A Practical Assessment of Modern IT Project Complexity Management Tools: Taming Positive, Appropriate, Negative Complexity

A Practical Assessment of Modern IT Project Complexity Management Tools: Taming Positive, Appropriate, Negative Complexity

Stefan Morcov, Liliane Pintelon, Rob J. Kusters
Copyright: © 2021 |Pages: 19
DOI: 10.4018/IJITPM.2021070106
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Complexity is ubiquitous in modern engineering and project management. It is traditionally associated with failure. Also, complexity works! It delivers functionality, creativity, innovation. Complexity management contributes to the success of high-risk IT projects, helps better project understanding, allows for better prioritization and planning of resources. Managing negative complexity reduces project risk. Positive and appropriate complexity are catalysts for opportunities. This paper is a qualitative longitudinal study based on multiple industry project cases, consisting in the repeated evaluation of a set of complexity management tools. The tools were deployed in a classical process framework: plan, identify, analyze, plan responses, monitor, and control. The evaluated tools red-flag and measure complexity, analyze its sources and effects, and plan mitigation strategies. The study aims to provide project managers with methods for increasing project success rates and reducing failure in complex IT project environments.
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Today’s engineering technology projects and products are larger, more complicated, difficult, complex. Project complexity strongly correlates with project failure, poor project management performance, and increased risk (Williams, 2005) (Patanakul, 2014) (Floricel, Michel, & Piperca, 2016) (Bjorvatn & Wald, 2018). IT projects have a high derail rate, with industry reports suggesting that only a handful are successful – between 16% and 31% (Standish Group, 1994) (Standish Group, 2014). While it is known that IT projects tend to have high-cost overruns on average, research shows that a surprisingly large number of IT projects incur massive cost and schedule challenges. In fact, one in six IT projects is expected to be “a black swan, with a cost overrun of 200%, on average, and a schedule overrun of almost 70%”. (Flyvbjerg & Budzier, 2011). A significant number of IT projects are reporting incredible losses: Levi Strauss’ SAP implementation was a $5 million project that led to an almost $200 million loss; the “Toll Collect” project cost Germany $10 billion in lost revenue; the overall losses incurred by underperforming IT projects in the US is estimated at $55 billion annually (Flyvbjerg & Budzier, 2011). When the European Commission finally launched the Schengen Information System (SIS II) in 2013, the project was more than 6 years late and 8 times more expensive than the initial estimate, at a final cost of €500 million (European Court of Auditors, 2014).

Research in IT project complexity is thus particularly relevant for today’s IT and software engineering environments. Complexity is a ubiquitous characteristic of contemporary engineering and project management. While complexity is traditionally associated with high-cost and high failure risk, the traditional approaches of simplifying and reducing complexity do not consider the essential benefits offered by technological and organizational complexity. We notice all around us that complexity works: it delivers advanced functionality to products such as smartphones, cars, spacecrafts; it supports innovation, creativity, adaptability and viability of organizations (Morcov, Pintelon, & Kusters, 2020b) (Maurer, 2017) (Bar-Yam, 2003) (Stacey, 1995). While significant contributions have been made to understanding project complexity, there is still a strong need for practical tools that enable identification and analysis of project complexity and associated strategies, and for validation of such proposed tools.

The objective of this paper is to analyze why, when,andhow specific tools for the management of IT project complexity should be applied, based on an assessment of their impact in practice. The evaluated tools were:

  • 1.

    Red-flagging and measuring complexity: 3 complexity measurement tools.

  • 2.

    Specialized tools for identification and analysis of complexity causes and effects, management, and mitigation of IT project complexity, designed and validated as part of a larger research project (Morcov, Pintelon, & Kusters, 2020b).

The research method was a longitudinal evaluation based on the application and repeated evaluation of the said tools, in several project cases, with a live assessment of their impact in the respective projects. The main research approach was qualitative. The tool deployment process followed a standard process composed of: planning, identification, analysis, response planning, and monitoring and control. The evaluated tools were deployed, tested, and evaluated repeatedly with multiple participants, over a period of 7 months. They were tested in a real project context, in conjunction with other typical IT project management tools.

The paper brings insights from the industry that support and enhance project complexity management theory, and aims to provide project managers with more efficient theoretical and practical tools for driving project management performance and project success.

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