Taking lessons from policy theory into practice: 3 examples

Notes for ANZSOG/ ANU Crawford School/ UNSW Canberra workshop. Powerpoint here. The recording of the lecture (skip to 2m30) and Q&A is here (right click to download mp3 or dropbox link):

The context for this workshop is the idea that policy theories could be more helpful to policymakers/ practitioners if we could all communicate more effectively with each other. Academics draw general and relatively abstract conclusions from multiple cases. Practitioners draw very similar conclusions from rich descriptions of direct experience in a smaller number of cases. How can we bring together their insights and use a language that we all understand? Or, more ambitiously, how can we use policy theory-based insights to inform the early career development training that civil servants and researchers receive?

The first step is to translate policy theories into a non-technical language by trying to speak with an audience beyond our immediate peers (see for example Practical Lessons from Policy Theories).

However, translation is not enough. A second crucial step is to consider how policymakers and practitioners are likely to make sense of theoretical insights when they apply them to particular aims or responsibilities. For example:

1. Central government policymakers may accept the descriptive accuracy of policy theories emphasising limited central control, but not the recommendation that they should let go, share power, and describe their limits to the public.
2. Scientists may accept key limitations to ‘evidence based policymaking’ but reject the idea that they should respond by becoming better storytellers or more manipulative operators.
3. Researchers and practitioners struggle to resolve hard choices when combining evidence and ‘coproduction’ while ‘scaling up’ policy interventions. Evidence choice is political choice. Can we do more than merely encourage people to accept this point?

I discuss these examples below because they are closest to my heart (especially example 1). Note throughout that I am presenting one interpretation about: (1) the most promising insights, and (2) their implications for practice. Other interpretations of the literature and its implications are available. They are just a bit harder to find.

Example 1: the policy cycle endures despite its descriptive inaccuracy

The policy cycle does not describe and explain the policy process well:

• If we insist on keeping the cycle metaphor, it is more accurate to see the process as a huge set of policy cycles that connect with each other in messy and unpredictable ways.
• The cycle approach also links strongly to the idea of ‘comprehensive rationality’ in which a small group of policymakers and analysts are in full possession of the facts and full control of the policy process. They carry out their aims through a series of stages.

Policy theories provide more descriptive and explanatory usefulness. Their insights include:

• Limited choice. Policymakers inherit organisations, rules, and choices. Most ‘new’ choice is a revision of the old.
• Limited attention. Policymakers must ignore almost all of the policy problems for which they are formally responsible. They pay attention to some, and delegate most responsibility to civil servants. Bureaucrats rely on other actors for information and advice, and they build relationships on trust and information exchange.
• Limited central control. Policy may appear to be made at the ‘top’ or in the ‘centre’, but in practice policymaking responsibility is spread across many levels and types of government (many ‘centres’). ‘Street level’ actors make policy as they deliver. Policy outcomes appear to ‘emerge’ locally despite central government attempts to control their fate.
• Limited policy change. Most policy change is minor, made and influenced by actors who interpret new evidence through the lens of their beliefs. Well-established beliefs limit the opportunities of new solutions. Governments tend to rely on trial-and-error, based on previous agreements, rather than radical policy change based on a new agenda. New solutions succeed only during brief and infrequent windows of opportunity.

However, the cycle metaphor endures because:

• It provides a simple model of policymaking with stages that map onto important policymaking functions.
• It provides a way to project policymaking to the public. You know how we make policy, and that we are in charge, so you know who to hold to account.

In that context, we may want to be pragmatic about our advice:

1. One option is via complexity theory, in which scholars generally encourage policymakers to accept and describe their limits:

• Accept routine error, reduce short-term performance management, engage more in trial and error, and ‘let go’ to allow local actors the flexibility to adapt and respond to their context.
• However, would a government in the Westminster tradition really embrace this advice? No. They need to balance (a) pragmatic policymaking, and (b) an image of governing competence.

2. Another option is to try to help improve an existing approach.

• Koski and Workman build on PET to recommend ways to process information more effectively.
• Studies built on MSA tend to focus on ‘entrepreneurs’ having a technically and politically feasible solution ready for the next window of opportunity.
• Sanderson describes the skills required for ‘intelligent policymaking’.
• I sum up these approaches in ‘How Can Policy Theory Have an Impact on Policy Making?’ Teaching Public Administration, 33, 1, 22-39 

Further reading (blog posts):

The language of complexity does not mix well with the language of Westminster-style accountability

Making Sense of Policymaking: why it’s always someone else’s fault and nothing ever changes

Two stories of British politics: the Westminster model versus Complex Government

Example 2: how to deal with a lack of ‘evidence based policymaking’

I used to read many papers on tobacco policy, with the same basic message: we have the evidence of tobacco harm, and evidence of which solutions work, but there is an evidence-policy gap caused by too-powerful tobacco companies, low political will, and pathological policymaking. These accounts are not informed by theories of policymaking.

I then read Oliver et al’s paper on the lack of policy theory in health/ environmental scholarship on the ‘barriers’ to the use of evidence in policy. Very few articles rely on policy concepts, and most of the few rely on the policy cycle. This lack of policy theory is clear in their description of possible solutions – better communication, networking, timing, and more science literacy in government – which does not describe well the need to respond to policymaker psychology and a complex policymaking environment.

