Anton Rossouw Pmoz 2009 Adaptive Project Management
10-12 August 2009, National Convention Centre, Canberra
Adaptive Project Management
Applying a Complexity Science approach to
Project Management during organisational
PhD Student: Anton Rossouw
The challenge of Change:
“We are all trying to cope with a cataract of interwoven
technological, economic, societal and ecological changes on
a global scale” (McMillan, 2008, p14)
Equilibrium is death ! (Pascale et al., 2000)
“It is not the strongest of the species that survives, nor the
most intelligent, but the one that is most responsive to
change” Charles Darwin 1859
Introducing Complexity science as a view of dynamical
change, and interpreting it for use during projects as
Adaptive Project Management.
Acceleration of change
Post 1950’s Information Age Megashift (Naisbitt,1982).
Instant access to information accelerates our lives and
the pace of change (Gleick, 2000).
Globalisation, social networking communities, virtual
Projects are recognized as instruments of change
(Blake and Bush, 2009).
Change models such as Complexity Science (Dooley,
2004) that will help us to improve the way we deal with
Complicated vs. Complex
Linear behaviour, Predictable.
Equal to the sum of its parts.
Non-Linear responses, unpredictable
Positive and Negative feedback,
Cannot be adequately described by
analysing the components alone.
In the “Zone”
Ralph Stacey’s Agreement and Certainty Matrix: (Stacey,1996)
More from Macmillan at http://www.plexusinstitute.org/edgeware/archive/think/main_aides3.html
A shift away from the predictability of classical science.
A new multidisciplinary science, still emerging, with
various interpretations and definitions. Offers a
fundamental world-view shift (Dent, 1999).
Time driven dynamical systems; that are “living”,
learning, evolving and spontaneously self-organising.
Open to environmental interaction, nonlinear behaviors,
unpredictable emergent phenomena, self-organising.
Order for free at the edge of chaos (Kaufman, 1993).
Evolution and collapse of societies (Diamond, 2005).
Map of Complexity evolution
Source : Brian Castellani : http://www.art-sciencefactory.com/complexity-map_feb09.html
Complexity in Action
Robot powered by Physarum slime mould. Sources (17 June 2009) :
Manchester UK: Source: Johnson (2001) Source: Johnson (2007)
Image 22 June 2009 Google Earth
Ant Farm Simulator: Source (17 June 2009) :
Flocking behaviour – 3D Boids: Source (17 June 2009)
A Mindset Shift
Traditional worldview Emerging worldview
Reductionism, external focus Holism, internal and external
Singular linear causality Mutual non-linear causality
Objective reality Perspectival reality
Survival of the fittest Adaptive self-organisation
Discreet entity focus Relationship focus
Either/Or thinking Polarity thinking
Hierarchical levels Heterarchy within levels
Prediction and control Understanding and facilitation
Deterministic equilibrium Patterns and lifecycles
Top down influenced behaviour Bottom up emergent behaviour
Focus on Directives Focus on Feedback
Focus on averages Focus on variations and trends
Source: Dent 2001, p8
Complex Adaptive Systems
Many interacting time driven agents, system wide
emergence, learning and adaptation, self organising.
Rich short-range information exchange, with positive,
negative, direct and indirect feedback.
Non-linear cause and effect, open to feeding on and
exchanging energy from the environment.
Historical “memory” of the past influences current action
and future evolution, seeking advantage for itself.
High energy evolution happens far from equilibrium at
“edge of chaos” learning, low energy leads to collapse.
Source: Cilliers, 1998.
CAS : Source (22 June 2009) http://en.wikipedia.org/wiki/Complex_adaptive_system
Complexity and Management Science
Consistent response against traditional Taylorist
command-and-control management practiced today
A shift from working on (apart from) to working within (a
part of) the organisation.
Organisations are change challenged complex adaptive
systems (Anderson, 1999).
Applied as models and metaphors for strategic
management (Stacey, 2007), change management
(McMillan, 2004), learning (Anderson, 1999).
Complexity and Project Management
Project management (Ivory and Alderman, 2005,
Cooke-Davies et al., 2007, Jaafari, 2003).
Information systems development projects (Benbya
and McKelvey, 2006).
Project social capital (Weaver, 2007).
Innovation projects (Harkema, 2003).
Project based organisations (Sato et al., 2004).
Agile methodologies (Meso and Jain, 2006).
To the project as a Network
Shadow Network L M
E R P
K I T
Adapted from Stacey,1996 Organisation B
Environment / Landscape
Complexity perspective on Change
Cause and Effect Opportunistic
An Event Continuous
Source: McMillan,2004, p67
Adaptive Project Management
An interpretation of complexity as applied to projects as
Complex Adaptive Systems:
A new model for dynamical adaptive change management.
Participative leadership influence is more effective than the
traditional command and control management styles.
Supplemental to (not a replacement of) traditional models.
The balancing act of integrating the Complicated
(mechanism) and the Complex (organism) into an outcome.
Spontaneous re-organisation happens at the right conditions.
Adapt and evolve the plan (not time) and seek the free order.
Rich interactive environments with communication fuels
“edge of chaos” creative and innovative spontaneous events.
Value of Complexity thinking?
A new way of understanding the adaptive dynamics of
organisations, projects and change.
The promise of emergent order for free.
Innovative change happens at the edge of chaos.
The influence of leadership as a-part-of the system.
Leadership can be formal and also emergent.
Accentuate the importance of memory, start-up rules,
diversity and the power of close communication.
Anticipate non-linear unexpected events. Understanding
the space between logic and paradox.
Santa Fe Institute: www.santafe.edu
Plexus Institute: www.plexusinstitute.org
Complexity Society: www.complexity-society.com
Ralph Stacey: www.herts.ac.uk/courses/schools-of-
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