The Empirical Reality of IT Project Cost Overruns: Discovering A Power-Law Distribution

成果类型:
Article
署名作者:
Flyvbjerg, Bent; Budzier, Alexander; Lee, Jong Seok; Keil, Mark; Lunn, Daniel; Bester, Dirk W.
署名单位:
University of Oxford; IT University Copenhagen; University of Oxford; University of Tennessee System; University of Tennessee Knoxville; University System of Georgia; Georgia State University; University System of Georgia; Georgia State University; University of Oxford
刊物名称:
JOURNAL OF MANAGEMENT INFORMATION SYSTEMS
ISSN/ISSBN:
0742-1222
DOI:
10.1080/07421222.2022.2096544
发表日期:
2022
页码:
607-639
关键词:
information-systems RISK-MANAGEMENT MODEL PERSPECTIVE adaptation mitigation modularity BEHAVIOR product forest
摘要:
If managers assume a normal or near-normal distribution of Information Technology (IT) project cost overruns, as is common, and cost overruns can be shown to follow a power-law distribution, managers may be unwittingly exposing their organizations to extreme risk by severely underestimating the probability of large cost overruns. In this research, we collect and analyze a large sample comprised of 5,392 IT projects to empirically examine the probability distribution of IT project cost overruns. Further, we propose and examine a mechanism that can explain such a distribution. Our results reveal that IT projects are far riskier in terms of cost than normally assumed by decision makers and scholars. Specifically, we found that IT project cost overruns follow a power-law distribution in which there are a large number of projects with relatively small overruns and a fat tail that includes a smaller number of projects with extreme overruns. A possible generative mechanism for the identified power-law distribution is found in interdependencies among technological components in IT systems. We propose and demonstrate, through computer simulation, that a problem in a single technological component can lead to chain reactions in which other interdependent components are affected, causing substantial overruns. What the power law tells us is that extreme IT project cost overruns will occur and that the prevalence of these will be grossly underestimated if managers assume that overruns follow a normal or near-normal distribution. This underscores the importance of realistically assessing and mitigating the cost risk of new IT projects up front.
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