I remember I once read in Wikipedia about a law stating that the actual delivering time will always be 4 times less to 4 times more from the estimated time, even when you aware that law and know every detail in the project. What is that concept so I can look it up again?
It sounds like the Cone of Uncertainty. The idea is that at the beginning of a project or effort, there is enough uncertainty that estimates are generally in the range of being 4x over or 1/4 of the time it will take to complete. As the project progresses, these uncertainties begin to be resolved or better understood and the range of estimation becomes better.
Steve McConnell writes about this concept in Rapid Development and Software Project Survival Guide. It's also discussed on the Construx (McConnell's company) website. The idea in software development, however, originated with Barry Boehm in Software Engineering Economics.
Cone of Uncertainty
Research in the software industry on the Cone of Uncertainty stated that in the beginning of the project life cycle (i.e. before gathering of requirements) estimates have in general an uncertainty of factor 4 on both the high side and the low side (Boehm 1981). This means that the actual effort or scope can be 4 times or 1/4 of the first estimates.
There is also a more generic law which emphasizes
even when you aware that law part:
Hofstadter's Law: It always takes longer than you expect, even when you take into account Hofstadter's Law.
Other related tendencies listed at the end of the optimistic bias page: illusion of control, illusory superiority, normalcy bias, positivity bias, reference class forecasting, self-serving bias, wishful thinking.
The three-step protocol for managing optimism bias and the planning fallacy:
- Identify an appropriate reference class (e.g., school building project, IT project, family room addition, etc.).
- Obtain the statistics of the referenced class (e.g., percentage by which expenditures exceeded budget, project delays, cost per square foot, etc.). Use this objective research to generate a baseline prediction.
- If, despite your disciplined efforts, you believe optimism bias is still at play, adjust the baseline prediction as necessary.