So, I wrote The Politics of Evidence-Based Policymaking and one zillion blog posts to help identify the ways in which policy theories could help explain the relationship between evidence and policy.

Since then, the highest demand to speak about the book has come from government/ public servant, NGO, and scientific audiences outside my discipline. The feedback is generally that: (a) the book’s description sums up their experience of engagement with the policy process, and (b) maybe it opens up discussion about how to engage more effectively.

But how exactly do we turn empirical descriptions of policymaking into practical advice?

For example, scientist/ researcher audiences want to know the answer to a question like: Why don’t policymakers listen to your evidence? and so I focus on three conversation starters:

1. they have a broader view on what counts as good evidence (see ANZSOG description)
2. they have to ignore almost all information (a nice way into bounded rationality and policymaker psychology)
3. they do not understand or control the process in which they seek to use evidence (a way into ‘the policy process’)

We can then consider many possible responses in the sequel What can you do when policymakers ignore your evidence?

Examples include:

• ‘How to do it’ advice. I compare tips for individuals (from experienced practitioners) with tips based on policy concepts. They are quite similar-looking tips – e.g. find out where the action is, learn the rules, tell good stories, engage allies, seek windows of opportunity – but I describe mine as 5 impossible tasks!
• Organisational reform. I describe work with the European Commission Joint Research Centre to identify 8 skills or functions of an organisation bringing together the supply/demand of knowledge.
• Ethical dilemmas. I use key policy theories to ask people how far they want to go to privilege evidence in policy. It’s fun to talk about these things with the type of scientist who sees any form of storytelling as manipulation.

Further reading:

Is Evidence-Based Policymaking the same as good policymaking?

A 5-step strategy to make evidence count

Political science improves our understanding of evidence-based policymaking, but does it produce better advice?

Principles of science advice to government: key problems and feasible solutions

Example 3: how to encourage realistic evidence-informed policy transfer

This focus on EBPM is useful context for discussions of ‘policy learning’ and ‘policy transfer’, and it was the focus of my ANZOG talk entitled (rather ambitiously) ‘teaching evidence-based policy to fly’.

I’ve taken a personal interest in this one because I’m part of a project – called IMAJINE – in which we have to combine academic theory and practical responses. We are trying to share policy solutions across Europe rather than explain why few people share them!

For me, the context is potentially overwhelming:

• Policy learning is a political process, and expert-driven learning is one of many possibilities, alongside dialogue, bargaining, and hierarchical models.
• Indeed, researchers often do badly because they don’t learn how to deal with the politics.
• Policy transfer can be maximal or minimal, and driven voluntarily or via coercion. A policy solution, when ‘imported’, can be mimicked, translated or transformed.
• When transfer is voluntary, receptivity to new solutions is more important than their supply.
• There are very different ‘evidence-based’ models on how to ‘scale up’ policy success.

So, when we start to focus on sharing lessons, we will have three things to discover:

1. What is the evidence for success, and from where does it come? Governments often project success without backing it up.
2. What story do policymakers tell about the problem they are trying to solve, the solutions they produced, and why? Two different governments may be framing and trying to solve the same problem in very different ways.
3. Was the policy introduced in a comparable policymaking system? People tend to focus on political system comparability (e.g. is it unitary or federal?), but I think the key is in policymaking system comparability (e.g. what are the rules and dominant ideas?).

To be honest, when one of our external assessors asked me how well I thought I would do, we both smiled because the answer may be ‘not very’. In other words, the most practical lesson may be the hardest to take, although I find it comforting: the literature suggests that policymakers might ignore you for 20 years then suddenly become very (but briefly) interested in your work.

 

The slides are a bit wonky because I combined my old ppt to the Scottish Government with a new one for UNSW Paul Cairney ANU Policy practical 22 October 2018

I wanted to compare how I describe things to (1) civil servants (2) practitioners/ researcher (3) me, but who has the time/ desire to listen to 3 powerpoints in one go? If the answer is you, let me know and we’ll set up a Zoom call.

Teaching evidence based policy to fly: how to deal with the politics of policy learning and transfer

This post provides (a generous amount of) background for my ANZSOG talk Teaching evidence based policy to fly: transferring sound policies across the world.

The event’s description sums up key conclusions in the literature on policy learning and policy transfer:

1. technology and ‘entrepreneurs’ help ideas spread internationally, and domestic policymakers can use them to be more informed about global policy innovation, but
2. there can be major unintended consequences to importing ideas, such as the adoption of policy solutions with poorly-evidenced success, or a broader sense of failed transportation caused by factors such as a poor fit between the aims of the exporter/importer.

In this post, I connect these conclusions to broader themes in policy studies, which suggest that:

3. policy learning and policy transfer are political processes, not ‘rational’ or technical searches for information
4. the use of evidence to spread policy innovation requires two interconnected choices: what counts as good evidence, and what role central governments should play.
5. the following ’11 question guide’ to evidence based policy transfer serves more as a way to reflect than a blueprint for action.

As usual, I suggest that we focus less on how we think we’d like to do it, and more on how people actually do it.

Policy transfer describes the use of evidence about policy in one political system to help develop policy in another. Taken at face value, it sounds like a great idea: why would a government try to reinvent the wheel when another government has shown how to do it?

