One of the unfinished tasks in From Poverty to Power is developing a better model for analysing processes of change, so I’ve been going back to my prehistoric roots as a physics undergraduate, and reading about complexity and chaos. Exploring the Science of Complexity is a newish (February 08) paper from the Overseas Development Institute that wrestles with the question posed by Robert Chambers back in 1997, does the new physics provide ‘a deep paradigmatic insight, an interesting parallel, or an insignificant coincidence’ for development practitioners?
Complexity science’s starting point is that Isaac Newton’s reductionist picture of a world in which change happens in a smooth and predictable fashion, is a mirage: in real life, change is almost always hard to predict and happens in fits and starts (think of the weather, stock markets, traffic, love or crowds): as one thinker memorably observed ‘calling a situation non-linear is like going to the zoo and talking about all the interesting non-elephant animals you can see there.’
The first challenge for the authors of the ODI paper is to describe complexity science for non-scientists. It turns out to be more of a broad current of thinking than a single, well defined discipline. They narrow it down to three sets of concepts:
1. Complex systems are characterised by interdependence and high levels of feedback, which means that in practice behaviours emerge unpredictably from the interactions between the parts. Example: climate change or weather systems, which are full of feedback loops between atmosphere, water and land.
2. Change within such systems is non-linear (i.e. not described by ‘X is proportional to Y’), discontinuous and highly sensitive to initial conditions. Example: the infamous ‘butterfly’s wing’ that triggers a series of changes leading to a hurricane half way across the world, or the sand in an egg timer: a steady stream of sand falls onto the pile, but the avalanches of sand that fall down the side of the pile vary in size and are entirely unpredictable.
3. ‘Adaptive agents’ in a system both react to and shape the system. Out of numerous individual processes of ‘self organization’ by adaptive agents, an overall pattern emerges that is impossible to predict in advance. Example: the movements of flocks of birds or schools of fish. In development terms, the parallel would be seeing poor people as adaptive agents, generating their own politics and processes – the job of development agencies is to accompany and support such processes, but not to try and steer, still less control, them.
How is all this relevant to development? Reading the paper, a lot of the concepts resonate with thinking in the development field: trying to grasp the complexity and uniqueness of different change processes; scepticism of grand plans; the NGOs’ preference for getting processes right rather than emphasizing particular outcomes or targets. Some of the points that grabbed my attention:
Planners v Searchers (to steal William Easterly’s shorthand): in an unpredictable world it is futile to devise elaborate plans to reach specific outcomes. The authors cite the anti-globalization movement and the US marines as examples of an alternative approach: establish a simple set of principles (in the case of the marines, capture the high ground, stay in touch, and keep moving), but then accept that where this leads is context-specific and unpredictable. This is the antithesis of the kind of planning set out in the ‘logical frameworks’ of organizations like DFID (the UK Development Ministry) – ‘smart’ (specific, measurable, achievable, realistic and timebound) planning may actually be quite dumb. What would NGO campaigning look like modelled on the US marine corps?!
More History, less Maths: Separating out causes and effects is central to most economic modelling – but if causes and effects are multiple and intertwined through feedback loops, they cannot be disaggregated: if cause A leads to effect A* and cause B leads to B*, the effect of A + B combined will not necessarily be A* + B*. Instead, we may be better advised to rely on broader lessons from history and ‘soft’ social science, rather than pursue the seductive certainties of ‘hard’ predictive science. Even with the soft stuff, though, the path dependence of most processes means that we have to be careful in applying the lessons of one historical experience to another context. The paper argues that the search for ‘best practice’ should be replaced by a search for ‘good principles’.
Monitoring, Evaluation and Learning: The paper argues that MEL, a growth industry across the development sector, should respond to complexity not by giving up and going home, but by ‘shifting to value learning from unexpected outcomes’, as well as using drivers of change and scenario planning. I think it may be even worse than that – if every situation is specific, what ‘learning’ would actually help design or improve work in other places and times? It’s not at all clear from the paper.
Leadership: another vogue word in development NGOs. The paper argues that in a world of complexity and chaos, leaders should be more Che Guevara than Stalin, acting as subversives, disrupting and challenging existing taboos, patterns of thought, and practice, encouraging novelty, and ‘interpreting rather than creating change’.
Finally, the ‘edge of chaos’ – sounds like a nightmare, but it turns out that edge of chaos situations, poised between anarchy or social breakdown on one side, and paralysis and inertia on the other, are ‘the place of maximum innovation within human systems’. There, either side of a discontinuity, small inputs can trigger a big jump – the proverbial straw that broke the camel’s back. But managers and planners beware – they are not places where you can control events. ‘Change agents’ be they NGOs, grassroots organization or political parties, should therefore seek out such edge of chaos situations, work out suitable US marine style basic principles, and then work with energy and imagination, seeing where it leads. Sounds like fun. This has obvious resonances with the previous blog discussion on shocks and change.
Overall, I go with the ‘useful metaphor’ category in Robert Chambers’ list of options – anyone disagree?