Big (But Not Bad) Data and Merger Efficiencies

By Gregory P. Luib & Mike Cowie, Dechert

“Big data” has become one of the hottest subjects for antitrust enforcers around the globe. There is concern that large tech companies are amassing vast amounts of data and will use that data to entrench their dominant positions. With this emerging view, more data may be viewed as anticompetitive.

Yet, recent transactions such as CVS-Aetna (in which Dechert represented CVS) and AT&T-Time Warner show how the use of data can be procompetitive, reducing costs and benefitting consumers in the process. Under the right circumstances, big data can drive substantial merger efficiencies, a key showing in obtaining merger clearance.

What Is Big Data?

As a threshold matter, what is big data? There is no consensus definition, but big data is often described as having four key characteristics (the “four Vs”): Volume (i.e. size and scale), Velocity (i.e. rate at which it is generated), Variety (i.e. different types and forms), and Value.¹ Big data may be comprised of information that is provided by consumers or generated from such consumer information. It may be used to identify consumer preferences or to predict consumer behavior.

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