Almost. I have sent a full draft following external feedback and review (next stage: copy-editing). All going well, it will be out in November 2019.
Let’s imagine a heroic researcher, producing the best evidence and fearlessly ‘speaking truth to power’. Then, let’s place this person in four scenarios, each of which combines a discussion of evidence, policy, and politics in different ways.
Now, let’s use these scenarios to produce a 5-step way to ‘make evidence count’.
A narrow focus on making the supply of evidence count, via ‘evidence-based policymaking’, will always be dispiriting because it ignores politics or treats political choice as an inconvenience. If we:
In other words, think about the positive and necessary role of democratic politics before bemoaning post-truth politics and policy-based-evidence-making.
Policy is not made in a cycle containing a linear series of separate stages and we won’t ‘make evidence count’ by using it to inform our practices.
You might not want to give up the cycle image because it presents a simple account of how you should make policy. It suggests that we elect policymakers then: identify their aims, identify policies to achieve those aims, select a policy measure, ensure that the selection is legitimised by the population or its legislature, identify the necessary resources, implement and then evaluate. Or, policymakers aided by expert policy analysts make and legitimise choices, skilful public servants carry them out, and, policy analysts assess the results using evidence.
One compromise is to keep the cycle then show how messy it is in practice:
However, there comes a point when there is too much mess, and the image no longer helps you explain (a) to the public what you are doing, or (b) to providers of evidence how they should engage in political systems. By this point, simple messages from more complicated policy theories may be more useful.
Or, we may no longer want a cycle to symbolise a single source of policymaking authority. In a multi-level system, with many ‘centres’ possessing their own sources of legitimate authority, a single and simple policy cycle seems too artificial to be useful.
People are ‘cognitive misers’ seeking ‘rational’ and ‘irrational’ shortcuts to gather information for action, so you won’t get far if you bombard them with too much evidence. Policymakers already have too much evidence and they seek ways to reduce their cognitive load, relying on: (a) trusted sources of concise evidence relevant to their aims, and (b) their own experience, gut instinct, beliefs, and emotions.
The implication of both shortcuts is that we need to tell simple and persuasive stories about the substance and implications of the evidence we present. To say that ‘the evidence does not speak for itself’ may seem trite, but I’ve met too many people who assume naively that it will somehow ‘win the day’. In contrast, civil servants know that the evidence-informed advice they give to ministers needs to relate to the story that government ministers tell to the public.
In a complex or multi-level environment, one story to one audience (such as a minister) is not enough. If there are many key sources of policymaking authority – including public bodies with high autonomy, organisations and practitioners with the discretion to deliver services, and service users involved in designing services – there are many stories being told about what we should be doing and why. We may convince one audience and alienate (or fail to inspire) another with the same story.
Let me give you one example of the dilemmas that must arise when you combine evidence and politics to produce policy: how do you produce a model of ‘evidence based best practice’ which combines evidence and governance principles in a consistent way? Here are 3 ideal-type models which answer the question in very different ways
The table helps us think through the tensions between models, built on very different principles of good evidence and governance.
In practice, you may want to combine different elements, perhaps while arguing that the loss of consistency is lower than the gain from flexibility. Or, the dynamics of political systems limit such choice or prompt ad hoc and inconsistent choices.
I built a lot of this analysis on the experiences of the Scottish Government, which juggles all three models, including a key focus on improvement method in its Early Years Collaborative.
However, Kathryn Oliver and I show that the UK government faces the same basic dilemma and addresses it in similar ways.
The example freshest in my mind is Sure Start. Its rationale was built on RCT evidence and systematic review. However, its roll-out was built more on local flexibility and service design than insistence on fidelity to a model. More recently, the Troubled Families programme initially set the policy agenda and criteria for inclusion, but increasingly invites local public bodies to select the most appropriate interventions, aided by the Early Intervention Foundation which reviews the evidence but does not insist on one-best-way. Emily St Denny and I explore these issues further in our forthcoming book on prevention policy, an exemplar case study of a field in which it is difficult to know how to ‘make evidence count’.
