Data Collection (and Analysis) as Development

Here’s a paragraph from a boarder-line scathing short essay on “Data Driven Development Decisions” posted by The Springfield Centre. A self-proclaimed “leader in the market systems approach to development in low and middle-income economies – also referred to as making markets work for the poor”. The central point of the essay is this: setting the monitoring and evaluation function of your program apart from the rest is antithetical to the purpose of the development project.

Essentially, the job of a development programme aiming to stimulate systemic change, is to get one over on the system. Systems are pretty knowledgeable. Of all the things there are to know, they know most of them. You have to find out (or try to find out) something that it doesn’t know in a way that benefits the poor. That might be a business model that the system didn’t know was profitable, a function that the system didn’t know was needed to improve efficiency, or an input that the system didn’t know was more cost effective. One thing that systems – particularly in developing countries – aren’t that great at is producing and aggregating information into nice little digestible packages. So, in order to find the little nuggets of information that might allow you to change the system, you need to put in the effort – and that effort is in data collection.

A few things:

First, yes. I happen to agree that the key effort of a development project (for those who aren’t poor at least) is to collect and analyze data. However, it’s not just any data collection. The necessary qualifier is the collection of good data that actually informs about the things we think the data is telling us. A huge problem is collecting data that is of poor quality and doesn’t actually inform about any pertinent questions.

Second, what is data collection? Data collection need not always be quantitative. Lots of really good work has been done with careful qualitative data collection and analysis. I cut my teeth in development studies in the IDS program at Calvin College. It was (and still is) a great program and has been integral in my education and career, but most folks in the program seemed to have a bias against quantitative data collection and analysis. This might be because reading and understanding quantitative evaluations and studies is more difficult (when anyone is first learning) than reading and understanding qualitative evaluations and studies. However, once I actually got out into the world and started collecting my own data I realized that careful qualitative data collection is much more difficult and time intensive than careful quantitative data collection.

Third, It seems to me that many who are either (a) averse to working in monitoring and evaluation or (b) who resist making it the key function of their program (and not just a function to appease donors), hold these feelings because they believe that monitoring and evaluation is boring. They were first interested in development work because they wanted to help people directly and that (somehow) certainly doesn’t include sitting behind a spreadsheet all day.

I have two responses to this: (a) Well, good development is actually (strictly speaking) boring, not very glamorous, and doesn’t photograph well. (b) Although, if one can get past the mundane tasks (that are actually part of every job) the task of development is actually super exciting. Being at the forefront and being able to witness (perhaps) the most dramatic reduction in human suffering of all time is certainly exciting and anything but boring.


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