Here's where trust is genuinely built or destroyed. Every research organization makes mistakes. Mislabeled samples. Coding errors in statistical analysis. Protocol deviations during recruitment. The question isn't whether errors occur—it's what happens when they're discovered.

If Monitoring, Evaluation, and Learning (MEL) were only about tools and templates, most development organizations would be doing exceptionally well. They have log frames. They have indicators. They have dashboards, frameworks, and reports stacked neatly in shared folders. Yet, despite all this structure, the same questions keep coming back: Why didn’t this programme achieve what we expected? Why does the data look good, but the reality feel different? Why do we keep repeating

This post explores the profound connection between my passion for chess and my work in data, technology, and health research.