Using Monitoring Data for Adaptive Management
This post is written by Asmare Melesse, Monitoring, Evaluation, and Learning Director on FTF Ethiopia Value Chain Activity
For KNOWvember at Fintrac, staff around the world convened virtually to reflect on our knowledge - how we produce it and use it - for stronger agricultural development results. This is the first in a series about monitoring, evaluation, and learning as part of that effort (read the second and third ones here and here). For more information, contact firstname.lastname@example.org.
With monitoring and evaluation (M&E), it’s one thing to collect program data, analyze it, and report findings on program achievements against targets. It’s quite another to turn that data into actionable insights for timely decision making. We talk about it across the development industry and at USAID it is codified into the Collaboration, Learning, and Adapting (CLA) framework. I have been a part of multiple data collection initiatives across Ethiopia and it’s not always the case that routine monitoring data makes it off the shelf and into our programs. When it does, of course, it can be game changing.
Our Feed the Future Ethiopia Value Chain Activity (FTFE VCA) team makes it a priority to use M&E data for much more than standard reporting. Our team prepares monthly data visualizations to keep track of targets versus achievements and to motivate our field teams to achieve stronger results. USAID’s CLA framework is an example of successful adaptive management. Two of my colleagues go into much more detail in the second and third posts of this series.
At Fintrac, we are fortunate to have strong systems in place to gather, store, analyze, and visualize our data in actionable ways. For instance, our internal Client Impact and Results Information System (CIRIS) platform allows for routine monitoring data to be continuously entered and reviewed by staff from any location in real time. In Ethiopia, we use this in concert with data visualization tools like Tableau to inform our agronomists, trainers, and other technical staff of monitoring progress on a number of top line indicators such as the total number of direct beneficiaries, youth, or females reached over time. Project leadership also draws on the data to refine their implementation strategy.
In a world where data is an extremely valuable resource, it is refreshing to see it is used beneficially. In our sector, examples abound from using traceability systems for tracking food systems to determining insurance payouts from drought-risk data. We all have the power to use our systems to go further than simple reporting. It’s a matter of prioritizing its use to adaptively manage our projects.