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.
The IAD provides a language, and way of thinking, about the ways in which different institutions foster collective action. The language is so complicated that I have cheated by summarising key terms in this box (and describing polycentric governance in a different post) to stay within the 1000 words limit:
Governing the Commons
For me, the best way to understand the IAD is through the lens of Governing the Commons (and the research agenda it inspired), which explains how to rethink ‘tragedies of the commons’ and encourage better management of common pool resources (CPRs).
Ostrom rejects the uncritical use of rational choice games to conclude – too quickly – that disastrous collective action problems are inevitable unless we ‘privatize’ commons or secure major government intervention (which is tricky anyway when global problems require international cooperation). The tragedy of the commons presents a too-bleak view of humanity, in which it would be surprising to find cooperation even when the fate of the world is in human hands.
Alternatively, what if there is evidence that people often work collectively and effectively without major coercion? People are social beings who share information, build trust by becoming known as reliable and predictable, and come together to produce, monitor and enforce rules for the group’s benefit. They produce agreements with each other that could be enforced if necessary.
The IAD helps us analyse these cooperative arrangements. Ostrom describes 8 ‘design principles’ of enduring and effective CPR management shared by many real world examples:
These design principles help explain why some communities manage CPRs successfully. They allow users to share the same commitment and expect the long-term benefits to be worthwhile.
However, Ostrom stressed that there is no blueprint – no hard and fast rules – to CPR management. There are three particular complications:
Good management requires high trust to encourage norms of reciprocity. Trust is crucial to minimizing the costs of compliance monitoring and enforcement. Trust may develop when participants communicate regularly, share an understanding of their common interests, reciprocate each other’s cooperation, and have proven reliable in the past.
Design principles are important to developing trust and solidarity, but so are ‘evolutionary’ changes to behaviour. Actors have often learned about rule efficacy – to encourage cooperation and punish opportunism – through trial-and-error over a long period, beginning with simple, low-cost operational rules producing quick wins.
Institutions contain a large, complicated set of rules that serve many different purposes, and need to be understood and analysed in different ways.
Different purposes include:
We also need to analyse the relative costs and simplicity of different rules, and the rules about the other rules, including
By now, you may be thinking that the IAD – and analysis of resource management – is complicated. This is true, partly because each case study – of the physical conditions and social practices regarding resource management – is different in some way. We can use the IAD to compare experiences, but accept that a profoundly successful scheme in one context may fail miserably in another.
Simplicity versus complexity: the world is complex, but should our analysis follow suit?
Indeed, this is why we need to think about rational choice games and the IAD simultaneously, to understand the analytical trade-offs.
Game theory laboratory experiments – built on simple rules and relatively small numbers of parameters – produce parsimonious analysis and results that we can understand relatively easily.
We may reject simple games as unrealistic, but what if we take this criticism to its extreme?
IAD in-depth field studies embrace complexity to try to understand the key dimensions of each study’s context. When we put them all together, there are too many concepts, variables, global applications, and variations-by-context, to contain in a simple theory.
The IAD addresses this trade off by offering a language to help organize research, encouraging people to learn it then use it to apply many different theories to explain different parts of the whole picture.
In other words, it is OK to reject simple models as unrealistic, but to embrace real-world complexity may require a rather complicated language.
Policy Concepts in 1000 Words: Rational Choice and the IAD (the older post for the 1st edition)
Democratic governance is defined by the regular rotation of elected leaders. Amidst the churn, the civil service is expected to act as the repository of received wisdom about past policies, including assessments of what works and what doesn’t. The claim is that to avoid repeating the same mistakes we need to know what happened last time and what were the effects. Institutional memory is thus central to the pragmatic task of governing.
What is institutional memory? And, how is it different to policy learning?
Despite increasing recognition of the role that memory can or should play in the policy process, the concept has defied easy scholarly definition.
In the classic account, institutional memory is the sum total of files, procedures and knowledge held by an organisation. Christopher Pollitt, who has pioneered the study of institutional memory, refers to the accumulated knowledge and experience of staff, technical systems, including electronic databases and various kinds of paper records, the management system, and the norms and values of the organizational culture, when talking about institutional memory. In this view, which is based on the key principles of the new institutionalism, memory is essentially an archive.
