Catalyzing Stories Project

Plexus Network members came together in late 2018 to develop and publish stories that reflect an author’s unique experience, practice and management of addressing complexity in their own systems. 

Buck The System: Sense-making and Acting Into Complexity at the United States Department of Labor

Acting into uncertainty, ambiguity, and complexity requires continuous rational cognition, discernment, action, reflection, and adaptation.  Bruce Waltuck shares his story of acting to create change without the awareness of the optimal patterns and methods for acting into complexity, and the consequences that followed.  Each of you reading this will bring your own experiences, knowledge, understanding, and insights.  As is the case with truly complex situations, we are compelled to look back at what we have done, and what we think happened.  We hopefully learn in retrospect, and with new knowledge and understanding, consider what we might have done differently- and will do differently in the future.

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Learn about the language & concepts of complexity referenced in this story.

The complete nonlinear dynamics & complexity glossary

A complex, nonlinear, interactive system which has the ability to adapt to a changing environment. Such systems are characterized by the potential for self-organization, existing in a nonequilibrium environment. CAS’s evolve by random mutation, self-organization, the transformation of their internal models of the environment, and natural selection. Examples include living organisms, the nervous system, the immune system, the economy, corporations, societies, and so on. In a CAS, semi-autonomous agents interact according to certain rules of interaction, evolving to maximize some measure like fitness. The agents are diverse in both form and capability and they adapt by changing their rules and, hence, behavior, as they gain experience. Complex, adaptive systems evolve historically, meaning their past or history, i.e., their experience, is added onto them and determines their future trajectory. Their adaptability can either be increased or decreased by the rules shaping their interaction. Moreover, unanticipated, emergent structures can play a determining role in the evolution of such systems, which is why such systems show a great deal of unpredictability. However, it is also the case that a CAS has the potential of a great deal of creativity that was not programmed-into them from the beginning. Considering an organization, e.g., a hospital, as a CAS shifts how change is enacted. For example, change can be understood as a kind of self-organization resulting from enhanced interconnectivity as well as connectivity to the environment, the cultivation of diversity of viewpoint of organizational members, and experimenting with alternative “rules” and structures.

See: Adaptation; Emergence; Genetic Algorithm; Self-organization Bibliography: Dooley (1997); Gell-mann (1994); Holland (1995); Kauffman (1995)

Bruce Waltuck,
Bruce Waltuck,Master of Arts in Complexity, Chaos, and Creativity
Bruce is an award-winning designer and facilitator of organizational change initiatives. Bruce brings a unique perspective and approach informed by his deep understanding of the complexity inherent in human systems. He has taught and presented to more than 25,000 people throughout the U.S., Canada, Brazil, and Southeast Asia, helping others achieve improved Adaptive Response Capacity.

Why Schools Fail the Complexity Test and What They Need to Do to Pass It

Peter Barnard writes about how a secondary school in the UK abandoned its same-age organisational structure by repopulating homeroom groups with students from all grades. The original intention was to improve collaboration, but the change took on a life of its own, accelerating the school community on a journey towards realizing the many advantages of operating as a complex adaptive system. It is a story about counter-intuitive ideas and how these can sometimes lead to surprising outcomes. For this school, a new operational system emerged, one that led to further inquiry and incremental change in the field of education; a model now used by a growing number of schools worldwide. 

Read Story

Learn about the language & concepts of complexity referenced in this story.

The complete nonlinear dynamics & complexity glossary

A complex, nonlinear, interactive system which has the ability to adapt to a changing environment. Such systems are characterized by the potential for self-organization, existing in a nonequilibrium environment. CAS’s evolve by random mutation, self-organization, the transformation of their internal models of the environment, and natural selection. Examples include living organisms, the nervous system, the immune system, the economy, corporations, societies, and so on. In a CAS, semi-autonomous agents interact according to certain rules of interaction, evolving to maximize some measure like fitness. The agents are diverse in both form and capability and they adapt by changing their rules and, hence, behavior, as they gain experience. Complex, adaptive systems evolve historically, meaning their past or history, i.e., their experience, is added onto them and determines their future trajectory. Their adaptability can either be increased or decreased by the rules shaping their interaction. Moreover, unanticipated, emergent structures can play a determining role in the evolution of such systems, which is why such systems show a great deal of unpredictability. However, it is also the case that a CAS has the potential of a great deal of creativity that was not programmed-into them from the beginning. Considering an organization, e.g., a hospital, as a CAS shifts how change is enacted. For example, change can be understood as a kind of self-organization resulting from enhanced interconnectivity as well as connectivity to the environment, the cultivation of diversity of viewpoint of organizational members, and experimenting with alternative “rules” and structures.

