Let’s say you need to lay off a significant number of your employees, you’ve consulted with managers about what positions to eliminate, and you have a list in hand of those slated for termination. But as an HR pro, you’re somewhere between a bit worried and absolutely terrified that this reduction in force will come back to haunt the company.
It may look to you as though there are too many women, or too many workers over age 40, or too many other protected-class members of some other kind on the list, and you fear a lawsuit for discrimination. Consider hiring a forensic economist to analyze data about your chosen candidates for layoff and let you know of any potential hazards.
Experts in firms like the Center for Forensic Economic Studies can conduct a series of what they say are easily administered Chi-square and T tests that will answer a basic question: Is there a disproportionate percentage of protected-class members in the group chosen for layoff?
Data the economist would need are an employee ID number for each person, date of birth, gender, and Equal Employment Opportunity Commission race code. And if the test results do suggest some kind of discrimination, that isn’t the end of the story: Where the results can be explained based on performance ratings, seniority rankings, or some other nondiscriminatory factors, your choices can be defended in court.
We asked senior economist David Adams, of the Center for Forensic Economic Studies, to discuss the benefits of such testing. For example, when is a RIF too small to warrant tests? “If you plan to reduce the number of your employees by at least 10 percent, the testing will definitely be worthwhile,” said Adams. “We analyzed data on just 23 employees for a recent client. But if you’re laying off 5 percent or less of your workforce, test results may not be helpful.” Many small and mid-sized companies use the service, he noted, especially if they carry employment practices liability insurance and their insurance carrier requests the tests.
“When you have test results, you’ve raised the risks for plaintiffs in a class-action or disparate impact lawsuit, and you’ve mitigated the subjectivity that can govern the decisions of individual managers. It’s like an insurance policy,” comments Adams. For more from the center, see its website at www.cfes.com.
Tip: The same kinds of data analysis can help an organization to conduct its own self-audit for alignment with Office of Federal Contractor Compliance Programs requirements.