An essay on complex adaptive systems

Complexity science is not a single theory. It is a combination of various theories and concepts from a variety of disciplines—biology, anthropology, economy, sociology, management and others that studies complex adaptive systems (CAS).

All three terms in the name CAS are significant in the definition of a CAS: 

  1. Complex implies diversity, many connections among a wide variety of elements. 
  2. Adaptive suggests the capacity to alter or change, the ability to learn from experience. 
  3. A system is a set of connected or interdependent things. From this definition, it is possible to approach organizations, communities and societies as complex adaptive systems.

NOTES

How about conversations people have as complex social processes, rather than reifing an organisation itself as an entity in a complex adaptive system (usually based on the physical world). Read on about the principles

Complexity science seeks to understand:  

  • how complex adaptive systems work the patterns of relationships within them
  • how they are sustained
  • how they self-organize
  • how outcomes emerge

…instead of describing how systems should behave, complexity science focuses the analysis on the interdependencies and interrelationships among their elements to describe how systems actually behave.

I started to understand better the role of relationships, connection and interactions. I began to understand the concepts of emerging orders, self-organizing, nonlinearity. I began to see the importance of pattern recognition, the difference between the whole and the mere sum of the parts, the value of outliers and diversity, and how small inputs can lead to big changes and so on. 

PRINCIPLES

The Whole Is Greater Than The Sum Of Its Parts

…interpersonal and organizing activities at the local level were essential to promote individual-level changes and organizational capacities of communities. But, but at the more macro level, the mass media played an important role to shape public opinion, creating a supporting environment for structural changes to occur.A multimedia, multi-method strategy allowed…to have both individual and social change catalysts operating simultaneously and over time. 

Order Is Emergent and Self-Organizing

The most illuminating paradox of all is that in complex adaptive systems order is emergent and self-organizing. In a healthy, complex adaptive system, control is distributed rather than centralized, meaning that the outcomes emerge from a process of self-organization rather than being assigned and controlled externally by a centralized body. Order emerges from the interactions among the individuals. It results as a function of the patterns of interrelationships between the agents, and it is characterized by unpredictability. It is not able to predict precisely how the interrelationships between the parts will evolve.

The System Changes When It Chooses To Be Disturbed

The system will choose to be disturbed when the information adds new meaning to what exists. In other words, the system becomes different because it understands the world differently. It is not just the intensity or frequency of the message that gets our attention; but mostly how meaningful the message is to us personally…The key word here is “choice.” The system “chooses” to be disturbed by something it considers meaningful. People do not want to be bossed; they want information so they can, when they can, make their own choices and decisions.

Free Flow Of Diverse Information Is Essential For The System To Evolve

Meaningful information can be presented in various forms to convey a meaning for the system/receptor, and the more diverse the sources, the better. Complexity science values both diversity and participation.

Diversity means not only having different voices on an issue, but it also means addressing issues generally considered taboo. Participation means creating an environment in which everyone can feel comfortable sharing opinions and feelings. It is not only what information is being shared, but also who is sharing it. The wider the variety of people who share ideas, the greater the opportunity for new associations to form and new patterns of meanings to emerge. 

Planning the Unpredictable

…operative planning usually follows a complicated, linear, step-by-step approach. These planning methods require that an organization plan its mission and goals in terms of actions, activities, outputs, outcomes and measurable results. 

But does social reality work that way? First, not all social processes are linear, meaning that not every action has a direct and single effect. Second, there are many unpredictable events that can influence one’s strategy, and so it should be flexible enough to adapt. Third, by detailing how expected outcomes will be measured, the assumption is that they are the only possible outcomes ergo, one is predisposed to them””and focuses on measuring them exclusively, perhaps overlooking other important factors. In a world that asks for measurable outcomes, it is easier to go with the flow and not resist the dominant currents. But when the measure of success is defined in quantitative terms, what matters more is how much was done, and not the quality of the processes and the relationships. 

Interventions in complex adaptive systems require careful consideration and planning but of a kind different from a mechanistic system. It is more important to understand local conditions and to be aware of the uncertainty and feedback that accompanies any intervention than to predict the number and type of the outcomes expected.

Complexity science recognizes the difficulty of planning everything in detail, especially when working within an unpredictable and constantly changing environment. It suggests that the best way to plan is by establishing minimum specifications and a general sense of direction, that is, to describe the mission the organization is pursuing and a few basic principles on how the organization should get there. Allowing the flexibility of multiple approaches by trying several small experiments, reflecting carefully on what happens and gradually shifting time and attention toward those things that seem to be working the best. Once the minimum specifications have been set, the organizational leadership should then allow appropriate autonomy for individuals to self-organize and adapt as time goes by to a continually changing context.

Complex Adaptive Systems Are History And Context Dependent

Evaluations and impact assessment are another challenge for organizations…generally positive results demonstrated by impact evaluations of….strategies…have created expectations of regularity and predictability about social change. This positivist approach leads us to think that there are “effective” ways to change societies. Many organizations, especially international aid organizations and foundations, use concepts as “best practices” to re-enforce the idea that successful experiences in one setting can be replicated in different settings. This notion of replication privileges the importance of “outside experts,” and it re-enforces beliefs that local organizations and communities need them to find the “right” solutions. 

