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Confronting the monster of measurement in complexity

September 23, 2022 By Chris Corrigan Complexity, Evaluation, Featured

In our Complexity from the Inside Out program, we do a session on evaluation, looking at some of the implications that complexity has for traditional models of monitoring and evaluation. This is especially an issue in the non-profit world where organizations find themselves managing complexity while being subject to requirements from funders that treat their operations as if they were ordered and predictable.

It is common for participants in these sessions to ask the question “Complexity is all good, but how do we actually deal with the funding bodies that want us to measure everything and create targets?”

Well, this report from a series of conversation convened by the UN Development Program offers a helpful starting point for having these conversations with funders. Here are some of their framing questions:

  • How can we measure in ways that enable and incentivize learning and adaptation?
  • For whom and why do we measure (recognizing that measurement is often an extractive activity done to satisfy a donor rather than something with the primary objective of learning and empowering local change agents)?
  • What should we measure when we are just starting out (e.g. at the intervention design stage) given we may not know what solutions or success will look like? What is the role of baselines and how do we change measures as we learn and adapt?

In my experience, having these conversations early on is critical so that a grantee working on a complex project and their funders can create an evaluation approach that is coherent with the work they are doing. In this article you will find many good conversations starters and framing ideas to help start this co-creation without alienating anyone in the conversation. It pays to meet people where they are at, and that includes funders and folks that are wedded to ordered approaches to evaluating change work despite the reality that those approaches might not work, or even be harmful, to a complex project.

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