Therefore, wouldn’t it be nice if I turned up to the lecture, equipped with a ‘blueprint’ for ‘evidence based’ policy transfer, and declared how to do it in a series of realistic and straightforward steps? Unfortunately, there are three main obstacles:

1. ‘Evidence based’ is a highly misleading description of the use of information in policy.
2. To transfer a policy blueprint completely, in this manner, would require all places and contexts to be the same, and for the policy process to be technocratic and apolitical.
3. There are general academic guides on how to learn lessons from others systematically – such as Richard Rose’s ‘practical guide’  – but most academic work on learning and transfer does not suggest that policymakers follow this kind of advice.

Instead, policy learning is a political process – involving the exercise of power to determine what and how to learn – and it is difficult to separate policy transfer from the wider use of evidence and ideas in policy processes.

Let’s take each of these points in turn, before reflecting on their implications for any X-step guide:

3 reasons why ‘evidence based’ does not describe policymaking

In a series of ANZSOG talks on ‘evidence based policymaking’ (EBPM), I describe three main factors, all of which are broadly relevant to transfer:

1. There are many forms of policy-relevant evidence and few policymakers adhere to a strict ‘hierarchy’ of knowledge.

Therefore, it is unclear how one government can, or should, generate evidence of another government’s policy success.

2. Policymakers must find ways to ignore most evidence – such as by combining ‘rational’ and ‘irrational’ cognitive shortcuts – to be able to act quickly.

The generation of policy transfer lessons is a highly political process in which actors adapt to this need to prioritise information while competing with each other. They exercise power to: prioritise some information and downplay the rest, define the nature of the policy problem, and evaluate the success of another government’s solutions. There is a strong possibility that policymakers will import policy solutions without knowing if, and why, they were successful.

3. They do not control the policy process in which they engage.

We should not treat ‘policy transfer’ as separate from the policy process in which policymakers and influencers engage. Rather, the evidence of international experience competes with many other sources of ideas and evidence within a complex policymaking system.

The literature on ‘policy learning’ tells a similar story

Studies of the use of evaluation evidence (perhaps to answer the question: was this policy successful?) have long described policymakers using the research process for many different purposes, from short term problem-solving and long-term enlightenment, to putting off decisions or using evidence cynically to support an existing policy.

We should therefore reject the temptation to (a) equate ‘policy learning’ with a simplistic process that we might associate with teachers transmitting facts to children, or (b) assume that adults simply change their beliefs when faced with new evidence. Rather, Dunlop and Radaelli describe policy learning as a political process in the following ways:

1.It is collective and rule-bound

Individuals combine cognition and emotion to process information, in organisations with rules that influence their motive and ability to learn, and in wider systems, in which many actors cooperate and compete to establish the rules of evidence gathering and analysis, or policymaking environments that constrain or facilitate their action.

2.’Evidence based’ is one of several types of policy learning

• Epistemic. Primarily by scientific experts transmitting knowledge to policymakers.
• Reflection. Open dialogue to incorporate diverse forms of knowledge and encourage cooperation.
• Bargaining. Actors learn how to cooperate and compete effectively.
• Hierarchy. Actors with authority learn how to impose their aims; others learn the limits to their discretion.

3.The process can be ‘dysfunctional’: driven by groupthink, limited analysis, and learning how to dominate policymaking, not improve policy.

Their analysis can produce relevant take-home points such as:

• Experts will be ineffective if they assume that policy learning is epistemic. The assumption will leave them ill-prepared to deal with bargaining.
• There is more than one legitimate way to learn, such as via deliberative processes that incorporate more perspectives and forms of knowledge.

What does the literature on transfer tell us?

‘Policy transfer’ can describe a spectrum of activity:

• driven voluntarily, by a desire to learn from the story of another government’s policy’s success. In such cases, importers use shortcuts to learning, such as by restricting their search to systems with which they have something in common (such as geography or ideology), learning via intermediaries such as ‘entrepreneurs’, or limiting their searches for evidence of success.
• driven by various forms of pressure, including encouragement by central (or supranational) governments, international norms or agreements, ‘spillover’ effects causing one system to respond to innovation by another, or demands by businesses to minimise the cost of doing business.

In that context, some of the literature focuses on warning against unsuccessful policy transfer caused by factors such as:

• Failing to generate or use enough evidence on what made the initial policy successful
• Failing to adapt that policy to local circumstances
• Failing to back policy change with sufficient resources

However, other studies highlight some major qualifications:

• If the process is about using ideas about one system to inform another, our attention may shift from ‘transfer’ to ‘translation’ or ‘transformation’, and the idea of ‘successful transfer’ makes less sense
• Transfer success is not the same as implementation success, which depends on a wider range of factors
• Nor is it the same as ‘policy success’, which can be assessed by a mix of questions to reflect political reality: did it make the government more re-electable, was the process of change relatively manageable, and did it produce intended outcomes?

The use of evidence to spread policy innovation requires a combination of profound political and governance choices

When encouraging policy diffusion within a political system, choices about: (a) what counts as ‘good’ evidence of policy success have a major connection to (b) what counts as good governance.

For example, consider these ideal-types or models in table 1:

In one scenario, we begin by relying primarily on RCT evidence (multiple international trials) and import a relatively fixed model, to ensure ‘fidelity’ to a proven intervention and allow us to measure its effect in a new context. This choice of good evidence limits the ability of subnational policymakers to adapt policy to local contexts.