*Background. This is a post for my talk at the Government Economic Service and Government Social Research Service Annual Training Conference (15th September 2017). This year’s theme is ‘Impact and Future-Proofing: Making Evidence Count’. My brief is to discuss evidence use in the Scottish Government, but it faces the same basic question as the UK Government: how do you combine principles of evidence quality and governance principles? In other words, if you were in a position to design an (a) evidence-gathering system and (b) a political system, you’d soon find major points of tension between them. Resolving those tensions involves political choice, not more evidence. Of course, you are not in a position to design both systems, so the more complicated question is: how do you satisfy principles of evidence and governance in a complex policy process, often driven by policymaker psychology, over which you have little control? Here are 7 different ‘answers’.
Powerpoint Paul Cairney @ GES GSRS 2017
This is a guest post by William L. Swann (left) and Seo Young Kim (right), discussing how to use insights from the Institutional Collective Action Framework to think about how to improve collaborative governance. The full paper has been submitted to the series for Policy and Politics called Practical Lessons from Policy Theories.
Many public policy problems cannot be addressed effectively by a single, solitary government. Consider the problems facing the Greater Los Angeles Area, a heavily fragmented landscape of 88 cities and numerous unincorporated areas and special districts. Whether it is combatting rising homelessness, abating the country’s worst air pollution, cleaning the toxic L.A. River, or quelling gang violence, any policy alternative pursued unilaterally is limited by overlapping authority and externalities that alter the actions of other governments.
Problems of fragmented authority are not confined to metropolitan areas. They are also found in multi-level governance scenarios such as the restoration of Chesapeake Bay, as well as in international relations as demonstrated by recent global events such as “Brexit” and the U.S.’s withdrawal from the Paris Climate Agreement. In short, fragmentation problems manifest at every scale of governance, horizontally, vertically, and even functionally within governments.
In many cases governments would be better off coordinating and working together, but they face barriers that prevent them from doing so. These barriers are what the policy literature refers to as ‘institutional collective action’ (ICA) dilemmas, or collective action problems in which a government’s incentives do not align with collectively desirable outcomes. For example, all governments in a region benefit from less air pollution, but each government has an incentive to free ride and enjoy cleaner air without contributing to the cost of obtaining it.
The ICA Framework, developed by Professor Richard Feiock, has emerged as a practical analytical instrument for understanding and improving fragmented governance. This framework assumes that governments must match the scale and coerciveness of the policy intervention (or mechanism) to the scale and nature of the policy problem to achieve efficient and desired outcomes.
For example, informal networks (a mechanism) can be highly effective at overcoming simple collective action problems. But as problems become increasingly complex, more obtrusive mechanisms, such as governmental consolidation or imposed collaboration, are needed to achieve collective goals and more efficient outcomes. The more obtrusive the mechanism, however, the more actors’ autonomy diminishes and the higher the transaction costs (monitoring, enforcement, information, and agency) of governing.
We explored what actionable steps policymakers can take to improve their results with collaboration in fragmented systems. Our study offers three general practical recommendations based on the empirical literature that can enhance institutional collaborative governance.
First, institutional collaboration is more likely to emerge and work effectively when policymakers employ networking strategies that incorporate frequent, face-to-face interactions.
Government actors networking with popular, well-endowed actors (“bridging strategies”) as well as developing closer-knit, reciprocal ties with a smaller set of actors (“bonding strategies”) will result in more collaborative participation, especially when policymakers interact often and in-person.
Policy network characteristics are also important to consider. Research on estuary governance indicates that in newly formed, emerging networks, bridging strategies may be more advantageous, at least initially, because they can provide organizational legitimacy and access to resources. However, once collaboratives mature, developing stronger and more reciprocal bonds with fewer actors reduces the likelihood of opportunistic behavior that can hinder collaborative effectiveness.
Second, policymakers should design collaborative arrangements that reduce transaction costs which hinder collaboration.