The problem with this definition is that it is hard to distinguish the concept from policy learning (see also here). If policy learning is in part about increasing knowledge about policy, including correcting for past mistakes, then we could perhaps conceive of a continuum from learning to memory with an inflection point where one starts and the other stops. But, this is easier to imagine than it is to measure empirically. It also doesn’t acknowledge the forms memories take and the ways memories are contested, suppressed and actively forgotten.
In our recent contribution to this debate (see here and here) we define memories as ‘representations of the past’ that actors draw on to narrate what has been learned when developing and implementing policy. When these narratives are embedded in processes they become ‘institutionalised’. It is this emphasis on embedded narratives that distinguishes institutional memory from policy learning. Institutional memory may facilitate policy learning but equally some memories may prohibit genuine adaptation and innovation. As a result, while there is an obvious affinity between the two concepts it is imperative that they remain distinct avenues of inquiry. Policy learning has unequivocally positive connotations that are echoed in some conceptualisations of institutional memory (i.e. Pollitt). But, equally, memory (at least in a ‘static’ form) can be said to provide administrative agents with an advantage over political principals (think of the satirical Sir Humphrey of Yes Minister fame). The below table seeks to distinguish between these two conceptualisations of institutional memory:
Key debates: Is institutional memory declining?
The scholar who has done the most to advance our understanding of institutional memory in government is Christopher Pollitt. His main contention is that institutional memory has declined over recent decades due to: the high rotation of staff in the civil service, changes in IT systems which prevent proper archiving, regular organisational restructuring, rewarding management skills above all others, and adopting new management ‘fads’ that favour constant change as they become popular. This combination of factors has proven to be a perfect recipe for the loss of institutional memory within organisations. The result is a contempt for the past that leads to repeated policy failure.
We came to a different view. Our argument is that one of the key reasons why institutional memory is said to have declined is that it has been conceptualised in a ‘static’ manner more in keeping with an older way of doing government. This practice has assumed that knowledge on a given topic is held centrally (by government departments) and can be made explicit for the purpose of archiving. But, if government doesn’t actually work this way (see relevant posts on networks here) then we shouldn’t expect it to remember this way either. Instead of static repositories of summative documents holding a singular ‘objective’ memory, we propose a more ‘dynamic’ people-centred conceptualisation that sees institutional memory as a composite of intersubjective memories open to change. This draws to the fore the role of actors as crucial interpreters of memory, combining the documentary record with their own perspectives to create a story about the past. In this view, institutional memory has not declined, it is simply being captured in a fundamentally different way.
Key debates: How can an institution improve how it remembers?
How an institution might improve its memory is intrinsically linked to how memory is defined and whether or not it is actually in decline. If we follow Pollitt’s view that memory is about the archive of accumulated knowledge that is being ignored or deliberately dismantled by managerialism then the answer involves returning to an older way of doing government that placed a higher value on experience. By putting a higher value on the past as a resource institutions would reduce staff turnover, stop regular restructures and changes in IT systems, etc. For those of us who work in an institution where restructuring and IT changes are the norm, this solution has obvious attractions. But, would it actually improve memory? Or would it simply make it easier to preserve the status quo (a process that involves actively forgetting disruptive but generative innovations)?
Our definition, relying as it does on a more dynamic conceptualisation of memory, is sceptical about the need to improve practices of remembering. But, if an institution did want to remember better we would favour increasing the opportunity for actors within an institution to reflect on and narrate the past. One example of this might be a ‘Wikipedia’ model of memory in which the story of a policy, it success and failure, is constructed by those involved, highlighting points of consensus and conjecture.
Corbett J, Grube D, Lovell H, Scott R. “Singular memory or institutional memories? Toward a dynamic approach”. Governance. 2018;00:1–19. https://doi.org/10.1111/gove.12340
Pollitt, C. 2009. “Bureaucracies Remember, Post‐Bureaucratic Organizations Forget?” Public Administration 87 (2): 198-218.
Pollitt, C. 2000. “Institutional Amnesia: A Paradox of the ‘Information Age’?” Prometheus 18 (1): 5-16.