In another scenario, we begin by relying primary on governance principles, such as to respect local discretion as well as incorporate practitioner and user experience as important knowledge claims. The choice of governance model relates closely to a less narrow sense of what counts as good evidence, but also a more limited ability to evaluate policy success scientifically.

In other words, the political choice to privilege some forms of evidence is difficult to separate from another political choice to privilege the role of one form of government.

Telling a policy transfer story: 11 questions to encourage successful evidence based policy transfer  

In that context, these steps to evidence-informed policy transfer serve more to encourage reflection than provide a blueprint for action. I accept that 11 is less catchy than 10.

1. What problem did policymakers say they were trying to solve, and why?
2. What solution(s) did they produce?
3. Why?

Points 1-3 represent the classic and necessary questions from policy studies: (1) ‘what is policy?’ (2)  ‘how much did policy change?’ and (3) why? Until we have a good answer, we do not know how to draw comparable lessons. Learning from another government’s policy choices is no substitute for learning from more meaningful policy change.

4. Was the project introduced in a country or region which is sufficiently comparable? Comparability can relate to the size and type of country, the nature of the problem, the aims of the borrowing/ lending government and their measures of success.

5. Was it introduced nationwide, or in a region which is sufficiently representative of the national experience (it is not an outlier)?

6. How do we account for the role of scale, and the different cultures and expectations in each policy field?

Points 4-6 inform initial background discussions of case study reports. We need to focus on comparability when describing the context in which the original policy developed. It is not enough to state that two political systems are different. We need to identify the relevance and implications of the differences, from another government’s definition of the problem to the logistics of their task.

7. Has the project been evaluated independently, subject to peer review and/ or using measures deemed acceptable to the government?

8. Has the evaluation been of a sufficient period in proportion to the expected outcomes?

9. Are we confident that this project has been evaluated the most favourably – i.e. that our search for relevant lessons has been systematic, based on recognisable criteria (rather than reputations)?

10. Are we identifying ‘Good practice’ based on positive experience, ‘Promising approaches’ based on positive but unsystematic findings, ‘Research–based’ or based on ‘sound theory informed by a growing body of empirical research’, or ‘Evidence–based’, when ‘the programme or practice has been rigorously evaluated and has consistently been shown to work’?

Points 7-10 raise issues about the relationships between (a) what evidence we should use to evaluate success or potential, and (b) how long we should wait to declare success.

11. What will be the relationship between evidence and governance?

Should we identify the same basic model and transfer it uniformly, tell a qualitative story about the model and invite people to adapt it, or focus pragmatically on an eclectic range of evidential sources and focus on the training of the actors who will implement policy?

In conclusion

Information technology has allowed us to gather a huge amount of policy-relevant information across the globe. However, it has not solved the limitations we face in defining policy problems clearly, gathering evidence on policy solutions systematically, and generating international lessons that we can use to inform domestic policy processes.

This rise in available evidence is not a substitute for policy analysis and political choice. These choices range from how to adjudicate between competing policy preference, to how to define good evidence and good government. A lack of attention to these wider questions helps explain why – at least from some perspectives – policy transfer seems to fail.

Paul Cairney Auckland Policy Transfer 12.10.18

 

 

The Politics of Evidence-Based Policymaking: ANZSOG talks

This post introduces a series of related talks on ‘the politics of evidence-based policymaking’ (EBPM) that I’m giving as part of larger series of talks during this ANZOG-funded/organised trip.

The EBPM talks begin with a discussion of the same three points: what counts as evidence, why we must ignore most of it (and how), and the policy process in which policymakers use some of it. However, the framing of these points, and the ways in which we discuss the implications, varies markedly by audience. So, in this post, I provide a short discussion of the three points, then show how the audience matters (referring to the city as a shorthand for each talk).

The overall take-home points are highly practical, in the same way that critical thinking has many practical applications (in other words, I’m not offering a map, toolbox, or blueprint):

• If you begin with (a) the question ‘why don’t policymakers use my evidence?’ I like to think you will end with (b) the question ‘why did I ever think they would?’.
• If you begin by taking the latter as (a) a criticism of politics and policymakers, I hope you will end by taking it as (b) a statement of the inevitability of the trade-offs that must accompany political choice.
• We may address these issues by improving the supply and use of evidence. However, it is more important to maintain the legitimacy of the politicians and political systems in which policymakers choose to ignore evidence. Technocracy is no substitute for democracy.

3 ways to describe the use of evidence in policymaking

1. Discussions of the use of evidence in policy often begin as a valence issue: who wouldn’t want to use good evidence when making policy?

However, it only remains a valence issue when we refuse to define evidence and justify what counts as good evidence. After that, you soon see the political choices emerge. A reference to evidence is often a shorthand for scientific research evidence, and good often refers to specific research methods (such as randomised control trials). Or, you find people arguing very strongly in the almost-opposite direction, criticising this shorthand as exclusionary and questioning the ability of scientists to justify claims to superior knowledge. Somewhere in the middle, we find that a focus on evidence is a good way to think about the many forms of information or knowledge on which we might make decisions, including: a wider range of research methods and analyses, knowledge from experience, and data relating to the local context with which policy would interact.

