This post forms one part of the Policy Analysis in 750 words series. It draws on this 500 Words post, then my interpretation of co-authored work with Drs Emily St Denny and John Boswell (which I would be delighted to share if it gets published). It trails off at the end.
In policy studies, ambiguity describes the ability to entertain more than one interpretation of a policy problem. There are many ways to frame issues as problems. However, only some frames receive high policymaker attention, and policy change relates strongly to that attention. Resolving ambiguity in your favour is the prize.
Policy studies focus on different aspects of this dynamic, including:
- The exercise of power, such as of the narrator to tell stories and the audience to engage with or ignore them.
- Policy learning, in which people collaborate (and compete) to assign concrete meaning to abstract aims.
- A complex process in which many policymakers and influencers are cooperating/ competing to define problems in many policymaking centres.
They suggest that resolving ambiguity affects policy in different ways, to influence the:
- Single policy instrument produced by one centre,
- Accumulation of separate instruments emerging from many centres, or
- Outcome of collaboration across those centres.
The latter descriptions, reflecting multi-centric policymaking, seem particularly relevant to major contemporary policy problems – such as global public health and climate crises – in which cooperation across (and outside of) many levels and types of government is essential.
Resolving ambiguity in policy analysis texts
This context helps us to interpret common (Step 1) advice in policy analysis textbooks: define a policy problem for your client, using your skills of research and persuasion but tailoring your advice to your client’s interests and beliefs. Yet, gone are the mythical days of elite analysts communicating to a single core executive in charge of formulating and implementing all policy instruments. Many analysts engage with many centres producing (or co-producing) many instruments. Resolving ambiguity in one centre does not guarantee the delivery of your aims across many.
Two ways to resolve ambiguity in policy analysis
Classic debates would highlight two different responses:
- ‘Top down’ accounts see this issue through the lens of a single central government, examining how to reassert central control by minimising implementation gaps.
Policy analysis may focus on (a) defining the policy problem, and (b) ensuring the implementation of its solution.
- ‘Bottom up’ accounts identify the inevitability (and legitimacy) of policy influence in multiple centres. Policy analysis may focus on how to define the problem in cooperation with other centres, or to set a strategic direction and encourage other centres to make sense of it in their context.
This terminology went out of fashion, but note the existence of each tendency in two ideal-type approaches to contemporary policy problems:
1. Centralised and formalised approaches.
Seek clarity and order to address urgent policy problems. Define the policy problem clearly, translate that definition into strategies for each centre, and develop a common set of effective ‘tools’ to ensure cooperation and delivery.
Policy analysis may focus on technical aspects, such as how to create a fine-detail blueprint for action, backed by performance management and accountability measures that tie actors to specific commitments.
The tagline may be: ambiguity is a problem to be solved, to direct policy actors towards a common goal.
2. Decentralised, informal, collaborative approaches.
Seek collaboration to make sense of, and address, problems. Reject a single definition of the problem, encourage actors in each centre (or in concert) to deliberate to make sense of problems together, and co-create the rules to guide a continuous process of collective behaviour.
Policy analysis may focus on how to contribute to a collaborative process of sense-making and rule-making.
The tagline may be: ambiguity presents an opportunity to energise policy actors, to harness the potential for innovation arising from deliberation.
Pick one approach and stick with it?
Describing these approaches in such binary terms makes the situation – and choice between approaches – look relatively straightforward. However, note the following issues:
- Many policy sectors (and intersectoral agendas) are characterised by intense disagreement on which choice to make. These disagreements intersect with others (such as when people seek not only transformative policy change to solve global problems, but also equitable process and outcomes).
- Some sectors seem to involve actors seeking the best of both worlds (centralise and localise, formalise and deliberate) without recognising the trade-offs and dilemmas that arise.
- I have described these options as choices, but did not establish if anyone is in the position to make or contribute to that choice.
In that context, resolving ambiguity in your favour may still be the prize, but where would you even begin?
Further reading
Well, that was an unsatisfying end to the post, eh? Maybe I’ll write a better one when some things are published. In the meantime, some of these papers and posts explore some of these issues:
- Policy Concepts in 1000 Words: the Institutional Analysis and Development Framework (IAD) and Governing the Commons – the IAD is your go-to framework to study collaborative governance
- Improving policy implementation through collaborative policymaking
- The future of public health policymaking after COVID-19: lessons from Health in All Policies – identifies these dilemmas in relation to health equity strategies
- The future of education equity policy: ‘neoliberal’ versus ‘social justice’ approaches – identifies equivalent debates in education
- A systematic review of energy systems – tries to discourage people from thinking that we can solve these issues with a vague reference to ‘systems thinking’
- The contested relationship between governance and evidence – relates ‘evidence based’ to ‘collaborative’ approaches to governance (as does Who should be involved in the process of policy analysis?)
- This page describes a book and many posts on ‘prevention’ policy. We complain that governments use the phrase ‘prevention is better than cure’ without defining prevention, and that they want centralised and decentralised approaches to ‘preventive policymaking’.
- The myth of ‘evidence based policymaking’ in a decentred state argues that policymakers don’t really know what they want, and couldn’t get it if they tried.
- The politics of policy design – tries to make you feel good about never really resolving these dilemmas.