From Planning to Scanning
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Oduber
December /999
From Planning to Scanning - the implications of chaos and complexity theoy for otganisation development
Bob Walder could never predict the resting place an individual
77« sciences of chaos and conzplexitv are providing many interesting insights into natural systems. /articulary around
grain.
the possibzlitv ?f prediction in chaotic s stems and the enle/gence on sci/Loiganised behaviour in complex ones. As the
In some circumstances though, such systems often
show great stability. At other starting values the
business environment becomes more connected (and hence complep and e /iihits mont chaotic Jeatures this points lo new
series above quickly converges to a single value or flip flops between two. However, in certain ranges ii displays the unpredictable behaviour shown. The cocktail of new behaviours fir the successful company of areas of stability arc known as attractors and areas of chaos exist as we move from one to another. toozoriow. inetaIhoïv for thr organisation. This paper explores the current situation whilst a second paper (to Ji7low) presents a radical
Systems found near attractors have very limited adaptability (a single value gives little room manoeuvre). In nature such systems tend to fall out of harmony with their environment and die out.
-ooüoo-
\Vho would have thought a few years ago that the central planning that was one of the cornerstones of communism would be so completely discredited and
that we would see such widespread faith in the 'hidden hand' of market f'orces. This failure, though, is an inevitable consequence of the emerging theories of chaos and complexity.
Chaos Theory - tells us that behind apparent disorder (a swirling stream) there are in fhct discernible patterns and relationships between events. These patterns allow us to determine hounds of behaviour but the detail is sometimes chaotic. \Vhen talking about non linear system (cg ones with feedback loops - most of the real world) it is often impossible to predict future
Complexity theory -
tells
us that groups of connected entities will
naturally organise themselves to produce group entities with their own (mcta) behaviours. \Ve see
outcomes. This is not a feature of the size of the system it is frature of the nature of non-linear
this in nature as cells organise themselves into plants and these into forests and so on. Furthermore quite simple behaviours in the original entities can produce quite complex metabehaviours. A computer simulation was created of flying birds each with the following simple rules:
systems. The box illustrates the projection forward of Ax (l-x). a time series with on/v two variables, x Ihe two lines show the difference in behaviour with
a 1% change in the starting value of variable A. They track each other for a few cycles but are soon conipletely dihlerent.
Steer to avoid crowding
lo us e an analogy, if ne were to pour sand from a jug onto a single point we would be able to predict the shape çor boundary) of the emergi ig pile but \ve
Steer toward the averag
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