Te Rā Whakamana: The Experiment We’re Already Running

15/07/2025

Te Rā Whakamana is the space where we reflect on what it takes to deliver public outcomes, and not just announce them. Every Tuesday, we draw on empirical and published work to better understand the hard part of government work: the relational, adaptive, on-the-ground processes where systems either earn legitimacy or lose it altogether.

Our working hypothesis is that in Aotearoa, service delivery and implementation are especially complex because authority is not singular. It moves. It’s negotiated. It’s shared. That is why this series holds space for the practice of implementation as a living, learning process, where delivery is not the tail end of the policy cycle, but the place where the real work begins.

This week, we turn to some local academics who have been thinking and writing about implementation and learning for a decade or so. I’ve been sitting with one of their papers for the last month, especially this line from Eppel, Turner, and Wolf: “Policy actors too are taken to affect, but not be affected by change in public policy actors” (Eppel, Turner, & Wolf, 2011, p. 48). It’s a dense sentence, but that’s because it’s describing something dense. It’s calling attention to how we still pretend that policy delivery is separate from the people doing it: as if implementation happens to systems, not through them. As if the actors involved in delivery somehow stand outside the adaptive loops their work creates.

Elizabeth Eppel and the team aren’t just making a philosophical point. They are making a foundational point as to why delivery so often fails. We still build policy as if delivery is mechanical. For example, how institutions are designed is still called the machinery of government. We act like contexts are stable, not dynamic. We measure success as if outcomes are the product of fidelity to a plan, rather than the emergent result of people navigating complexity on the ground (Eppel et al., 2011). And when implementation doesn’t go to script, we often frame it as failure.

But here’s the truth, Eppel and her colleagues insist we confront: implementation is already an experiment. Always has been. The question is not whether we should run experiments; the question is whether we’ll admit we’re already running them, and whether we’re willing to learn from them.

This distinction matters because too often, governments pretend they’re in control of variables they can’t hold still. When a policy hits the ground, the environment shifts. Not because the policy is bad, but because reality is reactive. Implementation is not the final phase of the policy cycle: it’s the site where good intentions meet emergent reality, where feedback loops start kicking, and where learning either happens or it doesn’t. And when it doesn’t, the system ossifies. It can no longer see the signals it needs to adapt (Eppel et al., 2011).

Eppel, Turner, and Wolf are not just describing complexity for its own sake; they’re explaining how complex systems behave when we’re inside them. They’re pointing to the loops of interdependence that make prediction impossible and learning essential. I think they’re saying: you can’t stand outside the system and manage it like a machine. You have to engage it as a living, adaptive process. That means policies need to be treated as hypotheses. Delivery is not execution; it’s inquiry (Eppel et al., 2011).

That’s not a comfortable stance for public management systems built on command and control. Experimental thinking challenges government systems. It asks for institutional humility. It requires systems to admit they don’t have all the answers, and that some of what they try will fail. And in a political environment that punishes uncertainty, that can feel risky, even dangerous.

But the alternative is worse. Pretending you know more than you do leads to systems that are technically compliant but practically useless. We end up with policies that look clean in Cabinet papers but fail in the field. We end up treating adaptation as error, instead of as the system’s way of telling us something important.

If you want a concrete example of what experimental implementation looks like in practice, look at the Māori Communities COVID-19 Fund (MCCF). This wasn’t just a funding stream; it was an adaptive, on-the-ground experiment in delivery. It emerged from real system constraints: vaccination inequity, structural bias, and the collapse of the mainstream delivery model under pressure. It was designed and delivered at speed by actors inside the system who knew the plan would need to evolve the moment it hit the ground (DTK & Associates, 2023).

The MCCF didn’t succeed because it followed a pre-written script. It succeeded because it adjusted in real time. Regional Te Puni Kōkiri officials worked alongside Iwi and Māori Hauora providers to build new circuits of delivery, blending authorising environments with community realities. Decision rights moved closer to where the work was happening. Some investments were made in 48 hours because that’s what it took. Providers built services on the fly: vaccination events, mobile outreach, marae-based support systems, often using methods the mainstream system lacked the capacity, capability, or frankly, trust relationships to deliver.

MCCF wasn’t a perfect delivery. It was adaptive delivery. It was messy, relational, and fast-moving. But it closed vaccination gaps, built resilience, and supported whānau through some of the most challenging phases of the pandemic. That’s what learning in motion looks like.

And here’s the part the system still struggles to see: experiments like the MCCF are not self-managing. They don’t just unfold safely because we hope they will. People hold them together. In this case, the regional kaimahi of Te Puni Kōkiri acted as relational weavers, positioned at the interface of community need and Crown authorisation. They were not just fund administrators. They were the boundary spanners in the Crown and Māori relationship, working in the tradition of street-level bureaucracy (Lipsky, 1980), but also beyond it: ensuring the Crown’s rapid moves did not become reckless ones. They wove the threads between policy, context, and care. They protected whānau from the worst tendencies of the system: transactionalism, overreach, and neglect. They ensured the experiment did not harm.

The MCCF reminds us that complexity is not an excuse for inaction; it’s an invitation to rethink how we work. Lifting vaccination rates wasn’t just about supply, it was also about trust, proximity, and reducing administrative burden. It required new forms of boundary-spanning behaviour, where government officials stopped managing from a distance and started co-producing solutions alongside the communities most affected. And the learning happened laterally—not just up to ministers, but sideways across communities, providers, and officials figuring it out together (DTK & Associates, 2023).

That’s not a linear rollout. That’s a relational experiment. And it’s how change actually happens.

This has particular resonance in Aotearoa. We live in a system where authority is plural by design. Legitimacy is earned, not assumed. Solutions emerge from negotiation and whanaungatanga, not from top-down direction. The Crown can declare a framework, but it can’t declare implementation success. That has to be co-created on the ground, in relationship.

So the challenge is not to add “experimentation” as a new policy trend. It’s to recognise that we’re already in the experiment. Every policy implementation is a live inquiry into what works, what doesn’t, and why. The question is whether we’re designing for learning or just defending the plan.

Te Rā Whakamana is where this becomes real. It’s where policy leaves the spreadsheet and meets the ground. It’s where systems reveal their actual behaviour—not the version we imagined, but the version that exists in practice. That’s not failure. That’s feedback.

The work now is to listen.

References

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

Eppel, E., Turner, D., & Wolf, A. (2011). Complex policy implementation: The role of experimentation and learning. Policy Quarterly, 7(1), 45–54. https://doi.org/10.26686/pq.v7i1.4404

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