Indicators are often treated as neutral measures of progress. In practice, they only make sense through judgement, conversation, and institutional context. Drawing on place-based environmental programmes, this post reflects on why indicators need to be revisited, interpreted, and sometimes reworked if they are to support adaptation rather than constrain it.
Indicators are now a routine feature of work in complex settings. They appear in climate adaptation strategies, biodiversity programmes, land-use planning, infrastructure investment, and public policy. They promise clarity in situations marked by uncertainty, competing values, and long timeframes. Used well, they can help people notice change, focus attention, and support shared conversations about direction.
Working across long-running environmental and place-based programmes, however, I’ve seen that indicators rarely do this work on their own. In practice, they are interpreted, prioritised, and acted on by people and institutions operating under pressure, with limited time and imperfect information. Monitoring and evaluation frameworks remind us that indicators only become useful when they are embedded in wider cycles of interpretation, decision, and adjustment, as part of the management and decision-making system, where choices are actually made and revisited. This post reflects on how indicators actually function in real-world settings, and why judgement and adaptation, rather than measurement alone, remain central to making sense of change over time.
Adaptation initiatives are increasingly framed as projects, strategies, or plans designed to respond to future risk. While these efforts play an important role, they often struggle to support learning and adjustment once implementation begins. Here, adaptation is treated not as a one-off intervention, but as an ongoing process of adjustment, learning, and decision-making over time, aligned with principles of adaptive management.
These reflections draw on experience from environmental programmes, including freshwater and catchment management, but the patterns will be familiar across many policy and practice contexts where decisions must be revisited as conditions shift. They sit alongside earlier work on effective indicators for freshwater management, which emphasised both the technical qualities of good indicators and the social learning processes through which they are developed and used. While those examples are sector-specific, the underlying dynamics travel well.
Indicators as aids to judgement
Indicators are often presented as objective signals. Yet their influence lies less in the numbers themselves than in how those numbers are read and used. Deciding whether a trend is concerning, acceptable, or encouraging is always a judgement call, shaped by context, expectations, and values. Even apparently simple questions such as “Are we on track?” depend on prior choices about what to track, how to aggregate, and which outcomes are being privileged.
In complex settings, indicators rarely align neatly. One indicator may suggest improvement while another points in the opposite direction. Thresholds are often contested, and responses are rarely obvious. At that point, the work moves beyond technical measurement into deliberation. People weigh trade-offs, consider implications across different orders of outcome, and decide what matters most in the moment. In practice, this tends to happen implicitly rather than as a clearly articulated or supported activity, particularly in programmes spanning environmental, social, and institutional domains.
Seen this way, indicators support judgement rather than replace it. They provide prompts for discussion, not answers. Treating them as definitive can narrow the space for reflection, while recognising their provisional nature keeps attention on the decisions they are meant to inform. In earlier freshwater work, for example, indicators were explicitly framed as building blocks in a performance story, to be interpreted alongside conceptual models, local knowledge, and evidence about cause–effect relationships, rather than as free-standing verdicts on success or failure.
For readers wanting a short overview of indicator design and use, I’ve pulled together a set of resources and examples on the Learning for Sustainability page on developing indicators and metrics.
Revisiting indicators over time
This pattern of indicators becoming fixed reference points is not confined to freshwater work. In many sustainability and public-sector programmes, indicators play a central role in how progress is described and decisions are justified. Considerable effort goes into selecting them, agreeing definitions, and aligning them with reporting requirements. Far less attention is paid to how they are revisited as circumstances change. In many systems, indicators become fixed reference points, tied to reporting cycles and accountability frameworks that reward consistency over responsiveness. Lists harden, even as the issues they are meant to illuminate continue to evolve.
This pattern has been noted in recent work on climate adaptation metrics and public-sector performance. In these settings, established indicator regimes tend to stabilise what is monitored and rewarded, often at the expense of learning and responsiveness. I explore these patterns, and some practical ways of keeping indicator sets under review, on an accompanying Learning for Sustainability indicators and metrics resource page.
Adaptive practice requires a different stance. Conditions change, sometimes slowly, sometimes abruptly. New information emerges, priorities shift, and assumptions that once seemed reasonable lose their footing. In these situations, the most important question is not whether indicators are being met, but whether they are still helping people notice what matters. This aligns with adaptive management, which treats monitoring as part of a continuous cycle of planning, acting, checking, and adjusting, rather than as the final step.
Programmes that genuinely support adaptation tend to build in moments to reflect on indicators themselves. Questions such as the following become routine parts of practice:
- Are these indicators still relevant to our current objectives and risks?
- What are they no longer capturing, given what we now know?
- Where are people seeing patterns on the ground that sit outside the formal measures?
