In my first post on our new project(s) in Bangor yesterday I promised to make some comments today on complexity in Government.   Now this is not a definitive post, but the first of many that will come as I think of them and have the time.  I'll use the brambles theme as they are posted but I have learnt not to be too definitive about promising blog post series, it leads to writers block!  This post is going to set the scene a bit, expect more on solutions downstream.

One of the issues that came up yesterday was the hoary old one of objectives.  Now the need to define objectives is reality in government at all levels.  Its a consequence of the engineering myths that grew out of management practice in the 80s, the self-imposed pressure of big ideas and a growing cult of accountability that has swung the pendulum too far from discovery and experimentation.  It's as easy one to deal with at a pragmatic level, you just define a nice generic platitude and work out the measurement system as you go along.  But that smacks of inauthenticity, necessary as it may be.

The problem is that complex adaptive systems have propensities and express dispositions as they evolve.  That means that precise expectations are difficult to set.  In theory that means we need to move to smaller interventions with fast feedback loops and take corrective action.  That approach does not really go with the psychology of government initiatives and in the development sector it is compounded by the desire to fund in bigger buckets and justify results by over idealised promises or expectations.

We then have the linked issue of people who discover complexity theory and then jump on a band wagon without thinking the consequences through.  This results in three cardinal errors:

  • Using complexity theory to describe why things have gone wrong in the past and metaphorically (or literally in some cases) throw up their hands and advocate self-organisation or free market capitalism as the only solution.
  • They focus on modelling as a potential solution, using examples where that has informed human actors,  They tend to confuse a method to create information with a solution.  A common error for good and ill, it's crediting the messenger, the corollary of shooting them.
  • Assuming that everything is complex and forgetting the ability of humans explicitly and implicitly to create constraints that reach the point where we have order and predictability.  This and other aspects of enabling constraints and the role of human cognition make human systems different and in some ways easier to manage, if you think differently.

I have often argue that the modellers who dominate too much complexity thinking are simply peddling a new form of certainty, confusing simulation with prediction. The desire of decision makers to be given advise about what will happen, or to gain accurate probability assessments is legion.  Pandering to it is deadly.

I think the solution to all of these lies in redefining research and investigation and allowing different patterns of behaviour to emerge.  It also means creating an approach to evidence that is inductive in proof, but deductive in creation.  That will be for Brambles III next week.


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Brambles I

I woke bright and early at the Management Centre in Bangor University to a view ...


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Judge not, but enable judgement

After yesterday's productive session at Bangor University I got the train back to London and ...


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