Why this matters
Impact investing has momentum. But more capital hasn’t meant more clarity about what’s actually changing.
Impact investing has crossed the $1.5 trillion threshold. This signals a growing consensus that financial capital can be mobilised to create positive social and environmental outcomes.
But here’s the paradox: Can we say with confidence that we’ve achieved $1.5 trillion worth of impact? Do we truly know what’s changed, for whom, and how? Despite 15+ years of field-building, infrastructure development, and sophisticated measurement systems, the field still struggles to answer these fundamental questions.
This is not just a technical problem. It is a strategic and legitimacy risk. More data has not translated into more clarity or more impact. If we continue to treat measurement as a compliance function — a search for increasingly precise, decontextualised metrics — we risk repeating the trajectory of ESG: more information, less insight, and mounting critique.
Impact measurement must evolve. Not just to become more rigorous or standardised, but to become more relevant, relational, and responsive to the world we are trying to shape.
What’s broken
Three tensions sit at the heart of how we currently measure — each one a barrier to seeing change as it actually happens.
Impact investors increasingly work at the intersection of complex, overlapping systems: health and climate, food and equity, finance and resilience. Yet our measurement systems remain rooted in assumptions of linear causality, isolated attribution, and short-term feedback loops.
Social and environmental outcomes are treated as distinct domains, even when they interact in every context — from rural adaptation to urban infrastructure. Our categories create boundaries where systems see none.
Despite advances in standards, indicators, and benchmarks, we lack meaningful tools to understand how systems shift over time — or how our capital contributes to those shifts. We have sophisticated instruments for measuring stocks of impact, but almost none for tracking the flow of change.
In reality, measurement is also relational, political, and ethical. It reflects who sets the terms, whose voices are included, and what gets counted as evidence. When these dynamics are unexamined, measurement can become extractive — especially for those most affected by the work but least involved in shaping how it is assessed.
These aren’t abstract concerns. They shape how strategies are designed, how decisions are made, and what kinds of change are even visible. If we keep optimising measurement for accountability to funders or regulators, we risk losing sight of our broader ambition: to create conditions for equitable, lasting, and systemic change.
What changes
Four shifts — from measurement as control to measurement as contribution. Each one moves away from a default logic that constrains how we think about impact.
From annual KPIs to intermediate patterns and milestones
Measurement today is dominated by short-term outputs and annual KPIs — the primary tools for assessing progress, driving reporting cycles, and shaping funding decisions. But this short-termism flattens nuance, obscures momentum, and can distort long-range strategy.
The opportunity is to introduce intermediate time horizons — typically 2 to 5 years — as the default orientation for assessing systems change. This is the difference between measuring the stock of impact (a snapshot) and the flow of change over time. Most meaningful progress in complex systems is not instantaneous or directly attributable. But it can be sensed, tracked, and interpreted — if we know where and how to look.
Are we measuring over the right time horizons — or are we locked into reporting cycles that don’t match how change actually unfolds?
From singular metrics to collective action signals
Most impact reporting isolates what an individual actor has done — at the level of an organisation, a fund, or a project. This emphasis on attribution overlooks a critical fact: systems-level outcomes are co-produced. Change happens when actors align, coordinate, or adapt in response to one another.
The opportunity is to develop collective action indicators — signals of shared contribution, alignment, and momentum. These signals don’t replace KPIs; they contextualise them. They tell us whether efforts are reinforcing each other, whether energy is diffusing or concentrating, and whether we are building toward durable systems shifts.
Are our current measurement tools suited to the kinds of systemic change we are trying to support — or are they designed for a simpler story?
From values-neutral to values-informed measurement
Many measurement systems position themselves as neutral and objective. But all measurement reflects values — whether visible or hidden. The choice of what to measure, how to measure it, and whose voices are included all reflect assumptions about what matters.
When values are implicit, they often default to investor preferences, technocratic feasibility, or reputational risk. This risks obscuring trade-offs, reinforcing blind spots, and weakening accountability to those most affected by the work.
The opportunity is to make values explicit, embedded, and measurable — not as lofty intentions, but as operational commitments. When values are surfaced, organizations can examine how well their strategies, structures, and indicators are aligned — and where meaningful reflection or course correction is needed. Values-informed measurement doesn’t ask for perfection. It asks for clarity, integrity, and coherence.
How are our organisation’s core values expressed in what we currently measure? Where might there be inconsistencies between what we say matters and what we actually track?
From technical data to relational understanding
Measurement is often treated as a technical task: data collection, indicator tracking, analysis. While these are essential, this framing obscures deeper questions: Who decides what counts? Who is measured — and how? Who gets to interpret and act on results?
In practice, measurement is relational. It is shaped by power, trust, access, and incentives. When these dynamics are unexamined, measurement becomes extractive — especially for communities and contexts most affected by decisions but least involved in shaping them.
The opportunity is to embrace a relational lens. This includes designing participatory and collaborative approaches to data collection, acknowledging the expertise of those closest to the issues, tracking the quality of relationships and networks — not just transactions — and using data as a tool for dialogue, not just compliance. Relational measurement reinforces the idea that impact is not something done to people — it is something shaped by and with them.
What important perspectives might we be missing — and how could we create space to include a broader range of voices in interpreting results?
What’s next
Evolving how we measure won’t resolve impact investing’s fundamental tensions. But it might offer better responses than the defaults we’ve come to accept.
It might allow us to see beyond performance snapshots to track signals of momentum, resilience, and behaviour change. To uncover early indicators of contribution, rather than waiting for outcomes that are neither attributable nor generalisable. To strengthen shared insight, not just shared language — building the connective tissue between funders, managers, practitioners, and communities. And to support adaptive decision-making, rather than anchoring legitimacy to the wrong metrics.
This is not a detour from the dominant trajectory of impact investing — with its regulation, reporting cycles, and standard-setting. It is a necessary extension, a complementary agenda that asks: What do we do next, once the infrastructure is built? What’s the agenda for the next 10–15 years?
Across the field, organizations are already experimenting with approaches that reflect these principles — testing new forms of learning, co-creating indicators, investing in shared infrastructure. But these efforts remain largely fragmented and under-connected. The opportunity is not another centralised framework. It is greater coherence, visibility, and mutual learning.
Start with what we have
Prototypes and promising models already exist — from impact collaboratives piloting shared data platforms, to community-based organizations with context-specific indicators, to catalytic funders resourcing multi-year adaptive learning agendas. Rather than design entirely new systems, we can begin by mapping and synthesising what has already been tested.
Bridge across fields and functions
Place-based funders, climate-aligned investors, and systems-oriented philanthropies often work on similar challenges from different vantage points, with limited alignment on language, data practices, or learning mechanisms. Bridging requires mutual visibility, language that supports translation, and space for shared inquiry.
Make this work easier to engage and act upon
For measurement to evolve in practice, it must become more accessible — particularly for actors navigating time, capacity, and legitimacy constraints. This means entry-level tools, scalable support models, and clearer funding strategies for collaborative approaches. Not uniform adoption, but measurement pluralism.
Over the next decade, the legitimacy of impact investing will depend not just on capital deployed, but on how seriously the field attends to outcomes, context, and complexity. The challenge is no longer to make metrics more sophisticated, but to ensure that what we measure is commensurate with how change actually happens: relationally, incrementally, across systems, and over time.
Measurement has always reflected more than numbers — it surfaces what we value, what we prioritise, and what we are prepared to act on. If we are serious about enabling more impact — not merely reporting on it — we must work towards systems that help us see what is emerging, not only what was planned.