PLAYBOOK
Tailoring Your Pay Equity Audit to Workforce Size
and Resource Availability
Conducting effective pay equity audits requires choosing the right statistical methods and techniques for your organization's size and resources. This overview will introduce you to pay equity audit methodologies for various organization types, from small organizations on tight budgets, all the way up to the largest employers that require large-scale, in-depth statistical modeling.
Understand Your Needs, Know Your Budget and Resource Constraints
Limited resources are a common barrier to achieving pay equity. However, according to Gail Greenfield, EVP of Pay Equity and Total Rewards Strategy and Solutions at Trusaic, there are a range of solutions that can accommodate different budgets and capabilities. Peek into what these approaches might look like, from the least resource-intensive on the left to the most resource-intensive on the right.
Do-It-Yourself Approach
Go through the free online tools highlighted in this playbook and find low-barrier downloadable checklists from pay equity organizations that address your specific needs.
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Limited
Budget
Seek budget-friendly software solutions that provide basic guidance and walk you through the process, but allow you to work at your own pace. Lean on peers' recommendations.
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Specialized Advice
Zero in on specific needs or challenges you're facing, such as job evaluations or data analysis. Engage consultants for focused tasks to leverage their expertise within your budget constraints.
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Full-service Consulting
If resources permit, expert consultants can provide comprehensive evaluations, ongoing support, and customized strategies tailored to your organization's unique needs.
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Choosing the Right Statistical Method For You
There is no universally applicable, one-size-fits-all method to measure pay equity. Every pay equity audit is different and needs to be tailored to your organization. Scroll down for an overview of some commonly-used methods.
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Multivariate Regression: Analyzing Large Employee Groups
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This regression analysis is well-suited for large, diverse employee groups (30 or more, with at least 5-10 members in subgroups). It examines multiple factors like experience, education, and job duties simultaneously, comparing how they influence pay across different groups. By isolating each factor's impact, it reveals any unexplained pay gaps potentially attributable to gender, race, or other protected characteristics.
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Descriptive Analysis: Analyzing Small Employee Groups
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When employee numbers are too small for regression analysis, employers can still check for pay fairness using simpler tools like averages, medians, and correlations. This descriptive approach looks at one key factor at a time, like job role or experience, and compares it to pay.
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Cohort Study: Analyzing Small Employee Groups
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A cohort study tracks protected characteristics such as gender, race, and ethnicity by comparing employees hired around the same time in similar roles. This reveals whether one group starts at higher pay, receives raises faster, or reaches higher pay grades compared to others in the same cohort over time.
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Comparative Ratios: Analyzing Small Employee Groups
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A comparative ratio, also known as a compa-ratio, measures an employee's pay relative to the median compensation for similar positions within the company or target market. Compensation professionals commonly use this formula to assess the competitiveness of an employee's pay level.
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