Policy-Making as Designing: The Added Value of Design Thinking for Public Administration and Public Policy 9781447365952

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New Perspectives in Policy & Politics Edited by Sarah Ayres, Steve Martin and Felicity Matthews

Policy-Making as Designing The Added Value of Design Thinking for Public Administration and Public Policy Edited by Arwin van Buuren, Jenny M. Lewis and B. Guy Peters

New Perspectives in Policy & Politics Edited by Sarah Ayres, Steve Martin and Felicity Matthews

POLICY-​MAKING AS DESIGNING The Added Value of Design Thinking for Public Administration and Public Policy Edited by Arwin van Buuren, Jenny M. Lewis and B. Guy Peters

First published in Great Britain in 2023 by Policy Press, an imprint of Bristol University Press University of Bristol 1–​9 Old Park Hill Bristol BS2 8BB UK t: +​44 (0)117 374 6645 e: bup-​[email protected] Details of international sales and distribution partners are available at policy.bristoluniversitypress.co.uk © Bristol University Press 2023 British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library ISBN 978-1-4473-6593-8 hardcover ISBN 978-1-4473-6594-5 ePub ISBN 978-1-4473-6595-2 ePdf The right of Arwin van Buuren, Jenny M. Lewis and B. Guy Peters to be identified as editors of this work has been asserted by them in accordance with the Copyright, Designs and Patents Act 1988. All rights reserved: no part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise without the prior permission of Bristol University Press. Every reasonable effort has been made to obtain permission to reproduce copyrighted material. If, however, anyone knows of an oversight, please contact the publisher. The statements and opinions contained within this publication are solely those of the editors and contributors and not of the University of Bristol or Bristol University Press. The University of Bristol and Bristol University Press disclaim responsibility for any injury to persons or property resulting from any material published in this publication. Bristol University Press and Policy Press work to counter discrimination on grounds of gender, race, disability, age and sexuality. Cover design: Dave Worth Front cover image: Stocksy #3754272 [The Laundry Room] Bristol University Press and Policy Press use environmentally responsible print partners. Printed and bound in Great Britain by CPI Group (UK) Ltd, Croydon, CR0 4YY

Contents List of figures and tables Notes on contributors

v vii

1

Improving public policy and administration: exploring the potential of design Arwin van Buuren, Jenny M. Lewis, B. Guy Peters and William Voorberg

2

Applying design in public administration: a literature review to explore the state of the art Margot Hermus, Arwin van Buuren and Victor Bekkers

18

3

Challenges in applying design thinking to public policy: dealing with the varieties of policy formulation and their vicissitudes Michael Howlett

51

4

Designing environments for experimentation, learning and innovation in public policy and governance Maurits Waardenburg, Martijn Groenleer and Jorrit De Jong

72

5

Policy Labs: the next frontier of policy design and evaluation? Karol Olejniczak, Sylwia Borkowska-​Waszak, Anna Domaradzka and Yaerin Park

98

6

When design meets power: design thinking, public sector innovation and the politics of policy-making Jenny M. Lewis, Michael McGann and Emma Blomkamp

125

7

Designing institutions for designing policy B. Guy Peters

151

8

Applying design science in public policy and administration research A. Georges L. Romme and Albert Meijer

171

9

Using a design approach to create collaborative governance John M. Bryson, Barbara Crosby and Danbi Seo

191

iii

1

Policy-Making as Designing

10

Policy-​making as designing: taking stock and looking forward Arwin van Buuren, Jenny M. Lewis and B. Guy Peters

Index

218

230

iv

List of figures and tables Figures 2.1 2.2 5.1 6.1 6.2 6.3 6.4 8.1

Flowchart of article selection Amount of publications per year REACT –​generic design process in policy labs Methods used ‘quite’ or ‘very frequently’ by PSI labs (%) Public sector design levels that PSI labs quite or very frequently engage in (%) Stages of the innovation cycle that PSI labs quite or very frequently work at (%) Where projects originate from (non-​government PSI labs) The iterative and complementary nature of creating, assessing, theorising and justifying activity in PPA research

24 25 113 137 139 140 142 175

Tables 1.1 2.1 2.2 2.3 A.3.1 A.3.2 A.3.3 A.3.4 4.1 4.2 5.1 5.2 5.3 6.1 6.2 7.1 A.9.1 A.9.2 A.9.3

Three design approaches in public administration Type of solution and level of (intended) implementation (%) Stakeholders: types and level of involvement Different approaches to design in public administration Design problems ordered by domain Design goals and their frequency Implementation status of designs Design methods mentioned in included articles Examples of collaborations in the OCFL (Organised Crime Field Lab) Evolution of the OCFL (Organised Crime Field Lab) as design environment (2014–​2018) Policy labs worldwide Summary of selected case studies Methods and tools used by policy labs Three approaches to policy Profile of lab participants Institutions and designing Policies for minority-​owned businesses in Minnesota Development of collaborative governance: forums, arenas, and courts in the early stage, 2014–​2015 Development of collaborative governance: forums, arenas, and courts in the intermediate (Cohort) stage, 2016–​mid-​2017

v

10 27 31 32 44 44 44 45 84 87 105 107 114 132 136 157 211 212 213

Policy-Making as Designing

9.4 10.1 10.2

Development of collaborative governance: forums, arenas, and courts in the later (Synergy) stage, mid-​2017–​mid-​2018 The potentials of designerly approaches for policy-​making Conjectures between modes of design in policy-​making

vi

214 219 223

Notes on contributors Victor Bekkers is Full Professor of Public Administration at Erasmus University Rotterdam, Netherlands. Emma Blomkamp is Founder of CoDesignCo, Australia, and Honorary Fellow at the University of Melbourne. Sylwia Borkowska-Waszak is a PhD student at the University of Strathclyde, UK. John M. Bryson is McKnight Presidential Professor Emeritus at the University of Minnesota Twin Cities, USA. Arwin van Buuren is Full Professor of Public Administration at Erasmus University Rotterdam, Netherlands. Barbara Crosby is Associate Professor Emerita at the University of Minnesota Twin Cities, USA. Anna Domaradzka is Assistant Professor at the University of Warsaw, Poland. Martijn Groenleer is Professor of Public Governance at Tilburg University, Netherlands. Margot Hermus is a former PhD student at Erasmus University Rotterdam, Netherlands. Michael Howlett is Canada Research Chair (Tier 1) and Burnaby Mountain Professor at Simon Fraser University, Canada. Jorrit De Jong is Emma Bloomberg Senior Lecturer in Public Policy and Management at Harvard Kennedy School, USA. Jenny M. Lewis is Professor of Public Policy at the University of Melbourne, Australia. Michael McGann is Lecturer in Political Science at the University of Melbourne, Australia.

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Albert Meijer is Full Professor of Public Innovation at Utrecht University, Netherlands. Karol Olejniczak is Associate Professor of Public Policy at SWPS University, Poland. Yaerin Park is Visiting Researcher Fellow at George Mason University, Korea. B. Guy Peters is Maurice Falk Professor of American Government at the University of Pittsburgh, USA. A. Georges L. Romme is Professor of Entrepreneurship and Innovation at Eindhoven University of Technology, Netherlands. Danbi Seo is Assistant Professor at Arizona State University, USA. William Voorberg is Postdoctoral Researcher at Leiden University, Netherlands. Maurits Waardenburg is a PhD student at Tilburg University, Netherlands.

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Improving public policy and administration: exploring the potential of design Arwin van Buuren, Jenny M. Lewis, B. Guy Peters and William Voorberg

Introduction Governments see themselves as increasingly confronted with complex or wicked problems (such as climate change and migration). Characteristic for such issues is that many different stakeholders are involved, with different ambitions, interests and perceptions. A solution for one actor may imply an increase in problems for others (Head, 2008). At the same time, citizens’ expectations of public services have increased (Armstrong et al, 2014; Kimbell, 2016; Bailey and Lloyd, 2017; Bason, 2017). In this context, design approaches are seen as a promising way to provide smarter and more agile ways to empathise with these actors and their problems, and to find mutually beneficial opportunities and solutions (Armstrong et al, 2014; Bason, 2016; Mintrom and Luetjens, 2016). At the same time, thinking about design for public issues is far from new. Some 50 years ago, Herbert Simon already called public administration (PA) a design science. That implies, in the view of Simon, that this field is different from the natural sciences since it studies the artificial –​or human made –​instead of the natural and, as such, deals with the contingent instead of the necessary –​with how things might be instead of with how things are. Design ‘is concerned with how things ought to be, with devising artefacts to attain goals’ (Simon, 1969: 133). In Simon’s view, the core of designing is the ability to deal with situations as one encounters them by both diagnosing the problem and devising a way to deal with it. Whether that solution is the design of a material artefact, a treatment plan for a sick patient or a social welfare policy does not really matter. The idea of PA as a design science has since then been underlined by several scholars in the field (for example, Shangraw and Crow, 1989; Frederickson, 2000; Meier, 2005; Walker, 2011). However, it seems that the current attention on design and design methods aligns with a different approach to Simon’s. Recent applications of design methods involve the use of design or policy labs, design charrettes and 1

Policy-Making as Designing

other experimental and exploratory approaches. This suggests the rise of a new set of methods and organisations that potentially have impacts on policy-​making processes. That is, more human-​or user-​centered (instead of problem-​centered) approaches, and an openness to inquiry and creativity, are not always part of more traditional understandings of policy design. Design thinking can help develop new options, focusing on outcomes instead of solutions, providing room for experimenting, and recognising and exercising a new type of distributed (instead of hierarchical) authority (Christiansen and Bunt, 2014; Kimbell, 2016). Arriving at this point, two questions emerge. On the one hand, the rise of new, more designerly approaches to policy design raise questions about the similarities and differences between these and more traditional conceptualisations of design in PA and the possible evolution we can witness in thinking about PA as a design science. Furthermore, focusing on the potential of such designerly approaches, one could ask to what extent PA as a field can benefit from the application of design methods and principles. Applying design (as the design thinking literature refers to it) to policy-​making and service delivery also raises serious questions about the applicability of these design methods, which are mostly derived from industrial and product design. Moreover, it raises serious dilemmas when it comes to typical PA values, such as accountability, legal certainty and predictability (Considine et al, 2009; Hillgren et al, 2011; Gascó, 2017). This volume addresses these issues. We try to clarify these dilemmas and difficulties, in order to bring the debate on design for policy and PA to a higher level. Too often, we witness a rather uncritical appraisal of design and design thinking without serious attention directed at understanding its limitations and side effects. Moreover, there appears to be a rather deep chasm between the more traditional and more contemporary design approaches in the field, while the opportunities for cross-​fertilisation are not explored let alone utilised. Until now, systematic empirical attention for the new design approach in PA is lacking. The same holds true for a critical reflection on the question of whether a more designerly way of thinking (Cross, 2011) can help to improve PA and public policy. We therefore need a better understanding of the different applications of design in the fields of public policy and PA, how they relate to each other and their implications, in order to say something substantiated about the potential contribution of the present-​day design orientation to PA. In this introductory chapter we elaborate in the next two sections on how the design orientation in the study of PA and public policy manifested itself over the last decades. In the fourth section, we elaborate on what characterises the current attention for design in PA and public policy and how we can explain this attention. Subsequently, in the fifth section we argue that we can distinguish three ideal-​types of design approaches that 2

Improving public policy and administration

are now simultaneously present in PA and public policy. We examine how these types are similar or different in terms of logic, methods and motives. In the sixth section, we explain how we can explain and understand this proliferation of different design perspectives in PA and public policy. In the seventh section, we introduce the contributions to this edited volume and assess how they can be considered illustrations of one or more of the ideal-​ types that were identified in the fifth section. In the final section, having a more elaborate understanding of these three ideal-​types, generated from the contributions in this volume, we draw some conclusions on the promises of design for PA and public policy.

Public administration: a design science Without doubt, Herbert Simon is the main point of reference when it comes to the idea of PA as a design science. In his seminal work, The sciences of the artificial (1969), he elaborated on this idea. Based upon his idea of bounded rationality, Simon focused on all kinds of systematic decision support systems to enhance the search for optimal design solutions. Other scholars, like Trudi Miller (1984), Lawrence Radine (1987) and Vincent Ostrom (1974), also contributed to the idea of PA as a design science. In his article on the intellectual crisis in American PA, Ostrom stated: ‘An appropriate theory of design is necessary both to understand how a system will work and how modifications or changes in a system will affect its performance’ (1974: 102). In line with the approach taken by Simon, others have also argued for further developing the field of PA as a design discipline (Keiser and Meier, 1996). However, their plea mainly ends in an argument for using more sophisticated methods for analysing data in order to facilitate the step to prescription. This is quite a dominant logic in publications that focus upon PA as a design science. Most of this literature problematises this volume but does not present convincing illustrations of designs based upon in-​depth PA knowledge and it is rarely accomplished with the help of a clear and transparent design methodology. Another main line of argument has been fuelled by studies that apply experimental research logics. Doing experiments (testing interventions) is said to result in usable knowledge which fits into the ambition of the discipline being a design science (Walker, 2011; Jilke et al, 2016). The rise of what is called ‘behavioral PA’ has contributed strongly to this line of thinking: testing specific interventions with the help of field or survey experiments can help PA to influence citizens’ choice architecture (Grimmelikhuijsen et al, 2017). The issue of ‘PA as a design science’ is thus regularly raised by scholars in the field, but at the moment the most dominant idea is to achieve this by looking for more rigorous experimental research approaches, drawn from 3

Policy-Making as Designing

the natural sciences. We thus begin from a starting point that the traditional view of PA as a design science is strongly dominated by an informational approach to design (Chapter 2, this volume).

Public policy: a design science Simon’s concern with design also influenced the study of public policy (‘a course of action, adopted or proposed by a government, party, business, or individual’, as defined by the Australian Concise Oxford Dictionary), and one could argue that his interest in design in PA was driven by a desire to design better public policies. And even before Simon’s contributions, Harold Lasswell’s discussions of decision-​making (1956) and the policy sciences (1951) were directed at finding mechanisms for improving the design of public interventions into the economy and society. As the design approach grew in public policy, however, it was less based on bounded rationality and had more of a technocratic approach. The assumption of a first wave of analysis (that is, first after Simon and Lasswell) was that the goal of design should be to develop mechanisms or algorithms that would produce clear and usable answers for the policy designer. Beginning with John Dryzek (1983; see also Bobrow and Dryzek, 1987) and then continuing through Linder and Peters (1984; 1991) this approach was seen to be excessively optimistic about the capacity to produce viable policy designs, given some of the political pitfalls that might arise in designing. Policy instruments were one of the elements included in the algorithms of the first wave of design. A second wave of thinking about policy design focused almost exclusively on the design and selection of instruments (Howlett, 2010; Howlett and Lejano, 2013). While this literature did develop the analysis of policy instruments far beyond the initial work by Christopher Hood (2007) and others, it still appears to have been quite narrow in focus, especially because it tended to ignore issues such as problem structuring and evaluation in the design process. Although perhaps more attuned to political constraints than some of the earlier literature on policy design, much of the approach based on instruments still assumed a capacity for experts and analysts to develop the correct answers for policy problems and to be able to implement those answers with relative ease. Updated for the digital age (Hood and Margetts, 2007), to expand the focus on how government gets information, these contributions provide high-​level accounts of design for policy, based on the detectors and effectors that governments use to steer states. The design orientation is thus strongly manifest in the literature on policy design. In this literature, the central question is how policies (and the way in which they are accomplished) can be designed in such a way 4

Improving public policy and administration

that they effectively solve the issues they are meant to act upon. Whenever governments make policy, alone or in conjunction with their partners in the private sector, some form of policy formulation is involved (Jordan and Turnpenny, 2015). That formulation may be relatively unconscious, simply treading the same paths that have been used in the past, as the historical institutionalists would argue. Or the formulation may be a more conscious process of designing policy (Turnbull, 2018). Such a design process will involve developing a policy that is related to the understanding of the policy problem, an explicit set of goals and values, and the strategies for implementing the policy. Processes of policy design and formulation have often been performed within government itself, often by the public bureaucracy, and perhaps by legislatures. However, policy design efforts have also involved expertise from outside the public sector, whether from think tanks, universities or private consultants. In contemporary times, designing has been opened even further to include stakeholders from the private sector and citizens.

‘Designerly’ approaches in public administration and public policy It seems nowadays that approaches to design for policy and PA have turned a corner. Many governments are experimenting with design labs and are applying design methods or design thinking to their primary processes of policy-​making, service delivery and decision-​making. This new use of ‘design’ is characterised by a process of creativity and participation. The latter implies that more ideas from different sources are included. This can be labelled as design for policy. In this process, design is considered a way to better understand and structure a policy problem, rather than finding solutions for predefined goals (Hoppe, 2018). While much of the earlier literature sought to eliminate options quickly in order to settle on the apparent best solution, design thinking approaches to policy design have attempted to include a wider variety of actors in the policy process and create a wider range of possible solutions. This new approach of design finds fertile ground in contemporary governance approaches, in which collaboration is sought with civil society to come up with solutions for contemporary problems, by organising processes of co-​creation and social innovation (Considine and Lewis, 2003; Ansell and Gash, 2007; Hartley et al, 2013). As such, design becomes by definition a process of co-​design. Co-​design is considered an interesting way to organise such a process (Bovaird and Loeffler, 2012; Farr, 2013). This coincides with a change in the field of industrial design, as designers have sought to evolve design into a framework for solving social problems through actively engaging with those affected (Torjman, 2012). Transferred to the public 5

Policy-Making as Designing

domain, the focus on end-​users is present in the New Public Management paradigm, pushing the desires and wishes of end-​users (as clients asking for value-​for-​money) to the fore. It is even more apparent in the current collaborative approaches, where end-​users are considered to be co-​creators or co-​producers of public policy and services (Rhodes, 1996; Considine and Lewis, 2003; Torfing et al, 2012), thereby striving for legitimate policy and/​or public service, rather than effective policy and services. These kind of design approaches provide methods to redesign policies, services and goods based upon the perspectives, needs and experiences of the end-​users. The underlying assumption is that such an inclusive approach may increase the satisfaction of the end-​users and their appreciation of public policy actions. This is in line with new (network) modes of governance that sit in contrast to hierarchical or market-​driven means of coordinating. While there is a significant difference between tokenistic consultation and genuine end-user engagement, it is clear that a focus on collaboration and the involvement of users has contributed to the growth of design approaches. Such a perception of design is thus clearly distinct from the (boundedly) rational and deductive idea of policy design, that is, design of policy (as described in the section on ‘Public policy: a design science’, which sits easily with Simon and is about devising policies that will address a particular set of goals). In that conception, the design of public policy is considered a set of sequential steps that begins with a problem and results in a solution to that problem. As such, it is based on the ubiquitous policy cycle (first proposed by Laswell in 1956). The set of steps that unfold in between in this model (agenda-​setting, policy formulation, decision-​making, implementation and evaluation) have been roundly criticised, but still provide a useful heuristic framework and a means for structuring what is a vast field (Jann and Wegrich, 2007). One major break that design for policy represents from a ‘traditional’ policy process (design of policy) is the breadth of the search in identifying problems and solutions. A second break is the focus on empathy, rather than rationality and/​or political considerations, in addressing policy problems. A third is the inclusion of all those affected by a particular problem in working towards understanding how to define it in order to address it. A fourth is a focus on the idea of working with provisional ideas (following the logic of abduction), resulting in a search to find ways to approach policy-​making as a process of (rapid) prototyping (Kimbell and Bailey, 2017). These differences with more traditional approaches of policy design, as conceived by those who are seeking value-​maximising solutions, even when they recognise the bounded nature of this, bring with them a different set of principles, approaches and methods for arriving at solutions. The design approach begins with empathy rather than a dispassionate rationality as a fundamental principle for policy-​ making. It applies human-​centred design as an overarching approach, which 6

Improving public policy and administration

uses creative principles and works on the needs, contexts, behaviours and emotions of those who are affected in order to design solutions that serve their needs. As such, the design process can be considered as important as what is being designed (output). The techniques employed include rapid prototyping and trial-​and-​error, agility and sprints, and a range of methods that seek to generate ‘outside the box’ ideas. The question arises how we can explain the (renewed) attention for design in PA and public policy. We discern two important arguments given by scholars in the field. First, many of them stress the fact that design fits well the complexity of many public issues. It is a common notion in the design sciences that traditional scientific research (inductive or deductive) is suitable to ‘tame’ or ‘determinate’ issues, but that wicked issues require methods that enable abduction (intelligent speculation, probability reasoning), trial-​and-​ error and an iterative exploration of the ‘problem space’ and the ‘solution space’ (Dorst and Cross, 2001; Dorst, 2006; Wylant, 2010). Turnbull (2018) argues, in that regard, that for policy-​makers, policy design offers an orientation that supposes a possibility to consider public policy that can be designed in terms of ends and means. The ‘double diamond’ created by the Stanford Design School has been replicated (and modified) many times and is now widely used as a basis for all sorts of trail design approaches. At its core is the notion of two motions of opening up (divergence) followed by narrowing down (convergence) –​first in relation to the problem and then in relation to the solution. The four steps of discover, design, develop and deliver are close to ubiquitous in design thinking, and have spread rapidly by means of public innovation units and policy labs with a commitment to this new means of tackling problems. These have strong international networks (McGann et al, 2018b) and a process of transferring ideas between them is apparent in studies of public sector innovation units (Tõnurist et al, 2017). Second, the increased attention for design can be attributed to the fact that there is an increased focus on innovation and learning in the public sector. The multiple challenges that have faced governments at all levels over the last few decades, and especially following the last global financial crisis and the introduction of new austerity measures in many nations, have often been seen as requiring innovative approaches. This has moved innovation to centre stage in the public sector, taking it well beyond its beginnings as an evolutionary economics concept of ‘creative destruction’ following Schumpeter (1949) and applied only to the development of new products for greater profits. Innovation in a public sector context has caught the attention of governments seeking to address intractable problems with fewer resources, while faced by an increasingly sceptical and demanding populace (Lewis et al, 2017). The rise of the idea of innovation inside government, rather than government merely supporting innovation by the private sector (Considine et al, 2009), and a more recent focus on the innovation capacity 7

Policy-Making as Designing

of public sector organisations (Lewis et al, 2017), can be seen around the world. Governments routinely award public sector innovation prizes in many countries. The European Commission has been prioritising research grants on public sector innovation (or social innovation) for some years now, which has resulted in comparative research on the topic across its member states. It has also created the Innobarometer to map and rank member states. Others have created innovative city indices and the smart city movement has taken off around the world. In line with these broad trends, there seems to be a growing willingness to explore new methods, tools and approaches and to test them in a rather pragmatic and iterative way. This is accompanied by a call for greater tolerance for making mistakes and learning from them, in the safe space afforded by a pilot, a (living, urban or field) lab environment or a policy experiment.

Coining design approaches in public administration and public policy In the current design discourse in the field of PA and public policy, we can at least discern three different design approaches. The most influential design approach in PA, in line with the work of Simon, arises from a rational design perspective, or design as optimisation. These contributions sit easily with a formal design methodology, based upon expertise, objectivity and rationality. In that logic, design is a matter of search and discovery: it is about developing systematic search approaches that help to simplify or even solve complex problems (Alexander and Orbach, 1982). In the contribution of Hermus et al (Chapter 2, this volume), this is called the informational approach of design, which covers the vast majority of design-​oriented studies in the field. These approaches can either be highly expert-​driven (without any room for users or stakeholders to influence the design process), or there can also be room for various levels of consultation with stakeholders who provide input or feedback on a scientifically induced design. Second, the domains of public policy and public service delivery are witnessing a steep rise of interest in pragmatic, ‘learning-​by-​doing’ approaches to solve perilous issues (a more ‘inspirational’ approach of design [Chapter 2, this volume]). These design as exploration approaches involve living labs, design charrettes, policy experiments, prototyping and other innovative ways of finding solutions for contemporary policy problems. As such, design-​oriented methodologies are more and more used to formulate public policies or to design public services (Bason, 2016; Mintrom and Luetjens, 2016). This may involve the design of policies and services, which aims to find solutions to wicked problems in a new and creative way. As the survey of Lewis et al (Chapter 6, this volume) shows, these public sector innovation labs use all kinds of design methods and focus predominantly 8

Improving public policy and administration

upon the first phases of the design and policy cycle: problem exploration and idea generation. The chapter of Waardenburg et al (Chapter 4, this volume) shows an example of such a design approach used as method for a learning and coaching programme for public professionals dealing with crime-​fighting. Design methods (for example, a customer journey or service blueprinting) not only foster creativity, they also enable explicating and assembling (tacit) knowledge and expertise from different sources into testable artefacts. The third approach conceptualises design as a matter of co-​creation and dialogue, that is, design as co-​design with users and stakeholders. Many design approaches are characterised by a strong focus on co-​design, which refers to the inclusion of multiple stakeholders (for example, citizens, non-​ government organisations, public and private professional organisations) in the design process (Blomkamp, 2018). Such a participatory conception of design finds it origins in design studies (for example, Kolko, 2010; Xenakis and Arnellos, 2013; Norman and Verganti, 2014), thereby focusing on the deliberative and reasoned approach to design. The review of Hermus et al (Chapter 2, this volume) reveals that especially the more participation-​ oriented and user-​centered design approaches emphasise the value of design as a way to co-​create with a wide variety of actors. Design is considered as a way to arrive at social innovation, by inviting the ‘unusual’ actors to the process of policy-​making. Designing as an activity enables joint learning and reframing. The latter application of design departs from the idea that design is especially suitable in a context of wicked or ill-​structured issues –​ although this is largely untested in practice. The creativity that is allowed by a design approach, but also its focus on joint imagination and overcoming frame controversies, make design a promising avenue for dealing with social challenges. At the same time, to date the empirical evidence to substantiate this claim remains rather slim. We thus can distinguish three ideal-​type design approaches. One approach begins from a rational strand whereby design can be considered as a method to find the best solution (within limits) for a certain problem (design as optimisation). It sits easily with Simon’s work on the topic and summarises the ‘old’ design tradition in public policy. The second perspective uses design methodology to enhance creativity, learning and experimentation. Third, we distinguish a perspective that focuses upon the idea of design as a matter of co-​creation, dialogue and shared sense-​making. In this body of literature the notion of co-​design is emphasised. Design is a matter of mobilising all relevant stakeholders in an attempt to jointly create solutions to persistent problems. In the two latter approaches the emphasis is often at least on the process of learning, inspiring and reflection as on the ultimate outcomes in terms of products or artefacts. These three types are not mutually exclusive. Table 1.1 summarises them. 9

Policy-Making as Designing Table 1.1: Three design approaches in public administration Design as (bounded) optimisation

Design as exploration

Design as co-​creation

Logic

Design as translating knowledge into the best possible solution

Design as a creative art: finding novel solutions to problems

Design as a participatory endeavour: all affected actors engage in defining problems and solutions

Methods used

Tools to translate formal Tools that foster out-​ knowledge into artefacts of-​the-​box thinking and innovation

Tools for dialogue and interaction

Motive

Putting the best available knowledge into solutions helps practice to solve its problems

Design processes can bring actors together, foster learning and build consensus

Related concepts

Evidence-​based design, Design-​thinking, open scientific design, innovation, design as knowledge-​based design, imagination design as problem-​solving

Design thinking can enlarge the solution space, foster creativity and enhance imaginative power

Co-​design, collaborative design, participatory design

Illustrating different design approaches: the content of this book In this volume, our selection of chapters illustrate what are main issues and questions to be addressed about each of these approaches. Hermus et al (Chapter 2) present the results of a systematic literature review of design-​oriented studies in the field of PA. Although they found a wide variety of methods and approaches, they also conclude that there is an overrepresentation of more expert-​d riven and informational design approaches. Moreover, collaboration is often restricted to public officials and to consultation instead of co-​creation. Finally, although a more design-​ led way of thinking is increasingly used in practice as a way to come to policies and services, it is not yet used by scholars in the field as a method for investigation or doing research. They put a provocative question on the agenda of our discipline, which is about how to connect design and design thinking to our way of doing research in order to intertwine scientific and societal validation of our knowledge and to increase our impact as a field. The contribution of Howlett (Chapter 3) clearly approaches policy design as a way of optimisation. Howlett examines how policy design entails a variety of approaches to formulate policy (see also Howlett, 2018). He advocates for a distinction with ‘design thinking’, which is a form of reasoning backwards from the value to be created by a policy endeavour. He emphasises the merits of a design approach to policy compared to non-​analytical ways of 10

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policy-​making. In his view, design involves knowledge of the basic building blocks or materials with which actors must work in constructing an artefact such as a product or policy. It also means the elaboration of a set of principles regarding how these materials should be combined in that construction, and the requisites for making such combinations. Moreover, designing effective policies presuppose a clear understanding of the processes by which a policy alternative becomes translated into reality and the barriers that exist between concept and realisation. Olejniczak et al (Chapter 5) discuss how policy labs are effective vehicles to find solutions to contemporary policy problems. They conclude, among other things, that policy labs can strengthen the quality of policy evaluations, since they offer a safe place, which encourages the involvement of other stakeholders, thereby improving their effectiveness. For instance, they argue that policy labs are well equipped to determine the feasibility and scalability of policy programmes, due to a more flexible time-​frame than regular policy implementation. This allows for trial-​and-​ error and ex-​ante pilot studies. Debating design as exploration, Peters (Chapter 7) illustrates the institutional context as a delimiter of design space and underlines the importance of institutional design as a condition for effective policy design (see also Heikkula and Andersson, 2018). In doing so, his contribution provides a more elaborate understanding of how the institutional context is conditional to allow design thinking to thrive. Consequently, one may argue that public policy is in need of methodological innovation, beyond existing methods of action research and design experiments. This is the focal point in the contribution of Romme and Meijer (Chapter 8), building on the work of Simon. They examine how the design science perspective enables PPA scholars to embrace a broad array of both research outputs and validation. In doing so, different traditions and notions of theory testing are represented in one approach. Lewis et al (Chapter 6) argue that Public Sector Innovation (PSI) labs are proliferations of ‘design-​for-​policy’, that is, developing policy proposals and reforms. These labs allow various stakeholders to collectively experiment on innovations. This can be concluded from their survey results, which show how the majority of these labs use human-​centred methods, rather than, for instance, evidence-​based methods. However, they point out how co-​design may imply something different than including creativity in the policy process, thereby demarcating the difference between the second and third perspective. Design as co-​creation is addressed by two chapters. For starters, Waardenburg et al (Chapter 4) show how design in a collaborative context may take shape. They argue that in order to create a problem-​solving space, continuous feedback, a facilitative process (such as the inclusion of both future and current collaborators), and an accountability structure are prime conditions for co-​design. Second, Bryson et al (Chapter 9), building on 11

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their three-​dimensional view of power, look at how design explores the basic settings of public action (that is, forums, arenas and courts). They examine in their chapter how these settings need to be (re)designed in order to facilitate collaborative governance. It is important to analyse critically new design approaches and their effectiveness to come up with and deliver innovative policy interventions (design of services, interventions, tools, and so on). The rapid evolution of all kinds of labs, studios, ateliers, and so on, and the uncritical application of all kinds of design-​based or inspired methods and tools, deserves to be assessed more objectively in order to find out whether and under which conditions such approaches really add to traditional ways of designing policies. While there is a rapidly growing body of cases that suggest that these approaches can work well on the ‘front end’ of a range of problems, helping to understand what the problem actually is, it is much less certain that they can work on improving policy decision-​making and changing policy systems. Related to that, it seems that these approaches are useful for service design but the evidence on their utility for policy design is much less clear (see McGann et al, 2018a; 2018b; Chapter 6, this volume). Hence, several chapters in this volume address the potential as well as the shortcomings of design-​oriented approaches in public policy (Chapters 5 and 6, this volume).

The promises of design-​oriented thinking for public administration and public policy From the various contributions to this volume, we can conclude that the use of design approaches in PA is potentially very promising and can help to revitalise the idea of PA as a design science, which can enhance its societal relevance and impact. It fits well into the current emphasis that many governments are placing on qualities such as participation, learning, creativity and public value. The current emphasis on evidence-​based or evidence-​informed policies fit nicely in the idea of design as optimisation. Policy-​analytical and other forms of knowledge are used (in a systematic and rigorous way) to contribute to more rationalised and analytical ways of problem-​solving (as it is approached in the tradition of Laswell, see Turnbull, 2018). Unlocking existing knowledge and combining different sources of knowledge can help policy-​makers tremendously to enhance the effectiveness of governmental steering attempts. The same holds true for simulations, scenario exercises, data visualisations and the like. These methods are rapidly entering the world of public policy and management, often enthusiastically appraised by innovation labs and other agencies (Williamson, 2015). Design as exploration allows policy-​makers to opt for a more hypothetical way of working: possible and plausible solutions can be tested and refined. 12

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In doing so, design offers an approach to both creatively and systematically explore what the best solution is to the policy problem. In this approach, the benefit of design lies predominantly in broadening the scope of solutions that are taken into account and the room for experimentation (Dorst, 2011), which is usually not characteristic of governmental efforts. Therefore, in a context which is generally dominated by accountability structures, a design approach offers the liberty to imagine alternative solutions. As Peters shows in his contribution to this volume (Chapter 7), that might create tension with existing institutions and may even ask for heavy reconsideration of these institutions. However, due to the out-​of-​the-​box character of this design approach, it offers tools to develop in collaboration with other stakeholders, interventions and products that potentially may work. This is where the benefits of the second approach also touches upon the benefits of the third approach –​design as co-​creation. By including multiple stakeholders (for example, stemming from both business and civil society alike) in the development of policy/​public service, the design orientation allows for creativity and imagination in public policy, which may improve its quality. Moreover, due to its inclusive character, design as a form of co-​creation can facilitate a stronger user-​orientation in policy-​making and service provision by including citizens and end-​users as co-​designers, which also can add to its perceived legitimacy. In the final chapter we will more critically reflect upon the question of whether the ‘new’ design orientation, resembling especially the latter two approaches, holds its promises and how it relates to the ‘old’ design approaches in public policy-​making. We will also outline some ideas on how to fulfil the potential of designerly ways of working in public sector organisations and reflect upon the consequences of that. References Alexander, S. and Orbach, R. (1982) Density of states on fractals, Journal de Physique Lettres, 43(17), 625–​631. Ansell, C. and Gash, C. (2007) Collaborative governance in theory and practice, Journal of Public Administration Research and Theory, 18(4), 543–​571. Armstrong, L., Bailey, J., Julier, G. and Kimbell, L. (2014) Social design futures: HEI research and the AHRC. Swindon: Arts and Humanities Research Council. Bailey, J. and Lloyd, P. (2017) The introduction of design to policymaking: Policy Lab and the UK government, Annual Review of Policy Design, 5(1), 1–​14. Bason, C. (ed) (2016) Design for policy. Oxon: Routledge. Bason, C. (2017) Leading public design: Discovering human-​centred governance. Bristol: Policy Press. Blomkamp, E. (2018) The promise of co-​design for public policy, Australian Journal of Public Administration, 77(4), 729–​743. 13

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Bobrow, D. and Dryzek, J.S. (1987) Policy analysis by design. Pittsburgh: University of Pittsburgh Press. Bovaird, T. and Loeffler, E. (2012) From engagement to co-​production: The contribution of users and communities to outcomes and public value, Voluntas: International Journal of Voluntary and Nonprofit Organizations, 23(4), 1119–​1138. Christiansen, J. and Bunt, L. (2014) Innovating public policy: Allowing for social complexity and uncertainty in the design of public outcomes. In C. Bason (ed), Design for policy. Oxon: Routledge, pp 41–​56. Considine, M. and Lewis, J.M. (2003) Bureaucracy, network, or enterprise? Comparing models of governance in Australia, Britain, the Netherlands, and New Zealand, Public Administration Review, 63(2), 131–​140. Considine, M., Lewis, J.M. and Alexander, D. (2009) Networks, innovation and public policy: Politicians, bureaucrats and the pathways to change inside government. Basingstoke: Palgrave Macmillan. Cross, N. (2011) Design thinking: Understanding how designers think and work. London: Bloomsbury Publishing. Dorst, K. (2006) Design problems and design paradoxes, Design Issues, 22(3), 4–​17. Dorst, K. (2011) The core of ‘design thinking’ and its application, Design Studies, 32(6), 521–​532. Dorst, K. and Cross, N. (2001) Creativity in the design process: Co-​evolution of problem–​solution, Design Studies, 22(5), 425–​437. Dryzek, J.S. (1983) Don’t toss coins in garbage cans: A prologue to policy design, Journal of Public Policy, 3(4), 345–​367. Farr, M. (2013) ‘Citizens and the co-creation of public service innovation’. In Osborne, S.P. and Brown, L. (eds), Handbook of Innovation in Public Services. Cheltenham: Edward Elgar, pp 445–458. Frederickson, H.G. (2000) Can bureaucracy be beautiful?, Public Administration Review, 60(1), 47–​53. Gascó, M. (2017) Living labs: Implementing open innovation in the public sector, Government Information Quarterly, 34(1), 90–​98. Grimmelikhuijsen, S., Jilke, S., Olsen, A.L. and Tummers, L. (2017) Behavioral public administration: Combining insights from public administration and psychology, Public Administration Review, 77(1), 45–​56. Hartley, J., Sørensen, E. and Torfing, J. (2013) Collaborative innovation: A viable alternative to market competition and organisational entrepreneurship, Public Administration Review, 73(6), 821–​830. Head, B.W. (2008) Wicked problems in public policy, Public Policy, 3(2), 101–118. Heikkula, T. and Andersson, K. (2018) Policy design and the added value of the institutional analysis development framework, Policy & Politics, 46(2), 309–​324.

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Hillgren, P.A., Seravalli, A. and Emilson, A. (2011) Prototyping and infrastructuring in design for social innovation, CoDesign, 7(3–​4), 169–​183. Hood, C. (2007) Intellectual obsolescence and intellectual makeovers: Reflections on the tools of government after two decades, Governance, 20(1), 127–​144. Hood, C. and Margetts, H.Z. (2007) The tools of government in the digital age, 2nd edn. London: Palgrave Macmillan. Hoppe, R. (2018) Heuristics for practitioners of policy design: Rules-​ of-​thumb for structuring unstructured problems, Public Policy and Administration, 33(4), 384–​408. Howlett, M. (2010) Designing public policy: Principles and instruments. London: Routledge. Howlett, M. (2018) Matching policy tools and their targets: Beyond nudges and utility maximisation in policy design, Policy & Politics, 46(1), 101–​124. Howlett, M. and Lejano, R.P. (2013) Tales from the crypt: The rise and fall (and rebirth?) of policy design, Administration & Society, 45(3), 357–​381. Jann, W. and Wegrich, K. (2007) Theories of the policy cycle. In F. Fischer, G.J. Miller and M.S. Sidney (eds), Handbook of public policy analysis: Theory, politics and methods. New York: CRC Press, pp 43–​62. Jilke, S., Van de Walle, S. and Kim, S. (2016) Generating usable knowledge through an experimental approach to public administration, Public Administration Review, 76(1), 69–​72. Jordan, A.J. and Turnpenny, J.R. (2015) The tools of policy formulation. Cheltenham: Edward Elgar. Kimbell, L. (2016) Design in the time of policy problems. Proceedings of DRS 2016, Design Research Society 50th Anniversary Conference, pp 1–​14. https://​doi.org/​10.21606/​drs.2016.498 Kimbell, L. and Bailey, J. (2017) Prototyping and the new spirit of policy-​ making, CoDesign, 13(3), 214–​226. Kolko, J. (2010) Abductive thinking and sensemaking: The drivers of design synthesis, Design Issues, 26(1), 15–​28. Lasswell, H.D. (1951) The policy orientation. In H.D. Lasswell and D. Lerner (eds), The policy sciences: Recent developments in theory and method. Stanford: Stanford University Press, pp 1–15. Lasswell, H.D. (1956) The decision process: Seven categories of functional analysis. College Park: Bureau of Government Research, University of Maryland. Lewis, J.M., Ricard, L.M., Klijn, E.H.K. and Ysa, T. (2017) Innovation in city governments: Structures, networks, and leadership. London: Routledge. Linder, S.H. and Peters, B.G. (1984) From social theory to policy design, Journal of Public Policy, 4(3), 237–​259. Linder, S.H. and Peters, B.G. (1991) The logic of public policy design: Linking policy actors and plausible instruments, Knowledge and Policy, 4(1–​2), 121–​151. 15

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McGann, M., Lewis, J.M. and Blomkamp, E. (2018a) Mapping public sector innovation units in Australia and New Zealand: 2018 survey report. McGann, M., Blomkamp, E. and Lewis, J.M. (2018b) The rise of public sector innovation labs: Experiments in design thinking for policy, Policy Sciences, 51, 249–​267. Meier, K.J. (2005) Public administration and the myth of positivism: The antichrist’s view, Administrative Theory & Praxis, 27(4), 650–​668. Miller, T.C. (1984) Public sector performance: A conceptual turning point. Baltimore: Johns Hopkins University Press. Mintrom, M. and Luetjens, J. (2016) Design thinking in policymaking processes: Opportunities and challenges, Australian Journal of Public Administration, 75(3), 391–​402. Norman, D.A. and Verganti, R. (2014) Incremental and radical innovation: Design research vs. technology and meaning change, Design Issues, 30(1), 78–​96. Ostrom, V. (1974) The intellectual crisis in American public administration. Tuscaloosa: University of Alabama Press. Radine, L.B. (1987) Organisation theory in administrative law: A proposal for a design science, The American Sociologist, 18(3), 278–​283. Rhodes, R.A.W. (1997) Understanding governance: Policy networks, governance, reflexivity, and accountability. Buckingham: Open University Press. Schumpeter, J.A. (1934) Change and the entrepreneur. Cambridge, MA: Harvard University Press. Shangraw, R.F. and Crow, M.M. (1989) Public administration as a design science, International Journal of Public Administration, 21(6–​8), 153–​160. Simon, H. (1969) The sciences of the artificial. Cambridge, MA: The MIT Press. Tõnurist, P., Kattel, R. and Lember, V. (2017) Innovation labs in the public sector: What they are and what they do?, Public Management Review, 19(10), 1455–​1479. Torfing, J., Peters, B.G., Pierre, J. and Sorenson, E. (2012) Interactive governance: Advancing the paradigm. Oxford: Oxford University Press. Torjman, L. (2012) Labs: Designing the future. Ontar io: MaRS Discovery District. Turnbull, N. (2018) Policy design: Its enduring appeal in a complex world and how to think it differently, Public Policy and Administration, 33(4), 357–​364. Walker, R.M. (2011) Globalised public management: An interdisciplinary design science?, Journal of Public Administration Research and Theory, 21(suppl_1​ ), i53–​i59. Williamson, B. (2015) Governing methods: Policy innovation labs, design and data science in the digital governance of education, Journal of Educational Administration and History, 47(3), 251–​271.

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Wylant, B. (2010) Design thinking and the question of modernity, The Design Journal, 13(2), 217–​231. Xenakis, I. and Arnellos, A. (2013) The relation between interaction aesthetics and affordances, Design Studies, 34(1), 57–​73.

