1. T306 managing complexity: a systems approach TUTORIAL 7 BLOCK 1 – PART 4

2. SOME PERSPECTIVES ON COMPLEXITY Complexity is a property of something Complexity is a property of something Condition of the universe (non-linear) Condition of the universe (non-linear) Complex systems Complex systems Complex adaptive systems Complex adaptive systems Complex responsive processes Complex responsive processes Complexity is something we experience Complexity is something we experience Differs depending on who is experiencing (perceived complexity) Differs depending on who is experiencing (perceived complexity) Complexity is an emerging discipline Complexity is an emerging discipline A new science (AI, cognitive science, ecology, game theory) A new science (AI, cognitive science, ecology, game theory) Complexity theory includes: organismic complexity, structural complexity, hierarchic complexity, dynamic complexity, etc.) Complexity theory includes: organismic complexity, structural complexity, hierarchic complexity, dynamic complexity, etc.) Complexity is used to describe a new way of thinking (paradigm) Complexity is used to describe a new way of thinking (paradigm) Nature of emergence, learning and adaptation Nature of emergence, learning and adaptation Metaphors Metaphors

3. Applied chaos theory Cambell (1993) – characteristics:  Purpose and function  Size and configuration  Structure  He recognizes 3 categories of complexity  Static complexity  Embedded complexity  Dynamic complexity (incl. dynamic processes)  Total complexity = all 3 should exist, not at all times

4. Applied chaos theory Cambell states: Cambell states: Complexity occurs in dynamical systems, namely systems whose internal microscopic or external macroscopic motion is affected by one or more forces Complexity occurs in dynamical systems, namely systems whose internal microscopic or external macroscopic motion is affected by one or more forces Not all complex systems are self-organizing, but all self-organizing systems are complex Not all complex systems are self-organizing, but all self-organizing systems are complex His study isn’t one of holism vs. reductionism, but rather reductionism in the context of holism (systematic embedded in systemic) His study isn’t one of holism vs. reductionism, but rather reductionism in the context of holism (systematic embedded in systemic)

5. Structural information processing – S treufert & Swezey Researchers are considered with the processes that ‘generate the content of managerial and organizational function’ Researchers are considered with the processes that ‘generate the content of managerial and organizational function’ Their concern is with structure, managerial information processing, processing org. input into output (transformation processes) Their concern is with structure, managerial information processing, processing org. input into output (transformation processes)

6. Applications in sociology Turner (1997) – new sciences of complexity have equipped sociologists with ‘a set of very powerful intellectual tools or concepts to think with’. He divided them into 6 categories Turner (1997) – new sciences of complexity have equipped sociologists with ‘a set of very powerful intellectual tools or concepts to think with’. He divided them into 6 categories A new use of cause and prediction A new use of cause and prediction A richer understanding of feedback and iteration A richer understanding of feedback and iteration A revolution in the idea of time A revolution in the idea of time An anthology of recognizable structures and shapes An anthology of recognizable structures and shapes The idea of the attractor as a way of dissolving old dualisms The idea of the attractor as a way of dissolving old dualisms The technique of (non-linear dynamic) modelling The technique of (non-linear dynamic) modelling

7. Complexity as variety (Kelly, 1994) Complexity is the property of a system of being able to adopt a large number of states or behaviours. This leads, in the field of management cybernetics, to the notion of variety engineering Complexity is the property of a system of being able to adopt a large number of states or behaviours. This leads, in the field of management cybernetics, to the notion of variety engineering There seems to be a “requisite variety” – a minimum complexity or diversity of parts – for such processes as self-organization, evolution, learning and life There seems to be a “requisite variety” – a minimum complexity or diversity of parts – for such processes as self-organization, evolution, learning and life What is variety? When enough variety is enough? What is variety? When enough variety is enough?

