What's So New About Complexity Theory? -- Peter Murray, August 4, 2002
46th Annual Meeting of the International Society for the Systems Sciences (ISSS), Shanghai, P.R. China, August 2-6, 2002.
Sunday, August 4, 2002, 1:45 p.m., Session on Systems Practice
This digest was created in real-time during the meeting, based on the speaker's presentation(s) and comments from the audience. These should not be viewed as official
transcripts of the meeting, but only as an interpretation by a single individual. Lapses, grammatical errors, and typing mistakes may not have been corrected. Questions about content should be
directed to the originator. These notes have been contributed by David Ing (daviding@systemicbusiness.org) at the IBM Advanced Business Institute ( http://www.ibm.com/abi ).
[only 2 of 6 papers showed up for the Systems Practice session, so the time expanded]
Less to be gained by mathematical approach
More of a metaphor approach
Two complexity narratives:
Basis
Molecular, e.g. a flock of birds
Simple units, following simple rules, although the whole is complicated.
Network, e.g. a network of people who interact, so that the network as a whole behaves differently
Behaviour of the system as a whole emerges from the rules.
Then can define how the units work, and see behaviour at the totality.
Attractor:
Water flows towards the centre -- a point attractor.
If there's a hump, then the water flows around it -- a cyclical attractor.
Also, strange attractors, where the system can flow around in the attractor, with an unpredictable behaviour.
A powerful idea in complexity: the basic rules, when they work together, create an environment, where the thing is following a track, but the track is unpredictable.
Deterministic - chaos: This is how a company might operate.
Even though can influence things, are moving around in a confined space.
If you think about the interactions, the shape of the attractor can change.
Not only does the water flow around the attractor unpredictably, the attractor may not be the same as yesterday.
Fitness: Stuart Kauffman
Fitness landscape, as some success criteria.
A landscape between peaks.
Want to tweak so that we're closer to a peak.
Challenge: when you see another peak that is desirable, need to go down before climbing that new peak.
Might be trapped in a peak.
[Starting to talk like this is how companies behave, although we don't really know if they do].
Network fitness:
Could have strong or weak coupling.
Coupling may not be appropriate to the situation, e.g. a rigid structure (bureaucracy) which isn't good in a crisis.
Self-Organization: Even some mechanical systems organize themselves.
Can have chaotic situations, which are stable in some places.
When you freeze water, the molecules line up, and you get order.
The order emerges, and it's not obvious that the order is built-in.
Dissipative system: pump in energy, and it maintains a local stability despite the environment.
Network view:
Edge of chaos: A creative environment needs to be a balance between chaos and order.
Teaching on the MBA
Hull has an MBA structure on a modular basis, i.e. strategy for 5 days, then a week to write assignments, and then off to something else.
An instructor gets parachuted in, and then needs to fit in immediately.
Case study:
Usually pretty sloppy about the question: "Here's a company. It's in trouble. What are you going to do about it?"
Some people move towards an attractor: rather discuss football; or "I will find the right answer".
Group is forming into something.
Then is football is unproductive, that can nudge the students towards another attractor.
Fitness: The group will develop its activity, pull in the information it needs, and will deal with the case.
Some students will take a "careful" line.
Might think that the games should have perfect attractor, ....)
Need to give up a peak to go to another peak.
Self-organization: Would like to be positive.
Self-organization requires creativity.
Ofori Dankwa and Julian (2001)
They were looking at "complexity (which we can call their Level 2 and 4).
Level complexity: simple, one theory that explains a relatively static situation, e.g. Porter's Five Forces, Maslow's hierarchy.
Level 2 complexity, on organizational life and time cycles, like fitness landscapes.
Drucker 1954, "What business are we in?"
Prahalad, Competing for the Future
Level 3 complexity (high): Competing values.
Different things might happen -- network fitness
Like Belbin team roles -- getting a team right.
Emergent process.
Level 4 complexity (very high): complexity and retrainment theories
More self-organization, pulling and pushing.
e.g. Stacey
Metaphors are interesting.
They're fun.
Not proving that they work: many haven't been proved in physical systems and biological systems, let alone human systems.
They help "us" to make sense -- maybe for technical people.
A seduction: if you can write down rules, then can understand human behaviour. (!)
They are re-presentations, repackaging ideas that are well-defined in the management literature.
Some things aren't so complex.
[Comments]
Metaphors: learning in one field can be applied in another field.
Is there a strong cultural component in metaphors?
e.g. Do metaphors of the family work better or worse than metaphors around complexity?
Was sent to Santa Fe Institute for a weekend.
Metaphors versus models.
MBA students, half of whom are technical.
Use a hard system (like VSM) then move towards a soft system.
Complexity fails when it tries to explain subjectivity.
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