So, what begins as a valence issue becomes a gateway to many discussions about how to understand profound political choices regarding: how we make knowledge claims, how to ‘co-produce’ knowledge via dialogue among many groups, and the relationship between choices about evidence and governance.

2. It is impossible to pay attention to all policy relevant evidence.

There is far more information about the world than we are able to process. A focus on evidence gaps often gives way to the recognition that we need to find effective ways to ignore most evidence.

There are many ways to describe how individuals combine cognition and emotion to limit their attention enough to make choices, and policy studies (to all intents and purposes) describe equivalent processes – described, for example, as ‘institutions’ or rules – in organisations and systems.

One shortcut between information and choice is to set aims and priorities; to focus evidence gathering on a small number of problems or one way to define a problem, and identify the most reliable or trustworthy sources of evidence (often via evidence ‘synthesis’). Another is to make decisions quickly by relying on emotion, gut instinct, habit, and existing knowledge or familiarity with evidence.

Either way, agenda setting and problem definition are political processes that address uncertainty and ambiguity. We gather evidence to reduce uncertainty, but first we must reduce ambiguity by exercising power to define the problem we seek to solve.

3. It is impossible to control the policy process in which people use evidence.

Policy textbooks (well, my textbook at least!) provide a contrast between:

• The model of a ‘policy cycle’ that sums up straightforward policymaking, through a series of stages, over which policymakers have clear control. At each stage, you know where evidence fits in: to help define the problem, generate solutions, and evaluate the results to set the agenda for the next cycle.
• A more complex ‘policy process’, or policymaking environment, of which policymakers have limited knowledge and even less control. In this environment, it is difficult to know with whom engage, the rules of engagement, or the likely impact of evidence.

Overall, policy theories have much to offer people with an interest in evidence-use in policy, but primarily as a way to (a) manage expectations, to (b) produce more realistic strategies and less dispiriting conclusions. It is useful to frame our aim as to analyse the role of evidence within a policy process that (a) we don’t quite understand, rather than (b) we would like to exist.

The events themselves

Below, you will find a short discussion of the variations of audience and topic. I’ll update and reflect on this discussion (in a revised version of this post) after taking part in the events.

Social science and policy studies: knowledge claims, bounded rationality, and policy theory

For Auckland and Wellington A, I’m aiming for an audience containing a high proportion of people with a background in social science and policy studies. I describe the discussion as ‘meta’ because I am talking about how I talk about EBPM to other audiences, then inviting discussion on key parts of that talk, such as how to conceptualise the policy process and present conceptual insights to people who have no intention of deep dives into policy theory.

I often use the phrase ‘I’ve read it, so you don’t have to’ partly as a joke, but also to stress the importance of disciplinary synthesis when we engage in interdisciplinary (and inter-professional) discussion. If so, it is important to discuss how to produce such ‘synthetic’ accounts.

I tend to describe key components of a policymaking environment quickly: many policy makers and influencers spread across many levels and types of government, institutions, networks, socioeconomic factors and events, and ideas. However, each of these terms represents a shorthand to describe a large and diverse literature. For example, I can describe an ‘institution’ in a few sentences, but the study of institutions contains a variety of approaches.

Background post: I know my audience, but does my other audience know I know my audience?

Academic-practitioner discussions: improving the use of research evidence in policy

For Wellington B and Melbourne, the audience is an academic-practitioner mix. We discuss ways in which we can encourage the greater use of research evidence in policy, perhaps via closer collaboration between suppliers and users.

Discussions with scientists: why do policymakers ignore my evidence?

Sydney UNSW focuses more on researchers in scientific fields (often not in social science).  I frame the question in a way that often seems central to scientific researcher interest: why do policymakers seem to ignore my evidence, and what can I do about it?

Then, I tend to push back on the idea that the fault lies with politics and policymakers, to encourage researchers to think more about the policy process and how to engage effectively in it. If I’m trying to be annoying, I’ll suggest to a scientific audience that they see themselves as ‘rational’ and politicians as ‘irrational’. However, the more substantive discussion involves comparing (a) ‘how to make an impact’ advice drawn from the personal accounts of experienced individuals, giving advice to individuals, and (b) the sort of advice you might draw from policy theories which focus more on systems.

Background post: What can you do when policymakers ignore your evidence?

Early career researchers: the need to build ‘impact’ into career development

Canberra UNSW is more focused on early career researchers. I think this is the most difficult talk because I don’t rely on the same joke about my role: to turn up at the end of research projects to explain why they failed to have a non-academic impact.  Instead, my aim is to encourage intelligent discussion about situating the ‘how to’ advice for individual researchers into a wider discussion of policymaking systems.

Similarly, Brisbane A and B are about how to engage with practitioners, and communicate well to non-academic audiences, when most of your work and training is about something else entirely (such as learning about research methods and how to engage with the technical language of research).

Background posts:

What can you do when policymakers ignore your evidence? Tips from the ‘how to’ literature from the science community

What can you do when policymakers ignore your evidence? Encourage ‘knowledge management for policy’

See also:

1. A similar talk at LSHTM (powerpoint and audio)

Now available as a live recording (of the powerpoint and sound; the hand waving exists only in our memories and our hearts) https://t.co/UcK5IdVL0R https://t.co/tKFt0OcSYC

— Professor Paul Cairney (@CairneyPaul) November 21, 2018

2. European Health Forum Gastein 2018 ‘Policy in Evidence’ (from 6 minutes)

https://webcasting.streamdis.eu/Mediasite/Play/8143157d976146b4afd297897c68be5e1d?catalog=62e4886848394f339ff678a494afd77f21&playFrom=126439&autoStart=true

 

See also:

Evidence-based policymaking and the new policy sciences

 

Why don’t policymakers listen to your evidence?

