Prompted by an interesting blog on the results-agenda for development aid from Owen Barder this weekend I’m interested to hear some of the language and some understanding of systems and complexity permeating into the development aid environment.
The discussion talks in and around the impact of what we might call Performance Management. It seems that Aid Agencies have traditionally not been used to accounting for the benefits actually achieved, but are now required to so more and more e.g. as the UK taxpayer apparently needs to know, but I suspect the UK Govt wants to quantify bang-for-buck as it juggles it’s “savings” priorities. It seems the key questions are around whether measurement changes the nature of the aid itself (sometimes this is appropriate) but dangerously, the aid ends up being prioritised primarily to improve the measurement statistic alone i.e. managing the outputs, rather than improving system’s effectiveness. Sound a familiar problem ?
In more closed, well-defined, harder systems and processes, feedback of key measurements is often key to control and stability. In open, less-well defined, heuristic, softer systems – often where people are involved, motivations are not entirely clear, outcomes less predictable – hard statistics have narrower meaning, and should be used with caution as a means of feedback.
Anyway here’s my response to Owen, trying to see if this is familiar ground for him:
Owen, a very interesting piece (and some of the comments)
It’s fascinating to hear some of the language of systems thinking permeating through this discussion. I’m not familiar with the aid environment and methods, but I’m wondering if this manifests at some stage in , for instance, visual representations of the complexity that is talked about, in say causal diagrams – characterising system structure and causal relationships, or where necessary definable processes. These relationships can be between ”hard”, clearly definable parameters, some of which one might term as “results”, or softer, qualitative, maybe even gut-feel parameters. It ehances the ability to identify the positive (self-reinforcing) feedback loops, negative (self-limiting) feedback loops through which the outcomes play out. By extracting key features, one might show how, for instance, a results-driven system could lead to unintended consequences – for a wider audience. I’m not describing anything particular new here, but I’m interested to see if some of the systems concepts and methods are being applied.
Owen, is this old ground for you ?
Owen replies: John: thanks. No, this is not old ground for me. I believe that development has much to learn from this thinking about complex and emergent systems.
So, is this an OPPORTUNITY FOR RESEARCH ?