As much as success stories may attract new converts…the pressure to “succeed” in traditional terms may also prevent innovation within the field, not only in terms of project design and implementation but in terms of evaluation. The required predefinition of the evaluation methods and indicators [leave] little room for opportunities and unexpected changes that arise during the implementation process”.

In closing

Planning and evaluation are important to social change, but we need to open our minds to new ways to understand how social systems evolve. So instead of looking for the formulae for social change, it may be more useful to understand and focus more on the processes that lead to effective interventions. 

The issues discussed here are not new. Indeed, some of the “answers” proposed by complexity science are not new. But as some complexity theorists state: “In many contexts, these ‘answers’ were not explainable by theory.” They were the intuitive responses known by many but appeared illogical, or at least idiosyncratic, when viewed through traditional scientific theories. Complexity science provides the language, the metaphors, the conceptual frameworks, the models and the theories that help make the idiosyncrasies nonidiosyncratic and the illogical logical. It also provides a rigorous approach to study some of the key dimensions of organizational life.

For the most part, social scientists and practitioners are trained erroneously in believing that social change phenomena, much like “raising a child,” can be predicted, controlled, and achieved in linear steps””and with a high degree of certainty. This problematic prevailing mindset” ”if we do this to people, they will behave in this way” ”is a result of the overwhelming dominance of Newtonian thinking that spilled over to social science and was reified over decades without much questioning. To question this prevailing paradigm meant turning upside down the Holy Grail and inviting derision and condescension about “not being scientific enough.” The notion that the thoughts and actions of human beings could be predicted and measured in the same way as the movement of heavenly bodies seemed to me as being downright faulty

The social change enterprise, in my opinion, was badly in need of a framework that could explain the certainty and uncertainty associated with outcomes, as also the agreement and disagreement about how those outcomes could be achieved. What we needed was a framework that could explain why small inputs in a social system could result in surprisingly big outcomes; and why often big, expensive interventions yielded small, dismal outcomes. We also needed a framework that could account for the simultaneous order and disorder in a system, as well as the co-existence of paradoxes and contradictions. 

- Arvind Singhal

NOTES

I have created several posts that are sections from this post…

  1. Rather than seeking to change individual behaviour, seek to influence the social context in which individuals act
  2. How system SHOULD behave vs how systems ACTUALLY behave
  3. Complexity science provides the tools that help make the idiosyncrasies nonidiosyncratic
  4. Leave best practices and pre-defined evaluation out of complex environments; which are history and context dependent
  5. Planning the Unpredictable
  6. We have been badly in need of a framework that explains the certainty and uncertainty associated with outcomes

Related links

Organisational Culture - focus on what’s behind the behaviours, not the abstraction

Emergence - Clouds and Clocks

The danger of reification

Stop ‘doing things’ to people and start to work together

Culture cannot be managed from outside as a whole

Strange Attractors

From KM to complexity - Necessary silos, cognitive truths about knowledge sharing, narrative as mediator, the zone of effective diffusion, and decision-making

Organisations are not Complex Adaptive Systems

Positive feedback loops amplify deviations from the norm

Ability to respond to emergent outcomes…

Strategic plans nor change initiatives work out as designed

What is a strategy?

From strategic planning to purpose and resilience

Emergent practices

Emergence focus

Organisations are not systems at all

Organizations need to model both their deterministic and emergent properties

You navigate complexity you don’t conquerer it

Complex = not simple and never fully knowable. Just too many variables interact

What is complex need not be complicated, like two people in a bedroom

3 ways of thinking

Trojan mice

Key properties of Complex Adaptive Systems

Anticipation replaces prediction

Focus on continuously improving processes, not achieving outcomes

As natural systems evolve to become more complex, their resilience increases…

In order to serve your interests, your actions have to indirectly serve the whole

We treat our ideas like albatrosses treat their chicks

Boundaries and context

On boundaries…

Fractals - looking at Enterprise 2.0 adoption and value from a complex system perspective

The main difference between predictable systems and complex systems

People in organizations are rarely people at all

One cannot reduce the complexity. One can only shift the burden

Beware of outcomes thinking in complex environments

Replicate starting conditions

Prediction and emergence

Wicked problem solving - relationship of emergent mess to essence

On the Cynefin framework

Cynefin framework (abstraction) (wikipedia)

Using the Cynefin framework

The delicate conversion of conflict into cooperation

Characteristics of Emergent Communities

Idealistic vs Naturalistic

From systems thinking to complexity

Behaviors that emerge from the interaction instead of specifying in advance

How can I influence the constraints

Complex adaptive theory in human systems is different from in the physical world

Humans do not behave like ants, termites, bacteria, etc…

Measure impact rather than outcomes and the folly of targets

For achievable business goals we need to action behavioural goals

Set goals for behaviour, not targets for performance

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