Outcome bias is the tendency to judge the quality of a decision primarily by its outcome rather than by the information available at the time the decision was made.

• A. Judging a decision based on outcomes rather than information available at decision time
• B. Evaluating a decision solely on the accuracy of its forecast
• C. Assuming future results will mimic past success
• D. Overestimating how long a task will take

Answer: (A)

Outcome bias shows up when we judge how good a decision was by the result it produced, rather than by the information and options available at the moment the decision was made. This matters because the outcome can be heavily influenced by luck, randomness, or external factors beyond what the decision-maker could control. Evaluating a decision only by its outcome rewards favorable luck and can unfairly penalize well-reasoned choices that didn’t turn out as hoped. Understanding this helps you focus on the quality of the decision process—the data considered, assumptions made, and alternatives weighed—rather than just the final result. For example, a plan might succeed because market conditions favored it, making the decision look brilliant even if the reasoning was solid but contingent on favorable luck; conversely, a sound decision can look poor if the outcome is unlucky. Other options describe related ideas—forecast accuracy focuses on predictive performance, not the decision context; assuming future results will mirror past success is a different bias; and overestimating how long a task will take points to the planning fallacy.