Recent Supreme Court Decision Will Likely Impact Damages in Large, Complex Actions

On March 22, 2016, the Supreme Court handed down its opinion in Tyson Foods v. Bouaphakeo, 136 S. Ct. 1036 (2016), addressing the question of when statistical sampling evidence may be used to establish class-wide liability.

In Tyson, a class of workers at one meat processing plant sued their employer under the Fair Labor Standards Act. The workers alleged that the company failed to pay them overtime compensation for time spent donning and doffing the workers’ protective garb. Since the employer did not maintain records of the time spent donning and doffing, the class of workers hired an expert to estimate the average time workers in various departments spent donning and doffing their gear.

Tyson Foods challenged the use of statistical sampling to prove liability under the FLSA. It contended that the variance in time spent donning and doffing by each individual worker rendered the sampling methodology too speculative to be reliable.

The Supreme Court affirmed the admission of the statistical sampling evidence and rejected a categorical exclusion of such evidence. Instead, the admission of statistical sampling evidence to show liability depends on a number of different considerations, including: (1) the extent to which the sampling methodology is reliable; (2) the claims of the underlying cause of action; (3) the purpose for which the evidence is introduced; (4) the harm to a defendant’s ability to litigate individual defenses to every claim against it; and (5) the availability of other, direct evidence.

The use of statistical sampling to establish liability or damages in large, complex actions is still very much a hotly contested issue. The fact that the Supreme Court declined to categorically exclude such evidence in the class action context may indicate a growing willingness on the part of courts to admit such evidence, provided it bears certain indicia of reliability. Certainly defendants should expect plaintiffs’ counsel to look for creative ways to use statistical sampling to prove liability or damages in large, complex actions. These may include not only class actions, but also antitrust, RICO, and False Claims Act actions, where there is alleged to exist an underlying universe of similar activities.