RE: Developing effective, inclusive and gender responsive MEAL systems | Eval Forward

Dear Eriasafu,

Many thanks for the post, and good to be in touch on the subject of monitoring, much neglected and given short thrift by the evaluation community.

I like your observation on how time complying to demands of collecting data all the way to the top of the results framework or theory of change, often missing out on the assumption along the way, crowds out time for reflection and learning. I believe such reflection comes in revealing the unknown through listening to and learning from those in need, not measuring those in charge - excluded and underserved communities.

So, how to resolve the issue you raise as to how "MEL/MEAL systems are limited to compliance, outcomes and impact, and rarely include cross cutting issues such as gender and leave-no-one behind principles."

It strikes me as ironic how, as monitoring is all about learning, it, itself, shows a limited capacity to learn about its past. The pursuits of measuring outcomes and impact are not so much limiting as they are mis-guided. Even if you had more time, outcome and impact indicators generate limited value for learning purposes. This is easier said than done in comparison to measuring indicators laid out in some needy theory of change or logic model. Indicators do what they are supposed to do, they measure things that happened, or not, in the past. They don’t tell you what to do. Monitoring does and should not entertain using rigorous – as a statistician would define the term - methods geared to academic concerns and obsessive pursuits of measuring and attributing intervention effects.

Monitoring has different requirements as highlighted above; that is, if it is to help managers resolve their decision uncertainties. Your claim ignores the hegemony of mainly transient, academically inclined western evaluators, and those in the monitoring and results measurement community, addicted to single narratives, and rigid methodological dogmas. Monitoring needs to free itself from these mechanistic approaches; and managers need to step up, afford primacy to the voices and needs of indigenous communities, and take ownership to ensure monitoring does generate insights for decision-making purposes that benefit those who legitimize, not just measure the predicted results defined by those who fund, development and humanitarian aid.

Of course, including gender and ensuring no-one gets left behind is important. However, and without sounding glib, doing this means management not getting left behind by, for example:

  • Pointing out that exploring assumptions matter as much as, if not more than measuring indicators and the ‘system’ needs to be driven by questions defined by those who are its primary users, and they do not include external evaluators;
  • Highlighting how, although numbers are important, they are arguably not as important as learning how, for example, the numbers of men and women or boys and girls came to be and how and how well they interact with  together.

 

Thanks again, and I hope the above helps,

Daniel