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Applying design in public administration: a literature review to explore the state of the art Margot Hermus, Arwin van Buuren and Victor Bekkers

Introduction Public sector organisations face many intractable issues, such as climate change, migration and integration, chronic diseases, aging and inequality. These issues touch upon different interests and values and are surrounded with uncertainty and controversy. Furthermore, governments also face financial pressures, urging them to come up with cost-​efficient solutions. Citizens, simultaneously, expect governments to develop policies and services that fit their needs without causing excessive bureaucracy or unwanted inequalities (Kimbell, 2016; Bason, 2017). As a result, the problems governments are dealing with have become increasingly complex, and so have the solutions –​policies and services –​they develop: they have become increasingly integrated, spanning across levels of public administration and involving different actors (Chindarkar et al, 2017). As a result, governments are confronted with a significant design challenge: how to deal with ‘wicked problems’ (Rittel and Webber, 1973) in such a way that effective and efficient policies and services result, which are perceived as legitimate. Design is advocated as a promising development in public administration for various reasons. Design processes are supposed to result in feasible and reliable policies, services and interventions, while addressing complex or even wicked social problems. They are said to foster creativity and develop innovation capabilities, by helping participants to imagine alternative solutions and features. In addition, design is supposed to help integrate insights from different fields, sources or actors, thus increasing the chances of a successful implementation of a policy that meets the needs of users. Designed policies and services are potentially more responsive to the needs of those who work with them (Steen, 2011; Bailey and Lloyd, 2016; Chindarkar et al, 2017; Blomkamp, 2018). The question how scholars in public administration can contribute to this challenge and enhance the design capacities of public governments is far from new within the field. At the first Minnowbrook Conference (1968), 18

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Herbert Simon held a set of lectures on artificial or design sciences. These sciences focus on the artificial –​the manmade –​as opposed to the natural sciences. Artificial sciences therefore incorporate design, which is ‘concerned with how things ought to be, with devising artefacts to attain goals’ (Simon, 1969: 133). For Shangraw and Crow (1989), public administration fits Simon’s definition of an artificial science neatly. They notice that this notion of public administration as a design science was broadly supported in the academic literature, but that there were few applications. Providing an analysis of the design of a policy was more common than providing a design for a policy. The (mostly normative) discussion about the alleged necessity to define public administration as a design science has continued to this day (for example, Frederickson, 2000; Meier, 2005; Barzelay and Thompson, 2010; Walker, 2011; Howlett and Lejano, 2012; Blomkamp, 2018; Peters, 2018). Recently, attention for the potential of design in public administration is growing. Public organisations are looking to apply design as a way of working (for example, Bason, 2017). Simultaneously, there is a shift within the design field from designing products to designing for purposes (such as experiences, interactions and services) (Buchanan, 2015; Mintrom and Luetjens, 2016; Junginger, 2017). This movement is described as the transition from ‘design’ to ‘design thinking’ and has now spread from the private to the public sector (Brown, 2009; Clarke and Craft, 2019). This development and the discussion surrounding it provide an excellent opportunity to take stock of the ways in which design is currently used in the field of public administration. We aim to contribute to the debate on the value of design (thinking) for public administration and the development of the latter into a design science by conducting a systematic literature review into the empirical applications of design in public administration –​encompassing both policy and administration –​since the reviving of the discussion by Shangraw and Crow in 1989. We answer the question: what kind of design applications can be found in the field of public administration and how can they be understood in terms of goals, processes and outcomes? In the following section, we present a conceptualisation of design in the public sector. The next section presents the research strategy. Then we present a systematic literature review of articles on design published in public administration journals between 1989 and 2016. Our findings show an increase in design-​ oriented studies, representing a broad variety in processes and methods –​ currently mostly focused on the application of scientific knowledge but sometimes also departing from a user perspective. Based upon this variety we present a typology that represents the various design approaches in terms of aims and methods. This typology is a useful starting point for further developing and refining design approaches in public administration. This can help deliver the promise of design to combine scientific rigour and societal relevance. 19

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Design for policy and services –​a conceptualisation Design has different meanings and appearances in different contexts, due to differences in philosophical, epistemological and disciplinary backgrounds (Johansson-​Sköldberg et al, 2013). This section therefore does not aim to come up with an authoritative definition of design, but rather to explore the concept and its potential contribution to the field of public administration in order to facilitate the interpretation of the results found in our systematic literature review. It also presents a useful distinction –​devised by Brown (2009) –​of three spaces that helps to structure analysing design processes: the spaces of inspiration, ideation and implementation. Design is concerned with how things ought to be, rather than how they currently are (Simon, 1969). A designer comes up with a solution and tries to realise this ideal by giving it form and shape (Nelson and Stolterman, 2012: 1). In the context of policy design, design is seen as instrumental in the sense that it links problems to solutions and rational in the sense that the process should be knowledge and logic driven. In other words, policy or service designs are systems, instruments and institutions that address public demands in an effective and efficient manner (Howlett et al, 2015; Hoppe, 2018). Designs are as such focused on achieving specific results and therefore should be judged on their value and utility for users (Cross, 2006). Within the design literature, however, design is often conceived as inherently different from science in three ways –​especially because of its instrumental, utility-​driven purpose (Cross, 2006; Dorst, 2011). First, unravelling causal relations or understanding the outcomes of current designs requires different ways of thinking than developing them. When solving a problem, scientists traditionally conduct an analysis of the problem by systematically exploring it to discover the underlying mechanisms. Designers, however, take a solution-​focused approach, by taking the needs and wishes of the ‘users’ into account. They move back and forth between problem and solution, working iteratively and allowing the problem definition to evolve in light of what emerges as a possible solution (Cross, 2006; Hillgren et al, 2011). Second, designers focus their efforts on those elements of a problem they perceive as actionable, rather than analysing the problem in its entirety. Designers thus not only define the problem, but also the problem or design space: those aspects that can be influenced by their design (Cross, 2006; Brown, 2009; Howlett et al, 2015). The third difference is the type of logic that is employed within the process. Science uses either the logic of induction to generalise theoretical explanations, or the logic of deduction to predict consequences. Designers, with their ambition to come to novel forms, use the logic of abduction –​the logic of what could be –​making educated guesses and provisional hypotheses to generate ideas to develop valuable designs (Cross, 2006; Dorst, 2011). 20

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Design processes thus need to enable solution-​focused, abductive thinking, targeted at actionable elements of the identified problem and/​or solution. Brown (2009) proposes to think of these processes as a trajectory through three overlapping spaces –​the spaces of inspiration, ideation and implementation. The space of inspiration explores the problem or opportunity that started the process. The space of ideation encompasses the processes of generating, developing and prototyping or testing ideas. The last space, the space of implementation, brings the designed solution from the experimentation phase to being used within the intended context. Because ideas and designs are constantly reworked and refined, a design process develops iteratively rather than linearly. Following this line of reasoning, it is sensible to expect that design processes in the public sector will take many forms and shapes. A useful distinction in design perspectives or approaches differentiates between studies that aim to combine design with more academic or scientific logic and which are aimed at translating knowledge into evidence-​based solutions, and studies that stress the role of creativity, innovation and empathy in processes to come to (user-​ centred) solutions. Both perspectives, strikingly characterised by Sanders (2005) as the informational and the inspirational approach of (research for) design, are present in the discourse on design for public administration. The informational approach is based on the scientific model and its measures of quality: reliability, validity and rigour. Processes are characterised by investigation, analysis and planning and rely primarily on extrapolation from the past (Sanders, 2005). Applied to public administration, this approach focuses on the analysis of problems, instruments and outcomes. Designs are based on (expert) knowledge of and experience with relationships between means and ends (Linder and Peters, 1984; Howlett et al, 2015; Peters, 2018). The context in which a design is to be implemented is of great importance. This is because it is necessary to understand both how an organisation works and how a change will affect its performance to ensure the success and reliability of a design (Ostrom, 1974; Shangraw and Crow, 1989). The informational approach takes values, governance structures and the policy logic present within this context into account as fixed assumptions. The designer aims to develop the optimal way to reach a predetermined goal, in a more or less systematic way (Shangraw and Crow, 1989; Howlett, 2014; Howlett et al, 2015). The inspirational approach focuses on the extent to which the perspectives of those involved in the design and implementation process are included. The focus is on the (future) appropriation of the design in the implementation phase, in which users make it part of their daily practice (Bjögvinsson et al, 2012). Proponents of this approach argue that lack of insight in how citizens and bureaucrats experience policies and services leads to unintended consequences and therefore hampers implementation (Mulgan, 21

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2014; Mintrom and Luetjens, 2016). Including the perspectives of citizens and bureaucrats provides a deeper, more empathetic understanding of the problem and leads to better, tailor-​made solutions. In turn, these tailor-​made solutions ensure ownership of the solution both in-​and outside the public sector organisation and improve (long-​term) cooperation between different actors (Steen, 2011; Bjogvinsson et al, 2012; Junginger, 2017). Curiosity and empathy are seen as a way to transcend organisational and procedural silos, established hierarchies or bureaucratic categories and thus, design is explicitly seen as a way to challenge the status quo (Bjogvinsson et al, 2012; Mintrom and Luetjens, 2016; Bason, 2017; OECD, 2017). We will use this distinction and the three spaces distinguished by Brown (2009) as structuring devices for the remainder of this chapter. Our review will show to what extent these discourses and approaches are applied in public administration literature and how they contribute to the challenge of designing efficient, effective and legitimate policies and services that can tackle the wicked problems societies are dealing with.

Research strategy In order to provide a comprehensive state of the art of design applications in public administration, we have conducted a systematic literature review, following the guidelines of the PRISMA framework (Liberati et al, 2009) to ensure the quality and transparency of the review process. Our review covers the period between 1989 and 2016, starting from the seminal article of Shangraw and Crow (1989) that revived the discussion on public administration as a design science. Search strategy Our search process encompasses three steps. First, we searched the Web of Science (WoS) database using the broad search term ‘design’. We searched for articles published in English from 1989 up to and including 2016 and restricted our search by using the WoS category ‘public administration’, to ensure that our search was confined to public administration journals only, since our aim is to provide an overview of the empirical applications of design in public administration. We used the term ‘design’ to include as many different approaches as possible. It is possible, however, that scholars apply design without labelling it as such and that, therefore, their articles were not retrieved in our searches. Adding more search terms, however, also increases the risks of contamination of the findings. We found 2176 hits. As a second step, we then did an additional search using the term ‘lab’, using the same restrictions to ensure we included any policy or living labs that did not show up during our first search. This search resulted in 15 hits. 22

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After peer review, received at the 2017 ICPP conference, we decided to include a third search in a different set of journals. Because of the developments in the design field, we decided to check a number of relevant design journals to see if any articles that meet our criteria are published there. We looked for English articles published from 1989 up to and including 2016 that use one or more of the terms ‘policy’, ‘government’, or ‘governance’. We retrieved 36 abstracts and selected two articles for full-​text examination. Eligibility criteria and record selection Based on the conceptualisation of design described in the previous section, we developed the following study eligibility criteria to use for record selection: 1. The research has a design goal or ambition with a focus to come up with a solution to address a specific problem. 2. The end product (designed artefact) is specified and focused towards the central goal/​value/​problem that the process was focused on and changes the status quo. 3. There is a description of (elements of) a design process and/​or method. The last two criteria are straightforward when it comes to the design of material objects, but are more difficult to apply when it comes to (intangible) services, systems or policies, given the multitude of possible end products. However, it is important to have these criteria to exclude incremental policy adjustments (that are often constructed with a specific goal in mind) and evaluations or other types of studies that end in reflections but not in a concrete and ‘tangible’ product. The criteria used try to make a clear demarcation, while being open enough in terms of topics and methods to allow for a rich variance of design applications that can be expected based on the conceptualisation in the foregoing section. We explicitly aim to select studies that represent different approaches to design in the public sector, to ensure that we capture the different applications of design currently present in the field of public administration. We used a two-​step process for article selection, as is depicted in Figure 2.1. An overview of all included articles can be found in Appendix 1. In both steps, we used the eligibility criteria described above. First, we assessed titles and abstract only. We mostly excluded studies that did not aim to come up with a specific solution for a problem –​for example, articles that either focused on research design or on a normative discussion of design. In case of doubt, articles were included for the next step. Second, we conducted a full-​text read on all articles. In this step, articles were mostly excluded because they did not present a specific end-​product or because they presented an evaluation or analysis of a (given) design rather than a description of a design process. 23

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Included

Eligibility

Screening

Identification

Figure 2.1: Flowchart of article selection Records identified in PA journals – search term ‘design’ (n = 2176)

Additional records identified in PA journals – search term ‘lab’ (n = 15)

Journals – search terms ‘Policy’, ‘government’ or ‘governance’ (n = 36)

Records after duplicates removed (n = 2227)

Records screened (n = 2227)

Records excluded (n = 1942)

Full-text articles assessed for eligibility (n = 285)

Full-text articles excluded (n = 193)

Studies included in qualitative synthesis (n = 92)

In order to have a systematic selection of articles, the assessment was done by one of the authors. During assessment of titles and abstracts, articles were always included in case of doubt. In this phase, 1942 articles were excluded because they did not meet the eligibility criteria, leaving 285 articles for full-​text assessment. During the phase of full-​text assessment, one of the other authors assessed about 10 per cent of articles (including those articles of which inclusion was doubted) to ensure intercoder reliability; 92 articles were included in the review. Of included articles, the following data is collected and coded using Excel: • • • • • • •

metadata about authors, year of publication, journal and country of study; purpose/​aim/​problem central to the study; end product/​result; design methods; involved parties/​stakeholders in the design process; extent of stakeholder involvement in the design process; sources of knowledge used.

24

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Results: design in public administration Over time, we can see an upward trend in the amount of publications on design application in Public Administration (see Figure 2.2). Between 1990 and 1999, on average 1.1 article was published per year. Between 2000 and 2009 the average was 3.4 and between 2010 and 2016 it was 6.9. The selected articles (n =​92) are published in no less than 38 different journals: 37 public administration journals and one design journal (The Design Journal). The most frequent journals are Administration in Social Work (9.8%), Public Management Review (8.7%), Climate Policy (7.6%), Journal of Homeland and Security Management (6.5%) and Public Personnel and Management (6.5%). In the rest of this section, we will discuss the different applications of the design represented in these studies. We categorise our findings using the three spaces of Brown (inspiration, ideation and implementation) presented above. We also use the distinction between a more informational and a more inspirational approach as a sensitising device to order the variety of design approaches which we came across. Design problems: the inspiration space The studies in our selection comprise a broad range of subjects and problems. An overview of domains can be found in Table A.3.1 (Appendix 2). One notable finding is that in 32.6 per cent of articles, the design process was focused on the inner workings of government; on the management of public organisations or policy processes itself. Other studies focus on a specific domain and on the development and/​or implementation of (parts of) policies and services. The two (policy) domains most frequently

Figure 2.2: Amount of publications per year 10 8

10 10 8

5 4

4

4 3

1

1

1

1

3 2

1 1 0 0

3

3

3

3

0

1990 1991 1992 1993 1994 1995 19 96 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 20 08 2009 20 10 2011 2012 2013 2014 2015 2016

1

3

Amount of publications

Linear average (amount of publications)

25

Policy-Making as Designing

mentioned are health and social care (18.5%) and environmental or climate policy (15.2%). One of the elements described in the conceptualisation that distinguishes design from traditional science is its focus on the actionable aspects of a problem, by defining a design space, a context in which designs can be actualised. In the inspiration space, the problem is explored to see which needs, flaws and opportunities emerge from the current situation. These perceived needs and opportunities determine what design capacities are needed. We have found four different design goals. These goals show some overlap with the distinction between informational and inspirational approaches to design which we described previously. An overview of the frequency of those goals can be found in Table A.3.2 (Appendix 2). A majority of the articles (over 50%) see the application of scientific knowledge and methods as their goal and the perceived need emerging from the current situation –​fitting with an informational approach to design (where knowledge or information is collected to inform the analysis and improve its results). The intention is to make social science usable, or to provide systematic ways of generating options (compare Askew et al, 2010; Buurman and Babovic, 2016). The second goal, integrating knowledge from different sources, encompasses studies that combine, for example, scientific knowledge with empirical data and/​or user/​local knowledge to gain knowledge on the context in which the design needs to function. The two other goals –​incorporating local/​user knowledge and generating (user) support –​both point to a central position of the user within the design process, an indication of a more inspirational approach. Including local or user knowledge into the design, to ensure it meets the needs of a specific case, is among others used in cases of strategic planning (compare Collion and Kissi, 1993; Iglesias Alonso, 2014). Generating support is a related, but separate goal: the focus is less on understanding the perspective of these users, and more on ensuring that they will work with the design –​while the latter can be primarily based on scientific knowledge (compare Abrams et al, 2013). This difference in goals is also reflected in the variety of methods that is used in the inspiration space. It is difficult to determine exactly which method is used and with what purpose, because in academic articles, process descriptions are often dense and subordinate to theoretical considerations or empirical findings. Most articles present a theory section. However, articles using a more informational approach use this section as an exploration of the problem rather than an introduction on the topic. They make an inventory of all scientific knowledge pertaining to the topic, supplemented by information on the case at hand (sometimes from non-​academic, existing data sources). A subset of articles is formed by articles that supplement scientific knowledge 26

Applying design in public administration

by empirical data collected to determine the opportunities and constraints stemming from the context that influence the design space. An example of this approach is the study by Adaman et al (2009). They assessed that a policy change did not lead to effective preservation of the Burdur basin. In order to find out why, they conducted interviews, focus groups and a survey to find out how citizens and other stakeholders experienced the current situation and what demands a new solution should meet. Inspirational processes are focused on generating rather than applying knowledge. In general, we see that inspirational processes are more holistic, where the inspiration and the ideation spaces –​and sometimes also the implementation phase –​overlap. For studies using this approach, the main goal of the inspiration space is to visualise the perspective of the user and make their tacit, experiential knowledge visible. There are specific methods available for this purpose. Radnor et al (2014) and Trischler and Scott (2016) both use service design methods. Both studies are conducted in the context of a university, looking at the experiences of international students with the service systems at the universities. Service design methods are used to make a detailed map or blueprint of the current service processes. This map is made with students, so that it reflects their experience and to ensure that the experience becomes palpable for staff members of these universities. Designed solutions: the ideation space Our review revealed a great variety of products or artefacts, developed for different levels of government. Table 2.1 provides an overview of the design products, organised by type and (intended) level of implementation.

Table 2.1: Type of solution and level of (intended) implementation (%) Framework Method

Management structure

Policy or service

Instrument Total

Generic

2.1

2.1

-​

-​

-​

4.2

Supranational

1.1

-​

-​

3.2

1.1

5.3

National

3.2

1.1

1.1

11.6

2.1

18.9

Regional

1.1

-​

-​

2.1

4.2

7.4

Local

1.1

2.1

1.1

8.4

2.1

14.7

Interorganisational

2.1

2.1

3.2

4.2

-​

11.6

Organisation Total

9.5

4.2

-​

18.9

5.3

20.2

11.6

5.4

48.4

14.8

Note: Some articles resulted in more than one design. N =​95

27

37.9 100

Policy-Making as Designing

Almost half of the design products are policies and services (or strategies, programmes, systems and so on). Examples are a reform agenda for the housing market for migrants in China (Huang and Tao, 2015), and a redesign of the student enrolment process at a university (Radnor et al, 2014). Sometimes a design process delivers an instrument or tool that can be used as part of a policy or service. A web-​based portal to help local governments to share expertise, for example (Ford and Murphy, 2008). A small category of designs is formed by management or organisational structures, focusing not so much on the content of the policy or service, but on the way it is managed. Examples are an organisational structure for cross-​sector research networks (Klenk and Hickey, 2012) and a service delivery system meant to overcome fragmentation of health and human services (Libby and Austin, 2002). Frameworks and methods are specifically developed for use in multiple contexts. For instance, Kahan et al (2009) developed an operational framework that organisations can use to incorporate resilience. When we look at the designed solutions and the used approaches, the link between design approach and targeted level of government stands out. Studies using an inspirational approach focus mostly on the lower levels. Only two articles using this approach aim to design a policy or a method intended for national governments. All other studies focusing on the national or supranational level are informational in nature. Designs aimed at higher levels of government thus seem focused at designing optimal solutions by applying scientific knowledge. One of the articles proposes a redesign of the American constitution in order to repair the distorting influences of minority interests on public governance (Cook, 2016). Cook designs this redesign by theoretical reasoning, based on literature on the interaction between public bureaucracies and private parties. At the regional, local, or (inter)organisational level, the picture is much more balanced. Design-​oriented studies regarding climate policy offer an interesting illustration of these differences in approaches on different levels. Schott (2013) provides (theoretical) arguments for harmonising carbon prices between different countries. In a similar vein, Buurman and Babovic (2016) present scientific methods to help national governments to deal with the uncertainty that comes with climate adaptation. Studies using an inspirational approach deal with similar problems, but in different ways. Van de Kerkhof (2006) describes the value of a deliberative approach within environmental policymaking at the national level. Stakeholder groups were explicitly asked to develop multiple strategies to reduce emissions in their sector, then they individually scored all options and gave conditions under which a specific option was acceptable to them. The outcomes of these steps were integrated in a policy strategy that was written collaboratively. Cloutier et al (2015) look at climate adaptation measures at the local level, and more specifically at the involvement of stakeholders, in order to link climate-​related issues 28

Applying design in public administration

with urban and social issues and to overcome barriers in implementation. Instead of systematically comparing options, as in the study of Buurman and Babovic, generating possible measures from a more inspirational stance is the main focus of the process. However, this kind of approaches is still in a minority. For researchers it is much easier to design in a way that suits their normal repertoire instead of applying a more explorative and open approach. Informational and inspirational approaches differ in their processes of ideation. Informational approaches look for designs that are reliable, valid and are based on rigorous analytical processes. In addition, they try to design for the future by extrapolating from the past (Sanders, 2005). The ideation space is the space where solutions are generated, developed and tested (Brown, 2009). The studies of Cook (2016) and Buurman and Babovic (2016) show two different types of informational approaches: Cook has a more theoretical approach, focusing on the translation of knowledge, whereas Buurman and Babovic focus on providing a design based on a rigorous analytic process, using empirical data from a case to illustrate their method. Stakeholders can inform such a systematic approach, as shown by the article by Hajkowicz et al (2013), who design a decision model for human services departments to target investments. They review the available literature on similar models, identify the objectives, criteria and decision options relevant to decision makers and create an evaluation table in which they present performance data against the identified criteria. They ask bureaucrats, who work in these departments, to weigh the criteria. Then they design their model using a multiple criteria analysis. Stakeholders can thus participate in the development of ideas within an informational approach. More often, stakeholders are involved in the testing of an idea or prototype. This can be by giving feedback (for example, Abrams et al, 2013), but also by participating in field or lab experiments. In the UK, the Cabinet Office’s Behavioural Insights Team led a large randomised controlled trial, designed to test the effectiveness of mobile phone text messaging as an alternative method to induce people to pay their outstanding fines. Citizens with outstanding fines thus participated in this trial not actively influencing the design by suggesting ideas or improvements, but purely by their behaviour (Haynes et al, 2013). Within the inspirational approach, the focus is less on the reliability and validity of the designs, and more on the generativity, evocativeness and relevance of the process, which can be characterised by experimentation, ambiguity and surprise (Sanders, 2005). The processes are therefore more open, researchers are less central to the design (process) and stakeholders have more influence on the content of the design. Their input is more central to the course of the process. This can be done in different ways. In some studies, researchers deliberately collect input from relevant stakeholders. An example of this is in two strategic planning processes for cities in Spain, where 29

Policy-Making as Designing

long-​term strategies were developed in a continuous process of reflection, in which citizens and other relevant stakeholders were actively involved (Iglesias Alonso, 2014; Ruano, 2015). Designs in use: the implementation space The third space, the implementation space, is an important one, especially because design is often promoted as a way to improve the societal impact of public administration as a scientific discipline. Table A.3.3 (Appendix 2) shows the implementation status of all studies included in our selection. Strikingly, in the majority of the cases (52.2%), the researchers did not intend or attempt to implement the design they came up with. In 29.3 per cent (which is the majority of those instances of design at which implementation was really aimed), the design was implemented successfully. Implementation failed in only 4.3 per cent of cases. This ratio can possibly be explained by a publication bias: articles describing an implemented design might be easier to publish, and proponents of design might be more likely to publish them. For some studies, implementation was not the focus of the article and implementation status and/​or intent were unclear or outside the scope of the article. Within the informational approach, implementation not only seems to be less relevant from the perspective of the designer, but it seems also to be more difficult compared to the inspirational approach. The latter is clearly illustrated by Klauer et al (2006). They present a method for structured decision-​making, meant for participatory settings that need an interdisciplinary approach in order to take both environmental and socioeconomic consequences of decisions into account. However, their project ended prematurely because political decision makers backed out of the process when they sensed the outcome was not going to be acceptable to them. In this type of design project, a design is made based on scientific knowledge and/​or empirical data, which is then presented to the implementers with the explicit intention to generate support and ensure the use of the design, rather than to enrich the solution by including their perspective (as is more common within the inspirational approach). An example of this informational approach is the previously mentioned study by Abrams et al., focusing on the development of a performance indicator report regarding cardiac arrests for the Boston emergency services. The manager made a draft report based on scientific literature and existing field data. He presented this prototype to the professionals during a training exercise, actively invited feedback and reworked his design (Abrams et al, 2013). Within the inspirational approach, the focus on the future implementation of the design is often more central to the process. The most intensive type 30

Applying design in public administration

of stakeholder participation seen in this approach, is a process within which researchers only facilitate the process and intend to help professionals to generate, test and implement ideas. An example of this way of working is the article by Kellie et al, (2012). A large NHS trust aimed to reduce to number of healthcare associated infections. An action learning process was set up to develop the skills and abilities of nurses in order for them to feel comfortable with implementing and experimenting with solutions. The process was considered a pivotal success, not necessarily because the chosen solutions were innovative, but because the process was perceived as legitimate by all employees. It holds true for both the informational and inspirational approach that projects that have a close connection to practice from the start –​for instance because they are commissioned by public sector organisations –​have higher chances of being implemented. This kind of embedding ensures that the people who need to work with the design are involved from the start and the implementation space is brought to the front from the beginning. The implemented studies of Abrams et al (2013) and Kellie et al (2012) were both conducted within a public sector organisation and thus strongly embedded in the context of application. These examples represent a pattern we distinguish when we look at stakeholder participation in design processes. Table 2.2 provides an overview of the types of stakeholders included in the different processes and their level of involvement. It shows that civil servants are the most common stakeholders in design applications. Citizens, as recipients of services and ‘targets’ of policies, are not as often involved. This could

Table 2.2: Stakeholders: types and level of involvement No role Input

Design Feedback Test

Unclear Total

No stakeholders specified

19

-​

-​

-​

-​

-​

19

Experts

-​

5

2

4

-​

1

12

Civil servants (implementers) 10

22 (1*) 19 (6*) 19 (1*)

16 (1*) 1

87

Policy-​makers

8

-​

2 (2*)

-​

-​

-​

10

Interest groups and private actors

-​

7

5 (4*)

3

-​

1

16

Citizen(s) (groups)

-​

4

4 (3*)

3

1

-​

12

Service users

-​

4

6 (1*)

3

4

-​

17

Total

37

42

38

32

21

3

173

Note: because multiple groups of stakeholders can be involved at multiple stages in one process, this table works with absolute numbers (of instances of stakeholder involvement) rather than percentages * =​group/​committee with representatives of stakeholder groups

31

Policy-Making as Designing

have different causes. Table A1 (Appendix 2) shows that a significant part of design processes is focused on the inner workings of governments and public sector organisations. In these cases, civil servants are the main users of the designs (although they are seldom involved as co-​designers. Processes aimed at policies or services relevant for citizens and other external stakeholders have a broader range of users. Table 2.2 shows that design processes in which they are involved are less common. Studies such as the article of Van de Kerkhof (2006) and Cloutier et al (2015) show that inspirational processes aimed at integrating stakeholder perspectives can lead to enriched policies, supported by stakeholders, but their designs have not (yet) been implemented. Although these inspirational processes are more focused on the future implementation of their design, the actual implication of the results of these processes within (political) policy-making processes is not a given (compare Clarke and Craft, 2019).

Design approaches in public administration: a typology The previous sections have described a great variety of applications of design in the public sector context. In our conceptualisation, we discussed the distinction made by Sanders (2005) between informational and inspirational approaches. She states that both approaches are necessary if design is to contribute to solving complex social issues. From our review, it has become clear that this distinction is useful to structure the variety of approaches used within public administration, but that we have to complement it with another distinction to justify the variety of approaches we found. We thus present a two-​level typology (see Table 2.3) that complements the informational/​ inspirational distinction with a distinction between approaches focusing upon the content of design (the way knowledge is used), the context of design (the situation in which it has to be employed) and the impact of design (the cognitive or practical changes design evokes). The informational approach accounts for 71.7 per cent of the articles. Articles within this approach aim to contribute to better policies and services by applying scientific knowledge and methods to public sector problems. Within this approach, the first, knowledge-​focused, subtype is theory-​driven

Table 2.3: Different approaches to design in public administration Informational approach

Inspirational approach

Knowledge-​focused

Theory-​driven design

Synthesis-​oriented design

Situation-​focused

Evidence-​driven design

User-​oriented design

Implementation-​focused

Consensus-​driven design

Change-​oriented design

32

Applying design in public administration

design, purely focused on the application of scientific knowledge –​such as the redesign of the American constitution by Cook (2016). None of the 26 studies in this type are implemented. They target all levels of government and most notably also the supranational level, with studies focusing on climate policy and the EU. The second subtype –​an example of a situation-​focused approach –​is evidence-​driven design, formed by studies who supplement their theoretical argumentation or systematic analysis with empirical data on the studied context, either collected from stakeholders or from existing sources. The previously cited study of Buurman and Babovic (2016) is an example. This category is very broad in terms of end products. The third subtype is implementation-​focused: consensus-​driven design. Articles in this group work towards the best supported solution rather than the best solution per se. Most of the designs within this subtype are implemented. The processes are mostly done within public organisations and focus quite often on HRM topics. An example of this subtype is the performance indicator report developed by Abrams et al (2013). Within the inspirational approach, we discern a similar subdivision. The inspirational approach focuses on the perspective of the user, on including local knowledge and designing new solutions by embracing creativity and experimentation. The first (knowledge-​focused) subtype is synthesis-​ oriented design, an approach oriented to integrating knowledge from different actors, sources and perspectives. Comparison between this subtype and consensus-​driven design shows that both types focus on accomplishing a supported solution, albeit that within the inspirational approach local knowledge is equal to scientific knowledge and the perspectives are to be integrated, whereas in the informational approach the local knowledge of stakeholders is used to fine-​tune a design primarily based upon scientific evidence. Studies in this subtype often focus on reforms, policies and strategies. Implementation is unclear in a remarkable number of cases, indicating that generating ideas might be more important in these processes than implementing them. Examples of this subtype are the studies of Van de Kerkhof (2006) and Cloutier et al (2015). The second, situation-​focused subtype –​user-​oriented design –​is focused on understanding the user perspective as a way to gain better insight in the situation at hand. This approach has not been used very often (3.3%). It is thus far only applied in the domains of education and healthcare, in which users are easily identified and interaction with users forms a significant part of service provision. Examples of user-​oriented design are the articles of Radnor et al (2014) and Trischler and Scott (2016). The third subtype is the implementation-​focused approach. Within the informational approach, stakeholder-​oriented meant seeking consensus and support of stakeholders. Within the inspirational approach, the perspectives 33

Policy-Making as Designing

of users come to the fore within all three subtypes. Change-​oriented design, however, is characterised by the fact that the process is not so much aimed at generating solutions rather than transferring skills and tools to the participants so that they can design and implement solutions within their own organisations. These processes are conducted within public sector organisations and have the highest implementation rate of all types. They are quite often related to HRM and/​or conducted in care related organisations. An example of this approach is the study of Kellie et al (2012). Our analysis shows that there is a strong dominance of more informational approaches, which fit nicely in a more science-​or expert-​driven approach of design that predominates the traditional line of thinking about PA as a design science. Currently, design is mostly seen as a way to translate scientific knowledge into something useful for practice, either or not in consultation with stakeholders. The large variety of approaches and methods shows that there is no overarching design methodology underlying all these processes. There are however many existing methods that can be used in these processes (see also Table A.3.4 in Appendix 2). This clearly shows that there is no common design methodology in public administration, but that scholars in the field look for ways to come up with new, more state-​of-​the-​art methods for solution-​driven research.

Discussion, conclusions and research agenda We started this chapter with the question how public administration as a design science has evolved since the article of Shangraw and Crow (1989). First of all, we can conclude that there is an increase and proliferation in design-​oriented studies reported in PA journals, in which a wide variety of designs is accomplished, but mostly oriented towards delivering concrete policies and services at the level of national or local governments or public sector organisations. We can see that on the one hand knowledge-​driven approaches are popular within public administration. This seems to fit the idea of a design science that is concerned with ‘how things ought to be’ rather than how they are (Simon, 1969), and with giving form and shape to ideal solutions (Nelson and Stolterman, 2012). More recently, we can see efforts to involve (future) users of the design and integrate their perspectives. Our review shows a great variety in design processes and methods. The distinction between more informational approaches and more inspirational approaches proved very useful. We used it as a basis to develop a two-​ level typology of six design approaches that represent the state of the art. There is a strong overrepresentation of design approaches following an informational logic. This logic is represented on all levels of government, whereas the inspirational approach is currently concentrated on the lower levels of government and on public sector organisations. Commissioned 34

Applying design in public administration

designs have a better chance of being implemented than unsolicited designs. The same holds true for designs that are accomplished within public sector organisations compared to designs invented elsewhere. The range of actors involved in design processes is often rather limited, with an exception for public servants, relativising the user-​centeredness of many design attempts in public administration. Design is more and more applauded as a creative and collaborative approach to find more effective and responsive solutions for wicked problems and (co-​)create policies and services that are more responsive to the needs of citizens. Although we found some examples of such approaches and their number appears to be growing, more traditional, expert-​driven forms of design, with quite low levels of participation, let alone co-​creation, characterise the current state of public administration as a design science. Design is more often seen as a way of ‘translating’ knowledge than as a way of ‘producing’ knowledge. To strengthen the design-​orientation within public administration, it is first of all important to more systematically analyse design efforts and their outcomes. Currently, studies that present a design attempt are often not very clear about the design problem they try to solve and the ultimate design they deliver. Many studies only mention but a few elements of a design process and do not explicitly present their methods. In addition, many studies do not explicate their contribution to their scientific field. Knowing how and why design works, can help scholars in the field to take part in such design processes and to use them as a way for societal validation of their academic knowledge. Our typology of design approaches can form a basis for a more elaborate portfolio of (validated) design methodologies in public administration, but this certainly necessitates more rigorous analyses of how they work out in practice. More importantly, however, it is valuable to explore the possibilities of strengthening the design orientation in public administration and policy studies. One of the most challenging avenues for doing so is to explore how a more ‘designerly’ way of thinking and current ideas about design-​thinking can be applied in public policy and public administration research as a way to come to actionable knowledge. For example: can we approach policymaking as prototyping (Kimbell and Bailey, 2017)? And how to embed typical design methods, like ideation, future-​oriented visioning, reframing and evocative sketching in administrative processes aimed at delivering services and interventions (Bason, 2014)? Finally, we are convinced that applying design does not only hold promise for the practice of public administration, it can also contribute to scientific research by providing opportunities to translate scientific knowledge to applicable interventions and test their working which also means that new findings can be added to the disciplinary knowledge base. In addition, design 35

Policy-Making as Designing

can help to intertwine scientific and societal validation, by developing and testing artefacts based upon state-​of-​the-​art knowledge, which contributes to the societal impact of public administration as a discipline. However, for this potential to be realised, it is important that design approaches and methodologies are developed further and that scholars reflect on their merits for both theory and practice, to come to a more coherent and substantive image of public administration as a design science. Appendix 1: overview of articles included in review Abrams, H.C., Moyer, P.H. and Dyer, K.S. (2013). A participatory approach to generating frontline interest and support for the development of a performance indicators report. Public Performance & Management Review, 36(4), 529–​543. https://​doi.org/​10.2753/​PMR1​530-​957​6360​402 Adaman, F., Hakyemez, S. and Ozkaynak, B. (2009). The political ecology of a Ramsar site conservation failure: The case of Burdur Lake, Turkey. Environment and Planning C: Government and Policy, 27(5), 783–​800. https://​ doi.org/​10.1068/​c0840 Ahlqvist, T., Valovirta, V. and Loikkanen, T. (2012). Innovation policy roadmapping as a systemic instrument for forward-​looking policy design. Science and Public Policy, 39(2), 178–​190. https://​doi.org/​10.1093/​sci​pol/​ scs​016 Alvarez McHatton, P., Bradshaw, W., Gallagher, P. A. and Reeves, R. (2011). Results from a strategic planning process benefits for a nonprofit organisation. Nonprofit Management & Leadership, 22(2), 233–​249. https://​ doi.org/​10.1002/​nml Andersen, L.B., Eriksson, T., Kristensen, N. and Pedersen, L. H. (2012). Attracting public service motivated employees: how to design compensation packages. International Review of Administrative Sciences, 78(4), 615–​641. https://​doi.org/​10.1177/​00208​5231​2455​298 Askew, R., John, P. and Liu, H. (2010). Can policy makers listen to researchers? An application of the design experiment methodology to a local drugs policy intervention. Policy and Politics, 38(4), 583–​598. https://​ doi.org/​10.1332/​03055​7310​X501​758 Aslam, M.A. (2001). Technology transfer under the CDM: Materialising the myth in the Japanese context? Climate Policy, 1(4), 451–​464. https://​ doi.org/​10.1016/​S1469-​3062(01)00035-​3 Avery, G. (2000). Outsourcing public health laboratory services: A blueprint for determining whether to privatise and how. Public Administration Review, 60(4), 330–​337. https://​doi.org/​10.1111/​0033-​3352.00095 Basile, R.E. and Marvin Bentley, J. (1993). State economic development strategy: Designing a tool for evaluating policy. International Journal of Public Administration, 16(10), 1587–​1617. https://​doi.org/​10.1080/​019006​9930​ 8524​862 36

Applying design in public administration

Boulos, G., Huggins, L.J., Siciliano, M.D., Ling, H., Yackovich, J.C., Mossé, D. and Comfort, L. K. (2012). Compare and draw lessons –​designing resilience for communities at risk: Socio-​technical decision support for near-​field tsunamis. Journal of Comparative Policy Analysis: Research and Practice, 14(2), 160–​174. https://​doi.org/​10.1080/1​ 38769​ 88.2012.6646​ 90 Branscomb, L.M., Ellis, R.N. and Fagan, M. (2012). Between safety and security: The policy challenges of transporting toxic inhalation hazards. Journal of Homeland Security and Emergency Management, 9(2). https://​doi. org/​10.1515/​1547-​7355.1999 Brook, B.W., Edney, K., Hillerbrand, R., Karlsson, R. and Symons, J. (2016). Energy research within the UNFCCC: A proposal to guard against ongoing climate-​deadlock. Climate Policy, 16(6), 803–​813. https://​doi.org/​ 10.1080/​14693​062.2015.1037​820 Buurman, J. and Babovic, V. (2016). Adaptation pathways and real options analysis: An approach to deep uncertainty in climate change adaptation policies. Policy and Society, 35(2), 137–​150. https://​doi.org/​10.1016/​j.pol​ soc.2016.05.002 Caloffi, A. and Mariani, M. (2011). Shaping regional policy responses: The design of innovation poles. Policy Studies, 32(4), 413–​428. https://​doi.org/​ 10.1080/​01442​872.2011.571​857 Caputo, R.K. (1991). Managing information systems: An ethical framework and information needs matrix. Administration in Social Work, 15(4), 53–​64 Chen, Y.-​M., Wu, D. and Wu, C.-​K. (2009). A game theory approach for evaluating terrorist threats and deploying response agents in urban environments. Journal of Homeland Security & Emergency Management, 6(1), 1–​25. https://​doi.org/​10.2202/​1547-​7355.1488 Claiborne, N. and Lawson, H.A. (2011). A two-​site case study of consultation to develop supervisory teams in child welfare. Administration in Social Work, 35(4), 389–​411. https://​doi.org/​10.1080/​03643​107.2011.599​749 Clement, S., Moore, S.A., Lockwood, M. and Mitchell, M. (2015). Using insights from pragmatism to develop reforms that strengthen institutional competence for conserving biodiversity. Policy Sciences, 48(4), 463–​489. https://​doi.org/​10.1007/​s11​077-​015-​9222-​0 Cloutier, G., Joerin, F., Dubois, C., Labarthe, M., Legay, C. and Viens, D. (2015). Planning adaptation based on local actors’ knowledge and participation: A climate governance experiment. Climate Policy, 15(4), 458–​474. https://​doi.org/​10.1080/​14693​062.2014.937​388 Collion, M.-​H and Kissi, A. (1993). Learning by doing: Developing a programme planning method in Morocco. Public Administration and Development, 13(3), 261–​270. https://​doi.org/​10.1002/​pad.423​0130​308 Cook, B.J. (2016). Curing the mischiefs of faction in the American administrative state. The American Review of Public Administration, 46(1), 3–​27. https://​doi.org/​10.1177/​02750​7401​5612​160 37

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Appendix 2: Tables Table A.3.1: Design problems ordered by domain Domain of study

Number

Percentage

General management and policy processes

30

32.6

Health and social care

17

18.5

Environmental/​climate policy

14

15.2

Economic/​financial policy

9

9.8

Safety and security

6

6.5

Urban and rural planning

4

4.3

Education

4

4.3

Justice

3

3.3

Development cooperation

2

2.2

Strategic planning

2

2.2

E-​government Total

1

1.1

92

100

Table A.3.2: Design goals and their frequency Framing

Number

Percentage

Apply scientific knowledge and/​or methods

50

54.3

Integrate knowledge from different sources

11

12.0

Incorporate local/​user knowledge

30

32.7

Generate (user) support

16

17.4

Number

Percentage

27

29.3

Implemented with limited success

3

3.3

Implementation failed

4

4.3

Note: one article can mention multiple goals

Table A.3.3: Implementation status of designs Implementation status Implemented with success

Intention to implement

2

2.2

Unclear

8

8.7

48

52.2

No implementation intent/​attempt

44

Applying design in public administration Table A.3.4: Design methods mentioned in included articles Method

Number

Analytic methods: A priori approach

1

Multiple criteria analysis

2

Evolutionary approach

1

Game theory

1

Laboratory/​field experiments

1

Strategic planning

2

Mapping methods Adaptive policy making/​adaptation pathways/​real options analysis

11

Context-​driven approach

1

Innovation policy roadmapping

1

Participatory methods: (Participatory) action research

7

Collaborative governance/​process

3

Co-​production intervention

1

Information system development

1

Strategic planning

3

Inquiry-​based communications

1

Participatory (policy) approach

2

Mapping methods Exploratory concept mapping/​Delphi

1

Integrated assessment of decisions under uncertainty for sustainable development (IANUS)

1

Interactive backcasting/​dialectical approach/​grid method

1

Impact diagramming/​Venn diagramming

1

Design methods Service design

2

Iterative redesign

1

Design experiment

1

Design team intervention

2

Service blueprinting

1

45

Policy-Making as Designing

Acknowledgements We would like to thank the two anonymous reviewers and the editors for their valuable and constructive critiques and suggestions on an earlier version of this chapter. They helped us to improve the chapter substantially. Furthermore, we would like thank participants in the panel ‘The design of policy and governance design: principles, practices and potentials’ at the 3rd International Conference on Public Policy (ICPP) in Singapore, June 2017, for their insightful feedback that helped us improve the article selection.

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Howlett, M. (2014) From the ‘old’ to the ‘new’ policy design: design thinking beyond markets and collaborative governance, Policy Sciences, 47(3): 187–​ 207, doi: 10.1007/​s11077-​014-​9199-​0 Howlett, M. and Lejano, R.P. (2012) Tales from the crypt: the rise and fall (and rebirth?) of policy design, Administration and Society, 45(3): 357–​81, doi: 10.1172/​JCI200320249 Howlett, M., Mukherjee, I. and Woo, J.J. (2015) From tools to toolkits in policy design studies: the new design orientation towards policy formulation research, Policy and Politics, 43(2): 291–​311. doi: 10.1332/​ 147084414X13992869118596 Huang, Y. and Tao, R. (2015) Housing migrants in Chinese cities: current status and policy design, Environment and Planning C: Government and Policy, 33(3): 640–​60, doi: 10.1068/​c12120. Iglesias Alonso, A. (2014) The shaping of local self-​government and economic development through city strategic planning: a case study, Lex Localis, 12(3): 373–​91, doi: 10.4335/​12.3.373-​391(2014) Johansson-​Sköldberg, U., Woodilla, J. and Çetinkaya, M. (2013) Design thinking: past, present and possible futures, Creativity and Innovation Management, 22(2): 121–​46, doi: 10.1111/​caim.12023 Junginger, S. (2017) Design research and practice for the public good: a reflection, She Ji: The Journal of Design, Economics, and Innovation, 3(4): 290–​ 302, doi: 10.1016/​j.sheji.2018.02.005 Kahan, J.H., Allen, A.C. and George, J.K. (2009) An operational framework for resilience, Journal of Homeland Security and Emergency Management, 6(1): 1–​47, doi: 10.2202/​1547–​7355.1675 Kellie, J., Milsom, B. and Henderson, E. (2012). Leadership through action learning: A bottom-​up approach to ‘best practice’ in ‘infection prevention and control’ in a UK NHS trust. Public Money & Management, 32(4), 289–​ 296. https://​doi.org/​10.1080/​09540​962.2012.691​308 Kimbell, L. (2016) Design in the time of policy problems, Proceedings of DRS 2016, Design Research Society 50th Anniversary Conference, pp 1–​14, doi: 10.21606/​drs.2016.498 Kimbell, L. and Bailey, J. (2017) Prototyping and the new spirit of policy-​ making, CoDesign, 13(3): 214–​26, doi: 10.1080/​15710882.2017.1355003 Kellie, J., Milsom, B. and Henderson, E. (2012). Leadership through action learning: a bottom-​up approach to ‘best practice’ in ‘infection prevention and control’ in a UK NHS trust, Public Money & Management, 32(4), 289–​ 96. doi: 10.1080/​09540962.2012.691308 Klauer, B., Drechsler, M. and Messner, F. (2006) Multicriteria analysis under uncertainty with IANUS: method and empirical results, Environment and Planning C: Government and Policy, 24(2): 235–​56, doi: 10.1068/​c03102s

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Klenk, N.L. and Hickey, G.M. (2012) Improving the social robustness of research networks for sustainable natural resource management: results of a delphi study in Canada, Science and Public Policy, 39(3): 357–​72, doi: 10.1093/​scipol/​scs024 Libby, M.K. and Austin, M.J. (2002) Building a coalition of non-​profit agencies to collaborate with a county health and human services agency, Administration In Social Work, 26(4): 81–​99, doi: 10.1300/​J147v26n04 Liberati, A., Altman, D.G., Tetzlaff, J., Mulrow, C., Gøtzsche, P.C., Ioannidis, J.P.A. and Moher, D. (2009) The PRISMA statement for reporting systematic reviews and meta-​analyses of studies that evaluate health care interventions: explanation and elaboration, Journal of Clinical Epidemiology, 62(10): e1–​34. doi: 10.1016/​j.jclinepi.2009.06.006 Linder, S.H. and Peters, B.G. (1984) From social theory to policy design, Journal of Public Policy, 4(3): 237–​59, doi: 10.1017/​S0143814X0000221X Meier (2005) Public administration and the myth of positivism: the antichrist’s view, Administrative Theory and Praxis, 27(4): 650–​68. doi: 10.1080/​ 10841806.2005.11029511 Mintrom, M. and Luetjens, J. (2016) Design thinking in policymaking processes: opportunities and challenges, Australian Journal of Public Administration, 75(3): 391–​402, doi: 10.1111/​1467–​8500.12211 Mulgan, G. (2014) Design in public and social innovation: What works and what could work better, London: Nesta. Nelson, H.G., Stolterman, E. (2012) The design way: Intentional change in an unpredictable world, Cambridge: The MIT Press. OECD (2017) Embracing innovation in government: global trends 2018, Paris: OECD Publishing. Ostrom, V. (1974) The intellectual crisis in american public administration, Tuscaloosa, AL: The University of Alabama Press. Peters, B.G. (2018) Policy problems and policy design, Cheltenham: Edward Elgar Publishing. Radnor, Z., Osborne, S.P., Kinder, T. and Mutton, J. (2014) Operationalising co-​production in public services delivery: the contribution of service blueprinting, Public Management Review, 16(3): 402–​23, doi: 10.1080/​ 14719037.2013.848923 Rittel, H.W.J. and Webber, M.M. (1973) Dilemmas in a general theory of planning, Policy Sciences, 4(2): 155–​69, doi: 10.1007/​BF01405730 Ruano, J.M. (2015) Local strategic planning in Spain: a case study, Transylvanian Review of Administrative Sciences, 2015(2015): 71–​85. Sanders, E.B.N. (2005) Information, inspiration and co-​creation, In Proceedings of the 6th International Conference of the European Academy of Design, (Bremen: University of the Arts). Schott, S. (2013) Carbon pricing options for Canada, Canadian Public Policy, 39: S109–​24. doi: 10.3138/​CPP.39.Supplement2. S109 49

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Shangraw, R.F and Crow, M.M. (1989) Public administration theory as a design science, Public Administration Review, 49(2): 153–​60. doi: 10.2307/​ 977335 Simon, H.A. (1969) The sciences of the artificial, Cambridge, MA: The MIT Press. Steen, M. (2011) Tensions in human-​centred design, CoDesign, 7(1): 45–​60, doi: 10.1080/​15710882.2011.563314 Trischler, J. and Scott, D.R. (2016) Designing public services: the usefulness of three service design methods for identifying user experiences, Public Management Review, 18(5): 718–​39, doi: 10.1080/​14719037.2015.1028017 van de Kerkhof, M. (2006) Making a difference: on the constraints of consensus building and the relevance of deliberation in stakeholder dialogues, Policy Sciences, 39(3): 279–​99, doi: 10.1007/​sll077-​006-​9024-​5 Walker, R.M. (2011) Globalised public management: an interdisciplinary design science?, Journal of Public Administration Research and Theory, 21(S1): 53–​9, doi: 10.1093/​jopart/​muq064

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Challenges in applying design thinking to public policy: dealing with the varieties of policy formulation and their vicissitudes Michael Howlett

Introduction: policy formulation and the relationship between traditional policy design studies and ‘design thinking’ in the policy realm Policy design is an activity undertaken in the process of formulating policy options with an eye towards the effectiveness of subsequent implementation activity. It involves the conscious effort on the part of analysts and advisors to scrutinise, learn and apply lessons from best practices and past policy successes and failures to the crafting of policy alternatives which are expected to achieve government aims and ambitions in an efficient and effective way (Howlett et al 2009; Howlett and Mukherjee 2017; 2018). Policy design in this sense is thus only one of many possible types of policy formulation, one centred on knowledge generation and application in the creation of policy alternatives logically and experientially expected to attain specific government goals. It is not synonymous with formulation but is rather a variety of the latter. It can thus be thought of as a form of generating policy alternatives which goes about formulating policy options in a ‘design’ way: that is, as a calculated method of knowledge-​intensive problem resolution (Colebatch 2017; Howlett 2019). This is very different from other formulation techniques such as legislative bargaining, corrupt or clientelistic promotion of alternatives, promotion of schemes embodying partisan electoral advantage, or alternative generation centred on other non-​knowledge driven processes such as bureaucratic politics and budget maximisation or leader experiences and heuristics (Gans-​Morse et al, 2014; Chindarkar et al, 2017; Schneider and Ingram 2018). These latter processes are all equally efforts to formulate policy alternatives but do not resemble at all what is commonly meant by ‘design’ and hence are sometimes referred to as ‘non-​design’ (Howlett and Mukherjee 2014). 51

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It is also true, however, that ‘design’ can be undertaken in many different ways and policy studies must deal not only with design and non-​design formulation activities but also with the origins, evaluations and propensities of different design-​oriented formulation efforts. These range from top-​ down expert-​driven ‘technocratic’ planning exercises to more wide-​open public participation processes (Bason 2014; Howlett and Mukherjee 2017; Blomkamp 2018). The current literature on policy design, for example, features an ongoing debate between adherents of traditional approaches to the subject in the policy sciences who draw on early work on the subject by figures such as Linder and Peters (Linder and Peters 1987; 1988; 1990a; 1990b; 1990c; 1991) and those importing into policy-making the insights of design practices in other fields such as industrial engineering and product development: ‘design-​ thinking’. The former emphasises the complexity and difficulties faced by policy formulation given the situatedness and context-​ridden nature of policy advice and knowledge use, while the latter emphasises processes of re-​imagining problems, re-​casting solutions through ideation and developing, testing and refining policy ‘prototypes’ (Dorst 2011; Bason 2014; Chapter 1, this volume). This chapter examines both these two approaches to policy design from the perspective of the literature on the policy sciences and its aims and ambitions. It discusses the similarities and differences between traditional and more recent kinds of design thinking around policy formulation and implementation concerns and sets out a model of basic formulation types and the place policy design and ‘design thinking’ holds within them. As it shows, while both approaches are broadly similar in their rejection of non-​design based approaches to formulation, they differ in many important aspects, especially in the understanding they provide of the challenges faced by formulators in dealing not only with idea generation but also with the political and other issues involved in moving policy ideas into practice. In particular, it is argued that adherents of ‘design-​thinking’ in the policy realm need to expand their reach and consider not only how to generate novel ideas but also the lessons of more traditional approaches concerning the challenges which these ideas face in policy formulation, decision-​making and implementation.

