While it may seem counter-intuitive, sometimes the benchmark for a lower level job role is higher than that of a higher level role. This can happen for a few different reasons:
- Data Composition: The companies that comprise the benchmarks in a job family may vary across levels. If companies in adjacent levels have different compensation philosophies, the salary by level progression in the data may deviate from the expected level progression for an individual company.
- Data Distribution: Due to the distribution of data, there are instances where the lower and upper ends of distributions may overlap with adjacent levels. This is particularly true for the 10th and 90th percentiles, where the very bottom end of the P3 distribution may stretch lower than that of P2.
- External Factors: In instances where external factors impact the value of equity compensation e.g. stock appreciation, this can result in unintuitive variation between levels. If the data points in a given benchmark are from companies that have experienced high growth since equity was granted, it can cause benchmarks to be higher than adjacent levels, in cases where equity benchmarks are taking into account stock appreciation.
When this happens, we advise customers to look at the adjacent levels for the impacted role and come up with a smooth-line distribution across the varying levels that is appropriate for their organization and its needs.