HANNAH BATES: Welcome to HBR On Strategy, case studies and conversations with the world’s top business and management experts, hand-selected to help you unlock new ways of doing business.
Fueled by the promise of concrete insights, organizations are now more than ever prioritizing data in their decision-making processes. But it can go wrong. Many leaders don’t understand that their decisions are only as good as how they interpret the data.
Today, Professor Michael Luca of Johns Hopkins Carey Business School and Professor Amy Edmondson of Harvard Business School will share a framework for making better decisions by interpreting your data more effectively. You’ll learn how to tell if the data you’re collecting is relevant to your goal, how to avoid some common traps of misusing data, and how to synthesize internal and external data.
This episode originally aired on HBR IdeaCast in August 2024. Here it is.
CURT NICKISCH: Welcome to the HBR IdeaCast from Harvard Business Review. I’m Curt Nickisch.
You’re a business owner and you’re interested in reaching out to new customers. You know that data is important. I mean, that’s clear, right? So you put out a survey into the field asking what kinds of products your ideal customers are looking for. You get that data back and you have a clear decision made for you as to which direction to go. You develop and sell that new product with a big marketing push behind it and it flops. But how can the data be wrong? It was so obvious. Today’s guests believe in data, of course, but they see major ways in which over reliance or under reliance on studies and statistics steer organizations wrong.
Whether it’s internal or external data, they found that leaders often go to one of two extremes, believing that the data at hand is infallible or dismissing it outright. They’ve developed a framework for a better way to discuss and process data in making business decisions, to interrogate the data at hand.
Michael Luca is a professor at Johns Hopkins Carey Business School, and Amy Edmondson is a professor at Harvard Business School. They wrote the HBR article “Where Data-Driven Decision-Making Can Go Wrong.” Welcome. Thanks so much to both of you.
AMY EDMONDSON: Thanks for having us.
MIKE LUCA: Thank you.
CURT NICKISCH: So are business leaders relying too heavily on data to make decisions?
AMY EDMONDSON: I don’t think that’s quite the problem. One of the things that really motivated Michael and me to get together is that I study leadership and leadership conversations particularly around really difficult, important decisions. And Michael is a data science expert. And our mutual observation is that when leadership teams an…
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This episode was produced by Mary Dooe, and me Hannah Bates. Ian Fox is our editor. Special thanks to Maureen Hoch, Erica Truxler, Ramsey Khabbaz, Nicole Smith, Anne Bartholomew, and you – our listener. See you next week.
