Title
Five things you should know about cost overrun
Author
Flyvbjerg, Bent (University of Oxford)
Ansar, Atif (University of Oxford)
Budzier, Alexander (University of Oxford)
Buhl, Søren (Aalborg University)
Cantarelli, Chantal (University of Sheffield)
Garbuio, Massimo (University of Sydney)
Glenting, Carsten (Viegand Maagøe A/S)
Holm, Mette Skamris (Aalborg Municipality)
Lovallo, Dan (University of Sydney)
Lunn, Daniel (University of Oxford)
Molin, E.J.E. (TU Delft Transport and Logistics) 
Rønnest, Arne (Esrum Kloster and Møllegård)
Stewart, Allison (Infrastructure Victoria)
van Wee, G.P. (TU Delft Transport and Logistics)
Date
2018
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.
Subject
Agency
Behavioral science
Cost forecasting
Cost overrun
Cost underestimation
De-biasing
Deception
Delusion
Moral hazard
Optimism bias
Reference class forecasting
Root causes of cost overrun
Strategic misrepresentation
To reference this document use:
http://resolver.tudelft.nl/uuid:d3e0c917-2038-4a46-8968-7522e41736af
DOI
https://doi.org/10.1016/j.tra.2018.07.013
Embargo date
2019-02-12
ISSN
0965-8564
Source
Transportation Research. Part A: Policy & Practice, 118, 174-190
Bibliographical note
Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
Part of collection
Institutional Repository
Document type
journal article
Rights
© 2018 Bent Flyvbjerg, Atif Ansar, Alexander Budzier, Søren Buhl, Chantal Cantarelli, Massimo Garbuio, Carsten Glenting, Mette Skamris Holm, Dan Lovallo, Daniel Lunn, E.J.E. Molin, Arne Rønnest, Allison Stewart, G.P. van Wee