Summarising complexity and some of its influences

I recently wrote an article for the Shiatsu Therapy Association of Australia on complexity for their journal ‘Pointers’. Following is a modified excerpt outlining in general terms what a complex system is and some of the ways such theories are being interpreted in organisations and academia:

I would like to begin by summarising some fundamental features of complex systems:

  1. They are made up of many parts which all interact simultaneously and many of which can influence each other (think of an economy, an ecosystem or even the dynamics at a party).
  2. They are non-linear, meaning that small changes can have big effects and big changes may have small effects.
  3. They are capable of self-organising; all of their parts can come together spontaneously to create a pattern in how they relate. Such a pattern is described as an ’emergent property’. One example would be a stock market crash, another would be the formation of a school of fish.
  4. Stable patterns in these systems are known as attractors. It can often be very hard to understand the conditions that will lead to a stable pattern.
  5. The patterns that these systems generate are inherently unpredictable on many levels, yet still predictable in some ways.

As these ideas percolate into mainstream western culture there is a growing awareness that linear, analytical thought is not always useful when dealing with complexity. If you truly accept that the world is interconnected, inherently unpredictable, continually evolving and nonlinear, then you live in a world where simple cause and effect thinking is not useful anymore. Disciplines such as ‘systems thinking’ have sprung up to try and address this. Systems thinkers aim to shift the focus from looking at the basic building blocks in a system to seeking to understand the principles of organisation in a systemi. They recognise that each part of a system is embedded in a broader complex whole which needs to be taken into account to truly understand that part. Prominent systems thinker Peter Senge goes further to talk about systems as ‘holographic’ii by which he means that the whole is present in the parts. He describes this as very subtle, and I agree, for the whole in this sense is not a thing, it is the ‘essence’ or ‘spirt’ of the whole that will be present in each part. This notion can be traced back to the scientific method of Johann Wolfgang von Goethe in the 17 and 1800s who came to this conclusion through his deeply experiential study of plants. He called what I am calling the ‘essence’ of a plant the ‘urpflanze’iii. In this model, rather than panning back to get an overview of a system, you dive into it to get a sense of the whole through the parts. Whilst this way of seeing is not very prevalent yet, via influential thinkers like Peter Senge it is beginning to gain some attention.

Responses to complexity are cropping up in many different forms in many different disciplines. The Presencing Institute recently launched an online course called the ULab working with ‘Theory U’ and had 30,000 participants from 190 countries in the first intake. This course leads people thorough a process “to co-sense and co-shape the future that you feel is wanting to emerge in your work, and life, right now.”iv Whilst they don’t directly talk that much about complex systems, they have a grounding in this theory as is evident in the writings of people teaching in this coursev. This idea of co-sensing and co-creating I see as a direct response to the unpredictability and self-organising capacities of our societies and organisations due to their complexity. Another more literal response to systems sensing has been around for a long time and involves taking physical measurements (such as the creation of indicatorsvi or ecological footprint calculationsvii) as a form of sensing a system, but this is very different to the more intuitive ‘sensing the emerging future’ of the Presencing Institute.

Another well developed response to complexity is agent based modelling, where systems are modelled in computer simulations of ‘agents’ interacting together. This is yielding insights in fields as diverse as economicsviii to epidemiologyix and starting to shift some of the underlying metaphors that shape how we understand the world. Some of the counter intuitive results that emerge in these models are changing the ways people think. People are starting to recognise the limitations of analytical thought in understanding complexities of the living the world. Mechanistic metaphors of the world such as an intuitive belief that ‘a large intervention is required to get a large result’ are starting to shift.

Summarising some of the current responses to complexity in organisations and academia:

  1. There is a shift from focussing on the individual parts of a system to how the system is organised (a shift from focussing on things to relationships).
  2. There is a recognised need to stay connected to what is happening in a system (to sense what is going on and hence improve feedback mechanisms).
  3. Agent based modelling is used in the scientific community rather than analysis to try and understand complexity as the limits of analysis become apparent.
  4. Some people are starting to recognise a deeper sense of holism in complex systems where the whole is seen as present in the parts.

There are of course also other ways people are responding to complexity, but those above are some that I am most familiar with.

iFritjof Capra, The Web of Life, 1997, Flamingo, p29

iiPeter Senge speaking at the FIELD-Support Conference in September 2014: https://www.youtube.com/watch?v=OqMAi4h9zVQ

iiiSee Henri Bortoft’s book for more information on Goethe’s methods: The Wholeness of Nature: Goethe’s way of Science, 1996, Floris Books

ivFrom the home page of the free online course called “Transforming Business, Society, and Self with U.Lab” http://www.edx.org/course/transforming-business-society-self-u-lab-mitx-15-671x

vSee both Peter Senge, The Fifth Discipline, 1990, 2006, Doubleday and Otto Scharmer, Theory U, 2009, Berrett-Koehler. Both books contain explanations of complexity.

vi For an introduction to what an indicator is, view this short video by Alan AtKisson https://www.youtube.com/watch?v=lHO4qvKOTig

viiFor more about ecological footprints see the Global Footprint Network’s webpage www.footprintnetwork.org

viiiMelanie Mitchell, Complexity: A Guided Tour, 2009, Oxford University Press, p9

ixRicard Solé, Phase Transitions, 2011, Princeton University Press, chapter 9

 

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