Human Capital Management

Why Conduct a Pay Equity Analysis

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This article was written by Exude’s Edwina White and Jon White.

Conducting a Pay Equity Analysis

Pay equity on the minds of the public now more than ever. In a perfect world, every employee would be paid the same as their peer who does the same work, however, no matter how many laws and regulations are passed there are still gaps in the system. Gaps include women continuing to earn less than men, African Americans earning less than Caucasian coworkers for the same job roles, and discriminations still based around other things including age, national origin, or disability status. Even organizations that strive to pay equitably may have inequities because of biases from earlier years. Many of these disparities are the result of historic discrimination and there is no excuse for the continuation of them. In other words: there is work to be done.

Advantages of a Pay Equity Analysis

Many boards are making this pay equity a priority. The federal government requires its contractors to conduct these analyses and numerous states require employers also ensure that they are not discriminating against protected classes.  A pay equity analysis provides that insurance and can also insulate a firm from potential wage discrimination lawsuits based on its protected classes. They also help to identify systemic and individual equity issues so that they can be evaluated and addressed before their effects impact the entire company.

Do you have a pay equity problem?

A pay equity analysis is a statistical analysis designed to answer this important question and is the first step to begin implementing further regulations for your company’s equity. Salaries can vary for many reasons based on several variables including job responsibilities, tenure, education, prior experience, performance ratings, etc.  In evaluating pay equity, the analyst or statistician uses statistical methods that can identify the various factors that are correlated with salary differences.  Multiple linear regression is the gold standard statistical method to use in these situations.  The regression analysis tells us how large a role each of the standard reasons (job responsibilities, tenure, etc.) have in predicting compensation as well as other factors that should not have a role, such as race, age, and gender.

The idea behind this analysis is to weigh how much each factor in an employee’s professional background contributes to how much they are being compensated, and then to evaluate every employee based on these weights to ensure everyone is being compensated fairly. This is the best way to make sure all employees are being paid based on the same scale and that unethical practices against protected classes are being avoided.

Deliverables: What to Expect Out of Your Analysis

  1. Development of a statistical models specific to your firm that predict salary based on the standard variables as well as testing the impact of race, gender, and age. This model may provide:
    • Impact of the standard variables
    • Impact of the race, gender, and age
    • Predicted versus actual salaries
  2. A Distribution Analysis to determine if any adverse salary impacts on protected classes are caused by adverse distribution of standard variables. Of particular interest in there are the outliers- there may be salaries significantly different than those of the model predictions.  This can identify employees who may be underpaid as well as employees who may be overpaid. For example, lower average salaries for protected classes may be a result of protected classes being concentrated in lower paying job grades.  This analysis provides a thorough outline of who is getting paid what and exactly how it compares to others based on their professional backgrounds.

By conducting a pay equity analysis, you ensure the entirety of your workforce is being compensated on a fair basis with statistical methods to maintain it moving forward. Don’t continue to let pay discrepancies go unnoticed, contact us to strengthen your equity management today!