Statistical Evidence in Wage and Hour Class Actions: Impact on Certification and Trial

Description

The use of statistical evidence has long been part of complex wage and hour litigation and has evolved since the U.S. Supreme Court ruled against the employer in Tyson Foods Inc. v. Bouaphakeo, holding that statistical sampling was a permissible form of evidence that a jury may consider in determining hours employees worked and to establish classwide liability in an FLSA action.

In some cases, plaintiffs seek to use the testimony of a representative sample of employees to establish a prima facie case under the FLSA or state wage and hour statutes. As such, defense counsel may challenge the propriety of using statistical sampling and the soundness of any statistical methodology.

Plaintiffs may also attempt to use statistical sampling when the universe of data is not available, or no data is available, to establish liability and class-wide damages. When limited data is available (a sample), plaintiffs may apply inferential statistical analysis to prove/disprove classwide assertions provided the sample meets the criteria of being representative of the population. If no data is available, plaintiffs can utilize a survey of the class members to establish class-wide liability and damages.

Effective defense techniques include contesting whether the use of sampling would be appropriate under the framework established in Tyson Foods, challenging whether the sample used is representative, questioning surveys and their methodology, and arguing that a more individualized determination of liability and damages is required by the Rules Enabling Act or due process.

Listen as our distinguished panel reviews strategic approaches to disputing or leveraging statistical evidence in wage and hour class actions in light of Tyson Foods and its progeny. Our panel will discuss the uses of representative evidence and statistical sampling techniques relevant to wage and hour cases and offer best practices for plaintiff and defense counsel.