Insights from Complexity Theory: Understanding Organizations Better

Faculty Contributor: Amit Gupta, Associate Professor
Student Contributors: S. Anish

There is no single unified theory of complexity, but several theories explaining related phenomena from areas as diverse as mathematics, computer science, physics, chemistry, biology, ecology and economics. Complex systems are characterised by the inherent difficulty experienced by an observer in explaining and describing the behaviour of the system at a macro level in terms of its constituent parts. Complex systems are typically made up of a large number of constituent entities that interact with each other and also with its environment ¹. They exhibit non-linear behaviour, that is, even seemingly insignificant causes can snowball into significant effects. An example would be that of rumours originating from insignifincant sources leading to panic and subsequent large scale commotion and disaster. As a holistic entity they exhibit characteristics that are more than the mere sum of parts. Social systems, from civilizations at an aggregate level to an individual at the constituent level, are all examples of complex systems. The biological domain is rife with such behaviour as in the case of ant colonies, beehives, flock of birds, herds of cattle and indeed groups of human beings.

The theory of complex systems is then essentially an attempt to unravel the fundamental principles that are common across all these systems. At present there is no single unified theory of complexity, but rather a verity of theories that explain several behaviours common to a complex system. Thus in order to comprehend the rich nature of a complex system it becomes essential to develop an integrated view of all its interdependent characteristics.

Unifying Themes of a Complex Adaptive System

A Complex Adaptive System (CAS) is a system that exhibits certain behaviours like learning, self-organisation, emergence, co-evolution etc. which are common across a variety of systems like ant colonies, human settlements, organisations etc. Understanding some of these unifying themes of a CAS would help develop metaphors that relate directly to the case of an organization.

Self-organisation and Emergence

The concept of self-organisation first appeared in the 1940�s and 1950�s when cybernetics scientists started exploring neural networks. Self-organisation is the capacity of a system to spontaneously self-organize themselves into greater states of complexity ². The constituent entities of a complex system interact locally among themselves and this leads to reshaping and renewal of the system as a whole as a spontaneous adaptation to changes in the external environment. For example a flock of birds spontaneously reshape their flock in response to changes in wind or while foraging or for protection from prey. Social ants, herds of cattle, termites, bees all display this phenomenon of self-organisation. Human beings too self organize into groups, communities, civilizations and economies as a response to their collective need for material resources. Key features of self-organisation are:

• It takes place spontaneously.
• The constituent entities are unconscious to the process.
• There is no external strategic guidance for the process.
• The organisation is essentially an open system exchanging energy and matter with its environment and is capable of survival even away from states of equilibrium.

This new set of properties that is displayed by the collective system as a whole but is not apparent from the behaviour of the constituent individuals of the system is referred to as emergence. Individual ants, for example, may not have great intelligence, but by working together they exhibit intelligence as a group that is greater than the sum of their individual intelligence. There is an interesting ongoing debate between neuroscientists and philosophers as to whether consciousness and intelligence can be described as emergent properties of the collective interaction of neurons of the brain³.

Learning and Adaptive Behaviour

Complex adaptive systems are self-organizing, but they differ from other self organizing systems in that they learn to adapt to changes in their environment. It is this ability to learn that�s the key differentiator between an adaptive and a non adaptive system. Thus although the weather cycle is a complex system, it lacks the property of learning and is therefore not a complex adaptive system. Complex adaptive systems are found everywhere in the natural world. For example they are found in cells, the brain, in insect-colonies and in the human context, in cultural, social, economic and political systems.

Complex adaptive systems are adaptive because they respond actively to events, seeking benefits from any situation. For example, human beings continuously learn from their experiences and respond to changes in their environment. Thus �complex adaptive systems are pattern seekers which interact with their environment, learn from their experiences and then adapt while non-living complex systems do not� � ¹

Co-evolution

Co-evolution is an extension to the Darwinian idea of evolution. The central concept of co-evolution is that different systems sharing resources in a common environment interact and influence each other�s evolutionary path². To exemplify this concept in the biological realm would be to consider the evolution of insects and plants sharing a common eco-system space. The plant would evolve and would develop toxic chemicals in defence against the insect and the insect in turn would evolve and develop detoxifying counter measures. Here both the plant and the insect influence the evolution of each other without any transfer of genetic material. In the human context the eco-system for organisations would constitute the social, cultural, technical, economic, geographic and other related dimensions. Firms operating in an eco-system would respond to each other�s evolution and this would influence their development.

Organisations Are Complex Adaptive Systems

The inadequacy of the classical mechanistic approach to analyzing social systems became more and more apparent in the early twenty-first century with the advent of a period of massive dynamics and chaos brought about by the high level of interconnectivity and advances in technology. The behaviour of organisations with increased levels of interconnections fails to fall in line with the classical descriptors and theories. Social systems (organisations being a subset) display a myriad of complexity in their form and feature. They represent an intricate web of interconnectivity among human beings that is able to self-organize in response to changes. There is some learning and adaptation at an individual level, with limited depth of vision, and at a system level, order and direction develops, that empowers the group as a whole in better coping with the changes in its environment.

