• Understand and explain key terms, definitions, concepts, theories and models about IT project management challenges covered in the course.
• Present a clear and coherent argument for your choice of relevant theories and models including their advantages and limitations in the analysis of project management challenges.
• Apply the selected key terms, definitions, concepts, theories and models in a systematic analysis of project management cases.
• Discuss and reflect on practical and theoretical implications for IT project management resulting from the analysis of cases.
• Produce a clear and meaningful narrative that follows academic writing conventions; e.g.; proper references, a clear structure, and well articulated arguments.

Complexity in contemporary project management

The context and conditions of contemporary IT software and systems are complex and constantly changing. While traditional large scale (in house or vendor based) monolithic projects are still carried out, today's software and systems development range from small phone apps to large complex inter-organizational systems, and from embedded software to standard products. Projects may involve several teams and vendors from different continents. At the same time, development paradigms, principles, and practices have evolved from the traditional waterfall over agile to current explorations into continuous delivery and deployment.

Project and program managers must have a holisitic understanding of the organizational, technical, and cultural context and challenges in order to navigate in this complex context.

The course builds on the students' knowledge about basic project management concepts, techniques and challenges, and discusses current project and program management challenges and dilemmas. The aim of the course is to improve the students' ability to become reflective project managers in multiple contexts and settings. 

The course seeks to further students knowledge about the root causes of complexity, the human element in IT project management and how time and resources constraints are implicating the possibilities to handle project complexities. 

The course aims to strengthen both the academic and explanatory capacity as well as introducing hands on, practical means to deal with salient issues.   

The literature can be changed before the semester begins. Students are advised to consult the syllabus on Canvas before buying any materials.

The course readings primarily consist of research articles and case descriptions.

• Andrews, Thomas D. Using Project Complexity Determinations to Establish Required Levels of Project Rigor. United States.
• Cool, K., Dierickx, I., & Costa, L. A. (2012). Diseconomies of time compression
• Drummond, H. (2017). Megaproject Escalation of Commitment: An Update and Appraisal. In The Oxford Handbook of Megaproject Management. Oxford University Press
• Gerster, D., Dremel, C., Conboy, K., Mayer, R., & vom Brocke, J. (2021). How Fujitsu and Four Fortune 500 Companies Managed Time Complexities Using Organizational Agility. MIS Quarterly Executive, 20(2), 127–150.
• Henningsson et al. (2022) Time compression management in Information System projects: Learning from the Maersk-Hamburg Sud acquisition integration
• Hoda, R., & Murugesan, L. K. (2016). Multi-level agile project management challenges: A self-organizing team perspective. Journal of Systems and Software, 117, 245-257.
• Keil, M., & Robey, D. (1999). Turning around troubled software projects: An exploratory study of the deescalation of commitment to failing courses of action. Journal of Management Information Systems, 15(4), 63-87.
• Mahring, M., Keil, M., Mathiassen, L., & Pries-Heje, J. (2008). Making IT project de-escalation happen: An exploration into key roles. Journal of the Association for Information Systems, 9(8), 462–496.
• Moe, N. B., Dingsøyr, T., & Dybå, T. (2010). A teamwork model for understanding an agile team: A case study of a Scrum project. Information and software technology, 52(5), 480-491.
• Morcov, S., Pintelon, L. ., & Kusters, R. . (2021). Definitions, characteristics and measures of IT project complexity - a systematic literature review. International Journal of Information Systems and Project Management, 8(2), 5–21.
• Nieto-Rodriguez, A. (2021). The Project Economy Has Arrived Use these skills and tools to make the most of it. Harvard Business Review, 99(6), 38-45
• O’Connor, M., Conboy, K., & Dennehy, D. (2023). Time is of the essence: a systematic literature review of temporality in information systems development research. Information Technology & People (West Linn, Or.), 36(3), 1200–1234.
• Omar, M., Alaidaros, H., & Romli, R. (2020). An improved software project monitoring task model of Agile Kanban method: A practitioners’ perspective. International Journal on Advanced Science, Engineering and Information Technology, 10(2), 548-554.
• Snowden, David J. & Boone, Mary E. (2007). A Leader’s Framework for Decision Making. The Magazine (November)
• Sommer, A. F., Hedegaard, C., Dukovska-Popovska, I., & Steger-Jensen, K. (2015). Improved Product Development Performance through Agile/Stage-Gate Hybrids: The Next-Generation Stage-Gate Process? Research Technology Management, 58(1), 34–45
• The five core IT shifts of scaled agile organizations. Quentin Jadoul, Dániel Róna, Arsen Storozhev, and Alexander Sukharevsky. April 15, 2021. McKinsey Insights
• Thesing, T., Feldmann, C., & Burchardt, M. (2021). Agile versus waterfall project management: decision model for selecting the appropriate approach to a project. Procedia Computer Science, 181, 746-756. Published.
• Wendler, R. (2014). Development of the organizational agility maturity model. Federated Conference on Computer Science and Information Systems, 1197–1206