Similarities in design approaches to policy-making: a common disdain for non-​design formulation processes Historically, the policy sciences have identified and engaged with several varieties of policy formulation, not all of which share a design-​orientation. In addition to knowledge-​based policy formulation, policy scholars have also studied other kinds of less knowledge-​or evidence-​centred policy-making 52

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activity, such as the common and oft-​observed situation where policy formulation emerges from processes such as legislative or executive bargaining and political trade-​offs, electoral competition and partisan manoeuvring (Howlett and Mukherjee 2014). Like design-​based activities in engineering and architecture, activities undertaken in design-​based policy formulation processes involve the collection and application of knowledge concerning the capabilities of the basic building blocks or materials with which actors must work in constructing a policy object; articulation of some principles regarding how these materials should be combined in that construction; and an understanding of the processes by which an object is constructed and the trade-​offs that often must be made in translating a plan into action (Schon 1984; 1988; Gero and Kannengiesser 2008; Howlett 2019). In general, most policy scholars prefer such design-​based formulation processes to non design-​based types as a knowledge-​based orientation is seen by most scholars and practitioners as critical to effective policy-making. This is because such processes embody the lessons learned from previous policy activities when a new policy is being developed or an old one reformed and thus are thought to be less likely to repeat past errors and failures (Turnbull 2017; Howlett 2019). Hence in whatever guise it is propounded, as either ‘traditional policy design’ or ‘design-​thinking’ or any other nomenclature, policy ‘design’ is espoused by its proponents, observers, practitioners and scholars as a preferable method of formulation to ‘non-​design’ ones. That is, knowledge-​based and analytical approaches to policy-making are thought to be more likely to achieve a successful resolution of a problem than more overtly political and less knowledge-​based and often inherently biased non-​design processes. These latter are thought to be more likely to promote unworkable policy alternatives, ones which are likely to mis-​specify targets and misunderstand policy target behaviour, devote governing resources to purely partisan or personal rather than programmatic ends, and in so doing fail to address the actual sources of a problem and match an effective solution to them (May 1981; Weimer 1992; Rose 1993; 2005; Grabosky 1995; Schneider and Ingram 1997; 2005; Gunningham and Sinclair 1999). Thus, in both the case of traditional policy design and design-​thinking, the ‘added-​value’ of design activity in the policy realm is the expectation that more policies will succeed in their aims, and fewer fail, the more good design principles and practices are followed in policy formulation and poor practices, and non-​design ones eschewed (Marsh and McConnell 2010; McConnell 2010; Howlett 2019). The disdain held towards non-​design formulation processes is true of traditional approaches to policy design in the field, which highlight the value of evidence-​based policy analysis over partisan wrangling in the generation 53

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of policy alternatives (Nutley et al 2007). It is also true of more recent efforts incorporating ‘design thinking’ in the policy realm, an approach which promotes a form of creative, innovative, policy formulation activity which is expected to allow problems to be approached in new or innovative ways (Dorst 2011; Bason 2014; Blomkamp 2018). Outside sharing this general ‘design’ orientation and a disdain for policy ‘non-​design’ efforts, however, as Clarke and Craft (2019) have also recently pointed out, traditional policy design and design-​thinking in the policy realm do not have very much in common. Several of their principle differences and their consequences are set out below. These include fundamental differences in how policy formulation is approached, whether or not innovation is considered to be the central or only goal of design activity, what their belief is in the value of expert-​vs public-​ driven design processes, whether or not they articulate clear principles for superior designs, and whether considerations of the barriers which design options face in decision-​making and implementation are incorporated into their analyses.

Differences between traditional policy design and design-​ thinking in public policy-making The level of self-​reflectiveness traditional policy design and design-​ thinking approaches have towards the understanding of policy formulation and the place of policy design within it One fundamental difference between the two design approaches relates to the extent to which each is conscious of its own role in the policy process and policy formulation vis-​a-​vis the other possible varieties of formulation cited above. It is not a universal certainty, for example, that all formulation at all times must or should proceed in a knowledge-​intensive ‘design’ fashion. Rather it may well be the case that formulation based on deep historical but idiosyncratic experiential knowledge of policy actors concerning past efforts to define problems and invoke solutions to them may be of more value in some circumstances, when reducing the information and knowledge needs of policy-making is important, such as due to unexpected turns of events or when policies need to be developed quickly (Tenbensel 2004). It is also the case that in some instances the need to legitimate policies leads to more partisan or electoral considerations trumping evidentiary ones which do not enjoy public support (Turnbull 2017). An approach to policy-making and policy formulation, especially a knowledge-​centric one, must be able to specify when and why such factors prevail and under what circumstances. It must be able to do so in order to properly assess its own role and the potential for implementable policy 54

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alternatives to emerge from its processes in any specific policy-making situation or context. Only the traditional approach to policy design in the policy sciences, however, has a wide-​enough lens on formulation activities to be able to assess its ability to develop feasible options in different design circumstances. That is, the traditional way of thinking about policy design in the policy sciences (Linder and Peters 1987; 1988; 1990a; 1990b; 1990c; 1991) clearly recognises and is built upon the understanding that there are a variety of formulation practices, each with its own proponents and vagaries, which can pose difficulties to the creation and adoption of knowledge-​driven plans and policies. This self-​reflection allows it to offer ways in which such limits can be incorporated or transcended in the design process, or not, as the case may be. This level of self-​awareness is missing in the design-​thinking approaches mooted to date. While they stress novelty, innovation and ‘outside the box’ consideration of policy alternatives, proponents of design-​thinking pay very little attention to concerns about the varieties of formulation and the problems each encounters, including how to deal with the political nature and implications of the workings of public policy formulation, decision-​ making and implementation processes (Clarke and Craft 2019). Different propensities to promote innovation over reform or other possible policy outcomes A second difference is contained in the preference each approach has for innovation or policy reform. ‘Design thinking’ is a kind of problem-​solving activity which its proponents advocate as a way to escape the ‘iron cage’ of past precedents in favour of the promotion of policy innovation (Dorst 2011). As set out by Dorst and others (Brown and Wyatt 2007; Dorst 2011), it self-​consciously involves reasoning backwards from the value expected to be created by a policy endeavour –​such as a new product in a manufacturing context or a new policy in a governmental one –​without being locked into the manner in which problems and solutions have been matched in the past. Efforts to promote such ‘design-​thinking’ in policy-making are very focused on this approach and give a great deal of attention to the articulation of techniques –​such as ideationism or prototyping –​which are intended to generate new ideas and thinking about old (and new) problems (Kimbell and Bailey 2017). Hence for its proponents ‘design thinking’ is synonymous with an open-​ ended re-​thinking of past practices and current problems. This typically involves the conscious effort to re-​frame problems and articulate innovative, ‘outside the box’, solutions to problems, often in an open participatory ‘co-​design’ setting (Dorst 2011; Blomkamp 2018; Bason 2014) which can 55

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be contrasted with the more bookish and historically-​oriented traditional design approaches. These latter approaches also consider innovation but argue that the circumstances which allow innovative policy alternatives to be successfully adopted and implemented are quite rare (Considine 2012; Howlett and Rayner 2013). More traditional thinking around policy design in the policy sciences is thus usually less concerned with innovation, per se, and more concerned with understanding how policy processes work in order to allow innovative alternatives to be articulated and adopted (Howlett 2019). This difference extends to the extent to which knowledge of past precedents and actions are judged to be useful in policy formulation, and the different levels of attention each pays to past lessons concerning the political and administrative feasibility of any alternatives generated in a formulation process, including a design one. The latter is a hallmark of traditional work in the policy sciences on the subject (Cavala and Wildavsky 1970; Meltsner 1972; Majone 1975) but is largely ignored in the ‘design-​thinking’ approach (Mintrom and Luetjens 2016). Hence, from a traditional policy design perspective, while design-​thinking may excel at the articulation of new approaches and ideas about policy problems and solutions, the form of (re)problematisation and invention which is characteristic of design thinking in many technological and creative spheres of activity –​from product to graphic design –​which adherents would like to see adopted in policy-making, is seen by adherents of traditional design approaches as capturing only a small part of the range of activities which go into the understanding and crafting of feasible policy alternatives (Meltsner 1972; Webber 1986; Meuleman 2010; Skodvin et al, 2010; Clarke and Craft 2019). Different beliefs in the virtues of expert vs popular participation in policy formulation Closely related to this point is a third important difference between the two approaches which has to do with the assumptions each makes about how best to go about design practices, however these are oriented. In the case of traditional design studies, a preference for expertise in information provision commonly leads to a preference for more closed, expert-​driven design processes than those espoused by proponents of design-​thinking and, especially, co-​design. This is because it is expected that experts have policy-​relevant knowledge which they can quickly identify and apply to the articulation of policy problems and solutions (Howlett 2019). In the case of ‘design-​thinking’, on the other hand, a distinct preference for more open, publicly-​driven processes is apparent and justified by the belief that expert-​driven processes are biased towards the status quo and filter out new 56

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evidence and knowledge which could contribute to innovative solutions (Blomkamp 2018). This is clear, for example, in the extent to which each approach considers detailed knowledge of the basic tools of public policy-making to be essential to effective formulation and implementation. The pioneers of traditional policy design research in the 1980s and 1990s, for example, argued that detailed knowledge of policy tools was highly significant to policy design (Schon 1984; 1988; Waks 2001; Barzelay and Thompson 2010). They argued policy design should involve detailed knowledge of the basic building blocks of policies with which actors must work in constructing an artifact such as a product or policy. For them, ‘policy instruments’ which involve the utilisation of state authority or its conscious limitation in the pursuit of government aims, are the basic techniques used in all policies and hence a major subject of policy design research and practice (Dahl and Lindblom 1953; Kirschen et al 1964; Edelman 1964; Hood 1986, Salamon 2002). Although traditional design studies in the policy realm remain firmly grounded in this belief (Howlett 2019), little of this literature is referenced by studies of ‘design thinking’ in the policy realm. As set out above, many design-​thinking formulation exercises rely instead on the expertise of crowds or the public in the hope that breaking down expert clusters and involving the public will help fashion innovative instrument alternatives (Blomkamp 2018). But the public, generally, has little knowledge of the wide variety of possible tools which can be deployed, what are the lessons that can be gleaned from their past use which are relevant in contemporary settings, or their technical strengths and weaknesses and merits and demerits vis-​a-​vis the possible deployment of other kind of tools either singly or in combination. As a result, although co-​design and a ‘design-​thinking’ orientation towards policy design may help transcend an excessive reliance of administrators and politicians on overly familiar or favoured tools, they can easily fall prey to the promotion of well-​known or popular ones or recommend infeasible or incompatible combinations and mixes of tools, defeating the entire purpose of an innovation-​centred design process (Moreno-​Jiménez et al, 2014; Bason and Schneider 2014).

Differences in the articulation and understanding of the principles behind policy tool choices and use As noted above, at least part of the purpose of any policy design approach to policy formulation involves the elaboration of a set of principles regarding how policy tools should be combined in the construction of policy portfolios. This is a complex question which requires due regard for the aesthetic, functional, historical, institutional and other factors which influence effective 57

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take-​up of policy tools and reduce compliance and non-​compliance costs (Howlett 2019). Again, this is an area upon in which many traditional policy design scholars work, developing a range of principles concerning how the elements in public policy programmes should be arranged. This involves, for example, promoting better knowledge of the strengths and weaknesses of specific kinds of policy tools and articulating criteria such as ‘coherence’, ‘integration’, ‘consistency’ and ‘complementarity’ in tool interactions which can guide designers in the preparation of policy options and alternatives (Grabosky 1995; Briassoulis 2005a; 2005b; Hou and Brewer 2010; Rogge et al 2017; Howlett 2018). Policy-​oriented economists studying the tools of government in the 1950s to the 1980s, for example, were concerned largely with the study of business–​government relations in the industrial sector and focused their efforts on better understanding the issues around mitigating the potential negative effects of state regulation and state-​based economic policy formation on business efficiency. These studies articulated a set of principles around tool deployment linked to the ability of specific kinds of tools to correct specific kinds of market failures (Zeckhauser and Schaefer 1968; Bator 1958; Breyer 1979; Wolf 1987; 1988; Le Grand 1991; Zerbe and McCurdy 1999; Howlett 2005). Careful examination of instruments and instrument choices taking these principles into account was expected to lead to allowing practitioners to more readily draw appropriate lessons from experiences with the use of particular techniques including, for example, when tools such as regulation and taxes could be used with positive effect and when not (Salamon 1981; Woodside 1986). Similarly, students of instrument choice in the 1990s–​2000s improved on these early models by introducing more complexity and subtlety into their analyses of policy instrument use and the principles and considerations around tool choices and policy designs. These studies expanded the analysis outside of the area of economic policy and into realms such as social and environmental policy-making. They highlighted the importance of contextual considerations such as the basis of support in society and government for particular kinds of tools in their analyses of the reasons why specific tool selections would be attractive to governments at specific times and why established tools and regimes, in general, would be difficult to change (Bressers and O’Toole 1998; de Bruijn and Hufen 1998; van Nispen and Ringeling 1998). More recently, scholars from the traditional school have focused on the use of multiple tools or ‘policy instrument mixes’ rather than upon single instrument choices (Gunningham and Young 1997; Gunningham et al 1998; Gunningham and Sinclair 1999; Flanagan et al 2011; Rogge and Reichardt

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2016) and have articulated a set of principles linked to their optimisation. Several key principles for effective policy designs emerged from this work such as, for example, the idea to be parsimonious not only in initially combining tools (Tinbergen 1952; Knudson 2009) but also dynamically or sequentially (Doern and Wilson 1974; Doern 1981; Tupper and Doern 1981; Doern and Phidd 1983). All of this work culminated in thinking around how to design ‘smart’ packages of tools which take these precepts into account (Gunningham et al, 1998; Gunningham and Sinclair 1999; Eliadis et al, 2005). Principles such as ‘consistency’ or the ability of multiple policy tools to reinforce rather than undermine each other in the pursuit of policy goals; ‘coherence’ or the ability of multiple policy goals to co-​exist with each other and with instrument norms in a logical fashion; and ‘congruence’ or the ability of goals and instruments to work together in a uni-​directional or mutually supportive fashion, all emerged as important measures of superiority in policy mixes (Howlett and Rayner 2007; Kern and Howlett 2009; Lanzalaco 2011). As pointed out above, however, studies of co-​design and ‘design-​thinking’ have not engaged at all with the tools literature and thus have also not addressed issues around the articulation of any principles which would allow identification of superior policy alternatives rather than just ‘innovative’ ones (Binder and Brandt 2008; Lee 2008; Donaldson 2018).

Problems in understanding policy feasibility and the constraints placed upon policy-makers and implementation of policy options A fifth significant difference between the two approaches concerns how they have dealt with issues around the feasibility of the proposals and designs which emerge from the design process. This relates to their understanding and incorporation of information on the manner in which policy alternatives become translated into reality and the barriers that exist between concept and realisation in public policy decision-​making and implementation as well as formulation, per se (deLeon 1988). The policy studies literature is replete with case studies and examples of the successful and unsuccessful implementation of policy designs which highlight the significance of this element (de Montis et al, 2016). Again, however, thinking and reflection about this aspect of policy-making is lacking in many design-​thinking or co-​design efforts which assume, whether explicitly to implicitly, that any combination of tools is possible in any circumstance (Clarke and Craft 2019). As proponents of more traditional approaches have argued, however, decision-​makers do not have unlimited degrees of freedom in their policy

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choices (Christensen et al, 2002). Determining how much room to manoeuvre designers have to be creative (Considine 2012) or, to put it another way, to what degree they are ‘context bound’ in time and space (Howlett 2019) is a key facet of policy formulation which traditional policy design studies has helped elucidate. Many empirical studies in the traditional policy design orientation, for example, have noted that the kind of full freedom in combining any and all design elements which is often pre-​ supposed by proponents of design-​thinking and co-​design is only found in very specific circumstances. These are the rare instances which Thelen (2003) terms ‘replacement’ or ‘exhaustion’ situations –​when older tool elements have been swept aside or abandoned and an opportunity exists for entirely new mix of tools to be designed or adopted de novo. Consideration of ‘goodness of fit’ between tool and governance context, for example, is another, related, contextual and process-​related concern which has been investigated and developed in traditional policy design studies (Brandl 1988). Work on ‘policy styles’ and administrative traditions (Kagan 2001; Richardson et al, 1982; Freeman 1985; Knill 1998; Howlett and Tosun 2019) have identified common patterns and motifs in the construction of typical policy designs in different jurisdictions reflecting such concerns (Kiss et al, 2013; Howlett 2004; 2019). It is argued such factors lead to distinct preferences for particular kinds of tools in particular jurisdictions and sectors, which heavily influence the kinds of policy alternatives which are preferred or likely to be adopted. Some of the reasons for this are historical and institutional in nature but others are capacity-​related. Different kinds of state activity require different capabilities on the part of state and societal actors, for example, and since different governance modes rely on these to greater or lesser degrees, policy designs must consider both the desired governance context and the actual resources available to a governmental or non-​ governmental actor if a policy alternative has any chance of being accepted or successfully implemented. Planning and ‘steering’, for example, involve direct coordination of key actors by governments, requiring a high level of government policy capacity to identify and utilise a wide range of policy tools in a successful ‘arrangement’ (Arts et al, 2006; Arts and van Tatenhove 2004). Imposing taxes, such as a carbon tax, for example, is another choice which requires high levels of government legitimacy which may or may not exist. Although proponents of design-​thinking have recently urged the creation of policy labs which can address some of these issues in field-​testing policy prototypes (McGann et al, 2018), their insights and findings have not yet affected design-​thinking approaches or methods for identifying and promoting specific kinds of designs in any kind of systematic way (Kimbell and Bailey 2017). 60

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Conclusion: the relationship between design thinking and policy design and the need for the former to consider the lessons of the latter Governments grapple daily with complex problems involving situations in which they must deal with multiple actors, ideas and interests in complex problem environments which typically evolve and change over time. This means that there is often a high level of uncertainty in policy-making and the modern policy studies movement began with the observation that public policy-making undertaken without effective policy formulation is unlikely to attain desired results in a cost efficient and effective way (Lasswell 1958; Stone 1988; Arts and van Tatenhove 2004). This conclusion has led to an emphasis on ‘design’ in the discipline, part of an effort to apply knowledge and analysis to the creation of policy alternatives in the expectation that these kinds of options will be more capable of resolving policy problems than alternatives arising from non-​design situations (Mintrom 2007). That is, situations in which these concerns are absent or over-​r idden by partisan and electoral advantage and other concerns. Both traditional design studies in the policy sciences and more contemporary efforts at co-​design and ‘design-​thinking’ are similar in that they share this general disdain for non knowledge-​based formulation. Both are efforts made in the attempt to avoid the unnecessary failures, expense and waste involved in less analytical and knowledge-​intensive forms of policy formulation. Both these approaches have proved fruitful in helping opening up the ‘black box’ of policy formulation, an activity which, although pivotal to policy-making, has not received its due share of attention (Howlett and Mukherjee 2017; Clarke and Craft 2019). But while the former is solidly entrenched in the studies and findings of the policy sciences, the latter represents the more recent effort to apply to policy formulation the kinds of product development processes which have been successful in other fields such as manufacturing and marketing but whose relevance to policy-making is less clear (Lindgaard and Wesselius 2017). Hence while both ‘design’ approaches to policy formulation can be clearly set apart from ‘non-​design’ ones, the two approaches differ greatly in their orientation to, and understanding of, policy formulation and policymaking more generally. As the other essays in this issue detail, these design approaches differ in terms of the extent to which they rely upon formal, technical analysis and other kinds of ‘crowd-​based’ or co-​design activities. However, as has been set out above, they also differ in the extent to which they are informed by extant knowledge of policy tools, their ability to uncover, articulate and apply principles of better policy design, and the degree to which their deliberations are informed by concerns around the 61

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political and administrative feasibility of the options which are generated in policy design processes. These distinctions are important and their implications deserve additional attention. That is, unless adherents of design-​thinking wish to serve only as ‘skunk-​works’ or idea factories which aim to generate innovative ideas without regard for their feasibility or appreciation of their likely implementation problems, they would do well to consider and incorporate the lessons of more traditional approaches about these subjects. These are lessons about policy tools, policy processes and the constraints on policymakers and policy advice which make possible, but also temper, the application of knowledge in policy-making and the potential of new ideas to successfully emerge from the policy process. References Arts, B. and van Tatenhove, J. (2004) Policy and power: a conceptual framework between the ‘old’ and ’new’ policy idioms, Policy Sciences, 37: 339–​56. doi: 10.1007/​s11077-​005-​0156-​9 Arts, B., Leroy, P. and van Tatenhove, J. (2006) Political modernisation and policy arrangements: a framework for understanding environmental policy change, Public Organization Review, 6: 93–​106. doi: 10.1007/​ s11115-​006-​0001-​4 Barzelay, M. and Thompson, F. (2010) Back to the future: making public administration a design science, Public Administration Review, 70(Supplement S1): s295–​97. doi: 10.1111/​j.1540-​6210.2010.02137.x Bason, C. (2014) Design for policy, farnham and burlington, VT: Gower. Bason, C. and Schneider, A. (2014) Public design in global perspective; empirical trends, In C. Bason (ed), Design for policy, Farnham and Burlington, VT: Gower, pp. 23–​40. Bator, F.M. (1958) The anatomy of market failure, Quarterly Journal of Economics 72(3): 351–​79. doi: 10.2307/​1882231 Binder, T. and Brandt, E. (2008) The design:lab as platform in participatory design research, CoDesign, 4(2): 115–​29. doi: 10.1080/​15710880802117113 Blomkamp, E. (2018) The promise of co-​d esign for public policy, Australian Journal of Public Administration, 77(4): 729–​43. doi: 10.1111/​ 1467-​8500.12310 Brandl, J. (1988) On politics and policy analysis as the design and assessment of institutions, Journal of Policy Analysis and Management, 7(3): 419–​24. doi: 10.2307/​3323721 Bressers, H.T.A. and O’Toole, L.J. (1998) The selection of policy instruments: a network-​based perspective, Journal of Public Policy, 18(3): 213–​ 39. doi: 10.1017/​S0143814X98000117

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Designing environments for experimentation, learning and innovation in public policy and governance Maurits Waardenburg, Martijn Groenleer and Jorrit De Jong Introduction Research on how the public sector can become more innovative and deliver public value more effectively and efficiently has proliferated over the past two decades (Borins, 2014). Most of this research focuses on innovations in policies and instruments. Moore and Hartley (2008) argue that an important but still understudied category is innovation in governance. Institutional arrangements for nominating complex public problems, developing multi-​agency responses and evaluating societal outcomes can themselves be innovations. Given the complexities of reconciling perspectives and interests across institutions and sectors, designing innovations in governance to achieve improved social outcomes is challenging (Bardach, 2001; Cels et al, 2012; Forrer et al, 2014). Ansell and Torfing (2014) highlight the importance of setting the right conditions for design processes in collaborative governance contexts. Working in collaborative governance arrangements requires much more attention to questions of composition, role and structure than in traditional government, where these questions are mostly settled and the focus is primarily on policies and instruments. It remains unclear, though, what conditions are conducive to the design of innovative governance arrangements, and how to create them. Recent design science research has advanced our understanding of the value of design thinking and using the design process for public policy innovations (Bason, 2010; 2017). Existing work tends to focus either on conceptual and theoretical explorations of design processes (Dorst, 2011; Howlett, 2014; Mintrom and Luetjens, 2016) or on case studies (Hillgren et al, 2011; Bryson et al, 2013). It does not formulate and test propositions about the conditions for effective design in today’s collaborative governance contexts. Simultaneously, collaborative governance theorists have explored conditions influencing the success of collaborative processes (Ansell and 72

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Gash, 2008; Emerson et al, 2012), but this work does not say whether these conditions are conducive for collaborative innovation engaged in policy design nor how to change these conditions in a dynamic design environment. Bason (2010: 19) claims that for public sector innovation, ‘random incrementalism still seems to be the rule rather than the exception. New thinking often happens by chance and against the odds, and the potential of a more conscious, strategic and systematic approach to innovation across public organisations and sectors is not realised’. Mintrom and Luetjens (2016: 399) confirm that ‘there are few empirical studies on actual use of design thinking ... in the private and public sphere’, let alone in new collaborative governance settings. This chapter aims to fill this gap by exploring, through empirical study, what a more general approach to designing environments for experimenting with, learning about and innovating in collaborative governance looks like. We answer the following question: How does one design an environment that creates the conditions that support collaborations in overcoming the most common challenges in their design process? To answer this question, we draw on the literatures on collaborative governance and design science in public policy and gain new insights by designing an environment for experimenting, learning and innovating ourselves: the Organised Crime Field Lab (OCFL). We launched the OCFL in collaboration with the Public Prosecution Service and the National Police in the Netherlands in 2014. Our objective was twofold: to facilitate practitioners in developing innovative solutions to ‘wicked’ crime problems, and to advance knowledge of the design features that enable or hinder effective collaboration. Between 2014 and 2017, a total of 18 multi-​agency crime-​fighting collaborations, and a total of 161 individuals, participated in the OCFL, including police officers, public prosecutors, tax inspectors, local and regional government officials and non-​state stakeholders (for example, an energy company fraud specialist). We provided these collaborations and individuals with training and coaching, which evolved over the years in content and form. Topics covered included the analysis of complex problems and stakeholder configurations, strategic public management, cross-​sector collaboration and leadership. Our methods were participant-​centred and discussion-​based, using customised teaching cases. With a five-​day intensive residential workshop at its core, the programme grew into a year-​long trajectory that started with a kick-​off day, followed by pre-​workshop preparatory meetings as well as post-​workshop reflection and progress review sessions. As an environment for learning, experimentation and innovation, the OCFL facilitated the design process of the 18 collaborations and generated significant qualitative and quantitative data. In a quasi-​experimental action research framework, we observed collaborations and surveyed and interviewed individuals about the challenges they encountered. We used 73

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this data both to improve our understanding of what facilitates and impedes collaboration, and to improve the design of the OCFL over the years. As such, we ourselves adopted a design approach, experimenting with and learning about the design features of the collaborative space that supports collaborations in their own design process. Design processes thus took place at two distinct levels of analysis: first, at the level of the 18 collaborations designing innovative crime-​fighting approaches and, second, at the level of the trainers, coaches and researchers in charge of designing and managing the OCFL as an environment for learning, experimentation and innovation. This chapter focuses on the latter level of analysis. We begin with a brief literature review on design processes and environments in collaborative governance contexts, then describe our research approach and present the origins, context and evolution of the OCFL design. Based on this, we formulate propositions on the conditions of the design environment that may support collaborative governance design processes. They include a problem-​solving space that allows for continuous iteration in practice and provides pre-​structuring of the problem-​solving process through frameworks and scaffolding; a facilitation process that includes future collaborators in problem definition and the selection of fellow collaborators and provides coaching on teaming practices; and an accountability structure that involves collaborators’ top management and immediate superiors, and that allows for reporting various types of progress, including progress in terms of learning. By putting forward conditions required for design work in novel collaborative governance settings, we make a fresh contribution to both the literatures on collaborative governance and design science in public policy.

Design in a collaborative governance context The notion of public administration as a multi-​disciplinary design science is not new. Simon (1996) referred to the management field broadly as an artificial science –​different from the natural sciences because problems and answers differ depending on manmade contexts. Shangraw and Crow (1989: 156) built on this idea: ‘Public administration ... draws knowledge from [other behavioural science fields], for the purpose of designing, constructing, and evaluating institutions and mechanisms for the public good.’ Nevertheless, over the past decades, both the concept of ‘design’ in public policy and the notion of ‘design science’ in public administration have been largely absent. Various explanations have been offered. Howlett (2014: 187) argues that in the 1990s and 2000s, design approaches to governance were neglected because ‘design’ was associated with blueprints and top-​down government, which seemed incompatible with conceptualisations of governance as a phenomenon of bottom-​up, emergent action in networks. 74

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Bryson et al (2013: 24) suggest that risk-​averse administrative cultures and structural barriers to experimentation have favoured traditional bureaucratic approaches. In recent years, however, the need to understand and advance the art and science of governance design has resurfaced. In many countries, trends toward decentralisation and privatisation raise new questions about how to coordinate between actors, sectors and levels of government and organise collective decision-​making around wicked societal problems. A design approach to collaborative governance, understood as a process of small-​ scale experimentation, learning by doing, and co-​creation of innovative solutions, might fit the dynamism and uncertainty of contemporary social and institutional challenges. Thus, a design thinking approach neither has to be top-​down nor risky, but can rather serve as a way to satisfy the increasing demand for governance design that is inclusive of stakeholders, consensus-​ oriented and deliberative, and mindful of the constraints and complexities inherent in the public sector.

Design processes for collaborative governance Recent literature has explored the question of what constitutes an effective policy design process in today’s ‘messy’ policy contexts. Mintrom and Luetjens (2016) describe five phases of policy design processes: first, empathetically observing the target group; second, exploring the problem; third, canvassing possible solutions; fourth, developing a prototype solution; and fifth, testing the prototype with the target group. The novelty of this design approach lies in the fact that it is user-​centred, non-​linear and iterative, and more comfortable with incompleteness, uncertainty and outside-​the-​box solutions. The goal is not to invent a superior policy design in one take, but rather to develop a Minimum Viable Product (MVP) in collaboration with users. There is no irreversible path from problem definition to solution, but rather a back-​and-​forth process between the ‘problem space’ and the ‘solution space’. The type of reasoning employed to draw conclusions from these iterative processes has also received renewed attention. In traditional policy design, inductive and deductive reasoning were the primary logics. Even when assumptions and data were dubious, value was attached to a theory of change grounded in such reasoning. In stark contrast stands the non-​linear, iterative process underlying design thinking in today’s policy context, which requires abductive reasoning. Abductive reasoning involves inferring explanations for phenomena from incomplete or uncertain premises (Dorst, 2011). It acknowledges the difficulty of gathering all relevant information at once and rather tests assumptions through rapid prototyping. To reduce randomness and increase the plausibility of inferences, researchers use methods to structure this process of testing assumptions, such as framing, environmental 75

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context scanning, collaborative inquiry and stakeholder mapping (Dorst, 2011; Mintrom and Luetjens, 2016). Theorists are also starting to explore design processes specifically for novel governance arrangements, as opposed to the design of single services or policies. For instance, Hillgren et al (2011) discuss the slow, iterative process of ‘infrastructuring’ new collaborative arrangements, which is significantly different in nature from the traditional fast-​paced design approach of single service or policy prototyping. Building on this, Bryson et al (2013) show how the iterative nature of design is critical in efforts to design solutions with and for citizens and external stakeholders. The fact that new governance arrangements include multiple stakeholders and that the issues are multi-​ dimensional and volatile necessitates multiple ‘rounds’ of consultation, deliberation and design.

Exploring the design environment While the process of designing public policy and governance has received some attention in the literature as discussed earlier, the notion of an environment for designing has been explored much less. In much of the literature there is an implicit assumption that such an environment simply exists. The process approach emphasises steps or phases, and actors or stakeholders, but does not articulate where the design work gets done, under what conditions, or how to create those conditions (Ansell and Gash, 2008; Sorenson and Torfing, 2011; Ansell and Torfing, 2014). We define the design environment as the setting, more or less consciously created and maintained, in which actors experiment, learn and innovate to establish institutional arrangements to govern the nomination of complex public problems, the development of multi-​agency responses, and the evaluation of societal outcomes. This understanding builds on what Ansell and Torfing (2014: 191) call the ‘interactive arena’, which includes, among other issues, the ‘policy objectives, actor composition, role positions and work form’ adopted to facilitate the design process in collaborative governance contexts. Our conceptualisation of the design environment concretises and extends this idea in two ways. First, it includes what actors actually design and the strategies they employ to overcome challenges. Second, it considers not only the internal interactive arena but also how external actors support collaborators in their design process. A systematic empirical exploration of what constitutes a design environment that creates the conditions for collaborations to address common design-​ process challenges has been lacking. There have been numerous conceptual studies exploring effective conditions for collaborative governance to thrive, including Ansell and Gash’s (2008) model of collaborative governance and Emerson et al (2012) integrative framework for collaborative governance. 76

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However, none of these studies has, actively explored interventions to affect these conditions for collaborative governance in a design process nor did they explicitly focus on collaborations engaged in design work themselves. Case studies of particular design environments, like explorations of policy labs by Bailey and Lloyd (2017) and Williamson (2015) do give us a starting point. For instance, Bailey and Lloyd suggest a number of conditions for effectively designing policy labs, including political and institutional embedding, mechanisms to overcome cultural inhibitions that hinder collaboration, and a format that encourages collaboration and progress. Yet, through reflecting on the iterative design process that shaped the OCFL, we seek to formulate a more general understanding of design environment conditions that enable experimentation, learning and innovation in governance.

A research design for design research on collaborative governance To fill the observed gap in the literature, we used a quasi-​experimental action research approach, applying it at the two levels distinguished before. First, through training and coaching, we supported collaborations designing innovative approaches to complex organised-​crime issues. Like other action researchers, we participated in a ‘change situation’, working not only to understand but also to improve problem-​solving capacity. Simultaneously, we studied the teams’ responses to different iterations of our design environment (the OCFL training and coaching programme we created). More like engineers or doctors than biologists or physicists, we worked by trial and error, interacting directly with the crime-​fighting collaborations under study, introducing and dynamically adjusting conditions in the design environment to test the impact of these changes on their design process. Our approach closely followed the design process described by Mintrom and Luetjens (2016). We ‘empathetically observed’ the collaborative governance challenges of our target group and designed a prototype design environment to help the collaborations overcome these challenges. We tested this prototype with the actual target group and adjusted it based on direct observations and feedback in practice. Because we were pursuing a clear value –​effective collaboration to fight organised crime –​without a hypothesis about precisely how to produce it, we relied predominantly on abductive reasoning, inferring different potential approaches to produce the sought-​after value from incomplete or uncertain premises. Our action research approach allowed us to experiment with different interventions to support the collaborations’ design process and to move beyond the theoretical explorations of the design process and single case studies that have dominated the literature on collaborative governance and 77

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design science. It also allowed us to do so at a stage when more stringent social-​science methods, such as randomised controlled trials, seemed premature or even futile, since no clear hypotheses about ideal environments for collaborative governance processes exist and collaborative governance seems too messy to randomise across. Finally, it made it possible to facilitate change while studying collaboration processes and their design environments, and to combine experimentation, learning and innovation –​both at the level of the collaborations and at the level of the OCFL.

Case selection The case of crime-​fighting collaborations in the Netherlands is representative of a broader set of collaborative governance efforts seeking to design new solutions for ‘wicked’ problems –​problems that are difficult to solve because facts about their origins and character are incomplete and norms about their solutions are contradictory and changing. Collaborations focused on solving wicked problems are themselves a subset of collaborative governance efforts, or ‘structures of public policy decision making and management’ that bring together stakeholders from all sectors ‘in order to carry out a public purpose that could not otherwise be accomplished’ (Emerson et al, 2012: 2). We selected the case of crime-​fighting collaborations for three reasons. First, there are many similarities –​and hence possibilities for generalisation or at least wider hypothesis testing –​between these collaborations and collaborations tackling wicked problems in other domains. As with similar challenges in the environmental and cyber-​security domains, for instance, these wicked problems have surfaced due to the increased interconnectedness and economic intensification the world is facing. Responses by single organisations have proven to be too one-​dimensional, sub-​scale and inadequate to deal with them. As such, problem-​oriented collaborations have formed around solving these issues in more multi-​faceted, systemic ways, for instance through energy sector transition strategies or common cyber-​ security standards across organisations. Such collaborations all face similar growing pains of working with new partners for the first time, attempting to innovate across each organisations’ capabilities to resolve issues that have emerged because of a changing global economic context. Second, as a practical matter, we had a high degree of access to these crime-​fighting collaborations and room to experiment with their design environment, given previous work with the involved stakeholders. Third, and perhaps most importantly, the urgency of the underlying issue of organised crime in the Netherlands led to a high level of political priority and commitment among the stakeholders, which allowed us to work with the collaborations over a relatively long period of time without significant losses in participation or level of activity. 78

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Data collection and analysis To understand the impact of our design environment on the collaborations’ design process, data collection and analysis followed a two-​stage process. First, we had to gather and analyse data on the collaborations’ design processes themselves, particularly the challenges collaborators encountered. Second, to answer our research question, we collected and interpreted data on the extent to which our interventions in the design environment created conditions that helped collaborations overcome those challenges. We used various techniques to gather data on the collaborations’ design processes and challenges. Observation of the collaborations in practice helped to identify challenges and responses. For every year-​long OCFL trajectory, we, the researchers, each spent at least seven working days with the collaborations, equal to roughly two-​and-​a-​half to five full days of direct observation per collaboration (depending on how many participated), or just above 60 days of direct observations in total. We also engaged coaches –​ experienced practitioners from the collaborating organisations who were not participating in the collaborations themselves –​to spend a similar amount of time with each collaboration, which provided us with another source of roughly 90 days of indirect observations in total across all the OCFLs. We also used interviews and surveys to dig deeper and ask participants directly about the challenges they experienced. We interviewed all of the collaborations once in their group setting during the five-​day workshop that was part of the OCFL (total of 18 group interviews) and surveyed the 161 individual collaboration members once during the same weeklong workshop and twice after the workshop week. Almost all collaboration members completed these surveys. Throughout the process, we gathered collaborations’ deliverables and communications to enrich our understanding of the work they were doing and the approaches they were designing. We asked the collaborations to submit a range of documents, from initial problem definitions to implementation plans and progress reports. We were also copied in most email correspondence among collaboration members, revealing detailed insights about the challenges and how they dealt with them. To track changes in our design environment and their influence on collaborations’ success in overcoming challenges, we logged every change we made in the OCFL and kept records of our deliberations around the reasons for making these changes. These deliberations included debrief sessions immediately after and in between formal sessions in the OCFL (kick-​off day, weeklong workshop, reflection sessions, progress review meetings) and evaluation and preparation meetings at the end and beginning of each year-​long trajectory. During these sessions, trainers, coaches, researchers and managers from the collaborating organisations shared observations and discussed the effects of changes to the programme. Subsequent iterations of 79

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the programme used learnings from these discussions to improve facilitation of the collaborations’ design processes further. We analysed the resultant data at two successive levels. First, the debrief sessions and meetings at the beginning, middle and end of the year-​long OCFL trajectory were themselves moments of analysis during which we not only reflected on how to improve the OCFL as a design environment, but also advanced our understanding of how to design a design environment that supports collaborations in overcoming common challenges in their design process. These resembled the open-​to-​learning conversations proposed by Mintrom and Luetjens (2016) as an effective design-​thinking strategy, questioning various elements of the OCFL as a design environment with a diverse set of individuals around the table. Second, we engaged in a final sense-m ​ aking process (Mintrom and Luetjens, 2016). After four OCFL trajectories had transpired, we synthesised our understandings of primary collaborative challenges and effective interventions in the design environment. We organised our observations, ‘physically, placing items that are related next to each other’ (Mintrom and Luetjens, 2016: 398). This allowed us to discover the (often complex) relationships between collaborations’ design processes and the results thereof, and between our interventions and the design environment.

Validity A key challenge for this approach is its internal validity. Using the tracking approach described earlier, we sought to trace the causal process and effects of certain interventions in the design environment. However, it was often possible to imagine several other explanations for observed changes in the collaborations’ design processes. Ensuring temporal proximity between changes in the design environment and observations of collaborations’ responses made it possible to establish a causal pathway for our observations with a higher degree of reliability. Herr and Anderson (2014) propose a number of other methods to safeguard internal validity for action-​research approaches. To ensure dialogic validity –​ essentially peer review in action –​we conducted reflection sessions not only among ourselves, but also with external practitioners and academics. In addition, extensive documentation helped ensure process validity –​recording findings carefully to allow ongoing learning and continuously looping back to refine earlier conclusions. External validity is another critical challenge for this type of action research. The generalisation of findings from an approach essentially relying on a set of case studies (the collaborations in the OCFL) may be problematic. Given the particularities of the case and its specific context, propositions would not necessarily be valid for all other cases and in other contexts. For example, 80

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the OCFL was replicated four times, but always in a specific local crime-​ fighting context to which the design was adapted. This affected certain OCFL features like the number, composition and size of collaborations participating and the most important collaboration obstacles to deal with, which depended in large part on the history of collaboration in a region. For instance, as explored later in this chapter, the focus on learning how to work together was much larger in earlier editions of the OCFL as many participants had not worked together before. Such particularities should be kept in mind when trying to generalise from this particular study. Nevertheless, there are insights to be gained for the design environments of other collaborative efforts dealing with wicked problems in the same or other domains. In our propositions, we heeded particular attention to draw insights across the four OCFLs we conducted, which makes the findings on particularly important features already more universal. In addition, rather than simply transplanting them, these insights should be tried and tested for the particularities of other cases –​an inherent feature of the very design process (Howlett, 2014), the subject of our exploration.

The evolution of the Organised Crime Field Lab Following the publication of a case study we wrote on innovation in the fight against human trafficking in the Netherlands, the chief prosecutor of the Dutch Public Prosecution Service inquired whether the approach might be applied in other areas. As scholars of cross-​boundary collaboration and public-​sector innovation, eager to study ‘innovation in action’, we agreed to co-​create a programme that offered training and coaching to aspiring innovators and an opportunity to learn while doing through action research (Waardenburg et al, 2018). The programme’s goal was to forge collaborations to fight organised crime through innovative methods. Programme participants would design collaborative approaches to specific, intractable organised crime problems. The idea was to look beyond arrests and prosecutions and identify ways to prevent and deter crime by thinking more strategically and systemically about the problem –​for example, by erecting barriers for criminals and putting pressure on individuals and organisations that (consciously or not) facilitate such crime. The general philosophy was to frustrate criminal processes as well as the social, economic and administrative infrastructure that enables them, and put the criminals out of business. This preventative approach required close collaboration between the Public Prosecution Service, the National Police and other organisations such as local and regional government and tax authorities. It demanded a new mindset and skillset for prosecutors, undertaking responsibilities and activities far beyond their traditional role in collaboration with different actors. 81

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Training and coaching programme (2014) The first edition of what would become the OCFL took place in 2014. Forty people participated in a five-​day workshop, each bringing a personal challenge to reflect on. The programme’s focus was training and coaching to equip public prosecutors, police officers and city officials with the skills to operate strategically and systemically in tackling crime. Conventionally, these professional groups receive training separately. This cross-​boundary programme, bringing together multiple professions around a societal issue, was a novelty. Before the workshop, we asked participants to write down their most pressing collaboration challenge, including a description of the substantive problem, the outcomes they were trying to achieve, the involved partners and their roles, and the roadblocks to effective collaboration. This resulted in a rich overview of challenges on which to build during the workshop. The workshop comprised highly interactive sessions around customised teaching cases relevant to several themes: analysis of wicked problems and stakeholder configurations, strategic thinking and acting, smart cross-​boundary collaboration and adaptive leadership. During discussions, we offered analytic frameworks to help examine practical problems and identify action alternatives. Workshop participants received guidance not only from us as trainers, but also from coaches from their own organisations. This support structure, however, ended after the workshop. Post-​workshop surveys showed significant variability in progress made on participants’ challenges. Those who made the most progress reported leaving the programme with a clearer definition of their substantive problem, better articulated goals and indicators of success, and a more focused strategy for accomplishing desired results. Those who made the least progress cited struggles to apply frameworks and define action alternatives in the short timeframe allotted and suffered from the lack of support structure after the workshop to make progress and implement what they had learned. While the participants and management of the organisations involved reported in evaluation surveys and debrief conversations that the first edition of the OCFL avant-​la-​lettre was helpful, we were concerned about the ‘real-​world’ impact. Would participants be able to apply lessons learned to innovate across organisational boundaries? What if we made application and collaboration more integral to the OCFL?