Well-designed collaborative institutions can lower the barriers to participation and information sharing, make it easier to monitor the behaviors of partners, grant greater flexibility in collaborative work, and allow for more credible commitments from partners.
Research suggests policymakers can achieve this by
Considering the context, however, is crucial. Collaboratives that thrive on informal, close-knit, reciprocal relations, for example, may be severely damaged by the introduction of monitoring mechanisms that signal distrust.
Third, institutional collaboration is enhanced by the development and harnessing of collaborative capacity.
Research suggests signaling organizational competencies and capacities, such as budget, political support, and human resources, may be more effective at lowering barriers to collaboration than ‘homophily’ (a tendency to associate with similar others in networks). Policymakers can begin building collaborative capacity by seeking political leadership involvement, granting greater managerial autonomy, and looking to higher-level governments (e.g., national, state, or provincial governments) for financial and technical support for collaboration.
Finally, we recognize that not all policymakers operate in similar institutional contexts, and collaboration can often be mandated by higher-level authorities in more centralized nations. Nonetheless, visible joint gains, economic incentives, transparent rules, and equitable distribution of joint benefits and costs are critical components of voluntary or mandated collaboration.
The recommendations offered here are, at best, only the tip of the iceberg on valuable practical insight that can be gleaned from collaborative governance research. While these suggestions are consistent with empirical findings from broader public management and policy networks literatures, much could be learned from a closer inspection of the overlap between ICA studies and other streams of collaborative governance work.
Collaboration is a valuable tool of governance, and, like any tool, it should be utilized appropriately. Collaboration is not easily managed and can encounter many obstacles. We suggest that governments generally avoid collaborating unless there are joint gains that cannot be achieved alone. But the key to solving many of society’s intractable problems, or just simply improving everyday public service delivery, lies in a clearer understanding of how collaboration can be used effectively within different fragmented systems.
See also our project website IMAJINE.
Two recent articles explore the role of academics in the ‘co-production’ of policy and/or knowledge.
Both papers suggest (I think) that academic engagement in the ‘real world’ is highly valuable, and that we should not pretend that we can remain aloof from politics when producing new knowledge (research production is political even if it is not overtly party political). They also suggest that it is fraught with difficulty and, perhaps, an often-thankless task with no guarantee of professional or policy payoffs (intrinsic motivation still trumps extrinsic motivation).
So, what should we do?
I plan to experiment a little bit while conducting some new research over the next 4 years. For example, I am part of a new project called IMAJINE, and plan to speak with policymakers, from the start to the end, about what they want from the research and how they’ll use it. My working assumption is that it will help boost the academic value and policy relevance of the research.
I have mocked up a paper abstract to describe this kind of work:
In this paper, we use policy theory to explain why the ‘co-production’ of comparative research with policymakers makes it more policy relevant: it allows researchers to frame their policy analysis with reference to the ways in which policymakers frame policy problems; and, it helps them identify which policymaking venues matter, and the rules of engagement within them. In other words, theoretically-informed researchers can, to some extent, emulate the strategies of interest groups when they work out ‘where the action is’ and how to adapt to policy agendas to maximise their influence. Successful groups identify their audience and work out what it wants, rather than present their own fixed views to anyone who will listen.
Yet, when described so provocatively, our argument raises several practical and ethical dilemmas about the role of academic research. In abstract discussions, they include questions such as: should you engage this much with politics and policymakers, or maintain a critical distance; and, if you engage, should you simply reflect or seek to influence the policy agenda? In practice, such binary choices are artificial, prompting us to explore how to manage our engagement in politics and reflect on our potential influence.
We explore these issues with reference to a new Horizon 2020 funded project IMAJINE, which includes a work package – led by Cairney – on the use of evidence and learning from the many ways in which EU, national, and regional policymakers have tried to reduce territorial inequalities.
