Data Collected, Intelligence Lost: The Structural Suppression of Learning in Community-Based MEAL Systems in Post-Conflict Northern Uganda

Monitoring, Evaluation, Accountability and Learning (MEAL) systems across community-based programs in Sub-Saharan Africa are predominantly architected to satisfy upward donor reporting obligations rather than to support adaptive program management. This paper draws on field observations from child protection, education, livelihood, and youth programming across a post-conflict district to diagnose a structural misalignment between what MEAL systems measure and what field-level programs actually need to learn. Using the principal-agent framework, the analysis shows that local implementing organizations, as agents, are compelled to optimize data flows for the informational needs of distant donors, as principals, at the systematic expense of internal and downward learning. Five practitioner arenas are examined: school dropout reintegration, caregiver engagement, community feedback mechanisms, Village Savings and Loan Associations (VSLAs), and youth-led monitoring. Each is analyzed through a consistent diagnostic lens: the compliance metric extracted for upward reporting, the operational intelligence suppressed by aggregation, and the low-cost adaptive pivot achievable without additional data collection burden. Situating this diagnosis within complex adaptive systems theory and the Made in Africa Evaluation paradigm, the paper argues that post-conflict, rural contexts operate as non-linear systems in which rigid logframe architectures systematically produce epistemological blind spots. The core finding is not that organizations collect insufficient data; it is that data already sitting in case files, VSLA ledgers, scorecard registers, and youth monitoring logs is seldom repurposed for learning. The paper concludes with a zero-added-burden operational blueprint for practicing evaluators, offering concrete low-cost internal review mechanisms that can be embedded within existing MEAL infrastructure.