I’m a big fan of accountability when it comes to aid and development. We should be asking if our interventions have impact, and identifying interventions that are effective means of addressing particular development challenges. Of course, this is a bit like arguing for clean air and clean water. Seriously, who’s going to argue for dirtier water or air. Who really argues for ineffective aid and development spending?
More often than not, discussions of accountability and impact serve only to inflate narrow differences in approach, emphasis, or opinion into full on “good guys”/ “bad guys” arguments, where the “bad guys” are somehow against evaluation, hostile to the effective use of aid dollars, and indeed actively out to hurt the global poor. This serves nothing but particular cults of personality and, in my opinion, serves to squash out really important problems with the accountability/impact agenda in development. And there are major problems with this agenda as it is currently framed – around the belief that we have proven means of measuring what works and how, if only we would just apply those tools.
When we start from this as a foundation, the accountability discussion is narrowed to a rather tepid debate about the application of the right tools to select the right programs. If all we are really talking about are tools, any skepticism toward efforts to account for the impact of aid projects and dollars is easily labeled an exercise in obfuscation, a refusal to “learn what works,” or an example of organizations and individuals captured by their own intellectual inertia. In narrowing the debate to an argument about the willingness of individuals and organizations to apply these tools to their projects, we are closing off discussion of a critical problem in development: we don’t actually know exactly what we are trying to measure.
Look, you can (fairly easily) measure the intended impact of a given project or program if you set things up for monitoring and evaluation at the outset. Hell, with enough time and money, we can often piece enough data together to do a decent post-hoc evaluation. But both cases assume two things:
1) The project correctly identified the challenge at hand, and the intervention was actually foundational/central to the needs of the people at hand.
This is a pretty weak assumption. I filled up a book arguing that a lot of the things that we assume about life for the global poor are incorrect, and therefore that many of our fundamental assumptions about how to address the needs of the global poor are incorrect. And when much of what we do in development is based on assumptions about people we’ve never met and places we’ve never visited, it is likely that many projects which achieve their intended outcomes are actually doing relatively little for their target populations.
Bad news: this is pretty consistent with the findings of a really large academic literature on development. This is why HURDL focuses so heavily on the implementation of a research approach that defines the challenges of the population as part of its initial fieldwork, and continually revisits and revises those challenges as it sorts out the distinct and differentiated vulnerabilities (for explanation of those terms, see page one of here or here) experienced by various segments of the population.
Simply evaluating a portfolio of projects in terms of their stated goals serves to close off the project cycle into an ever more hermetically-sealed, self-referential world in which the needs of the target population recede ever further from design, monitoring, and evaluation. Sure, by introducing that drought-tolerant strain of millet to the region, you helped create a stable source of household food that guards against the impact of climate variability. This project could record high levels of variety uptake, large numbers of farmers trained on the growth of that variety, and even improved annual yields during slight downturns in rain. By all normal project metrics, it would be a success. But if the biggest problem in the area was finding adequate water for household livestock, that millet crop isn’t much good, and may well fail in the first truly dry season because men cannot tend their fields when they have to migrate with their animals in search of water. Thus, the project achieved its goal of making agriculture more “climate smart,” but failed to actually address the main problem in the area. Project indicators will likely capture the first half of the previous scenario, and totally miss the second half (especially if that really dry year comes after the project cycle is over).
2) The intended impact was the only impact of the intervention.
If all that we are evaluating is the achievement of the expected goals of a project, we fail to capture the wider set of impacts that any intervention into a complex system will produce. So, for example, an organization might install a borehole in a village in an effort to introduce safe drinking water and therefore lower rates of morbidity associated with water-borne illness. Because this is the goal of the project, monitoring and evaluation will center on identifying who uses the borehole, and their water-borne illness outcomes. And if this intervention fails to lower rates of water-borne illness among borehole users, perhaps because post-pump sanitation issues remain unresolved by this intervention, monitoring and evaluation efforts will likely grade the intervention a failure.
Sure, that new borehole might not have resulted in lowered morbidity from water-borne illness. But what if it radically reduced the amount of time women spent gathering water, time they now spend on their own economic activities and education…efforts that, in the long term, produced improved household sanitation practices that ended up achieving the original goal of the borehole in an indirect manner? In this case, is the borehole a failure? Well, in one sense, yes – it did not produce the intended outcome in the intended timeframe. But in another sense, it had a constructive impact on the community that, in the much longer term, produced the desired outcome in a manner that is no longer dependent on infrastructure. Calling that a failure is nonsensical.
Nearly every conversation I see about aid accountability and impact suffers from one or both of these problems. These are easy mistakes to make if we assume that we have 1) correctly identified the challenges that we should address and 2) we know how best to address those challenges. When these assumptions don’t hold up under scrutiny (which is often), we need to rethink what it means to be accountable with aid dollars, and how we identify the impact we do (or do not) have.
What am I getting at? I think we are at a point where we must reframe development interventions away from known technical or social “fixes” for known problems to catalysts for change that populations can build upon in locally appropriate, but often unpredictable, ways. The former framing of development is the technocrats’ dream, beautifully embodied in the (failing) Millennium Village Project, just the latest incarnation of Mitchell’s Rule of Experts or Easterly’s White Man’s Burden. The latter requires a radical embrace of complexity and uncertainty that I suspect Ben Ramalingan might support (I’m not sure how Owen Barder would feel about this). I think the real conversation in aid/development accountability and impact is about how to think about these concepts in the context of chaotic, complex systems.