By Jen Carsen, J.D. and Sharon McKnight, CCP SPHR
Wouldn’t it be great if every job title in your organization were included in every salary database?
Alas, that’s probably never going to happen. But the good news is that a large percentage of your job titles will in fact be there, even if they’re hidden in places you may not initially think to look.
Think keywords, not job titles
Because job titles aren’t consistent across organizations, it can be helpful to search using keywords instead of job titles when scouring salary databases.
For example, if you’re looking for salary data for a helpdesk technician, you’ll have better luck finding pertinent data if you search using the keywords “support” or “computer.” Keywords can usually be determined by looking at a job’s primary function(s). For example, a helpdesk technician provides user support for computer systems.
It’s important to remember that you can’t rely solely on a job’s title to insure that the salary data for it is valid for your position. Job titles can point you in the right direction to find applicable data, but you have to dig into the details of the job you’ve found to make sure it’s a good match for your position before you use its market data. Using keywords to search for jobs helps insure that the data you find will be relevant.
Job descriptions: Look for at least an 80% match
Whenever possible, review the job description for the job you’ve found before deciding to use its data. Even the summary description provided by most surveys is a better indicator of a match than just the title.
A good rule of thumb is that if the job description matches 80% or more of your job, then it’s a strong match. If it matches less than 70%, though, it’s not a match and you need to keep looking for a closer match for your position.
Solving the riddle of the blended job
Added to the issue of job title variation is the reality that many jobs are really a combination of multiple functions. For example, they can start out being one thing and end up being quite another. New responsibilities, sometimes not related to the original job, can be added that broaden the scope of a position and, in effect, make it another job altogether.
Even when a job doesn’t morph into a completely different creature, adding responsibilities can alter the position enough that salary data for only the base job doesn’t paint an accurate picture of its market value.
In those cases, blended job data is a good solution for more accurate salary data. BLR’s Salary Finder makes blending salary data of multiple jobs into one composite position a pretty easy task.
If all else fails…
So you’ve scoured the salary survey database and still can’t find a job that matches your position. You’ve used every keyword you can think of and even broken the job down into its key components to create a blended job but can’t find enough relevant jobs to include. What now?
Accept that this is okay. Not every job in your organization is going to be included in any given salary survey. But that doesn’t mean you can’t have valid market data for that pesky position.
If you have valid market data for all of the benchmark* jobs in your organization and have organized them into a job worth hierarchy (ranked lowest to highest), you can now slot the non-benchmark jobs in. These jobs are slotted into the hierarchy based on their overall value to the organization in relation to the market.
At least 50% of the jobs in your hierarchy should be benchmarked using market data, and the fewer jobs “slotted” in your structure, the better. The more slotted jobs in your job worth hierarchy, the less confidence you can have in its validity.
*WorldatWork defines benchmark jobs as positions that are “commonly found in many organizations and used to make pay comparisons, either within the organization or to compare to jobs outside the organization. They are used for making pay comparisons to develop or validate a job worth hierarchy.”