Since 2016, my most common academic presentation to interdisciplinary scientist/ researcher audiences is a variant of the question, ‘why don’t policymakers listen to your evidence?’

I tend to provide three main answers.

1. Many policymakers have many different ideas about what counts as good evidence

Few policymakers know or care about the criteria developed by some scientists to describe a hierarchy of scientific evidence. For some scientists, at the top of this hierarchy is the randomised control trial (RCT) and the systematic review of RCTs, with expertise much further down the list, followed by practitioner experience and service user feedback near the bottom.

Yet, most policymakers – and many academics – prefer a wider range of sources of information, combining their own experience with information ranging from peer reviewed scientific evidence and the ‘grey’ literature, to public opinion and feedback from consultation.

While it may be possible to persuade some central government departments or agencies to privilege scientific evidence, they also pursue other key principles, such as to foster consensus driven policymaking or a shift from centralist to localist practices.

Consequently, they often only recommend interventions rather than impose one uniform evidence-based position. If local actors favour a different policy solution, we may find that the same type of evidence may have more or less effect in different parts of government.

2. Policymakers have to ignore almost all evidence and almost every decision taken in their name

Many scientists articulate the idea that policymakers and scientists should cooperate to use the best evidence to determine ‘what works’ in policy (in forums such as INGSA, European Commission, OECD). Their language is often reminiscent of 1950s discussions of the pursuit of ‘comprehensive rationality’ in policymaking.

The key difference is that EBPM is often described as an ideal by scientists, to be compared with the more disappointing processes they find when they engage in politics. In contrast, ‘comprehensive rationality’ is an ideal-type, used to describe what cannot happen, and the practical implications of that impossibility.

The ideal-type involves a core group of elected policymakers at the ‘top’, identifying their values or the problems they seek to solve, and translating their policies into action to maximise benefits to society, aided by neutral organisations gathering all the facts necessary to produce policy solutions. Yet, in practice, they are unable to: separate values from facts in any meaningful way; rank policy aims in a logical and consistent manner; gather information comprehensively, or possess the cognitive ability to process it.

Instead, Simon famously described policymakers addressing ‘bounded rationality’ by using ‘rules of thumb’ to limit their analysis and produce ‘good enough’ decisions. More recently, punctuated equilibrium theory uses bounded rationality to show that policymakers can only pay attention to a tiny proportion of their responsibilities, which limits their control of the many decisions made in their name.

More recent discussions focus on the ‘rational’ short cuts that policymakers use to identify good enough sources of information, combined with the ‘irrational’ ways in which they use their beliefs, emotions, habits, and familiarity with issues to identify policy problems and solutions (see this post on the meaning of ‘irrational’). Or, they explore how individuals communicate their narrow expertise within a system of which they have almost no knowledge. In each case, ‘most members of the system are not paying attention to most issues most of the time’.

This scarcity of attention helps explain, for example, why policymakers ignore most issues in the absence of a focusing event, policymaking organisations make searches for information which miss key elements routinely, and organisations fail to respond to events or changing circumstances proportionately.

In that context, attempts to describe a policy agenda focusing merely on ‘what works’ are based on misleading expectations. Rather, we can describe key parts of the policymaking environment – such as institutions, policy communities/ networks, or paradigms – as a reflection of the ways in which policymakers deal with their bounded rationality and lack of control of the policy process.

3. Policymakers do not control the policy process (in the way that a policy cycle suggests)

Scientists often appear to be drawn to the idea of a linear and orderly policy cycle with discrete stages – such as agenda setting, policy formulation, legitimation, implementation, evaluation, policy maintenance/ succession/ termination – because it offers a simple and appealing model which gives clear advice on how to engage.

Indeed, the stages approach began partly as a proposal to make the policy process more scientific and based on systematic policy analysis. It offers an idea of how policy should be made: elected policymakers in central government, aided by expert policy analysts, make and legitimise choices; skilful public servants carry them out; and, policy analysts assess the results with the aid of scientific evidence.

Yet, few policy theories describe this cycle as useful, while most – including the advocacy coalition framework , and the multiple streams approach – are based on a rejection of the explanatory value of orderly stages.

Policy theories also suggest that the cycle provides misleading practical advice: you will generally not find an orderly process with a clearly defined debate on problem definition, a single moment of authoritative choice, and a clear chance to use scientific evidence to evaluate policy before deciding whether or not to continue. Instead, the cycle exists as a story for policymakers to tell about their work, partly because it is consistent with the idea of elected policymakers being in charge and accountable.

Some scholars also question the appropriateness of a stages ideal, since it suggests that there should be a core group of policymakers making policy from the ‘top down’ and obliging others to carry out their aims, which does not leave room for, for example, the diffusion of power in multi-level systems, or the use of ‘localism’ to tailor policy to local needs and desires.

Now go to:

What can you do when policymakers ignore your evidence?

