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Complex Adaptive Operating System: Creating Methods for Complex Project Management
Abstract
The world of complex project management is in an acute state of flux. Contributing factors include
the speed of change, the increasing complexity of and interactivity between systems, and the need
for a higher level of cognitive complexity to understand the context and actions required in the current
environment. In order to address this situation effectively, we need to be able to create and apply
new knowledge quickly and wisely across the boundaries of worldviews, disciplines, and cultures.
Many of the methods and models currently in use—including some of the most innovative—are
based on an understanding of human systems that is neither sufficient to explain what is happening
nor capable of being the sole basis of sustainable activity. While many traditional approaches may
have worked well when transformational change occurred in tens of generations, today’s new normal
of constant, disruptive change requires an entirely new approach. With transformational change now occurring in less than a human generation, there is insufficient time for new tools to develop a pedigree. The current generation of project management tools, although so new that they are unproven, may offer a much better chance of success than the tools that are no longer consistently reliable. In its discussion paper for the 2012 roundtable series, ICCPM says the following about what is required for success:
"Today’s leaders of complex major projects need a set of capabilities that enable them to deal creatively,
adaptively and successfully with emergence, collaboration and cross-cultural/sector issues, all prevalent
features of the new economy. Flexible models are required to support a richer, more complex
approach to benefits realization of cost, schedule (time), scope, quality and risk. (ICCPM, 2012, p. 16)"
This case study demonstrates how ICCPM and its community are developing a richer understanding
of the issues and new frameworks, models, and method to achieve project success.
... A key challenge to the successful management of projects is their increasing complexity (Marle & Vidal, 2016;PMI, 2013;San Cristóbal et al., 2018) due to the limited effectiveness of traditional plan and control based methods for managing complex projects (Böhle et al., 2016;Elia et al., 2021;Findlay & Straus, 2015). Drawing on complex adaptive systems theory, complex projects are defined as complex adaptive systems characterised by unclear cause and effect relationships due to emergent properties, adaption and non-linear effects from agent interactions and feedback loops influenced by sources of complexity (Bakhshi et al., 2016;Remington et al., 2009;Vidal et al., 2011). ...
... The differences between the individual and shared project team and stakeholder perceptions provide a window into their situation models of the complex project. This means individual situation models of a complex project could be elicited indirectly by measuring the perceptions of project team members and other stakeholders to provide the system-wide information that Findlay and Straus (2015) argue is necessary to manage complex projects as complex adaptive systems. To date, the limited project research about mental models has focussed on longer-term stable team mental models (e.g., Shafique & Mollaoglu-Scott 2020;Hsu et al. 2011;Wu et al. 2023). ...
... This means teams need to take a proactive approach to question their knowledge and assumptions about the management of a complex project drawing on diverse views of its current state. As Findlay and Straus (2015) argue, methods of managing complex projects as complex adaptive systems need to draw on system-wide information to understand these projects. If project team members and other stakeholder's individual situation models of a complex project were indirectly measured as individual level perceptions this would provide the requisite system-wide information and enable comparisons of mental models as Chang et al. (2021) described. ...
Understanding the current state of a complex project is challenging but essential for project teams to make effective management decisions. This research explores whether the indirect elicitation and comparison of mental models measured through individual level perceptions can encourage project team double loop learning about a complex project to inform management decisions. The best-worst scaling object case method was applied at the individual level to measure system-wide perceptions of two case study projects, demonstrating its efficacy in capturing team and stakeholder perceptions, and measuring how these change over time. Analysis of the case studies showed that highlighting the differences in mental models uncovered using the best-worst scaling object case method at the individual level can facilitate double loop learning and prompt management decisions about complex projects.
Two important aspects of future software engineering techniques will be the ability to seamlessly move from analysis models to design models and the ability to model dynamic systems where scenarios and structures may change at run-time. Use Case Maps (UCMs) are used as a visual notation for describing causal relationships between responsibilities of one or more use cases. UCMs are a scenario-based software engineering technique most useful at the early stages of software development. The notation is applicable to use case capturing and elicitation, use case validation, as well as high-level architectural design and test case generation. UCMs provide a behavioural framework for evaluating and making architectural decisions at a high level of design. Architectural decisions may be based on performance analysis of UCMs. UCMs bridge the gap between requirements and design by combining behaviour and structure in one view and by flexibly allocating scenario responsibilities to architectural components. They also provide dynamic (run-time) refinement capability for variations of scenarios and structure and they allow incremental development and integration of complex scenarios. Therefore, UCMs address the issues mentioned above.
Change is accelerating, and as the complexity of the systems in which we live grows, so do the unanticipated side effects of human actions, further increasing complexity. Many scholars call for the development of systems thinking to improve our ability to manage wisely. But how do people learn in and about complex dynamic systems? Learning is a feedback process in which our decisions alter the real world, we receive information feedback about the world and revise the decisions we make and the mental models that motivate those decisions. Unfortunately, in the world of social action various impediments slow or prevent these learning feedbacks from functioning, allowing erroneous and harmful behaviors and beliefs to persist. The barriers to learning include the dynamic complexity of the systems themselves; inadequate and ambiguous outcome feedback; systematic mispercep-tions of feedback; inability to simulate mentally the dynamics of our cognitive maps; poor interpersonal and organizational inquiry skills; and poor scientific reasoning skills. To be successful, methods to enhance learning about complex systems must address all these impediments. Effective methods for learning in and about complex dynamic systems must include (1) tools to elicit participant knowledge, articulate and reframe perceptions, and create maps of the feedback structure of a problem from those perceptions; (2) simulation tools and management flight simulators to assess the dynamics of those maps and test new policies; and (3) methods to improve scientific reasoning skills, strengthen group process, and overcome defensive routines for individuals and teams.