We’ve all been told that correlation does not imply causation. Yet many business leaders, elected officials, and media outlets still make causal claims based on misleading correlations. These claims are too often unscrutinized, amplified, and mistakenly used to guide decisions.
Leaders: Stop Confusing Correlation with Causation
We must learn to analyze data and assess causal claims — a skill that is increasingly important for business and government leaders. One way to accomplish this is by emphasizing the value of experiments in organizations. A large body of research in behavioral economics and psychology has highlighted systematic mistakes we can make when looking at data. We tend to seek evidence that confirms our preconceived notions and ignore data that might go against our hypotheses. We neglect important aspects of the way that data was generated. More broadly, it’s easy to focus on the data in front of you, even when the most important data is missing. This can lead to mistakes and avoidable disasters, whether it’s an individual, a company, or a government that’s making the decision.