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High unemployment, inflation, scarcity of necessary skills, along with rapidly advancing technology are just a few of the causes of stress impacting Human Resource professionals. The approach to recruiting and rewarding talent has become more flexible and creative – organizations are trying so many things to get people in the door, and keep them. Yet, one thing remains constant, getting pay right is foundational and that starts with using quality salary survey data in order to set competitive hiring ranges and equitably manage pay.
Several factors go into making decisions around which salary surveys are right for your organization. Coverage and similarity to your industry and jobs is important. Fresh or timely data is increasingly important now that wages are changing so rapidly. No longer can you age, or roll-forward, last year’s data and expect to get an accurate reflection of competitive pay. While each of those factors can be determined based on objective measures, (i.e., Does the survey include the jobs I need, or not?) the bigger question is how do you make sure you’re using quality salary surveys.
Taking massive amounts of employee data from hundreds of organizations and combining them in valid ways to produce useful salary survey data is no small feat. Mistakes can be made and they will impact the number of jobs included, the statistics reported (e.g., 25th and 75th percentiles, median), and the overall usefulness of the data when comparing one pay element to another.
Typically, survey administrators/vendors have a process in place that includes a variety of checks and balances along with quality auditing measures. Best not to assume, however. Ask your survey vendors to explain their process and how they handle data anomalies.
This article lays out several quality control steps we think are important in the survey production process. How do the practices of the survey vendors you use compare?
To make sure each survey is the best it can be — from pre-participation through data collection, analysis, and publication — vendors should start by establishing a project plan that takes into account lessons learned from past survey seasons, incorporates advances in technology and operations, and adjusts the survey for anticipated changes in the relevant industry or labor market.
During the planning process a survey team typically comes together to assess the target participation list to create an optimal mix, modify any survey questions to reflect current trends and practices, or add in new questions to start tracking emerging issues. Additionally, it’s during this initial phase that the team determines specific quality standards. One of the objectives is to look at potential data deviations for each survey, defining what is and isn’t acceptable.
5 key factors to consider when selecting surveys
With any survey, the administrator expects a certain percentage of participants to provide data that deviates from the norm. These deviations vary for each survey based on factors such as industry type and participation size. In larger surveys, with data from many participants, there is less impact from data deviations on the resulting statistics than there is in a survey with a smaller participant group.
When it comes to choosing a survey data provider to work with, a recent Mercer survey showed that 89% of participants said “ease of participation” plays a role (while 36% said it plays a major role). The process can be a complex and even confusing thing for participants. Vividly detailing what is expected from participants as early as possible and providing technology that makes submission easy is much appreciated by participants.
Next comes job matching, which can be challenging. Survey position lists will vary from year to year. Proactively informing the participants of changes and in some cases working directly with them to explain any new or altered job positions helps organizations more easily match their existing positions to any new or changed positions in the database.
As data submissions begin to roll in, with the help of automation (and some keenly observant survey specialists), submissions are analyzed in a variety of ways, keeping an eye out for any abnormalities or discrepancies that might compromise the accuracy of the survey. Significant changes in a data point from one year to the next or complications stemming from dealing with parent/subsidiary data reporting are examples of situations that the survey administrator would research and verify.
Once all data has been submitted, the next step is usually looking across all the data to identify outliers and discrepancies by job, job level, and a variety of other ways. This step involves not only identifying the outliers, but also determining how to handle them. When it comes to accounting for these outliers, there are many steps that go into verifying whether the outlying data is relevant, or if it should be omitted from the final results.
As part of producing a quality product, survey vendors should be looking to continuously improve the product and data delivered to you, the participant and purchaser. Just as in the planning phase, the various members of the survey team should be debriefing to identify any opportunities for improvement going forward, whether it be to the process or survey itself.
With an extensive library of salary surveys and a highly skilled survey production team, not only do we have a rigorous multi-step quality assurance process that includes automated intelligence, but through Mercer’s award-winning innovation, Data Connector, clients receive a platform to upload data securely, make matches to Mercer Job Library catalog, and address any audit. After all, a good survey collection process is what leads to high quality salary survey data that allows you to confidently set pay ranges for employees.
Do you think Mercer’s surveys might be right for you? Email us or give us a call at 855-286-5302.