Cited by 56Software Engineering Techniques and PracticesConstruction Project Management and PerformanceInformation Technology Governance and Strategy

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Mitigating risk of failure in information technology projects: Causes and mechanisms

Open access
Schmidt, Jens·2023·Project Leadership and Society

Abstract

This paper shows how causes and mechanisms behind past information technology (IT) project failures can be used for systematic risk mitigation in new IT projects. This is significant because successful IT projects are needed to realise the benefit potential of digitalisation, whereas failed IT projects overspend resources and underdeliver benefits. In this paper we a) identify factors and causes that lead to IT project failure, b) analyse the consistency over time of the identified factors and causes, c) expose mechanisms of failure by analysing failure factors, causes, and common features of IT projects, and d) show how this knowledge can be used in IT project risk evaluations. The paper uses hermeneutic literature review, statistical analysis of failure factors in the literature, content analysis of the reviewed literature, and process tracing.

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  • Preliminary observations and project documentation reveal several implementation issues in the Kelurahan Cantik project, including weak coordination of stakeholder requirements, unclear change control processes, limited risk mitigation efforts, and technology mismatches.

    “Preliminary observations and project documentation reveal several implementation issues, including weak coordination of stakeholder requirements, unclear change control processes, limited risk mitigation efforts, and technology mismatches (Kampermann et al., 2021;Schmidt, 2023).”

    From PROJECT MANAGEMENT CHALLENGES IN PUBLIC SECTOR IT: A CASE STUDY IN PALU (2026) · cites this paper as Schmidt, 2023

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Research works printed but not linked: 57

