General Mills Builds Up Big Data to Answer Big Questions

Wayde Fleener likes solving real-world problems, which led him into what we now call Big Data analytics. He started out on a different path, studying chemical engineering at the University of Minnesota. But he realized he didn’t want to go on for a PhD because it would mean a career in research, and he wanted to do applied work. After a stint in investment banking in Asia, Fleener went to a loyalty marketing agency.

Fleener, 36, still remembers the day when a colleague came to him and said a name, “big data,” had been coined for what they were doing. “We called it decision science,” he says. After working on programs for the consumer packaged goods industry, he found himself intrigued by the challenges they face, as companies indirectly connected to their consumers. He came to General Mills in mid-2013, becoming a senior manager/data scientist in its 200+-person Consumer Insights group, a unit of marketing comprised largely of researchers. He spoke with MIT Sloan Management Review contributing editor Michael Fitzgerald.

What did General Mills want in a data scientist for its marketing group?

The leader for consumer insights, Jeanine Bassett [vice president of Global Consumer Insights at General Mills] was concerned about how much of our decision making was based on outside research. She wanted more decision making based on our intuition and utilizing the data we had in-house. She wanted us to become less reliant on research. During the whole interview process, they said, “We need someone to really help us to answer these questions, about what we think we know.” So I came in to get after the data that we had internally and how we could benefit from it. And they gave me a lot of leeway.

Did they also give you a sense of urgency, of needing to get things done quickly?

Yes. They wanted everything as quickly as possible but not at the sacrifice of accuracy.