Perspectives on Complexity Theory

Complex Adaptive Systems -- MIT and Jurgen Appelo

Courtesy: MIT.Edu

Examples of Complex Adaptive Systems -- Economy, Organisations, Human Brain, Developing Embryos, Ant Colonies, etc.

I have modified the text to suit my needs, however it doesn't take away the core essence of the MIT Essay. 

• Complexity results from inter relationships, interactions, and inter-connectivity among the constituent elements within a system, and between the system and its environment.
• Many natural systems exhibit such complexity -- Brain, Immune system, Ecologies, societies, etc.)
• Such systems are called Complex Adaptive Systems (CAS).

CAS

• CAS are dynamic systems capable of Adapting, Evolving, and Changing with environment.
• There is no separation between the system and its environment as the system always keep adapting to the changing environment.
• The system closely linked with other related systems and together with the environment forms an ecosystem.
• Change within such an ecosystem needs to be seen as co-evolution with all related systems rather than an adaptation to a separate and distinct environment.
• CAS are real systems and are fundamentally unpredictable in their behaviour. Long term prediction and control are therefore believed to be not possible.  

Attributes of CAS

• Distributed Control: There is no single centralised control mechanism that governs system behaviour. Although the inter-relationships between elements of the system produces coherence, the overall behaviour usually cannot be explained merely as the sum of individual parts.
• Connectivity: Because all the entities within the system are inter-related, have an inter-action, and are inter-connected, a decision or action in one part of the system will have an influence in all other parts, but may be nor uniformly.
• Co-evolution: Elements within the system will change based on their interactions with one another and the environment. The behaviour patterns are also seen to change with passage of time. The co-evolution patterns are captured in Fitness landscape, which is is nothing but an array of all possible survival strategies available to a system. The landscape is  a series of overlapping graphs with crests and troughs. Fitness landscape is the mathematical term for inspect & adapt and a state of continuous learning. 
• Sensitive dependence on initial conditions: CAS are very sensitive to their dependence on their initial conditions. Small changes my have profound impact on overall behaviour, or a huge upset may not have an impact at all [Example Edward Lorentz's Weather Forecast experiments, Butterfly Effect]. 
• Emergent Order: From interaction of individual agents arises some kind of global property or pattern that could not be predicted from understanding agents at individual level. E.g. Consciousness is an emergent property of constant interactions of neurons. Global properties arise from aggregate behaviour of individuals. And this arises from competition and cooperation among the agents. [This basically contravenes with the accepted 2nd law of thermodynamics that systems tend towards disorder. This has been shown to be not true, by Ilya Prigogine's seminal work on Dissipative Structures]. It is basically possible for order of "new survival strategies" to emerge from disorder through a process of spontaneous self organisation (If a system is in a state of spontaneous self organisation, it can go from a state of disorder to a state of order). Example, Starlings. 
• Far from Equilibrium: If a system remains at equilibrium, it will die, however if you push it away from equilibrium, where they are allowed to explore their space of possibilities, they will create different structures and new patterns of relationships to thrive. Complex Adaptive Systems function best when they combine order and chaos in an appropriate measure. E.g. heartbeat is orderly and regular, however there is a subtle but apparently fundamental irregularity. 
• State of Paradox: CAS ingrain dynamics combining both order and chaos. There is a bounded instability, or the edge of chaos -- this is the state of paradox where there is both stability and instability, competition and cooperation, order and disorder.
• Fractal: CAS exhibits fractal symmetry.  

A Team is a Complex Adaptive System (CAS)

A Team (for e.g. Software Development Team) is a CAS since it consists of parts (people) that for a system (team) and the system shows complex behaviour while it keeps adapting to a changing environment. 

Management 3.0 - Jurgen Appelo

How to Change? - Daniel Gilbert

• If you want to change, change your belief system (you won't change by simply adopting a new line of thinking; because you won't buy into it for long)
• To change your belief system, seek "changing" experiences; because your beliefs always spring up in response to your experiences.

4 Conversational Models - Susan Scott

1. Team conversations: engage individuals and teams in friction-less debates that interrogate reality and ignite dialogue around clarifying goals, solving problems, evaluating opportunities and designing strategies. 
2. Coaching conversations: engage individuals and teams in conversations that increase clarity, improve understanding as part of change management. 
3. Delegation conversations: clarify responsibilities and raise level of personal accountability, ensuring that each employee has a clear path for development, action plans are implemented, deadlines are met, goals achieved, and leaders are free to take on more complex responsibilities. 
4. Confrontation conversations: engage individuals and teams in conversations which successfully resolve attitudinal, performance or behavioural issues, naming and addressing tough challenges, provoking learning, and enriching relationships.