  1. Adzmi, 2018, A theoretical framework of critical success factors on information technology project management during project planning, Int. J. Eng. Technol., 7, 650, 10.14419/ijet.v7i4.35.23078 · DOI
  2. Ahimbisibwe, 2017, Empirical comparison of traditional plan-based and agile methodologies, J. Enterprise Inf. Manag., 30, 400, 10.1108/JEIM-06-2015-0056 · DOI
  3. Ayat, 2021, Current trends analysis and prioritization of success factors: a systematic literature review of ict projects, Int. J. Manag. Proj. Bus., 14, 652, 10.1108/IJMPB-02-2020-0075 · DOI
  4. Bhoola, 2018, Hr activities and practices for project success: a multi-method approach from indian it firms, Aust. J. Inf. Syst., 22
  5. Boell, 2014, A hermeneutic approach for conducting literature reviews and literature searches, Commun. Assoc. Inf. Syst., 34, 257
  6. Brown, 2001, Modernisation or failure? IT development projects in the UK public sector, Financ. Account Manag., 17, 363, 10.1111/1468-0408.00139 · DOI
  7. Bullen, 1981, A primer on critical success factors, Sloan WP, 69, 1220
  8. Cerpa, 2009, Why did your project fail?, Commun. ACM, 52, 10.1145/1610252.1610286 · DOI
  9. Charette, 2005, Why software fails, IEEE Spectrum, 42, 42, 10.1109/MSPEC.2005.1502528 · DOI
  10. Chiyangwa, 2017, Modelling the critical success factors of agile software development projects in South Africa, S. Afr. J. Inf. Manag., 19, 1, 10.4102/sajim.v19i1.838 · DOI
  11. Christensen, 2011, The big idea: the new m&a playbook, Harv. Bus. Rev., 89
  12. Chua, 2009, Exhuming it projects from their graves: an analysis of eight failure cases and their risk factors, J. Comput. Inf. Syst., 49, 31
  13. Cole, 1995, Runaway projects - cause and effects, Software World (UK), 26
  14. Davidsen, 2010, A longitudinal study of development and maintenance, Inf. Software Technol., 52, 707, 10.1016/j.infsof.2010.03.003 · DOI
  15. Dice, 1945, Measures of the amount of ecologic association between species, Ecology, 26, 297, 10.2307/1932409 · DOI
  16. El-Emam, 2008, A replicated survey of it software project failures, Software, IEEE, 25
  17. Flyvbjerg, 2006, Five misunderstandings about case-study research, Qual. Enq., 12, 219, 10.1177/1077800405284363 · DOI · Paper page
  18. Flyvbjerg, 2009, Survival of the unfittest: why the worst infrastructure gets built—and what we can do about it, Oxf. Rev. Econ. Pol., 3, 344, 10.1093/oxrep/grp024 · DOI
  19. Flyvbjerg, 2021, Top ten behavioral biases in project management: an overview, Proj. Manag. J., 52, 531, 10.1177/87569728211049046 · DOI
  20. Flyvbjerg, 2021, The cost-benefit fallacy: why cost-benefit analysis is broken and how to fix the cost-benefit fallacy: why cost-benefit analysis is broken and how to fix it, J. Benefit-Cost Anal., 12, 1, 10.1017/bca.2021.9 · DOI
  21. Flyvbjerg, 2011, Why your it project may be riskier than you think, Harv. Bus. Rev., 601
  22. Flyvbjerg, 2022, The empirical reality of it project cost overruns: discovering a power-law distribution, J. Manag. Inf. Syst., 39, 607, 10.1080/07421222.2022.2096544 · DOI
  23. Flyvbjerg, 2002, Underestimating costs in public works projects: error or lie?, APA J., 68, 279
  24. Fortune, 2006, Framing of project critical success factors by a systems model, Int. J. Proj. Manag., 24, 53, 10.1016/j.ijproman.2005.07.004 · DOI
  25. Fowler, 2007, Are information systems' success and failure factors related?: an exploratory study, J. Organ. End User Comput., 19, 1, 10.4018/joeuc.2007040101 · DOI
  26. Freund, 1988, Critical success factors, Plann. Rev., 16, 20, 10.1108/eb054225 · DOI
  27. Guo, 2019, Measuring information system project success through a software-assisted qualitative content analysis, Inf. Technol. Libr., 38, 53
  28. Ika, 2022, Moving beyond the planning fallacy: the emergence of a new principle of project behavior, IEEE Trans. Eng. Manag., 69, 3310, 10.1109/TEM.2020.3040526 · DOI
  29. Ika, 2022, The “re-meaning” of project success: updating and recalibrating for a modern project management, Int. J. Proj. Manag., 40, 835, 10.1016/j.ijproman.2022.08.001 · DOI
  30. Ika, 2022, The “re-meaning” of project success: updating and recalibrating for a modern project management, Int. J. Proj. Manag., 40, 835, 10.1016/j.ijproman.2022.08.001 · DOI
  31. Inal, 2015, Ensuring success in a large scale software project: an examination of the learning styles and characteristics of the potential end users, Gazi Univ. J. Sci., 28, 535
  32. Jones, 1995, Patterns of large software systems: failure and success, IEEE Computer, 28, 86, 10.1109/2.366170 · DOI
