The Importance of Statistical Evidence - Randall v Rolls Royce

Earlier this month, Hon. Sarah Evans Barker of the US District Court for the Southern District of Indiana denied certification of a putative gender discrimination class action.

Judge Barker's decision is notable not only due to the novel nature of  the class theory that she rejected, but also due to its thorough analysis of the competing statistical evidence before the court. The decision highlights the significance of powerful expert reports and testimony in class actions... (Morgan Lewis Labor and Employment lawflash)

Judge Barker's decision was heavily influenced by her examination of the competing statistical analyses offered by each party's expert. Her opinion stated that:

"if there is a dispute as to the value or applicability or efficacy of either side's expert statistical analysis, the way in which that dispute is resolved impacts both the underlying systemic discrimination claim and the determination of whether a viable class action exists."

In her opinion, Judge Barker acknowledged that the commonality requirement for class certification presents a "relatively low hurdle". According to the Morgan Lewis lawflash, she concluded that "the requirement was not met here, primarily because 'we do not find Dr. Drogin's [plaintiff's expert's] statistical analysis convincing.'" Judge Barker's decision then goes on to discuss a detailed analysis of the statistical evidence relating to the typicality requirement of Federal Rule 23(a) for class certification.

The discussion of statistical evidence in Randall is likely to be important for future class action claims in litigation. But the impact of Randall goes further - it has important implications for proactive analyses as well. Employers should review documentation of their compensation decisions to ensure that this documentation clearly captures the variables determining compensation. The Randall decision criticized the plaintiff's expert analysis for failure to account for fundamental variables determining compensation, such as pay grade. In the event of litigation, an employer will need not only a clearly articulated compensation policy, but also data points for the variables determining compensation. As part of a risk management plan, employers should plan for what information and data will be needed to defend a claim, and to ensure that this information and data is collected and maintained.

Why Employment Attorneys Should Care About Statistics

Why should employment attorneys care about statistics? In many cases, a lack of direct evidence or a "smoking gun" may mean that statistical analysis is the only evidence available. Attorneys with an understanding of these statistical analyses and the inferences drawn from these analyses are better positioned to advise their clients on the merits of the matter.

As noted by Bessey, Gilmartin and Stancavage in their paper "A Review of Statistical Books For Use In Employment Discrimination Lawsuits", this need is not satisfied by hiring an expert specializing in the use of statistics in employment discrimination matters. They state "[w]e are not advocating that these experts be replaced by technically sophisticated attorneys. Rather, we are arguing that attorneys will become more effective collaborators if they possess some knowledge of quantitative methods."

Bessey, Gilmartin and Stancavage make an excellent argument for why attorneys should have an understanding of quantitative methods:

"[T]rial attorneys who are knowledgeable about statistical methods are more effective during the pretrial preparation phase of a case, because they can take a more proactive stance when working with labor economists, industrial psychologists, and other experts to plan data collection, data analysis, and rebuttal activities. They understand what proof is needed for their case-in-chief and know that the analyses will be appropriate and provide them with the information they need. They can speculate about what analyses might be presented by the opposing side (and have their own expert carry out parallel analyses prior to rebuttal), and they can anticipate (and therefore prepare for) possible attacks on the analyses that they present. All of these activities lead to a more coherent and effective presentation at trial."

As an economic and statistical consultant specializing in employment issues, I couldn't agree more. While employment attorneys need not be quantitative experts in their own right, a basic familiarity with common statistical concepts and techniques as applied to law will allow them to better serve their clients and to participate in meaningful discussions with their experts.