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Where data-driven decision making can go wrong

Where data-driven decision making can go wrong

The problem

When managers are presented with internal data or an external study, they too often automatically accept its accuracy and relevance to their business or dismiss it outright.

Why it happens

Managers mistakenly confuse causation with correlation, underestimate the importance of sample size, focus on the wrong outcome, misjudge generalizability, or overemphasize a specific outcome.

The right approach

Leaders should ask probing questions about the evidence in a rigorous discussion of its utility. They should create a psychologically safe environment so that participants feel comfortable offering different points of view.

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