A framework for navigating uncertainty in public policy design
People are rarely as predictable as we'd like to believe. Yet, policymaking—a forum directly concerned with people and their behaviour—demands that civil servants and ministers accurately predict, design, and deliver policy interventions up-front. It's a doctrine reinforced by guesswork, relying on simplified cost-benefit analysis models that fail to capture even the simplest of real-world dynamics, increasing the risk of expensive failures, and harming those most in need.
Part of my role as a service designer at HMRC's Policy Lab is being exposed to some of the earliest decisions in policymaking. Our team collaborates with policy, technology, and cost experts across HMRC to better understand how new policy ideas "impact" both citizens and the organisation itself. We bring a user-centred design perspective to the table, leveraging user research, systems thinking, and strategic design tools to embed public value in decisions that typically favour cost-benefit analyses—to shape effective and feasible policies.
In a government department like HMRC, though, where impact is traditionally inseparable from cost, it can be difficult. While cost-benefit analyses provide a quantitative method that enables policy teams to give ministers clear, concise options and recommendations in line with the UK government's guide to policy appraisal—the 'Green Book'—qualitative tools and frameworks that look to understand real-world dynamics are often overlooked or under-considered.
This brings me to the framework that I've been developing through my work impacting policy at HMRC and studying at UCL's Institute for Innovation and Public Purpose. It's an alternative approach to policy appraisal that looks to leverage analytical rigour while dealing with diversity and uncertainty to help policy teams break down, navigate, and evaluate policy decisions.
The structure, inspired by Simon Sharpe's work on risk-opportunity analysis, follows three main decisions: (1) Whether to act?; (2) How much effort?; and (3) Where to direct the effort? Each decision frames a method or perspective that looks to better understand the contextual layers of a policy, create an appropriate way to evaluate it, and understand the relationships a change may reinforce or balance.
Ultimately, this is not a "how to" guide—it's an invitation for policy teams to think more broadly about the decisions we make. To consider policymaking, not as something static, but as a lever in a system that is constantly evolving.
The first hurdle to policymaking is deciding if there is even a decision to be made at all. Traditional policymaking works by responding to market failures. It centres interventions around the assumption that an "optimal" state exists and can be maintained or fixed through the allocation of resources. Essentially, if it's not "broken," don't fix it. If it is, get it back to the same way it was before.
The problem is, by thinking of policies as corrections through allocation, we fail to acknowledge their role in the formation of new problems and opportunities through exploration adjacent to the correction itself. Essentially, this approach fails to appreciate the context in which a policy may exist and does not help to understand any number of the unintended consequences that action or (more importantly) inaction may cause.
Building context
Borrowing language from Vinnova's Mission-Design framework, I find that shifting this perspective is about identifying all of the possible “angles” a policy problem can be understood from. It’s about building the architecture of the problem. Sense-making and connecting context to understand the elements and actors involved, their relationships, the nature of the interactions between them and then how a decision could potentially impact them.
Moore’s strategic triangle creates a series of useful prompts around the “strategic” elements of a policy decision.
The strategic triangle framework is a great place to start. It is a simple method of building context around the “strategic” elements of a policy by looking to define and understand the public value, operational capacity and legitimacy of a potential decision. By navigating the framework, and answering the questions it proposes, this tool provides a number of angles to identify imbalances and build a narrative around a potential decision.
For example, the operational capacity of a customer support service may not be very efficient. This could be because there is no legitimacy, support, or political drive to improve it, as the policy-makers in charge lack a way of defining how an improvement may create public value.
I find this framework effective as a narrative-building tool during systems mapping sessions with policy teams. It enables policymakers to experience the "messy" part of design, "touching" the system as they map it while giving everyone in the room a way of communicating it effectively—alignment which is often just as crucial as the final outputs themselves.
Defining the problem
Once an initial view of a system has been built around a policy, creating a problem definition is a crucial step. At HMRC Policy Lab, problem definitions are created with policy teams as an agreement of the work we will carry out with them. They are an effective way of communicating why a decision needs to be made and gives direction for the necessary work that needs to follow.
A good problem definition, supported by Eugene Bardach's guide to policy analysis, "The Eightfold Path to More Effective Problem Solving," accurately reflects the problem in a way that can be evaluated, understands the root cause(s) of the problem and does not define the solution within the definition itself.