The United States District Court for the Western District of New York recently granted an early dismissal of a class action lawsuit prior to class certification. Mandala v. NTT Data, Inc., 18-CV-6591 CJS, 2019 WL 3237361, at *1 (W.D.N.Y. July 18, 2019). The plaintiffs in Mandala were two African-American men who applied for and were offered jobs with the defendant employer. After the employer conducted a criminal background check on the plaintiffs and found they each had a felony criminal conviction, the employer withdrew their job offers. The plaintiffs filed a class action lawsuit against the employer alleging claims for disparate impact race discrimination under Title VII, and violations of New York state laws prohibiting criminal history discrimination and regulating the background check process.
According to the plaintiffs, the employer’s criminal background check policy for job applicants illegally discriminated against African-American job candidates. The plaintiffs alleged that the employer had a “policy and practice of denying job opportunities to individuals with certain criminal convictions” such as felonies. As a result, the plaintiffs claimed that “because African Americans interact with the criminal justice system at much higher rates than Whites, [the employer’s] policy and practice of denying individuals with convictions job opportunities creates a disparate impact on African Americans in violation of Title VII.” In support of their argument, the plaintiffs relied on statistics from the U.S. Department of Justice and the Federal Bureau of Investigation, among other sources.
The employer filed a motion to dismiss alleging that the plaintiffs failed to state a claim under Title VII because they improperly based their disparate impact claim on general population statistics. First, the employer argued that the plaintiffs’ claim failed because they did not specify whether the statistics cited reflected misdemeanor crimes, felonies, or both. Second, the employer argued that “to use general population statistics to create an inference of disparate impact, the general populace must be representative of the relevant applicant pool,” and the plaintiffs did not indicate whether the general population statistics they cited reflected individuals who had qualifications that would make them viable job candidates.
The court agreed with the employer and found that the plaintiffs failed to allege that the employer’s policy of refusing to hire convicted felons was “related to the statistical disparity in the numbers of African Americans arrested and convicted of crimes in proportion to their representative numbers in the pool of qualified applicants.” Because general statistics showing that African Americans are statistically more likely to interact with the criminal justice system than Caucasians were “inadequate to show a relationship between the pool of applicants who are Caucasian versus African Americans and their respective rates of felony convictions,” the court dismissed the plaintiffs’ class action lawsuit before they could even attempt to certify a class.
Although Mandala is a win for employers, employees and job applicants can still rely on statistical data to show disparate impact discrimination in other contexts. The court distinguished Mandala from a sex discrimination case in which the Supreme Court found that reliance on general population demographic data was permissible when “there was no reason to suppose that physical height and weight characteristics of Alabama men and women differ markedly from those of the national population.” So, employers should continue to be mindful of the possibility of disparate impact discrimination when implementing hiring and employment policies.