By John Clark, Corporate Faculty, Harrisburg University of Science & Technology
The concepts of risk and uncertainty are associated. Project management experts generally agree that every project possesses some degree of risk as well as uncertainty (Liu et al., 2018). The standard risk management model involving identification, analysis, response, and monitor and control is the subject of extensive investigation. There is ample evidence that risk management, when properly applied, improves the likelihood of project success. However, traditional project management considers uncertainty and complexity to be sources of risk (PMI, 2017). Using traditional risk management, project managers deploy control and avoid responses which are counterproductive since uncertainty and ambiguity are fluid and emergent (Carvalho & Rabechini, 2017). Uncertainty and ambiguity in projects are rising due to globalization and technology advances (Bosch-Rekveldt, Bakker & Hertogh, 2018). Possibly, the project manager, using only traditional risk management approaches, is inadequately prepared to lead the twenty-first century project.
Risk management is a core knowledge area in PMBOK. Based on contingency theory, the project manager forms risk responses on the assumption that the future will resemble the past (Miterev, Engwall & Jerbrant, 2017). Traditionally, project managers are trained to avoid unmeasurable uncertainties (Carvalho & Rabechini, 2017). As a result, the ability of the project manager to address risk in fluid and adaptive environments becomes diminished.
Viewing the project as an open system possibly provides insight regarding how to manage risk and uncertainty in the twenty-first project. Von Bertalanffy (1950; 1969), in his theory of general system dynamics, explained that internal and external forces influence an open system. I would argue that the project is an open system. Viewing the project as an open system reveals the integration between internal and external project forces. The connectivity resident in the project provides the project manager a path to transform risks and uncertainties into strengths and opportunities (Dönmez & Grote, 2018).
The absence of information is a source of uncertainty and ambiguity. Consequently, logic dictates that seeking information is a suitable approach to address uncertainty and ambiguity. Since the project is an open system, the twenty-first century project manager obtains information through collaboration and knowledge sharing (Bond-Barnard, Fletcher & Steyn, 2018). Rather than taking a traditional approach to avoiding uncertainty and ambiguity, the project manager must create an environment that embraces the interdependencies present in the project. The project manager must establish a learning environment which emphasizes collaboration, partnership, and knowledge sharing both internally and externally to the project. Ingenuity and creativity emerge in a learning environment (Rolstadås & Shiefloe, 2017). I offer that it is necessary for the project manager to be competent in creating an environment conducive to collaboration and knowledge sharing in the project team. How do you manage risk and uncertainty?
Thank you for reading my post. For my next posting, I plan to share my thoughts on leadership in complexity. Complexity is known as the “edge of chaos” since emergent qualities such as ingenuity and creativity are available in a reflexive stable project environment (Kiridena & Sense, 2017, p. 63). The project manager, behaving as a leader, is capable of is a leader. There are various emerging leadership styles available to project managers. Like uncertainty and ambiguity, there is evidence showing that project complexity is rising. Leadership styles offer the project manager new paradigms and competencies necessary to manage project complexity.
References
Bond-Barnard, T., Fletcher, L., & Steyn, H. (2018). Linking trust and collaboration in project teams to project management success. International Journal of Managing Projects in Business, 11(2), 432-457. http://doi.org.10.1108/ijmpb-06-2017-0068
Bosch-Rekveldt, M., Bakker, H., & Hertogh, M. (2018). Comparing project complexity across different industry sectors. Complexity, 2018(3246508), 1-12. http://doi.org.10.1155/2018/3246508
Carvalho, M. M., & Rabechini, R. (2017). Can project sustainability management impact project success? An empirical study applying a contingent approach. International Journal of Project Management, 35, 1120-1132. http://doi.org.10.1016/j.ijproman.2017.02.018
Dönmez, D., & Grote, G. (2018). Two sides of the same coin – How agile software development teams approach uncertainty as threats and opportunities. Information and Software Technology, 93, 94-111. http://doi.org.10.1016/j.infsof.2017.08.015
Kiridena, S., & Sense, A. (2017). Profiling project complexity: Insights from complexity science and project management literature. Project Management Journal, 47(6), 56-74. http://doi.10.1177/875697281604700605
Liu, D., Zhang, X., Gao, C., Yang, M., Li, Q., & Li, M. (2018). Cost management system of electric power engineering project based on project management theory. Journal of Intelligent & Fuzzy Systems, 34, 975-984. http://doi.org.10.3233/jifs-169391
Miterev, M., Engwall, M., & Jerbrant, A. (2017). Mechanisms of isomorphism in project-based organizations. Project Management Journal, 48(5), 9-24. http://doi.org.10.1177/875697281704800502
PMI. (2017). A guide to the project management body of knowledge PMBOK guide (6th ed.). Newtown Square, PA: Project Management Institute.
Rolstadås, A., & Shiefloe, P. M. (2017). Modeling project complexity. International Journal of Managing Projects in Business, 10(2), 295-314. http://doi.org.10.1108/ijmpb-02-2016-0015
von Bertalanffy, L. (1950). An outline of general system theory. British Journal of the Philosophy of Science, 1, 134-165. http://doi.org.10.1093/bjps/1.2.134
von Bertalanffy, L. (1969). General system theory. New York, NY: George Braziller.
