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Mass. federal court: statistical evidence of age discrimination could permit reasonable jury to find that company laid off employee because of his age

This week a federal court in Massachusetts ruled against Areva, Inc. in an age discrimination case. The court held that a reasonable jury could determine that Areva laid off Farrokh Seifaee because of his age. Seifaee was 61 years old at the time of his termination in October 2013.

Seifaee worked for Areva as an engineer and had worked for the company, and its corporate predecessors, for 25 years at the time of his termination. Areva terminated Seifaee as part of a reduction in force (RIF) that it instituted to save money because of the company’s financial problems. To decide who Areva wanted to lay off, the company rated employees based on criteria such as current and past evaluations of each employee and the employee’s critical or unique skills. Based on these criteria, Areva ranked Seifaee 130th on the list of 136 employees considered for layoff. Areva laid off 14 employees, including Seifaee. Of the 14 employees laid off, all were older than 55 and 12 were older that 60.

Seifaee’s lawyer presented the opinion of an expert who performed a statistical analysis on Areva’s layoff. The expert found that the statistical disparity in the RIF “clearly supports a claim of age bias.” Seifaee’s lawyer also presented, among other things, evidence that Areva retained employees younger than him who had performance problems and less unique skills and experience than him.

In ruling against Areva, the court reasoned that “the mere fact alone that a supposedly objective process could look across a company at 136 employees and happen by chance to select an entire cohort of persons aged 55 or older for termination, while possible, seems statistically improbable (as Seifaee’s expert contends) and that alone might justify a verdict in Seifaee’s favor.”

This case demonstrates how statistical evidence can help to reveal discriminatory bias. When it appears that an employer has disproportionately selected employees in a protected category, like age, for lay off, statistical analyses can tell you how likely that disparity was merely a product of chance. If the odds that the disparity was a product of chance are slim enough, it is reasonable to conclude that the employer terminated the employees in the protected category because of their protected trait.