Not All Salary Surveys are Created Equal

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 a 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 towards the East Coast, based on the prevalence of the financial sector.

Differentials vary by Job Level

Interestingly (but not surprisingly), geographic differential change 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.

How the Compensation Tool Builds Better Geographic Differentials

The Compensation Tool reviews the market values of jobs that exist across multiple scopes, comparing the compensation data. Based on this analysis, the Compensation Tool is able to determine the most suitable differential for each scope, compared to another.

With our Survey Scope Comparison report, users can determine the best geographic differentials to apply for each survey. The Compensation Tool allows comparisons across all data cuts such as industry, revenue, FTEs, and location.

Case Study

Recently, I was working with a client that was applying a 15% premium for roles in Seattle with all of their surveys, and for some surveys, this was completely appropriate, but for others, it significantly over-indexed the market value of the roles. Since some of their salary surveys were predominantly west coast participants, the premiums were already built in. By applying a 15% differential to a survey where the West Coast is already heavily represented, the Company was over-indexing their 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.