|Legal skirmishes continue over whether the detailed employee pay data collection scheme (on top of the original basic employee census data) should be enforced. In 2017, the Trump administration suspended the EEOC-1 Component 2 data collection rules, which originated during the Obama Administration. But, in March 2019, a federal court held that those rules should go into effect anyway. |
The federal court decision is currently being appealed. In the meantime, the Equal Employment Opportunity Commission (EEOC) gives employers the following helpful reminders regarding the pay data collection rules:
Component 1 data. This refers to basic employee census information that’s been required for many years. Data for calendar year 2018 was due on May 31, 2019.
Component 2 data. This covers employee hours worked and W-2 wage numbers for a dozen pay brackets by gender, race and ethnicity. The EEOC says employers should begin preparing to submit this data for the 2017 and 2018 calendar years by September 30, 2019. The EEOC plans to open its server to data uploads by mid-July.
On the EEOC Radar
In general, the new EEOC-1 rules will require employers with at least 100 employees to submit detailed Component 2 data. Gearing up to submit this type of data involves more than a simple accounting exercise. Back in 2016, the EEOC described its reason for requesting this data as “to support the EEOC’s pay discrimination investigations.”
Processing the data electronically will make it easier for the EEOC to quickly spot red flags. But what data might catch the attention of the EEOC?
The EEOC has published aggregated national employment demographic patterns based on the basic Component 1 data from the EEO-1 form. One approach to determine whether you’re an outlier that might draw EEOC scrutiny is to simply benchmark your workforce against that data. You can find the numbers on the EEOC’s website (EEOC.gov) in the employment statistics area.
Component 1 data for 2017 has already been posted. If you crunch the numbers, you’ll see that under the heading of “first/mid-level officials and managers” the following national ethnic proportional breakdown:
2017 National Breakdown of First/Mid-Level Officials and Managers
| Demographic|| Percentage|
| White men|| 46%|
| White women|| 29%|
| Black men|| 4%|
| Black women|| 4%|
| Hispanic men|| 5%|
| Hispanic women|| 3%|
| Asian men|| 5%|
| Asian women|| 3%|
Additional Component 1 data is also available for the following categories of workers:
- Executive/senior-level officials and managers,
- Sales workers,
- Office and clerical workers,
- Craft workers,
- Laborers, and
- Service workers.
How does your workforce compare to the data published on the EEOC data website? If you vary from these norms, it could raise a red flag.
To get a clearer picture of how an EEOC analyst might evaluate your company, you’d want to research data based on your industry sector, size and geographic location. If your employee demographics (including pay data) seems outside of the norms, the next step is to conduct a “pay practices self-audit.” There are plenty of outside experts who specialize in performing these audits.
Also think about what kind of data might be subject to discovery, should you wind up with a lawsuit. Information exchanged with attorneys who do this kind of work could be protected from external review by the attorney-client privilege.
When looking just at pay data, you can also crunch some of your own numbers to get a first look at your profile. For example, Glassdoor (an employment search and review website) provides a simple formula you can use to look for potential gender-based pay discrimination. It involves comparing the average pay for all the women on your payroll with the equivalent number for men.
Dividing the women’s average pay by the men’s gives you what Glassdoor calls “unadjusted gender pay gap.” You may have a gender discrimination problem if this metric shows that, on average, women in your organization earn 80% of the amount that men earn. However, if the number turns out to be 120%, you might have a different kind of discrimination problem on your hands.
The second part of the calculation is adjusting the gender pay gap ratio for nondiscriminatory factors that influence pay. Examples of these factors include:
- Disproportionate gender representation in a particular job category,
- Differences in tenure, and
- Differences in education.
What’s even more important than crunching the numbers is how you respond to any anomalies. If you identify an unjustifiable pay disparity and don’t follow up with a plan to address it, you could be in more hot water than if you never poked around in the first place.
Having pay and employment patterns that are demographically out of the norm for similar employers isn’t conclusive evidence that you’re engaged in illegal discrimination. But if you do find yourself with such a profile and it doesn’t make sense to implement big changes in your pay or hiring policies, be ready to demonstrate why your policies aren’t discriminatory.
The EEOC-1 Component 2 data collection rules would likely increase the chances of EEOC inquiry into your pay and hiring practices. Right now, it’s uncertain whether these rules will be shot down on appeal. But, with the tentative implementation deadline looming, it’s prudent to start gathering the requisite data for 2017 and 2018, as well as to consider conducting a self-audit to unearth and possibly remedy any potential red flags. Contact your financial and HR professionals for more information.