Allegations of workplace discrimination against a federal regulator have unleashed another round of debates on disparate impact – the controversial legal doctrine that uses statistics to prove an employer’s bias. But some experts say the debate is misguided, since available facts on the case aren’t at all indicative of disparate impact.

Industry leaders and litigators have been crying foul since last month, when an American Banker report revealed that performance evaluations at the Consumer Financial Protection Bureau favored white employees. The CFPB has often wielded disparate impact in suits against auto lenders, so observers have revelled in the "irony" of it all.

“When it comes to disparate impact, is the CFPB attempting to impose a standard on others that that they seemingly are unable to meet themselves?” asked Congressman Jeb Hensarling of the Republican party, which has dismissed disparate impact as a viable legal doctrine.

But others across the aisle in congress, namely Democrat Maxine Waters, have heralded the case as proof that "disparate impact exists" and is a crucial way of rooting out unintentional discrimination.

Disparate Impact vs. Disparate Treatment

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Citing confidential agency data, American Banker reported that white employees at CFPB were twice as likely to receive top scores on performance reviews compared to their African American or Hispanic colleagues. The article spawned a House Financial Services sub-committee hearing, which heard testimony from a disgruntled CFPB employee and an outside investigator.

But as committee members discussed the merits of disparate impact, employment attorney Cynthia Calvert was confused. The allegations against the CFPB seemed to have little, if anything, to do with disparate impact, she said.

"In order to have a disparate impact case," Calvert said, "you have to be pointing to a policy that’s facially neutral but that impacts a protected category more strongly."

The classic example, she says, is a pre-employment screening test that isn't justified by "business neccessity." If an employer asks prospective hires to prove their ability to lift 50 pounds, even though the job requires them to lift no more than 15 pounds, then the test is inadvertently "screening women out," said Calvert.

In that case, the discrimination is unintentional – caused by a flawed policy or test. But the CFPB case doesn't seem to involve a flawed test. More likely with performance evaluations, it is the bias of supervisors conducting the tests that causes the disparate results.

"I can think of ways that an evaluation instrument might be biased, but honestly it involves stretching my imagination," said Calvert, who added that the allegations against the CFPB would fit better in a disparate treatment case.

Calvert, whose firm Workforce 21C advises employers on HR matters, is not directly involved with the CFPB situation and noted that she had not seen the format of the evaluations in question.

The confusion around the case could stem from the fact that the American Banker revelations revolved around statistics. But as Calvert said, "when you're proving disparate impact, you use statistics. It doesn’t mean that any time you have statistics, you have disparate impact."

Former CFPB enforcement attorney Ronald Rubin, who has written on the subject for the Wall Street Journal, agreed with Calvert's assessment.

“The disparate impact doctrine is about whether the hiring test or performance review process itself is flawed because it unintentionally produces lower ratings for minorities or women,” said Rubin, a partner at Hunton & Williams LLP. “If your managers are intentionally discriminating, that’s a different issue.  Any performance review process run by racist managers is going to produce disparate results.”

How to Avoid Bias in Performance Evaluations

In advising clients on how to limit racial, ethnic or gender bias in staff evaluations, Calvert says the first step is always to "recognize that bias exists."

Bias frequently appears in evaluations because they are inherently reliant on supervisors – all of whom carry their own set of assumptions.

"Those assumptions affect what we notice and what we remember and what we expect from people," she said. But Calvert said there are a few simple ways to block those biases from entering into the performance evaluation.

1. Restructure the evaluation forms. When an evaluator has to give a numerical rating, it's based on a gut feel. "And a gut feel is influenced by bias almost by definition," said Calvert. So she recommends structuring the forms so the evaluator must first write comments about the employee before choosing what score to give.

" If you put the comments first, that slows the evaluator down," she said. "He or she has to think through the exact examples that are going into that rating."

2. Use evidence-based comments. Evaluators should avoid vague comments, since broad statements are more likely to be influenced by assumptions and perceptions. Instead of saying "John has troubled meeting deadlines," the evaluator would be better off writing "John was late on submitting three assignments this quarter."

3. Use more than one evaluator. Forcing multiple evaluators to sit down together makes it less likely for bias to enter into the  discussion. "Studies show that if you have to justify what you’re saying, you slow down and make sure what you’re saying is supportable," Calvert said.

4. Be on the look-out. Frequently measuring the results of all evaluations will make an employer better suited to notice if bias is skewing outcomes. In the CFPB case, the union requested the agency to produce a report on performance evaluations by gender, race and ethnicity.