Metacognition at work
Kruger and Dunning (1999) showed that the lowest performers in a domain tend to overestimate their level: the skills needed to do well are the same skills needed to judge one's own performance. Applied to a project, a novice is unaware of the range of invisible complications (technical dependencies, surprises, acceptance phases) and proposes estimates that are too short.
Conversely, the most competent people tend to slightly underestimate their relative standing, because they assume that what feels easy to them is easy for others. Contrary to a popular belief, the model does not say that experts overestimate risks.
A caveat: part of this effect may be a statistical artifact (Gignac & Zajenkowski, 2020). Treat it as a rule of thumb for caution, not as a law.
The planning fallacy
Kahneman and Tversky (1979) described the planning fallacy: we build our estimate on the ideal scenario of the current project (the "inside view"), ignoring the statistics of comparable projects (the "outside view"). Buehler, Griffin and Ross (1994) later showed that this bias persists even when people know about their past overruns.
Three practices to correct course
- Planning poker: each member estimates in secret, then everyone reveals at once and the team discusses the gaps. Collective estimation neutralizes individual overconfidence and anchoring (see for example Mahnič & Hovelja, 2012).
- Three-point estimation (PERT): expected duration = (Optimistic + 4 × Most likely + Pessimistic) / 6. With 2, 4 and 12 days you get (2 + 16 + 12) / 6 = 5 days, not 4 (Malcolm et al., 1959).
- History over intuition: plan from the speed actually observed over previous cycles.
In FluidOps
Estimate your cards in effort points in Scrum sprints, then let velocity (the points actually completed per sprint) become your forecast capacity. Compare planned and actual in the analytics. To learn how to split and estimate, try the Scrum demo.
Sources
- Kruger, J., & Dunning, D. (1999). Unskilled and unaware of it: How difficulties in recognizing one's own incompetence lead to inflated self-assessments. Journal of Personality and Social Psychology, 77(6), 1121-1134. doi:10.1037/0022-3514.77.6.1121
- Gignac, G. E., & Zajenkowski, M. (2020). The Dunning-Kruger effect is (mostly) a statistical artefact: Valid approaches to testing the hypothesis with individual differences data. Intelligence, 80, 101449. doi:10.1016/j.intell.2020.101449
- Kahneman, D., & Tversky, A. (1979). Intuitive prediction: Biases and corrective procedures. TIMS Studies in Management Science, 12, 313-327 (reprinted in Judgment under Uncertainty, Cambridge University Press, 1982, pp. 414-421). doi:10.1017/CBO9780511809477.031
- Buehler, R., Griffin, D., & Ross, M. (1994). Exploring the "planning fallacy": Why people underestimate their task completion times. Journal of Personality and Social Psychology, 67(3), 366-381. doi:10.1037/0022-3514.67.3.366
- Malcolm, D. G., Roseboom, J. H., Clark, C. E., & Fazar, W. (1959). Application of a technique for research and development program evaluation. Operations Research, 7(5), 646-669. doi:10.1287/opre.7.5.646
- Mahnič, V., & Hovelja, T. (2012). On using planning poker for estimating user stories. Journal of Systems and Software, 85(9), 2086-2095. doi:10.1016/j.jss.2012.04.005