Towards an experimentation, learning and innovation environment (2015) Insights into collaborative governance challenges from the first edition of the OCFL helped us fine-​tune the curriculum for the second edition. Managing 82

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the expectations of participants and stakeholders became an important part of the work of creating the environment for learning, experimentation and innovation. Participants in the first edition tended to have a binary conception of ‘work’ and ‘training’. Echoing the sentiment of others, one participant explained that she ‘thought this was just a training. I didn’t know we actually had to do work as well’. The OCFL was intended to be both things at once, which to most participants was a new –​and sometimes confusing –​experience. For the second edition, we therefore made it clear that participants would not merely be taking a ‘course’; they would take part in a year-​long trajectory that brought their work into the classroom, organised on-​the-​job learning, and provided ongoing reflection and progress documentation. Instead of having the collaborating organisations select participants based on a variety of motives, we worked with the organisations to identify priority crime problems in need of innovative approaches and select and invite individuals who could work on them (but were not necessarily doing so already). For this, we partnered with the Task Force Brabant Zeeland, an initiative of the police, the public prosecutor’s office, the tax authority and local governments to stimulate collaborative efforts to fight organised crime in the southwestern part of the Netherlands. We trained and coached participants as members of eight collaborations to redefine their respective crime problems, develop a theory of change, take coordinated actions, and indicate for what kind of results they would like to be held accountable as a collaboration. See Table 4.1 for three examples of collaborations in the OCFL. There were two further structural changes in the training and coaching programme of the 2015 OCFL edition. First, we developed a structured working process over a nine-​month period, with designated activities and milestones along the way to support the collaborations including a kick-​off meeting several weeks before the workshop and frameworks and models employed to help collaborations proceed strategically and systemically. Second, we helped to create an accountability structure that involved the top-​level executives of each participating organisation working together to align their directives and mandates and check in on the collaborations and their progress through two progress review meetings. Despite these structural changes, designing an environment that facilitates progress in the collaborations’ design process turned out to be a complex challenge. Several participants expressed confusion about why their parent organisations had selected them, sometimes noting that they had never worked on the problem at hand. Interviews also revealed a lingering sense that this was a training on top of their work and expectations that teams would iterate their approach in practice after the workshop and report their progress were not sufficiently clear from the start. Additionally, because top-​level executives were far removed from field work, the accountability 83

Policy-Making as Designing Table 4.1: Examples of collaborations in the OCFL (Organised Crime Field Lab) Crime problem

Collaboration composition

Innovative approaches

Eradicating marijuana plantations in local neighbourhoods (OCFL, 2015)

Intimidation of and violence against citizens allured or forced into growing weed in homes; fire hazard from illegally constructed electricity supply

Public prosecutor, police, tax authority, local government, energy system operator

Using electricity network to pinpoint illegal domestic marijuana plantations in neighbourhoods; joint awareness campaigns to raise alertness and targeted enforcement in prone areas

Putting criminal entrepreneurs out of business (OCFL, 2016)

Entrepreneurs operating in the ‘grey zone’ with a network of (quasi-​) illegal business activities including brothels and drugs shops; disregard for the law and tax obligations, intimidation and extortion of citizens

Public prosecutor, police, tax authority, local government

Offering an opportunity for criminal entrepreneurs to ‘confess’ and stop illegal activities. If offer is not taken up, coordinated effort to make business operations unmanageable through stringent tax audits, blanket denial of permit requests, and other similar tools

Sabotaging Albanian criminal gangs (OCFL, 2017)

Criminal gangs using Amsterdam as logistics hub for drugs trade; violence and intimidation of other gangs as well as facilitators

Public prosecutor, police, tax authority, local government, Regional Information and Expertise Centre

Lifting the veil of anonymity for suspects through smart use of big data and collaboration with Albanian authorities; targeted enforcement actions against priority suspects –​ for example, checking legal status, tracing money laundering streams

structure designed contributed to participants not viewing collaborative work as part of their core daily tasks. Finally, our own observations revealed that basic collaboration challenges like trust-​building and teaming were among the most significant hurdles the collaborations experienced, an element we did not explicitly integrate in the earliest editions of the OCFL.

Adjusting and improving the design environment (2016–​2017) In 2016, the OCFL moved to the east of the Netherlands with adjustments to the design environment based on the previous edition. Expectations that OCFL work would continue beyond the week-​long workshop, during which the six participating collaborations designed their crime-​fighting approaches, 84

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were made more explicit upfront at the start of the OCFL: trainers instructed collaborations to test their approaches in practice and explained that progress would be monitored at pre-​planned intervals. A committee representing all stakeholders nominated problems and selected participants for six collaborations, paying more attention to whether participations were already working on the underlying issues (nonetheless, interviews revealed that not all were). For this iteration, we also introduced explicit training and coaching on collaboration practices. In addition, we organised a separate training session for middle management to ensure that they were aware of what OCFL work entailed and to help them see it as an integral part of their employees’ daily work. Middle managers also participated in the progress review sessions. These changes in the trajectory may be one factor that led to fewer observations and mentions (in surveys and interviews) of confusion around expectations, participant selection and accountability. Yet, some deeper-​seated issues lingered: participants still felt that the problem and participant selection were externally imposed, which may have been because the collaborations were more or less formed for the OCFL. In addition, we observed that collaborative process issues persisted despite explicit coaching on teaming –​most likely because these growing pains may be inevitable for any new collaboration. Finally, despite our efforts, middle management participation was not yet comprehensive and consistent throughout the trajectory. We took these lessons on-​board in the next edition of the OCFL we organised. In 2017 we worked with the Amsterdam and Rotterdam metropolitan regions in the OCFL West NL. Building on insights from the past OCFLs, potential participants selected crime problems in a more bottom-​up way, and at least some of the participants selected themselves around these problems. By selecting collaborators in four collaborations that were either emerging or already existent, we could, in theory, shift the focus from overcoming initial challenges like trust building to producing societal outcomes. In practice, however, we observed the usual collaboration challenges, suggesting that facilitating the collaborative process remains critical in any type of collaborative design environment, no matter how mature the collaboration. In its most mature form, our design environment approximated participants’ real-​life accountability environment, including the full involvement of middle management at all stages of the OCFL trajectory. Expectations were explicit from the start not only that collaborations would be required to iterate in practice and report their progress during the OCFL trajectory, but also that they would continue to exist after the final OCFL progress review sessions. Most participants reported in interviews that the OCFL was an integral part of their work and a welcome support in their efforts to find solutions to the selected crime issues. 85

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Between 2014 and 2017, the OCFL evolved from a workshop on smart collaboration into a design environment –​optimised over iterations –​to facilitate collaborations in the process of designing innovative solutions to wicked organised-​crime problems. It began as an externally-​imposed training and ended up a vital part of participants’ work, with many potential future participators seeking to enter their own collaborations into the trajectory. Getting results in practice evolved from a conceptual discussion point to the core of the programme. For a summary of adjustments and improvements, see Table 4.2.

Propositions for conditions that facilitate the collaborative design process In our design of the OCFL, we took steps in line with state-​of-​the-​art knowledge on effective policy design processes (Mintrom and Luetjens, 2016). We observed the initial ‘target group’ and the challenges they faced in collaboratively addressing organised crime. We explored possible solutions –​ from immersive training and coaching programmes to specific interventions such as introducing problem-​structuring frameworks and conducting teaming ­exercises –​while prototyping and testing these solutions as part of the OCFL. Rather than following sequential phases, our design process was highly dynamic. We proceeded in rounds, with our target group expanding and diversifying over time, and the crime problems becoming more rooted in practice. We tested solutions, such as introducing explicit accountability mechanisms, and tailored them to the needs of our target group, for instance by increasingly focusing on how to measure societal outcomes and account for collaborative performance. As in policy design processes, heavy user involvement, continuous iteration and outside-​the-​box thinking characterised our design of the design environment. By evaluating activities, results and participant experiences as well as organising feedback and brainstorming sessions with our partners, we developed a deeper understanding of learning needs, aspirations and constraints. Our iterations of the design environment over four years allowed us to experiment with and learn about the conditions that support collaborations in overcoming their collaborative governance challenges and engaging in collaborative innovation design. Contrary to the implicit assumptions in existing literature, environments for collaborations to design innovative solutions do not simply exist; they must be created and maintained. We thus consciously designed the OCFL as a setting in which collaborations and individual collaborators experimented, learned and innovated. Concretising and expanding existing notions of the setting in which the design process takes place, we explored a more concrete and extended conception of the design environment, specifying 86

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Table 4.2: Evolution of the OCFL (Organised Crime Field Lab) as design environment (2014–​2018) Field Lab East-​Netherlands (2016)

Field Lab West-​Netherlands (2017)

Number of participants/​teams

40 individual participants.

8 collaborations, comprising 41 individuals in total.

6 collaborations, comprising 44 individuals in total.

4 collaborations, comprising 36 individuals in total.

Focus of training and coaching

Concepts and cases in strategic management in collaborative governance settings.

Concepts and cases plus working in and shaping a real-​life problem-​ oriented collaboration to improve societal outcomes.

Concepts and cases, working on a real-​life collaboration plus increased focus on creative thinking and iteration in collaborative design.

Concepts and cases, working on a real-​life collaboration in an iterative design process plus increased focus on managing accountability relationships.

Structure of design process

Input: template for Input: template for team challenge; individual challenge; output: presentation with team, output: personal takeaways. takeaways and next steps. Two after-​programme progress review sessions.

Input: Detailed guide for the 9-​month design process with structured templates for deliverables for each step; output: multiple along the stages of the process, including a problem definition, approach presentation and several progress updates. Multiple check-​in points and stock-​taking sessions and coaching throughout on substance and process.

Selection of problems and participants

Participants selected by organisations based on merit and potential. Problems selected by participants.

Problems selected top-​ down by organisations; participants selected based on merit, potential and existing involvement with and responsibility for selected problems.

Problems selected by Task Force Brabant-​Zeeland; participants selected top-​down by organisations based on merit and potential.

Problems selected collaboratively and bottom-​up by organisations in consultation with participants. Selection of participants primarily based on involvement with and responsibility for selected problems. (continued )

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Field Lab South-​Netherlands (2015)

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Table 4.2: Evolution of the OCFL (Organised Crime Field Lab) as design environment (2014–2018) (continued) Condition in design environment Smart Collaboration Workshop (2014)

Field Lab South-​Netherlands (2015)

Field Lab East-​Netherlands (2016)

Field Lab West-​Netherlands (2017)

Facilitation of collaboration process

Participants part of temporary collaboration around Field Lab –​main focus was overcoming initial hurdles of setting up collaborations.

Participants part of longer lasting collaborations around Field Lab –​coaching on teaming practices explicitly introduced as core element of programme.

Individuals part of existing collaborative governance arrangements –​ focus on perfecting teaming practices.

Participants in workshop as individuals –​no active collaboration work in training.

Top management actively involved Top management involved as sponsor and accountability as sounding board for innovations mechanism; middle management involved as sounding by collaborations; OCFL still feels board; OCFL feels like more integral part of daily work. largely like ‘addition to daily work’.

Progress reporting mechanism

Not applicable.

Two progress review meetings designed and planned ad hoc with selection of high-​level representatives.

Research element

Participant evaluations and feedback and interaction with collaborating organisations informed research agenda.

Research becomes integral part of OCFL; research design and data-​collection are focused on documenting progress, understanding obstacles, and identifying enabling conditions for innovation in collaborative governance. Ongoing research feeds back into programme re-​design as OCFL uses action research and design thinking to learn about collaborative governance and optimise conditions for collaborative design in the design environment at the same time.

Multiple check-​in and stock-​taking meetings designed, planned and formalised with purposeful selection of high-​level representatives.

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Integration of OCFL in own Top management involved organisation and day-​to-​day work as sponsors; training feels like ‘addition to work’.

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what collaborations actually design and how they can be supported in this process through external facilitation. By thinking outside of the mould of existing institutional arrangements, we designed an environment that exists between rather than within formal organisational structures –​a kind of parallel context where the design work gets done. We went beyond the design process and questions of steps or phases, actors or stakeholders, to explore the conditions under which collaborations design innovative solutions, and how to create such conditions as part of the environment in which they design. The resultant design environment helped collaborations face the three most common categories of challenges collaborations face in their design process: substantive problem-​solving challenges, collaborative process challenges and multi-​relational accountability challenges (Waardenburg et al, 2020). We now discuss our findings and formulate propositions about the conditions under which collaborations design innovative solutions that can be tested in further research and inform practice along these three common categories of challenges faced by collaborations engaged in design work.

Conditions supporting substantive problem-​solving Substantive problem-​solving challenges comprise the technically and politically difficult work of defining the problem, developing an appropriate solution, and designing performance measures to determine whether the solution has been successful (Agranoff, 2007; Bryson et al, 2015; Head and Alford, 2015). Based on in-​g roup interviews and surveys on collaboration challenges across all OCFL trajectories, we found that defining the problem and finding appropriate approaches was consistently seen as the greatest challenge. This is partly inherent in the paradoxical nature of collaborative problem-​solving in the context of solving wicked societal problems, which requires simultaneous analysis and action to move closer to a solution. Through our iterations of the design environment, we found that sufficient space and time to experiment with solutions and obtain feedback from practice is critical. In the first edition of the OCFL, participants were asked to bring their own substantive challenges, but these challenges were a secondary element, and there were no mechanisms for real-​life feedback. In the following years, substantive problem-​solving around real-​ life crime problems in collaborative settings became an increasingly integral part of the trajectory. Feedback from trainers, coaches and superiors and experimentation in practice helped collaborators adjust their designs. In post-​workshop evaluation surveys, participants reported that these feedback mechanisms were among the core elements that brought the programme to life. This finding leads us to a first proposition, to be investigated in future research: 89

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Proposition 1: A design environment requires designated space and time to experiment with and prototype different approaches in order to obtain feedback from practice. Another condition of the environment that supported collaborations in their design process was a pre-​structured problem-​solving process. Within each of the collaborations, participants invariably had different perspectives on the problems at hand, how to solve them and how to measure progress. In collaborative governance settings, there are often multiple (sometimes competing) values to achieve, and these values may change along the way through the collaborative process of defining and redefining a ‘public value proposition’ (Moore, 2013). In the OCFLs, the crime-​fighting collaborations continuously shifted their perceptions of the optimal balance between repressive and preventative approaches and the scope of the problem they wanted to tackle. To facilitate this messy process, we increasingly sought to pre-​structure it by providing analytic frameworks and practical scaffolding in the form of questions, suggestions and templates for outputs around, for example, iterations on problem definitions, solutions and implementation plans, and performance reports. A second proposition highlights the importance of frameworks and scaffolding: Proposition 2: When problems and solutions are not clear, and there is a lack of consensus around substance, structuring the substantive problem-​solving process through frameworks and scaffolding may help collaborations progress and support their design process.

Conditions supporting the collaborative process Collaborative process challenges pertain to reconciling the perspectives and interests of partners and building trust (Ansell and Gash, 2008; Provan and Kenis, 2008; Emerson et al, 2012; Bryson et al, 2015). As described by Hillgren et al (2011), this process of ‘infrastructuring’ new collaborative governance arrangements is messy and complex. The involvement of many different (and sometimes new) actors may improve the response to the problem at hand, but sacrifices efficiency and complicates coordination. In the OCFL, we were able to facilitate and observe the collaborative process over time, with participants facing consecutive challenges of initial trust-​building, building shared objectives and taking collaborative actions. Unfortunately, a year was still too short to see the full development of the collaborations’ potential. Some collaborations finally secured results after we had left; some continue to work together today. Nevertheless, we were able to glean some insights for the conditions that the design environment should create.

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First, over the course of the OCFL trajectories, the importance of the initial collaboration conditions became clear. In contrast to traditional policy design settings, which are often stable and known, the design setting in a collaborative governance context is characterised by dynamic problems and unfamiliar partners. In the first two Field Labs, when individual participants brought their own problems (2014) or were selected rather independently from problems (2015), they were sometimes reluctant to participate in the collaborative design process –​likely because they saw this as extra work externally imposed on them. For this reason, by the third Field Lab, we started to embrace a bottom-​up approach centred on selecting collaborative governance problems that most participants were at least somewhat involved in solving and allowing for more participant self-​selection. This removed a major source of inertia, which is one possible explanation for why collaborations moved to action much more quickly and consistently in the third and fourth OCFLs than in the first two. From this finding follows a third proposition: Proposition 3: Building the initial design environment from the bottom up –​ including future collaborators in problem selection and definition as well as the selection of ultimate collaboration participants –​is critical to ensure buy-​in among collaborators and progress on designs. Second, facilitation of the teaming process was also revealed as an important condition of the design environment. In the first two OCFLs, we focused most of our attention on the substantive problem-​solving challenges that collaborations struggled with. However, it became obvious that many of the challenges the collaborations were experiencing were not rooted in an inability to resolve content problems, but rather in an inability to overcome typical teaming hurdles, such as building trust, managing process and aligning perspectives. As a result, in the third and fourth OCFL, we explicitly introduced training on teaming, co-​facilitation by coaches and mediation where necessary. This investment upfront helped collaborations to surface and deal with their teaming challenges early on in the design process. This finding is in line with Howlett’s (2017) suggestion that procedural elements of the design environment are just as critical as substantive elements in today’s policy context. This leads us to a fourth proposition: Proposition 4: As part of the design environment, it is critical to provide external facilitation of the collaborative process, including coaching on teaming practices, in addition to facilitating the substantive problem-​solving process of collaborations engaged in design.

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Conditions supporting accountability relationships Multi-​relational accountability challenges are difficulties collaborations experience in reporting to new channels of accountability, including to other organisations and society at large, that exist in tension with old channels of accountability (Moore and Hartley, 2008; Moynihan et al, 2011; Bryson et al, 2015). In the OCFL, individual collaborators had to account for their progress and performance not only to their own superiors, but also to superiors from the other organisations involved, as well as the political arena. Accountability challenges were not a central component of the first OCFL edition, but accountability structures were introduced in the second edition to incentivise progress. Yet, the second edition did not make accountability expectations explicit from the start and participants were asked to report to top management without involving their immediate supervisors. This only heightened the sense that the OCFL work was an extra burden. As such, we started to involve middle management in periodic progress review discussions and organised separate training sessions for them in the third edition. This established much clearer incentives for participants to invest in the programme, leading us to a fifth proposition. Proposition 5: As part of the design environment, it is critical to involve the immediate superiors of collaborators in periodic progress review discussions and the broader design process to ensure that the design process is not seen as something external to collaborators’ daily tasks. The second key condition in relation to accountability structures that we identified is closely related to the first condition for substantive problem-​ solving processes. Collaborators need wide discretion for testing and prototyping. Prototyping may take longer in collaborative governance settings that require a broad range of actors to coordinate their actions. Moreover, these actors may pursue various values and have different interpretations of progress. As such, results in practice may take longer to materialise, and reporting mechanisms may need to allow for various interpretations of progress. This was evident when collaborations secured results well after the OCFLs had ended –​including some that had looked close to giving up. Their approaches and results often looked markedly different from the approaches and intended results they had initially designed in the weeklong workshop. To accommodate for this, in the second, third and fourth Field Labs, progress review meetings were extended after the OCFL trajectories had ended. In addition, in the third and fourth Field Labs, expectations of a long-​run trajectory with frequent pre-​planned progress review meetings were made 92

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more explicit to the participating collaborations from the start. This finding leads us to a final proposition for future research: Proposition 6: To encourage collaborations to make progress in their design process, progress review meetings are essential, but the evaluation of progress should allow for various interpretations of progress and take into account that collaborative design processes may take longer to unfold than traditional design processes focused on single products or services.

Conclusion In this chapter, we set out to answer the following question: How does one design an environment that creates the conditions that support collaborations in overcoming the most common challenges in their design process? To do so, we reviewed the relevant literature on design in public policy and governance, and we presented the experimentation, learning and innovation environment we designed ourselves: the Organised Crime Field Lab (OCFL). Despite experimentation in practice with policy design in collaborative governance settings, the environment in which policy design processes take place has received relatively little attention in the academic literature. There is an implicit assumption in most academic work on policy design that the environment simply exists and does not need to or cannot be manipulated. Ansell and Torfing (2014), like other governance theorists, do refer to the concept of the ‘interactive arena’ in which collaborations work and operate, but empirical explorations of how to actively shape such a design environment that creates the conditions for collaborations to address common design process challenges have been scarce. Case studies of particular design environments like the explorations of policy labs by Bailey and Lloyd (2017) and Williamson (2015) provide a first stepping stone. The OCFL allowed us to experiment, learn and innovate with a design environment that is conducive to overcoming common challenges in collaborative design processes. We identified several conditions that flow from the design environment and may support collaborative design processes: first, a problem-​solving space that 1) allows for continuous feedback and a lot of iteration in practice, and 2) provides pre-​structuring of the problem-​solving process through frameworks and scaffolding; second, a facilitative process that 3) includes future collaborators in problem selection and definition as well as the selection of fellow collaborators and 4) addresses the collaborative process, including coaching on teaming practices; finally, an accountability structure that 5) involves not only the collaborators’ top management but also their immediate superiors to ensure the design process is seen as part of their daily work and 6) offers sufficient time, discretion and flexibility to 93

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account in different ways for various types of progress, including progress in terms of learning. We gained a number of more general insights from the design process we undertook. First, setting up a design environment, like policy design itself, is an iterative process. Iteration in practice helped us to recognise the importance of certain conditions of the design environment, such as team creation from the bottom up and facilitation of the team process, which we had initially left out of our design. Second, optimising a design environment requires customisation to the local policy context. For example, we had to adjust for local differences when selecting crime problems and participants and adjust our focus on particular collaboration challenges depending on the history of collaboration in each area. Finally, our work revealed that the facilitation of innovative designs for collaborative governance requires a lot of time and patience, given collaborators’ unfamiliarity with this novel way of working. This chapter helps to advance the field by contributing an understanding of how to best influence known conditions for effective collaboration, rather than being passive observers of this phenomenon. As explained, this requires a consciously developed design environment, including coaching, scaffolding and feedback loops. It also views collaborative governance arrangements through a new lens of design science. This allows the field to move past the conceptualisation of governance as a phenomenon of bottom-​up, emergent action in networks that can only be observed from afar, to an active concept of collaborative governance as part of which a multiplicity of actors can be supported in their plight to design new policies. The significance of this lies at the very roots of the notion of public administration as a design science: seeking to ‘design, construct, and evaluate institutions and mechanisms for the public good’ (Shangraw and Crow, 1989: 156). Ultimately, this chapter points at mechanisms to effectively engender problem-​oriented collaboration to minimise public value losses from emergent challenges like networked, organised crime. Our research presents a first step in a systematic empirical exploration of key conditions of the design environment for collaborative governance. Limitations are inherent in the nature of the case study approach we adopted. Remaining questions include the following: was a yearlong cycle long enough to reach conclusive answers and might additional cycles of experimentation lead to a deeper and more granular understanding of conditions for effective collaborative design? Would replication of the research design in other institutional, cultural, geographic and policy contexts lead to different observations and conclusions? Testing the propositions that our research generated in other contexts, and over a longer period of time, through comparative analysis and longitudinal research, would be helpful in moving this field of study forward. Finally, once there is triangulated evidence 94

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from different contexts that certain design environment conditions are critical to enable innovative governance design, this could be further tested in more standardised experimental settings with an actual control group. If it is true that pressing public problems require both innovation and cross-​ boundary collaboration, we have to face the fact that the academic literature provides little guidance with regards to how this type of work might be supported, guided and governed. The contribution of our research lies in the way it approaches both the practical challenge of designing environments to do the work and the opportunity to learn from the process as it unfolds. As such, it brings together public policy and design science in an attempt to advance the art and science of public problem-​solving. References Agranoff, R. (2007) Managing within networks: Adding value to public organizations, Washington, DC: Georgetown University Press. Ansell, C. and Gash, A. (2008) Collaborative governance in theory and practice, Journal of Public Administration Research and Theory, 18(4): 543–​71. doi: 10.1093/​jopart/​mum032. Ansell, C. and Torfing, J. (2014) Public innovation through collaboration and design, New York, NY: Routledge. Bailey, J. and Lloyd, P. (2017) The introduction of design to policymaking: policy lab and the UK government, Annual Review of Policy Design, 5(1): 1–​14. Bardach, E. (2001) Developmental dynamics: interagency collaboration as an emergent phenomenon, Journal of Public Administration Research and Theory, 11(2): 149–​64. doi: 10.1093/​oxfordjournals.jpart.a003497 Bason, C. (2010) Leading public sector innovation: Co-​creating for a better society, Bristol: Policy Press. Bason, C. (2017) Leading public design: Discovering human-​centred governance, Bristol: Policy Press. Borins, S.F. (2014) The persistence of innovation in government, Washington, DC: Brookings Institution Press with Ash Center for Democratic Governance and Innovation. Bryson, J.M., Quick, K.S., Slotterback, C.S. and Crosby, B.C. (2013) Designing public participation processes’, Public Administration Review, 73(1): 23–​34. doi: 10.1111/​j.1540-​6210.2012.02678.x. Bryson, J.M., Crosby, B.C. and Stone, M.M. (2015) Designing and implementing cross-​sector collaborations: needed and challenging, Public Administration Review, 75(5): 647–​63. doi: 10.1111/​puar.12432. Cels, S., de Jong, J. and Nauta, F. (2012) Agents of change: Strategy and tactics for social innovation, Washington, DC: Brookings Institution Press. Dorst, K. (2011) The core of ‘design thinking’ and its application, Design Studies, 32(6): 521–​32. doi: 10.1016/​j.destud.2011.07.006.

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Emerson, K., Nabatchi, T. and Balogh, S. (2012) An integrative framework for collaborative governance, Journal of Public Administration Research and Theory, 22(1): 1–​29. doi: 10.1093/​jopart/​mur011. Forrer, J., Kee, J. J. and Boyer, E. (2014) Governing cross-​sector collaboration, San Francisco, CA: John Wiley and Sons. Head, B.W. and Alford, J. (2015) Wicked problems: implications for public policy and management, Administration and Society, 47(6): 711–​39. doi: 10.1177/​0095399713481601. Herr, K. and Anderson, G.L. (2014) The action research dissertation: A guide for students and faculty, Thousand Oaks, California: Sage publications. Hillgren, P.A., Seravalli, A. and Emilson, A. (2011) Prototyping and infrastructuring in design for social innovation, Codesign-I​ nternational Journal of Cocreation in Design and the Arts, 7(3–​4): 169–​83. Howlett, M. (2014) From the ‘old’ to the ‘new’ policy design: design thinking beyond markets and collaborative governance, Policy Sciences, 47(3): 187–​ 207. doi: 10.1007/​s11077-​014-​9199-​0. Howlett, M. (2017) Policy tools and their role in policy formulation: dealing with procedural and substantive instruments, Handbook of Policy Formulation, Cheltenham: Edward Elgar, pp 96–​111. Mintrom, M. and Luetjens. J, 2016, Design thinking in policymaking processes: opportunities and challenges, Australian Journal of Public Administration, 75(3): 391–​402. doi: 10.1111/​1467–​8500.12211. Moore, M. and Hartley, J. (2008) Innovations in governance, Public Management Review, 10(1): 3–​20. doi: 10.1080/​14719030701763161. Moore, M.H. (2013) Recognizing public value, Cambrige, MA: Harvard University Press. Moynihan, D.P., Fernandez, S., Kim, S., LeRoux, K.M., Piotrowski, S.J. and Wright, B.E. and Yang, K. F. (2011) Performance regimes amidst governance complexity, Journal of Public Administration Research and Theory, 21: i141–​i155. doi: 10.1093/​jopart/​muq059. Provan, K.G. and Kenis, P. (2008) Modes of network governance: structure, management, and effectiveness, Journal of Public Administration Research and Theory, 18(2): 229–​52. doi: 10.1093/​jopart/​mum015. Shangraw, R.F. and Crow, M.M. (1989) Public administration as a design science, Public Administration Review, 49(2): 153–​8. doi: 10.2307/​977335. Simon, H.A. (1996) The sciences of the artificial, Cambridge, MA: MIT Press. Sorensen, E. and Torfing, J. (2011) Enhancing collaborative innovation in the public sector, Administration and Society, 43(8): 842–​68. doi: 10.1177/​ 0095399711418768. Waardenburg, M., Groenleer, M., de Jong, J. and Bolhaar, H. (2018) Evidence-​based prevention of organised crime: assessing a new collaborative approach, Public Administration Review, 78(2): 315–​17. doi: 10.1111/​ puar.12889. 96

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Waardenburg, M., Groenleer, M., de Jong, J. and Keijser, B. (2020) Paradoxes of collaborative governance: investigating the real-​life dynamics of multi-​ agency collaborations using a quasi-​experimental action-​research approach, Public Management Review, 22(3): 386–407. Williamson, B. (2015) Governing methods: policy innovation labs, design and data science in the digital governance of education, Journal of Educational Administration and History, 47(3): 251–​71. doi: 10.1080/​ 00220620.2015.1038693.

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Policy Labs: the next frontier of policy design and evaluation? Karol Olejniczak, Sylwia Borkowska-​Waszak, Anna Domaradzka and Yaerin Park Introduction Policy labs have been emerging all over the world with a mission to support policy practitioners with innovative solutions, grounded in empirical research. This trend started less than a decade ago (Price, 2015; Tõnurist et al, 2017), and a recent study has identified 78 policy labs in the European Union alone (Fuller and Lochard, 2016). While the idea of policy labs has gained considerable popularity, the term tends to be applied to different activities and approaches. This could be explained by the diverse strands that have provided methods for labs, such as design thinking, behavioural insights, collaborative governance and social entrepreneurship. This lack of a coherent typology of labs limits the possibility of comparing their operations and outcomes for academic and practical purposes. The emerging practices of policy labs claim to bring promising innovations to the public sector. However, it remains unclear to what extent these varied practices provide truly new ways of addressing the challenges that have already been identified by existing public policy routines. This chapter addresses the problem by looking at policy labs from the perspective of a well-​established evaluation practice (Scriven, 1977; Chelimsky, 1985; Shaw et al, 2006; Newcomer et al, 2015). Evaluation has been systematically developing since the 1960s, accompanying subsequent waves of public programmes and becoming a standard of modern public management around the world (European Commission, 1995; OECD, 1998; Furubo et al, 2002; Jacob et al, 2015; Bohni et al, 2018). It has a dynamic worldwide community covering all policy fields, with numerous international, national and even regional associations across the world (for example, American Evaluation Association, European Evaluation Society, Australasian Evaluation Society) and its own highly respectable journals (for example, American Journal of Evaluation, Evaluation, Evaluation and Programme Planning). In order to underline the importance of evaluation practice for evidence-​informed public policies and social betterment, the

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year 2015 was celebrated as an International Year of Evaluation (United Nations Evaluation Group, 2013). Over the years, three broad challenges have emerged from global evaluation practice in relation to its contribution to public policies: • Establishing what solutions work highlights the need of verifying the causal relation between public interventions and observed changes, and making a fair judgement about their value. This provides public policy with accountability for executed programmes, and indicates which interventions are worth financing in the future. • Explaining why solutions work (or not) covers approaches and methods that provide insights into the complex nature of mechanisms responsible for socio-​economic change. An understanding of these mechanisms enables the designing of more effective interventions. • Transferring research findings into policy actions focuses on bridging the gap between the extensive production of policy studies and their limited utilisation in decision-​making processes. Resolving this issue could substantially strengthen evidence-​informed policies. This chapter challenges the emerging practice of policy labs, by addressing the following question: What possible synergies between evaluation practice and policy labs could help in addressing the three challenges of public policy: establishing what interventions work, explaining their change mechanisms, and using research findings? For this purpose, we analyse the functions, structures and processes of 20 well-​established policy labs from Western Europe, North America, South America, Australia and Asia. The comparative, deductive content analysis covers grey literature, documents and web content on lab activities, as well as records from the analysed sample of policy labs. The chapter consists of five parts. The next section provides a literature review explaining in more detail the nature of each of the aforementioned challenges of public policy that have emerged from evaluation practice. Section three provides the method of case study selection and the analytical framework used for reviewing and synthesising policy lab operations. Section four presents findings on the labs’ functions, structures and their processes. These findings are confronted with the three challenges identified by evaluation practice, leading to a discussion of the possible advantages gained from synergies between evaluation inquiry and policy labs. The final section summarises the conclusion and indicates areas for further research.

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The chapter advances our understanding of the synergies between policy labs and evaluation practice that could enhance evidence-​informed policies. We find that policy labs are not an alternative development to established practices of public policy. They are rather a promising addition. The structures, functions and processes of policy labs can help to address evaluation challenges mainly related to explaining why solutions work (focusing on users, unpacking behavioural change mechanisms, building and testing solutions in iterative REACT process) and translating research findings into decision-​making (involving policy stakeholders and providing platforms for safe learning through experimentation). At the same time, policy labs may benefit from evaluation theory and practice in gaining a deeper understanding of challenges that relate to establishing what works, as well as valuing public interventions, incorporating systems thinking and complexity, and scaling-​up solutions. We believe that these synergies, when turned into an exchange of practices, could eventually enhance the effectiveness of public policies.

Challenges emerging from evaluation practice Evaluation practice is an integral element of the policy process, which can be characterised as a series of stages of problem solving (from framing the policy issue, through development of solutions, selection of tools, implementation, to final assessment of effects) (Weiss, 1999; Howlett, 2011; Colebatch and Hoppe, 2018). Evaluation on the one hand ensures the accountability of public investments, and on the other, it enables learning and therefore the improved utility of public interventions over time (Chelimsky, 1997; Mark et al, 2000; Newcomer et al, 2015). Single evaluation inquiries can be oriented on different functions, such as improving interventions planning, increasing the technical quality of performance, improving accountability, strengthening internal organisational capacities, enhancing ownership among stakeholders, or even empowering marginalised groups (Batterbury, 2006; Mertens, 2008). However, the ultimate goal of evaluation is ‘social betterment’ through policy learning (Henry et al, 2003), since evidence-​informed interventions are likely to be more effective in serving citizens. At the level of everyday management practices, evaluation is defined as the use of a diverse spectrum of socio-​economic research methods for systematic inquiry of the worth and merit of public interventions. It includes data collation, analysis, interpretation, assessment and dissemination of results (Patton, 2004; Mathison, 2005). Evaluation inquiries are executed by independent teams of social science researchers who follow ethical and methodological standards. The evaluation tasks are often assigned to designated teams of public professionals called ‘evaluation units’ who either 100

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execute studies by themselves, or commission studies and convey their findings to the institutions responsible for planning and implementing policies. Evaluation practice has systematically developed since the 1960s, starting in the United States in response to the Great Society initiative. The large-​ scale federal programmes were coupled with a mandate for evaluation, often conducted in the form of pilot programmes and experiments (Patton, 2004) –​ similarly to policy labs today. Evaluation activities grew in popularity in the 1970s as part of the toolbox for rationalising public expenditures in the era of crisis. The performance-​based management promoted by the OECD, World Bank and European Union made monitoring and evaluation a standard of modern public management. This further disseminated evaluation practice across the world (Derlien, 1990), although the policy scope and institutional embedding of evaluation vary across countries (Furubo et al, 2002; Jacob et al, 2015). As the theory and practice of evaluative inquiry have advanced over the years, a number of challenges and major issues for debate have emerged. Alkin (2013) summarises these developments in the form of an evaluation tree. He identifies the shared roots of accountability, control and social inquiry, and then points out three branches: challenges in the philosophy of valuing, methodological issues, and the use of evaluation (Alkin, 2013). So far, this evaluation tree constitutes the most comprehensive attempt to map evaluation challenges; however, it focuses mainly on theoretical developments, and is largely US-​centric. A more practice-​oriented approach has been encapsulated by the so-​called evaluation realists, who articulate evaluation challenges in the form of a mission statement. Evaluation aims at establishing ‘What works, for whom and in what context’ (Pawson and Tilley, 1997). The first part of the question refers to the outcomes and measures of success. The other two search for mechanisms triggered by interventions in a target population and in a certain environment. In time, this question was linked to a broader evidence-​based policy movement (Pawson, 2006; Davies et al, 2009; Shillabeer et al, 2011). Following these debates, we have organised the evaluation challenges discussed in this chapter around three issues: establishing what policy solutions work, explaining why solutions work (or not), and transferring those research findings into policy actions. We discuss them in more detail in the next subsections.

The challenge of establishing what solution works Value assessment of policy intervention through appropriate evaluation methods and practices has been at the centre of interest of both theorists and practitioners of public policy (Alkin, 2013; Dunn, 2017; Wildawsky, 2017). It is important for public policy because it provides accountability 101

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for executed programmes, and indicates which interventions are worth financing in the future. There are two main limitations of assessing the value of policy interventions. The first is the causality issue –​the relation between an implemented solution and the observable change. Causality can be approached from various stances, such as the successionist, configurationist and generativist perspectives (Ray Pawson’s classification discussed in Stern et al, 2012). While the successionists focus on analysing the direct association between a treatment and an observed outcome, the configurationists pay attention to the attributes that lead to variations in outcomes, and the generativists focus on identifying the supporting factors underlying an observed causal relation (Stern et al, 2012). In evaluation practices, researchers are expected to adopt various analytical approaches and designs depending on the causality stances and modes they intend to advocate. The second challenge is related to the politics of valuing interventions, namely establishing evaluation criteria and reference points. The key criteria used in the assessment of public policy programmes and interventions include utility, legality, transparency, effectiveness, efficiency and sustainability (Olejniczak and Mazur, 2014). Depending on the criteria used, different pictures of policy outcomes emerge. Evaluators are aware of this issue, and they are cautious about clarifying what criteria can be applied. Additional issues in valuing interventions are created by the timeframe and inclusion of observable side effects. Evaluators analyse the short-​term results, long-​term impact and side effects of the policy intervention, and communicate the findings to the stakeholders. At times, the stakeholders involved in certain evaluation processes may require the outputs to be delivered within a shorter timeframe, while some actors prefer to see the results within a relatively longer timeframe. Thus, there are challenges and trade-​offs associated with the politics of valuing interventions.

The challenge of explaining why a solution works or does not work Public policy is about triggering a behavioural change mechanism (Shafir, 2013; Weaver, 2015; World Bank, 2015). This recent perspective is very much in line with the public policy ‘classics’ stating that public policy is about changing the choices and behaviours of policy actors (Lasswell, 1951; Simon, 1997; Wildawsky, 2017). Evaluation literature follows this logic, arguing that public interventions (projects, programmes, policies and regulations) should be viewed as levers designed to activate certain change mechanisms among policy addressees, which in turn should lead to the desired effects (Rossi et al, 1999; Astbury and Leeuw, 2010; Chen, 2004). 102

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This perspective, confronted with everyday policy practice, highlights two widespread shortcomings. First, designers of policy interventions often ignore the existence of these mechanisms, assuming a direct, automatic link between a policy action (input) and the policy addressees reaction (outcome), and neglecting side effects. This so-​called ‘black box’ approach to policy design has been widely criticised in both practice and literature of evaluation (Astbury and Leeuw, 2010; Pawson, 2013). Second, even when unpacking the black box of mechanisms, policy practitioners often follow the rational choice theory, assuming the full rationality of policy addressees, and their unchanging set of preferences (Amadae, 2007). This assumption stands in contrast with recent empirical findings of cognitive psychology, revealing how bounded rationality often leads to systematic errors and biases in decision-​making (Simon, 1997; Kahneman, 2011; Shafir, 2013). Therefore, in order to design effective policy it is crucial to obtain more realistic insights into the change mechanisms that drive the response of the policy addressees to the implemented policy measures (Shafir, 2013; Weaver, 2015).

The challenge of transferring research findings into policy actions The raison d’être of all applied policy research, including evaluation studies, is to be used in decision-​making processes. In its early days, evaluation practice was driven by an assumption, similar to the one made by the community of policy analysts, that the relation between the production of knowledge and its application is linear. Thus, the execution of credible studies alone should be a sufficient condition for its use in the policy-making process. By the end of the 1970s, the policy research community started to recognise the growing gap between the production of analyses and their incorporation into programme decision-​making (Weiss, 1988). By linking evaluation literature with the broader body of work on knowledge utilisation, three main causes can be identified. The first problem is the issue of timing. The majority of evaluations have a summative nature, thus they come at a relatively late stage in the policy cycle. But even ex-​ante evaluations that aim to comment on programme drafts often arrive late in the decision-​making process –​when decisions have already been made and consensus around the programme has been built. The second issue lies in the differences between the two communities –​the producers of knowledge (researchers, analysts, evaluators), and the potential users of knowledge (decision-​makers –​politicians, senior civil servants, programme and project managers). The crucial discrepancies relate to different purposes, mindsets and languages. Policy researchers focus on 103

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valid knowledge generation and finding optimal solutions. Decision makers focus on finding a solution that allows the feasible amelioration of problems. Researchers tend to explore the details and increase uncertainty, while decision makers try to decrease the complexity and uncertainty they cope with on an everyday basis. Finally, evaluators tend to use academic language, focusing their narrative on theories and methodological specifics, while practitioners use the language of actions and practical implications (Caplan, 1979; Nutley et al, 2007). The third issue is the complex nature of organisational learning combined with the peculiarities of public sector decision-​making. Individual and organisational policy actors absorb information and learn in complex, non-​ linear ways (Leeuw et al, 1994; Olejniczak and Mazur, 2014). Furthermore, bureaucratic organisations have their own established routines, and tend to develop risk avoidance. Challenging the status quo of a particular policy requires a body of evidence aligned with other organisational and political processes that can eventually create a punctuated equilibrium. This makes the learning process highly incremental.

Scope and method of the study There is still a scarcity of academic literature providing a worldwide overview on labs. Previous examples of research using case studies have applied a literature search, and selected labs mentioned in at least two different sources (McGann et al, 2018). As a result, European policy labs have dominated the selections, as they are more present in English-​speaking publications than Asian, African and South-​American labs. Moreover, policy labs in Europe have operated for relatively longer, have had more opportunities to network, and are consequently more widely recognised. In order to ensure higher generalisability of the findings, it is important to keep the balance between the selection of case studies from various geographical locations and the labs’ level of operation (international, national, regional or local). Therefore, this study aimed at finding a worldwide database of policy labs, including their geographical location and operational level. The only sources providing such a broad overview available online, at the time of conducting the study, were the ‘World of Labs’ map prepared by NESTA (Price, 2015), updated by Irish academics (O’Rafferty, 2016), and the report Public Policy Labs in European Union Member States by the EU Policy Lab (Fuller and Lochard, 2016). Their non-​academic and European origin could have been a drawback, possibly limiting their knowledge about the labs in other continents. However, NESTA provided information on at least five labs on each continent, while both organisations had prepared networking events for labs: NESTA’s Lab Works in 2015 (London, UK) and 2016 (Santiago, Chile), and EU Policy Lab’s Lab Connections in 2016 104

Policy Labs Table 5.1: Policy labs worldwide Policy labs

Local

Regional

National

Europe

16

21

19

9

65

North America

15

17

8

4

44

Asia

1

2

6

6

15

Latin America

2

1

5

1

9

Africa

0

0

1

6

7

Australia and Oceania

1

0

3

2

6

35

41

42

28

146

TOTAL

Other

Total

Source: elaborated by the authors on the basis of Fuller and Lochard, 2016; O’Rafferty, 2016; Price, 2015

(Brussels, Belgium). Thus, they appeared up-​to-​date and reliable, and their consolidation formed the basis for further case study selection. The list was updated and validated using the review of data added to NESTA’s webpage as well as desk research. Table 5.1 summarises the initial pool for case study selection. The initial desk research revealed that the lab population is highly incoherent when it comes to experience, published online contents, and the relationship between their activities and public policies. Therefore, for the purpose of selecting a comparable pool of cases, further selection criteria were applied. The first filter was the definition of the phenomenon. The study focused on policy labs –​the entities that declare a public policy focus, for example, policy design, solutions for citizens or social impact, providing an open forum for new ideas and solutions to social problems. That excluded entrepreneurship labs, the majority of which support start-​up companies, and ‘influencers’ –​organisations that are interested in labs and social innovation, publish articles and reports about them, and offer networking events, but do not design public policies on their own. Examples of excluded entities are: NESTA (UK), iMinds (Belgium), OECD Observatory for Public Sector Innovation (France), World Bank (USA) and LabGov (Italy). The second filter was related to the geographical scope. The study aimed to include the continents with the highest number of nationally grown policy labs addressing a diversity of national, regional and local activities. This criterion led to the exclusion of Africa as it hosted mostly international (for example, UNESCO) labs by the time that this study was conducted (from May 2016 to May 2017). Moreover, Asia and Australia were merged into one geographical group. In order to avoid an imbalance (with Europe and North America dominating the population), we decided to have an equal number of case studies from all four geographical groups. 105

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In order to identify the labs to be studied in each geographical area, the last sampling step was introduced –​focusing on positive outliers. These were defined in terms of experience (labs in operation for at least one year and active at the time of the study), and data availability (labs having an operative website with information on their activities and additional documents, available in English or Spanish). We are aware of the limitations of a web-​based study. However, we assumed that website communication is an important dissemination tool for policy labs. Therefore, in the case of positive outliers, the websites were sufficiently developed for us to gather reliable data, especially in terms of labs’ know-​how and experience. Whenever possible, we complemented webpage data with official documents produced by labs, such as reports, articles and guidebooks. The final list of selected case studies covers 20 labs located on five continent groups, in 16 countries and 20 cities. It includes diverse labs in terms of all criteria on every continent. In each geographical group there are labs with various ownership statuses, levels of operation and years of experience (see Table 5.2). Data on the selected labs was collected using desk research conducted by the authors. Analysis was based on exploratory coding followed by a comparative analysis. Codes were formed around three broad groups of issues: 1. Structures –​ who they are. This analysis covered organisational arrangements, legal status and form (public, private, NGOs), level of operation, experience in their activity as a lab, and their networks. 2. Functions –​what labs do and what outcomes they produce. Analysis covered labs’ overall mission, topics covered, types of interventions (regulations, small community projects, big programmes, and so on), and their reported impact, including case studies and the scope of influence on policies. 3. Processes –​how they do it. This included the approaches, methods and tools that labs apply in designing public interventions. The findings from the analysis were synthesised in the form of comparative tables, and these formed the basis for a discussion on labs’ contribution to the main challenges identified by evaluation practice.

