On first appearance, the following do not appear to have much in common:
Emergence – order out of chaos
Emergence is often referred to as “the whole is greater than the sum of its parts”. Many interactions at a local level gives rise spontaneously to a system wide pattern that gives the system itself a form of order. In other words, order emerges out of chaos. Order and disorder paradoxically co-exist. The patterns that emerge provide order to the system and yet at the same time unpredictable or novel behaviour can be observed. If we observe our flock of Starlings we can see that each bird is coordinating its movements in response to the birds that are closest to it however if we observe the flock we can see that patterns emerge and disappear as the flock moves back and forth across the sky but the overall characteristics of the flock is recognisable.
Self-organising behaviour
A complex system is characterised by non-linear dynamics. In a linear system the more or less of one variable will result in a proportional change in another. So if we press our foot down on the accelerator our car goes faster. In a non-linear system this is not the case. Small changes can have large effects and large changes can have no effect. This is the famous ‘Butterfly Effect’.
Non-linear systems are characterised by positive and negative feedback. Positive feedback loops amplify a behaviour within the system; whilst negative feedback dampens a behaviour. In a complex system, patterns act back on the agents themselves to affect local interactions and yet at the same time local interactions are altering the system wide patterns. There is therefore a complex interplay between the macro patterns of the system and the micro moment by moment interactions between agents.
Self-organising dynamics can be observed if we examine the stock market. The market consists of large numbers of traders who are regulating each others’ behaviour through their interactions at a local level through their buying and selling activities. In each trade the seller and buyer receive immediate feedback from each other about the price of their commodity. Each individual trade contributes to the dynamics of the market as a whole. The pattern of the market can shift abruptly when positive feedback loops encourage the selling or buying of shares in particularly directions. The fall and the rise of the market emerges out of the local level behaviour of all the actors in the market as they attempt to anticipate changes in the pattern of the market.
The dynamics of a complex system are therefore self-organising meaning that local interactions produce order and that order is not imposed from outside of the system. Control is therefore distributed across the system and no single person or entity is in control. Order cannot be designed into a complex system.
A few simple rules can generate complex patterns
The study of complex systems reveals that a few simple rules can generate complex patterns of behaviour. If we study a crowd moving through Victoria Station at ‘rush hour’ we are likely to observe that people are taking the least congested path they can see towards where they wish to go whilst trying to avoid bumping into the people coming towards them. People mutually regulate each others’ speed so we tend not to see people running and we do not tend to observe people pushing each other out of the way. We can think of everyone simultaneously collaborating and competing with each other as they try to get through the station as quickly and safely as possible. If we stood at one of the vantage points in the station and looked down, then we would observe flows of people moving through the station concourse and as bottlenecks emerged people changing the direction of travel to avoid the busier spaces.
Capacity to adapt
The agents in a complex adaptive system demonstrate the capacity to learn and to adapt their behaviour in response to the behaviour of other agents. In the Stock Market if the market starts to fall then this will influence the behaviour of each agent. If I find that Victoria Station is becoming more and more congested, I may change my route and go via a different station. The agents in a system can therefore change the rules they are choosing to follow. The capacity of each agent to adjust their behaviour gives the system adaptive capacity meaning that complex systems can evolve in response to environmental changes. If we take the case of the car industry as the price of fuel increases and society gets more concerned about the impact of CO2 emissions on the environment, the demand for cars with low fuel consumption and emissions increases. The behaviour of the different car manufacturers changes in response to this changing pattern in car market. They car manufacturers are also contributing to this pattern through their choice of new products that they put into the market. If a company does not adapt its behaviour then consumers will select not to buy its product. The process of selection thereby operates to amplify or dampen different patterns of behaviour. In a rain forest if the environment changes, for instance if there is an unusual drop in temperature, those species that are more able to adapt to the change in conditions will survive and those that are unable to will fall in number.
What are the implications of Complexity Theory for organisations?
If we accept that organisations are themselves complex systems then the following become apparent:
Order is not predetermined in an organisation. That is to say what happens one day will not necessarily happen on the next. Instead order is continuously created and recreated through the complex interactions by employees, suppliers and customers on an ongoing basis. Under certain conditions when the dominant patterns become unstable, then qualitatively different forms of behaviour can emerge.
No one is in control of the system. Those in leadership positions have influence but they cannot control how people behave nor can they predict the outcomes of their interventions. It is not possible to predict the behaviour of markets, consumers or competitors with any accuracy because new patterns can emerge in ways that are unpredictable, although in hindsight it is possible to make sense of how specific patterns may have come about. The global financial crisis is an illustration of how a new pattern can emerge in a form that few people anticipated or predicted.
No one is able to see the whole and understand the new patterns that are emerging. We can only respond to patterns that we are experiencing at a local level and the information that we are receiving through these interactions.
How an organisation functions cannot be determined by the imposition of top down rules and through design. Rather patterns of behaviour arise through the self-organising behaviour at the local level between employees interacting with, creating and re-creating patterns of behaviour across the organisation. In an organisation, we can think of the patterns of behaviour being social norms.
Change in organisations is necessarily messy, emergent and unpredictable. Small acts of change may have a dramatic impact on the behaviour of others; whilst significant gestures and attempts at change may have little effect. Novel forms of behaviour are constantly emerging whilst stable patterns are disappearing or being disrupted.
This perspective helps us understand why between 70 – 90% of organisational change initiatives fail. The traditional approach to changing organisations is for a small group of individuals in senior roles deciding how the organisation needs to change and then planning how to move the organisation from its current state to a desired future state. This way of thinking is predicated on linear and deterministic assumptions.
How do we help organisations to change in a complex world?
Firstly, we need to recognise that change in organisation is an emergent phenomenon that takes place when people change how they interact with each other. And that change requires a disruption and disturbance to an existing pattern.
Secondly, people have the capacity to be able to reflect on their behaviour, to learn and to adapt. This means that each of us can adjust our behaviour if we can understand the patterns that our behaviour contributes to at a system level. Leaders and change agents can help facilitate change therefore by helping people across the system to notice how they are reacting and responding to each others’ behaviour.
Thirdly, we are all interdependent and mutually regulating each others’ behaviour. We both amplify and dampen each others’ behaviour. If collectively, we become aware of how each of us is contributing to maintaining a pattern then new forms of organisation become possible. However, what emerges is necessarily unpredictable and unknown.
Finally, given we cannot predict the outcome of any changes we need to experiment and learn about the intended and unintended consequences of our actions and then readjust.
Change processes therefore need to:
Bring groups of people together from inside and outside of the organisation Help them notice the patterns that are maintained through their collective behaviour
Enable people to reflect on how they mutually regulate each other’s behaviour and become aware of the implicit rules that inform these interactions
Experiment with changes that are intended to interrupt unhelpful or problematic patterns
Observe and review what emerges as a consequence of any changes.
If you want to learn more about a relational and complexity based approach to organisation change then please drop me a line.
