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Guide: Structure and check for pay equity

Identify variables to test

Choose variables for your pay equity analysis. These are examples of variables that could be included in a pay equity analysis. Control variables will vary depending on your compensation philosophy, the independent variable will be related to what you are checking for (in this case, gender equity), and the dependent variable will depend on how you pay your people (e.g., salary, bonus, stock). Control variables: job level, performance scores, seniority, work experience. Independent variable: gender. Dependent variable: pay ratio.

Now that you’ve established who or what you want to compare, you can identify the variables you want to test.

Your independent variable is what you are testing to see if it affects the dependent variable or outcome you care about. The dependent variable is the outcome measure you care about that might be affected by the control and independent variable(s). For a gender pay equity analysis, the independent variable is employee gender and the dependent variable is a pay outcome (e.g., salary).

Factors that should influence pay, as determined by your compensation philosophy, are your control variables. For example, your philosophy might mean that employees at a higher job level should receive more compensation or employees with lower performance ratings should receive lower compensation. Therefore, example control variables might include job level, performance, or work experience. It’s also important to consider whether any of your control variables could be influenced by bias, conscious or unconscious.

If your organization’s total pay package includes multiple types of compensation (e.g., salary, bonus, equity), analyze each piece separately as they may be influenced by different variables. Looking only at the magnitude of pay differences can create false alarm where differences are not statistically meaningful, and using pay ratios helps fix the absolute value problems of exchange rates, geographies, levels, etc.

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