Findings: a review of lab operations and their potential contribution This section presents the findings from the comparative study on policy labs and discusses how they could contribute to addressing the three policy challenges presented in the literature section. We summarise the key patterns that emerged across cases in relation to the structures, purpose and processes 106

newgenrtpdf

Table 5.2: Summary of selected case studies No. Europe

Location

Legal status

Level of operation

Design Policy Lab

Italy, Milan

Launch year 2000

academic

local, international

2

Kennisland

Netherlands, Amsterdam

1999

NGO

local

3

La 27e Région

France, Paris

2008

NGO of public entities

regional

4

MindLab

Denmark, Copenhagen

2002

public

national

5

UK Policy Lab

UK, London

2014

public

national

6

Alberta CoLab

Canada, Alberta

2014

public

regional, local

7

GovLab

USA, New York

2012

academic

national, regional, local

8

GOVLabPHL

USA, Philadelphia

2016

public–​academic partnership

local

9

Ideas42 & Gov42

USA, Chicago, New York

2008

NGO

local, international

Social and Behavioral Sciences Team

USA, Washington DC

2014

public

national

10

(continued )

Policy Labs

107

North America

Policy lab

1

newgenrtpdf

Table 5.2: Summary of selected case studies (continued) No. Latin America

Location

Legal status

Level of operation

Ethos Laboratorio de Políticas Públicas

Mexico, Mexico City

2008

NGO

national, international

12

iGovLab Laboratório de inovação em Governo

Brazil, San Paulo

2015

NGO of public–​ academic partnership

national, local

13

LabGob Laboratorio de Gobierno

Chile, Santiago

2014

public

national

14

LPP Laboratorio de Políticas Públicas

Brazil, Rio de Janeiro

2000

academic

national

15

Smart Lab

Argentina, Buenos Aires

2015

public

local

16

Auckland Co-​Design Lab

New Zealand, Auckland

2015

public

regional, local

17

NSW Behavioural Insights Unit

Australia, New South Wales

2012

public

regional

18

PS21

Singapore, Singapore

1995

public

national

19

Pulse Lab Jakarta

Indonesia, Jakarta

2012

NGO–​public partnership

national

20

Seoul Innovation Bureau

Korea, Seoul

2013

public

local

Source: authors’ own elaboration on the basis of web content

Launch year

Policy-Making as Designing

108 Asia and Australia

Policy lab

11

Policy Labs

of policy labs. Due to a lack of coherent typologies and comparative frameworks in the current literature, the focus was on creating a primary synthesis and identifying shared characteristics. Structures: who labs are The legal status of policy labs substantially varies, with no visible patterns in terms of regional diversity. Half of the selected labs are exclusively owned by public sector entities representing different levels of governance. Strikingly, in the Asia & Australia group there is not a single lab without public sector ownership. Three of the studied labs function as independent non-​government organisations (Ethos, Ideas42, Gov42, Kennisland) and another three are run by universities (Design Policy Lab, GovLab, LPP). The remaining four labs take the form of NGOs launched in various inter-​ organisational partnerships: public–​academic (iGov Lab, GovLabPHL), public–​NGO (Pulse Lab Jakarta) or between multiple public sector entities (La 27e Region). The labs’ focus on public policy can explain this clear dominance of the public sector. Other studies have analysed in more detail how ownership influences labs’ activity and characteristics (McGann et al, 2018). The selected labs operate at local, regional and national levels. Some of them are also active at the international level (for example, Design Policy Lab, Ethos). The majority of labs specialise in one particular level of governance (mostly national), but seven of them operate at more than one level (for example, GoVLab, Alberta CoLab, Auckland Co-​Design Lab, iGovLab). The experience of the studied labs varies from two to 23 years. The oldest five labs in our selection were launched between 1995 and 2002: three European, one Asian and one Latin American. However, it can be highlighted that Mindlab is the oldest institution actually launched under the policy lab name, while others started out as a different organisation and only later transformed into a lab. As a result of the recent boom in lab development (clearly visible in the Americas and Asia), the majority of the studied labs are no more than seven years old. The youngest lab included in the analysis is the Philadelphian GOVLabPHL launched in 2016. In terms of networks, labs’ regular partners usually include local and regional authorities, public administration institutions and private stakeholders, who actively contribute to projects for the common good. They often engage with researchers specialised in a particular policy area. Civil society organisations are an important partner for labs, as they represent wider groups of citizens or specific social interests. As for private sector companies or corporations, they are usually involved as sponsors of projects or as partners in programmes supporting entrepreneurship. Some labs are also associated with various 109

Policy-Making as Designing

international projects, usually financed by transnational foundations, OECD or the European Commission. In general, labs diversify policy ownership by engaging various actors or groups representing different stakeholders. Often this function is strengthened by the fact that they operate in a physical space outside an administration with its set routines and standard regulations, which stimulates open discussion among equal partners. Functions: what labs do In terms of purpose, the studied labs usually define themselves as platforms or ‘shared spaces’ of collaboration, knowledge production and implementation, to highlight their inter-​sectoral bridging capacity. Sometimes they also define themselves as action research-​oriented units that aim to promote government effectiveness and cultural shifts. The thematic scope of labs’ actual operations varies substantially: some of them focus on a particular sectoral policy (for example, housing and civil society empowerment in the case of Kennisland), while some do not have a particular specialisation, and support policy-​design processes depending on their founders’ needs. This observation runs in line with previous studies. For example, Australian labs cover the whole spectrum of social policy issues, including housing and welfare, public administration and governance, education, health, transport, policing, as well as the criminal justice system (McGann et al, 2018). The analysis of policy lab missions and key activities did not reveal any clear geographical patterns. However, across all regions we could identify three main specialisation patterns: 1. serving the government: aiming to improve public services and policies, and train administrative staff (MindLab, UK Policy Lab, PS21, Alberta CoLab, LabGob; iGovLab, GOVLabPHL, La 27e Région). Two labs framed their mission as ‘changing the way of governance’ (Design Policy Lab, GovLab,); 2. serving the community: aiming to solve specific social problems. Here, labs’ areas of interest were diverse and broad, including issues like health, poverty, housing, domestic violence (NSW Behavioural Insights Unit, Seoul Innovation Bureau), youth and families (Auckland Co-​design), human rights, urban development (LPP), poverty alleviation, social development, gender equality, democratic governance (ETHOS), making society smarter, empowering citizens (Kennisland); 3. serving both the government and the community (Social and Behavioral Sciences Team, Pulse Lab Jakarta).

110

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In general, policy labs produce programmes and projects that seek to explore ideas, solve problems, train leaders and deliver tools to improve public services through innovation. This includes creating spaces for entrepreneurs, SMEs, students, academics, citizens and NGOs to use their talent, ideas and experiences related to a particular public service in order to find solutions to existing challenges. Labs aim to create impacts in two major ways: by engaging citizens, and by changing the culture of government through increasing the adoption of suggested changes and improvements by the relevant agencies and departments. However, with regards to the effects of policy labs’ activity, the study has found little evidence. It seems that labs’ ambition to create meaningful change in these two areas has not been followed by a clear idea of what exact impact they are aiming at, nor a way to measure it. For example, when reporting on ‘impact’, labs do not discuss long-​term, structural change in the situation of the addressees. Instead, they present short-​term, mainly process-​related outcomes (meetings, reports, and so on). Likewise, their success stories have a highly processual character –​they report on connections, networks and actors’ involvement, and the scale of dissemination. This clear mislabelling of process indicators as impact indicators can be partially explained by the short period of existence of some labs, but in other cases it may be associated with a reluctance to make outcomes measurable and public. In other words, the level of labs’ transparency may be influenced by their partners’ expectations, as well as the political sensitivity of some matters addressed. We can conclude that what seems to be lacking is a systemised effort to measure the impact after fully implementing a project. Some labs are satisfied with general feedback from the community, partner institutions or local governments (‘Looks like the mayor is happy’) often collected during workshops. However, there seems to be little research done in measuring real change in the behaviours of citizens, public servants or organisational actors. The lack of this feedback loop may limit the positive impact of labs’ work, as it hinders learning from experience and developing better tools in the future. Therefore, there is a need to develop greater reflexivity in terms of the short-​and long-​term effects of labs’ work. Processes: how labs do things The processes and toolbox of policy labs are heavily based on design practice including design thinking and industrial design (Bason, 2014; IDEO, 2015; Stickdorn and Schneider, 2012). Numerous labs refer to various versions of the design process with a spectrum of techniques

111

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for each of them (Andrews, 2015; Kieboom et al, 2015; Mortati, 2015; MindLab, 2017; Open Policy Making, 2017). This observation is in line with findings of earlier comparative studies that point out a recurring pattern in service-​design rationale, which is a participatory, human-​centred approach (McGann et al, 2018). In order to find a broader pattern in lab processes and methods, we decided to map them on a two-​dimensional matrix (Kumar, 2012). The first dimension is ontological in nature –​it extends from experiential immersion in reality on the one hand, to a more theoretical abstraction of policy issues on the other. It captures well the tension existing in public policy practice, between the complex, often chaotic reality of a particular policy problem, and the conceptual efforts to make sense out of this reality, finding more general principles that could be applied to problem-​solving, and even transferred to other policy situations. The second dimension describes the nature of involvement with a policy issue. It ranges from inquiry –​focused on understanding the policy issue, to creation –​focused on active manipulation and change of the matters addressed by the particular policy. This second dimension illustrates well the continuous struggle in public policy practice to feed diagnostic studies into decision-​making and implementation, or looking more broadly –​to integrate the insights from various research inquiries into policy actions. Mapping the activities of the analysed labs onto this matrix allowed us to uncover five areas of activity accompanied by a variety of tools and techniques (see Figure 5.1 and Table 5.3). Following labs’ practice of making procedures user-​friendly and easy to grasp, we named our generic process REACT. This is an acronym created from the first letters of each of its stages. First, the work of labs starts with assisting policy-makers in redefining a policy issue. The policy problem is often framed in terms of various target groups, segments of policy addressees and their desired behaviours. Second, labs engage in deep exploration of the reality that they want to change. This involves collecting relevant data from multiple sources to fully understand the problems, behaviours and context of target groups. Third, policy labs move into the analysis stage, hypothesising about the factors and contexts that facilitate or hamper the desired policy change. Fourth, they take an active role and undertake creative sessions, in which they try to construct potential solutions to the studied problems. Fifth, labs provide a safe space for experimentation, which allows them to test in practice the prototypes of designed solutions. This whole process is often not linear, but iterative. For example, after completing the first series of testing, labs might discover a new group of service users, and therefore decide to further explore the characteristics of this group and repeat the analysis, creation and testing processes. 112

Policy Labs Figure 5.1: REACT –​generic design process in policy labs THEORY Analysing the problem

Creating solutions

Redefining the policy issue

INQUIRY

Exploring the situation

ACTION

Testing solutions REALITY

Source: authors’ own elaboration, based on Andrews, 2015; MindLab, 2017; Kumar, 2012 and web content

The REACT matrix (Figure 5.1) highlights the dialectical nature of applied policy design and the efforts of policy labs to integrate in one stream various activities and perspectives that have been traditionally separated in policy-making. Policy labs constantly balance between abstraction and fine-​g rained reality, between research inquiry to understand problems and proactive development of solutions to the problems. We believe this is an important characteristic that distinguishes labs from other institutions involved in policy design and evaluation, which traditionally tend to focus on a single sphere (for example, theoretical reflection or implementation). Looking into the toolbox of policy labs, two patterns seem dominant. First, there is the participatory orientation, focused on tools and methods (for example, ethnographies, interviews, workshops, crowdsourcing, brainstorming) involving representatives of various stakeholders in the exploration and co-​ creation of solutions. Labs from all continents, including almost all analysed labs from Europe, Australia and Asia, subscribe to this orientation. The human-​centred approach welcomes citizens’ ideas and solutions, embraces ambiguity and makes it possible to identify the conditions for co-​design and implementation. Some labs also highlight the need to involve participants 113

Policy-Making as Designing Table 5.3: Methods and tools used by policy labs

Analysing the problem Creating solutions Behavioural bottlenecks analysis, 'Backstage' policy levers, Data discovery cards, Brainstorming, Data science, Concept posters, Evidence safari, Crowdsourcing, Film and sound, Explore your ideas, Pattern recognition, Future scenarios and speculations, Personas, How might we?, Perspective cards, Idea sketch sheets, Policy canvas, Ideas days/'jams', Portraits, Ideation sheets, Priority grid, Logic models, Stakeholders map, Role cards, Target group, Service blueprints, User decision journey, Speculative design. User segmentation. Redefining the policy issue Five whys, Change cards, Hopes and fears cards, Project focus, Stakeholders map, Target group, Theory of change; Exploring the situation Behavioural bottlenecks mapping, Cultural probes, Design ethnography, Desk research, Film ethnography, Interviews, People shadowing, Service safaris, User journeys.

ACTION

INQUIRY

THEORY

Testing solutions Desktop prototyping, Experience prototyping, Experiments (including Randomised Control Trials), Proto - and provotypes, Serious games.

REALITY Source: authors’ own elaboration based on Andrews, 2015; MindLab, 2017; Kumar, 2012 and web content

during the prototyping and testing stage, in order to increase the takeup of solutions, empower beneficiaries and socially embed these solutions. The second pattern is the use of behavioural insights, characteristic of the Anglo-​Saxon labs analysed in this chapter (GOVLabPHL, Ideas42 & Gov42, Social and Behavioral Sciences Team, Alberta CoLab, NSW Behavioural Insights Unit). These insights are particularly valid for the exploration, creation and testing stages. The first two stages use knowledge about human motivations and decision-​making processes. Exploration involves mapping behavioural bottlenecks -​factors that obstruct desired behaviours of policy addressees. Creation uses behavioural change strategies (including ‘nudging’) in the design of potential solutions. The testing stage relies on small, low-​cost interventions accompanied by experiments (usually randomised control trials). 114

Policy Labs

The policy labs analysed in this chapter often highlight that their work aims at scaling-​up the tested solutions. However, there is little evidence on how labs get involved in scaling-​up and actual policy design. They can lobby, advocate and disseminate their findings among multiple policy actors and stakeholders, but they are usually not directly involved in the full-​scale policy design, which some authors see as one of the biggest limitations of policy labs (McGann et al, 2018). Thus, we adopt the perspective that scaling-​up is a separate meta-​process that goes beyond the typical cycle of lab activities, and requires a separate set of activities, methods and tools.

Labs and the challenges identified by evaluation practice The synthesis of lab practices presented in this section makes it possible to explore the ways in which policy labs address or fail to recognise the three challenges identified by evaluation practice. We start with the challenge of establishing what solution works. Looking at current lab practices, it seems that labs have little to contribute to the ongoing debate addressing the challenges of valuing interventions; they could benefit from incorporating the existing body of knowledge from evaluation into their practices. Labs could learn from evaluators’ community discussions that have, over the years, sought to overcome paradigm divides, using more sentient ways of mixing methods and exploring the effects of complex interventions (Stern et al, 2012; Bamberger et al, 2015). Evaluation practice offers a high level of emphasis on obtaining strong causality, namely causality from the successionist perspective, through rigorous evaluation methods such as Randomised Controlled Trials (RCTs). However, recent evaluation trends stress that not only ‘what works’ is important, but also ‘in what context,’ and ‘for whom’ are critical elements in assessing the effectiveness of a policy intervention based on various perspectives and notions of causality. What significantly worked in Setting A might not work in Setting B or C. As generativists of causality argue, the contextual factors or supporting mechanisms of Setting B or C may be different from Setting A. Particularly, the last element ‘for whom’, leads us directly to the issue of assessing the value of evaluation findings, since it involves making judgements for the beneficiaries of the evaluation. This implies that the evaluation inquiry requires evolving practices that balance rigour and flexibility in the use of methods and analytical approaches. Moreover, creating synergetic effects between the use of labs and evaluation can promote making value judgements of the findings. This can be achieved by incorporating stakeholder perspectives and different value judgements at the early stage of the programme design and by addressing the needs and interests of programme beneficiaries, in particular, enhancing the responsiveness of previously underrepresented populations in evaluation. 115

Policy-Making as Designing

In case of the second issue, explaining why a solution works or not, there are three promising synergies emerging from labs and evaluation practice that could address the challenge of unpacking the black box of mechanisms. Both evaluation practice and labs use a theory-​driven approach that defines public intervention as a ‘theory’ –​a hypothesis yet to be tested and verified in a real-​life situation (Rossi et al, 1999; Chen, 2004; Coryn et al, 2011; Donaldson, 2007). The real value of the theory-​driven approach, especially for decision-​makers, is its explanatory dimension. It reveals how a programme works, with whom and under what circumstances (Astbury and Leeuw, 2010: 365), and explains the mechanisms that have led to the success or failure of the intervention. The five-​stage REACT process applied by labs (compare Figure 5.1) seems to provide Programme Theory building that is easier than the reverse process of theory building in evaluation. In labs, the exploratory and analytical phases help articulate the ‘hypothesis on obstructing problems’ (HOP) –​the key barriers that block the desired behaviour. Then, the creative phase provides ideas for solutions –​that is, the ‘hypothesis on intervention types’ (HITs) that can address these barriers. When the testing phase shows limited results, designers can go back and reconsider either their diagnosis of the main barrier (that is, HOP) or the selection of policy instruments (HIT). This logic is aligned with the human cognitive process of everyday hypothesis testing as part of problem solving (Evans, 2017). As a result, it is more intuitive and accessible to practitioners. Second, labs add an important aspect to the explanation of mechanisms –​ behavioural insights into the users on a particular public intervention. The basic strategy here is to break down the ‘journey’ of the policy actor throughout the intervention into a sequence of interactions and decisions, and then analyse ‘behavioural bottlenecks’, including individual heuristics and biases that can block desired behaviours (Ly et al, 2013; Service et al, 2015; Stephans, 2016). This provides a number of advantages: it allows exploration of observed (not declared) behaviours and their drivers, clarifies the synthesis of diagnostic findings in the form of user profiles and their decision journeys, and links policy practice with the growing body of psychological and cognitive research on human decision-​making. This approach also focuses the attention of decision-​makers on concrete change in behaviours, and allows the formation of hypotheses on the barriers or gaps that hinder such change. Finally, labs combine approaches in constructing intervention theory that are usually separated in evaluation practice. They use a deductive approach by referring to scholarly theories (mainly behavioural science and design) and earlier intervention results from academic literature. They also use an inductive approach –​conducting fieldwork and generating a grounded 116

Policy Labs

theory. Labs add to these a user-​focused approach –​working with intended users to extract and make explicit their implicit underlying assumptions as well as their theory of change. Leading evaluation theorists have been calling for such a combined approach (Donaldson, 2007; Patton, 2010). The last challenge of transferring research findings into policy actions has been the focus of both the theory and practice of evaluation. This body of knowledge, when combined with lab practices could lead to promising developments in ameliorating the problem of evidence-​ informed policy. Labs’ scope of operations provides perspectives for better utilisation of research by addressing the issue of timing. The majority of labs focus on working at the early stages of the policy-making process –​that is, problem definition and policy formulation. Some labs (for example, GovLab) focus on improving already existing services. What is especially interesting is that labs often try to build, within the main policy cycle, a smaller loop of design–​testing–​adaptation (Haynes et al, 2012). They gain some time by applying small-​scale experiments and testing prototypes. This allows them to deliver meaningful feedback on ‘what works and why’ exactly when decision-​makers need it –​relatively early on in the policy process. Both evaluation practices and labs are well aware of the importance of overcoming the ‘language’ barrier between researchers and decision-​makers. The evaluation tradition has focused on improving ways and forms of communication with potential users of knowledge. This includes studies on understanding the credibility of information in the eyes of the beholder (Miller, 2014), effective data visualisation (Azzam et al, 2013) and broader knowledge brokering strategies (Olejniczak et al, 2016). To this, labs could add their organisational structures that facilitate the utilisation of their products. The involvement of stakeholders and partnership structures with policy actors would build engagement and a sense of ownership of the developed solutions. This, combined with co-​designing initiatives, could address the gap between producers and users of knowledge, since all interested parties would be involved in the process.

Conclusions The reviewed practices of labs seem indeed promising in addressing the challenges of public policy. However, the methodological limitations of our current study (with analysis based only on desk research of web sources and labs’ own reports) mean that at least three issues would benefit from further research. First, our study was aimed at addressing the current lack of coherent typologies and comparative frameworks among policy labs. This focus on synthesis and shared characteristics has limited the discussion of heterogeneity 117

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among labs. Future comparative studies could use the analytical frames developed in this chapter (typologies of labs, generic matrix of the design process) to explore geographical and topical variations (including the growing phenomenon of digital policy labs), and factors influencing the diversity of labs. Second, it is unclear how effective the analysed labs are in feeding their solutions into the actual policy-making and policy implementation process. Are they stand-​alone initiatives that strive for decision-​makers’ attention, and occasionally feed ideas into the policy cycle, or are they integrated into the institutional policy system of a particular region or government? These questions have been difficult to address through this research due to the short history of lab operations. A new cycle of interviews with lab personnel could provide us with better understanding of how systematic their role is in the policy process. This leads to the last limitation –​we do not know how sustainable the labs are in the long run and what make them durable in organisational terms. Based on current observations, we can hypothesise that labs set up in a local or regional government by a single public policy leader will have a lower survival rate than initiatives established by a coalition of academic researchers and government representatives. However, this hypothesis can only be verified in the future. With the majority of the labs being relatively young (2–​3 years old), it is still far too early to decide if they are just a temporary fashion or an approach that will substantially change the way we design our public policies. Despite these limitations, through our analysis of the practices of policy labs around the world, we have identified a number of synergies between policy labs and evaluation that could be beneficial for both, and that could advance general public policy practice. In relation to the challenge of establishing what works and valuing public interventions, policy labs are more likely to be beneficiaries than being contributors in advancing current practices. Policy labs focus on services and projects that are relatively simple and manageable interventions, rarely developing policy or even programme solutions. They have a tendency to use methods that infer relatively quick, short-​term and strong causal relationships. However, public programmes have grown in complexity (multi-​level, multi-​objective interventions) often with extended timeframes (multi-​annual planning). Furthermore, today’s policy issues are often wicked policy problems that require a more sophisticated understanding of the social dynamics and environments surrounding a certain policy intervention. Thus, well-​established evaluation practices can support labs in tackling issues, ranging from conceptual and processual complexity to the non-​linear causality of more complex interventions. In particular, evaluation brings 118

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together various perspectives of causality and complexity theories that can help labs measure their impact and understand how systems change over time as well as from place to place. Additionally, insights from evaluation theories and practices can also help policy labs improve the reliability and value assessment of their prototype solutions. There is a range of evaluative criteria suggested by evaluation practitioners, and therefore results may vary depending on the criteria applied. Moreover, the available timeframe changes the results of assessments. Policy labs currently tend to focus on generating short-​term effects by using RCTs, anticipated declared utility or satisfaction tests by stakeholders. In the future, policy labs should identify and apply more advanced approaches to valuing. With regards to the second challenge of explaining change mechanisms, labs and evaluation share common ground in defining public interventions as ‘theories’ yet to be tested and verified in real-​life situations. Lab practices can add to evaluation practice their strong focus on the final users of policy (policy addressees) –​their identification, understanding and targeting. Some labs seem to be ahead of evaluation practice in terms of integrating behavioural insights into public policy. Furthermore, the generic REACT process offered by labs to constructing intervention theory is better aligned with human problem solving, and is therefore more likely to be accommodated by policy practitioners. Looking at the third challenge of feeding research findings into decision-​ making, policy labs seem to be better equipped than evaluation in addressing the timing issue of delivering results to knowledge users. Labs can help to determine the feasibility and scalability of policy programmes in a relatively flexible timeframe, through means such as implementing ex-​ante pilot projects. Policy labs also offer collaborative structures. They are used as a safe space that encourages the involvement of citizens and stakeholders in co-​designing public solutions. These organisational arrangements can help to serve the ‘use’ purpose of evaluation. They can be important in the policy feedback loop process. This is particularly significant because labs place the tools directly in the hands of the decision-​makers, encourage them to partner up with researchers to generate relevant data and evidence, and make assessments to promote the effectiveness of policies and programmes. Evaluation theories can guide policy labs to think more about their systemic influence and their sustainability. Labs declare an ambitious aim of cultural shift, but they seem to have limited recognition of the complex mechanisms driving organisational learning, including inter-​organisational collaborations and political discourses. Evaluation theorists such as Carol Weiss and Peter Rossi offer effective frameworks and principles for those issues. Evaluation practice can also contribute to scaling-​up, by emphasising 119

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the need for external validity, using approaches such as experiments that are larger in scale in terms of the greater representativeness of samples or increased implementation scale. To conclude, policy labs are not an alternative development to established practices of public policy. They are rather a promising addition that, when combined with existing evaluation practices, can allow both entities to mutually benefit one another and create synergies to improve the craft of public policy. Funding details This work was supported by Narodowe Centrum Nauki under Grant number 2014/​13/​B/​HS5/​03610. Open access of this chapter was financed by the Ministry of Science and Higher Education in Poland under the 2019-​2022 program “Regional Initiative of Excellence”, project number 012 /​RID /​2018/​19. Acknowledgements The authors would like to thank the team of editors of the volume, the editors of the journal and the two anonymous reviewers for their most valuable comments that substantially improved the content of this chapter.

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When design meets power: design thinking, public sector innovation and the politics of policy-making Jenny M. Lewis, Michael McGann and Emma Blomkamp

Introduction Innovation has become a much-​used word in the public sector in the last two decades (Hartley, 2005; Osborne and Brown, 2013). As governments seek solutions to pressing issues within the inevitable financial constraints they face, they have increasingly turned to the idea of ‘innovation’ to help them address the complexity of problems with which they are grappling (Lewis et al, 2017). While innovation might be considered problematic in governmental contexts, given that it has strong normatively positive overtones on the one hand, but presents significant challenges to traditional bureaucratic procedures on the other, it is an idea that has gained currency around the world. This is in part demonstrated by the creation of many public sector innovation (PSI) labs at multiple levels of government in individual countries, as well as in international organisations such as the OECD, with its Observatory of Public Sector Innovation (OPSI) established in 2014. Responding to this rising focus on public sector innovation, governments have begun experimenting with design-​led or ‘design thinking’ approaches as a way of reframing policy issues and generating and testing new solutions to public problems (Bason, 2013; Design Council (UK), 2013; Kimbell, 2016; Blomkamp, 2018). Although seldom concretely defined, design thinking can be loosely understood as a ‘human-​centred’ approach to innovation that draws from the processes used by industrial and product designers. In terms of design researchers, it is: ‘Performing the complex creative feat of the parallel creation of a thing (object, service, system) and its way of working’ (Dorst, 2011: 525). Design thinking is increasingly being looked to by organisations who have a need to broaden their repertoire of strategies for addressing open-​ended and complex challenges (Dorst, 2011). This has in part been driven by a social turn (Chen et al, 2016) within the field of industrial design, as designers, inspired the participatory philosophies of theorists such as Papanek and Manzini, have sought to evolve design beyond a tool for the development of functional consumer products into a process for 125

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the collaborative development of ‘radical change’ (Bjögvinsson et al, 2012). Its proponents claim that it can help solve contemporary policy challenges in areas as diverse as health, climate change and employment. For many working in policy, design thinking constitutes a ‘bottom-​up’ approach where the gap between designers and citizens is narrowed through decisions being informed and even sometimes driven by those who are affected by policies (Kolko, 2018). This participatory focus of design draws from the democratic concept whereby all those ‘affected by design decisions should be involved in the process of making the decisions’ (Sanoff, 1990: i). In particular, developing more collaborative approaches that involve multi-​actor networks of public and private stakeholders is viewed as a key imperative (Sørensen and Waldorff, 2014). In this context, the extension of design thinking to policy –​particularly participatory and co-​design approaches –​ resonates with principles of network governance (Considine and Lewis, 2003), participatory governance (Fung, 2015), and co-​production (Voorberg et al, 2015). However, design thinking has not been universally seen as aligned with increasing participation and democracy. Iskander (2018), for example, argues that it is inherently conservative, based on privileging the designer ahead of those who are meant to be served by the process. Her argument is that, not only is it nothing new, but design thinking suffers from the same limitations of other policy-making approaches by protecting the powerful. This raises the question of what is different about design, and how well it aligns with policy processes. Despite its growing popularity, there has not been much critical investigation into the impact of design thinking on policy-making (Clarke and Craft, 2018). This chapter asks three questions: first, what is really new about design thinking in the public sector? Second, how does it challenge or differ from more traditional approaches to policy-making? And third, what impact, if any, does it have on the process of policy-making? We first address these three questions by examining design thinking and comparing it to two alternative approaches to policy-making: rational-​process and participatory models. Distinguishing design thinking from these models at an analytical level helps us to understand the potential of design thinking to genuinely reshape policy-making by impacting on the normative goals and epistemological frameworks guiding it. The realisation of these impacts very much depends on how design thinking is operationalised within policy systems at a practice level. That is, whether design thinking influences policy-making throughout the multiple stages of policy-making or is primarily being applied only in the early stages of problem exploration; and whether it is applied to large scale and central policy issues, or only to small scale and peripheral issues. The structuring of design thinking’s practical application will determine whether ‘the introduction of design [thinking] to policy-making’ (Bailey and Lloyd, 126

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2016) is fundamentally changing the nature of policy-making processes as predicted by some theorists (for example, Kimbell, 2016) or tinkering around the edges of existing decision-​models. Hence, we use an empirical study of PSI labs to tackle this question of impacts on policy-making in practice. One of the most important ways in which design thinking is being taken up and applied by within policy systems is the recent proliferation of PSI labs. Insights into how design thinking is currently being deployed within policy systems can be generated by focusing on them because they are now numerous and can be understood as ‘design-​for-​policy’ entrepreneurs: that is, as policy actors who promote ‘design-​for-​policy’ ideas through their advocacy and pursuit of design thinking approaches to public problem solving (compare Mintrom, 1997). We claim this for several reasons. First, important proponents of design thinking (entrepreneurs) have been centrally involved as directors of PSI labs (for example, Christian Bason at MindLab in Denmark). Second, some have described the role of PSI labs as being ‘to create motivation and commitment to design thinking for policy-making’ (Mintrom and Luetjens, 2016: 400). Third, recent surveys have shown that PSI labs continue to be established and indeed rely heavily on design thinking (Fuller and Lochard, 2016; Centre for Policy Innovation and Public Engagement, 2018; McGann et al, 2018a). Accordingly, to test how design thinking is having an impact on policy-making, we explore empirically how it is being applied by PSI labs to address public and policy problems. We do so by drawing on a survey of over 50 PSI labs in Australia and New Zealand conducted in early 2018, which gathered data on the stages of innovation PSI labs are working on, the extent to which they are undertaking policy-​ related projects and activities, and the different levels of government with which they are working. The chapter proceeds by first comparing a design approach to two alternative approaches to policy-making, to address the first two questions. We then briefly review the recent emergence and proliferation of PSI labs, arguing that they represent the vanguard of design thinking in the public sector, and present an empirical account of PSI labs in Australia and New Zealand to explore whether design is having an impact on policy-making (our third question). We use the term ‘PSI labs’ in this chapter to include innovation units, teams and other agencies –​both inside and outside government –​that focus on innovation in the public sector. Although our data shows that PSI labs –​both within and outside of government –​are very frequently being engaged to solve problems by agencies and departments across multiple levels of government in Australia and New Zealand, it also shows that much of their activity is concentrated at the level of discrete service redesign projects or managing stakeholder consultation processes. Few PSI labs in Australia or New Zealand are directly engaged in developing policy proposals or reforms, or work on systemic change, focusing instead on the 127

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earlier exploratory work of scoping problems. In the concluding discussion, we identify several factors that help to explain the currently limited reach of design thinking within policy systems and the degree of fit between design thinking and more traditional approaches to policy design.

Design thinking as an alternative approach to policy-making What is novel about design thinking in comparison to other approaches to policy-making? One answer lies in the form of reasoning underpinning design thinking, and what it implies for the sequencing of problem-​solving processes and the normative values that ought to guide decision-​making. Design thinking is based on a form of reasoning that moves beyond the analysis and problem solving we often associate with the policy process to create the end value desired, in the absence of knowing what to create and how to create it (Dorst, 2011). This abductive reasoning can be likened to a phenomenological form of analysis where complex situations are distilled as ‘themes’ through ‘a process of insightful invention, discovery and disclosure’ (Dorst, 2011: 258). For design thinkers, this phenomenological orientation implies that policy making should be guided by the values of ‘empathy’ and ‘curiosity’, along with ‘rationality’ (Torjman, 2012: 19), and a focus on ‘crafting new solutions with people, not just for them’ (Carstensen and Bason, 2012: 6). It is important to first search for the central paradox of a problem, then only work iteratively towards a solution once the nature of the core paradox is understood (Dorst, 2011). When conventional problem solving fails, a focus on the problem-​as-​presented first needs to be deconstructed (Hekkert and Van Dijk, 2011) before it can be solved. For these reasons, its supporters claim that the application of design thinking approaches is helping to generate ‘an entirely different decision-​making model for policy’ (Bailey and Lloyd, 2016: 6); one that involves far more than just an extension to the existing repertoire of policy design tools but ‘a different way for policymaking to be done’ (Bason, 2014: 3). These statements suggest a stark contrast between the logics of design thinking and traditional policy design approaches (Clarke and Craft, 2018); at least compared to the rational-​process models depicted in policy handbooks, against which proponents of design thinking position themselves. Policy handbooks generally suggest that policy-making constitutes a coherent ‘process of authoritative problem solving’ in which the government and its bureaucracies solve ‘known problems’ through the exercise of instrumental rationality (Colebatch, 2005: 14). While there are arguments about the extent to which policy-making is technically rational in practice, some believe that it should be more so, and others claim that such models provide useful frameworks for policy practitioners, regardless of how closely the process mirrors this in practice. Consider process models of 128

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the policy cycle, which proceed sequentially from agenda-​setting, through policy analysis and formulation, decision-​making, policy implementation and finally to monitoring and evaluation (see, for example, Althaus et al, 2013). These models are inspired by Lerner and Lasswell’s (1951) ‘stages’ schema of policy-making as a sequence of ‘intelligence; recommendation; prescription; invocation; application; appraisal; and termination’ (Bridgman and Davis, 2003: 99). Goals are formulated and then choices are enumerated, analysed and modelled before the option deemed most efficient is selected for implementation (Wagle, 2000: 208). Throughout this policy-making process there is an expectation of ‘rigorous ... appraisal of problems and solutions’ (Considine, 2012: 707) through data gathering, forecasting and modelling. Within a rational-​process model, policy analysts systematically develop policy options to solve problems pre-​determined by governments, and they do this by applying ‘knowledge about policy means gained from experience, and reason’ to determine those ‘courses of action that are likely to succeed in attaining their desired goals or aims’ (Howlett, 2014: 188). This understanding assumes that the specification of policy goals precedes the tasks of policy analysis and instrument design (see, for example, Bridgman and Davis, 2003), and that the analyst’s job involves ‘determining the best means to a given end’ (Dryzek, 2002: 213). In rational choice models of this process, the selection of policy options and instruments should be ‘empirically driven’ (Wagle, 2000) in the sense of being determined by social-​scientific knowledge about ‘what works and why’ (Parsons, 2002), and occurring outside politics (Lewis, 2003). This view of policy design is underpinned by the belief that policy challenges can be reduced to technical problems that can be scientifically solved (Head, 2008). But it also frames policies as the result of rational choices by policymakers (that is, the government). The contemporary movement towards ‘evidence-​ based’ policy-making is a species of this scientism in that it posits verifiable social-​scientific knowledge as the ‘modern currency of public policy’ (Adams, 2004: 30). Many alternatives to this rational model have been proposed as correctives to its theoretical and practical limitations, and they are too numerous to cover here. What are most important for this chapter are interpretive and participatory models, since these come closest to some aspects of what is presented as a design approach. They similarly emphasise how the development of solutions is deeply dependent ‘on the prior work of problem construction and reconstruction’ (Fischer and Forester, 1993: 3), and on how the work of both problem construction and solution analysis is ‘intimately involved with relations of power’ (Fischer and Forester, 1993: 7). Design thinking, considered here as the parallel creation of a thing and its way of working (see Dorst, 2011), pushes policy decision-​making towards ‘a fundamentally creative form of deliberation, which operates with different decision processes to those of rational choice’ (Considine, 2012: 708). It 129

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implies an iterative and ‘self-​correcting’ approach to policy-making that proceeds through interlocking processes of scoping, defining and reframing problems; ideating, prototyping and testing solutions; and learning by doing (Torjman, 2012: 10). The iterative nature of policy-making from a design thinking perspective stems from viewing the design process as a ‘bottom up’ approach to public problem solving that is playful, creative and, at times, even illogical (Kolko, 2018; see also Considine, 2012). Creativity is central to design thinking, but it is also often linked to participatory approaches, because creative design tools can be used to facilitate a more collaborative approach by bringing different kinds of people and knowledge into the policy process (Blomkamp, 2018). Design thinking approaches can be placed along a spectrum according to the degree to which they are genuinely participatory. Human-​centred or user-​centred design emphasises understanding citizens’ views and experiences during the stages of problem definition. Here, the tools of design may continue to be employed within (rather than challenge) rational choice models by becoming part of the methodology for searching for alternatives during the process of considering how to solve a problem (Considine, 2012). Co-​ design approaches, on the other hand, embody a much stronger democratic commitment to including those affected by a policy or institution as active participants in designing the solution. Regardless of distinctions about the extent of participation, empathising with, and widening the inclusion of citizens in the decision-​process, is generally regarded as a core tenet of how design thinking is viewed within the policy context. Critical and discursive approaches to policy (for example, Fischer and Forester, 1993; Yanow, 1996) relate to co-​design for policy, as they similarly ‘favour participatory techniques in which a panel of citizens is at the heart of the analytic process’ (Hoppe, 1999: 208). Habermas’ theory of communicative action provides an illustrative example (see for example Renn, 2006), and is often taken as the groundwork for developing and applying a more participatory turn in policy design (Fischer and Forester, 1993; Hoppe, 1999; Dryzek, 2002). At issue in these competing accounts are the conditions under which actors can ‘speak truth to power’ and what constitutes policy knowledge in this process. Discursive approaches view knowledge in terms of the deliberative ‘exchange of arguments and reflections’ (Renn, 2006: 35) and see it as the public’s role to speak truth to power. Design thinking embraces situated and abductive forms of reasoning that depend upon designers deeply immersing themselves in thickly experiential policy contexts (Bailey and Lloyd, 2016; Kimbell, 2016). Participatory design thinking approaches, according to proponents, require designers to have humility and ‘an emotional connection’ to the people involved in the process (Kolko, 2018). Within this paradigm, ‘emotion and intuition’ are 130

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treated as valid bases for determining viable options (Bason, 2013: x). This marks an important difference with deliberative approaches which, while recognising the importance of empathy in mobilising participants to gain mutual understanding, nevertheless privilege the ‘inherent rationality’ (Renn, 2006: 35) of argumentative persuasion as the basis for adjudicating options. Beyond work that is focused on design-​led and participatory approaches to policy, some recent work by Peters (2018) compares ‘old’ and ‘new’ policy design, and claims that while the processes are very different, the purposes (of improving the economy and society) are less so. The main difference, according to Peters, is the attempt to open up designing to a wider range of ideas and possibilities, and to emphasise innovation. His comparison between old and new policy design highlights an emphasis on ambiguity and openness in the new design, which he views as positive in moving from a technocratic form of design to one that is ‘more open, and less deterministic’ (Peters, 2018: 128). In summary, Peters argues that we need to meld the emphasis on precision and closure in older versions of policy design with the supposed virtues of new design –​openness and ambiguity. A similar argument is made by Clarke and Craft (2018), who claim that design thinking provides some advantages that allow the shortcomings of traditional policy design to be addressed. In summary, the application of design thinking does not sit easily alongside the pursuit of other approaches to policy, according to some of its promoters. The evidence for action that is generated by abductive and creative reasoning styles ‘is the antithesis of the ideal evidence base required for developing a policy’ (O’Rafferty et al, 2016: 14) within rational choice models. Others, however, have suggested that design approaches have substantial overlap with more traditional policy design (Peters, 2018). Further, some have argued that design is able to deal with some aspects of policy but not others –​particularly in regard to the interface with political and institutional constraints, while recognising that it has potential benefits in terms of adaptability, gaining more user perspectives, and better using collaborative approaches (Clarke and Craft, 2018). This discussion of the contrasts and complementarities of design thinking and rational and participatory approaches to policy-making, suggest some likely tensions when design meets power. These are summarised in Table 6.1. The logics and foundations that underpin these approaches, and the basis on which they can speak truth to power (meaning political and policy systems), are different in each of these (although not always in conflict). For design, creativity is valued over technical expertise and democratic principles, and imagination over evidence and discussion, although design is associated with involving users (more or less). It seems that speaking design to power, on the basis of creative ideas rather than technical expertise and democracy –​ concepts that are built into the policy process –​will face some significant 131

Policy-Making as Designing Table 6.1: Three approaches to policy Rational

Participatory

Design thinking

Logic

Soundness (deduction, induction, objectivity, analysis)

Inclusion (consultation, argumentation, collaboration)

Innovation (humanity, intuition, Abduction-​2)

Foundation

Evidence

Discussion

Imagination

Speak truth to power on the basis of:

Technical expertise

Democratic principles

Creative ideas

resistance. We return to this in the conclusion, following our exploration of PSI labs as exemplars of design thinking in practice.

Public Sector Innovation labs as ‘design-​for-​policy’ entrepreneurs As previously noted, one the most important ways in which design thinking is being taken up in practice within policy systems is through the spread of PSI labs. In 2016, it was estimated that there were more than 60 public policy innovation labs within EU member states alone (Fuller and Lochard, 2016), while others have estimated that, worldwide, around 100 PSI labs had been established at various levels of government, with new labs being created at ‘a rate of at least one a month’ (Price, 2015). Recent research suggests this is likely to be a gross under-​estimation of the number of PSI labs worldwide, since 52 PSI labs have been identified in Australia and New Zealand (McGann et al, 2018a) and 41 in Canada (Centre for Policy Innovation and Public Engagement, 2018). Many PSI labs are not formally part of the public sector yet work extensively with governments. This includes some of the most prominent PSI labs internationally such as Nesta’s Innovation Lab, MARS lab in Toronto, and GovLab in New York, who have become key influencers ‘in the global circulation of policy lab ideas’ (Williamson, 2015b: 4) and in the diffusion of design-​based ideas as a framework for public innovation (Williamson, 2015b). They resemble policy entrepreneurs, working to shape the terms of debate on policy innovation in ways that promote a particular set of approaches to problem solving (Mintrom, 1997). Their place within policy systems can perhaps be best understood if they are regarded as similar to think tanks and other small organisations that work with government but have substantial autonomy. Like other small organisations that work closely with government, PSI labs have an emphasis on organisational autonomy and capacity to provide expertise and legitimacy to the public sector. Previous international research on PSI labs suggests that most of them work across government agencies and 132

When design meets power

departments, traverse multiple policy sectors, are rarely subject to specific performance measures or strenuous evaluations, and operate with high levels of autonomy (Williamson, 2015b; Tõnurist et al, 2017). These characteristics have led them to be described as new boundary-​crossing organisational forms, or ‘innovation intermediaries’ (Williamson, 2015a: 254), in that they are designed to overcome a range of barriers that make innovation and cross-​cutting coordination difficult within public sector bureaucracies. These include the ‘highly sectoralised’ (Carstensen and Bason, 2012: 3) nature of the public service both administratively and horizontally between policy domains, and the bureaucratic structure of traditional public sector organisations which fosters risk aversion and resistance to change. In this sense, PSI labs, like think tanks, can be understood as forward-​looking or ‘pioneering policy entrepreneurs’ (Fraussen and Halpin, 2017: 116), with Williamson observing that they combine ‘elements of the political think tank, media production ... design and digital R&D’ (2015a, 4). In short, PSI labs can be understood as a specific kind of ‘design-​for-​policy entrepreneur’. By this we mean that they are entities whose contribution to policy systems lies in their capacity to develop creative policy solutions using design approaches and methods, but that they also promote design approaches and are driven by design entrepreneurs. They can be understood as experimental sites ‘for solving the social and public problems that vex governments’ (Williamson, 2015b: 4). We claim that they are experimental in three related senses: as organisations; in their approaches and methods; and in policy-making. First, they are often ‘in and of themselves experimental initiatives’ in that they are predominantly small-​scale and ‘nascent structures’ rather than mature entities (Fuller and Lochard, 2016: 1). For example, the 35 (largely North American and European) PSI labs surveyed by Tõnurist and her colleagues (2017) had an average of just six to seven staff and a life-​span between three and four years (see also Fuller and Lochard, 2016). Among the 26 government-​based labs surveyed in Australia and New Zealand, 50 per cent had less than six staff and more than half were established within the last two years (McGann et al, 2018a). The small size of PSI labs affords them a degree of agility that many regard as crucial to their capacity to act as public ‘change agents’ (Schuurman and Tõnurist, 2017: 9). But it also makes their survival highly contingent on ongoing political patronage as they are comparatively easy to shut down compared with more established public sector organisations. This is illustrated by the recent closure of the longstanding MindLab, following a change in the Danish government’s political priorities (Guay, 2018). Those that endure, such as the UK Behavioural Insights Team, tend to be backed by ‘senior champions’ and high-​level secretaries ‘who are able to open doors and offer protection’ (John, 2014: 264). 133

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The second sense in which PSI labs can be understood as experimental concerns their role as structures for applying ‘experimental methods’ (Puttick, 2014: 4). PSI labs typically employ a toolbox of innovation approaches that combine a hybrid of ‘digital, data science, and especially design-​oriented methodologies’ such as human-​centred design and user ethnography. The methods and approaches that they bring are generally considered to require skills ‘beyond what most trained civil servants usually possess’ (Carstensen and Bason, 2012: 5). Their authority and influence therefore lies in their claims to methodological rather than subject-​matter expertise (Williamson, 2015a: 260), particularly as PSI labs tend to work across agencies and policy sectors rather than being geared towards a specific policy domain (Fuller and Lochard, 2016: 14). Several commentators expressly define PSI labs in terms of their commitment to taking a design thinking approach to public problem solving. For example, La 27e Région’s overview of public policy labs in EU member states defines them as ‘emerging structures that construct public policies in an innovative, design-​oriented fashion, in particular by engaging citizens and companies working with the public sector’ (Fuller and Lochard, 2016: 2). Similarly, Bason and Schneider (2014: 35 emphasis added) argue that PSI labs ‘tackle complex public/​social problems that more traditional governmental structures fail to resolve, in particular, using design to experiment and propose innovative public services and policies and at the same time reform and change the way government operates’. The third way in which they are experimental, PSI labs are often explicitly linked to a shift towards more participatory forms of policy-making –​which emphasise the empowerment of citizens and the role of ‘inter-​organisational communities of practice’ (Sørensen and Torfing, 2015: 154) in driving public and policy innovation (Carstensen and Bason, 2012; Schuurman and Tõnurist, 2017). Multi-​actor collaboration across various stages of the policy cycle, proponents argue, can fundamentally change the way that public problems are perceived (Mintrom and Luetjens, 2016) thereby preventing public sector organisations ‘from wasting money, time and energy on solving the “wrong” problem’ (Sørensen and Torfing, 2015: 152). In particular, involving those citizens who are affected by policy problems can help to reframe public problems in more acute ways ‘than professionals acting alone’ (Fung, 2015: 5) through overcoming information asymmetries between public administrations and service or policy users. This can enhance implementation outcomes by promoting greater awareness of citizens’ needs among public managers and ensuring that designs are empathetic to how citizens’ ‘experience and interact with social problems, services, and programs’ (Clarke and Craft, 2018: 8). As Hartley, Sørensen and Torfing (2013) argue, there are benefits from involving citizens throughout all stages of the design process –​in the definition and framing of problems, in the generation of new and creative solutions, and in the implementation of effective solutions. 134

When design meets power

These authors also argue that policy can be enhanced when it is created through participation and dialogue (Hartley et al, 2013: 825–​826). We therefore argue that PSI labs can be considered as design-​for-​policy entrepreneurs. They are exemplars of the championing and application of design thinking in the public sector and are often related to participatory approaches to policy-making. In the next section, we use an empirical study of PSI labs in Australia and New Zealand to assess their potential impact on policy systems.

