Applying complexity science to project managment during change

1. 10-12 August 2009, National Convention Centre, Canberra
Adaptive Project Management
Applying a Complexity Science approach to
Project Management during organisational
change.
PhD Student: Anton Rossouw

2. Introduction
 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.

3. 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
worlds.
 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
change.

4. Complicated vs. Complex
 Complicated System
 Linear behaviour, Predictable.
 Equal to the sum of its parts.
 Complex System
 Non-Linear responses, unpredictable
behaviour.
 Positive and Negative feedback,
spontaneous emergence.
 Cannot be adequately described by
analysing the components alone.
Source: Cilliers,1998.

5. 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

6. Complexity Science
 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).

7. Map of Complexity evolution
Source : Brian Castellani : http://www.art-sciencefactory.com/complexity-map_feb09.html

8. Complexity in Action
Robot powered by Physarum slime mould. Sources (17 June 2009) :
http://www.guardian.co.uk/science/2006/feb/15/uknews.robots
http://www.daviddarling.info/encyclopedia/S/slime_mold.html
Jazz Improvisation
Manchester UK: Source: Johnson (2001) Source: Johnson (2007)
Image 22 June 2009 Google Earth
Ant Farm Simulator: Source (17 June 2009) :
http://www.geocities.com/chamonate/hormigas/antfarm/
Flocking behaviour – 3D Boids: Source (17 June 2009)
http://www.navgen.com/3d_boids/index.html

9. 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
 Determinism  Indeterminism
 Survival of the fittest  Adaptive self-organisation
 Discreet entity focus  Relationship focus
 Either/Or thinking  Polarity thinking
 Modern/Classical  Postmodern
 Hierarchical levels  Heterarchy within levels
 Prediction and control  Understanding and facilitation
 Patriarchy  Equality
 Logic  Paradox
 Physics  Biology
 Deterministic equilibrium  Patterns and lifecycles
 Top down influenced behaviour  Bottom up emergent behaviour
 Focus on Directives  Focus on Feedback
 Specialist  Generalist
 Assembly  Morphogenisis
 Focus on averages  Focus on variations and trends
Source: Dent 2001, p8

10. 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.

11. CAS Diagram
CAS : Source (22 June 2009) http://en.wikipedia.org/wiki/Complex_adaptive_system

12. Complexity and Management Science
 Consistent response against traditional Taylorist
command-and-control management practiced today
(McMillan, 2008).
 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).

13. 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).

14. The project as a Hierarchy

15. To the project as a Network
Agent X
Legitimate Network
Shadow Network L M
A O
B
N
C
D
E R P
F
Q
Project 1
Organisation A
G
J H
S U
K I T
Project 2
Adapted from Stacey,1996 Organisation B
Environment / Landscape

16. Complexity perspective on Change
Traditional Dynamical
Linear Non-Linear
Disruptive Creative
Cause and Effect Opportunistic
Incremental Revolutionary
An Event Continuous
Calamitous Turbulent
Controllable Uncontrollable
Abnormal Normal
Predictable Unpredictable
Source: McMillan,2004, p67

17. 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.

18. 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.

19. Resources
 Santa Fe Institute: www.santafe.edu
 Plexus Institute: www.plexusinstitute.org
 Complexity Society: www.complexity-society.com
 Emergence Journal:
www.emergence.org/ECO_site/web-content/table.html
 Ralph Stacey: www.herts.ac.uk/courses/schools-of-
study/business/research/complexity-and-management-
centre/home.cfm
 Book: KAUFFMAN, S. (1995) At Home in the Universe:
The Search for Laws of Self-Organization and
Complexity, New York, Oxford University Press.

20. References (1)
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 BENBYA, H. & MCKELVEY, B. (2006) Toward a complexity theory of information systems development. Information Technology
and People, 19, 12-34.
 BLAKE, I. & BUSH, C. (2009) Project Managing Change : practical tools and techniques to make change happen, Harlow, Pearson
Education.
 CILLIERS, P. (1998) Complexity and postmodernism: Understanding complex systems, London and New York, Routledge.
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strange landscape of complexity theory, and its relationship to project management. Project Management Journal, 38.
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21. References (2)
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 MCMILLAN, E. (2004) Complexity, Organizations and Change, London, Routledge.
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