The Development Intelligence Lab recently asked sector experts - including Institute Director Chris Roche, Institute Research Fellow Allan Illingworth, Gordon Peake and Jocelyn Condon - whether performance monitoring contributed to improved performance. The results were published in The Intel on the Development Intelligence Lab site with Chris and Allan's response extracted below.
Does performance monitoring lead to better performance?
Often not.
Why? Performance and evaluation systems tend to be short-termist. They focus on the visible, countable and predictable. But we challenge you to think of a single development pathway which is well understood in this way.
Performance systems often ignore the inherently political nature of development in favour of ‘best practice’ world views, ways of knowing and being. They are usually more about accountability (what happened, when?) than learning and adaptation (why has something worked or not, for whom, and what must change?).
But none of this is to say that performance monitoring is pointless.
So, what can be done?
First, we need to reimagine the purpose and practice of evaluation itself. A good starting point is learning from indigenous, locally-led perspectives, and approaches such as the Rebbilib initiative in the Pacific. Drawing from Micronesian master navigators this sees the mapping of voyages and destinations as being defined by what Pacific people value and where they want to go, not set by a foreign brains-trust.
Second, we need to tip the scale of investment away from ‘what happened’ towards more learning, feedback and adaptation. Pooling local knowledge allows the ideas, beliefs and relationships which underpin social change to be understood and shared.
Finally, a solid look at governance arrangements for performance systems under a new development strategy is key. We already recognise the importance of gathering multiple perspectives, but we can do better to bring these to bear when it comes to the use, or indeed non-use or abuse, of findings.
This contribution is republished from The Intel, Development Intelligence Lab. Read the original.