8. Applying complexity science in organizations Ralph Stacey (1996) He saw the science of complexity as providing a ‘new frame of reference’ to break out of the trap of thinking of successful organizations as ‘systems tending to states of stable equilibrium adaptation to their market, societal, and political environments’ He saw the science of complexity as providing a ‘new frame of reference’ to break out of the trap of thinking of successful organizations as ‘systems tending to states of stable equilibrium adaptation to their market, societal, and political environments’ Regards a ‘complex adaptive system’ (CAS) as a system that Regards a ‘complex adaptive system’ (CAS) as a system that Consists of a large no. of agents interrelated non-linearly Consists of a large no. of agents interrelated non-linearly Interacts with other CAS to form the environ. to respond to Interacts with other CAS to form the environ. to respond to Employs feedback Employs feedback Acts in relation to tits environment and observes responses Acts in relation to tits environment and observes responses

9. Chaos theory and strange attractors ‘Butterfly effect’ – Edward Lorenze ‘Butterfly effect’ – Edward Lorenze A means to convey the extreme sensitivity of the systems that emerge (the idea that a butterfly flapping its wings over the Amazon could lead to a hurricane on the other side of the world A means to convey the extreme sensitivity of the systems that emerge (the idea that a butterfly flapping its wings over the Amazon could lead to a hurricane on the other side of the world Attractor – (pendulum) Attractor – (pendulum) Things in motion being pulled toward a definitive point or region during its cycles or periods Things in motion being pulled toward a definitive point or region during its cycles or periods It is as if things in motion have no degrees of freedom in their choices of movement It is as if things in motion have no degrees of freedom in their choices of movement ‘Point attractor’ = the position a pendulum swings back to when it comes to ‘rest’ ‘Point attractor’ = the position a pendulum swings back to when it comes to ‘rest’ ‘Pendulum fluctuation’ = closed-loop attractor ‘Pendulum fluctuation’ = closed-loop attractor ‘Strange attractor’ = pattern results from a non-linear chaotic system, characterized by a line infinitely long, never repeating itself, never crossing itself, never following the same path but drawn in limited space and continuing indefinitely ‘Strange attractor’ = pattern results from a non-linear chaotic system, characterized by a line infinitely long, never repeating itself, never crossing itself, never following the same path but drawn in limited space and continuing indefinitely

10. Chaos theory and strange attractors Meri (1995) – 4 types of human behaviour, related to understandings from chaos theory and the different forms of attractors Meri (1995) – 4 types of human behaviour, related to understandings from chaos theory and the different forms of attractors Repeating former behaviour in the same way, e.g. industrial repetitive tasks Repeating former behaviour in the same way, e.g. industrial repetitive tasks Varying behaviour slightly and predictably, e.g. a man shaving his face Varying behaviour slightly and predictably, e.g. a man shaving his face Adapting new behaviours that intermix linearity and non- linearity, e.g. immigrating to a new country Adapting new behaviours that intermix linearity and non- linearity, e.g. immigrating to a new country Chaotic behaviour leading to a new, more complex mode, e.g. social chaos as in Russia in the 1990s Chaotic behaviour leading to a new, more complex mode, e.g. social chaos as in Russia in the 1990s

11. Soft systems methodology (SSM) Read appendix D, page 192 Read appendix D, page 192 Understand SSM as a learning system; study the figure on page 203 (appendix D) Understand SSM as a learning system; study the figure on page 203 (appendix D) Compare SSM with HSM Compare SSM with HSM

12. CSA case study Read part 4 of block 1, page 141 Read part 4 of block 1, page 141 Revise your understanding by going through the answers of SAQs (self-assessment questions), they will help in answering TMAs Revise your understanding by going through the answers of SAQs (self-assessment questions), they will help in answering TMAs Read appendix B, page 156: CSA case study Read appendix B, page 156: CSA case study The case study is detailed The case study is detailed Figure SA1 on page 143 & rich picture on page 144 will help you understand the whole picture Figure SA1 on page 143 & rich picture on page 144 will help you understand the whole picture Understand the complexity in it Understand the complexity in it Diagram your thoughts Diagram your thoughts Work in groups Work in groups