Survey of Australian and New Zealand labs In 2013, the UK Design Council argued that there was relatively little evidence of design thinking being applied strategically in government. Despite the spread of PSI labs and the claims of their most ardent supporters, it remains unclear whether many labs undertake projects of a long-​term, complex nature or work on high-​level and strategic policy change. Previous studies suggest that their activities are more likely to be directed at discrete projects and service design, with few labs engaged in scaling or implementing solutions (Tõnurist et al, 2017; McGann et al, 2018b). Exploring this and related questions, a survey of PSI labs in Australia and New Zealand was conducted in early 2018 (McGann et al, 2018a) to map the emerging landscape of PSI labs in these countries, and to understand the impact of design thinking on policy. In our survey, PSI labs were asked about: the organisation’s size and history; their relationship to government; the background and skills of their staff; the policy areas they work on; the methods they use; and the levels of design and stages of innovation they focus on. For the purposes of this chapter, the analysis draws on the responses to questions on: 1. their methods (as an indication of the extent to which our claim that they are design for policy entrepreneurs is supported); 2. the levels of design and stages of innovation they are working on (an indication of their ability to have an impact on policy-making in practice); and 3. their relationship to government (an indication of their closeness to the policy process –​a proxy for their ability to have an impact on policymaking in practice). Because we were uncertain about how broadly we needed to search to find PSI labs, they were defined as any unit or team that was ‘established for the purposes of supporting public or social innovation’ including both ‘units within government, or the public sector, as well as non-​government organisations and labs that work with governments on public sector innovation’. Potential 135

Policy-Making as Designing Table 6.2: Profile of lab participants

New Zealand Australia

Based within government

Independent from government

Mixed organisations

5

7

1

21

16

2

participants were recruited through a variety of methods, including direct approaches to PSI labs that were already known to the researchers, publicising the survey through the supporting research unit’s email database, and via sub-​ national and national government networks. The online survey was promoted via Twitter using the hashtag #psilabs, which is commonly recognised by practitioners within the PSI labs field (Williamson, 2015a), and participating labs were also asked to nominate other units and teams via a snowball sampling approach. A total of 52 PSI labs responded to the survey, including 13 from New Zealand and 39 from Australia (see Table 6.2). Twenty-​six of the PSI labs that participated in the survey were based within various levels of government in Australia and New Zealand, while 23 identified as non-​government labs. Three were ‘mixed organisations’ that operated as a partnership between government and a community sector or non-​profit organisation. A map showing the names and geographical locations of the respondents is shown in the Appendix.

Methods Applying design thinking to policy implies not just wider engagement with citizens and the inclusion of multi-​actor networks in policy making but doing so through the mobilisation of specific sets of creative or ‘designerly’ techniques that are not typical of conventional policy approaches, such as mapping user journeys, design ethnography, prototyping and visual thinking (Design Council (UK), 2013; Kimbell, 2016). The methods ‘very’ or ‘quite frequently’ used by survey respondents (see Figure 6.1), confirms our conceptualisation of PSI labs as design-​for-​policy entrepreneurs. It illustrates that PSI labs, at least in Australia and New Zealand, make extensive use of methods associated with human-​centred design. About two thirds of these PSI labs reported using methods such as interviews or empathy conversations; systems thinking and mapping; citizen and stakeholder engagement; and user testing or prototyping ‘quite’ or ‘very frequently’. More traditional social-​ scientific methods such as ‘randomised control trials’, ‘survey research’, and ‘analysis of (big) data sets’ were less frequently used by our sample of PSI labs. Levels and stagesThe UK Design Council (2013) distinguishes three different levels at which design thinking may be employed within the public 136

newgenrtpdf

Figure 6.1: Methods used ‘quite’ or ‘very frequently’ by PSI labs (%)

Research literature/evidence reviews/syntheses

20 10 0

Ag i fra le m m et ew ho or ds k

Citizen/stakeholder engagement through workshops, walkthroughs, etc.

Hu des man ign -cen fra t me red wo rk

137

User testing or prototyping

30

Ethnographic methods such as participant observation

Analysis of existing (big) data sets

Design sprints

Agile or lean project management

Interviews and/or empathy conversations Focus groups

When design meets power

Randomised control trials or random assignment experiments 80 Service mapping or Behavioural Insights (re)design 70 Evi den 60 fra ce-ba Survey research Systems thinking or mapping me 50 wo sed rk 40

Policy-Making as Designing

sector –​what it calls ‘the public sector design ladder’: (i) design for discrete problems (usually service design projects); (2) design as a capability developed in public sector employees, and (3) design of policy. We include design as a stakeholder-​engagement or consultation tool as a fourth area, given the emphasis on this in the literature. This is an alternative to Buchanan’s (1992) ‘four orders of design’, with a focus on the third order of service design (discrete problems) and the fourth order of systems (policy) design. Buchanan’s (1992) first two orders of graphic and object design are excluded here since they are less relevant for policy-making. Figures 6.2 and 3 show the different levels of the public sector design ladder (discrete problems, capability building, stakeholder engagement/​consultation, and design for policy) and policy innovation cycles that PSI labs in Australia and New Zealand reported ‘quite’ or ‘very frequently’ working at, as a means for examining their focus in policy processes. Despite the complexity of contemporary policy challenges featuring highly in accounts of why PSI labs are needed, relatively few (less than 30 per cent) reported that they frequently worked at the design-​for-​policy level (that is, ‘developing policy proposals and reforms’). Indeed, this was the reform activity, or level of the public sector design ladder, that PSI labs were least likely to report frequently working on in our survey (see Figure 6.2). This contrasted with activities at the level of design for discrete problems, capability building and consultation. Figure 6.3 likewise shows that the PSI labs surveyed predominantly concentrate on the earlier stages of the innovation cycle (see Puttick, 2014: 14), namely: identifying/​ scoping problems and generating ideas, followed by piloting and prototyping solutions. Relatively fewer (less than half) reported frequently working on evaluation or scaling activities, while the proportion that reported working on ‘systemic change’ was also much lower than the proportion that reported being engaged in problem scoping activities or generating ideas –​core activities of almost all the surveyed PSI labs.

Relationship to government One of the common distinctions between PSI labs and other public sector organisations is ‘the power and control relations’ that separate them from the rest of government (Tõnurist et al, 2017: 9). This implies that PSI labs act as semi-​autonomous structures that operate somewhat outside traditional bureaucratic lines of authority. However, it is also the case that many PSI labs are located formally outside the public sector. This is reflected in the varying degrees of accountability to government reported by the PSI labs surveyed. As already observed, 23 of the labs surveyed were non-​government organisations that operated as either for-​profit or non-​profit organisations working in partnership with government departments and agencies. While 138

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Figure 6.2: Public sector design levels that PSI labs quite or very frequently engage in (%)

Business systems or process improvement

Service or customer experience (re)design

or n f on i sig De ultat s con Enhancing governmentcitizen or stakeholder communication/engagement

lity t abi Cap opmen el dev Supporting and developing partnerships

Providing training and skillsbuilding to public servants

When design meets power

e

t cre dis or ms n f le sig prob

139

Consulting with stakeholders

De

Developing policy proposals or reforms

Organisational change management 100 90 80 70 f o n 60 is g cy i De pol 50 40 30 20 10 0

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Figure 6.3: Stages of the innovation cycle that PSI labs quite or very frequently work at (%) Identifying and scoping problems 100 80 60

Generating ideas

40 20 140

0

Scaling and spreading new approaches, programs or services

Piloting/prototyping solutions

Evaluating programs/trials/pilots

Policy-Making as Designing

Working on systemic change

When design meets power

six of these were financially independent from government, eleven reported that more than half of their annual funding was ‘contract funding from government clients’. This illustrates the dependency of many non-​government PSI labs on public funding and suggests that they act as quasi-​public consultancies, akin to the ‘hidden public service’ of commissioned consultants identified by Craft and Howlett (2013: 194) in their research on the externalisation of policy advice. This is further supported by how frequently the non-​government PSI labs reported working on projects originating from government agencies and departments. As illustrated in Figure 6.4, 70 per cent indicated that the projects they typically work on either ‘quite’ or ‘very frequently’ originate from a government department or agency, whether at a state or federal level. One in four non-​government PSI labs also reported ‘quite frequently’ working on projects originating from the central branches of government. Of the government-​based PSI labs surveyed, these were structurally located at varying levels (local, state, and national government) and in a range of different branches of government, but rarely across agencies or different levels of government. This does not mean that they were not working across levels or agencies; rather, it reflects structural arrangements that were generally with(in) a single department. Despite government-​based PSI labs being largely situated within existing government structures, under the auspices of a single parent agency or department, they nevertheless reported a considerable degree of autonomy to determine their work priorities and projects. When asked, ‘Who ultimately determines or decides which priorities and projects your unit or team works on?’, 13 of the government-​ based PSI units reported that these decisions were made internally, either collectively by the staff or, more typically, by the director or manager of the lab. Only five reported that these decisions were made by the head or executive of the department or agency within which they were situated. This could suggest some disconnection between labs and the policy process. Even if they are located within government, their freedom to innovate and independence to determine their own projects may mean that their work is not directly aligned to current political or policy priorities.

Conclusion: design thinking and policy-making Our aim in this chapter has been to examine what, if anything, is really new about design thinking for policy, how it differs from and challenges other approaches to policy-making, and what impact design thinking might be having on policy-making systems in practice. Analytically, we have argued that design thinking incorporates imagination, creativity and playfulness within the epistemological framework of policy-making in a way that rational-​process and even participatory approaches to policy-making 141

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Figure 6.4: Where projects originate from (non-​government PSI labs)

A government department or agency Central executive branch of government (e.g. a Prime Minister's or Mayor's Office) Policy-Making as Designing

Your parent department(s) or agency(ies) (if relevant) Private enterprises or businesses 142

Community sector (not-for-profit) organisations A local or municipal government From within your own unit or (e.g. self-generated projects) 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Never or not very often

Sometimes

Quite frequently

Very frequently

When design meets power

have historically struggled to do. In so doing, it recasts policy-making as a more reflexive, uncertain and even ambiguous process compared with the instrumental rationality of policy-making as depicted in policy handbooks or the deliberative tribunal of participatory models. The realisation of this alternative approach to policy-making will depend however on how design thinking is operationalised and drawn upon in practice by governments and other key policy actors. Hence, we used an empirical study of PSI labs in two nations to understand what impact, if any, design thinking might be having on policy-making systems in practice. These rapidly multiplying exemplars of design thinking are being promoted by their supporters as radically changing approaches to solving policy problems, so provide a useful focus. Our results indicate that while PSI labs are positioned as potential contributors to the policy process and are seen to be providing opportunities for improving policy design, they are so far having minimal impact on policy through changing practices and models for decision-​making. The activities of PSI labs are predominantly concentrated at the front end of the policy and innovation cycles. Similar to their counterparts around the world (McGann et al, 2018b), labs in Australia and New Zealand focus on: scoping and defining problems, generating ideas, and, to a lesser extent, prototyping solutions. Moreover, insofar as PSI labs are involving citizens and other stakeholder networks in these processes of problem definition, ideating and prototyping solutions, our findings suggest that PSI labs are generally working at the level of solving discrete service delivery problems rather than high-​level policy development. That is, PSI labs are more likely to work on process and service innovation projects, where design thinking homes in on the experiences of citizens interacting with government services and helps develop more client-​focused solutions (Mintrom and Luetjens, 2016) without necessarily involving citizens in deciding what (or how or whether) programmes and services should be delivered. Some of the recent literature (Clarke and Craft, 2018; Peters, 2018) has similarly questioned the likely ‘fit’ of design thinking with more traditional policy design. Tõnurist and colleagues attribute the front-​end focus to PSI labs’ small size and partial autonomy from the rest of the public sector, which limits their ability ‘to catalyse and push through public sector-​wide changes’. They also suggest that this may in fact be dangerous for PSI labs, with labs risking disestablishment when they come too close to the policy process. The more policy-​driven their activities are, the more resistance they encounter both inside and outside the public sector. Hence, labs tend to specialise in ‘quick experimentations’ but lack ‘the capabilities and authority’ to influence the scaling-​up and implementation of solutions (Tõnurist et al, 2017: 1473). On the other hand, given that design thinking is very much about spending time creatively addressing the multiple and conflicting statements that go hand in hand with challenging problems (Dorst, 2011), perhaps it is not 143

Policy-Making as Designing

surprising that this is where the attention of PSI labs has fallen within the policy cycle. Further, some claim that design thinking is not able to provide guidance on how to address politically contentious policy-making activities in practice, and hence it is not surprising that it focuses on service delivery (Clarke and Craft, 2018). PSI labs face similar challenges to those of other proponents of co-​design for policy, which combines elements of the participatory and design thinking approaches delineated above. Co-​design is typically applied in small, site-​ specific groups and in localised settings, which renders the prospects of scaling the results into system-​wide responses with multiple delivery channels problematic (Blomkamp, 2018). Clarke and Craft (2018) also claim that there is little evidence that design thinking’s methods can be standardised and scaled up to an entire policy sector, or government, over long periods of time. This underscores the potential limitations of participatory and design approaches to policy. While reframing problems and ideating solutions with citizens might be feasible for solving community problems in localised settings, the vocabulary and methodic practices of design may start to crumble when they are extended to system-​wide challenges and understanding the complicated linkages between the public, the market and the state (Chen et al, 2016). Moreover, the development and dissemination of design capabilities both within and by labs remains a real challenge for public sector innovation; these new logics and practices require significant cultural change and capacity building to embed within government (Christiansen, 2016; Malmberg and Holmlid, 2018). As Dorst (2011: 528) notes, one of design thinking’s central activities –​new frame creation –​‘looks to be a largely informal activity’. The contrast with well understood approaches like surveys is likely to make creative activities appear wildly unproductive and unfocused to cash-​ strapped governments. PSI labs may be helping to drive a more participatory and design-​oriented approach to public service innovation, but they are still some distance from achieving wider impacts on policy-making. Innovative, collaboratively proposed ideas must still be diffused into the larger policy-making process and ‘sold’ to decision-​makers. Design-​oriented approaches may remain ‘tools’ for generating policy options rather than forums for designing (and making) policy decisions (Bailey and Lloyd, 2016). That is, design thinking (and the work of PSI labs) may be valued simply as the latest novel way for generating policy relevant knowledge and increasing the pool of ideas available to decision-​makers, without realising either greater creativity, or its potential to challenge and reshape policy-making into a more democratic and participatory process (Kimbell, 2016). In addition, design thinking can be seen as presuming that networked models of governance and user-​ centred approaches are always the best approach (Clarke and Craft, 2018). But institutional and cultural factors will surely continue to influence the 144

When design meets power

voices and forms of knowledge that take precedence in policy systems, and the broader range of policy design options available will (and should) be considered in the context of what is the best fit for a particular policy purpose, against the background of a multi-​layered policy context. From a policy design perspective, design thinking is divorced from institutions in the public sector and without strong links it will remain isolated and have little impact (Peters, 2018). Design thinking’s strength in opening up possibilities where there is little received wisdom and not many rules becomes its weakness when other policy tools need to be used to address problems and when institutions are required to make a design work. From the design-​for-​policy side, there are a substantial set of challenges. It has the potential to benefit governments wanting to address complex and open-​ ended challenges, but its practices simply might not fit with the constraints and realities of policy-making, which is ultimately a political act. Opportunities to combine insights from design thinking into policy design could nonetheless help to complement and improve on older forms of designing policy. Perhaps, as others have suggested, improvement in policy design rests on importing some of the best aspects of design thinking into policy design, rather than believing in a wholesale replacement of traditional approaches as a cure-​all. Policy design can aim to address all three of the foundations of evidence, discussion and imagination described in this chapter. Speaking to power can be based on each of technical expertise, democratic ideals and creativity, if these are treated as complementary rather than mutually exclusive virtues. In conclusion, we argue that if policymakers learn how to incorporate the insights and practices from design thinking into policy, and designers learn how to deal with the politics of the policy process, there could well be significant benefits for policy design and for everyone who is affected by it. Our examination of the conceptual foundations of design thinking, in order to assess whether it is really something new for policy-making, and whether it challenges alternative approaches to policy-making, suggests both complementarities and tensions. But in regard to its practical impact, there is little to suggest that it has (as yet) been significant in regard to having an impact on policy-making, although much more research needs to be done before solid claims can be made on this front. Our survey was relatively small and conducted in just two nations. The experiences of PSI labs in Australia and New Zealand may not be representative of their counterparts more globally, although our findings on the methods used by PSI labs, the service-​oriented focus of their work, and level of autonomy over the determination of their work priorities resonate with those of international studies (for example, Fuller and Lochard, 2016; Tõnurist et al, 2017). Our questions on methods, levels and stages in policy and innovation, and the relationship with government, provide some first indicators of how design 145

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thinking is being applied and how it is affecting policy-making. More study of this field, and over a longer time period, is needed before conclusions about design thinking and its impact on policy-making become clearer and stronger. Acknowledgements Part of the research upon which this chapter is based was funded by a grant from The Australia and New Zealand School of Government.

References Adams, D. (2004) ‘Usable knowledge in public policy’, Australian Journal of Public Administration, 63(1), 29–​42. doi: 10.1111/​j.1467-​8500.2004.00357.x Althaus, C., Bridgman, P., Davis, G. (2013) The Australian Policy Handbook (Crows Nest, NSW: Allen & Unwin). Bailey, J., Lloyd, P. (2016) ‘The introduction of design to policymaking: Policy Lab and the UK government’, Proceedings of DRS 2016: Design +​Research +​ Society, eds P. Lloyd, E. Bohemia (Brighton: Design Research Society), pp 3619–​3634. Bason, C. (2013) ‘Discovering co-​production by design’, Public and Collaborative: Exploring the Intersections of Design, Social Innovation and Public Policy, eds E. Manzini, E. Staszowski (New York: DESIS Network), pp viii–​xvi. Bason, C. (2014) Design for Policy (Farnham and Burlington, VT: Routledge). Bason, C., Schneider, A. (2014) ‘Public design in global perspective: empirical trends’, Design for Policy, ed. C. Bason (Farnham: Routledge), pp 23–​40. Bjögvinsson, E., Ehn, P., Hillgren, P. -​A. (2012) ‘Design things and design thinking: Contemporary participatory design challenges’, Design Issues, 28(3), 101–​116. Blomkamp, E. (2018) ‘The promise of co-​design for public policy’, Australian Journal of Public Administration, 4(77), 729–​743. doi: 10.1111/​ 1467-​8500.12310 Bridgman, P., Davis, G. (2003) ‘What use is a policy cycle? Plenty, if the aim is clear’, Australian Journal of Public Administration, 62(3), 98–​102. doi: 10.1046/​j.1467-​8500.2003.00342.x Buchanan, R. (1992) ‘Wicked problems in design thinking’, Design Issues, 8(2), 5–​21. doi: 10.2307/​1511637 Carstensen, H. V., Bason, C. (2012) ‘Powering collaborative policy innovation: Can innovation labs help?’, The Innovation Journal, 17(1), 2–​26. Centre for Policy Innovation and Public Engagement (2018) The Rise of Policy Innovation Labs: A Catalog of Policy Innovation Labs Across Canada (Toronto: Ryerson University). Chen, D. -​S., Lu-​Lin, C., Hummels, C., Koskinen, I. (2016) ‘Social design: An introduction’, International Journal of Design, 10(1), 1–​5. 146

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Christiansen, J. (2016) ‘Embedding design: Towards cultural change in government’, Service design impact report: Public sector, ed. B. Mager (Cologne: Service Design Network), pp 48–​59. Clarke, A., Craft, J. (2018) ‘The twin faces of public sector design’, Governance, 32(1), 5–​21. Colebatch, H. K. (2005) ‘Policy analysis, policy practice and political science’, Australian Journal of Public Administration, 64(3), 14–​23. doi: 10.1111/​ j.1467-​8500.2005.00448.x Considine, M. (2012) ‘Thinking outside the box? Applying design theory to public policy’, Politics & Policy, 40(4), 704–​724. Considine, M., Lewis, J. M. (2003) ‘Bureaucracy, network, or enterprise? Comparing models of governance in Australia, Britain, the Netherlands, and New Zealand’, Public Administration Review, 63(2), 131–​1 40. doi: 10.1111/​1540-​6210.00274 Craft, J., Howlett, M. (2013) ‘The dual dynamics of policy advisory systems; The impact of externalisation and politicisation on policy advice’, Policy and Society, 32(3), 187–​197. Design Council (UK) (2013) Design for Public Good [Online] (London: Design Council UK) https://​ojs.unbc.ca/​index.php/​des​ign/​arti​cle/​downl​oad/​ 540/​479. Dorst, K. (2011) ‘The core of ‘design thinking’ and its application’, Design Studies, 32(6), 521–​532. doi: 10.1016/​j.destud.2011.07.006 Dryzek, J. S. (2002) ‘Policy analysis and planning: From science to argument’, The Argumentative Turn in Policy Analysis and Planning, eds F. Fischer, J. Forester (Durham, NC: Duke University Press), pp 213–​232. Fischer, F., Forester, J. (eds) (1993) The Argumentative Turn in Policy Analysis and Planning (Durham, NC: Duke University Press). Fraussen, B., Halpin, D. (2017) ‘Think tanks and strategic policy-​making: The contribution of think tanks to policy advisory systems’, Policy Sciences, 50(1), 105–​124. doi: 10.1007/​s11077-​016-​9246-​0 Fuller, M., Lochard, A. (2016) Public Policy Labs in European Union Member States (Luxembourg: European Union). Fung, A. (2015) ‘Putting the public back into governance: the challenges of citizen participation and its future’, Public Administration Review, 75(4), 513–​522. doi: 10.1111/​puar.12361 Guay, J. (2018) ‘How Denmark lost its MindLab: the inside story’, Apolitical [Online] https://​apo​liti​cal.co/​solut​ion_​arti​cle/​how-​denm​ark-​lost-​its-​mind​ lab-​the-​ins​ide-​story/​. Hartley, J. (2005) ‘Innovation in governance and public services: Past and present’, Public Money & Management, 25(1), 27–​34. Hartley, J., Sørensen, E., Torfing, J. (2013) ‘Collaborative innovation: a viable alternative to market competition and organisational entrepreneurship’, Public Administration Review, 73(6), 821–​830. doi: 10.1111/​puar.12136 147

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Head, B. W. (2008) ‘Three lenses of evidence-​based policy’, Australian Journal of Public Administration, 67(1), 1–​11. doi: 10.1111/​j.1467-​8500.2007.00564.x Hekkert, P., Van Dijk, M. (2011) Vision in Design: A Guidebook for Innovators (Amsterdam: BIS Publishers). Hoppe, R. (1999) ‘Policy analysis, science and politics: from ‘speaking truth to power’ to ‘making sense together’, Science and Public Policy, 26(3), 201–​210. doi: 10.3152/​147154399781782482 Howlett, M. (2014) ‘From the ‘old’ to the ‘new’ policy design: Design thinking beyond markets and collaborative governance’, Policy Sciences, 47(3), 187–​207. doi: 10.1007/​s11077-​014-​9199-​0 Iskander, N. (2018) ‘Design thinking is fundamentally conservative and preserves the status quo’, Harvard Business Review. https://​hbr.org/​2018/​ 09/​des​ign-​think​ing-​is-​fundam​enta​lly-​conse​rvat​ive-​and-​preser​ves-​the-​sta​ tus-​quo?autoc​ompl​ete=​true John, P. (2014) ‘Policy entrepreneurship in UK central government: the behavioural insights team and the use of randomised controlled trials’, Public Policy and Administration, 29(3), 257–​267. doi: 10.1177/​0952076713509297 Kimbell, L. (2016) ‘Design in the time of policy problems’ Proceedings of DRS 2016: Design +​Research +​Society, eds P. Lloyd, E. Bohemia (Brighton: Design Research Society), pp 3605–​3618. Kolko, J. (2018) ‘The divisiveness of design thinking’, Interactions, 25(3), 28–​34. doi: 10.1145/​3194313 Lerner, D., Lasswell, H. D. (eds) (1951) The Policy Sciences: Recent Developments in scope and method (California: Stanford University Press). Lewis, J. M. (2003) ‘Evidence based policy: a technocratic wish in a political world’, Evidence-​based health policy: problems and possibilities, eds V. Lin and B. Gibson (Melbourne: Oxford University Press), 250–​259. Lewis, J. M., Ricard, L. M., Klijn, E. H., Figueras, T. Y. (2017) Innovation in City Governments: Structures, Networks, and Leadership (New York: Routledge). Malmberg, L., Holmlid, S., (2018) ‘Learning to design in public sector organisations: a critique towards effectiveness of design integration’ ServDes 2018 (Milan: Linköping University Electronic Press). McGann, M., Lewis, J. M., Blomkamp, E. (2018a) ‘Mapping public sector innovation units in Australia and New Zealand: 2018 survey report’ (Melbourne: The Policy Lab, University of Melbourne). McGann, M., Blomkamp, E., Lewis, J.M. (2018b) ‘The rise of public sector innovation labs: experiments in design thinking for policy’, Policy Sciences, 51(3), 249–​267. Mintrom, M. (1997) ‘Policy entrepreneurs and the diffusion of innovation’, American Journal of Political Science, 41(3), 738–​770. Mintrom, M., Luetjens, J. (2016) ‘Design thinking in policymaking processes: opportunities and challenges’, Australian Journal of Public Administration, 75(3), 391–​402. doi: 10.1111/​1467-​8500.12211 148

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O’Rafferty, S., de Eyto, A., Lewis, H. J. (2016) ‘Open practices: lessons from co-​design of public services for behaviour change’, Proceedings of DRS 2016: Design +​Research +​Society, eds P. Lloyd, E. Bohemia (Brighton: Design Research Society), pp 3573–​3590. Osborne, S., Brown, L. (2013) ‘Introduction: innovation in public services’ Handbook of Innovation in Public Services [Online], eds S. P. Osborne, L. Brown (Cheltenham: Edward Elgar Publishing), pp 1–​11, www.elga​ronl​ ine.com/​view/​978184​9809​740,xml. Parsons, W. (2002) ‘From muddling through to muddling up: evidence based policy making and the modernisation of British government’, Public Policy and Administration, 17(3), 43–​60. doi: 10.1177/​095207670201700304 Peters, B. G. (2018) Policy Problems and Policy Design (Cheltenham: Edward Elgar Publishing). Price, A. (2015) ‘World of labs’, World of Labs [Online] www.nesta.org.uk/​ blog/​world-​labs. Puttick, R. (2014) Innovation Teams and Labs: A Practice Guide [Online] (London: NESTA) www.nesta.org.uk/​publi​cati​ons/​inn​ovat​ion-​teams-​ and-​labs-​pract​ice-​guide. Renn, O. (2006) ‘Participatory processes for designing environmental policies’, Land Use Policy, 23(1), 34–​43. doi: 10.1016/​j.landusepol.2004.08.005 Sanoff, H. (1990) Participatory Design: Theory & Techniques (Raleigh, NC: Bookmasters). Schuurman, D., Tõnurist, P. (2017) ‘Innovation in the public sector: exploring the characteristics and potential of living labs and innovation labs’, Technology Innovation Management Review, 7(1), 7–​14. doi: 10.22215/​timreview/​1045 Sørensen, E., Torfing, J. (2015) ‘Enhancing public innovation through collaboration: leadership and new public governance’, New Frontiers in Social Innovation Research [Online], eds A. Nicholls, J. Simon, M. Gabriel (London: Palgrave Macmillan), pp 145–​169, http://​link.sprin​ger.com/​ 10,1057/​978113​7506​801. Sørensen, E., Waldorff, S. B. (2014) ‘Collaborative policy innovation: problems and potential’, The Innovation Journal, 19(3), 1. Tõnurist, P., Kattel, R., Lember, V. (2017) ‘Innovation labs in the public sector: what they are and what they do?’, Public Management Review, 19(10), 1455–​1479. Torjman, L. (2012) Labs: Designing the Future (Ontar io: MaRS Discovery District). Voorberg, W. H., Bekkers, V. J., Tummers, L. G. (2015) ‘A systematic review of co-​creation and co-​production: embarking on the social innovation journey’, Public Management Review, 17(9), 1333–​1357. doi: 10.1080/​ 14719037.2014.930505

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Wagle, U. (2000) ‘The policy science of democracy: the issues of methodology and citizen participation’, Policy Sciences, 33(2), 207–​223. doi: 10.1023/​A:1026500906034 Williamson, B. (2015a) ‘Governing methods: policy innovation labs, design and data science in the digital governance of education’, Journal of Educational Administration and History, 47(3), 251–​271. doi: 10.1080/​ 00220620.2015.1038693 Williamson, B. (2015b) Testing Governance: The Laboratory Lives and Methods of Policy Innovation Labs [Online], (Stirling: University of Stirling) https://​ code​acts​ined​ucat​ion.wordpr​ess.com/​2015/​03/​30/​test​ing-​gov​ernm​ent/​. Yanow, D. (1996) How Does a Policy Mean?: Interpreting Policy and Organizational Actions (Washington, DC: Georgetown University Press).

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Designing institutions for designing policy B. Guy Peters

The formulation and subsequent implementation of public policy is inherently a design activity (Simon, 1969). Designing involves recognising the existence of a problem present within the economy and society, attempting to understand the dynamics operating within that problem, and then devising a putative solution. Policy design is both a process of conscious thinking about options for good policy and the outcome of that process (see Howlett and Mukherjee, 2018). Whether the design activity is implicit or explicit it still exists, and ultimately the manner in which the design occurs will affect the success, or lack thereof, of the policy that results from that policy-making. A second premise, in addition to the perhaps obvious one that policymaking involves design, is that the institutions within which designing occurs will influence the type of designs which emerge, and also therefore affect the probabilities of success (leaving aside for the time being the meaning of success, but see Bohni et al, 2015) of the policy once designed. The various strands of reform in public administration, for example, may have had differential effects on the capacity to devise innovative and flexible approaches to policy. Throughout this chapter I will be demonstrating that the nature of designs and the institutions that perform the designing are closely connected. The influence of institutions on policy appears to involve two questions about those institutions. The first is choice of the institution itself. Legislatures will design differently than will the public bureaucracy, and both will design differently from the courts if they were to become involved in the process.1 And all of those institutions may design differently from policy labs or other organisations created specifically to foster policy innovation. At this level there may, however, be little real choice given institutionalised patterns of making decisions within the public sector as well as the capacity of external actors to venue shop and find means of activating one institution or another to become engaged in policy design activities Within institutions the structure and culture of the individual organisations will affect the manner in which designing takes place. We may posit that all bureaucracies involved in policy design will have some common characteristics, but there are also marked differences among versions of the 151

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bureaucracy that will affect their decisions about policy (see, for example, Cervantes and Radge, 2018). But to understand the relevance of those variations among institutions, and therefore to design better institutions for designing better policies, it is first necessary to consider the nature of policy design (see Brown and Watt, 2015), and the emerging emphasis on innovation and innovative organisations for design (Lewis, 2018). When we consider creating policy design institutions within and without the public sector we must remember that they are entering an already crowded institutional field. Policy advice is a game that any number of actors can play, and already have been playing for years (see Bandola-​Gill and Lyall, 2015). The question then becomes what is the value-​added for the newer, more innovative, approaches to policy advice that are connected with institutions such as the policy labs featured in many of the chapters in this volume. Scholars may be more enamoured of these newer approaches to policy advice than are practitioners, who may simply want an answer quickly and in their own terms, rather than an innovative solution to a problem that they did not know existed.2 This chapter will begin with a brief discussion of policy design ideas as they have developed over the past several decades. While policy formulation is inherently a component of the policy process, the concern with design is more recent and the contemporary ideas about designing should be considered. I will then proceed to a discussion of some of the institutional barriers to design, and especially those varieties of design considered newer and more innovative. And it will conclude with a discussion of the dilemmas which designers face as they attempt to have their ideas and their innovations introduced successfully in the public sector.

A short discourse on policy design As argued earlier, public policy studies is a design discipline, in some ways analogous to engineering or architecture. The expectation was that with sufficient cogitation and research policy scientists could produce mechanisms that would readily enable the design of policies that would work, and which could meet a specified set of goals. While this approach seriously underestimated the complexities of policy-making, it did initiate an ongoing search for the means through which policy-makers could design more effective programmes. In some ways the most recent spate of interest in policy design may be as naive, assuming that it will be relatively easy to develop and innovate solutions and creative ways of solving policy problems. ‘Old’ policy design Much of the early literature on policy design attempted to mimic the technocratic style of engineering, and perhaps also some elements of 152

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architecture, and develop algorithms for solving policy problems by linking those problems with an array of instruments. And then both choices of design attributes and their outcomes must be linked, with a set of values that would be used to assess the results of the design exercise (Linder and Peters, 1984; 1991). At this time there was great optimism (at least among some) that we could find ways to run policy problems through the ‘issue machine’ (Braybrooke, 1974) and generate usable results for the society. Those technocratic dreams foundered on the multiple shoals created by the real world of public policy, including political complexity, inadequate knowledge of policy dynamics, and the equifinality of most policy processes. The military adage that plans last until the first contact with the enemy could be used in a modified form to help understand why policy designing was rarely as successful as hoped. Policy designs also tend to produce sub-​optimal results in many cases in part because their enemy may be the very people they were intended to help –​citizens. That is, any policy design is based on assumptions about the behaviour of citizens that may well be based on excessively simplistic understanding of their reactions to policy. The idea of design has resurfaced several times in policy studies. One (see Howlett and Lejano, 2013; Howlett and Mukherjee, 2018) renaissance was characterised by an emphasis on policy instruments, although it tended to focus less on making the technocratic linkages that were central to the first round of design literature. Rather, it has tended to focus more on the nature of the instruments themselves. This second round of policy design tended to involve more concern with public administration than did the first major attempts, in part because instruments can be conceptualised as aspects of implementation through public sector organisations and their allies in the private sector. Further, there was an interest in thinking about portfolios of instruments that could be implemented, rather than dealing with individual instruments ad seriatim (Howlett and Rayner, 2013). Policy instruments are, however, only one element of policy design, and an excessive focus on that element of design may divert attention from even more fundamental issues. Focusing on instruments, for example, assumes that the designers understand fully the characteristics of the problem they are confronting, and further that it is a reasonably well-​structured problem that can be solved through conventional means. Even if one rejects the notion of wicked problems, or believes that the term is used in excess (Peters and Tarpley, forthcoming), many contemporary policy problems are poorly structured (Dunn, 2018) and it is difficult to map a set of solutions onto the array of problems that require solutions. Newer approaches to policy design, which may in turn be related to newer institutions, appear necessary to address those problems. And even more conventional and well-​structured problems may profit from more innovative solutions. Every existing policy domain has a more or less well-​established 153

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repertoire of dealing with the issues in that domain, and path dependency may dominate innovation. But how can innovation be brought into the policy design process so that better solutions are considered, if not necessarily adopted, for policy problems old and new? The ‘new design’ The most recent spate of interest in policy design has moved beyond the technocratic search for an almost magical algorithm to thinking about a more open and less mechanistic conception of design. This version of policy design is informed by developments in product design. While designing a major public policy may not appear similar to designing an automobile or a chair, the fundamental task is very similar. There is a problem, or perhaps an opportunity, and the best option for ‘solving’ that problem must be identified and then implemented. The solution may be more or less elegant or more or less successful, but the task remains to develop that solution. Although I will be typifying these dimensions of designing as ‘new’, at least some have been discussed for at least a decade or two in public administration and in public policy. In particular, the idea of making policy formulation more participatory and collaborative can hardly be considered new as an idea any longer (Donahue and Zeckhauser, 2011; Bason, 2016; 2018). But in practice the principle of collaboration often is ignored, as designers revert to their familiar insulated and routinised forms of policy formulation. This new design is in many ways the opposite of the older version of design. Perhaps most fundamentally the old design emphasised narrowing the parameters of choice in as rapid as possible a manner in order to come up with ‘the solution’. The new design, on the other hand, attempts to open up the problem and prevent any premature closure –​so-​called ‘upstreaming’. Perhaps what is most important is that newer approaches to design attempt to consider as wide a range of possible interventions as possible before beginning to narrow choices. The assumption of this version of design is that most designers, and perhaps especially design institutions, tend to have a limited repertoire of ideas that they tend to apply to any and all situations. A second principle of the new design is that designing should be open and participatory (Hisschemoller and Hoppe, 2018). This approach is in marked contrast to the conventional version of design which tends to have more restricted involvement of actors. With the development of more participatory and collaborative forms of governance it rather naturally follows that the design process for policy should also be more open. This openness is evident procedurally, and it is also argued to be true for the substance of design. If the intention is to gather more possible solutions before then beginning to winnow down those options, then enhanced participation is a useful tool for eliciting more involvement and more ideas. 154

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It is important to note, however, that not all newer design ideas are collaborative (see Considine, 2012). What is more fundamental is the openness of the process and the avoidance of premature closure. That openness can be achieved through involving a range of experts as well as through involving stakeholders, including the public, into the process. While the more technocratic solution may appear contradictory to the contemporary ideas favouring collaboration in the public sector, ‘upstreaming’ and focusing on multiple alternatives can be done with properly motivated and structured groups of experts as well as by involving stakeholders. A third principle of newer versions of policy design is that ambiguity is useful, Again, this is in marked contrast to the conventional models of policy design that have aimed for more definitive designs and clear ‘answers’ to policy problems. The difficulty with that perspective on design has been that the problems that governments face are often not so well structured as to permit such clear answers. Herbert Simon (1973) and other policy scholars (Dunn, 2018) have argued for the importance of well-​structured problems for finding solutions to those problems, but the real world tends to arrive on the designer’s computer screen in much messier forms. Therefore, more ambiguous responses may be more effective in coping with this very difficult policy world. It follows naturally from the principle of ambiguity that flexibility is important for good policy design, at least within the context of contemporary design. Much of conventional design has sought greater control over policy and administration through the design. Especially more conservative analysts concerned about the power of the ‘deep state’ or with the almost inevitable policy drift that occurs during implementation may want to design ‘tamper-​ proof ’ instruments (McCubbins et al, 1969). But as already noted, problems do not stand still, even if they are well-​structured at some point in time, so therefore designs for intervention should be capable of adaptation. Further, most policy design is redesign, rather than being written on a tabula rasa (Carter, 2012) and hence designing in flexibility from the outset will improve long-​term outcomes.3 The emphasis on ambiguity and flexibility in policy design may be analogous to concepts such as ‘strategic agility’ that have been more common in the private sector (Doz and Kosenen, 2010). While that term may appear an oxymoron, it actually describes well the demands on designers, public or private, to develop designs that combine some sense of long-​term strategic goals with the capacity to respond with some agility and flexibility to change in the short-​run. The design thus combines strategic goals with the capacity for tactical actions that are not programmed in advance, but represent seizing opportunities as presented by change in the operational environment. Following from the arguments about flexibility and adaptability the new design perspective argues for more systemic design (see Checkland and Poulter, 155

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2010). Much of the older design literature focused on designing objects –​a specific instrument or perhaps a group of instruments intended to alleviate a very specific and generally well-​structured policy problem. Policy designers are increasingly understanding that the world of policy problems is not quite so neatly delineated into policy domains and specific issues. Therefore, thinking about design in more systemic terms is also about thinking about boundary spanning institutions, organisations and individuals who can link problems and solutions. The dangers of over design All the hymns of praise to newer forms of policy design referred to earlier having been sung, however, there is the need to accept that not all policymaking will require highly innovative forms of policy. Indeed, one might argue that in some instances, ‘over-​designing’ policy may be as unprofitable as under-​designing.4 That is, simple solutions may be best for simple problems, and in some cases simple solutions may be best for complex problems because they may provide clearer opportunities for learning. A more complex solution with many moving parts may obfuscate any causal relationships between the intervention and the outcomes (see Peters, 2018: 54). The ‘new’ design processes described earlier may be more conducive to ‘over-​design’ than more traditional forms of policy formulation. By involving more actors and more alternative solutions in the process there is the danger of building Heath Robinson5 policy interventions that can include some elements of the ideas of all participants. The difficulty, of course, is that in any of the forms of design there may be no strong ex ante guidance about what will work, other than perhaps experience and judgement, which would tend to drive designing back to more traditional institutions and actors. Institutional designs and policy designs The earlier discussion of policy design, both old style and new style, provides a foundation for thinking about what sort of institutional structures might be most conducive to producing effective policy designs. That is no simple question, and raises at least two subsidiary questions. The first of these is that are we thinking about institutional structures more at a macro or a micro level. That is, are we thinking about how constitutional structures or at least structures of the public bureaucracy as a whole will shape policy-making and policy design, or are we thinking about how individual organisations within the bureaucracy are structured in order to make designing more effective? The second question is whether we are thinking about ‘old’ or ‘new’ design as the approach to formulating policy in the institution? These categories may 156

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watertight, but the general differences in styles of designing are important for understanding the institutions selected for the process. We could begin with a hypothesis that institutions that are good at one mode of policy design are unlikely to be good at another. This is true both for macro-​and micro-​level versions of institutions. Institutional designers can operate at both levels of generality when attempting to create structures that can facilitate creativity and consideration of a wider range of options in policy designing. If we put those two attributes –​institutions and styles of design –​together, Table 7.1 shows some examples of institutional structures which may be engaged in designing. This rather simple typology is descriptive, but it also can be prescriptive. That is, if the would-​be designer wants to create new and highly innovative design then he or she should not begin the institutions that are likely to emphasise path-​dependency and recreate only slightly different versions of existing policies. As will be pointed out later, the tendency of public bureaucracies in particular to resist innovation can be a major problem for more innovative policy designers, but at the same time may be a virtue of sorts for maintaining some level of credible commitment in programmes. It is also possible, however, to go too far in assuming that bureaucracies are inherently stodgy and resistant to innovation. Some bureaucracies, and especially some individual public administrators are committed to major change within the administrative system, and in the policies they administer. The typology presented in Table 7.1 is therefore a statement of tendencies rather than an ironclad law about the linkage of bureaucracies to older-​ style designing. The question of institutional engineering is an immense topic in itself, but in this chapter, I will focus more on the likely effects of institutional

Table 7.1: Institutions and designing Institutions Design style

Macro

Micro

Old

Parliaments

‘Policy shops’

Conventional bureaucracies

Within ministries

Audit institutions

Think tanks*

Collaborative

Autonomous

Participatory

Policy labs

Governance

Expert commissions

New

Note: *Especially those linked to political parties or interest groups

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structures on the capacity to design creative policy interventions. And more particularly on the capacity to generate those creative outcomes in the public sector, faced with numerous organisational and political constraints, such as those discussed in the following section. This discussion does not cover the possible success or failure of any of the policy designs, but is more concerned with how, and if, they will emerge from the processes within the institution.

Barriers to effective policy design If policy designing were easy, probably everyone would do it, and do it better than it appears to be performed in most contemporary governments. But designing is not easy, and would-​be designers face a range of constraints on their capacity to create new solutions to policy problems. This discussion will focus on newer instrumentalities of designing, but some of the same factors would apply to older forms of design as well (see de Vries et al, 2014). None of these impediments to design are insuperable, but they must be considered when designing institutions that are expected to then design policy. The other chapters in this volume have focused on the virtues of newer institutions for design, such as policy labs, policy charettes and other collaborative mechanisms, but this discussion will some caveats to that discussion. Political characteristics The first point for designing in the public sector is that politics is always present, and is always trumps. The technocratic perspectives of the early design literature often ignored the political elements that were inherent in any attempt to make public policy. Without turning this chapter into a short course in comparative politics, there are a number of factors that need to be considered. One will be the legitimacy of public interventions into economy and society, with less étatiste regimes generally less open to innovative, and therefore risky, designs. Also, Arend Lijphart’s familiar distinction between majoritarian and consensual democracies may play a role in designing policies. Everything else being equal, majoritarian regimes may produce clearer, and perhaps more innovative designs, while consensus regimes will produce more stable, albeit less innovative policies. Politicians, and increasingly bureaucrats, also must live in a world with a limited time horizon. For politicians, the time horizon is the next election, while for bureaucrats it may be the next performance review. Thus, designing highly innovative policies that may require time to be accepted and to have their anticipated impacts becomes difficult, and the actors may opt for a short-​term ‘patch’ (Howlett and Rayner, 2013) rather than a more genuine design or redesign of policy. Further, time is cultural as well as chronological, 158

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so that what appears to be a very long time in one culture may be a short time in another (Schneider, 1991). One of the important political features operating as a barrier to newer design strategies and institutions is the segmentation of the political system, both horizontally and vertically. As noted earlier, one component of newer approaches to policy design is an attempt to think more systemically rather than in discrete policy or ministerial domains. But the structure of governments and the structure even of legislative bodies tends to segment policy-making. Smaller entities such as towns and cities may be able to generate systemic responses to problems but this integrative designing is difficult for large, segmented national level governments (Peters, 2015). Organisational cultures As well as structural features of the public sector and individual organisations, the ideas that guide action within those organisations can also be important for their design orientation. While it may be popular to characterise bureaucratic organisations as anything but the carriers of ideas and as motivated by conceptions of the public interest, in reality ideas are important for understanding how public organisations perform their tasks. While institutionalists examining public organisations may emphasise the importance of having strong values that guide actions (March and Olsen, 1989) and are useful for integrating members of the institution, those very attributes may make policy design less likely to be innovative. The problem with a strong organisational culture is rather obviously that it tends to produce the same answers to whatever question is presented. Again, in some ways this is a virtue for the institution qua institution. It maintains the policy trajectory of the organisation and minimises decision-​making costs. But the strong internal culture is much less helpful when attempting to develop new ideas and new policies. And those organisations with strong and integrated internal cultures also tend to be effective at reproducing those cultures and therefore good at reproducing policy solutions. But although successful organisations often may have difficulties in innovating through the dominant culture, they may develop sub-​cultures that are interested in change and in undermining the dominant culture. Organisations with greater internal diversity, whether by professional training (see Linder and Peters, 1989), race, gender or any number of other attributes, may be more capable of innovation than are more uniform organisations. Also, organisations that are embedded in dense organisational networks may receive pressures for change from a range of conflicting sources, making less likely. Thus, if there are means available for undermining the dominance of one culture and its preference for certain policy solutions then innovation becomes more likely. 159

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Designing linkages with social actors The emphasis on participation in the ‘New Design’, and the need to facilitate information processing, both lead to a need to manage effectively linkages between the public sector and social actors. Those social actors may be organised in networks interacting with public sector organisations (Torfing et al, 2011) or they may be more individualised stakeholders and policy advocates. But no matter who they are, if the social actors are to make contributions to policy design then institutions must be designed in ways that facilitate their access and their influence. Increasingly public organisations are being designed to collaborate better with actors in their environment, but there may be some way to go in that effort. Ensuring access for social actors is not as easy as it might be thought to be (Klijn and Koppenjan, 2006). Conventional bureaucratic structures often are not receptive to including the ideas and proposals coming from outside their own structure. Even with networks attached to the institutions, the participation may be exclusive and thus limiting the range of ideas considered. More open forms of participation can be more inclusive, but may lack the institutionalised connections to policy-making that will link the ideas of social actors directly to policy. The examples given in several other chapters in this volume do, however, give more hopeful stories of the linkages between social actors and policy design. Managerialism The New Public Management has been blamed for many of the ills of contemporary public administration, perhaps with cause, but the relationship of managerialism of all sorts to policy design should be considered. The fundamental tenet of managerialism that public administration should be about service delivery, and not policy, can drive design out of the bureaucracy and assumes that the designing functions will not be performed within the bureaucracy itself. The emphasis on management may tend to drive policy design out of the public sector, or at least to specialised organisations within the public sector and therefore lose some of the information available within government itself. The various institutions described in the other chapters in this volume point to the ways in which policy-makers have responded to the need for improved policy advice. Further, the somewhat artificial separation of politics and administration, while long a tenet of some approaches to public administration, has been extended through the agency model associated with NPM. The use of the agency model for organising the public bureaucracy has tended to reduce the flow of information from field staffs and therefore to provide those charged with policy in the ministries perhaps less capable of designing 160

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effectively. As noted earlier the arguments from contemporary design thinking are that better designs will emerge from having more people involved in the process, and the agency model tends to eliminate one important source of ideas and information. If feedback from the clients and objects of policy is reduced then everything else being equal the quality of policy will also be reduced. One could extend the list of barriers to effective design mentioned earlier, although these are the central issues that arise from an institutional or organisational perspective. Most of these barriers emphasise the tendencies of organisations to reproduce their own patterns of behaviour and values, and therefore to be resistant to the innovations desired in most models of policy design. While that resistance and path-​dependence in institutions may argue for externalising policy designing, that strategy generates its own problems, to be discussed in the following section of the chapter.

