Journal article icon

Journal article

The empirical reality of IT project cost overruns: discovering a power-law distribution

Abstract:
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.
Publication status:
Published
Peer review status:
Peer reviewed

Actions

Access Document

Publisher copy:
10.1080/07421222.2022.2096544

Authors

More by this author
Institution:
University of Oxford
Division:
SSD
Department:
Saïd Business School
Role:
Author


Publisher:
Taylor and Francis
Journal:
Journal of Management Information Systems More from this journal
Volume:
39
Issue:
3
Pages:
607-639
Publication date:
2022-08-26
Acceptance date:
2022-05-05
DOI:
EISSN:
1557-928X
ISSN:
0742-1222


Language:
English
Keywords:
Pubs id:
1264246
Local pid:
pubs:1264246
Deposit date:
2022-06-21
ARK identifier:

Terms of use


Views and Downloads






If you are the owner of this record, you can report an update to it here: Report update to this record

TO TOP