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Measuring Systemic Change: A Practical Step-by-Step Process

There's no shortage of frameworks for thinking about systemic change. What's often missing is a clear process for actually measuring it. This page introduces a practical, step-by-step approach.

Systemic change has become a common goal in fields from international development to philanthropy to public health. Programmes aim for it, funders ask for evidence of it, and evaluators are expected to assess it. But measurement of systemic change is often inconsistent, unclear, or simply absent.

Part of the problem is conceptual: people mean different things by "systemic change." But even when there's agreement on what it means, there's often no clear process for how to go about measuring it. Frameworks abound, but practical methodology is thin.

This page sets out a six-step process for measuring systemic change. It's designed to be practical. Implementers and evaluators can actually use it while still being rigorous enough to produce credible evidence.

Why measuring systemic change is hard

Several things make systemic change difficult to measure:

• Systems are complex. They involve many actors, relationships, and feedback loops. Change in one part affects other parts in ways that are hard to predict or trace.
• Change happens at multiple levels. Individual actors change their behaviour; those changes aggregate into patterns; the overall system performs differently. Which level do you measure?
• Timescales are long. Systemic change often takes years to unfold. By the time it's visible, the programme that contributed to it may have ended.
• Attribution is difficult. Many factors influence how systems change. Isolating the contribution of a specific intervention is rarely straightforward.
• Definitions vary. Without a shared understanding of what "systemic change" means, it's hard to agree on what counts as evidence of it.

These are real challenges. But they don't make measurement impossible. They just mean you need a clear process that addresses them explicitly.

Two things you need to measure

A useful distinction is between system snapshots and system dynamics.

System snapshots: what exists and how well it's performing

A snapshot captures the state of the system at a point in time. It answers questions like:

• What actors are involved in this system?
• What actions are they taking?
• How well is the system performing in terms of outputs, quality, reach, efficiency?
• What's the composition of the system: how many actors, what types, what scale?

Snapshots are fundamentally descriptive. They tell you what the system looks like and how it's performing, but not why.

Take multiple snapshots over time, and you can see whether and how the system has changed. Composition may have shifted. Performance may have improved (or declined). New actors may have entered, or existing actors may be doing things differently.

System dynamics: why the system has changed

Knowing that the system has changed isn't enough. For strategy and evaluation purposes, you usually need to understand why it changed:

• What behaviour changes have occurred? Who is doing what differently?
• What drove those behaviour changes? What enabled or motivated them?
• How sustainable are the changes? Will they persist without continued intervention?
• What was the contribution of your programme versus other factors?

This is where evaluation gets harder, but also where it becomes most valuable. Understanding dynamics helps you learn what works, adapt your strategy, and make credible claims about contribution.

The six steps

The process has six steps, organised into two groups:

The first three steps can be repeated at different points in time to create comparable snapshots. The second three steps analyse what happened between snapshots and why.

Steps 1–3: System Snapshot

The snapshot steps establish what you're measuring and create a baseline (or ongoing assessment) of system composition and performance.

Step 1: Define the system. This means identifying the actors involved, the actions they take, and the boundaries of what you're including. A useful approach is Actions & Actors mapping, which defines systems in terms of concrete, observable elements rather than abstract variables.

Step 2: Describe the system. With the system defined, you can describe its current composition: how many actors of each type, what actions they're taking, what resources are flowing between them. This is largely descriptive work: documenting what exists.

Step 3: Assess performance. Beyond composition, you want to know how well the system is performing. This might include measures of output, quality, reach, efficiency, or other relevant dimensions. The right measures depend on what the system is supposed to do and what "good performance" means in context.

Repeat these steps later, and you have a second snapshot. Compare them, and you can see what's changed.

Steps 4–6: System Dynamics

The dynamics steps analyse why the system has changed and what it means for sustainability and attribution.

Step 4: Identify behaviour changes. Changes in system composition and performance ultimately come from changes in what actors do. This step identifies the specific behaviour changes that have occurred: who is doing what differently? This includes both the actors you worked with directly and others who may have changed independently or in response.

Step 5: Analyse drivers. Why did those behaviour changes happen? What enabled them, motivated them, or removed barriers to them? This is where you trace causal pathways, understanding the mechanisms through which change occurred.

Step 6: Assess sustainability and contribution. Finally, you need to assess whether the changes are likely to persist (sustainability) and what role your intervention played versus other factors (contribution). This is often the hardest part, but it's essential for learning and accountability.

What this process does and doesn't do

This process provides a structured way to approach systemic change measurement. It helps ensure you're asking the right questions in a logical sequence and gathering evidence at both the snapshot and dynamics level.

What it doesn't do is prescribe specific methods or tools. Different contexts will require different data collection approaches: quantitative surveys, qualitative interviews, secondary data analysis, participatory methods, and so on. The six steps are a framework for organising your measurement effort, not a replacement for methodological choices.

The process also doesn't resolve the fundamental challenges of measuring complex change. Attribution will still be difficult. Timescales will still be long. But having a clear process makes it possible to be systematic and transparent about how you're approaching these challenges.

Connecting strategy and evaluation

One advantage of this process is that it connects directly to strategy design. If your strategy is built around changing specific behaviours by specific actors (as it should be), then the same framework tells you what to measure.

The system definition (Step 1) should align with your theory of change. The behaviour changes you're trying to achieve (Step 4) should be the same ones your strategy is designed to produce. This creates coherence between what you're doing and how you're assessing whether it's working.

It also means that measurement isn't an afterthought. If you can't specify what behaviour changes you're trying to achieve and how you'd know if they happened, that's a sign your strategy needs more work.

Getting started

The full methodology is set out in the paper Six Steps to Assess Systemic Change (and Improve Your Strategy). It includes more detail on each step, guidance on practical application, and discussion of how the process connects to strategy development.

The paper also draws on several related frameworks:

• Actions & Actors System Mapping: for defining and describing systems (Steps 1–2)
• Mechanisms of Social Change (MOSC): the conceptual foundation for understanding how systems change
• What is Systemic Change?: a framework for defining what counts as systemic change