Planning fallacy
The planning fallacy is the cognitive bias toward predicting that one's own task will take less time than past tasks of similar scope. Identified by Daniel Kahneman and Amos Tversky in 1979 and replicated extensively (Buehler, Griffin & Ross 1994 onwards), the bias persists even when people are explicitly aware of past overruns on their own work.
The standard fix in the bias literature is 'reference-class forecasting' — instead of imagining how this task will unfold, use the distribution of completion times from a reference class of comparable past tasks. In software, this typically means consulting your team's historical sprint data rather than imagining how long the new story will take. Software estimation is a textbook case of the planning fallacy: meta-analyses (Halkjelsvik & Jørgensen 2012, 200+ studies) put the average overrun at ~30% with no clear improvement over decades. Note that the planning fallacy is a within-person bias — it's not that people are bad at estimating others' tasks (they're often well-calibrated for that) but that they're overconfident about their own.
Related terms
- Cone of Uncertainty
The Cone of Uncertainty is a model of estimation variance over the lifecycle of a software project, first articulated by Barry Boehm in his 1981 book Software Engineering Economics.
- Calibration error
Calibration error is the gap between the confidence someone reports in a prediction and the empirical accuracy of those predictions.
- Story points
A story-point estimate is a unit-less measure of relative effort assigned to a user story.