Turn evidence into learning, and learning into action.
In complex systems, differences between expected and observed results are often some of the most useful information available. MLE connects monitoring to learning and learning to changed decisions.
The team, donor and landscape need different things.
A useful MLE architecture makes evidence travel between real-time decisions, public accountability and the institutional memory that must survive the project.
The team needs real-time learning
Evidence must arrive at the pace of decision: debrief quickly, revise the maps, update the proposition and change the next foment while the signal is still useful.
Design implication: Internal learning becomes a formal part of implementation, not an informal stream separate from reporting.
The donor needs accountable explanation
Narrative reporting should show what changed, why, who authorized it and how fixed fiduciary, legal and safeguard obligations were protected.
Design implication: Adaptation becomes evidence-based change control rather than retrospective justification.
The landscape needs memory
Relationships, maps, outcome stories, institutional decisions and proposition logs should have a home beyond the intervention team.
Design implication: The record becomes usable by successor teams, local institutions and future investors rather than disappearing with project closure.
Track activity, direction and learning.
Compliance indicators
What did the intervention deliver or spend? Were activities undertaken and obligations met?
Useful for fiduciary and operational accountability. Insufficient on their own for judging system movement or the quality of learning.
Movement indicators
Is the landscape showing signals consistent with movement towards the Alternative HeadingAlternative Heading: A better direction an intervention seeks to support, revised as it learns. It is not a fixed blueprint for a final state.?
Look at changing practices, regulatoryRegulation: Any way actors shape what others can or cannot do, including rules, money, prices, custom and persuasion. It is broader than government regulation. exchange, relationships, institutional behaviour, distribution and feedback – not only biophysical end points.
Learning indicators
Is the team’s read deepening, and does learning alter what it does?
Track the pace of map updates, quality of deliberation, redesign of foments, use of dissent and whether evidence changes decisions.
Make the learning chain visible.
For each foment, preserve the original belief and the evidence that changed it. A successor team should be able to see not only what was done, but why the intervention evolved.
If we do X, we believe Y may happen because of Z. What signals and risks will we watch?
What actually happened? What moved, failed to move, surprised us or affected people differently?
What does the response reveal about the maps, feedback loops, power or practice configuration?
What will we pursue, modify, reinforce, abandon or investigate next – and why?
Look backwards from change and alongside action.
Outcome harvesting
Start from observed changes, verify them, then work back to how the intervention plausibly contributed.
Most Significant Change
Collect stories of consequential change and use structured deliberation to interpret why participants consider them significant.
Developmental evaluation
Embed evaluation close enough to the intervention to inform real-time sensemaking and adjustment alongside retrospective judgement.
Tell the causal story without pretending certainty.
Describe the foment, the proposition, the target interaction spaceInteraction space: Where strands meet and influence one another. It can extend beyond the landscape’s geographic boundary. and any changes from the approved plan.
Report intended and unintended responses, absence, dampening, rippleRipple: An effect that spreads from an initial disturbance but weakens unless something sustains it. In the Playbook, it may remain dependent on the intervention. and cascadeCascade: Change that becomes self-reinforcing: responses trigger further responses, so the intervention no longer supplies every push. It can spread harm as well as benefit. signals.
Explain what the response changed in the team’s maps, causal belief or understanding of headingHeading: The direction in which the landscape is currently moving, produced by many actors and their interactions..
State the next decision, its evidence and any required change control, budget or authorization.
Continue through connected concepts
Build the decision rights and structures through which learning changes action.
→State propositions clearly enough that response can teach you something.
→Maintain the living maps and attend to weak or absent signals.
→Connect proposition, response and revised causal understanding.
→Judge whether accumulated movement remains in the intended direction.
→Read the full Monitoring, learning and evaluation chapter.
The full reading provides the conceptual foundations, examples, sources and methodological detail behind this page.
Terms used on this page
- Heading
- The direction in which the landscape is currently moving, produced by many actors and their interactions.
- Alternative Heading
- A better direction an intervention seeks to support, revised as it learns. It is not a fixed blueprint for a final state.
- Regulation
- Any way actors shape what others can or cannot do, including rules, money, prices, custom and persuasion. It is broader than government regulation.
- Interaction space
- Where strands meet and influence one another. It can extend beyond the landscape’s geographic boundary.
- Foment
- A small, deliberate, time-bound intervention designed to test and influence how the system responds.
- Ripple
- An effect that spreads from an initial disturbance but weakens unless something sustains it. In the Playbook, it may remain dependent on the intervention.
- Cascade
- Change that becomes self-reinforcing: responses trigger further responses, so the intervention no longer supplies every push. It can spread harm as well as benefit.
