Skip to main content
SpringerLink
Log in

Risk reduction in a project portfolio

  • Published:
Journal of Systems Science and Systems Engineering Aims and scope Submit manuscript

Abstract

The positive impacts of managing projects as a portfolio are quantified by comparing the value of the integrated risk of a project portfolio and the aggregation of single project risks implemented separately. Firstly, the integrated risk is defined by proposing risky events based on set theory. Secondly, as projects interact with each other in a project portfolio, the integrated risk is evaluated by using a Bayesian network structure learning algorithm to construct an interdependent network of risks. Finally, the integrated risk of a practical case is assessed using this method, and the results show that the proposed method is an effective tool for calculating the extent of risk reduction of implementing a project portfolio and identifying the most risky project, so as to assist companies in making comprehensive decisions in the phase of portfolio selection and portfolio controlling.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Baker, N. & Freeland, J. (1975). Recent advances in R&D benefit measurement and project selection methods. Management Science, 21 (10): 1164–1175.

    Article  Google Scholar 

  2. Beringer, C., Jonas, D. & Gemünden, H.N. (2012). Establishing project portfolio management: an exploratory analysis of the influence of internal stakeholders’ interactions. Project Management Journal, 43 (6): 17–32.

    Article  Google Scholar 

  3. Beringer, C., Jonas, D. & Kock, A. (2013). Behavior of internal stakeholders in project portfolio management and its impact on success. International Journal of Project Management, 31 (6): 830–846.

    Article  Google Scholar 

  4. Bhattacharyya, R., Kumar, P. & Kar, S. (2011). Fuzzy R&D portfolio selection of interdependent projects. Computers and Mathematics with Applications, 62 (10): 3857–3870.

    Article  MathSciNet  MATH  Google Scholar 

  5. Campos, L.M. (2006). A scoring function for learning Bayesian networks based on mutual information and conditional independence tests. The Journal of Machine Learning Research, 7: 2149–2187.

    MathSciNet  MATH  Google Scholar 

  6. Chen, X.W., Anantha, G. & Lin, X. (2008). Improving Bayesian network structure learning with mutual information-based node ordering in the K2 algorithm. IEEE Transactions on Knowledge and Data Engineering, 20 (5): 628–640.

    Article  Google Scholar 

  7. Cooper, G.F. & Herskovits, E. (1992). A Bayesian method for the induction of probabilistic networks from data. Machine Learning, 9 (4): 309–347.

    MATH  Google Scholar 

  8. Costa, H.R., de O Barros, M. & Travassos, G.H. (2005). A risk based economical approach for evaluating software project portfolios. In ACM SIGSOFT Software Engineering Notes, 30 (4): 1–5.

    Article  Google Scholar 

  9. Cover, T.M. & Thomas, J.A. (2012). Elements of Information Theory (2nd ed.). Wiley, Hoboken, N.J.

    MATH  Google Scholar 

  10. Dickinson, M.W., Thornton, A.C. & Graves, S. (2001). Technology portfolio management: optimizing interdependent projects over multiple time periods. IEEE Transactions on Engineering Management, 48 (4): 518–527.

    Article  Google Scholar 

  11. Eilat, H., Golany, P.B. & Shtub, A. (2006). Constructing and evaluating balanced portfolios of R&D projects with interactions: a DEA based methodology. European Journal of Operational Research, 172 (3): 1018–1039.

    Article  MATH  Google Scholar 

  12. Gallati, R. (2003). Risk Management and Capital Adequacy. McGraw Hill Professional, New York.

    Google Scholar 

  13. Ghapanchi, A.H., Tavana, M., Khakbaz, M.H. & Low, G. (2012). A methodology for selecting portfolios of projects with interactions and under uncertainty. International Journal of Project Management, 30 (7): 791–803.

    Article  Google Scholar 

  14. Guan, D.J. & Guo, P. (2014). Relationship classification of project portfolio based on the measurement of interaction effects and their influences. Soft Science, 28 (10): 125–129.

    Google Scholar 

  15. Guan, D.J., Hipel, K.W., Fang, L. & Guo, P. (2014). Assessing project portfolio risk based on Bayesian network. IEEE International Conference on Systems, Man, and Cybernetics: 1546-1551, San Diego, California, USA, October 5-8, 2014, IEEE.

    Google Scholar 

  16. Guo, N. & Yu, S. (2013). Risk and uncertainty in project portfolio management. International Conference on Information Engineering and Applications, 3: 815–822, 2012. Springer, London.

    Google Scholar 

  17. Heckerman, D., Geiger, D. & Chickering, D.M. (1995). Learning Bayesian networks: the combination of knowledge and statistical data. Machine Learning, 20 (3): 197–243.

