The current PayScale “Develop a Market-Based Pay Structure” marketing publication is deceptive, inaccurate, and, given the apparent quality of their data, could set you up for a non-competitive and divisive pay program that increases turnover and employee dissatisfaction.
PayScale is a popular online market pricing “tool” presented by the company as a solution to compensation planning. The company’s marketing strategy involves convincing you that every other approach to compensation program development and maintenance is expensive and time-consuming, and that you need nothing but their data tool and all your pay problems will be solved. Think of those late night commercials for “only available on TV” products where the actors over-emote at the tragedy of the cheese burning on the pan, leaving the only option as their $49.99 unique patented special pan (order now and we’ll throw in a set of steak knives!). No, seriously, there’s a stock photo of a young woman with a shell-shocked expression tearing at her hair under a caption “Do you have time to fill out salary surveys?”
The current marketing brochure makes the following arguments/claims (among others):
- “Market pricing is the most effective approach to job evaluation.” FALSE – market pricing, by definition, IS NOT job evaluation. Job evaluation is the systematic analysis of jobs to determine their contribution to the organization, irrespective of the market. It is the only way to correctly determine how your jobs truly compare to those in the market, how to deal with jobs that have no market rates, and how to properly address jobs with combined or multiple functions. Market data is a tool to anchor an internally valid pay structure to ensure competitiveness — but it is just a tool.
- “[market data] takes less time to maintain.” FALSE – market-based pay programs are very time consuming to maintain, because every year you have to go out and collect market data for every single job. To do it right, you have to review multiple sources, and then figure out what to do when (inevitably) market rates for particular jobs rise or fall — do you put them in different grades only to have them move again next year? I’ve seen organizations spend hours on a single job trying to determine how much to adjust a market rate to account for lead responsibilities, or added responsibilities, or additional educational requirements. How do you adjust your ranges overall to reflect the multiple changes that go on with jobs and in the market — ever sit there with a spreadsheet struggling to develop a structure that accounts for pay compression, differing rates of market movement, or organization growth, all without any logic? With an effective internal evaluation structure in place, you can update a pay structure in a couple of days each year.
- “It is harder to manipulate the results [with market data]” FALSE – there is nothing easier to do than manipulate market data — to pick and choose which surveys to use for a particular job, which “cut” of the data, how much to age it, or weight a survey. The bottom line is that in a market-based system, you can use “legitimate” data sources to come up with just about any number you want.
- “A smart alternative to the expense of multiple survey sources is to use a data source that has good comprehensive coverage. PayScale is a good single-source option” FALSE — on so many levels. The reason that “real” compensation consultants (PayScale uses the word “traditional,” presumably as a way to suggest that PayScale is more “progressive”) recommend using multiple sources of data (we suggest, frankly, as many as you can find) is that each survey has its own “trends” — some attract higher-paying employers, some have different business models than you, some have smaller or larger samples. Multiple sources compensate for variance, and give you more reliable results, as well as increasing the likelihood of finding as many jobs as possible. No single source can cover all the variables — and no “algorithm” can substitute for real data.
- “The goal is to benchmark 75-80% of the positions within your organization.” FALSE — of course, if the only way you have to assign jobs to pay grades is through market data, you really need 100% of the positions, or some kind of internal equity model to fix the other 20-25%. On the other hand, with an internal equity structure tied to the market, you can do quite well with data for only about one-third of the jobs. That certainly makes it easier than scrambling through multiple sources trying to come up with “something” to use as a market rate. PayScale ends up with the obvious — suggesting using an internal evaluation method to slot jobs without market rates into pay grades — so they still say you need one, you just don’t use it effectively, only to cover the holes in their database.
Speaking of their database — probably the biggest and most worrisome critique of the PayScale tool is the very algorithm they brag about that they use for their predictions. PayScale’s data comes only from job seekers — it DOES NOT incorporate the entire spectrum of what people are paid. Given that you can assume that more highly-paid folks are less likely to be seeking jobs, and that those with longer service (generally earning more) are also less likely to be looking, we can make a pretty fair assumption that the PayScale model is set below the market.
In two tests we’ve done this year (one sitting in on a client’s PayScale sales pitch, and the other from data on a couple dozen jobs that a client purchased from PayScale) we found the PayScale data to be about 10-15% lower than the data from traditional surveys, particularly in entry-level jobs where the risk of pay-related turnover is so high. We’ve seen similar comments on message boards.
It’s taken us a number of years, but we’ve successfully moved all of our clients off of “pure-market based” pay structures, and helped many others fix compensation systems broken by over-reliance on market data. It’s not magic, and it can be done internally if people have the knowledge and exposure to the right techniques. Regardless of how you choose to establish your pay ranges, remember that survey data is only a tool, and only part of the process of establishing an effective compensation program. Relying on a single-source “product” with a modeling method that seems guaranteed to provide non-competitive results is likely to result in failure.