Over five years ago, the U.S. Equal Employment Opportunity Commission (EEOC) took a significant step toward uncovering pay inequities across American workplaces.

Their 2017–2018 EEO-1 Component 2 data collection initiative aimed to highlight salary disparities by capturing demographic and pay data, sparking an essential dialogue on pay equity.

Despite encountering pushback from some employer groups due to logistical and administrative complexities, the findings illuminated the scope of wage gaps across gender, race, and ethnicity, particularly in fields where men disproportionately occupy higher-paying roles.

With this data now public, the EEOC is re-evaluating its strategy to ensure future collections are even more insightful and actionable. In a rapidly changing workplace landscape where transparency and fair pay have become core concerns for employees, HR leaders and organizations alike, a structured, accessible approach to pay data collection could become instrumental in guiding compensation decisions.

As the agency prepares for the next phase, HR professionals have a critical opportunity to utilize pay equity insights to foster a culture rooted in fairness, transparency, and compliance.

In this piece, we’ll delve into the key findings of the EEOC’s initial data collection, discuss the potential for renewed efforts, and explore how HR can harness these insights to drive meaningful change.

Key Insights from Component 2 Data Collection

The EEOC’s initial Component 2 data collection from 2017 and 2018 brought to light pronounced pay disparities across U.S. industries, with systemic inequities evident in both gender and racial demographics. The following insights provide a closer look at the numbers that reflect these disparities:

• Gender-based pay disparities: Women in the workforce, particularly women of color, predominantly occupied lower pay bands. In 2018, the median pay for women ranged between $30,600 and $38,900, while men’s median pay fell between $39,000 and $49,900—a significant gap highlighting gender-based pay inequity.
• Racial pay inequities: Black and Hispanic employees faced lower median pay than white employees across sectors. For instance, Hispanic women’s pay median fell in the $24,400 to $30,600 range, while white men saw median bands above $49,900, especially in higher-paying roles within finance and technology.
• Occupational segregation: Certain demographics showed heavy concentration in lower-paying positions. For example, 57% of workers in the lowest pay band in hospitality earned under $19,239 annually, with the majority of these roles filled by Black and Hispanic women.
• Leadership representation: In sectors where women made up a larger portion of the workforce, such as healthcare, men still held 66% of the highest-paying roles, underscoring a leadership gap even within female-dominated fields.
• High pay bands largely male: Men occupied nearly 80% of top pay brackets in industries like finance and tech. In the highest pay band (over $208,000 annually), men accounted for more than two-thirds of the workforce across multiple sectors.
• Intersectional disparities: Even within specific racial demographics, men consistently held higher-paying roles. Among Asian workers, men’s pay bands were on average 10% higher than women’s, showing a clear intersection of race and gender disparities.
• Essential sector gaps: Healthcare and retail, industries essential during the pandemic, exhibited some of the widest pay gaps. In healthcare, for example, the average pay band for frontline roles was 20% lower than managerial roles, where men held the majority of positions.
• Tech underrepresentation: In technology, a sector with higher overall median pay, white men overwhelmingly occupied the upper pay tiers, with women and minority groups comprising less than 25% of the highest bands.
• Lower pay bands across sectors: Jobs paying under $30,000 annually were often filled by women and people of color in fields like retail, food services, and healthcare support. These roles frequently went to workers of color, who faced limited upward mobility.
• Limited year-to-year progress: A comparison of the 2017 and 2018 data showed minimal shifts in representation within pay bands, indicating the persistence of structural pay inequities despite broader economic and social shifts.

These figures underscore the continued challenges in achieving equitable pay across the U.S. workforce and highlight actionable areas where HR leaders can begin to close these gaps.

By understanding the depth of disparities, HR teams are better equipped to advocate for fairer compensation practices and to implement targeted, data-driven policies that drive positive change.

The EEOC’s Updated Strategy and Its Potential Impact

Building on the insights from the initial Component 2 data, the EEOC is exploring ways to refine its approach, focusing on adjustments that improve both the usability and impact of future data collections. Here’s how these refinements could make a difference:

• Enhanced Data Specificity: By collecting individual-level information such as tenure and education, HR professionals will gain a more nuanced view of pay disparities, helping them identify systemic inequities more accurately.
• Streamlined Data Submission: Simplifying data collection to align with existing payroll systems can reduce administrative burdens, making it easier for companies to participate in future EEOC data efforts.
• Employer Benchmarking Tools: The EEOC aims to provide comparative insights to employers, allowing them to see how their pay structures align with industry standards. This benchmarking empowers organizations to address inequities proactively.
• Pay Band Refinements: Updating pay bands across roles and sectors allows for more precise data, ensuring that industries with varying compensation structures are accurately represented in analyses.

These refinements not only streamline processes for employers but also provide actionable data that can support more equitable pay structures. In fostering transparency, the EEOC’s updated data collection approach empowers HR teams to design compensation practices that support fair and competitive workplace environments.

Why collecting pay data can be transformative moving forward

By gathering detailed information on factors like tenure, educational background, and role-specific data, HR teams can analyze compensation patterns across all demographics more accurately. This granular insight empowers HR to pinpoint specific areas where disparities persist, helping create strategic plans that foster inclusivity and fair pay practices without broad, generalized approaches.

The EEOC’s role in supporting this data collection aligns with the broader movement towards pay transparency and equitable workplace practices.

As more states enforce pay transparency laws, organizations are expected to set clear standards and proactively address any visible gaps.

A structured data collection framework would provide HR departments with actionable insights, reducing uncertainty around compliance and helping organizations cultivate trust with their employees.

Ultimately, with the support of refined data practices, organizations can navigate these evolving expectations more effectively—balancing business goals with their commitment to equity, improving morale, and fostering a culture of transparency that resonates across the workforce..

What do you think?

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