Rather than lots of new resources or fancy new interventions, Bill Gates puts data and measurement at the heart of improving the human condition. In his annual letter, he argues that evaluation and “feedback with precise measurement” make the difference between multiplying innovation and stopping it in its tracks. He credits data collection and evaluation – and learning from them – for reducing child mortality and improving student achievement, and sees them as critical for eradicating polio and advancing global food security.
Like Gates, the Millennium Challenge Corporation takes an evidence-based approach to development. We know that monitoring and evaluation—collecting data on what investments do and what impact they have—is key to reducing poverty. Without a rigorous results measurement system, we risk business as usual, doing things as we have always done them, without testing our assumptions about what really works. In a time of scarce resources for development, we simply can’t afford not to learn everything we can about what works and what doesn’t work. And we must then use that learning to increase our impact.
That’s why MCC employs a strong monitoring and evaluation process along our whole continuum of results and why MCC is pushing itself to learn and adapt our approach based on that learning. MCC has learned a lot from our first set of impact evaluations. In Nicaragua and El Salvador, we saw a direct link between farmer training activities and increases in farm income. Here, we are learning from what went right.
But it is where things didn’t go as we expected that we’re learning the most. Findings from Ghana and Armenia are making us question whether starter kits—a very common practice of offering inputs like seeds, fertilizer and equipment—really worked as we expected to create incentives and opportunities for farmers to adopt new techniques and change their behaviors in ways that will lead to increased income. Likewise, results from several countries are testing our assumptions about how long it takes farmers to adopt new practices, and for this to translate into increased income.
These lessons are helping us improve our practice, both in terms of how to do farmer training programs better and how to do evaluation better. We not only have the kind of feedback loop that Gates calls for, we are sharing it publicly so others can benefit from our learning as well. This is not always easy. Being transparent about results, even when we fall short of what we aimed to achieve, invites a lot of scrutiny. But it is central to accountability and learning.
We are delighted to have Bill Gates on the side of evidence-based development and offer him three cheers for elevating data and measurement from what many think a mundane topic to their rightful place as things that can change the world.