In class action litigation, "ascertainability" is the foundation upon which a multi-billion dollar case stands or falls. To prove a class is valid, lawyers must demonstrate that the group is cohesive, similarly situated, and, most importantly, reachable. However, as the legal landscape becomes increasingly digital, the data required to identify these individuals is often fragmented, consisting of nothing more than isolated IP addresses or incomplete contact records.
In a recent appearance on the Technically Legal podcast, Covalynt’s Don Beshada sat down to discuss why relying on traditional administrative tools to bridge these data gaps is no longer enough. He highlights a cautionary tale: the Apple antitrust case. Despite a certified class with potential damages of $20 billion, the plaintiffs saw their case derailed because they relied on "napkin matching" rather than sophisticated data science. This led to glaring anomalies—such as identifying several hundred thousand claimants in an Alaskan town of only 500 people—which Apple’s legal team used to successfully move for decertification.
As Don explains in the clip above, the difference between a successful certification and a total loss often comes down to the tools you bring to the fight. In the Apple case, the plaintiffs went to war with a "water pistol" while the defense showed up with a "tank" fueled by data science. For legal teams, the takeaway is clear: engaging a data science partner early in the process has become a necessity. At Covalynt, we specialize in transforming fragmented data sets, ensuring that your class is as airtight as your legal argument.
