Compensation professionals all use salary surveys as inputs into the management of salaries in their respective organizations. As we all know, surveys capture market data for benchmark jobs – representative positions that are commonly found across many employers – and this data is then used to inform about other (non-benchmark) roles.
As a survey provider for high-growth and developing markets, Birches Group is focused on countries with smaller markets, fewer employers and a myriad of different jobs, often defined differently from employer to employer. In our surveys, we capture occupationally-specific data as a reference, because our clients demand it. But are these references really valid or meaningful? Below is an example from Côte d’Ivoire:
You can see that the range of pay provided by job family (green columns) closely matches the overall data at the 50th percentile of the market (grey rectangle). The incumbent average data also varies a bit by job family, but clusters within the market range.
We would argue that fewer jobs might serve clients better. Here’s why.
Let’s suppose you hire three new staff this week – one in finance, one in marketing and one in engineering. All three are placed in the same salary band in your company, say band C. The starting salary for each is determined in accordance with your policy, and takes into account several factors, such as experience, education, past salary history and scarcity in the market. You might also consider internal equity and compression issues. In the end, all three individuals are successfully recruited and placed at three different salaries in band C, all within the lower half of the range.
Fast forward to the first pay review for the same three individuals. What factors are used to determine their pay movement? Performance? Budgets? Compa-ratio? Relationships with the boss and peers? Internal equity? Yes to all of these. Now how does their specific job role or occupation factor into the calculation? Not at all! You treat all the band C employees the same when applying your merit pay policy, don’t you?
Companies typically have generic pay bands. Jobs with comparable value to the organization are placed in the same band, regardless of occupation or role. Pay movement for individuals within the band is based on many factors, but it is company parameters and individual characteristics, not job or occupation, that determine pay progression.
If you agree with this conclusion, then what follows is even more important. The occupational differences reported by most surveys, while certainly interesting, do not actually mean that the reason for the difference is related to the occupation or the role. Rather, it illustrates that for any job, there is a range of compensation that varies according to individual circumstances.
Companies build their generic pay ranges by carefully selecting representative benchmark jobs across each job family. They look for multiple sources of data for each benchmark job and often create elaborate calculations, with weightings of various sorts, and using different percentiles of the market data, to establish the final going rate. This is then used to build a structure for all of the jobs at that grade in the company. By blending data into a single going rate, you are in effect, using generic data for your structure.
So, why not simplify your life, and use generic data to start with? Our grade averages report (other providers refer to them as level reports or roll-ups) provides all of the information you need to build a structure. Because all job data we collect is included, even those positions with insufficient data to be separately reported, the sample size is the largest and most reflective of the market practice.
Best of all, you no longer have to wring your hands about what to do if you cannot match enough specific jobs to the survey. As long as you know how the survey provider levels map to your internal grades, you’re good to go.
It’s time to rethink how surveys are conducted and used, and admit that false precision and complex processes are misleading and wasteful. De-emphasizing jobs is the first step. We will share more ideas in future articles.