This is a post for my talk at the ‘Politheor: European Policy Network’ event Write For Impact: Training In Op-Ed Writing For Policy Advocacy. There are other speakers with more experience of, and advice on, ‘op-ed’ writing. My aim is to describe key aspects of politics and policymaking to help the audience learn why they should write op-eds in a particular way for particular audiences.
A key rule in writing is to ‘know your audience’, but it’s easier said than done if you seek many sympathetic audiences in many parts of a complex policy process. Two simple rules should help make this process somewhat clearer:
We can use the same broad concepts to help explain both processes, in which many policymakers and influencers interact across many levels and types of government to produce what we call ‘policy’:
Policymakers receive too much information, and seek ways to ignore most of it while making decisions. To do so, they use ‘rational’ and ‘irrational’ means: selecting a limited number of regular sources of information, and relying on emotion, gut instinct, habit, and familiarity with information. In other words, your audience combines cognition and emotion to deal with information, and they can ignore information for long periods then quickly shift their attention towards it, even if that information has not really changed.
Consequently, an op-ed focusing solely ‘the facts’ can be relatively ineffective compared to an evidence-informed story, perhaps with a notional setting, plot, hero, and moral. Your aim shifts from providing more and more evidence to reduce uncertainty about a problem, to providing a persuasive reason to reduce ambiguity. Ambiguity relates to the fact that policymakers can understand a policy problem in many different ways – such as tobacco as an economic good, issue of civil liberties, or public health epidemic – but often pay exclusive attention to one.
So, your aim may be to influence the simple ways in which people understand the world, to influence their demand for more information. An emotional appeal can transform a factual case, but only if you know how people engage emotionally with information. Sometimes, the same story can succeed with one audience but fail with another.
Institutions are the rules people use in policymaking, including the formal, written down, and well understood rules setting out who is responsible for certain issues, and the informal, unwritten, and unclear rules informing action. The rules used by policymakers can help define the nature of a policy problem, who is best placed to solve it, who should be consulted routinely, and who can safely be ignored. These rules can endure for long periods and become like habits, particularly if policymakers pay little attention to a problem or why they define it in a particular way.
Such informal rules, about how to understand a problem and who to speak with about it, can be reinforced in networks of policymakers and influencers.
‘Policy community’ partly describes a sense that most policymaking is processed out of the public spotlight, often despite minimal high level policymaker interest. Senior policymakers delegate responsibility for policymaking to bureaucrats, who seek information and advice from groups. Groups exchange information for access to, and potential influence within, government, and policymakers have ‘standard operating procedures’ that favour particular sources of evidence and some participants over others
‘Policy community’ also describes a sense that the network seems fairly stable, built on high levels of trust between participants, based on factors such as reliability (the participant was a good source of information, and did not complain too much in public about decisions), a common aim or shared understanding of the problem, or the sense that influencers represent important groups.
So, the same policy case can have a greater impact if told by a well trusted actor in a policy community. Or, that community member may use networks to build key coalitions behind a case, use information from the network to understand which cases will have most impact, or know which audiences to seek.
This use of networks relates partly to learning the language of policy debate in particular ‘venues’, to learn what makes a convincing case. This language partly reflects a well-established ‘world view’ or the ‘core beliefs’ shared by participants. For example, a very specific ‘evidence-based’ language is used frequently in public health, while treasury departments look for some recognition of ‘value for money’ (according to a particular understanding of how you determine VFM). So, knowing your audience is knowing the terms of debate that are often so central to their worldview that they take them for granted and, in contrast, the forms of argument that are more difficult to pursue because they are challenging or unfamiliar to some audiences. Imagine a case that challenges completely someone’s world view, or one which is entirely consistent with it.
Some worldviews can be shattered by external events or crises, but this is a rare occurrence. It may be possible to generate a sense of crisis with reference to socioeconomic changes or events, but people will interpret these developments through the ‘lens’ of their own beliefs. In some cases, events seem impossible to ignore but we may not agree on their implications for action. In others, an external event only matters if policymakers pay attention to them. Indeed, we began this discussion with the insight that policymakers have to ignore almost all such information available to them.
Know your audience revisited: practical lessons from policy theories
To take into account all of these factors, while trying to make a very short and persuasive case, may seem impossible. Instead, we might pick up some basic rules of thumb from particular theories or approaches. We can discuss a few examples from ongoing work on ‘practical lessons from policy theories’.
