What is policy?
We are all subjected to policy outcomes, every day, in our work and personal lives. But what does the word 'policy' actually mean? Thirty years ago, the political scientists Hogwood and Gunn described policy as any or all of the following:
- a field of activity (e.g. foreign or health policy)
- a general intent (e.g. a drive to make the world a healthier place)
- a specific proposal (usually target driven)
- something that requires formal authorisation or legislation
- implementing a programme of action.
Clearly, these are broad definitions, but they highlight that the word 'policy' is closely linked to a problem and the strategies needed to solve it. Understanding how and why policy comes into existence, and who decides how it is acted on, is key to understanding how policy decisions are made.
It is important to understand that 'policy' is not a single outcome or event and is usually seen as a cycle, which moves from agenda setting to implementation, monitoring and evaluation (Figure 1).
The policy process has been characterised as being driven by "an interplay of institutions, ideas and interests" (Peter John, 1998). Typically, the process is contested and - like the political arena in which it takes place - messy (Figure 2). If researchers are to influence the policy process, they must be aware of its dynamics.
How does research influence policy?
What does the 'messy' field of policy making mean for researchers engaged in gathering evidence? Researchers, especially those in the applied field, are often expected to have policy influence and to see their research taken up into policy and practice. Several models have been put forward to explain how this happens.
Many researchers operate within the engineering model, which takes the view that results from good research 'speak for themselves' and will influence public policies in a direct, immediate and linear fashion. We rarely see this in practice.
Other models for viewing the influence of research on policy are explained below.
Enlightenment model: new evidence and ideas from research filter into policy networks and shape policy in complex and indirect ways. Research can support a process of 'enlightenment' among those who influence decision making.
Strategic model: decision makers commission research to delay decision making or make highly selective use of research findings to support their own interests or positions.
Elective affinity model: policy makers are more likely to act on research if the findings are in tune with their own pre-existing views and beliefs. Researchers can influence policy makers through sustained interaction - particularly by involving decision makers in the research process.
Two communities model: policy makers and researchers come from different communities and have gaps between them in terms of training, understanding respective technical issues, the use of language, incentives and rewards, accountabilities, time frames and so on.
Advocacy coalition model: stresses the need for collaboration among researchers, policy makers and affected stakeholders through networks.
For further information on these and other models, see Buse, Mays and Walt (2012) 'Making Health Policy' (Open University Press).
Summary
Policy making and the policy cycle are complex, competitive and subject to the interaction of many processes and people. Using Peter John's framework, researchers usually fall into the 'ideas' category; if they want to influence the policy cycle, researchers need to understand and respond to what is going on in the 'institutions' and 'interests' categories.
The recognised (but not exhaustive) models of how researchers interact with those who influence the policy cycle can help guide where and how researcher-policy engagement is most likely to have an impact on policy outcomes.