M&E Method Guides

Practical, no-jargon guides to the fundamentals of M&E. Use them to learn the method, then bring AI to speed up the work.

These guides vs AI for M&E guides

These guides cover the underlying M&E methods, no AI required. For step-by-step AI workflows on the same topics, see AI for M&E.

Five guides covering the M&E lifecycle

From planning a MEL system to designing an evaluation, collecting quality data, and turning results into decisions.

Choose an evaluation purpose, design type, methodology, and sampling approach. Includes a TOR checklist and downloadable templates.

A step-by-step workflow from learning questions to a results framework, indicator plan, and data collection schedule.

Choose between household surveys, focus group discussions, and key informant interviews. Includes instrument templates.

A data quality assurance guide covering the five quality dimensions, indicator quality, and a practical DQA process.

Turn M&E data into program decisions: assess quality, clean the dataset, build a learning agenda, and run decision sprints.

Covers quantitative analysis, qualitative synthesis, and how to connect findings to adaptive management decisions.

Decision Guides cover the trade-offs M&E teams hit most often: logframe vs theory of change, output vs outcome vs impact, and dozens more.

These guides cover the underlying M&E methods. For step-by-step AI workflows on the same topics, head to AI for M&E.