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Double Whammy - How ICT Projects are Fooled by Randomness and Screwed by Political Intent

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  • Alexander Budzier
  • Bent Flyvbjerg

Abstract

The cost-benefit analysis formulates the holy trinity of objectives of project management - cost, schedule, and benefits. As our previous research has shown, ICT projects deviate from their initial cost estimate by more than 10% in 8 out of 10 cases. Academic research has argued that Optimism Bias and Black Swan Blindness cause forecasts to fall short of actual costs. Firstly, optimism bias has been linked to effects of deception and delusion, which is caused by taking the inside-view and ignoring distributional information when making decisions. Secondly, we argued before that Black Swan Blindness makes decision-makers ignore outlying events even if decisions and judgements are based on the outside view. Using a sample of 1,471 ICT projects with a total value of USD 241 billion - we answer the question: Can we show the different effects of Normal Performance, Delusion, and Deception? We calculated the cumulative distribution function (CDF) of (actual-forecast)/forecast. Our results show that the CDF changes at two tipping points - the first one transforms an exponential function into a Gaussian bell curve. The second tipping point transforms the bell curve into a power law distribution with the power of 2. We argue that these results show that project performance up to the first tipping point is politically motivated and project performance above the second tipping point indicates that project managers and decision-makers are fooled by random outliers, because they are blind to thick tails. We then show that Black Swan ICT projects are a significant source of uncertainty to an organisation and that management needs to be aware of.

Suggested Citation

  • Alexander Budzier & Bent Flyvbjerg, 2013. "Double Whammy - How ICT Projects are Fooled by Randomness and Screwed by Political Intent," Papers 1304.4590, arXiv.org.
  • Handle: RePEc:arx:papers:1304.4590
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    References listed on IDEAS

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    7. Zhang, G. Peter & Keil, Mark & Rai, Arun & Mann, Joan, 2003. "Predicting information technology project escalation: A neural network approach," European Journal of Operational Research, Elsevier, vol. 146(1), pages 115-129, April.
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