75 Kellogg Insight how could you design an experiment to demonstrate that link, given your existing capabilities and constraints? And keep in mind that the infrastructure this requires may be quite dif - ferent from what is necessary for managing much of the big data that flows through an organization. For instance, the high-level dashboards that senior leaders are used to may not be capable of distinguishing among many subtle but important differences in when a campaign was rolled out, for instance, or how a delivery route was established. “It’s a very different thought process in terms of how you would actually build an IT system to support experimentation,” says Anderson. Thus, rather than try to outsource this work to a dedicated data-science team—or worse, a single piece of software—Anderson and Zettelmeyer recommend that firms train managers on how to think and ask ques- tions about data. “It requires a working knowledge of data science,” says Zettelmeyer. “This is a skill set that managers need in order to even be conscious that this is something they need to take charge of.” Featured Faculty Eric T. Anderson , Professor of Marketing at Kellogg Florian Zettelmeyer , Nancy L. Ertle Professor of Marketing at Kellogg Learn more from Eric Anderson and Florian Zettelmeyer in our Executive Education programs . Based on insights from Eric T. Anderson and Florian Zettelmeyer