See: Adaptation; Emergence; Genetic Algorithm; Self-organization Bibliography: Dooley (1997); Gell-mann (1994); Holland (1995); Kauffman (1995)

Peter A. Barnard
Peter A. BarnardPeter Barnard Consulting
Peter Barnard was a schoolteacher and the school principal of three contrasting secondary schools in the UK. He took an early interest in systems thinking which he applied as a Headteacher, questioning every directive and orthodoxy. Peter developed the research background on multi-age organisation (often called vertical tutoring) and as multi-age organisation became popular, he started an international consultancy, training schools and others in organisational change and transformation. In his dotage, Peter has returned to university to learn more about what he discovered through research. He writes books and papers and spends his summers growing fruit and vegetables.

Peter’s latest book is Socially Collaborative Schools: The heretic’s guide to mixed-age tutor groups, system design, and the goal of goodness. Rowman & Littlefield Publishers.  Additional papers on VT are available from at www.verticaltutoring.org

Moving from Complicated to Complex: An Organizational Transformation

Marc Narkus-Kramer, offers a timely story focused on his professional experiences and reflections about specific events that led to major organizational changes in the Center for Advanced Aviation System Development (CAASD) at MITRE.

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The Alaska Capstone Project: Addressing Aviation Safety in Alaska and Improving Air Traffic Control World-Wide

The Alaska Capstone Project provides a detailed example of how complexity thinking and agile management practices led to a significant reduction in aviation accidents in Alaska and provided a basis for revolutionizing surveillance technology that was adopted worldwide. This catalyzing story is a companion piece to Moving from Complicated to Complex: An Organizational Transformation.

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Learn about the language & concepts of complexity referenced in this story.

The complete nonlinear dynamics & complexity glossary

A complex, nonlinear, interactive system which has the ability to adapt to a changing environment. Such systems are characterized by the potential for self-organization, existing in a nonequilibrium environment. CAS’s evolve by random mutation, self-organization, the transformation of their internal models of the environment, and natural selection. Examples include living organisms, the nervous system, the immune system, the economy, corporations, societies, and so on. In a CAS, semi-autonomous agents interact according to certain rules of interaction, evolving to maximize some measure like fitness. The agents are diverse in both form and capability and they adapt by changing their rules and, hence, behavior, as they gain experience. Complex, adaptive systems evolve historically, meaning their past or history, i.e., their experience, is added onto them and determines their future trajectory. Their adaptability can either be increased or decreased by the rules shaping their interaction. Moreover, unanticipated, emergent structures can play a determining role in the evolution of such systems, which is why such systems show a great deal of unpredictability. However, it is also the case that a CAS has the potential of a great deal of creativity that was not programmed-into them from the beginning. Considering an organization, e.g., a hospital, as a CAS shifts how change is enacted. For example, change can be understood as a kind of self-organization resulting from enhanced interconnectivity as well as connectivity to the environment, the cultivation of diversity of viewpoint of organizational members, and experimenting with alternative “rules” and structures.

See: Adaptation; Emergence; Genetic Algorithm; Self-organization Bibliography: Dooley (1997); Gell-mann (1994); Holland (1995); Kauffman (1995)

Marc Narkus-Kramer
Marc Narkus-Kramer
Marc worked for 30 years at the MITRE Corporation. Though his training was in engineering, the most challenging part of his work was working with many stakeholders and developing enough consensus to ensure that projects could be successfully deployed. Marc, without knowing the principles of complexity theory and management, instinctively began applying these to his work. He is now retired and is interested in learning more about what he instinctively used in his job.

