TAKING LOCAL AREA WAGE STUDIES TO A NEW DEPTH
Every compensation leader with multi-unit responsibilities knows that the definition of competitive wages is different in each market where they operate. In the U.S., the labor market for most manager-level positions and higher tends to be on a national basis where talent moves within an industry and with comparably sized companies. But it’s a different story for hourly workers, and many exempt-level professional levels. These workers are far less likely to pack up their families and move to another city or state to take on a new position. Workers at these levels will change jobs and be more likely to switch career fields to where their skills are similar, so long as they can stay within a reasonable commuting distance. For example, a manufacturing machine operator may take a warehouse shipping/receiving job, or a restaurant worker may leave to take a position in retail.
So what’s a compensation leader to do? We see four basic market pricing techniques used to solve for geographic differentials in local area wages. The first three are fairly common approaches that companies take to geographic analysis, but we’re starting to do more work that allows us to drill deeper into local area wage data and provide micro labor market analyses.
- Applying a differential to a national structure
- Geographic scope cuts of benchmark survey data
- Custom market studies
- Micro labor market analyses
Applying Geographic Differentials
The most simplistic approach is to focus first on getting the overall national salary structure ‘right’ and then apply geographic differentials up or down from the national market to localize the data. We use our GeoAnalyzer to help come up with the right amount to use for adjusting the structure. GeoAnalyzer pulls in data from our Total Compensation Measurement® (TCM) suite of surveys and streamlines the process for deriving local market adjustment factors.
This is by far the fastest and easiest approach and it meets the needs of many. However, this approach doesn’t take into account the variability of how benchmark data for individual jobs can be influenced by local labor markets.
Geographic Scope Cuts
Another commonly used approach is to use the individual geographic scope cut data from the benchmark jobs in our TCM surveys. Both our Broad-based and Nonexempt surveys from TCM provide a range of options for geographic scope cuts, such as region, state, metropolitan area, or even 3-digit ZIP code.
The benefit to using this approach is that it does tie directly to reported survey data from the selected local labor market. One of the common challenges users face when relying on this approach is that they can’t always be assured that enough of other employers in each of their desired local markets will consistently be in the same benchmark survey.
Custom Market Studies
Custom salary surveys are far less common, but can be an effective way to achieve the benefits of having benchmark job data from specific peers in a local area if they are not all in the same benchmark salary survey. Supporting a company’s geographic market analysis is the top reason our clients reach out to us for assistance with their local market studies.
Custom benchmark surveys though can be expensive and most companies that use this approach will do so on a selective basis. For example, they may elect to only
- Include a small sample of benchmark jobs in a market,
- Analyze only a portion of their local markets where they operate, or
- Elect to analyze a market only periodically, i.e., every 3 – 5 years
Micro Labor Market Analyses
Our newest approach to helping solve geographic market data analysis needs started with a pragmatic conversation with one client. This client was already well versed in the traditional range of options above, but still faced constant challenges from field managers who believed the salary structures coming from the corporate compensation team didn’t adequately reflect the needs of their specific markets. With over 500 locations, the notion of a custom study was not feasible.
She had been using our metropolitan area cuts as well as our 3-digit ZIP code cuts of data, but still faced challenges from field management. My favorite quote when she was describing the problem was when she said, “My boss and I live in the same 3-digit ZIP code, but I drive through two completely different socio-economic markets when I drive from her house to mine.”
To illustrate the challenge, we zoomed in on just one metropolitan area surrounding Boston, MA. The picture below shows just the top half of the Boston area. There are a total of ten different 3-digit ZIP codes in the Boston Metropolitan Statistical Area (MSA) and we’re just showing the four on the north side of the MSA.
By visualizing the data this way, it was clear to see two things:
- The size of the overall MSA is too large and diverse to be considered one homogenous labor market for front-line hourly employees,
- Slicing based on 3-digit ZIP codes made some improvements to the overall size, but the areas are still too big and now create situations where neighboring towns might not be included in the same 3-digit ZIP code clustering.
To solve this problem, we created an interactive data analysis tool that allows the client to specify a mileage radius they would consider as a relevant labor market and then using the mapping geo coordinates of their locations and the full ZIP codes of all submitted market data, we calculate the summary market data statistics surrounding each client facility. You end up with many micro markets, but each one is focused on the immediate area around your locations. Once line managers saw the details behind the methodology, our client was able to calm their concerns about the accuracy of the compensation ranges.
There’s really no limit to the size of the radius to use when defining the micro market. We just think about it from a practical standpoint of how far people will typically commute to come to work today. 10 miles for entry-level hourly jobs seems reasonable in some parts of the country. We’ve also created the micro markets using a 40 mile radius in more rural areas. The math works the same. It’s just a matter of what makes sense for your situation.
This solution does require us to create composite jobs where we blend data from several similar benchmark jobs, but again, given the migratory pattern of how hourly workers move between traditional benchmark jobs it works out better to focus on broad job-skill definitions for defining pay in these micro labor markets.
All four approaches described here have merit and can help you meet your needs for gathering locally competitive labor markets. Each having its own set of benefits and other considerations. The best place to start is always with solid participation in the benchmark salary surveys. Contact us to learn more about how Aon can help meet your needs for market data.