I created Salary Data Index around a simple idea. Salary and workforce statistics are much more useful when you know what is behind the number.
A national average can tell part of the story, but it may look very different once occupation, industry, location, working hours, or the source of the data enters the picture. I use Salary Data Index to examine those differences and make wage and employment data easier to understand.
I cover topics related to salaries, wages, earnings, occupations, employment, workforce trends, regional pay differences, job tenure, compensation, and other statistics connected to how Americans work and earn.
Who I am
I’m Andrew Harper, a labor-market and compensation analyst with experience in workforce research, salary benchmarking, payroll data, and employment analysis.
I grew up outside Erie, Pennsylvania, in a family where conversations about money usually meant overtime, health insurance, grocery prices, and somebody finding a job that paid a little more per hour.
My interest in pay started early. After receiving one of my first grocery-store paychecks as a teenager, I went home and calculated what I had actually earned per hour after taxes.
Most teenagers had more interesting plans.
I later studied economics at Penn State University before working in regional workforce research. My early career involved occupational data, employment reports, demographic information, and regional labor-market comparisons.
I later moved into compensation analysis for a large healthcare employer, where I worked with salary surveys, job classifications, pay bands, market benchmarks, hiring data, and compensation reviews.
From there, I moved into workforce analytics for an HR and payroll technology company and eventually became a senior labor-market analyst.
Those experiences shape how I research, check, and update Salary Data Index articles.
What I look at
I don’t stop at asking how much a worker earns.
I may examine how pay changes between states or metropolitan areas, how wages differ across industries, what is happening to hourly or weekly earnings, how long workers remain with employers, and how labor-market conditions have changed over time.
Government datasets are often my starting point. Depending on the topic, I may use information published by the U.S. Bureau of Labor Statistics, U.S. Census Bureau, state labor agencies, and other government institutions.
I may also use academic studies and original research from established organizations when they provide useful context.
Different datasets measure different things, so I don’t treat similar-looking figures as automatically interchangeable.
That distinction is an important part of my work.
Why I created the site
Salary numbers are easy to repeat.
Explaining them properly takes more work.
A national salary figure may hide large geographic differences. Rising weekly earnings can reflect changes in hourly pay, hours worked, or both. A higher-paying city can become considerably less attractive after housing and other local costs enter the calculation.
I created Salary Data Index to get beyond the headline number without turning every article into an economics lecture.
I want you to leave with a clearer idea of what a statistic measures, where it comes from, and what it can reasonably tell you.
Numbers are the starting point.
The interesting part is figuring out what is happening behind them.