So, in the paper we (my future research partner and I), would:
Overall, you can see the potential problems: you ‘enter’ the political arena to find that it is highly political! You find that policymakers are mostly interested in (what you believe are) ineffective or inappropriate solutions and/ or they think about the problem in ways that make you, say, uncomfortable. So, should you engage in a critical way, risking exclusion from the ‘coproduction’ of policy, or in a pragmatic way, to ‘coproduce’ knowledge and maximise your chances of their impact in government?
The case study of territorial inequalities is a key source of such dilemmas …
…partly because it is difficult to tell how policymakers define and want to solve such policy problems. When defining ‘territorial inequalities’, they can refer broadly to geographical spread, such as within the EU Member States, or even within regions of states. They can focus on economic inequalities, inequalities linked strongly to gender, race or ethnicity, mental health, disability, and/ or inequalities spread across generations. They can focus on indicators of inequalities in areas such as health and education outcomes, housing tenure and quality, transport, and engagement with social work and criminal justice. While policymakers might want to address all such issues, they also prioritise the problems they want to solve and the policy instruments they are prepared to use.
When considering solutions, they can choose from three basic categories:
Based on my previous work with Emily St Denny, I’d expect that many governments express a high commitment to reduce inequalities – and it is often sincere – but without wanting to use tax/ spending as the primary means, and faced with limited evidence on the effectiveness of public services and prevention. Or, many will prefer to identify ‘evidence-based’ solutions for individuals rather than to address ‘structural’ factors linked to factors such as gender, ethnicity, and class. This is when the production and use of evidence becomes overtly ‘political’, because at the heart of many of these discussions is the extent to which individuals or their environments are to blame for unequal outcomes, and if richer regions should compensate poorer regions.
‘The evidence’ will not ‘win the day’ in such debates. Rather, the choice will be between, for example: (a) pragmatism, to frame evidence to contribute to well-established beliefs, about policy problems and solutions, held by the dominant actors in each political system; and, (b) critical distance, to produce what you feel to be the best evidence generated in the right way, and challenge policymakers to explain why they won’t use it. I suspect that (a) is more effective, but (b) better reflects what most academics thought they were signing up to.
For more on evidence/ policy dilemmas, see Kathryn Oliver and I have just published an article on the relationship between evidence and policy
“There is extensive health and public health literature on the ‘evidence-policy gap’, exploring the frustrating experiences of scientists trying to secure a response to the problems and solutions they raise and identifying the need for better evidence to reduce policymaker uncertainty. We offer a new perspective by using policy theory to propose research with greater impact, identifying the need to use persuasion to reduce ambiguity, and to adapt to multi-level policymaking systems”.
We use this table to describe how the policy process works, how effective actors respond, and the dilemmas that arise for advocates of scientific evidence: should they act this way too?
We summarise this argument in two posts for:
The article is part of a wider body of work in which one or both of us considers the relationship between evidence and policy in different ways, including:
Oliver, K., Innvar, S., Lorenc, T., Woodman, J. and Thomas, J. (2014a) ‘A systematic review of barriers to and facilitators of the use of evidence by policymakers’ BMC health services research, 14 (1), 2. http://www.biomedcentral.com/1472-6963/14/2
Oliver, K., Lorenc, T., & Innvær, S. (2014b) ‘New directions in evidence-based policy research: a critical analysis of the literature’, Health Research Policy and Systems, 12, 34 http://www.biomedcentral.com/content/pdf/1478-4505-12-34.pdf
Paul Cairney (2016) Evidence-based best practice is more political than it looks in Evidence and Policy
Many of my blog posts explore how people like scientists or researchers might understand and respond to the policy process:
There are more posts like this on my EBPM page
I am also guest editing a series of articles for the Open Access journal Palgrave Communications on the ‘politics of evidence-based policymaking’ and we are inviting submissions throughout 2017.
There are more details on that series here.
And finally ..
It can be quite daunting to produce a policy analysis paper or blog post for the first time. You learn about the constraints of political communication by being obliged to explain your ideas in an unusually small number of words. The short word length seems good at first, but then you realise that it makes your life harder: how can you fit all your evidence and key points in? The answer is that you can’t. You have to choose what to say and what to leave out.