Storytelling for policy impact
If you are telling a story with a setting, plot, hero, and moral, it may be more effective to focus on a hero than villain. More importantly, imagine two contrasting audiences: one is moved by your personal and story told to highlight some structural barriers to the wellbeing of key populations; another is unmoved, judges that person harshly, and thinks they would have done better in their shoes (perhaps they prefer to build policy on stereotypes of target populations). ‘Knowing your audience’ may involve some trial-and-error to determine which stories work under which circumstances.
Appealing to coalitions
Or, you may decide that it is impossible to write anything to appeal to all relevant audiences. Instead, you might tailor it to one, to reinforce its beliefs and encourage people to act. The ‘advocacy coalition framework’ describes such activities as routine: people go into politics to translate their beliefs into policy, they interpret the world through those beliefs, and they romanticise their own cause while demonising their opponents. If so, would a bland op-ed have much effect on any audience?
Learning from entrepreneurs
‘Policy entrepreneurs’ draw on three rules, two of which seem counterintuitive:
It all adds up to one simple piece of advice – timing and luck matters when making a policy case – but policy entrepreneurs know how to influence timing and help create their own luck.
On the day, we can use such concepts to help us think through the factors that you might think about while writing op-eds, even though it is very unlikely that you would mention them in your written work.
‘Rational choice theory’ is easy to caricature and dismiss, but difficult to define and describe, because it refers to a very broad and diverse body of work. So, we can identify some broad features but recognise that some studies display them more than others:
We can also identify two main types. The first is the abstract work which often involves building models or creating discussions based on openly unrealistic assumptions – for example, people have perfect information and judgement; they can act ‘optimally’ when faced with any situation.
‘Optimally’ is potentially misleading, since it refers to an ability to fulfil their individual preferences, by ranking them in order and being able to fulfil them. It does not necessarily refer to an optimal overall outcome, because things get complicated when many individuals, each seeking to fulfil their preferences, interact. We should also note that ‘rational’ refers to the ability to reason and act on reason (crucially, we do not have to assume that rational beings are selfish beings).
The second type involves more detailed and/ or realistic assumptions regarding the preferences of individuals and how they relate to specific institutional settings. In this case, the aim is to help explain outcomes.
The first type of work is a logical exercise, to help think through problems and often produce ‘paradoxical results’. Famous examples include:
The identification of such ‘collective action problems’ prompts us to consider the role of government and public policy in solving them. For example, we may identify ‘public goods’ to justify the role of the state as a supplement to, or replacement for, the market. Public goods are ‘non-excludable’ (no-one can be excluded from enjoying their benefits) and ‘non-rival’ (their use by one person does not diminish their value to another). Common examples, based on the argument that the state must intervene when the market would fail, regard national defence (the government should tax its citizens and businesses and provide national security) and clean air (the government should use a range of policy instruments to discourage pollution or encourage non-pollution).
In turn, the role of the state, or its institutions, can be analysed in the same rational choicey way, perhaps divided into three types of question:
Indeed, rational choice presents us with a way in which to justify a role for government, or to argue for a minimal role for the state, in favour of the market.
The work of Elinor Ostrom and colleagues presents a third option. Ostrom’s work demonstrates the potential for non-market solutions to collective action problems based on a combination of trust and less impositional means (than government institutions), to minimize the costs of monitoring and enforcing collective agreements. This approach involves individuals seeking agreements with each other that could be enshrined in a set of meaningful rules (which is what we now think of as an institution). The rules may be enforced by a private rather than state authority – the ‘commons’ would remain common and actors would observe each other’s behaviour and report rule-breaking to the third party that everyone pays for and agrees to respect. For Ostrom, the theoretical aim was to identify the conditions that have to be met for some groups to organize themselves to solve a collective action problem without state coercion, while the empirical aim was to identify concrete examples of this process. This approach has proved to be influential, winning Ostrom the Nobel Prize for economics in 2009 and demonstrating the direct policy relevance of institutional rational choice analysis (see the Institutional Analysis and Development Framework, IAD).
*here is how that section appears in the book (without the Harvard referencing removed).