U.S. will begin collecting data for pay equity analysis
The Trump administration has failed to block an Obama-era pay reporting rule. Employers of more than 100 workers will have to submit data to U.S. authorities by Sept. 30.
The federal government plans to collect pay data by race, ethnicity and gender from businesses by Sept. 30. Any business with over 100 employees will have to provide this data. It will use it to develop a pay equity analysis to combat discrimination. President Donald Trump's administration failed to block this collection in federal court, clearing the path for this action.
Business groups have supported Trump's efforts to stop this reporting to the U.S. Equal Employment Opportunity Commission (EEOC). They have complained of technical challenges in bridging HR information systems with payroll data. The U.S. Chamber of Commerce said pay equity analysis reports will add "a total burden of $1.3 billion per year" on businesses.
Former President Barack Obama's administration approved the pay equity analysis data collection. It was reversed by Trump in 2017, with little explanation. The National Women's Law Center (NWLC) filed a lawsuit in response.
U.S. District Judge Tanya Chutkan recently ruled in favor of the NWLC, disagreeing with the Trump administration and its argument that the pay equity analysis data collection will have "disruptive consequences."
HR has been showing interest in pay equity analysis, along with antibias tools. Analysts recently identified antibias HR tools as a new and fast-growing market.
HR is adopting pay equity tools
Courtney PaulsenHR analyst, Alameda Electrical Distributors, an Alcal Industries company
Ultimate Software, for instance, which makes the UltiPro HR system, includes a pay equity analysis tool. It is used by Courtney Paulsen, an HR analyst at Alameda Electrical Distributers, an Alcal Industries Inc. mechanical, electrical and plumbing distributor and contractor in Hayward, Calif.
Paulsen said the pay equity tool helps the company see if it's fairly paying its workers. It also provides insights to managers when making pay recommendations, she said.
The tool puts data into a manager's hands, which can help managers reduce biases and make compensation recommendations or raises more than a gut-based decision, according to Paulsen. "It's bringing a lot of transparency to it," she said.
The pay tool can perform an analysis by gender, age and ethnicity. It helps examine whether a supervisor is favoring men or women, Paulsen said.
"You are looking for any sort of disparity," Paulsen said. The tool helps to make sure employee pay is equitable and "based on their experience in the role that they're in," she said.
Ultimate Software said it plans to release enhancements to UltiPro to meet the EEOC reporting rule. But it is still waiting on final specifications, which have not yet been provided by the EEOC, a spokeswoman said in an email. Ultimate Software plans to give its customers the ability to file the EEOC data based on requirements.
EEOC's mixed messages about readiness
Samuel Haffer, chief data officer at the EEOC, warned the court in testimony that undertaking this collection by the Sept. 30 deadline will raise "major data validity and reliability issues."
EEOC spokeswoman Kimberly Smith-Brown said the agency wouldn't be commenting on Haffer's testimony.
But the agency's acting chairwoman, Victoria Lipnic, said in a prepared statement that it could meet the court order. "We, at the EEOC, understand the difficulties of these first-ever pay data collections in this time frame," she said.
One person who works with workforce data, Carol Rogers, deputy director and CIO of the Indiana Business Research Center at Indiana University's Kelley School of Business, doesn't believe it will be difficult for employers to comply with the law.
Employers are already submitting some characteristics of their workforce to the EEOC. "It wouldn't seem that difficult to add pay," Rogers said. The pay data information is already submitted to the IRS, she said.
Collecting pay data may help uncover systemic problems in industries, whether people are overpaid or underpaid relative to each other, Rogers said. But the data won't necessarily help analysts understand, for instance, whether women who have babies are penalized relative to men, or whether men who become fathers get a bump in pay, Rogers said.
The data also isn't attached to a resume, so some information may be missing, Rogers said. Still, collecting pay data "may be able to spot a trend in a particular type of industry," and this industrywide data may be helpful for firms in improving talent attraction, she said.