From M&E to L&A: Improving What We Measure and Why

This piece by Dave Algoso originally appeared on his blog, algoso.org, on August 27, 2015.

I had a chance to catch up with Alan Hudson yesterday, and the conversation brought me around to an idea that I’ve been trying to articulate for a while. Though admittedly still a bit abstract, here’s the idea.

We’ve made monitoring and evaluation—grouped together as M&E—a core expectation of any social or development effort. As I’ve argued before, M&E essentially serves a management function by supporting decisions at either the program/project level (for monitoring) or at the policymaker/donor level (for evaluation).

At any level, the practice is synonymous with merely tracking and measuring. You operationalize the practice by creating an M&E plan, hiring an M&E officer, and producing M&E reports. And that’s all well and good—I should know, because I’ve been that officer and written those reports.

However, both in M and in E, what we really care about is not the numbers that show up in the report. What we care about is what the numbers tell us and what we do with the numbers. This started to come out at last year’s M&E Tech conference, which focused heavily on the idea of feedback loops. It was an important recognition that the whole point is the changes that come about from M&E.

Put another way: what we really care about with M&E is what we learn and how we adapt in response to that learning. The next logical step would be to de-emphasize monitoring and evaluation as operational functions, replacing them with learning and adaptation: moving from M&E to L&A.

To make this concrete—perhaps for someone looking to apply complexity thinking, DDD, and related agendas in their work:

• First, jettison the requirements for an M&E section in your project proposals and plans; replace that with an L&A plan.
• Second, frame that plan around organizational processes and culture, rather than the research methods and indicators.
• And finally, don’t hire M&E officers who think like researchers; instead, hire L&A advisors ones who think like consultants.

An important caveat is that L&A in practice would only create a first-order feedback loop, where information becomes available to inform a self-motivated change. A second-order feedback loop occurs when the information actual compels the change through some form of accountability. LA&A: learning, adaptation, and accountability. But I suspect that may be a bridge too far for much of the social and development sector.