Looking to Benchmark Pay?
Interactive Exercise
If you want to use regression analyses to set compensation, but don't have the time and resources to collect data and formulate your own regression models, you may find ERI's Salary Assessor® software helpful. For this software, ERI:
- collects available salary survey data for jobs, areas, and industries
- evaluates each survey for validity and reliability
- compiles job salary ranges with midpoints along with duties, responsibilities, skills, and functions
Regression Equations
The salaries are analyzed using polynomial regression, which captures the non-linear nature of wages. Additional analysis is conducted using multiple regression. ERI uses the following factors to arrive at final compensation figures:
- geographic area
- years of experience
- revenue or assets
- performance level
- industry
- salary planning date
- education, skills, certifications, and shift work
By capturing the statistical relationships between salaries, geographic areas, industries, company size, years of experience, revenue (or assets), and other adjustments, users are provided with consensus results for any given position, including well- and not-so-well-surveyed positions, areas, industries, or earning levels.
The following exercise will show you how ERI's Salary Assessor works to set pay based upon multiple factors.