Further Reading

The politics of evidence-based policymaking

The politics of evidence-based policymaking: maximising the use of evidence in policy

Images of the policy process

How to communicate effectively with policymakers

Forthcoming special issue in Policy and Politics called ‘Practical lessons from policy theories’, which includes my discussion of how to be a ‘policy entrepreneur’.

What do we need to know about the politics of evidence-based policymaking?

Today, I’m helping to deliver a new course – Engaging Policymakers Training Programme – piloted by the Alliance for Useful Evidence and the UCL. Right now, it’s for UCL staff (and mostly early career researchers). My bit is about how we can better understand the policy process so that we can engage in it more effectively.  I have reproduced the brief guide below (for my two 2-hour sessions as part of a wider block). If anyone else is delivering something similar, please let me know. We could compare notes. 

This module will be delivered in two parts to combine theory and practice

Part 1: What do we need to know about the politics of evidence-based policymaking?

Policy theories provide a wealth of knowledge about the role of evidence in policymaking systems. They prompt us to understand and respond to two key dynamics:

1. Policymaker psychology. Policymakers combine rational and irrational shortcuts to gather information and make good enough decisions quickly. To appeal to rational shortcuts and minimise cognitive load, we reduce uncertainty by providing syntheses of the available evidence. To appeal to irrational shortcuts and engage emotional interest, we reduce ambiguity by telling stories or framing problems in specific ways.
2. Complex policymaking environments. These processes take place in the context of a policy environment out of the control of individual policymakers. Environments consist of: many actors in many levels and types of government; engaging with institutions and networks, each with their own informal and formal rules; responding to socioeconomic conditions and events; and, learning how to engage with dominant ideas or beliefs about the nature of the policy problem. In other words, there is no policy cycle or obvious stage in which to get involved.

In this seminar, we discuss how to respond effectively to these dynamics. We focus on unresolved issues:

1. Effective engagement with policymakers requires storytelling skills, but do we possess them?
2. It requires a combination of evidence and emotional appeals, but is it ethical to do more than describe the evidence?
3. The absence of a policy cycle, and presence of an ever-shifting context, requires us to engage for the long term, to form alliances, learn the rules, and build up trust in the messenger. However, do we have and how should we invest the time?

The format will be relatively informal. Cairney will begin by making some introductory points (not a powerpoint driven lecture) and encourage participants to relate the three questions to their research and engagement experience.

Gateway to further reading:

• Paul Cairney and Richard Kwiatkowski (2017) ‘How to communicate effectively with policymakers: combine insights from psychology and policy studies’, Palgrave Communications
• Paul Cairney and Kathryn Oliver (2017) ‘Evidence-based policymaking is not like evidence-based medicine, so how far should you go to bridge the divide between evidence and policy?’ Health Research Policy and Systems (HARPS), DOI: 10.1186/s12961-017-0192-x
• Paul Cairney, Kathryn Oliver, and Adam Wellstead (2016) ‘To Bridge the Divide between Evidence and Policy: Reduce Ambiguity as Much as Uncertainty’, Public Administration Review, Early View (forthcoming) DOI:10.1111/puar.12555 PDF

Part 2: How can we respond pragmatically and effectively to the politics of EBPM?

In this seminar, we move from abstract theory and general advice to concrete examples and specific strategies. Each participant should come prepared to speak about their research and present a theoretically informed policy analysis in 3 minutes (without the aid of powerpoint). Their analysis should address:

1. What policy problem does my research highlight?
2. What are the most technically and politically feasible solutions?
3. How should I engage in the policy process to highlight these problems and solutions?

After each presentation, each participant should be prepared to ask questions about the problem raised and the strategy to engage. Finally, to encourage learning, we will reflect on the memorability and impact of presentations.

• See: How to write theory-driven policy analysis

Powerpoint: Paul Cairney A4UE UCL 2017

How to write theory-driven policy analysis

Writing theory driven policy analysis 10.11.17

(or right click to download this lecture which accompanies my MPP)

Here is a guide to writing theory-driven policy analysis. Your aim is to identify a policy problem and solution, know your audience, and account for the complexity of policymaking.

At first, it may seem like daunting task to put together policy analysis and policy theory. On its own, policy analysis seems difficult but relatively straightforward: use evidence to identify and measure a policy problem, compare the merits of one or more solution, and make a recommendation on the steps to take us from policy to action.

However, policy process research tells us that people will engage emotionally with that evidence, and that policymakers operate in a complex system of which they have very limited knowledge and control.

So, how can we produce a policy analysis paper to which people will pay attention, and respond positively and effectively, under such circumstances? I focus on developing the critical analysis that will help you produce effective and feasible analysis. To do so, I show how policy analysis forms part of a collection of exercises to foster analysis informed by theory and reflection.

Aims of this document:

1. Describe the context. There are two fields of study – theory and analysis – which do not always speak to each other. Theory can inform analysis, but it is not always clear how. I show the payoff to theory-driven policy analysis and the difference between it and regular analysis. Note the two key factors that policy analysis should address: your audience will engage emotionally with your analysis, and the feasibility of your solutions depends on the complexity of the policy environment.
2. Describe how the coursework helps you combine policy theory and policy analysis. Policy analysis is one of four tasks. There is a reflection, to let you ‘show your work’; how your knowledge of policy theory guides your description of a problem and feasible solutions. The essay allows you to expand on theory, to describe how and why policy changes (and therefore what a realistic policy analysis would look like). The blogs encourage new communication skills. In one, you explore how you would expect a policy maker or influencer to sell the recommendations in your policy analysis. In another, you explain complex concepts to a non-academic audience.

