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Five things you should know about cost overrun

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  • Flyvbjerg, Bent
  • Ansar, Atif
  • Budzier, Alexander
  • Buhl, Søren
  • Cantarelli, Chantal
  • Garbuio, Massimo
  • Glenting, Carsten
  • Holm, Mette Skamris
  • Lovallo, Dan
  • Lunn, Daniel
  • Molin, Eric
  • Rønnest, Arne
  • Stewart, Allison
  • van Wee, Bert

Abstract

This paper gives an overview of good and bad practice for understanding and curbing cost overrun in large capital investment projects, with a critique of Love and Ahiaga-Dagbui (2018) as point of departure. Good practice entails: (a) Consistent definition and measurement of overrun; in contrast to mixing inconsistent baselines, price levels, etc. (b) Data collection that includes all valid and reliable data; as opposed to including idiosyncratically sampled data, data with removed outliers, non-valid data from consultancies, etc. (c) Recognition that cost overrun is systemically fat-tailed; in contrast to understanding overrun in terms of error and randomness. (d) Acknowledgment that the root cause of cost overrun is behavioral bias; in contrast to explanations in terms of scope changes, complexity, etc. (e) De-biasing cost estimates with reference class forecasting or similar methods based in behavioral science; as opposed to conventional methods of estimation, with their century-long track record of inaccuracy and systemic bias. Bad practice is characterized by violating at least one of these five points. Love and Ahiaga-Dagbui violate all five. In so doing, they produce an exceptionally useful and comprehensive catalog of the many pitfalls that exist, and must be avoided, for properly understanding and curbing cost overrun.

Suggested Citation

  • Flyvbjerg, Bent & Ansar, Atif & Budzier, Alexander & Buhl, Søren & Cantarelli, Chantal & Garbuio, Massimo & Glenting, Carsten & Holm, Mette Skamris & Lovallo, Dan & Lunn, Daniel & Molin, Eric & Rønnes, 2018. "Five things you should know about cost overrun," Transportation Research Part A: Policy and Practice, Elsevier, vol. 118(C), pages 174-190.
    • Handle: RePEc:eee:transa:v:118:y:2018:i:c:p:174-190
    DOI: 10.1016/j.tra.2018.07.013
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    References listed on IDEAS

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    Cited by:

    1. Flyvbjerg, Bent & Ansar, Atif & Budzier, Alexander & Buhl, Søren & Cantarelli, Chantal & Garbuio, Massimo & Glenting, Carsten & Holm, Mette Skamris & Lovallo, Dan & Molin, Eric & Rønnest, Arne & Stewa, 2019. "On de-bunking “Fake News” in the post-truth era: How to reduce statistical error in research," Transportation Research Part A: Policy and Practice, Elsevier, vol. 126(C), pages 409-411.
    2. Love, Peter E.D. & Ika, Lavagnon A. & Ahiaga-Dagbui, Dominic D., 2019. "On de-bunking ‘fake news’ in a post truth era: Why does the Planning Fallacy explanation for cost overruns fall short?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 126(C), pages 397-408.
    3. Giuliano Marella & Valentina Antoniucci, 2019. "Time Overrun in Public Works—Evidence from North-East Italy," Sustainability, MDPI, Open Access Journal, vol. 11(24), pages 1-1, December.
    4. Penyalver, Domingo & Turró, Mateu & Williamson, John B., 2019. "Measuring the value for money of transport infrastructure procurement; an intergenerational approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 119(C), pages 238-254.
    5. Lozano, Jorge-Mario & Zuluaga, Santiago & Sánchez-Silva, Mauricio, 2020. "Developing flexible management strategies in infrastructure: The sequential expansion problem for infrastructure analysis (SEPIA)," Reliability Engineering and System Safety, Elsevier, vol. 200(C).
    6. Ginés de Rus & Javier Campos & Daniel Graham & M. Pilar Socorro & Jorge Valido, 2020. "Evaluación Económica de Proyectos y Políticas de Transporte: Metodología y Aplicaciones. Parte 1: Metodología para el análisis coste-beneficio de proyectos y políticas de transporte," Working Papers 2020-11, FEDEA.

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