no individual provider’s data represents more than 25 percent on a weighted basis of that statistic.
Mistake 3: Using only one source of data. Unless there is a survey that very closely matches a company’s definition of the competitive market, it is a good idea to get more than one perspective by using multiple sources.
Mistake 4: Not understanding the origin of the data. Traditionally, salary survey databases were compiled using employer-reported data. However, nontraditional compensation resources are becoming more widely offered, and some providers even make limited amounts of data readily available free of charge via the Internet. This is the kind of data report an employee or manager may present about their own position. A quick Internet search could show what is easily accessible to employees, and they can respond with an explanation of the differences in their data and the data used by the company.
Some sources now mix employee-reported data with data collected from employers. Other nontraditional resources generate reports by mathematically altering data gathered from other surveys or resources. For example, they may obtain a survey with national averages and then apply a geographic differential to generate a pay rate for a specific zip code. Always know the origin of the data contained in the resource being used and check it against another survey source whenever possible. Preferably, one of the resources is a traditional salary survey with actual data collected from actual employers, which is the only source that can reflect real market data.
Mistake 5: Matching to job titles instead of descriptions. This is something to be especially concerned with when using employee-reported survey data. But, it can also be important when job descriptions have changed, and possibly expanded, as workers take on more responsibilities because of layoffs or cut backs.
Mistake 6: Expecting great data without participating in surveys. HR departments are doing more with fewer people these days, and participating in compensation surveys is low on the list of priorities. Look for survey providers who offer assistance with survey completion, as more and more providers offer extra services for survey completion at no charge. Many surveys will also offer the files a company submitted the previous year. If a company is uncertain about purchasing results, most providers will offer the discounted participant rate throughout the year to organizations that submitted data prior to the deadline.
Quality data can help recruit, motivate and retain quality talent, but it cannot guarantee success. Companies can add the human element to their compensation plans that is necessary to build a motivated, happy and loyal workforce. Following are a few common expectations employees or managers have of survey data and how HR professionals can address the issues.
- Expectation 1: The survey should include an exact match on criteria. It would be nice if all survey sources included every breakout for every job title, but that is not a realistic expectation. While a line manager may expect an exact match, the HR professional is likely to have to explain that the data contained in the report is enough information to draw certain conclusions. For example, there may be a match for the local area, but not within the same company size. The data is not invalid just because it does not match both criteria. This is also a case when having more than one resource could be beneficial.
- Expectation 2: The position should have a higher rate of pay. The first step is for the HR professional to gain an understanding of where the employee or manager acquired information leading them to the assumption that the rate of pay is too low. Then it is important to share the pay data used by human resources and explain its validity. This is a time when having familiarity with free Internet data sources is important, as it is a common resource for employees.
- Expectation 3: The position is unique and no survey will contain valid market data. While it is true that there are genuinely unique positions out there, a good number of the positions in a company will have some sort of valid benchmarking data available. HR professionals may need to walk through the job description and explain that while the tasks of the job differ slightly, the qualifications and years of experience are similar enough that anyone who was successful with the elements described in the job description in the survey would also be successful with the unique elements included in the job at an organization.
A good survey resource can provide a snapshot of the market used to consider when reviewing a compensation plans, but it cannot reveal the exact amount to pay — no survey can. Compensation is an art, and no amount of data can turn it into a science. Even the best data requires handling by someone who knows the goals of the organization.
Survey data will be more valuable to an organization if time is taken to put together a plan for survey resources. Determine how the data will be used throughout the year, and decide which elements are most important when making buying decisions. Work closely with data providers and request specific information to understand exactly what will be obtained from the investment. The right survey data in the right hands allow companies to make evidence-based compensation recommendations to support the overall goals of the organization.
Theresa M. Worman is the executive vice president of strategy and development for Compdata Surveys in Kansas City. She can be reached at email@example.com.
Greg J. Wolf is the managing principal for Compdata Consulting in Kansas City. He can be reached at firstname.lastname@example.org.
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