You also have to make this presentation ‘not about you’. In a long essay or research report you have time to show how great you are, to a captive audience. In a policy paper, imagine that you are trying to get the attention and support from someone that may not know or care about the issue you raise. In a blog post, your audience might stop reading at any point, so every sentence counts.
There are many guides out there to help you with the practical side, including the broad guidance I give you in the module guide, and Bardach’s 8-steps. In each case, the basic advice is to (a) identify a policy problem and at least one feasible solution, and (b) tailor the analysis to your audience.
Be concise, be smart
So, for example, I ask you to keep your analysis and presentations super-short on the assumption that you have to make your case quickly to people with 99 other things to do. What can you tell someone in a half-page (to get them to read all 2 pages)? Could you explain and solve a problem if you suddenly bumped into a government minister in a lift/ elevator?
It is tempting to try to tell someone everything you know, because everything is connected and to simplify is to describe a problem simplistically. Instead, be smart enough to know that such self-indulgence won’t impress your audience. They might smile politely, but their eyes are looking at the elevator lights.
Your aim is not to give a full account of a problem – it’s to get someone important to care about it.
Your aim is not to give a painstaking account of all possible solutions – it’s to give a sense that at least one solution is feasible and worth pursuing.
Your guiding statement should be: policymakers will only pay attention to your problem if they think they can solve it, and without that solution being too costly.
I don’t like to give you too much advice because I want you to be creative about your presentation; to be confident enough to take chances and feel that I’ll reward you for making the leap. At the very least, you have three key choices to make about how far you’ll go to make a point:
For our purposes, there are no wrong answers to these questions. Instead, I want you to make and defend your decisions. That is the aim of your policy paper ‘reflection’: to ‘show your work’.
You still have some room to be creative: tell me what you know about policy theory and British politics and how it informed your decisions. Here are some examples, but it is up to you to decide what to highlight:
Be a blogger
With a blog post, your audience is wider. You are trying to make an argument that will capture the attention of a more general audience (interested in politics and policy, but not a specialist) that might access your post from Twitter/ Facebook or via a search engine. This produces a new requirement, to: present a ‘punchy’ title which sums up the whole argument in under 140 characters (a statement is often better than a vague question); to summarise the whole argument in (say) 100 words in the first paragraph (what is the problem and solution?); and, to provide more information up to a maximum of 500 words. The reader can then be invited to read the whole policy analysis.
The style of blog posts varies markedly, so you should consult many examples before attempting your own (compare the LSE with The Conversation and newspaper columns to get a sense of variations in style). When you read other posts, take note of their strengths and weaknesses. For example, many posts associated with newspapers introduce a personal or case study element to ground the discussion in an emotional appeal. Sometimes this works, but sometimes it causes the reader to scroll down quickly to find the main argument. Consider if it is as, or more, effective to make your argument more direct and easy to find as soon as someone clicks the link on their phone. Many academic posts are too long (well beyond your 500 limit), take too long to get to the point, and do not make explicit recommendations, so you should not merely emulate them. You should also not just chop down your policy paper – this is about a new kind of communication.
Be reflective once again
Hopefully, by the end, you will appreciate the transferable life skills. I have generated some uncertainty about your task to reflect the sense among many actors that they don’t really know how to make a persuasive case and who to make it to. We can follow some basic Bardach-style guidance, but a lot of this kind of work relies on trial-and-error. I maintain a short word count to encourage you to get to the point, and I bang on about ‘stories’ in our module to encourage you to make a short and persuasive story to policymakers.
This process seems weird at first, but isn’t it also intuitive? For example, next time you’re in my seminar, measure how long it takes you to get bored and look forward to the weekend. Then imagine that policymakers have the same attention span as you. That’s how long you have to make your case!
See also: Professionalism online with social media
Here is the advice that my former lecturer, Professor Brian Hogwood, gave in 1992. Has the advice changed much since then?