    MATH  Google Scholar 

  18. Jaafari, A. (2001). Management of risks, uncertainties and opportunities on projects: time for a fundamental shift. International Journal of Project Management, 19 (2): 89–101.

    Article  Google Scholar 

  19. Jensen, F.V. (1996). An Introduction to Bayesian Networks. UCL Press, London.

    Google Scholar 

  20. Ji, J., Hu, R., Zhang H. & Liu, C. (2011). A hybrid method for learning Bayesian networks based on ant colony optimization. Applied Soft Computing, 11 (4): 3373–3384.

    Article  Google Scholar 

  21. Jonas, D. (2010). Empowering project portfolio managers: how management involvement impacts project portfolio management performance. International Journal of Project Management, 28 (8): 818–831.

    Article  Google Scholar 

  22. Kiiveri, H., Speed, T.P. & Carlin, J.B. (1984). Recursive causal models. Journal of the Australian Mathematical Society, 36 (1): 30–52.

    Article  MathSciNet  MATH  Google Scholar 

  23. Kolmogorov, A. (1968). Logical basis for information theory and probability theory. IEEE Transactions on Information Theory, 14 (5): 662–664.

    Article  MathSciNet  MATH  Google Scholar 

  24. Markowitz, H. (1952). Portfolio selection. The Journal of Finance, 7 (1): 77–91.

    Google Scholar 

  25. Martinsuo, M. (2013). Project portfolio management in practice and in context. International Journal of Project Management, 31 (6): 794–803.

    Article  Google Scholar 

  26. Martinsuo, M. & Lehtonen, P. (2007). Role of single-project management in achieving portfolio management efficiency. International Journal of Project Management, 25 (1): 56–65.

    Article  Google Scholar 

  27. Marwell, G., Oliver, P.E. & Prahl, R. (1988). Social networks and collective action: a theory of the critical mass, III. American Journal of Sociology, 94 (3): 502–534.

    Article  Google Scholar 

  28. McFarlan, F.W. (1981). Portfolio approach to information systems. Harvard Business Review, 59 (5): 142–150.

    Google Scholar 

  29. Nielsen, T.D. & Jensen, F.V. (2009). Bayesian Networks and Decision Graphs. Springer, New York.

    MATH  Google Scholar 

  30. Olsson, R. (2008). Risk management in a multi-project environment: an approach to manage portfolio risks. International Journal of Quality & Reliability Management, 25 (1): 60–71.

    Article  MathSciNet  Google Scholar 

  31. Pearl, J. (1988). Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Morgan Kaufmann, San Francisco, CA.

    MATH  Google Scholar 

  32. Pennypacker, J.S. & Dye L.D. (2002). Project portfolio management and managing multiple projects: two sides of the same coin. Project Management Institute Annual Seminars & Symposium: 1-10, Houston, Texas, USA, September 7-16, 2000, Marcel Dekker, New York.

    Google Scholar 

  33. Petit, Y. (2012). Project portfolios in dynamic environments: organizing for uncertainty. International Journal of Project Management, 30 (5): 539–553.

    Article  Google Scholar 

  34. PMI (Project Management Institute) (2008). A Guide to the Project Management Body of Knowledge (4th ed.). Newtown Square, PA.

    Google Scholar 

  35. Proakis, J.G. (1995). Digital Communications. McGraw-Hill, New York.

    MATH  Google Scholar 

  36. Sanchez, H., Robert, B. & Pellerin, R. (2008). A project portfolio risk-opportunity identification framework. Project Management Journal, 39 (3): 97–109.

    Article  Google Scholar 

  37. Schmidt, R.L. (1993). A model for R&D project selection with combined benefit, outcome and resource interactions. IEEE Transactions on Engineering Management, 40 (4): 403–410.

    Article  Google Scholar 

  38. Shannon, C.E. & Weaver, W. (1948). A mathematical theory of communication. Bell System Technical Journal, 27 (10): 623–656.

    Article  MathSciNet  MATH  Google Scholar 

  39. Stamelos, I., Angelis, L., Dimou, P. & Sakellaris, E. (2003). On the use of Bayesian belief networks for the prediction of software productivity. Information and Software Technology, 45 (1): 51–60.

    Article  Google Scholar 

  40. Teller, J. (2013). Portfolio risk management and its contribution to project portfolio success: an investigation of organization, process, and culture. Project Management Journal. 44 (2): 36–51.

    Article  Google Scholar 

  41. Wang, M., Chen, Z. & Cloutier, S. (2007). A hybrid Bayesian network learning method for constructing gene networks. Computational Biology and Chemistry, 31 (5): 361–372.

