Your Geographic Differentials are Probably Wrong

When I google “geographic differentials” for various cities (my Friday nights are boring…) I’m generally surprised at the abundance of misinformation out there that can create problems for Compensation practitioners.

Ignoring the fact that google results confuse the cost of living with the cost of labor, the misinformation I find frequently is that most online tools give a single percent as a geographic differential for a location. For example, the tools may say it costs 15% more to work in Seattle than in Denver or 20% more in San Francisco than in Dallas. While one number may make sense to most people and may be generally accurate on the whole, it is an oversimplification of the complex challenge companies face.

Geographic Differentials are Complex

Applying a single geographic differential can negatively impact a Company’s ability to be competitive or may even cause them to overpay.

One common practice for creating geographic differentials is to apply a single multiplier, based on the local cost of labor, against the national average. However, using a single geographic differential for all of your salary surveys may result in pay that is not competitive, or over-indexed.

Since no two salary surveys have identical participants, some may naturally have different geographic differentials built into the results. For example, some tech surveys are significantly west-coast weighted, due to the prevalence of tech jobs on the West Coast. Similarly, finance surveys may also be skewed toward the East Coast, based on the prevalence of the financial sector.

Geographic Differentials vary by Job Level

Interestingly (but not surprisingly), geographic differential changes based on the job level as well. Jobs that are paid less are typically more likely to have greater geographic differentials than those that pay more. The easiest example to conceptualize is minimum wage roles. In Texas, the minimum wage is $7.25 an hour, whereas in Seattle, it is $16.00 an hour — a 221% geographic differential! While this is an obvious example meant to demonstrate how significantly job level can impact pay, it is not an exaggeration.

Case Study

Recently, I was working with a client that was applying a +15% geographic differential for roles in Seattle with all of their surveys, and for some surveys, this was completely appropriate, but for others, it over-indexed the market value of the roles. How?! In some salary surveys the participants are predominantly west coast participants, and the premiums are already built in. By applying a 15% differential to a survey where the West Coast is already heavily represented, the Company was over-indexing its compensation bands to the market!

The client’s immediate reaction to reducing the geographic differential was shock and disbelief. Once we reviewed the salary survey data with the Compensation Tool’s Scope Comparison tool, we were able to clearly explain how the geographic differential was potentially over-indexing market values for the Seattle market.

CompTool Builds Better Geographic Differentials

CompTool reviews the market values of jobs that exist across multiple scopes, comparing compensation data against each scope. Based on this analysis, the Compensation Tool provides the differential for each scope, compared to another. So if you want to see how much of a geographic differential is already built in to the Seattle market, like I mentioned, our tool lets you compare Seattle to the National data cut, and boom… There you have it… 4% (or whatever it is now). It’s not just geo-diffs, though. The tool will allow you to compare across industries, revenue, and more.. Any data cut in your survey can be used.