The view that an organisation qualifies to fit in the definitions of a complex adaptive system helps in developing parallels between the principles of a CAS and that of an organisation. One qualitative approach to analyse and develop better insights about the deep nature of an organisation is to map the fundamental principles of a CAS like self-organisation, emergence, co-evolution, chaos, self-similarity as behaviours exhibited by the organisations as well. Exhibit 1 describes this qualitative approach to understanding various organisational phenomena as abstractions of a complex adaptive system.

There has been a dramatic increase in interest in the application of complexity theory in organisational science since the 1996 Organisation Science Winter Conference which focused on the application of complexity theory to organisations. A Y Lewin states that many ideologically rooted management advices like empowerment now emerge from the theoretical foundations of complexity, and thus this reframing of perspective promises to offer a great deal to organisation science⁴. We develop these interrelated concepts into a conceptual framework which broadly integrates tools and techniques that is relevant in the context of the applicability of complexity theory to organisations (Exhibit 2).

Organisational Design and Change: Implications for Managers

Principles drawn from complexity science are increasingly used as a guiding tool in the process of organisational transformation and renewal. The focus is on applying the learning by transforming from classical mechanistic to fluid and organic. Stacey (1996) has developed a theory of organisations using complexity, which is based on a few propositions, and this provides a valuable theoretical framework within which organisational change can be considered. They are:

1. All organisations are webs of non-linear feedback loops that connect to other people and organisations by webs of non-linear feedback loops.
2. �All organisations are paradoxes�. They are pulled towards stability by control processes, human need for security and stability, and adaptation to the environment. But they are also pulled to the opposite extreme of instability by the pull of organisational divisions and decentralization, human need for excitement and innovation, and remoteness from the environment.
3. If an organisation is pulled in to stability it will fail because it will ossify and be unable to easily change itself, but if it is pulled in to instability it will disintegrate. Success lies in sustaining an organisation in the borders between stability and instability. This is the edge of chaos.
4. The dynamics of the successful organisation are therefore those of irregular cycles and discontinuous trends, falling within qualitative patterns, fuzzy but recognizable categories taking the form of archetypes and templates.
5. The successful organisation because of its internal dynamics faces a completely unknown future.
6. Agents (people) within the systems (organisation) are unable to control the long term future. They cannot successfully apply traditional, analytical, long-term planning methods and controls to the long term future but use them only for the short term.
7. Long term planning and development should be a spontaneous, self-organizing process out of which new strategic directions may arise. Spontaneous self-organisation arises from political activity and group learning situations. Managers need to operate by considering similar or parallel situations.

Conclusion

The concept of organisations as a complex system, capable of naturally evolving strategies, structures and processes and self-adjusting to changes in environment, implies new roles and learning for managers as guides and facilitators of successful organisational transformations. These frameworks suggest that organisations operating as healthy complex adaptive systems operate in a special kind of order that they create themselves. Instead of a mission statement it�s a shared set of values that guides the process of self-organisation and emergent properties in an organisation.

Organisation science researchers today widely agree that complexity is definitely not a management fad, it is not merely a methodology or a set of tools; instead it�s a deeper perception of reality. Hence, business as �complex adaptive systems� is not a metaphor or a technique: rather, by understanding the characteristics of complex adaptive systems in general, we can find ways to understand and work with the deep nature of organizations⁴.

Contributors

Prof. Amit Gupta is a faculty in the Organisational Behaviour & Human Resource Management area at IIM Bangalore. He holds a Ph.D. in Organizational Behaviour from University of Maryland and a Post Graduate Diploma in Management from IIM Ahmedabad. He can be reached at amitg@iimb.ernet.in

S. Anish is a doctoral student in the area of Corporate Strategy and Policy at IIM Bangalore. He holds a Bachelors Degree in Technology in Electronics & Communication from the University of Kerala. He can be reached at anish.s08@iimb.ernet.in

Keywords

Complexity theory, Complex adaptive system, Organisation design and change

References

1. Gell-Mann, M, 1995, �What is complexity?� Complexity, Vol.1, No.1
2. Mc Millan, E, 2004, �Complexity, Organizations and Change�, New York: Routledge Publications.
3. Mitleton-Kelly, E, 2003. �Complex Systems and Evolutionary Perspectives on Organisations: The Application of Complexity Theory to Organisations� London: Emerald Group Publications, pp-20-40.
4. Lewin, A. Y, 1999, �Application of complexity to organization science�, Organization Science, Vol. 10, No. 3, May-June 1999, pp. 215.
5. Stacey, R. (1996). Complexity and Creativity in Organizations. San Francisco: Berrett-Koehler.

Links to online videos on complexity

1. Mackay, Robert, �An Interview� with Director Warwick Complexity Complex, University of Warwick
2. http://www2.warwick.ac.uk/fac/cross_fac/comcom/, Last Accessed on Nov 30, 2008.