Salary Ranges: Design for Competitiveness or Consistency?

For as long as I’ve designed salary ranges there has been an ongoing tension between designing them for external competitiveness with the market or for internal consistency. You might be asking, “Why can’t I have both?” Well, you can… to an extent. As with a lot of things, the data doesn’t always line up and give you a nice, neat result. Eventually in a consulting engagement, I have to present data to a client and ask them if they want to mimic market data even when it is not uniform or might even clash with the organization’s talent strategies. 

The following market data shows the 25th, 50th and 75th percentiles for different levels of User Interface Designers (US National data) along with some analytics in the table below: 

Analytics Definitions: 

“25TH COMPARED TO 50TH” - how much lower the 25th percentile is from the 50th

“75TH COMPARED TO 50TH” - how much higher the 75th percentile is from the 50th

“RANGE SPREAD FROM 25TH TO 75TH” - how much higher the 75th percentile is from the 25th

“GROWTH RATE OF 50TH” - how much higher the 50th percentile is compared to the next lower level

“OVERLAP BETWEEN LEVELS” - how much the lower level overlaps the next level up

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ISSUE 1: Comparison of 25th and 75th Percentiles to 50th percentile: 

It’s easy to see the 50th percentile doesn’t always line up exactly in the middle between the 25th and 75th percentiles. It’s not intuitive, but remember that percentiles merely tell us what percent of the sample is below a specific value (e.g., 75% of the data is below the 75th percentile). There are the same number of values above the 50th percentile as there are below it, but the values aren’t distributed evenly.  

The Principal level here is probably the best example. Since the 75th percentile and the 50th percentile are so close together, we can estimate there is a tight cluster of salaries between those two values and a more widely distributed group of salaries between the 25th and 50th percentiles. As a result, the 25th percentile is 17% below the 50th, while the 75th is only 7% above it. 

What would you do when setting the salary range maximum for the Principal level? 

ISSUE 2: Growth rate of 50th percentile: 

Often called “midpoint progression,” the rate of growth between 50th percentiles from one level to the next has a big impact on the salary increase size an organization gives through promotions. Traditional designs here often call for smaller increases at the bottom of the ladder and larger increases for the more senior levels, but this example it’s a little bit of the opposite. 

For perspective, if you were to start at the Entry level ($85,321) and set midpoint progressions at 15% for the next three levels and then 20% for the next three levels after that, you’d end up with a Principal midpoint of $224,230, well below the 50th percentile at that top level. 

How would you set midpoints in your salary structure based on the 50th percentile values? 

ISSUE 3: Overlap between levels:

Ideally, organizations want a lower salary range to overlap the one above it. The level of overlap is up for debate, but normally it could fall somewhere between 25% to 40%, meaning the top of the lower range doesn’t quite come to the midpoint of the next level up. Let’s use a promotion example again. 

In our table above, Level II actually doesn’t overlap at all with the Journey level above it (indicated by a negative number), so the Level II maximum of $118,678 falls below the Journey minimum of $120,905. As a result, if we were to promote someone from Level II to Journey, we automatically incur a cost of about $2,000 just to keep this person in the range at their new level. To adjust for this, an organization might widen the range spread of Level II or potentially increase the midpoint to help accomplish some kind of overlap.  

How would you solve for low or lack of overlap between ranges? 

Thank you for sticking with me on this longer, more technical look at market data analysis and salary structure design. These examples are meant to get you thinking about how the data can sometimes conflict with your talent strategies and the decisions organizations need to make in order to deliver balanced compensation programs.