Last week’s post on the use of statistics in reduction in force cases garnered some interest from a fellow blogger, Stephanie Thomas. She argues on her blog that small sample statistics still have a place in workforce reduction litigation. After reading Stephanie’s take on this issue, we carried the conversation over to Twitter (Are you following me on Twitter @jonhyman? If not, shame on you).
My conclusion is that the Schoonmaker decision merely begs the question of how small of a sample size is too small to make pure statistics irrelevant in a RIF case. Stephanie and I agree that you will see more expert witness battles on the issue of whether a sample size is large enough to be statistically relevant.
If I’m defending a RIF, the first thing I’m doing is hiring a statistical expert to opine that the sample size is too small to be statistically significant. From there, I’ll argue that under Schoonmaker the case should be dismissed, unless the plaintiff can come forward with some “plus” evidence of discrimination.
Conversely, if a RIFed employee wants to rely on statistics alone, he or she will have to hire an expert to opine that the sample size is large enough to be statistically significant. If you have competing experts, you very well might have a factual issue over the sample size. Or, the judge could decide as a matter of law that the sample size is too small and toss out the statistics as irrelevant.
On my first read through Schoonmaker, I thought it gave concrete answers on a plaintiff’s prima facie requirements in a workforce reduction. After more deliberation, and a healthy Twitter debate with Stephanie Thomas, I’ve now concluded that Schoonmaker may create more questions than it answers.