Compensating Your Employees Fairly

Written by an econometrician who consults on pay equity for Fortune 500 companies and government agencies, Compensating Your Employees Fairly demystifies the statistical and legal machinery behind internal pay equity. It walks employers, HR professionals, and legal counsel through the full arc of a compensation review: framing fairness in terms of organizational justice, understanding the legal theories of disparate treatment and disparate impact, mastering the mechanics and pitfalls of multiple regression analysis, building clean data sets and defensible similarly situated employee groupings, choosing among competing regression model structures, running alternative statistical tests, and following up on flagged disparities to make lawful compensation adjustments. It situates all of this within a rapidly changing enforcement landscape (the Ledbetter Fair Pay Act, the National Equal Pay Enforcement Task Force, the proposed Paycheck Fairness Act) and closes with a business case for proactive self-analysis as a litigation-avoidance and competitive-advantage strategy.

What it argues

Compensating Your Employees Fairly

Key ideas it contributes

• Compensation Policy Clarity and Objectivity — The degree to which pay decisions are governed by consistent, well-articulated, documented, objective criteria rather than arbitrary or discretionary judgment, and communicated transparently to employees.
• Compensation Data Quality and Completeness — The accuracy, consistency, comprehensiveness, and machine-readability of employee-level compensation and determinant data, including cradle-to-grave employment histories used as the foundation for statistical analysis.
• Similarly Situated Grouping Validity — The correctness with which employees are grouped for comparison based on similar work, responsibility levels, skills, and qualifications, so that only appropriate peers are compared in the analysis.
• Statistical Analysis Rigor — The methodological quality of the compensation review, including proper model specification, testing of regression assumptions, choice of appropriate model structure and statistical tests, and correct interpretation of results.
• Detected Pay Disparity — The estimated difference in compensation associated with protected group status or with peer comparison after controlling for legitimate determinants, evaluated for statistical and practical significance.
• Follow-Up Investigation and Remediation — The thoroughness of investigating flagged disparities to identify legitimate explanations and the lawful adjustment of compensation to correct genuine inequities without reducing anyone's pay.
• Perceived Compensation Fairness — Employees' perceptions of the fairness of pay outcomes and the procedures used to determine them, encompassing distributive and procedural (and relatedly informational) justice.
• Litigation and Regulatory Exposure — The organization's vulnerability to employment-practices lawsuits and regulatory investigations alleging compensation discrimination, and the associated financial and reputational exposure.
• Retention, Engagement, and Productivity Outcomes — Organizational outcomes attributed to internal pay equity, including employee retention, reduced absenteeism, engagement, motivation, productivity, and competitive advantage in attracting talent.