 

Discovering Complexity: A Story of an Organization in Crisis and its Response

David Hurst tells his story of how his organization was thrown into crisis by an ill-advised takeover on the eve of a sharp recession. He explains how the management team muddled through to grapple with complexity and to survive. He then develops a useful ecological model that maps the trajectories of complex systems in space and over time and helps managers deal with the dilemmas and paradoxes they will encounter.

Read Story

Learn about the language & concepts of complexity referenced in this story.

The complete nonlinear dynamics & complexity glossary

The ecocycle is the name given by David Hurst and Brenda Zimmerman in their 1994 article, From Life Cycle to Ecocycle (Journal of Management Inquiry 1994; 3; 339) to the use of ecologist C. S. Holling’s adaptive cycle (Holling, C.S. (1986). “The resilience of terrestrial ecosystems: Local surprise and global change. In W.C. Clark & R.E. Munn (Eds.), Sustainable development of the biosphere (pp. 292-317). Cambridge: Cambridge University Press) when applied to human organizations. The infinity loop-shaped cycle identifies four phases in the persistence of an ecosystem: exploration, conservation, creative destruction and renewal. The resulting mental model allows powerful analogies to be drawn between natural and human systems, disciplined by the multiple perspectives of complex adaptive systems. The framework has been extended (Hurst, 1995, 2012) to include the phases of emergent action (passion), rational action (reason) and constrained action (power) as well as many other management concepts.  Its application is featured in The Surprising Power of Liberating Structures (Lipmanowicz H. and McCandless K. (2013).

Resilience is the capacity of a system to absorb disturbance and reorganize while undergoing change so as to still retain essentially the same function, structure, identity, and feedbacks….. There are four crucial aspects of resilience. The first three can apply both to a whole system or the sub- systems that make it up.

  1. Latitude: the maximum amount a system can be changed before losing its ability to recover (before crossing a threshold which, if breached, makes recovery difficult or impossible).
  2. Resistance: the ease or difficulty of changing the system; how “resistant” it is to being changed.
  3. Precariousness: how close the current state of the system is to a limit or “threshold.”
  4. Panarchy: because of cross-scale interactions, the resilience of a system at a particular focal scale will depend on the influences from states and dynamics at scales above and below. For example, external oppressive politics, invasions, market shifts, or global climate change can trigger local surprises and regime shifts.

(Walker B., Holling C.S., Carpenter S.R. and Kinzing A., (2004) “Resilience, Adaptability and Transformability in Social-ecological Systems”, Ecology and Society 9(2): 5) A distinction should be made between engineering and ecological concepts of resilience (Holling, C.S., “Engineering Resilience versus Ecological Resilience” in Engineering with Ecological Constraints, National Academy of Engineering (1996)). Engineering resilience is concerned with maintaining the efficiency, constancy and predictability of the system and focuses on stability near a single equilibrium steady state. Ecological resilience on the other hand, is concerned with the persistence, change and unpredictability of the system and assumes the existence of multiple possible steady states.

The adaptive capacity of a system is its ability to adjust to changing internal demands and external circumstances and is a central feature of its resilience. This capacity is diminished by the emergence of socio-ecological traps (Carpenter S.R. and Brock W.A. (2008) “Adaptive Capacity and Traps”, Ecology and Society 13(2):40), in particular the withering of underused systems – the so-called ‘poverty’ trap – and lock-in by overused systems – the ‘rigidity’ trap. Rigidity traps occur in socio-ecological systems when institutions become highly connected, self-reinforcing and inflexible. In human organizations management by command and control can reduce diversity and inhibit innovation. In poverty traps, by contrast, connectivity and resilience are low and potential for change is not realized. Ideas and raw materials may be abundant but there is no capacity to focus and move the system forward.
David Hurst FRSA
David Hurst FRSA
David Hurst is a reflective practitioner, an executive who spent most of his management career in what he thinks of as organizational ‘train wrecks’ before becoming a management educator. He teaches on three graduate level programs at McGill University and in Finance and Organizational Behaviour at the DeGroote School of Business at McMaster University. He is also associated with the Center for Creative Leadership in Greensboro, North Carolina. He is a Contributing Editor to Strategy+Business. David’s first book was Crisis & Renewal (1995). His most recent book is The New Ecology of Leadership (2012) His latest video Beyond Cartesian Management His most recent article Lead Like a Gardener