Benefits and Compensation

Slotting Jobs In When There’s No Market Data for Them

Yesterday, BLR’s Senior Compensation Editor Sharon McKnight, CCP, SPHR, took us through the process of finding compensation data for those slippery jobs that are tough to classify. Today: What to do if you’ve gone through all those steps and still find yourself coming up empty.

Benchmark Jobs Are Key

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.

That’s okay, McKnight says. 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.

Benchmark jobs are key to the puzzle. 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.”

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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 nonbenchmark 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, but the fewer jobs “slotted” in your structure, the better.

Setting Expectations

Market-pricing jobs can be a challenging process but a bit less so when viewed from a practical perspective.

As a general rule, find as much salary data for as many of your jobs as you reasonably can using the salary survey data available to you and “slot” in the remainder. Remember, though, to never slot in more than 50% of your jobs. “The more slotted jobs in your job worth hierarchy, the less confidence you can have in its validity,” McKnight says.

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  • How you can use comp metrics to validate those hunches you have
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