Those following employment law developments well know that the EEOC and OFCCP are both aggressively pursuing systemic discrimination cases and, whenever possible, are not limiting their focus to a particular employer establishment or geographic region, but rather are investigating employers for violations on a companywide basis. Following U.S. Supreme Court’s 2011 decision in Wal-Mart Stores, Inc v. Dukes (94 EPD ¶44,193) the use of “formula relief” — i.e. relief based on representative statistical evidence— in assessing and awarding damages for large groups of aggrieved workers appeared to have suffered a severe blow. However, the U.S. Supreme Court’s ruling earlier this week in Tyson Foods, Inc. v. Bouaphake, a wage-hour case, provides some leeway for formula relief in certain circumstances. As my colleague Ron Miller explained in his blog post on the Tyson Foods case, a divided Court ruled that a federal district court did not err in certifying (and maintaining) a class of Tyson employees who alleged that the employer failed to compensate them for time spent donning and doffing personal protective equipment. Because Tyson failed to keep records of this time, the employees primarily relied on a study performed by an industrial relations expert to determine the average time engaged in donning and doffing activities. The representative sample may have been the only feasible way to establish employer liability, the Court observed, in concluding that such evidence cannot be deemed improper merely because the claim is brought on behalf of a class. In contrast to Dukes, where the employees were not similarly situated, the employees in Tyson Foods, who worked in the same facility, did similar work, and were paid under the same policy, could have introduced the expert witness’ study in a series of individual suits. Of note, the Court also pointed out that the case presented no occasion for adoption of broad and categorical rules governing the use of representative and statistical evidence in class actions. Rather, the ability to use a representative sample to establish classwide liability will depend on the purpose for which the sample is being introduced and on the underlying cause of action. No doubt, the EEOC and the OFCCP will take full advantage of Tyson Foods ruling. Indeed, in a directive (No 310) issued in July 2013, entitled, “Calculating Back Pay as a Part of Make-Whole Relief for Victims of Employment Discrimination,” the OFCCP specifically details the use of the “formula relief” model in calculating back pay in systemic discrimination cases. The Directive reflects the agency’s broad interpretation of the circumstances in which formula relief may be used. According to the OFCCP, formula relief is a way of approximating losses in circumstances in which it is unrealistic to attempt to compute individual losses with accuracy, such as:
- When calculating individual back pay relief for numerous aggrieved individuals is difficult because complete information or documentation (i.e., timecards, payroll records, tax returns) is unavailable or missing;
- When using the individual relief model to calculate back pay for each class member will likely cause significant delay or create an undue burden on individual class members to provide documentation to support their compensation and/or interim earnings ;
- When the number of class members exceeds the number of employment opportunities that are available;
- When the reconstruction of the employment decision is speculative (e.g., in the instance when there are no lines of progression), which makes it difficult for the CO to determine at what specific stage in the employment process the adverse action actually occurred, or any other situation in which (especially for jobs with few minimum qualifications) it would be impossible to determine which class members would have been hired absent discrimination; and/or
- When the losses can be calculated on a class-wide basis from available data, as may be the case with compensation issues.
Interested in submitting an article?
Submit your information to us today!Learn More