The dilemmas of organising for policy design The earlier discussion has identified a number of factors that may be important for designing institutions that will, in turn, design public policies. These institutions are not, however, as easy to design as would be, for example, an organisation charged primarily with service delivery, even if that service delivery were to involve multiple actors from the private sector. Creating organisations that will themselves need to be creative is not easy, given the tendency of organisations rather quickly to construct routines and to create programmed responses. But that task is all the more difficult because those design organisations will need to fit into larger governance structures that tend to prize predictability and routines over creativity and innovation. The designers of these design institutions for the public sector are likely to encounter several dilemmas when building or redirecting institutions. The external dilemma The first of these dilemmas I have labelled as an external dilemma. This design problem is encountered when designing institutions that are intended for designing policies in an open and creative manner. To the extent that the institution is indeed likely to produce those innovative policy ideas it may encounter difficulties in getting itself and its ideas accepted within the more conventional structures involved in making policy. The challenge for the institution then is to develop strategies for selling its ideas into a policymaking system that may already be thickly institutionalised (Selznick, 1992) and confident that it knows how to design policy without any new ideas or organisations. 161

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A codicil of the general external dilemma involves the environment within which design institutions must function. The institutional field within which a new and innovative design institution will have to operate often will be well populated with competitors, and have pressures toward isomorphism. The field may be filled with government organisations, think tanks, political party policy structures, universities and perhaps even freelancers all engaged in creating and advocated policy designs. These policy design organisations will vary in how innovative they will be, but most can be expected to be rather conventional. Those competitors are likely to enjoy some advantages over any arriviste policy designers, no matter how appealing their ideas and methodologies may be. The first advantage is simply that they are established, and have established relationships with their clients. Further, the work of more established designers may better meet the perceived needs of policy-makers than does the work of more innovative design institutions. The more innovative designers may pride themselves in identifying the needs that a policy-maker did not know that s/​he had, but those policy-makers would perhaps be happier if the needs they had already identified were addressed. The marketplace of ideas may be more resistant to innovation than would-​ be policy designers would like to think.

The decision-​making paradox A second a related dilemma or paradox arises from the use of inclusive mechanisms for designing. The most relevant of these potential difficulties reflects the logic of Fritz Scharpf ’s (1988) analysis of decision-​making in federal structures. Scharpf argued that as more actors with divergent interests are involved in decision-​making, and especially when each actor has the possibility of being a veto player, the chances of reaching innovative solutions are reduced. Decision-​making will then reflect only the lowest common denominator. The logic of Scharpf ’s argument is easily extended to designing within networks, or in any other arrangement that depends upon collaboration among multiple actors who may have divergent interests. To the extent that institutions are successful in integrating multiple interests in the process of designing policies, they may encounter difficulties in actually reaching the innovative policy designs being sought. Or, as already mentioned, the outcome may become a hodgepodge of different ideas rather than a single coherent approach to the policy problem. The structures may not give veto-​ player status to the actors, but if the institution is to be successful in being inclusive it must take into account the potentially wide range of policy ideas.

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The internal dilemma There is also an internal challenge for institutions that would be creative policy designers. Institutional design for policy design, and especially the new versions of design, presents something of a paradox and challenge for designers. On the one hand, institutions are usually defined through rules (Ostrom, 1990) or through commonly held values (March and Olsen, 1989). The purpose of institutions is to create regularities of behaviour and patterned outputs. While the degree of uniformity does vary –​the military versus universities, for ­example –​there are still expectations of some conformity to norms within the institutions. The question therefore becomes to what extent one can create institutions that are designed to produce behaviours that are innovative and unconventional. This, at least in part, depends upon the operational definition of an institution. If that definition is based primarily upon rules and compliance then the opportunities for innovation will be lessened. But less formalised structures may also have institutional features that are more conducive to discourse and open contestation over ideas (Schmidt, 2010). And less formalised institutions can complement the activities of more established institutions, or substitute for failings in those established structures (Helmke and Levitsky, 2004). As the innovative structures outlined in this volume develop, they may be able to complement the activities of more established institutions involved in policy designing. To the extent, however, that a policy design institution moves toward the informal and the unstructured, it may move into the territory governed by the external dilemma mentioned earlier. That is, relatively unstructured institutions may lack credibility in a policy-making world that is already populated by a host of seemingly competent and well-​organised institutions that readily can provide policy advice for policy-makers. Policy-makers seeking advice on policy design may require some source credibility, and unless they have been involved in the creation of the policy labs or analogous structures may not consider them as being as credible as other more established sources of policy ideas. The structural dilemma A fourth dilemma (or perhaps more accurately trilemma) is whether to create markets, networks or hierarchies as the fundamental organisational pattern for designing (see Considine et al, 2009). Each of these standard means of organisation can provide advantages for policy designers, but also would produce some costs. For example, while hierarchical organisations remain the most common format for organisations in the public sector, they may appear to be the least conducive to innovative designing. Conversely, 163

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markets for ideas should in principle be the most open format for designing, but may contain biases toward efficiency as a dominant evaluative criterion. Further, market-​like structures for designing may create a winner takes all mentality, while much of the emphasis in new design is on collaboration and cooperation in developing solutions. Much of the contemporary discussion of policy design, and alternatives to older forms of design, has focused on networks, or structures analogous to networks. This focus on networks corresponds to the emphasis on participation in contemporary designing (Bason, 2018). And although in democratic terms inclusiveness is laudable, the reliance on network formats is not a panacea for designing. The very thing that makes networks potentially valuable in designing may also lead to problems in decision-​making that obviates some of their utility as mechanisms for design. The presence of these three options, and their differential impacts on the performance of institutions, is hardly a new issue for policy formulation. Although hierarchies have dominated the process, there has been an increasing interest in a market for ideas as well as in using market actors such as consulting firms for policy advice. And networks or their equivalents have been central in formulation for some time, especially in corporatist or corporate pluralist regimes. Although ideas of inclusion and the use of networks of stakeholders dominate contemporary thinking about design, the other structures remain viable. The choice among them may depend upon a number of factors including the policy domain being considered, the capacity of the public bureaucracy, and the capacity of civil society. The institutionalisation dilemma Yet a fifth dilemma for institutions and policy design is that institutions may be especially useful for the type of design that is perhaps less likely to produce creative results. That is, older forms of policy design, and especially the common emphasis on policy instruments, can be addressed rather easily through formal institutional arrangements within the public sector. Thinking about newer, more creative, mechanisms for design may also require new institutions for design. However, as those institutions develop and institutionalise (Selznick, 1992) they may also become wedded to their own conventional practice and produce repetitive designs. Thus, even with newly formed and presumably creative institutions there is the danger of routinisation. The danger is that path dependence and institutional commitments to particular instruments will drive out more create efforts at policy design. Like other organisations within the public sector, once an organisation has gained experience with a limited range of policy instruments it will tend to choose the same instruments again and again (Linder and Peters, 1989). This persistence may be simply a function 164

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of habit (Sarigil, 2015) or it may reflect the belief that they know better how to make those instruments perform. For whatever reason, however, path dependency may dominate more creative choices, and what was once creative becomes routine. The experience with policy labs and other institutionalised attempts at policy design is not yet sufficient to know whether they will become routinised and begin to produce the predictable answers to problems that other policy formulation institutions do. The expectations among advocates is that they will remain open and innovative, but that has been the expectation of many previous founders of the institutions offering policy advice. The challenge for designers becomes how to keep the innovative from becoming the trite. The ambitions dilemma The final dilemma about design is perhaps the most fundamental. It concerns the ambitions of designers, and the ambitions of policy-makers. Most of the literature on policy design, including the chapters in this volume, assume that both policy designers and their clients want ‘to boldly go’ into the world of public policy with highly innovative ideas about policy, and to reconceptualise the policy problems and especially the policy solutions. Existing policies are sub-​optimal (although how do we know that is true?) and therefore governments need to proceed at full speed toward a newer and better future. This is a laudable set of assumptions about design, and in many cases, for example, cities attempting to become ‘smarter’, they appear justified. But there is a good deal of designing required that is essentially incremental, and which involves attempting to improve the performance of existing policies rather than making major innovations (Carter, 2012). This type of design is not fashionable, but it is design. And for the bureaucrats, legislative staffers and members of think tanks involved in the process it may still be a creative exercise. There has been some interest in the design literature in improving the less fashionable, incremental forms of designing –​especially through improving access to information –​but the emphasis remains more on innovative designing. Henry Ford once commented that had he asked his initial customers for automobiles what they wanted, the answer would have been a faster horse. And perhaps there would have been little wrong with supplying them with a faster horse, were that possible. Policy designers may therefore need to consider when incremental change can still be beneficial and still supply benefits without the risks involved in more creative designs. The temptation is to go for the clever new idea –​especially for academics who study designing –​rather than to think about amelioration and more bounded 165

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solutions for the policy problems being addressed. There are good reasons why bounded rationality does perform well in a complex and perhaps poorly understood world. The limits, as well as the virtues, of incremental design therefore must be considered when thinking about engaging in the ‘new’ forms of policy design. Further, some of the same methods involved in the ‘new’ design may be equally applicable, or perhaps even more applicable, when engaged in ‘old’ design. For example, collaborative methods may be even more successful in older design institutions because of the connections that existing organisations have with stakeholders surrounding the policy domain.

Summary on institutional choice In summary, Odysseus had it easy. He only had to navigate between Scylla and Charybdis. The contemporary institutional designer faces many more challenges when s/​he attempts to design structures and patterns of behaviour that can provide creativity and legitimacy for policy design. While the creation of new organisations dedicated to design has been an exciting development in the general arena of policy advice, institutionalising those structures both internally and within the institutional field that surrounds policy-making, is more difficult. As noted in other chapters in this volume, some of these more innovative design organisations have already floundered, and it is unclear how viable others may be. These organisations have the virtue of being new and seemingly innovative, but that novelty is a definite organisational risk as well (Boin and Goodin, 2007). The lower levels of institutionalisation may be conducive to creativity but may also generate unpredictability and perceived unreliability for potential clients. This discussion of the institutional options for design may appear excessively critical and pessimistic to some readers, especially those committed to policy labs and collaborative design. But it is always useful to have some scepticism about any fad in public policy and public administration. We have discussed Simon’s notion of design science in several places throughout this volume, but we should also remember his critique of the ‘proverbs of administration’ and our tendency to move from one end of a continuum to another. This has been true for competing virtues such as specialisation and coordination (Bouckaert et al, 2010) and may also be true for collaborative versus more hierarchical and technocratic forms of policy design.

Summary and conclusions The position of institutions attempting to provide newer forms of policy design for the public sector is analogous to that of the use of information in 166

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the public sector. That is, there may be more supply than there is effective demand. Other chapters in this volume have identified the proliferation of organisations within the public sector devoted to more innovative forms of policy design, but there is less evidence of the palatability of those design efforts for members of the institutions actually making the policy. There is often lip service paid to the idea of needing more innovative policies, but in practice many may be content with very familiar approaches to policy. The selection and design of institutions for policy design is not a simple question. It depends upon a number of factors, notably what type of policy ideas are to be privileged in the design and the how risk-​accepting the client of the design institution may be. While contemporary designing emphasises inclusive modes of design and with that structures that approximate networks structures, for more incremental forms of policy formulation traditional institutional structures are sufficient, or even preferable. This chapter has also, I believe, made it clear that the selection of an institution for policy design must be considered in the context of the existing array of other institutions within the public sector, and within society more generally. It is important to consider, and to advocate for, the new and evolving opportunities for design, but these must be considered along more conventional options for policy formulation when selecting institutional formats. Even if the existing institutional arrangements do welcome more innovative policy options, the environment remains competitive and the newer approaches must be prepared to demonstrate the added value of their approach to design. Notes At least in countries with strong court systems such as the United States and Germany, the courts will indeed be policy designers. But their designs will generally be based on legal premises rather than on more detailed understanding of policy dynamics as one would hope from the other design institutions. 2 This is obviously hyperbolic, but may also be truer than some policy designers may recognise. This is somewhat akin to the ‘policy myopia’ described by Nair and Howlett (2017). 3 But attempting to design for flexibility may present its own difficulties, especially politically. It is not very attractive –​either to politicians or to the public –​to have to argue that a proposed policy is good for a short time, but we really do not expect it to resolve the problem. Therefore, many policy proposals are oversold and implemented as if they were the answer to the problem, rather than a means of ameliorating the problem. 4 The argument here would be not dissimilar to Moshe Maor’s ideas about over-​ reaction and under-​reaction (2012) in policy-making. 5 Rube Goldberg for American readers. 1

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References Bandola-​Gill, J., Lyall, C. (2015), ‘Knowledge-​brokers and policy advice in policy formulation’, Handbook of Policy Formulation, eds. M. Howlett, I. Mukherjee, Cheltenham: Edward Elgar, 287–​309. Bason, C. (2016), Design for Policy, London: Routledge. Bason, C. (2018), Leading Public Sector Innovation: Co-​Creating for a Better Society, 2nd edn. Bristol: Policy Press. Bohni, N. S., Turksema, R., van der Knaap, P. (2015), Success in Evaluation: Focusing on the Positives, New Brunswick, NJ: Transaction. Boin, A., Goodin, R. E. (2007), ‘Institutionalising upstarts: the demons of domestication and the benefits of recalcitrance’, Acta Politica, 42(1), 49–​57. doi: 10.1057/​palgrave.ap.5500168 Bouckaert, G., Peters, B. G., Verhoest, K. (2010), The Coordination of Public Sector Organizations: Shifting Patterns of Public Management, Basingstoke: Macmillan. Braybrooke, D. (1974), Traffic Goes Through the Issue Machine: A Case Study of Issue Processing, London: Routledge & Kegan Paul. Brown, T., Watt, J. (2015), ‘Design thinking for social innovation’, Annual Review of Policy Design, 3 . Carter, P. (2012), ‘Policy as palimpsest’, Policy & Politics, 40(4), 423–​443 . Cervantes, N., Radge, Z. (2018), ‘Weber’s bureaucratic model in Brazil: the corruption of ideas as obstacles to the implementation of policy’, Geoforum, 95(1), 165–​168. doi: 10.1016/​j.geoforum.2018.06.015 Checkland, P., Poulter, J. (2010), ‘Soft systems methodology’, Systems Approaches for Management Change, eds. M. Reynolds, S. Holwell, London: Open University Press 125–​138. Considine, M. (2012), ‘Thinking outside the box? Applying design theory to public policy’, Politics & Policy, 40(4), 704–​724 . Considine, M., Lewis, J. M., Alexander, D. (2009), Networks, Innovation and Public Policy, Basingstoke: Palgrave. De Vries, H. A, Bekkers, V. J. J. M., Tummers, L. G. (2014), Innovation in the Public Sector: A Systematic Review and Future Research Agenda, Speyer: EGPA conference. Donahue, J. D., Zeckhauser, R. G. (2011), Collaborative Governance: Private Roles for Public Goals in Turbulent Times, Princeton, NJ: Princeton University Press. Doz, Y., Kosenen, M. (2010), ‘Embedding strategic agility: a leadership agenda for accelerating business model renewal’, Long-​Range Planning, 43(3), 370–​382. doi: 10.1016/​j.lrp.2009.07.006 Dunn, W. N. (2018), Public Policy Analysis: An Introduction, 6th edn. Englewood Cliffs, NJ: Prentice-​Hall.

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Helmke, G., Levitsky, S. (2004), ‘Informal institutions and comparative politics: a research agenda’, Perspectives on Politics, 2(4), 725–​7 40. doi: 10.1017/​S1537592704040472 Hisschemoller, M., Hoppe, R. (2018), ‘Coping with intractable controversies: the case for problem structuring in policy design and analysis’, Knowledge, Power and Participation in Environmental Policy Analysis, ed. X. Hoppe, London: Routledge 86–​101. Howlett, M., Lejano, R. P. (2013), ‘Tales from the crypt: the rise and fall (and rebirth?) of policy design’, Administration & Society, 45(3), 357–​381. Howlett, M., Mukherjee, I. (2018), Routledge Handbook of Policy Design, London: Routledge. Howlett, M., Rayner, J. (2013), ‘Patching and packaging in policy formulation: assessing policy portfolio design’, Politics and Governance, 2, 170–​182. doi: 10.17645/​pag.v1i2.95 Klijn, E.-​H., Koppenjan, J. F. M. (2006), ‘Institutional design: changing institutional features of networks’, Public Management Review, 8, 141–​160. doi: 10.1080/​14719030500518915 Lewis, J. (2018), ‘The rise of public sector innovation labs: experiments in design thinking for policy’, Policy Sciences, 51(3), 249–​267. Linder, S. H., Peters, B. G. (1984), ‘From social theory to policy design’, Journal of Public Policy, 4(3), 237–​259. doi: 10.1017/​S0143814X0000221X Linder, S. H, Peters, B. G. (1989), ‘Instruments of government: perceptions and contexts’, Journal of Public Policy, 9(1), 35–​5 8. doi: 10.1017/​ S0143814X00007960 Linder, S. H, Peters, B. G. (1991), ‘The logic of public policy design: linking policy actors and plausible instruments’, Knowledge and Policy, 4(2), 121–​ 151. doi: 10.1007/​BF02692751 March, J. G., Olsen, J. P. (1989), Rediscovering Institutions, New York: Free Press. McCubbins, M., Noll, R., Weingast, B. (1969), ‘Structure and process, politics and policy: administrative arrangements and the political control of agencies’, Virginia Law Review, 75(2), 431–​482. doi: 10.2307/​1073179 Nair, S., Howlett, M. (2017), ‘Policy myopia as a source of policy failure: adaptation and policy learning under deep uncertainty’, Policy & Politics, 45(1), 103–​118. Ostrom, E. (1990), Governing the Commons: The Evolution of Institutions of Collective Action, Cambridge: Cambridge University Press. Peters, B. G. (2015), Pursuing Horizontal Management: The Politics of Public Sector Coordination, Lawrence, KS: University Press of Kansas. Peters, B. G. (2018), Policy Problems and Policy Design, Cheltenham: Edward Elgar. Peters, B. G., Tarpley, M. M. (forthcoming), ‘Just how wicked are wicked problems?’, Policy and Society.

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Sarigil, Z. (2015), ‘Showing the path to path dependence: the habitual path’, European Political Science Review, 7(3), 221–​242. doi: 10.1017/​ S1755773914000198 Scharpf, F. W. (1988), ‘The joint decision trap: lessons from German federalism and European integration’, Public Administration, 66(2), 239–​278. doi: 10.1111/​j.1467-​9299.1988.tb00694.x Schmidt, V. A. (2010), Taking Ideas and Discourses Seriously: Explaining Change Through Discursive Institutionalism and the Fourth New Institutionalism, European Political Science Review, 2, 1–​25. Schneider, G. E. (1991), Time, Planning, and Policy Making: An Evaluation of a Complex Relationship, Bern: Peter Lang. Selznick, P. (1992), The Moral Community: Social Theory and the Promise of Community, Berkeley, CA: University of California Press. Simon, H. A. (1969), The Sciences of the Artificial, Cambridge, MA: MIT Press. Simon, H. A. (1973), ‘The structure of ill-​structured problems’, Artificial Intelligence, 4(2), 181–​201. doi: 10.1016/​0004-​3702(73)90011-​8 Sørensen, E., Torfing, J. (2011), ‘Enhancing collaborative innovation in the public sector’, Administration & Society, 43(6): 842–​68.

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Applying design science in public policy and administration research A. Georges L. Romme and Albert Meijer

Introduction Governments around the world are struggling to find innovative solutions for complex problems. Key issues are sustainability, the quality of living in cities, and inequalities and tensions between groups of citizens. To address these challenges, new forms of governance are needed which serve to make and implement collectively binding decisions that take into account the interests of all those affected, including future generations. Institutions for public governance and policy-making are, in their present form, often not up to the task. As a result, democratic and administrative bodies tend to respond to major problems and challenges using yesterday’s tools (Shkliarevsky, 2016; OECD, 2017; Zhang and Feeney, 2018). There is a growing debate about the role of academic researchers in governments’ responses to these challenges. The vast majority of public policy and administration scholars focus on describing and explaining how existing governance systems operate, but the need to engage in experimentation, interventions and other efforts to actually change (the conditions of) these systems is increasingly emphasised. Several scholars have therefore been advocating a fundamental rethink of the ‘bystander’ character of much research in the area of political science and public governance (for example, Ricci, 1984; Gunnell, 2004; Ansell, 2011; Schram et al, 2013). Accordingly, public policy and administration (PPA) research would need to be driven by extant theories and methods as well as be framed around pressing public issues and dilemmas in the real world (Smith, 2002; Shapiro, 2005; Schram et al, 2013; Buick et al, 2016). In this chapter, we contribute to this discourse by developing a design approach for PPA that integrates retrospective research (validation) and prospective research (design). We thus not only build on ‘conventional’ approaches to studying governance (for an overview, see Levi-​Faur, 2012) but also on design science. The notion of design science (DS) arises from Simon’s (1969) seminal work, and has been gaining momentum in fields such as information systems (for example, March and Smith, 1995), organisation studies (for example, Romme, 2003), and public policy and administration 171

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(for example, Shangraw and Crow, 1989; Considine, 2012; Bason, 2016; Ansell et al, 2017; Chapter 1, this volume). In the field of PPA, there is a long tradition of design that primarily draws upon the idea of an expert-​ driven rational policy design, often based on a top-​down, linear image of the policy-​making process (for example, Rivlin, 1973; Lindblom and Cohen, 1979; Peters and Pierre, 2006). This tradition builds upon retrospective research for its knowledge basis. A limitation of this approach, however, is that it often fails to incorporate insights from design science such as user engagement and creativity. Notably, PPA approaches to design science (for example, Shangraw and Crow, 1989; Bason, 2016) have acknowledged the key role of users and creativity, but also have limited attention for the need to build robust knowledge about governance based on retrospective research. In this chapter, we intend to synthesise both discourses in a framework that includes validation-​oriented science as well as creative design. As such, our key premise is that DS research needs to build on both retrospective (validation-​oriented) and prospective (design-​oriented) methods, and that consistent frameworks for this type of research are underdeveloped; some recent work on the value of design experiments is a notable exception (Stoker and John, 2009; Bakker and Denters, 2012). Our argument expands the latter work on design experiments, by highlighting the key mechanisms in these interactions between design and validation, rather than only conceptualising it as a specific type of experiment. The main contribution of this chapter is to develop a consistent methodology at the interface of design and science, as a strong foundation for PPA scholars to respond to many societal stakeholders calling for more evidence-​based policymaking (Chapter 1, this volume). This contribution is important because the lack of an inclusive framework may inhibit the development and adoption of DS in the field of PPA. In this respect, Simon (1969) emphasised that science is primarily about studying current (or past) practices, whereas design is about creating future practices. The fundamental difference between retrospective science and prospective design is what makes work at the science-​design interface so complex and challenging (Bason, 2016; Chapter 1, this volume). The argument is organised as follows. First, we explore the need for a consistent methodological framework at the interface between design and science, and then present a DS framework. Subsequently, two examples serve to illustrate this framework and explore the opportunities and challenges arising from this type of work. Finally, we discuss the implications of our argument.

Towards an inclusive methodology for design and validation in Public Policy and Administration Validation and design have become separate domains in PPA research. In line with the broader trend towards ‘scientification’ in the social sciences 172

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(Bond, 2007), the bulk of PPA research focuses on validation by studying current/​past behaviours and cognitions in order to identify generalisable patterns and build theories of policy and administration (for example, Kenis and Provan, 2009; Levi-​Faur, 2012; Sarto et al, 2016). As such, the field of PPA contains a large number of highly interesting theories (of all sorts) and research findings, but is far away from a coherent body of knowledge that informs and motivates practitioners to become more effective in addressing their real-​life administrative and political challenges (Ricci, 1984; Al-​Habil, 2011; Ansell, 2011; Gunnell, 2004; Schram et al, 2013). By contrast, the design perspective is still a niche approach in PPA research. The key contribution of this emerging approach is that it acknowledges the need for a focus on users (for example, citizens) as well as creativity as a key requirement for developing innovative solutions. While design-​oriented research has been receiving more attention lately, the design perspective used by PPA scholars almost exclusively focuses on the question how high-​quality designs can be realised in particular contexts (for example, Shangraw and Crow, 1989; Hood, 1991; Behn, 1996; 1997; Barzelay and Thompson, 2010; Dorst, 2012; Bason, 2017). Recent work in this area has made important contributions to design methodology (Stoker and John, 2009), but largely fails to connect context-​specific designs to the ambition of building theories. Simon’s (1969) seminal The Sciences of the Artificial provides the starting point for the development of an inclusive methodology for design in PPA. Simon (1969) identified two key properties of administrative and other artefacts: human intentionality and environmental contingency. For one, human intentionality pervades (the creation of) artefacts like budgeting systems or digital platforms for public participation. Moreover, the design, development and performance of these administrative artefacts are highly contingent on cultural, institutional and other environmental conditions. Thus, human intentionality and environmental contingency make an exclusively ‘scientific’ approach inadequate for studying this type of artefact and related phenomena (Simon, 1969). This implies that PPA research is primarily a ‘science of the artificial’, that is, a professional discipline at the interface of creative design and scientific validation (Simon, 1969; Shangraw and Crow, 1989; Hatchuel, 2001). Therefore, a methodology is needed that connects design and validation or, framed differently, prospective and retrospective approaches to research. Such an inclusive methodology for designing and validating policy interventions needs to acknowledge the diverse character of the PPA discipline. A mere focus on evidence-​based policy (Davies and Nutley, 2000) does not suffice. The ambiguity around key notions such as theory and testing illustrates this diverse (if not to say fragmented) nature of PPA scholarship. Many scholars argue that theory involves propositions or statements that are generalisable as well as applicable to, or testable on, individual cases, that is, 173

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‘a way of imposing conceptual order on the empirical complexity of the phenomenal world’ (Suddaby, 2014: 407). By contrast, others have been questioning this conception of theory (for example, Locke and Golden-​ Biddle, 1997; Flyvbjerg, 2001), because ‘we cannot improve the theorizing process until we describe it more explicitly, operate it more self-​consciously, and decouple it from validation more deliberately’ (Weick, 1989: 1). As such, Weick (1989), Flyvbjerg (2001) and others have been advocating theory as an act of ‘creative discovery’. Similarly, the notion of testing is also highly ambiguous in the field of PPA. For many scholars, ‘testing’ (theory) refers to ways to assess the internal and external validity of constructs, test hypotheses by means of inferential statistics, and so forth (for example, Kenis and Provan, 2009; Citrin et al, 2014). For others, testing involves probing activities that serve to find out what kind of practices and interventions ‘work’, and which do not (for example, Smith, 2002; Stoker and John, 2009; Schram et al, 2013; Buick et al, 2016). Assessing the authenticity and complexity of specific practices and interventions is then given precedence over the goal of developing and testing general knowledge. In any academic or professional field, it is rather difficult to make progress towards a coherent body of knowledge if key terms (such as theorising and testing) are highly ambiguous and disputed (Abbott, 1988). Therefore, we propose an inclusive taxonomy of key terminology regarding research activities and methods (compare March and Smith, 1995; Romme, 2016) which draws upon the distinction between design and validation. Design involves creating and assessing new PPA practices as well as developing new knowledge on these new practices or existing ones. Once (initial versions of) practices have been created, validation serves to theorise about them (for example, by codifying, generalising, modelling), and justify and (possibly) falsify the results of theorising activity. Following March and Smith (1995), we can further differentiate this high-​level categorisation into creating and assessing (together: design) and theorising and justifying (together: validation). Figure 8.1 provides an overview of the resulting framework. Creating involves the initial act of conceiving a PPA value, construct, model, principle or practice that is (perceived as) new. Assessing refers to the act of evaluating one or more of these research outputs against (value-​based) criteria such as usefulness, fairness, viability and desirability –​especially from the perspective of users (Bason, 2016). The acts of creation and assessment often go together, with many iterations back and forth. Moreover, creation and assessment have a specific meaning in the public sector since they are tightly connected to democratic and legal principles. In this respect, the focus on co-​ design does not only have an instrumental, but also a democratic value (Bason, 2016). 174

Applying design science in public policy Figure 8.1: The iterative and complementary nature of creating, assessing, theorising and justifying activity in PPA research Creating

Assessing DESIGN

VALIDATION Theorising

Justifying

Source: adapted from Romme and Reymen, 2018

Validation work can be further disentangled in theorising and justifying activities. Theorising is about linking constructs in terms of models and principles that are generalisable as well as applicable to individual cases. Justifying involves any effort to enhance the legitimacy of a particular research output, by scrutinising it in terms of criteria such as generalisability, internal and external validity, and reliability. Notably, the four research activities are highly complementary and tend to overlap substantially. For example, to be able to theorise by way of a (for example, conceptual, instrumental or mathematical) model, one first has to create or discover the relevant constructs regarding the PPA phenomenon at hand, and assess whether they are useful and desirable; and when scholars are building a model, they often return to design missing pieces (for example, constructs) of the emerging model. In other words, the various research activities feed on each other. The framework outlined in Figure 8.1 therefore merely serves to dissect the various steps, not to present them as independent stages of a research cycle. We also concur with March and Smith (1995) by using the notion of ‘justifying’ rather than ‘testing’. As argued earlier in this section, the notion of testing can be used in so many different ways and stages of the DS research cycle that it is rather meaningless as a generic label. Thus, the DS perspective suggests that PPA scholars need to specify a particular definition and interpretation of what constitutes a proper and meaningful ‘test’ in the context of one of the design and validation activities outlined in Figure 1. This test needs to be inclusive and therefore build on a pragmatist philosophy of science (Morgan, 2007). Interestingly, the ‘justifying’ notion is likely to raise the image of scholars being captured in the theoretical lens adopted (which is often the case). In the context of validating a particular theory, this ‘capture’ effect is indeed inevitable. In this respect, the DS perspective implies that the creative (theorising) process of comparing and possibly switching between theories is primarily fuelled by the creating and assessing (that is, design) activities. 175

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Figure 8.1 provides an overview of the iterative nature of design and validation –​as equivalent activities that together enable a viable and inclusive discourse on public administration and policy. It highlights the continuous interactions between the four types of research activity, both within and across the domains of design and validation. This figure also helps resolve some of the ambiguity around the notion of ‘theory’ arising from the tension between the conventional idea that theorising is a key element of validation and the idea that ‘theorising’ is key to creative design (Weick, 1989). As such, the iteration between the various activities is not a linear sequence, but rather a continuous interaction between them. Overall, the inclusive DS perspective advocated here assumes that design and validation are highly complementary, which serves to embrace different traditions and notions of theory and testing (as previously outlined). This broad perspective is needed to realise the double objective of providing a rigorous theoretical understanding of policy and administration and developing interventions for tackling major policy challenges and improving administrative practices.

Examples of research at design-​science interface We now turn to two examples that illustrate the iteration between the four research activities of the inclusive methodology. These examples are based on Ruijer et al (2018) and Romme et al (2018b). Full information about the research designs, data collection and data analysis is presented in these two publications. The first project involves a deliberate effort to redefine relations between citizens and government by introducing societal learning on the basis of open data. This project illustrates that a design approach is no guarantee for success but it is a robust method for systematically producing both theoretical knowledge and applied knowledge about the value of an innovative approach. The second example involves a project in which the political culture and policy-making processes of a municipality were transformed towards consent-​based collaboration. In this case, the design approach produced both a successful innovation and new theoretical knowledge. The examples highlight that the inclusive methodology outlined in Figure 8.1 is no guarantee for successful governance innovation, but does present a systematic and robust method for developing and assessing innovative solutions and generating new theoretical knowledge by testing these innovative solutions. Example 1: informational resources for collaborative governance Traditionally, governments develop public services and policies for citizens. In new arrangements advocated as New Public Governance (Osborne, 176

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2006), citizens appropriate certain services and develop new solutions for public problems. These new governance arrangements raise a myriad of issues regarding the new roles of government and citizens. The study by Ruijer et al (2018) focused on one specific dimension of this changing relation: information processes. In this respect, government agencies use various kinds of data to develop policy plans and interventions. Data may contribute to the rationality of government and the adequacy of government planning, and good data are therefore seen as a crucial resource for government. Moreover, new internet technologies and a changing culture of openness have resulted in a push for open data. Open data is expected to strengthen the transparency of government, but also to facilitate collaborations between governments and societal actors. These collaborations, however, prove difficult to realise. We illustrate this by means of a practical intervention that aimed to develop a new form of societal learning between societal actors and governments on the basis of open data. This intervention was conducted in the Dutch provincial government of Groningen. Drawing on Ruijer et al (2018), the remainder of this subsection depicts the various activities in terms of the categories identified in Figure 8.1. Creating Like many rural provinces in Europe, Groningen faces major problems arising from the structural decline of its population, such as declining public facilities and limited economic opportunities. This province has long had the ambition to work with citizen groups to find innovative solutions to tackle these problems. As researchers, Ruijer and coauthors introduced the idea of working with open government data to stimulate citizen initiatives aiming at improving the quality of life in Groningen. This intervention was part of a European project on open data for the public sector. Within the context of this European project, a tool for working with open data, based on the principle of user-​centrality, had previously been designed. The key ambition of the project in Groningen was to use this tool for creating new forms of collaboration between government and societal actors on the basis of innovative usage of data about key issues. To identify key problems and relevant data from a user perspective, the research team initiated a series of creative workshops with citizens and governmental representatives. Assessing These workshops served to identify several key problems and relevant data sources. The problems were positioned within the broader issue of dealing with the declining population of Groningen, while citizen groups raised two specific issues: setting up a home for the elderly and stimulating the 177

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circular economy. These issues were directly related to the plans of citizen groups to improve their environment in response to the broader problem of population decline. The workshops helped to shape the collaboration between the province and various civic initiatives on the basis of open data. At the heart of the planned interventions was the idea that a provincial government can stimulate civil society by providing the data and a platform for collaboration. In the process, the researchers observed that the citizen groups have a clear perspective on the data they needed for their plans, but they did not have the skills and the time to work with the data. Creating To tackle this problem, ‘slack capacity’ was created in the form of students who could work in teams on assignments to answer the questions from citizens, using open data from government. This experimental structure for developing a learning collaboration resulted in interesting ideas and outcomes for the citizens involved. Assessing and justifying The first tryouts of student teams working on these assignments also led the researchers to assess a mismatch between the data offered by government and the data needed by citizens. The province acknowledged this problem, but lacked the administrative capacity or the will to solve it on the short term and thereby make the data available. Particular kinds of data were protected and not made available for use, and middle managers played a key role in limiting funds for generating access to data. This effectively meant that the value of this new platform for open societal learning was demonstrated, but institutionalising it further proved to be a step too far. In spite of the discourse on the need to change and adapt to the information age, stability was still embraced as a key value in this bureaucratic organisation. The organisation thus continued to largely focus on survival rather than adaptation to the new era. As a result, maintaining exclusive access to strategic information resources was seen as crucial to the survival of the provincial organisation, and therefore the call for openness was (not openly) ignored but effectively dismantled. Theorising The key proposition in this study was that a regional government can effectively stimulate civil society by providing open data and creating a platform for interpreting these data and collaborating with/​between citizens.

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The evidence arising from the Groningen case suggests that a narrative about the coproduction of solutions with citizens needs to acknowledge the deep, institutionalised inertness of bureaucratic organisations. Justifying Subsequent explorations in other governmental settings highlighted the validity of the patterns found in the province of Groningen, but also suggest that dismantling the call for openness is not the only option. Depending on the position of the open data broker, s/​he can act as an innovation entrepreneur to use ‘information windows’ –​that is, types of information that are not seen as sensitive but still are useful for external stakeholders –​to develop more collaborative approaches to information. These innovation entrepreneurs help to reposition the organisation in the changing environment, while still respecting its core values. Theorising On the basis of these theories and justifications, new approaches to designing informational resources for collaborative governance can be developed. These approaches build on a theoretical understanding of the role of stability but also innovation in the public sector, and do not assume that the open discourse is simply reproduced within the organisation. Building upon Kingdon (1995) and Cohen et al (1972), additional theoretical notions such as ‘window of opportunity’, ‘garbage can’ and ‘innovation entrepreneur’ were used to enrich the theoretical understanding of these processes of social change. These interventions depart from the idea that information resources are strategic and political; thus, in developing information resources for collaborative governance, one needs to identify ‘information windows’ and ‘innovation entrepreneurs’ in rather chaotic decision-​making processes. A key issue here is timing: the ambition to realise a highly different mode of working for the province, within a timeframe of several months, proved not to be realistic. At the same time, this intervention provides crucial insights in the requirements for organisational change. As such, several key barriers in realising a vision of collaboration with citizens on the basis of open data have been identified, and alternative routes to realise these changes can now be developed. At the same time, this study helped to extend existing theory of the transition towards New Public Governance (Osborne, 2006). As such, there is a substantial gap between public administration practice and the dominant discourse about the impact of information technologies on access to information, and Ruijer et al (2018) developed key insights and notions to bridge this gap.

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Example 2: from competition and collusion to consent-​based policy-making Any attempt to increase participation by citizens in public governance is rather complex and challenging, also as a result of the rather inert institutions of representative democracy. Democratic bodies such as city councils often appear to be unable to make high-​quality decisions on public policy; moreover, many citizens appear to have lost trust in political institutions and their policy outcomes. In a study conducted in the Dutch municipality of Utrechtse Heuvelrug, Romme et al (2018b) explored whether and how the ‘informed consent’ principle can be used to improve public policy development and decision-​making. In 2012, the newly formed city of Utrechtse Heuvelrug (UH) was facing a high level of public distrust, resulting in a dysfunctional city council. UH had been created from a merger of five small villages, and one of the first decisions of UH’s newly formed city council was to build a new city hall, which caused many citizens to protest against their local politicians: more than five thousand citizens signed a collective letter of protest. This distrust rose even further due to several other local incidents. As a result, one of the aldermen had to step down and public distrust grew to an all-​time high. (In Dutch municipalities, the city council is the legislative body and the board of aldermen, chaired by the mayor, is its executive body.) UH’s city council and mayor were thus facing enormous challenges arising from the need to restore trust as well as increase civil participation in policy decisions. The remainder of this subsection outlines the subsequent flow of activities in terms of the categories in Figure 8.1. Creating Early 2012, the mayor decided to call upon UH’s citizens to investigate options for more effective local governance. All citizens were invited to volunteer to participate. A group of 15 citizens was thus formed, which named themselves the ‘bridge builders’; this group included several co-​ authors of the (later) article by Romme et al (2018b). Assessing As a first step, the bridge builders (BB) group decided to set up a number of meetings to investigate the needs of all people involved: civil servants, councillors, citizens and aldermen. Via these meetings, the BB group found there was not just one gap to bridge, but a larger number of gaps, misunderstandings, perceptions and miscommunications between all stakeholders. The BB group also studied and discussed several reports as 180

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well as several best practices in other municipalities, to identify and create several key values for successful participation projects. Creating The BB group decided to embrace two key values: first, the equivalence and involvement of all stakeholders, including those with huge stakes and opposing views and opinions; and second, the search for creative solutions to which all participants can consent. Subsequently, the BB group initiated and conducted several workshops with civil servants, councillors and aldermen to jointly develop a new collaborative approach. The BB group used these workshops to introduce participants to the key construct of informed consent (for example, Buchanan and Tullock, 1962; Romme, 1999; Romme and Endenburg, 2006) and familiarise them with the various instrumental principles that guide groups in making policy decisions by informed consent. These sessions served to create a deeper understanding of policy-making by informed consent. Assessing and creating In April 2013, the BB group presented its report to the city council. The report included the following principles for strengthening the connection between citizens and the municipal administration: (a) the city council decides at an early stage about the level of citizen participation that will be used for a specific policy issue; (b) the city council sets and defines the boundaries (for example, budget constraints, delivery time and other conditions) for any participation process; (c) a project group then gets the assignment to investigate the topic and decide by consent on a solution within the boundaries set by the city council; this project group is formed after an open call to all citizens; (d) when the project group delivers its solution, the city council only assesses if the solution proposed meets the boundaries defined earlier; if this is the case, the city council validates the solution; (e) if the project group cannot make a decision by informed consent within the given boundaries, the city council again has the authority to freely decide on the issue at hand. The city council discussed the recommendations of the BB group in a meeting that was also attended by one of the aldermen, representatives of civil servants, and several members of the BB group. The key outcome of this meeting was the decision, taken by informed consent of all participants, to launch a pilot project to obtain more practical experience. Creating Soon after this decision, the election of a new city council took place in March 2014, which resulted in eight parties being elected into the council. 181

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Interestingly, the eight leaders of these political parties elected into the council decided by consent on the new policy programme, including an agreement on major budget cuts. Theorising and justifying Evidently, this approach is fundamentally different than the common practice of forming majority coalitions. Its main theoretical background involves theories of policy-making by ‘informed consent’, as opposed to consensus or majority vote (Buchanan and Tullock, 1962; Romme and Endenburg, 2006). The following key hypothesis thus appeared to be justified in the UH setting: a local democracy can effectively make public policy by informed consent, and thereby transcend the common practice of majority voting and coalition formation. The first major ‘test’ of this hypothesis involved the aftermath of the election in 2014, when all political parties elected in the council decided by consent on the policy intentions for the next four years. Creating and assessing Inspired by these experiences, the new city council also formed a new taskforce to develop a new approach towards local democracy and governance, informed by their initial experiences as well as the BB’s recommendations. Towards the end of 2014, this taskforce delivered a report to the city council, which decided to adopt all of its recommendations. A key decision was to set up so-​called ‘Thursday evening’ meetings in which city councillors meet citizens to explore ideas as well as form opinions on a particular policy issue. These open meetings would enable the city council to more effectively take decisions (by consent) on issues previously explored and discussed in one or more ‘Thursday evening’ sessions. The city council expected this approach would provide more access to the expertise and ideas of citizens, and reinforce the council’s role as orchestrator of civil participation and local democracy. Theorising and justifying These new policy-making practices have been fully implemented as of February 2015, and the initial results are very promising. More broadly speaking, UH’s political processes appear to be transforming from a practice characterised by collusion and competition, to one characterised by collaboration. The UH example suggests that any effort to close the perceived gap between voters/​citizens, elected representatives, aldermen and civil servants best starts at the root of the problem: the need to respect the needs and interests of every individual citizen. In this respect, the principle of informed consent reflects the fundamental values of equivalence and 182

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mutual respect, and thus appears to provide an important alternative to decision rules such as consensus and majority vote. This alternative has long been neglected by political scientists (compare Buchanan and Tullock, 1962), although the informed consent principle has made inroads in various specific policy areas (for example, in European privacy law and in providing healthcare services). The prevailing praxis of democracy draws on majority rule and thereby promotes the formation of coalitions and majority–​ minority ploys, which in turn tend to undermine the natural preference for consent-​based collaboration. By contrast, the approach developed in UH appears to enable participation by all those citizens who want to directly contribute, while the city council maintains its role as orchestrator of civil participation and also retains the final authority to make policy decisions. This approach goes beyond the vast majority of civic participation practices, such as community building and neighbourhood support, which do not directly contribute to policy-making processes (for example, Smith, 2009; Zhang and Feeney, 2018). Theorising At a more general level, the UH example suggests that efforts to renew public governance are more likely to succeed if they exploit the strong desire of many citizens to engage in various forms of ‘expressive’ behaviour (Copeland and Laband, 2002) other than merely voting in an election every four years. Notably, many citizens may especially want to actively voice their concerns regarding topics and issues they are highly interested in, rather than a broad range of issues. Here, the key challenge for the theory and practice of democratic governance is how the reservoir of political interest and expertise, which is rather unevenly distributed across citizens and policy issues, can be used to support and inform policy-making in an effective but fair manner (Romme et al, 2018b).

