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Agile Project Management: Control Theory

controlControl Theory is another theory that is commonly used to examine the application of agile project management (APM). This theory was developed in the fields of mathematics and engineering to explain the behavior of dynamic systems (Vecchio, Dy, & Qian, 2016). One of the central concepts in this theory is dynamic systems. Dynamic systems are generally systems that evolve with time. Projects are typical examples of dynamic systems since they evolve with time due to changes in customer requirements, technology, legal and political environment, and the competitive environment (Mawdesley & Al-Jibouri, 2010).

Another key concept in the control theory is feedback. The theory proposes that the behavior of dynamic systems is influenced and modified by feedback (Persson, Mathiassen & Aaen, 2012). Feedback refers to the information derived from the output of the system. This information is routed back into the system forming part of cause-and-effect chain that transform the direction of the system. In order for the feedback mechanism to work, the system is broken down into phases so as the outcomes of one phase can be used as input for the next (Vecchio et al., 2016). This feedback mechanism causes the system to fine-tune itself until the desired end-product is realized.

The control theory has a significant implication on project management. It suggests that in order to effectively manage project especially those characterized by high level of uncertainty and complexity, the team should divide the project into distinct interfaces and implement each phase at time. The project team should also develop effective mechanisms for collecting feedback from each phase and factoring it into the design of the next phase. Project monitoring should be done by implementing employees rather than managers. Self-monitoring is also an essential part of agile control mechanisms.


Mawdesley, M., & Al-Jibouri, S. (2010). Modeling construction project productivity using system dynamics approach. International Journal of Productivity and Performance Management, 59 (1), 18- 36.

Persson, J., Mathiassen, L., & Aaen, I. (2011). Agile distributed software development: Enacting control through media and context. Information Systems Journal, 22 (6), 411- 433.

Vecchio, D., Dy, A., & Qian, Y. (2016). Control theory meets synthetic biology. Journal of the Royal Society Interface, 13 (120), 381- 390.