Fueled by the promise of concrete insights, organizations are increasingly prioritizing data in their decision-making processes. But that process can easily go wrong. Many leaders don’t understand that their decisions are only as good as how they interpret the data.

In this episode, Professor Michael Luca of Johns Hopkins Carey Business School and Professor Amy Edmondson of Harvard Business School share a framework for making better decisions by interpreting data more effectively.

Luca and Edmondson are coauthors of the HBR article "Where Data-Driven Decision-Making Can Go Wrong."

Key episode topics include: Analytics and data, data management, data strategy, data analysis, organizational decision making, strategy

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