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Confirmation Bias in Data Analysis: Seeing What You Want to See

Thomas DavenportHarvard Business Review11 min readAugust 16, 2021
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Summary

Even data-driven organizations fall prey to confirmation bias when analysts seek, interpret, and remember data that supports pre-existing beliefs while ignoring contradictory evidence. Davenport's research shows that teams given the same dataset reach conclusions aligned with their prior hypotheses 73% of the time. The article prescribes adversarial analysis practices, blind data exploration, and red team reviews that systematically challenge analytical conclusions before they inform decisions.

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