    Article  MATH  Google Scholar 

  42. Wang, S.Y. (1997). The development of microelectronics technology: the concept of “critical mass” and reform competition. China High Technology Enterprises, 1: 5–9.

    Google Scholar 

  43. Zhao, J., Guo, P. & Pan, N.Z. (2011). Risk measurement and selection optimization of project portfolio based on the interaction effect. Operations Research and Management Science, 20 (6): 120–126.

    Google Scholar 

Download references

Acknowledgments

The authors are grateful to the anonymous referees who provided thoughtful comments and suggestions which improved the quality of their paper. This research was supported by the National Natural Science Foundation of China (Grant No. 71272049 & No. 71402142), Ph.D. Programs Foundation of the Ministry of Education of China (Grant No. 20126102110052), and Humanities, Social Science and Management Research Fund of Northwestern Polytechnical University (Grant No. 2014RW0008).

Author information

Authors and Affiliations

  1. School of Management, Northwestern Polytechnical University, Xi’an, 710072, China

    Dujuan Guan & Peng Guo

  2. Department of Management, Hefei University, Hefei, 230601, China

    Dujuan Guan

  3. Department of Systems Design Engineering, University of Waterloo, Waterloo, Ontario, Canada, N2L 3G1

    Keith W. Hipel

  4. Centre for International Governance Innovation, Waterloo, Ontario, Canada, N2L 6C2

    Keith W. Hipel

  5. Department of Mechanical and Industrial Engineering, Ryerson University, Toronto, Ontario, Canada, M5B 2K3

    Liping Fang

Authors
  1. Dujuan Guan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Peng Guo
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Keith W. Hipel
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Liping Fang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Liping Fang.

Additional information

Dujuan Guan received the PhD degree in management science from Northwestern Polytechnical University in 2015 and the Bachelor of Science degree in applied mathematics from Xidian University in 2002. Currently, she is a lecturer with the Department of Management, Hefei University. Her research interests include management systems engineering, project management, and risk management. The central field of her recent research is risk management of project portfolios from a complex systems perspective. She has published academic papers in many journals, such as Journal of Management, Software Science, Mathematics in Practice and Theory.

Peng Guo is a professor, Vice Dean, and Vice Chairman of Academic Committee, School of Management at Northwestern Polytechnical University, and Member of the Council of the Operations Research Society of China. He received his PhD degree in management science from Northwestern Polytechnical University in 2002. His research interests include management systems engineering, risk management, project management, and complex systems. He has published over 100 papers in SCI/EI and other important academic journals, such as Natural Hazards, Operations Research and Management Science, Studies in Science of Science, China Soft Science.

Keith W. Hipel is University Professor of systems design engineering at the University of Waterloo, Past-President of the Academy of Science within the Royal Society of Canada, Senior Fellow of the Centre for International Governance Innovation, and Fellow of the Balsillie School of International Affairs. He received his BASc in civil engineering (1970), MASc in systems design (1972), and the PhD in civil engineering (1975) from Waterloo. His interdisciplinary research interest is the development of conflict resolution, multiple objective decision making and time series analysis techniques from a system-of-systems engineering perspective. Dr. Hipel is recipient of the Japan Society for the Promotion of Science Eminent Scientist Award; Joseph G. Wohl Outstanding Career Award (IEEE Systems, Man and Cybernetics (SMC) Society); IEEE SMC Norbert Wiener Award; Docteur Honoris Causa (France); Doctor Honoris Causa (Hungary); Sir John William Dawson Medal (Royal Society of Canada); and Engineering Medal for Research and Development (Professional Engineers Ontario).

Liping Fang is a professor of mechanical and industrial engineering and Associate Dean, Undergraduate Programs and Student Affairs, Faculty of Engineering and Architectural Science, at Ryerson University, Toronto, Canada, and also an Adjunct Professor with the Department of Systems Design Engineering, University of Waterloo. He received the BEng degree in electrical engineering from Tianjin University, China, in 1982, and the MASc and PhD degrees in systems design engineering from the University of Waterloo, in 1985 and 1989, respectively. He has actively carried out research and consulting activities in the areas of industrial engineering, systems engineering, engineering management, and decision making, particularly in interactive decision making, multiple criteria decision making, and decision support systems. He has published widely, including two books, two edited books, and numerous journal and conference papers. Dr. Fang is Fellow of the Engineering Institute of Canada and recipient of several professional awards.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Guan, D., Guo, P., Hipel, K.W. et al. Risk reduction in a project portfolio. J. Syst. Sci. Syst. Eng. 26, 3–22 (2017). https://doi.org/10.1007/s11518-016-5296-2

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11518-016-5296-2

Keywords

Search

Navigation