  33. Kappelman, 2006, Early warning signs of it project failure: the dominant dozen, Inf. Syst. Manag., 23, 31, 10.1201/1078.10580530/46352.23.4.20060901/95110.4 · DOI
  34. Keider, 1984, Why systems development projects fail, J. Inf. Syst. Manag., 1, 33
  35. Keil, 1998, A framework for identifying software project risks, Commun. ACM, 41, 76, 10.1145/287831.287843 · DOI
  36. Klein, 2020, Literature review expectations of project management journal®, Proj. Manag. J., 51, 239, 10.1177/8756972820916340 · DOI
  37. Love, 2022, Hundreds of years of pain, with minimal gain: capital project cost overruns, the past, present, and optimistic future, IEEE Eng. Manag. Rev., 50, 56, 10.1109/EMR.2022.3219362 · DOI
  38. Mackie, 1965, Causes and conditions, Am. Phil. Q., 2, 245
  39. Meier, 2008, Best project management and systems engineering practices in pre-acquisition practices in the federal intelligence and defence agencies, Proj. Manag. J., 39, 59, 10.1002/pmj.20035 · DOI
  40. Mughal, 2019, Behavioral factors for it project success in Pakistan: moderating effect of leadership styles, Manag. Sci. Lett., 9, 987, 10.5267/j.msl.2019.4.006 · DOI
  41. Müller, 2023, Changes in the editorial board of the project management journal, Proj. Manag. J., 54, 3, 10.1177/87569728221147654 · DOI
  42. Müller, 2015, The impact of relational norms on information technology project success and its moderation through project governance, Int. J. Manag. Proj. Bus., 8, 154, 10.1108/IJMPB-04-2014-0036 · DOI
  43. Myers, 1994, A disaster for everyone to see: an interpretive analysis of a failed is project, Account. Manag. Inf. Technol., 4, 185
  44. Packendorff, 1995, Inquiring into the temporary organization: new directions for project management research, Scand. J. Inf. Syst., 11, 319
  45. Paradies, 1988, Root cause analysis at savannah river plant, IEEE Conf. Hum. Fact. Power Plants, 479
  46. Pearson, 1895, Vii. note on regression and inheritance in the case of two parents, Proc. Roy. Soc. Lond., 58, 240
  47. Pinto, 2022, Coming to terms with project success: current perspectives and future challenges, Int. J. Proj. Manag., 40, 831, 10.1016/j.ijproman.2022.09.001 · DOI
  48. Pinto, 1990, The causes of project failure, IEEE Trans. Eng. Manag., 37, 269, 10.1109/17.62322 · DOI
  49. Pinto, 1987, Critical factors in successful project implementation, IEEE Trans. Eng. Manag. EM, 34
  50. Rockart, 1979, Chief executives define their own data needs, Harv. Bus. Rev., 81
  51. Schmidt, 2022, It project failure, termination, and the marginal cost trap, J. Mod. Project Manag., 10, 255
  52. Schmidt, 2001, Identifying software project risks: an international delphi study, J. Manag. Inf. Syst., 17, 5, 10.1080/07421222.2001.11045662 · DOI
  53. Sutton, 1995, What theory is not, Adm. Sci. Q., 40, 371, 10.2307/2393788 · DOI
  54. Trampusch, 2016, Between x and y: how process tracing contributes to opening the black box of causality, New Polit. Econ., 21, 437, 10.1080/13563467.2015.1134465 · DOI
  55. Weick, 1995, What theory is not, theorizing is, Adm. Sci. Q., 140, 385, 10.2307/2393789 · DOI
  56. Yaghoobi, 2018, Prioritizing key success factors of software projects using fuzzy ahp, J. Softw.: Evol. Process, 30
  57. Yeo, 2002, Critical failure factors in information system projects, Int. J. Proj. Manag., 20, 241, 10.1016/S0263-7863(01)00075-8 · DOI

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Metadata

Authors
Schmidt, J.
Affiliations
IT University of Copenhagen (DK)
Corresponding author
Schmidt, Jens
Venue
Project Leadership and Society
Publisher
Elsevier BV
Published
2023-12
Volume
4
Pages
100097
ISSN
2666-7215 (ISSN-L)
OpenAlex
W4386577622
Cited by
56
References
6
Citations by year
2026: 20 · 2025: 19 · 2024: 11 · 2023: 6
FWCI
10.30
Type
journal article
Language
en
Open access
Locations
  • Project Leadership and Society (publishedVersion, cc-by-nc-nd)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Econstor (Econstor) (submittedVersion, cc-by-nc-nd)
  • IT University Of Copenhagen (IT University of Copenhagen) (submittedVersion, cc-by-nc-nd)
Topics
  • Physical Sciences › Computer Science › Information Systems › Software Engineering Techniques and Practices
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Construction Project Management and Performance
  • Social Sciences › Business, Management and Accounting › Management Information Systems › Information Technology Governance and Strategy
Keywords
IT project failure, risk mitigation, failure causes, failure mechanisms, digitalization, IT project management

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