Ten Behavioral Biases in Project Planning and Management: An Overview by Bent Flyvbjerg ¹ ²

1 University of Oxford, Oxford, UK   2 IT University of Copenhagen, Copenhagen, Denmark

Bent Flyvbjerg is among the world’s foremost analysts of public project planning and management shortcomings. His research shows persuasively that there are multiple, repeated behaviors that have consistently resulted in high public works project cost overruns, demand estimate shortfalls and benefit overstatements. He has compiled a comprehensive history of over 2,000 projects on which he bases his findings and conclusions.

Read more here

Flyvbjerg’s findings are particularly relevant with the recent passage of the U.S. Infrastructure Investment and Jobs Act, commonly referred to as the $1.2 trillion Infrastructure Bill. The bill will disperse billions of dollars to state and local governments to fix crumbling bridges, repair roads, transit systems, airports, water and sewage works and expand broadband internet access and more.

Bay Area project planners, managers and funding agencies would be well advised to carefully study and learn from Flyvbjerg’s work to avoid the disastrous outcomes that have plagued so many of its earlier projects. The Bay Area has well over 100 projects planned or underway at this time. Plan Bay Area 2050 envisions transportation initiatives at a cost of $578 billion with many transit and rail megaprojects. The opportunities for diverting funds to projects of secondary importance, overly optimistic ridership projections, cost overruns, unnecessary delay and poor project execution abound.

Flyvbjerg argues there are ten most important behavioral biases in project planning and management that are likely to trip up project planners and managers. These biases negatively impact project outcomes and if the biases are not identified and dealt with up front it is inevitable that history will repeat itself. The Table below lists these critical biases. His evidence shows cognitive bias is only half the story; political bias is the other half.

  1. Strategic misrepresentation: The tendency to deliberately and systematically distort or misstate information for strategic purposes. Aka political bias, strategic bias, or power bias.
  2. Optimism bias: The tendency to be overly optimistic about the outcome of planned actions, including overestimation of the frequency and size of positive events and underestimation of the frequency and size of negative ones.
  3. Uniqueness bias: The tendency to see one’s project as more singular than it actually is.
  4. Planning fallacy: (writ large) The tendency to underestimate costs, schedule, and risk and overestimate benefits and opportunities.
  5. Overconfidence bias: The tendency to have excessive confidence in one’s own answers to questions.
  6. Hindsight bias: The tendency to see past events as being predictable at the time those events happened. Also known as the I-knew-it-all-along effect.
  7. Availability bias: The tendency to overestimate the viability of a project or other conditions based upon easily retrievable information. That which is more recent in memory is commonly over-weighted.
  8. Base rate fallacy: The tendency to ignore generic base rate information and focus on specific information pertaining to a certain case or small sample.
  9. Anchoring: The tendency to rely too heavily, or “anchor,” on one trait or piece of information when making decisions, typically the first piece of information acquired on the relevant subject.
  10. Escalation of commitment: The tendency to justify increased investment in a decision, based on the cumulative prior investment, despite new evidence suggesting the decision may be wrong. Also known as the sunk cost fallacy.

Underestimated costs + Overestimated benefits = Funding


“In situations with high political and organizational pressures, forecasters, planners, and decision-makers often resort to Machiavellian methods to make their projects look good on paper”


For those interested in greater detail, Flyvbjerg’s recent research is available at

https://journals.sagepub.com/doi/10.1177/87569728211049046
Project Management Journal Dec 2021, Vol. 52(6) 531–546

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