Friday, May 30, 2014

California Supreme Court Concludes That Statistical Sampling May Be Permitted To Establish Class Liability If Certain Conditions Are Met: Duran v. United States Bank Nat'l Ass'n.

On May 29, 2014, the California Supreme Court issued its opinion in Duran v. United States Bank Nat'l Ass'n., __ Cal.4th ___  (2014) [2014 Cal. LEXIS 3758], concluding that the statistical sampling methodology used by the court to adjudicate employer “liability” was error, and as such, required reversal of the judgment entered in favor of the class.  Importantly, the Court did not find that the use of statistical sampling to establish issues of liability was itself improper (it actually held that it may be permitted), but rather, merely held that the sampling model adopted by the trial court in this particular case employed a flawed methodology:
After certifying a class of 260 plaintiffs, the trial court devised a plan to determine the extent of USB's liability to all class members by extrapolating from a random sample. In the first phase of trial, the court heard testimony about the work habits of 21 plaintiffs. USB was not permitted to introduce evidence about the work habits of any plaintiff outside this sample. Nevertheless, based on testimony from the small sample group, the trial court found that the entire class had been misclassified. After the second phase of trial, which focused on testimony from statisticians, the court extrapolated the average amount of overtime reported by the sample group to the class as a whole, resulting in a verdict of approximately $15 million and an average recovery of over $ 57,000 per person.
As even the plaintiffs recognize, this result cannot stand. The judgment must be reversed because the trial court's flawed implementation of sampling prevented USB from showing that some class members were exempt and entitled to no recovery. A trial plan that relies on statistical sampling must be developed with expert input and must afford the defendant an opportunity to impeach the model or otherwise show its liability is reduced. Statistical sampling may provide an appropriate means of proving liability and damages in some wage and hour class actions. However, as outlined below, the trial court's particular approach to sampling here was profoundly flawed.
Slip Opinion, at 1-2.

As summarized by the Court, the overarching issue concerned the “management” of individualized issues in a certified class action.  Specifically, the trial court’s inflexible administration of the flawed sampling methodology was deemed to have “ignored” – rather than “managed” – the individualized issues presented by a core element of the employer’s outside sales exemption defense:
This appeal highlights difficult questions about how individual issues can be successfully managed in a complex class action. After reviewing the requirements of the outside salesperson exemption, we discuss the trial court's obligation to consider the manageability of individual issues in certifying a class action. In particular, we hold that a class action trial management plan must permit the litigation of relevant affirmative defenses, even when these defenses turn on individual questions.  Next, we explain how the trial court ignored individual issues here, hamstringing USB's ability to defend itself.  Finally, we describe the flaws in the trial plan's implementation of statistical sampling as proof of USB's  liability to the class.
Slip Opinion, at 18-19.

As explained by the Court, a proposal to establish liability using statistical evidence must be assessed at the certification stage to ensure that individualized issues are “manageable” – an assessment the trial court failed to undertake in this case:
In general, when a trial plan incorporates representative testimony and random sampling, a preliminary assessment should be done to determine the level of variability in the class. (See post, at p. 40.)  If the variability is too great, individual issues are more likely to swamp common ones and render the class action unmanageable.  No such assessment was done here. With no sensitivity to variability in the class, the court forced the case through trial with a flawed statistical plan that did not manage but instead ignored individual issues.
Slip Opinion, at 28-29.

Rather than assessing the manageability of the individualized issues presented by the outside sales exemption, the trial court used the statistical model to overcome the problematic “individualized” element of the exemption defense, and in so doing, substantively altered the law to permit class-adjudication:
Although the trial court‘s certification decision was apparently influenced by Sav-On, supra, 34 Cal.4th 319, the court overlooked our advisements about the need to manage individual issues in a class action. Although we found substantial evidence of common issues supporting certification in that misclassification case, we also articulated an important caveat: “Unquestionably, . . . defendant is entitled to defend against plaintiffs’ complaint by attempting to demonstrate wide variations in the types of stores and, consequently, in the types of activities and amounts of time per workweek the [class members] in those stores spent on different types of activities.” (Id. at pp. 329-330.)  In rigidly adhering to its flawed trial plan and excluding relevant evidence central to the defense, the court here did not manage individual issues. It ignored them.
We have long observed that the class action procedural device may not be used to abridge a party’s substantive rights. “Class actions are provided only as a means to enforce substantive law. Altering the substantive law to accommodate procedure would be to confuse the means with the ends—to sacrifice the goal for the going.” (City of San Jose v. Superior Court, supra, 12 Cal.3d at p. 462.) 
Slip Opinion, at 29-30.

As aptly stated by the Court, “Class actions do not create a ‘requirement of common evidence.’ Instead, class litigation may be appropriate if the circumstances of a particular case demonstrate that there is common evidence.”  See Slip Opinion, at 33.  Thus, for example, a theory which seeks to establish class-wide liability using an employer’s standardized employment policies is an appropriate candidate for certification because “[i]n such a case, the evidence for uniformity among class members would be strong, and common proof would be sufficient to call for the employer to defend its claimed exemption.”  See id., at 34-35.  In stark contrast, however, the Court makes clear that it would be inappropriate to use statistical sampling to artificially “manufacture predominate common issues where the factual record indicates none exist.”  See id., at 26-27.  Statistical sampling cannot be used to end-run such defects.  As held by the Court, “[s]tatistical methods cannot entirely substitute for common proof” as “[t]here must be some glue that binds class members together apart from statistical evidence.”  See id., at 26.

Importantly, the Court rejected the argument that an employer has a due process right to litigate a defense individually as to each and every class member [Slip Opinion, at 35 (“No case, to our knowledge, holds that a defendant has a due process right to litigate an affirmative defense as to each individual class member”)], but it also held that a trial court may not use this fact as a basis to eliminate individualized challenges when statistical methods are used to establish liability.  As explained by Justice Liu, “because [statistical] methods are inherently designed to reveal generalized characteristics of a population, they pose the risk that a defendant’s affirmative defenses as to individual employees will not be properly adjudicated.” See Slip Opinion, at 8 (Liu Concurring).  As such, “[i]f trial proceeds with a statistical model of proof, a defendant accused of misclassification must be given a chance to impeach that model or otherwise show that its liability is reduced because some plaintiffs were properly classified as exempt.”  See id., at 35.  Moreover, “[i]f a defense depends upon questions individual to each class member, the statistical model must be designed to accommodate these case-specific deviations.” See id., at 38.   However, “[i]f statistical methods are ultimately incompatible with the nature of the plaintiffs’ claims or the defendant‘s defenses, resort to statistical proof may not be appropriate.”  See id.

In closing, it is important to highlight that while reversal in this case may be perceived as a defense victory, when viewed at the macro level it actually is not.  As the focus of the opinion (and especially Justice Liu’s concurring opinion) was to lay the framework for successfully using statistical modeling to adjudicate liability issues in future cases, the net result of the Court’s opinion actually lays the framework for expanding (as opposed to reducing) the grounds on which future cases may be certified.

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