These conversations are often as valuable as the data they draw on, because they keep indicators connected to lived experience rather than locked into templates. In freshwater work, for example, I have seen interim indicators of behavioural or institutional change introduced, or recommended, to sit alongside longer-term environmental measures, recognising time lags and attribution challenges. In each case, those additions only emerged because teams periodically revisited what they were tracking and why.
Whose knowledge shapes indicators
Indicators are never neutral. They reflect particular ways of knowing and valuing the world. Decisions about what is measured, how it is measured, and what counts as credible evidence shape whose perspectives are visible and whose are marginalised. Indicator sets built solely from technical or biophysical measures risk overlooking social, cultural, and institutional conditions that are critical for adaptation.
When indicators privilege a narrow set of technical measures, they can crowd out experiential, local, or Indigenous knowledge that is essential for understanding what is changing and what responses are feasible. This does not mean all forms of knowledge need to be treated as equivalent in every decision, but it does mean being explicit about what different forms contribute and how they are brought into conversation. In freshwater programmes, for instance, efforts to combine scientific monitoring with Indigenous knowledge and land users’ practical experience produced richer conceptual models and more grounded indicator choices.
Where indicators are co-produced, or at least openly negotiated, they are more likely to support adaptation. They become shared reference points rather than external impositions. People are better able to see themselves in the measures and to trust the conversations that follow from them. Work on collaborative catchment management has shown that involving iwi, landholders, agencies, and scientists in conceptual modelling and indicator selection not only improves technical fit, but also strengthens relationships and willingness to act on what indicators reveal.
Institutional settings matter
Even well-designed indicators can undermine adaptation if they sit within institutional settings that discourage learning. Short funding cycles, rigid performance regimes, and compliance-oriented reporting can turn indicators into blunt instruments. Attention shifts from sense-making to justification, from reflection to defence. In such environments, the safest use of indicators is often to minimise surprises rather than surface emerging risks or uncomfortable trade-offs.
By contrast, where institutions make room for dialogue, iteration, and adjustment, the same indicators can support adaptive practice. Regular review points, space for narrative alongside metrics, and governance arrangements that value learning all influence how indicators are used. Earlier work on freshwater indicators suggested that frameworks such as the policy cycle and the orders of outcomes model can help here, by explicitly recognising that policy and practice evolve through successive cycles, and that institutional and behavioural changes often precede shifts in environmental condition.
This suggests that debates about indicators cannot be separated from questions of governance and accountability. The challenge is not simply technical. It is about designing institutional arrangements that allow indicators to inform judgement rather than constrain it. In complex adaptive systems, this often means accepting some uncertainty and variability in reported results, in exchange for more honest feedback and more timely course corrections.
Indicators in adaptive practice
A useful shift is to move away from asking whether indicators are being met, and toward asking what they are helping people notice and do next. This reframes indicators as part of an ongoing adaptive practice, grounded in principles of adaptive management, rather than as a scorecard. It also aligns with performance story approaches that focus on plausible contribution and learning, rather than definitive proof of impact.
In this framing, indicators support:
- shared attention to emerging patterns and trends across biophysical, social, cultural, and institutional domains
- conversations about trade-offs, priorities, and acceptable risk, grounded in explicit theories of change
- timely adjustment in response to new information, including shifts in strategy, practice, or partnership arrangements over time
- reflection on whether current approaches remain fit for purpose, and whether underlying assumptions still hold.
They do not eliminate uncertainty, but they can help people work with it more deliberately. In freshwater management, for example, using linked sets of indicators across driving forces, pressures, states, impacts, and responses made it easier to see where to intervene, and to recognise when progress in one part of the system was being offset by new pressures elsewhere.
Closing reflection
Indicators remain an important part of working in complex settings. The challenge, in my experience, is not to abandon them, but to hold them lightly enough that judgement and adaptation can still do their work. When indicators are treated as supports for learning within wider decision-making systems rather than as ends in themselves, they are more likely to contribute to meaningful change over time.
Many of these reflections are explored in more detail in earlier work on indicators and learning in environmental programmes, including guidance on selection criteria, conceptual frameworks, and collaborative processes for indicator development. While those examples are grounded in freshwater management, the patterns they reveal are recognisable wherever people are trying to make sense of change, act under uncertainty, and adapt together over time.
That, ultimately, is where indicators earn their keep, not as definitive measures of success, but as companions to judgement in ongoing practice.
This reflection connects with earlier work on effective indicators for freshwater management, which explores indicator design, conceptual frameworks, and the role of judgement in more detail. It also sits alongside the Learning for Sustainability pages on developing indicators and metrics, and on monitoring, evaluation, and learning (MEL) which bring together tools and reflections for using indicators as part of an ongoing learning cycle rather than a fixed reporting requirement. For readers working in climate adaptation, these themes are taken further in the climate adaptation hub, where indicators, feedback, and collective sense-making are treated as core infrastructure for adapting over time.
[* Image: FS-Stock via Adobe Stock]