Background notes.

I have written this document as if part of a book to be called Teaching Public Policy and co-authored with Dr Emily St Denny.

For that audience, I have two aims: (1) to persuade policy scholars-as-teachers to adopt this kind of coursework in their curriculum; and, (2) to show students how to complete it effectively.

If you prefer shorter advice, see Writing a policy paper and blog post and Writing an essay on politics, policymaking, and policy change.

If you are interested in more background reading, see: The New Policy Sciences (by Paul Cairney and Chris Weible) which describes the need to combine policy theory-driven research with policy analysis; and, Practical Lessons from Policy Theories which describes eight attempts by scholars to translate policy theory into lessons that can be used for policy analysis.

The theories make more sense if you have read the corresponding 1000 Words posts (based on Cairney, 2012). Some of the forthcoming text will look familiar if you read my blog because I am consolidating several individual posts into an overall discussion.

I’m not quite there yet (the chapter is a first draft, a bit scrappy at times, and longer than a chapter should be), so all comments welcome (in the comments bit).

Writing theory driven policy analysis 10.11.17

A 5-step strategy to make evidence count

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.

1. Imagine your hero presents to HM Treasury an evidence-based report concluding that a unitary UK state would be far more efficient than a union state guaranteeing Scottish devolution. The evidence is top quality and the reasoning is sound, but the research question is ridiculous. The result of political deliberation and electoral choice suggests that your hero is asking a research question that does not deserve to be funded in the current political climate. Your hero is a clown.
2. Imagine your hero presents to the Department of Health a report based on the systematic review of multiple randomised control trials. It recommends that you roll out an almost-identical early years or public health intervention across the whole country. We need high ‘fidelity’ to the model to ensure the correct ‘dosage’ and to measure its effect scientifically. The evidence is of the highest quality, but the research question is not quite right. The government has decided to devolve this responsibility to local public bodies and/ or encourage the co-production of public service design by local public bodies, communities, and service users. So, to focus narrowly on fidelity would be to ignore political choices (perhaps backed by different evidence) about how best to govern. If you don’t know the politics involved, you will ask the wrong questions or provide evidence with unclear relevance. Your hero is either a fool, naïve to the dynamics of governance, or a villain willing to ignore governance principles.        
3. Imagine two fundamentally different – but equally heroic – professions with their own ideas about evidence. One favours a hierarchy of evidence in which RCTs and their systematic review is at the top, and service user and practitioner feedback is near the bottom. The other rejects this hierarchy completely, identifying the unique, complex relationship between practitioner and service user which requires high discretion to make choices in situations that will differ each time. Trying to resolve a debate between them with reference to ‘the evidence’ makes no sense. This is about a conflict between two heroes with opposing beliefs and preferences that can only be resolved through compromise or political choice. This is, oh I don’t know, Batman v Superman, saved by Wonder Woman.
4. Imagine you want the evidence on hydraulic fracturing for shale oil and gas. We know that ‘the evidence’ follows the question: how much can we extract? How much revenue will it produce? Is it safe, from an engineering point of view? Is it safe, from a public health point of view? What will be its impact on climate change? What proportion of the public supports it? What proportion of the electorate supports it? Who will win and lose from the decision? It would be naïve to think that there is some kind of neutral way to produce an evidence-based analysis of such issues. The commissioning and integration of evidence has to be political. To pretend otherwise is a political strategy. Your hero may be another person’s villain.

Now, let’s use these scenarios to produce a 5-step way to ‘make evidence count’.

Step 1. Respect the positive role of politics

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:

• begin with a focus on why we need political systems to make authoritative choices between conflicting preferences, and take governance principles seriously, we can
• identify the demand for evidence in that context, then be more strategic and pragmatic about making evidence count, and
• be less dispirited about the outcome.

In other words, think about the positive and necessary role of democratic politics before bemoaning post-truth politics and policy-based-evidence-making.

Step 2. Reject simple models of evidence-based policymaking

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:

Discussing the challenges of evidence based policy including complexity of the landscape @OECD #evidence4gov pic.twitter.com/1yu3UIKKjO

— Rob Davies (@r0bdavies) June 26, 2017

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.

Step 3. Tell a simple story about your evidence

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.

Step 4.  Tailor your story to many audiences

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.

Step 5. Clarify and address key dilemmas with political choice, not evidence

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’.

If you prefer a 3-step take home message:

1. I think we use phrases like ‘impact’ and ‘make evidence count’ to reflect a vague and general worry about a decline in respect for evidence and experts. Certainly, when I go to large conferences of scientists, they usually tell a story about ‘post-truth’ politics.
2. Usually, these stories do not acknowledge the difference between two different explanations for an evidence-policy gap: (a) pathological policymaking and corrupt politicians, versus (b) complex policymaking and politicians having to make choices despite uncertainty.
3. To produce evidence with ‘impact’, and know how to ‘make evidence count’, we need to understand the policy process and the demand for evidence within it.

*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