This opinion piece was written by Verena Kontschieder, Federico Vaz & Neeraj Sonalkar. For more like this, see our government innovation newsfeed.
Today, we witness explicit calls to make public policy more “agile”, voiced by disappointed voters and decision makers in technology businesses, think tanks and international organisations alike.
These stakeholders tend to use novel instruments or establish innovation spaces in policy, like design thinking or policy labs. But systematic attempts to integrate such siloed initiatives into an end-to-end policymaking and policy experiencing framework seem absent.
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How should human experience-led design activities find their space in policy? We take inspiration from the product development cycle and its evolution to investigate how today’s sequential policymaking cycle approach — first proposed roughly 60 years ago — would need to be remodelled.
Comparing product development and policymaking cycles
Looking into recognised models of policy development from the 1970s to 2017, we learned that they all followed one basic logic that has remained unchanged over time: policymaking starts by identifying a public problem, followed by the formulation of policy options, decision-making on those options, implementation of the selected option and, finally, evaluation.
Product development, on the other hand, starts with the problem definition phase, proceeds with a conceptual design phase in which ideas are generated and options formulated, followed by a systems-level design phase that junctures into a detailed design phase where the idea is developed, tested and refined, and subsequently implemented or commercialised.
One of the major differences between policy and product cycles is that, in product design, testing and refinement have obtained an explicit focus. Mainstream policymaking models, by contrast, jump directly into implementation, with no explicit referral to testing or iterating. Policy formulation and implementation stages remain clearly separated from each other.
Equally remarkable is the differentiation between systems-level and detail design in the product design cycle: an explicit separator that specifies the need to think, from the outset, not just in abstract terms but also about the concrete actionable artefacts that embody them.
If policies are the set of rules and regulations that hold the idea or vision of the society we (or those in position to take such decisions) would like to live in, what is the detail design stage that makes the vision actionable?
Although public policy can also be constituted by inaction, in most cases, a policy is embodied by a service or program which enables (or restricts) end users in some way.
When we see policy as a regulatory framework detached from its implementation, we are working on the realm of imagination; a shared understanding that the proposed view of society is somehow better than it currently is.
In product development, imagination and creativity are valid sources for innovation. However, the testing of these shared views — mainly by means of prototyping — is crucial before deploying an innovation. Similarly, testing policy-based services in a detailed design stage would provide an essential step toward a more flexible and experimental policymaking.
Yet another crucial divergence of the two cycles lies with the evaluation stage. Even though it appears in both cycles, in the policy models it occurs entirely post-implementation.
Product development proposes test-based iterations
Product development proposes test-based iterations of probing bits and pieces to learn from as implementation is happening. This could serve both at the early policy formulation or problem identification stage, to refine the problem focus and to inform the set-up of the policy framework.
Concurrency as core
The stages in the policy cycle can also be split into its two “main” phases: “policymaking” and “policy implementation”. This distinction is similar to the “planning” and “engineering stages” of product development. However, a critical question is who is deciding in the two stages and how are they working together?
Today, in product development, the recommended approach is to have disciplinary mixed teams responsible for the entire product development, both planning and implementation. And best practice in product design is now to enable concurrency of planning and engineering phases.
In the 60s and 70s, however, such cross-functional team approaches were essentially absent. Instead, product development was of the compartmentalised, “over-the-wall” type: planning teams conceptualised the product, and this was passed onto design teams responsible for execution or implementation.
Likewise, a key critique of the current use of design for policy is that design is only used in the policy implementation stage, with designers tasked with operationalising predetermined solutions.
While the power of design to reframe a problem before delving into it has been acknowledged in general, in the policy realm, design is always presented with a defined problem for which a pre-conceived solution tends to be at hand, thus restricting its full potential, not to mention the outcome’s innovativeness.
Moving away from such “over the wall” approaches could end up being a key component in the evolution of policymaking
Moving away from such “over the wall” approaches could end up being a key component in the evolution of policymaking, as much as it was in product engineering.
A policy comes into being when the interaction with the user begins
Designing a regulatory framework holds different challenges than the ones in product and service design. Still, even if the outcome that is optimised for will necessarily differ for policy and product (or service) development, we argue there are lessons to be learned from the respective process, as we see policymaking as a design science.
Applied design science proposes a wider shift in perspective towards very poignant issues. For instance, the “Designing out Crime” Research Centre at the University of Technology, Sydney, recognised that addressing alcohol-fuelled violence through ever-tightening regulations and increased police presence stigmatised those involved as criminals rather than young people seeking a good time.
Adopting the latter over the former view paved the way for providing the proper supporting infrastructure like benches to rest, night buses, toilets, charging stations, etc., creating an experience focused on the policy problem.
Public institutions will require significant reformulation to encompass such change
Today’s policymaking worlds are characterised by a hitherto unknown need for speed, enormous potential for collateral damage, increasing complexities driven heavily by new technologies and consequences thereof, as well as voiced constituent and voter skepticism.
Focusing on what is meaningful to those affected by the policy could have significant implications in terms of the resulting user experience.
Of course, public institutions will require significant reformulation to encompass such changes. Establishing dedicated design departments in policymaking institutions could foster a more user-centred, collaborative way from the outset, via a gamut of stakeholders simultaneously and concurrently being part of the policy development process, realising a more end-to-end policy experiencing — rather than just policymaking — model.
A future model
We argue for a policymaking model based on a design science approach, in which the stages configure an optimised process focused on the human experience of the policy outcome. Such process would require the restructuring of well-established policy formulation practices.
This claim does not aim to depoliticise the policymaking process; on the contrary, it is based on the idea that, as a process, it can be restructured in a more socially accommodating manner, to achieve better, more human-centred (and thus highly socio-political) outcomes.
This would break with the rationale of policy models merely depicting reality, and rather propose a way of doing, by drawing upon decades of iterations in product development modelling. — Verena Kontschieder, Federico Vaz & Neeraj Sonalkar
(Picture credit: Unsplash)