Te Rā Whakamana: The Experiment We’re Already Running

14/07/2026

I take Eppel, Turner and Wolf’s argument that implementation is always an experiment, and use the Māori Communities COVID-19 Fund to show what learning in motion looks like.

Te Rā Whakamana is where we reflect on what it takes to deliver public outcomes, as opposed to announcing them. Each Tuesday we draw on empirical and published work to understand the hard part of government work, the relational, adaptive, on-the-ground processes through which systems earn legitimacy or lose it altogether.

Our working hypothesis is that service delivery and implementation in Aotearoa are especially complex because authority is not singular; it moves, and it is negotiated and shared. For that reason this series treats implementation as a living, learning process, in which delivery is the place where the real work begins rather than the tail end of the policy cycle.

This week I turn to local academics who have been thinking and writing about implementation and learning for a decade or so. I have been sitting with one of their papers for the last month, and especially with this line from Eppel, Turner, and Wolf: “Public policy actors, too, are taken to affect, but be unaffected by, the policy process” (Eppel et al., 2011, p. 186). The sentence is dense because it describes something dense. It draws attention to how we still pretend that policy delivery is separate from the people doing it, as if implementation happens to systems rather than through them, and as if the actors involved in delivery stand somehow outside the adaptive loops their work creates.

Elizabeth Eppel and her co-authors are making a basic argument about why delivery so often fails, and it goes beyond philosophy. We still build policy as if delivery were mechanical, to the point that the design of institutions is still called the machinery of government. We act as if contexts are stable rather than dynamic, and we measure success as if outcomes were the product of fidelity to a plan, when they are more often the emergent result of people working through complexity on the ground (Eppel et al., 2011). When implementation does not go to script, we tend to frame it as failure.

The truth Eppel and her colleagues ask us to confront is that implementation has always been an experiment. The question is therefore whether we will admit that we are already running experiments, and whether we are willing to learn from them, rather than whether we should run them at all.

The distinction matters because governments too often pretend to control variables they cannot hold still. When a policy reaches the ground, the environment shifts because reality reacts, and the policy need not be a bad one for that to happen. Implementation is the site where good intentions meet emergent reality, where feedback loops start to operate, and where learning either happens or does not. Where it does not, the system ossifies and can no longer see the signals it needs in order to adapt (Eppel et al., 2011).

Eppel, Turner, and Wolf are explaining how complex systems behave when we are inside them, rather than describing complexity for its own sake. They point to loops of interdependence that make prediction impossible and learning essential. As I read them, they are saying that we cannot stand outside the system and manage it like a machine, and must instead engage with it as a living, adaptive process, which means treating policies as hypotheses and delivery as a form of inquiry (Eppel et al., 2011).

That is an uncomfortable stance for public management systems built on command and control. Experimental thinking asks for institutional humility; it requires systems to admit that they do not have all the answers and that some of what they try will fail, which in a political environment that punishes uncertainty can feel risky, even dangerous.

The alternative is worse. Pretending to know more than we do leads to systems that are technically compliant but practically useless, to policies that look clean in Cabinet papers and fail in the field, and to a habit of treating adaptation as error when it is the system’s way of telling us something.

The Māori Communities COVID-19 Fund (MCCF) is a concrete example of experimental implementation. It was an adaptive, on-the-ground experiment in delivery as much as a funding stream, and it emerged from real system constraints: vaccination inequity, structural bias, and the collapse of the mainstream delivery model under pressure. People inside the system designed and delivered it at speed, knowing that the plan would need to change as soon as it reached the ground (DTK and Associates, 2023).

The MCCF succeeded because it adjusted in real time, not because it followed a pre-written script. Regional Te Puni Kōkiri officials worked with Iwi and Māori hauora providers to build new circuits of delivery that brought authorising environments and community realities together, and decision rights moved closer to where the work was happening. Some investments were made within 48 hours because that was what the situation required. Providers built services on the fly, including vaccination events, mobile outreach, and marae-based support, often using methods that the mainstream system lacked the capacity, the capability, or frankly the trust relationships to deliver.

Delivery under the MCCF was adaptive rather than perfect: messy, relational, and fast-moving. It closed vaccination gaps, built resilience, and supported whānau through some of the hardest phases of the pandemic, and I think it shows what learning in motion looks like.

What the system still struggles to see is that experiments like the MCCF do not manage themselves or unfold safely simply because we hope they will; people hold them together. In this case the regional kaimahi of Te Puni Kōkiri acted as relational weavers at the interface between community need and Crown authorisation. They were boundary spanners in the Crown–Māori relationship as well as fund administrators, working in the tradition of street-level bureaucracy (Lipsky, 1980) and beyond it, and making sure that the Crown’s rapid moves did not become reckless ones. They connected policy, context, and care, protected whānau from the worst tendencies of the system (transactionalism, overreach, and neglect), and made sure the experiment did no harm.

The MCCF reminds us that complexity is an invitation to rethink how we work rather than an excuse for inaction. Lifting vaccination rates depended on trust, proximity, and reduced administrative burden as well as on supply. It required new forms of boundary-spanning, in which officials stopped managing from a distance and began co-producing solutions with the communities most affected, and the learning travelled sideways across communities, providers, and officials working it out together, as well as upwards to ministers (DTK and Associates, 2023).

I would describe this as a relational experiment rather than a linear rollout, and in my experience it is how change tends to happen.

This matters particularly in Aotearoa, where authority is plural by design and legitimacy has to be earned rather than assumed. Solutions emerge from negotiation and whanaungatanga more than from top-down direction, and while the Crown can declare a framework, it cannot declare implementation a success; that has to be co-created on the ground, in relationship.

The challenge, then, is to recognise that we are already in the experiment, instead of adding “experimentation” as a new policy trend. Every implementation is a live inquiry into what works, what does not, and why, and the real question is whether we are designing for learning or simply defending the plan.

Te Rā Whakamana is the point at which policy leaves the spreadsheet and meets the ground, and at which systems reveal how they actually behave in practice as opposed to how we imagined they would. I read that gap as feedback rather than failure, and the work now is to listen to it.

References

DTK and Associates. (2023). Independent evaluation of the Māori Communities COVID-19 Fund for Te Puni Kōkiri. DTK and Associates.

Eppel, E., Turner, D., & Wolf, A. (2011). Complex policy implementation: The role of experimentation and learning. In B. Ryan & D. Gill (Eds.), Future state: Directions for public management in New Zealand (pp. 182–212). Victoria University Press.

Lipsky, M. (1980). Street-level bureaucracy: Dilemmas of the individual in public services. Russell Sage Foundation.