A 59-year-old engineer who was fired during a companywide reduction in force (RIF) could not prove his individual claim of intentional age discrimination with statistical evidence that the RIF mostly impacted employees over age 50, a California appeals court ruled.
The employer operates a nonprofit federally funded research and development center that provides aerospace technical assessments to the federal government.
The employee, who has degrees in mathematics, computer science and engineering, was hired in 2007, when he was 55 years old, to work as a senior project engineer.
Over the course of his employment, his supervisors counseled him on deficiencies in his interpersonal and communication skills. He was warned that his failure to improve his performance in these areas could result in corrective action. The employee was also counseled for failing to comply with the company’s corporate travel policies and procedures on several occasions, although he was not formally disciplined for this.
According to the terms of a collective bargaining agreement, employees were assigned a value ranking based on their skills and performance. The managers would place the employees into five groups, known as “bins,” with bin 1 containing the highest-ranked employees and bin 5 containing the lowest. In 2010 and 2011, the employee was placed in bin 5.
In late 2011, the company learned that its funding would be significantly impacted by projected U.S. Department of Defense budget cuts. In response, the company initiated an RIF. The pool of eligible employees included those ranked in bins 4 and 5 in 2011, as well as new employees who were unranked.
The employee was placed in the RIF-eligibility pool because of his 2011 ranking in bin 5, and his managers then selected him for the RIF. The company did not hire anyone to replace the employee. Instead, his position was eliminated and his remaining duties were given to an existing employee who was 14 years younger than him.
The employee filed a complaint against the company, alleging age discrimination in violation of the California Fair Employment and Housing Act (FEHA), among other claims. He alleged that the company used the RIF as a pretext to hide its true and illegal motivation to fire him because of his age.
The trial court dismissed the action before trial, and the employee appealed.
Proving Intentional Bias
The appellate court first noted that the employer had presented evidence of a legitimate, nondiscriminatory reason for firing the employee. The company reduced its workforce after learning that its funding may have been significantly reduced, and the employee was selected for the RIF through the use of standardized criteria.
Therefore, the employee could prove discrimination only by showing that the employer’s stated nondiscriminatory reason for the adverse action was untrue, or by showing that the employer acted with a discriminatory motive.
The employee argued that he produced sufficient statistical evidence showing that the RIF had a severe impact primarily on workers who were age 50 or older.
The court rejected this claim and affirmed the trial court’s dismissal of the lawsuit. Statistics can be used to create an inference of intentional discrimination in an individual case, but they must show a significant disparity and must eliminate nondiscriminatory reasons for the apparent disparity, the court explained.
Here, the court said, the statistical evidence reflected the ages, genders and bin rankings of company employees before and after the RIF. It didn’t account for age-neutral factors that were considered in connection with the RIF, such as an employee’s experience, performance and the anticipated future need for the employee’s skills. Therefore, the statistical evidence did not eliminate nondiscriminatory reasons for any apparent disparities and did not meet the more exacting standard required to raise an inference of discrimination in an individual case alleging intentional discrimination, the court concluded.
Foroudi v. The Aerospace Corp., Calif. Ct. App., No. B291302 (Nov. 24, 2020).
Professional Pointer: Statistics are often important in proving a disparate-impact discrimination claim, which asserts that a neutral employer policy unintentionally has a disparate impact on a protected class of employees. For example, a weight-lifting requirement may disproportionately prevent women from performing a warehouse job. In such a case, the employer’s motive is not generally at issue. In this case, however, the worker alleged intentional discrimination, so he had to show evidence of the employer’s discriminatory motive for the claim to survive.
Joanne Deschenaux, J.D., is a freelance writer in Annapolis, Md.