When it comes to understanding whether your work is making a difference, the way you evaluate matters as much as what you do. Evaluation isn’t just a reporting requirement; it’s a way of learning, about what works, for whom, in what contexts, and why.
But with so many approaches to choose from, how do you know which one best fits your project?
In this article, we explore three popular and powerful methodologies: Most Significant Change, Realist Evaluation, and Outcome Mapping. Unpacking what each does best, and how to decide which approach suits your needs.
1. Most Significant Change (MSC)
Most Significant Change is a qualitative, participatory approach to evaluation. Instead of starting with fixed indicators, MSC asks the people involved in a project, participants, staff, or partners, to share stories of change that they consider most significant. These stories are then collectively reviewed and discussed to identify what kinds of change are most valued and why.
Best for:
Projects where change is complex, unexpected, or hard to measure with numbers.
Programmes focusing on personal, social or behavioural change. For example, community empowerment, inclusion, or wellbeing.
Organisations that want to learn collaboratively and build reflection into their practice.
Strengths:
Captures rich, real-world experiences.
Builds ownership and shared understanding among participants.
Highlights unexpected or unintended outcomes.
Limitations:
Less suited to proving attribution or quantifying impact.
Requires time and facilitation to ensure stories are gathered and analysed systematically.
Use MSC when you want to understand change from the ground up, through the voices of those experiencing it.
2. Realist Evaluation
Realist Evaluation is a theory-driven methodology based on the principle that “context matters.” It asks not just whether a programme works, but what works, for whom, in what circumstances, and why. Realist evaluators develop and test CMO configurations, the relationships between Context, Mechanism, and Outcome, to explain how interventions produce change.
Best for:
Complex programmes with multiple stakeholders and settings.
Policy or systems-level interventions.
Projects that aim to replicate or scale an initiative and need to understand its underlying mechanisms.
Strengths:
Explains how and why outcomes occur.
Helps adapt programmes to new contexts.
Integrates qualitative and quantitative data.
Limitations:
Requires skilled facilitation and analytical rigour.
Can be time-consuming to design and interpret.
Use Realist Evaluation when you want to understand mechanisms of change and generate transferable learning that informs future design or policy.
3. Outcome Mapping (OM)
Outcome Mapping focuses on behavioural change in the people, organisations, or systems your initiative interacts with, known as boundary partners. Rather than measuring ultimate impacts, OM tracks shifts in actions, relationships, and practices that show progress towards long-term goals. It recognises that complex change is collaborative and non-linear.
Best for:
Development or partnership programmes working through networks or systems.
Interventions aiming to influence others’ behaviour rather than directly control outcomes.
Teams that want an ongoing learning and adaptation process, not a one-off evaluation.
Strengths:
Emphasises contribution over attribution.
Encourages continuous reflection and learning.
Makes intangible progress visible.
Limitations:
Doesn’t easily provide “hard evidence” for funders seeking quantifiable results.
Needs consistent documentation over time to be effective.
Use Outcome Mapping when you want to track behavioural and relational change and strengthen collaboration within complex systems.
Choosing Between Them
Selecting an evaluation methodology isn’t about right or wrong, it’s about fit. The right approach depends on what you most need to learn, who you’re learning with, and how you’ll use that insight.
If your goal is to understand how and why your programme works, to unpack the mechanisms that lead to change, then Realist Evaluation is your ally. It helps you look beneath the surface, exploring what works, for whom, in what circumstances, and why.
If you want to hear the human stories behind the change, and uncover outcomes that might never have been predicted, Most Significant Change offers a way in. It invites participants to share their lived experiences and helps teams make sense of what truly matters.
If your project is about shifting relationships, habits or collaboration over time, Outcome Mapping is a strong fit. It helps you trace how people’s actions evolve, how partnerships grow, and how influence spreads, recognising that real change is often relational rather than linear.
Of course, few real-world programmes fit neatly into one box. Often, the most powerful evaluations blend elements of each. You might use Realist principles to frame your inquiry and explain the mechanisms of change, Outcome Mapping to track behavioural shifts as they unfold, and Most Significant Change to capture the personal narratives that bring those findings to life.
Ultimately, the best approach is the one that helps you learn what matters most, and use that learning to do even more good.
In Summary
Evaluation is more than a box-ticking exercise. It’s an act of reflection and sense-making that allows you to see the story behind the data.
Most Significant Change reveals the human impact.
Realist Evaluation explains what drives it.
Outcome Mapping helps you sustain and adapt it.
Together, they remind us that change is complex, relational, and deeply human – and that understanding it well is the first step to doing good, better.
