Choosing the Right Compensation Data
This episode explains how compensation professionals and HR leaders can pick, judge, and use salary benchmark data when pricing jobs, especially in mid-market companies that have outgrown spreadsheets but are not ready for enterprise software. You will learn why pay data goes out of date so quickly, how to benchmark the full scope of a role instead of its title, how to handle title inflation, and how to price hybrid roles where one person does several jobs. The conversation also compares the strengths and weaknesses of traditional salary surveys, employee-reported pay data, and aggregated or predictive data sets, and covers what to do when a leader brings you a pay number generated by an AI tool. It closes with why executives still struggle to understand compensation, even though pay is often their largest expense.