Discussion and conclusion The inclusive methodology for design in PPA advocated in this chapter embraces validation-​oriented research as well as the creative design of new practices and their underlying constructs and models. Most research in PPA takes the existing institutional context as a fact of life, and thus, few scholars deliberately adopt a creative design-​and intervention-​oriented approach (for example, Smith, 2002; Gunnell, 2006; Ansell et al, 2017) that would make scholarship much more impactful and relevant to its societal stakeholders. In this chapter, we synthesised both discourses in a framework that includes scientific validation as well as creative design, as two complementary modes of research which tend to iteratively interact over time. 183

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Overall, the DS perspective enables PPA scholars to explicitly embrace a broad array of possible research outputs of design and validation work. This inclusive approach towards research activities and outputs serves to acknowledge different traditions and notions of theory and testing (as previously outlined). Moreover, it explicitly acknowledges that not only constructs and models, but for example also practices and their underlying values can be exposed to scientific validation in PPA. This broad perspective arises from the dual objective of providing a rigorous theoretical understanding of policy and administration and developing interventions for tackling current social problems and improving administrative practices. Notably, the DS methodology appears to go beyond action research and other applied research strategies. In this respect, DS systematically connects creative design (including intervention) with scientific validation through a variety of mainstream and non-​mainstream methods, whereas for example action researchers tend to focus exclusively on qualitative data collection and analysis (Eden and Huxham, 1996; Romme, 2003). DS therefore includes constructs and models as research outputs but also embraces values (for example, transparency and civic participation in first example), design principles (for example, for making policy decisions by consent in second example) and practices (for example, open data platform in ­example 1 and ‘Thursday evening meetings’ in e­ xample 2) as key resources and outputs of scholarly work in PPA. Most importantly, action research tends to emphasise retrospective problem diagnosis more than prospectively exploring and creating solutions (Romme, 2003). The two examples in the previous section illustrate the recursive and iterative nature of research at the design-​science interface, going back and forth between creating, assessing, theorising and justifying activities. They also illustrate the need for contextualising and adapting interventions to local settings and re-​adjusting theoretical concepts and models. These projects demonstrate how societal interventions are –​or are not –​realised through policy interventions, but also suggest that new theoretical understandings of collaborative forms of governance can be developed by focusing specifically on information processing and the relation with democratic institutions. The two design research projects highlight the need to understand collaborative governance in its relation to existing routines and institutions, such as the elections in the second example, and thus provide also a basis for more nuanced interventions. Therefore, the DS framework presented in this chapter apparently serves to integrate design and validation activities, and conceptualises PPA research as an iterative combination of these activities rather than separate research traditions. The examples also point at other challenges arising from work at the design-​validation interface. Both studies illustrate that practitioner–​scholar partnerships enable so-​called ‘insider–​outsider’ research (compare Bartunek 184

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and Louis, 1996). Insider-​outsider research has the overall quality of marginality, that is, one is neither altogether inside or altogether outside the system. In these partnerships, ‘the outsider’s assumptions, language, and cognitive frames are made explicit in the insider’s questions and vice versa. The parties, in a colloquial sense, keep each other honest –​or at least more conscious than a single party working alone may easily achieve’ (Bartunek and Louis, 1996: 62). An important requirement for this quality of marginality to arise is a shift in the power dynamics between scholars and practitioners, that is, the research design needs to involve the human agents in those systems as active participants in the research process, rather than merely as passive subjects and respondents. This shift towards equivalence of practitioners and scholars also serves to balance design and validation, given that practitioners have an interest in designing new tools and policies (compare practices), while scholars’ primary focus tends to be on validating the underlying constructs, models and principles. Here, one specific challenge is the democratic mandate of the research team to introduce new values into the system. To prevent capture or randomness, a systematic reflection on the origins of these values and the power positions in the field is crucial in this type of research. This exploratory chapter did not yet explicitly address the scope of application of the inclusive methodology proposed. In this respect, the DS framework is more likely to be applied in smaller jurisdictions than larger ones (for example, at national or supranational levels), due to two factors. First, smaller jurisdictions have a less complex stakeholder system, and second, the policy-making and implementation processes are more tightly coupled. These conditions may promote DS projects at local levels, while not completely inhibiting similar interventions at governmental levels beyond local ones. Examples of design-​driven projects at the national and global levels are New Zealand’s radical tax reform (Stephens, 1993), the active engagement of thousands of citizens in writing new legislation in Taiwan (Barry, 2016; Tang, 2016), and the creative design of an alternative global governance system (Romme et al, 2018a). The challenges arising from DS projects in large jurisdictions compared to smaller ones are, however, not yet well understood and require more research. The type of work enabled by the inclusive framework proposed here may be highly challenging (see also, Stoker and John, 2009; Bakker and Denters, 2012). In this respect, the first example shows that the initial energy and commitment arising from a deliberate intervention does not easily result in organisational changes and outcomes embraced by practitioners. The second example, though, suggests that public institutions can be deliberately transformed, especially when key agents and stakeholders share a sense of urgency regarding the dysfunctionality of existing arrangements and engage in a collective effort sustained over several years. The institutional work expected from researchers in these co-​creation processes demand skills and 185

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competences that are radically different from what researchers in our field usually learn. Notably, we are not arguing that all research needs to be design-​oriented or adopt the methodological framework presented earlier. In this respect, social science-​driven research into established or emerging PPA settings is entirely legitimate, because it provides a deeper awareness and understanding of these settings (see Figure 8.1). The point is that PPA, as a field, can only grow if (at least a substantial number of) scholars rise to the challenge of making a difference and deliberately engaging in attempts to co-​create practices with citizens, administrators and politicians. If the science as well as design tradition are nurtured, many new opportunities for impactful work at the interface between the two will arise. Of course, the question can be raised whether PPA scholars have the mindset, skills and incentives to engage in this type of research. In this respect, graduate programmes may have to be adapted to educate future generations of scholars in more inclusive methodologies such as design science. Moreover, journal editors, deans of public administration schools and other key stakeholders need to rethink some of their guidelines regarding research output and academic careers (Rousseau, 2012; Romme, 2016). One specific step for deans to consider is developing a so-​called ‘organisational learning contract’ that might be instrumental in redefining the expectations and commitments of the school’s leadership, faculty and students (Rousseau, 2012). In conclusion, a methodological framework for doing design science was developed in the first half of this chapter. Subsequently, we reviewed several examples of studies at the design-​science interface, and discussed the learnings and implications for future work in this area. The examples highlight that DS can prevent a flight into the academic ivory tower, but also avert an exclusive instrumentalisation of our discipline. References Abbott, A. (1988) The system of professions: An essay on the division of expert labor, Chicago, IL: University of Chicago Press. Al-​H abil, W.I. (2011) Positivist and phenomenological research in American public administration, International Journal of Public Administration 34(14): 946–​53. doi: 10.1080/​01900692.2011.615554 Ansell, C.K. (2011) Pragmatist democracy: Evolutionary learning as public philosophy, Oxford/​New York: Oxford University Press. Ansell, C., Sørensen, E. and Torfing, J. (2017) Improving policy implementation through collaborative policymaking, Policy & Politics, 45(3): 467–​86. Bakker, J. and Denters, B. (2012) Experimentando con un diseño experimental, Revista internacional de sociologia, 70(2): 121–​41. 186

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Barry, L. (2016) VTaiwan: public participation methods on the cyberpunk frontier of democracy, https://​civich​all.org/​civic​ist/​vtai​wan-​democr​acy-​ front​ier/​ Bartunek, J.M. and Louis, M.R. (1996) Insider/​outsider team research, Thousand Oaks, CA: Sage. Barzelay, M. and Thompson, F. (2010) Back to the future: making public administration a design science, special issue of Public Administration Review 70(s1): s295–​7. doi: 10.1111/​j.1540-​6210.2010.02137.x Bason, C. (2016) Design for policy, New York: Routledge. Bason, C. (2017) Leading public design: Human centered governance, Bristol: Policy Press. Behn, R.D. (1996) Public management: should it strive to be art, science, or engineering?, Journal of Public Administration Research and Theory, 6(1): 91–​ 123. doi: 10.1093/​oxfordjournals.jpart.a024305 Behn, R.D. (1997) The dilemmas of innovation in American government, In A.A. Altshuler and R.D. Behn (eds) Innovation in American government: Challenges, opportunities and dilemmas, Washington, DC: Brookings Institution, pp 3–​38. Bond, J.R. (2007) The scientification of the study of politics: some observations on the behavioral evolution in political science, The Journal of Politics, 69(4): 897–​907. doi: 10.1111/​j.1468-​2508.2007.00597.x Buchanan, J.M. and Tullock, G. (1962) The calculus of consent, Ann Arbor, MI: University of Michigan Press. Buick, F., Blackman, D., O’Flynn, J., O’Donnell, M. and West, D. (2016) Effective practitioner–​scholar relationships: lessons from a coproduction partnership, Public Administration Review, 76(1): 35–​47. doi: 10.1111/​ puar.12481 Citrin, J., Levy, M. and Wright, M. (2014) Multicultural policy and political support in European democracies, Comparative Political Studies, 47(11): 1531–​57. doi: 10.1177/​0010414013512604 Cohen, M.D., March, J.G. and Olsen, J.P. (1972) A garbage can model of organisational choice, Administrative Science Quarterly, 17(1): 1–​25. doi: 10.2307/​2392088 Considine, M. (2012) Thinking outside the box? Applying design theory to public policy, Policy & Politics, 40(4): 704–​24. Copeland, C. and Laband, D.N. (2002) Expressiveness and voting, Public Choice, 110(3–​4): 351–​63. doi: 10.1023/​A:1013093610591 Davies, H.T. and Nutley, S.M. (eds) (2000) What works? Evidence-​based policy and practice in public services , Bristol: Policy Press. Dorst, K. (2012) Frame innovation: Create new thinking by design, Cambridge, MA: MIT Press.

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Romme, A.G.L. (1999) Domination, self-​determination and circular organising, Organization Studies, 20(5): 801–​32. doi: 10.1177/​0170840 699205005 Romme, A.G.L. (2003) Making a difference: organisation as design, Organization Science, 14: 558–​73. doi: 10.1287/​orsc.14.5.558.16769 Romme, A.G.L. and Endenburg, G. (2006) Construction principles and design rules in the case of circular design, Organization Science, 17(2): 287–​ 97. doi: 10.1287/​orsc.1050.0169 Romme, A.G.L., Ansell, C., Buck, J., Choi, Y., Van der Eyden, R., Figueroa Huencho, V., John, E., Kunkler, T., Mair, J., Meijer, A., Meyer, R., Stephenson, K., Välikangas, L., Whitestone, N., Yu, C. (2018a) United people: designing a new model of global governance, Journal of Asian Scientific Research, 8: 152–​70. Romme, A.G.L., Broekgaarden, J., Huijzer, C., Reijmer, A. and Van der Eyden, R.A.I. (2018b) From competition and collusion to consent-​based collaboration: a case study of local democracy, International Journal of Public Administration, 41(3): 246–​55. doi: 10.1080/​01900692.2016.1263206 Romme, A.G.L., Reymen, I.M.M.J. (2018) Entrepreneurship at the interface of design and science: toward an inclusive framework, Journal of Business Venturing Insights, 10: e00094. doi: 10.1016/​j.jbvi.2018.e00094 Romme, G. (2016) The quest for professionalism: The case of management and entrepreneurship, Oxford: Oxford University Press. Rousseau, D.M. (2012) Designing a better business school: channelling Herbert Simon, addressing the critics, and developing actionable knowledge for professionalising managers, Journal of Management Studies, 49: 600–​18. doi: 10.1111/​j.1467-​6486.2011.01041.x Ruijer, E., Grimmelikhuijsen, S., Van den Berg, J. and Meijer, A. (2018) Open data work: understanding open data usage from a practice lens, International Review of Administrative Sciences, http://j​ ourna​ ls.sagep​ ub.com/​ doi/​full/​10.1177/​00208​5231​7753​068 Sarto, F., Veronesi, G., Kirkpatrick, I. and Cuccurullo, C. (2016) Exploring regionalism in public management reforms: the case of the Italian hospital sector, Policy & Politics, 44(4): 525–​45. Schram, S.F., Flyvbjerg, B. and Landman, T. (2013) Political political science: a phronetic approach, New Political Science, 35(3): 359–​72. doi: 10.1080/​07393148.2013.813687 Shangraw, R.F. and Crow, M.M. (1989) Public administration as a design science, Public Administration Review, 49(2): 153–​8. doi: 10.2307/​977335 Shapiro, I. (2005) The flight from reality in the human sciences, Princeton, NJ: Princeton University Press. Shkliarevsky, G. (2016) Rethinking democracy: a systems perspective on the global unrest, Systems Research and Behavioral Science, 33(3): 452–​70. doi: 10.1002/​sres.2331 189

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Using a design approach to create collaborative governance John M. Bryson, Barbara Crosby and Danbi Seo

Introduction In complex, shared-​power settings, policy-makers, administrators and many other decision makers increasingly must engage in collaborative governance in order to effectively address challenging public issues that cannot be handled by single public organisations alone, or even by single sectors (Gray and Purdy, 2018; Innes and Booher, 2018). These collaborations must be governed effectively if their public purposes are to be achieved. This chapter makes three contributions toward improving the governance of collaborations: first, we argue that a design approach to the governance of collaborations offers several benefits –​both for designing a process for developing and guiding collaborations and for creating specific governance designs. Second, we enrich the theoretical and practical understanding of the nature and elements of collaborative governance by drawing on Crosby and Bryson’s (2005) ‘triple three-​dimensional view of power’ to argue that the design and use of forums for dialogue and deliberation, arenas for decision making and courts for resolving residual disputes and reinforcing underlying norms are crucial to creating effective collaboration processes and governance regimes. And third, we illustrate our argument by examining the emergence of a collaboration designed to cope with the fragmented field of minority business support in order to foster greater racial equity in income and wealth. Collaboration in this case means the linking or sharing of information, resources, activities and capabilities by organisations to achieve jointly an outcome they could not achieve alone (Huxham and Vangen, 2005). Definitions of collaborative governance vary (Gash, 2016). We adapt Emerson and Nabatchi’s argument (2015: 18) to say it encompasses ‘the processes and structures of public policy –​and policy-​related [added] –​decision making and management that engage people across the boundaries of public agencies, levels of government and/​or the public, private, and civic spheres to carry out a public purpose that could not otherwise be accomplished’. Our argument proceeds in several sections. First, we review what a design approach might add to collaborative governance literature. Second, we reprise Crosby and Bryson’s (2005) ‘triple three-​dimensional view of power’ and 191

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their forums, arenas and courts framework and adapt it to the challenge of designing and realising effective collaborative governance. Third, we review relevant lacunae in the theory of collaborative governance. Fourth, we analyse a case illustrating how a collaboration and collaborative governance approach were designed to improve minority business support in the Twin Cities of Minnesota, USA. Finally, we present a number of conclusions regarding the promise of a design approach to collaborative governance.

The design approach Herbert Simon (1996:111) famously said, ‘Everyone designs who devises a course of action aimed at changing existing conditions into desired ones.’ Designing as a process and specific designs have typically focused on communication (designed messaging), material objects (products, buildings), activities or services (training, health and social care) and systems (logistics, financial management). Less attention has been paid to designing policy, although that is changing (Bason, 2014; Howlett, 2019). Our concern is with the linked challenges of designing the settings for collaboration and the governance of collaborations. The former involves the creation of collaborations, while the latter concerns the direction setting, policy-making effectiveness and implementation oversight of collaborations. The literature indicates that designing is an attitude, a process approach and a wide array of tools and techniques. As an attitude, design is open-​ minded, assumption-​challenging, end user-​oriented, outcome-​focused and innovation-​embracing (van Aken et al, 2007; Bason, 2017: 46–​50). As an approach, designing favours deep empathic exploration of the problem or challenge space; the generation of alternative scenarios and solutions, often through the engagement of end-​users; and the enacting of new practices in an experimental, pragmatic way (Fisher, 2016; Ansell and Torfing, 2014; Bason, 2017: 73–​87). The toolkit is extensive and emphasises creativity, active learning, full engagement of the senses and emotions, visualisation and prototyping (Ideo.org, 2015). A design approach differs from typical problem-​solving in that the problem definition is held more tentatively and often changed based on new information; solution development and implementation are not rigidly separated; the process is more bottom-​up than top-​down; and a far broader array of tools and techniques is brought to bear. Co-​labour of various kinds is involved, including co-​commissioning, co-​designing, co-​delivery and co-​assessment (Nabatchi, Sancino and Sicilia, 2017). A design approach is therefore more suitable for addressing challenges in complex situations than is problem-​solving, which is more suited to stable, technically simple, less feedback-​r ich situations. As situations requiring governance become more complex, Bason (2017: 50) advocates a design approach to ‘governance 192

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models’. So far, however, scholars have mostly neglected the role of power in creating effective designs, which is especially problematic when design is applied to governance.

The triple three-​dimensional view of power and the design and use of forums, arenas and courts Crosby and Bryson (2005: 401–​426) presented a triple three-​dimensional view of power and used it to describe and analyse the basic settings of public action –​forums, arenas and courts –​in their book Leadership for the Common Good and related publications. Their framework was applied to issues of public policy formulation, adoption and implementation. It was not developed to deal with issues of collaborative governance, but its applicability there is clearly justified, since the framework is particularly useful for understanding and shaping shared-​power situations where no one is wholly in charge. Collaborations are virtually always shared-​power arrangements in which organisations attempt to achieve together what they cannot achieve separately (Emerson and Nabatchi, 2015; Gray and Purdy, 2018). The triple three-​dimensional view of power integrates Giddens’ (1979; 1984) analytical separations among three kinds of human practices and Lukes’ (2005) three dimensions of power (see Figure 1). The three practices are: communication (signification), decision making (linked to domination via asymmetrically distributed resources) and the management of residual disputes and reinforcement of underlying norms (legitimation). The first dimension of power is observable action (Dahl, 1961); the second dimension highlights enablers and barriers to action (Bachrach and Baratz, 1963); and the third dimension comprises the often subtle shaping of felt needs, rights and responsibilities. The third dimension is comprised of what Giddens and Lukes call deep structures Giddens (1979; 1984) and Lukes (2005). Deep structures provide the rules and resources, broadly defined, that are drawn upon to create action in the first dimension. That action, however, is shaped by the ideas, rules, modes, media and methods of the second dimension (Bachrach and Baratz, 1963). The constituting elements of the second-​dimension biases attention toward some matters –​meaning issues, decisions, conflicts and policy preferences –​and away from others, which become non-​issues, non-​decisions and suppressed conflicts and policy preferences. Action in the first dimension then creates, recreates and reshapes the rules, resources and transformation relations of the second and third dimensions –​a process Giddens refers to as structuration. Action, in other words, reproduces the rules, resources and transformation relations that make it possible, but also can reshape those rules and resources. 193

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Crosby and Brysons (2005)argue that in shared-​power situations, the three dimensions of power show up in common sense and often easily recognisable ways as: formal and informal forums, for the creation and communication of meaning; formal and informal arenas, where policy and related decisions are made and implemented; and formal and informal courts, wherein residual disputes are settled and underlying norms are enforced. Their analytic framework is both positive and normative. The categories are analytic, but they use the framework and relevant literature to develop propositions that fit with design science principles for helping create what does not yet exist (Romme, 2003; Van Aken and Romme, 2012). Forums In keeping with Lukes (2005), Crosby and Bryson found that leaders and committed followers have the most impact via shaping or taking advantage of the ideas, rules, modes, media and methods in the second level of power. In forums, the most important of these are: communicative capability, interpretive schemes, relevance, norms of pragmatic communication, modes of argument and access rules. Communicative capability is simply the capacity to create and communicate meaning. This can include, for example, rhetorical skill, the ability to use various communications media, or the ability to assemble an audience when needed. Interpretive schemes are intersubjective organising frameworks we humans use to structure cognitions, interpretations, or understandings of events in ways that are meaningful and that allow us to articulate and evaluate what we experience. An individual’s and group’s set of interpretive schemes is structured by a set of relevances determined by his or her concerns (Schutz, 1967: 78–​86). Inside forums, competing, conflicting, or contradictory interpretive schemes must be at least partially mediated for concerted action to emerge. Designing as an approach is itself a kind of meta-​interpretive scheme that features framing and reframing (Dorst, 2015). Norms of social (not just personal) relevance and of pragmatic communication, as well as modes of argumentation and access rules, help mediate among schemes. Norms of pragmatic communication include four practical criteria for judging speech aimed at influencing action: Actors are expected to speak comprehensibly, sincerely, appropriately in context and accurately (Habermas, 1981; Forester, 1989). Argumentation is another important aspect of the mediation of differing interpretive schemes. Designing does this via idea and artifact creation and testing as part of developing persuasive problem frames and solutions. The design and use of forums influences which claims will be made, based on which information and which kinds of arguments, and what weight will be given to the claim and arguments backing it up. Last, rules governing access 194

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to participation in forums strongly influence who speaks what, where, when, why and how and who listens. In doing so, they strongly influence which decisions, issues, conflicts and policy preferences get discussed. The design and use of forums in particular circumstances does two things. First, it establishes the structural (collective) basis of a potential list of decisions, issues, conflicts and policy preferences which might be debated. And second, it mediates the transformation of that list into the actual decisions, issues, conflicts and policy preferences that will be addressed, on the one hand and those items that will not be discussed, on the other hand. Examples of forums include meetings, debates, journals and print and electronic media. Arenas In arenas the most important ideas, rules, modes, media and methods in the second level of power include decision-​making capabilities; domains; agendas; and planning, budgeting, decision making and implementation methods. We would add design methods, too. These strongly affect how differing, contesting, or conflicting capabilities are at least partially mediated in arenas. In addition, rules governing access to participation in the arenas affect which persons, groups, organisations and capabilities are admitted to arenas and thus influence which conflicts, issues and policy preferences will be considered as part of the decision-​making process. The decision-​making capabilities that actors have available to influence a sequence of decision-​making interactions depend on the rules and resources they can use (Pfeffer, 2010). These capabilities can range from verbal skill, to the ability to hire and fire, to budgetary control, all of which can affect decision outcomes through drawing on rules, resources and transformation relations that offer advantage. Decision making refers to the actual application of some or all of those capabilities in interaction. Actors’ differential capabilities will strongly influence which decisions, issues, conflicts and policy preferences count in particular circumstances. Arenas may be primarily economic, political, or organisational. In our case, we are interested in inter-​organisational decision-​making arenas and how they are governed. The chief function of arenas is distribution and redistribution of access to decision making, which helps to maintain or change organisational, political and economic relations. Astute designers understand the ways that new or existing arenas can affect the success of their efforts. Courts In courts the most important ideas, rules, modes, media and methods in the second level of power are conflict-​management and sanctioning capabilities, 195

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norms, jurisdiction, conflict management methods and access rules. These second-​dimension components strongly influence which residual conflicts get resolved and how and with what consequences for underlying norms in the system. Courts are associated with laws (or norms, principles, policies, rules and standards) and modes of sanctioning (ways of rewarding or punishing conduct). Courts are used to evaluate decisions or conduct in relation to laws or norms, usually in order to settle disputes and to enforce underlying norms in the system. Courts distribute and redistribute access to legitimacy and thereby help to maintain or change laws or other modes of sanctioning conduct. While courts are popularly associated with law enforcement, perhaps the most important court is the informal court of public opinion, which operates via norms. Courts that lie between the formal courts and the informal court of public opinion include regulatory bodies hearing conflicting views before rendering a decision and a host of alternative dispute resolution approaches. The Crosby–​Bryson framework leads to three observations crucial for understanding collaborative governance as the design and use of forums, arenas and courts. First, forums, arenas and courts and the way they are assembled into collaborative governance arrangements, or ‘regimes’ (Emerson and Nabatchi, 2015), are a product of design, although the process may be iterative and messy. Second, the ideas, rules, modes, media and methods that constitute the second dimension of forums, arenas and courts are both enablers of some things and constraints on others. Third, in situations in which no one is wholly in charge, typically the most effective way of influencing action and outcomes is indirection –​that is, by shaping the ideas, rules, modes, media and methods that strongly influence what will emerge as action and what will not (Crosby and Bryson, 2005). Indeed, that is what governance systems do; they shape what emerges and what does not.

The literature on collaborative governance We briefly review key contributions on the governance of collaborations, including Bryson et al (2006; 2015), Ansell and Gash (2008; 2018), Provan and Kenis (2008), Emerson and Nabatchi (2015), Gray and Purdy (2018), Innes and Booher (2018) and Romzek et al (2013). The Crosby and Bryson conceptualisation adds to each explicit attention to the three dimensions of power (action, structure and their dynamic linkages); the settings (forums, arenas and courts) that shape what emerges as action, issues, conflict and policy preferences; and interconnections of these settings as part of an effective governance approach. Bryson et al (2006) emphasise the importance of trust, norms and values in developing collaborative governance and then draw on an early

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version of Provan and Kenis’ (2008) work to incorporate three governance structures: self-​governing, lead organisation and network administrative organisation. Their 2015 update again does not explicitly differentiate among the levels of power, but it does highlight the importance of forums for strategy formulation. In our terms, Provan and Kenis are describing different kinds of arenas and their evolution over time, as well as contingencies affecting the choice of arena. Ansell and Gash’s (2008) collaborative governance model focuses on forums and the ‘institutional design rules that set the basic ground rules under which collaboration takes place’ (p 549). That said, distinctions among forums, arenas and courts are elided, except for attention to formal arenas as a source of mandates and formal courts as the setting for certain kinds of conflict management. Most of the focus is on the first dimension of power, along with implicit attention to the second dimension of power in the emphasis on the need for trust, shared understanding, clear ground rules, transparency, inclusion and commitment. The same observations can be made about Emerson, Nabatchi and Balogh (2011), with important additions. They consider the broader system context and structures within which collaboration takes place, pay more attention to outcomes and emphasise the creation of collaborative governance ‘regimes’. Their conception of regimes draws on Krasner’s (1983: 2) definition of a regime as ‘sets of implicit and explicit principles, rules, norms and decision-​making procedures around which actors’ expectations converge in a given area’. (The idea of regime, in our view, is an integrated set of forums, arenas and courts.) Emerson and Nabatch‘i (2015) book extends and deepens their earlier argument and provides many illustrative examples. Ansell and Gash (2018) see collaborative platforms as an important potential element of collaborative governance. They define collaborative platforms as ‘an organisation or programme with dedicated competencies, institutions and resources for facilitating the creation, adaptation and success of multiple or ongoing collaborative projects or networks’ (p 20). They envision these platforms as a kind of network administrative organisation designed to help govern multiple collaborations. Their discussion elides the distinctions among kinds of setting and the dimensions of power. Gray and Purdy (2018) provides perhaps the fullest conception of collaboration as a process. Special features of the book include the detailed attention to the micro-​dynamics of creating shared understanding, power and conflict dynamics and cross-​level dynamics. They draw explicitly on Giddens (1984) and structuration and pay attention to the second dimension of power without naming it as such. They do not distinguish very explicitly among forums, arenas and courts as settings.

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Innes and Booher (2018) provide perhaps the richest discussion of what we mean by the design and use of forums, thereby implicitly attending to the second dimension of power. They do not distinguish clearly among forums, arenas and courts; indeed, in their chapter on collaborative governance they refer to all three as forums. Finally, Romzek et al (2013) richly elaborate how what we would call informal courts operate as mechanisms for ensuring accountability. They pay a great deal of attention to the importance of norms, one of the constituting elements of courts and the rewards and sanctions designed to enforce those norms.

Applying the Crosby and Bryson framework to the case of Synergy (a pseudonym) In this section we demonstrate the usefulness of a design approach to collaborative governance and the usefulness of the Crosby–​B ryson framework. Specifically, we explore the design and use of forums, arenas and courts as part of the process of creating a collaboration and a specific design for its governance. Our example is Synergy, a collaboration of seven nonprofit organisations in the Twin Cities of Minnesota USA, whose purpose is to support minority-​owned businesses. Note that the case illustration is not a test of the framework, but is instead a kind of proof of concept –​or, in terms of the design literature, a human-​centred and theory-​informed prototype of how the framework can help with the design of a collaboration process and specific governance design. We begin with a brief overview of the context and our methodology, and then move to the case. The public challenges posed by racial inequality in income and wealth Racial income and wealth inequalities have been one of the most serious, persistent problems in Minnesota. Meanwhile, a bright spot has been minority-​owned business growth in Minnesota and the Twin Cities, which is higher percentage-​wise than white-​owned business growth, although minority-​owned businesses have on average fewer sales and less capitalisation. Minority-​owned businesses can have significant impact on reducing racial inequality (Bradford, 2014). Public policies that support minority-​owned businesses and minority entrepreneurs have, however, not functioned as effectively as they might. The lack of coordination among different policies and programmes has produced major gaps in support, caused confusion and resulted in limited impact on the growth of minority-​owned businesses (Accenture, 2015; Association for Economic Opportunity, 2017). Some of the most important

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public policies and programmes are outlined in Table A.9.1 (see Table A.9.1 in the appendix). Because of fragmented public policies, local-​level, bottom-​up collaboration can be a promising remedy, meaning it can help coordinate and integrate the efforts of organisations that are separated by the flows of authority and resources in existing ‘policy fields’ (Stone and Sandfort, 2009; Ansell et al, 2017). Synergy grew out of a growing realisation among organisations supporting minority entrepreneurs that they would be able to truly increase their impact only if they pooled their expertise and access to different types of entrepreneurs. The effort has been spearheaded by the Minority Business Development Association (MBDA) and especially its CEO. In gathering data, we used a longitudinal case study method (Eisenhardt, 1989; Yin, 2017). Our study so far covers four-​plus years from August 2014 through to December 2018. Our case analysis combines multiple sources of evidence: (1) Archival documents, including meeting documents, email communications regarding important decisions and strategic plans, annual reports, newsletters and media coverage of each participating organisation; (2) In-​depth, semi-​structured, longitudinal interviews with the key participants, including monthly interviews of MBDA’s CEO since August 2015, other participating organisations’ CEOs quarterly since 2017 and key staff and external consultants since 2015; there are a total of more than 107 interviews with 20 unduplicated interviewees over four-​plus years; (3) Participant observation, including more than 67 hours of observation in meetings and events, along with detailed field notes. We have anonymised the names of the participants and the collaboration. Synergy started as an idea in 2015 and has developed through overlapping stages, including pre-​c ollaboration, a ‘cohort’ phase and a formal collaboration. We argue that a design approach has permeated the endeavour. Links to design as an attitude, approach and toolkit will be noted in italics as we describe the case.

The pre-​collaboration phase In 2014, the MBDA board hired a new CEO and charged him with making a ‘transformational change’ and taking MBDA to the next level. The chief design focus at this stage for the new CEO and people working with him was understanding MBDA’s situation and what was needed to take MBDA ‘to the next level’ (see Table A.9.2 in the appendix). Additionally, they focused on redesign of MBDA and developing strategic partnerships and securing funding. Key design choices were whether or not to engage outside analysts and facilitators, how to redesign MBDA and whether and how to pursue strategic partnerships.

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Design and use of forums The CEO initiated a series of analyses of MBDA and the broader field of support for minority-​owned businesses. The approach accorded with design’s emphasis on deep engagement with the problematic situation, including understanding the system producing the problems. Multiple types of meetings with internal and external stakeholders were crucial forums for information gathering, deliberation and gaining allies. Also important were various consultations conducted by outside analysts and their reports. These helped the CEO see how the positive growth cycle of MBDA was limited by various ‘balancing loops’, for example, its shortage of business advisors (Senge, 2006). The crucial communicative ability was the CEO’s verbal skill, but also his related approachableness, legitimacy, relationships, interpersonal skill in various settings, openness to change and commitment to better outcomes (design attitude). The analyses revealed that several interpretive schemes were at work. The first was that the nonprofits supporting minority businesses were viewed as charities, meaning that they should be supported by grants, gifts and volunteers. The CEO decided it made sense to help contributors (foundations and corporations) see that they were making investments, not just charitable donations. The other interpretive scheme he began pushing was the need to think beyond individual minority support organisations and to think instead about the ecosystem of support for minority businesses (reframing). The analyses indicated that the policy field was highly fragmented and that a focus on the whole ecosystem was necessary in order to have significant impacts on minority-​owned businesses across the entrepreneurial lifecycle. Also relevant were interpretive schemes highlighting racial equity and socioeconomic wellbeing. The common relevance among all these schemes was the link to support for minority entrepreneurs and businesses and to the Twin Cities (reframing, synthesis). Early on, the CEO, MBDA staff and the MBDA board were expected to observe the norms of pragmatic communication in their pursuit of increasing the organisation’s impact on minority entrepreneurs. They also had to be sensitive to the differing cultural contexts of minority groups, as well as the business, banking and foundation communities. The modes of argument emphasised data-​gathering and analysis. Grant applications were also important vehicles for transmitting persuasive arguments about the need for change and protoyping potential solutions. By giving many stakeholders access to forums at this stage, the CEO ensured that he heard diverse perspectives, built or reinforced relationships and gained new insights about MBDA’s situation (design approach and attitude).

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Design and use of arenas In the pre-​collaboration stage, the CEO had considerable capability, including authority and leeway, to make decisions on behalf of MBDA, as long as he stayed within the bounds set by the board of directors. In terms of domain, he was mainly confined to MBDA’s management, but he also began to cultivate a number of external relations that would directly or indirectly affect future decision making. The agenda was initially focused on MBDA and how to shape its direction, alignments, operations and funding. The agenda began to expand beyond MBDA when the outside analysts’ report indicated that strategic partnerships with similar organisations could help magnify MBDA’s impact. The CEO strove to ensure that MBDA’s planning, budgeting, decision making and implementation methods helped MBDA become more mission-​focused, better aligned, more efficient and more effective. The design and use of courts The operation of formal and informal courts was not particularly apparent in the pre-​collaboration stages. MBDA’s CEO was committed to helping it move to the next level and there were some conflicts around shifting organisational norms. He sought to change the MBDA culture, especially via shifting the organisation’s norms regarding aspirations, productivity and performance (reframing). The idea was to build a court of public opinion within MBDA that endorsed having a higher standard of excellence and far greater impact. Effects of design and use of forums, arenas and courts in the pre-​collaboration stage The MBDA CEO and consultants developed a fuller picture of MBDA’s situation. They identified the feedback loops and limits to growth in MBDA’s current operating mode and recognised the need to tackle limiting loops and build on positive loops (Senge, 2006). MBDA staff and programmes were reorganised to achieve mission alignment. Dominant interpretive schemes began shifting toward the investment and ecosystem perspectives.

The intermediate collaboration phase This stage involved continued attention to strengthening MBDA’s focus and developing a collaboration among organisations supporting minority entrepreneurs (see Table A.9.3 in the appendix). The design focus was on 201

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continued organisational redesign and transformation at MBDA as well as on the process of forming and funding a full-​fledged collaboration. Key design choices were which MBDA programmes should be dropped or added and whether to move MBDA offices. Additionally, MBDA’s CEO and his advisers needed to make choices about proceeding with collaboration: How to use consultants, which organisations to include as partners and whether to use developmental evaluation (Patton, 2011). The CEOs of seven organisations, including MBDA, decided to form a ‘Cohort’ to explore further what collaboration might accomplish. As the CEOs got to know each other, they became clearer about what they wanted (co-​labour and emergent goals and solutions). They established work groups tasked with developing a common IT platform and intake process, a shared and much larger capital lending pool, joint branding and marketing strategies and uniform impact measures to be used by all members of the cohort (prototyping). The design and use of forums Important initial forums were MBDA board and staff meetings, client and funder conversations and ‘reconnaissance’ meetings with potential collaboration members. The MBDA CEO also organised some new forums –​ such as leadership team retreats for executive staff and mid-​level directors –​ that helped staff feel included in deliberations about MBDA’s direction and operations. The MBDA CEO used a number of forums (email exchanges, one-​on-​one and group meetings) to persuade CEOs of other local nonprofits supporting minority entrepreneurs to join MBDA as partners. Later forums included meetings of the Cohort and its workgroups. Communicative capabilities in this stage included especially the MBDA CEO’s assets and consultants’ facilitation skills. Also, the CEO realised that MBDA’s physical office space was making a significant symbolic statement. Specifically, he decided it conveyed an image of a shabby nonprofit. He and staff members then decided to remodel the office in a more businesslike style that would convey high standards. Additionally, the office was located in downtown Minneapolis, while the bulk of MBDA clients were based in North Minneapolis. MBDA thus began planning for a move to North Minneapolis to convey more forcefully its link to minority entrepreneurs (visualisation, artifacts). The CEO used his communicative capability to make speeches and organise conversations to give the issue of support for minority business more visibility at the local to national levels. Some staff used their communicative capability to convey their feeling of being overworked and skepticism about changes. The CEO’s communicative capability was supplemented by two consultants who were adept at planning and facilitating meetings among 202

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the CEOs who agreed to join the Cohort. The consultants’ written scope of work also was a form of virtual prototyping. As for interpretive schemes, the intermediate stage marked a stronger shift toward seeing MBDA and similar organisations as embedded in an ecosystem of policies, practices and multisector organisations (reframing). Cohort members bought into the idea of having ‘one front door’ for minority entrepreneurs who sought help with financing, business planning and certification (reframing). At the same time, the MBDA CEO detected what he called ‘small-​N nationalism’, within MBDA and the other partners. Small-​N nationalism was the label he put on organisations’ tendency to think foremost about their own interests rather than the mutual interests of the Cohort members. An additional significant interpretive scheme at this juncture was the understanding on the part of the CEOs and their staffs that the collaborative effort was an emergent, developmental process (reframing). The developmental evaluators helped Cohort members understand that collaboration was not an easy answer to hard problems, but was in fact a hard-​to-​achieve answer to hard problems. This helped foster provisional patience among Cohort members and make them willing to endorse a developmental approach to their joint work (design approach). Meanwhile, within MBDA, its CEO strove to emphasise the interpretive scheme ‘One MBDA’, which helped staff and board make sense of decisions to prune some programmes and initiate new ones. Staff realised that programming directly relevant to assisting minority entrepreneurs should continue and other programming should be dropped. When the Cohort set up workgroups, the members agreed to group titles that signaled what was relevant to each group. Honouring the norms of pragmatic communication is evident in one example each from MBDA and the Cohort. In deciding to first remodel MBDA offices and then planning to move to North Minneapolis, MBDA’s CEO demonstrated awareness of communication in context. In the example from the Cohort, the members charged each workgroup with developing objectives, identifying deliverables and making specific plans. Formal analyses continued to be important modes of argument. The remodelling of MBDA’s offices and the planned move were supported by analyses of the existing office space and of MBDA’s clients. MBDA’s CEO and consultants also used assigned readings and a focus on core values to help MBDC members develop shared understanding and commitments. By organising a learning tour to visit an ecosystem change effort in Memphis, the MBDA CEO helped make the idea of ecosystem change very real. Cohort members began to ‘think big’ (visioning). The group authorised a developmental evaluation (Patton, 2011) effort, involving two of the authors,

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to gather information about how the collaboration was working and to make recommendations for improvement. Access rules within MBDA were altered. Some new staff with needed skills, attitudes and energy were hired and some old staff moved on to other employment. (The CEO was careful to manage staff departures gracefully, ensuring that neither informal nor formal courts would react adversely to employees’ treatment.) The addition of the leadership retreats also gave senior staff members more access to each other’s thinking and concerns. Access to Cohort meetings was initially confined to CEOs and facilitators, but later some staff and the evaluators were invited. The design and use of arenas Key arenas at this stage were senior staff meetings, CEO and board deliberations and funders’ grant-​making venues. The Cohort also had some decision-​making authority –​chiefly concerning the decisions about whether to become a full-​blown collaboration and what the contours of that collaboration might be. Policy-making and implementation capabilities expanded inside and outside MBDA. The CEO began to share more authority with staff once he felt that he had a strong top team in place. He also attempted to influence national foundations’ priorities and analyses. For example, a foundation’s decision makers were inspired by his speeches and concept chapters on the ecosystem work and created a new grant programme to help female entrepreneurs and minority entrepreneurs achieve higher rates of success. MBDA’s CEO was invited to help design the grant process. In the end, he was able obtain grants for building the Cohort from various foundations and banks. The domain of the change effort also expanded. MBDA’s CEO attended to the decision-​making domain of the government programmes and nonprofits that he hoped would accept the spinoff of programmes not central to MBDA’s mission. He began working with funders whose domain was national while continuing to seek resources from funders in Minnesota, including garnering funding for the move to North Minneapolis. The Cohort members effectively expanded their domain to a broader client base. Additionally, the CEOs of potential partner organisations had capabilities to negotiate their organisations’ participation in the Cohort. Within MBDA, the decision agenda focused on adding projects such as a partnership with Junior Achievement to support entrepreneurial education and behaviour on the part of high school students and the MBDA-​sponsored ‘mini-​MBA’ to educate budding and more established entrepreneurs. The CEO eliminated programmes that did not align with the organisation’s mission. Top staff also put raising grant funds high on their agendas. The top 204

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items on the Cohort agenda included decisions about the Cohort’s future and raising more capital. Within MBDA, planning, budgeting, decision making and implementation methods became more participatory during this stage. The Cohort operated by consensus, a process formalised via separate MOUs between MBDA and each of the other members. Access to Cohort meetings expanded incrementally. In order to be a part of the Cohort, partners had to show a willingness to work with each other and focus on the joint aim of helping minority entrepreneurs, even if particular organisations focused on a specific type of minority entrepreneur. Initially, only the CEOs and facilitators attended Cohort meetings, but some staff were invited to participate by the fourth meeting and the evaluation team gained access by the seventh meeting. The design and use of courts All the Cohort organisations had to comply with legal requirements for nonprofits and had to help clients comply with requirements for participating in government programmes. MBDA and the Cohort gained local and national legitimacy in the informal court of public opinion by obtaining grants from major foundations. Toward the end of this stage, the group began discussing the need for and content of a set of guiding principles, which were adopted in the next stage. Effects of design and use of forums, arenas and courts in the intermediate collaboration stage The interaction of forums, arenas and courts in this stage helped MBDA staff become more aligned with and committed to the vision of One MBDA. At times, the staff were confused by internal changes but were cheered by the success of new projects and infusions of revenue and prepared for a move to a better physical location. MBDA stakeholders could see that the organisation was becoming more sophisticated. The Cohort, meanwhile, developed a shared understanding of the ecosystem of support for minority business and built trust among partners as well as a sense of direction and shared ways of working together.

The Later Collaboration Phase In this stage the Cohort moved to full-​fl edged collaboration. The workgroups and consultants conducted extensive market research (deep engagement with the problematic situation and possible solutions). Cohort members recognised the need for a new name –​Synergy –​and 205

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adopted a joint MOU to formalise governance arrangements. The MOU included an agreed mission; set of guiding principles; decision-​ making rules; a commitment to shared leadership, joint fund raising and other joint work; and methods for resolving conflicts (see Table 9.4 in the appendix). Design and use of forums In cohort meetings, participants considered multiple possibilities for naming their collaboration and settled on Synergy (reframing and prototyping). Drafts of the MOU were reviewed and reworked (prototyping). Workgroups continued meeting and made progress reports. The developmental evaluation team conducted quarterly interviews with CEOs and participating staff. Synergy members, facilitators and evaluators had many design-​oriented conversations about the MOU and accompanying case for funding, meant to convince funders to increase the capital loan and investment pool for minority business support. Successful ‘mixers’ apprised local stakeholders of the new collaboration and built support among lenders, government officials, foundation officers and others for transforming the ecosystem of support for minority business (coalition building). Synergy CEOs drew on their communicative capability to argue within the group for their vision of what collaboration might look like and accomplish. MBDA grant writers used their skill to craft successful grant proposals. A branding expert was hired to aid in developing a compelling identity for the collaboration. The emphasis on the ecosystem view and on support for minority business as a smart investment were dominant interpretive schemes in this stage. The MBDA CEO remained concerned about the evidence of ‘small-​N nationalism’ among partners as well as MBDA staff. The national context became more relevant, as Synergy members began making the case for funding that would help them nurture similar collaborations in other cities. The idea of a national focus developed for several reasons. First, foundations outside of Minnesota were more interested in what Synergy was doing than local foundations. National foundations wanted to see the work expanded to other cities because they could see its potential significance for addressing racial income and wealth disparities. Second, gaining resources for expanding the approach elsewhere would also add capacity locally to do the work. Third, more loan and investment capital was available nationally than in Minnesota. Finally, building successful collaborations in multiple cities would build support for a more coordinated set of federal and state policies in support of minority-​owned businesses. In other words, an effective advocacy coalition might be built (Jenkins-​Smith et al, 2015).

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Synergy members honoured norms of pragmatic communication as they sought to brand the collaboration so that its mission could be easily understood by multiple audiences. The name and logo signified an understanding that the partners sought to catalyse change rather than somehow accomplishing it all themselves. The logo’s circle of seven multicoloured dots signaled the distinctiveness of each collaborating organisation and their shared decision-​ making model (artifacts). Results and analysis of brainstorming sessions, the draft MOU, progress reports, a second learning trip (this time to New Orleans), developmental evaluation reports and a draft case for funding all were important modes of argument in this phase. The evaluation consultants, in particular, urged Synergy members to adopt a set of guiding principles that would be the heart of the joint MOU. The circulation of draft principles and draft MOU gave the members a chance to have their ideas included. Consultant feedback helped members understand their mutual work better and also heightened attention to the capacity gap among partners. The final MOU incorporated the agreed mission and guiding principles that recognised the need to strengthen the partnership as well as provide a unified, more effective support system for minority business. Synergy CEOs, some staff and consultants had access to Synergy meetings. Consultants held meetings among themselves, with MBDA’s CEO and separately with the other CEOs and some staff. The mixers were by invitation to a select group of clients, people from organisations that worked with Synergy members and funders. The design and use of arenas The Synergy MOU codified the guiding principles, decision-​making process and rules and allocations of formal authority, thus establishing Synergy as a formal governance arena. The MOU gave lead agency status (Provan and Kenis, 2008) to MBDA, specifically to act as the collaborative’s project manager. Working groups made important decisions about vendors to develop a single IT platform for minority entrepreneurs and to conduct market research. The IT platform is intended to be a ‘marketplace’, essentially a matchmaking service bringing together entrepreneurs, lenders, investors and technical service providers (Parker et al, 2016; Ansell and Gash, 2018). The workgroups extended their policy-​making and implementation capabilities by selecting consultants to carry out major tasks. The MOU gave policy-​making authority to Synergy and day-​to-​day project management responsibility to MBDA –​ both moves aimed at increasing Synergy’s governance, management and implementation capabilities.

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The MOU makes clear that Synergy’s central domain is minority business support in Minnesota. Still, the group seeks to have greater impact by helping build similar approaches in other metropolitan areas; additionally, some Synergy members are engaged in national efforts to dramatically increase pools of lending and credit resources. During this stage, agreement on the MOU and the investment case were high on Synergy’s agenda. The work groups also helped keep the IT platform, market research and capital development on the group’s agenda. The Synergy partners became more specific about planning, budgeting, decision making and implementation methods. In this stage, Synergy members directed attention to the significant differences in member organisations’ capacity to engage in the Synergy work. MBDA and another organisation had much larger staffs than the other five and therefore more ability to write grants, participate in work groups and handle other Synergy-​ related tasks. The MOU made clear that building the capacity of member organisations was to be an important part of Synergy’s purpose. The MOU also specified that each member organisation would have one vote on Synergy matters and it included details about the voting process. Additionally, members committed to developing an annual work plan and accompanying budget that identified outputs, outcomes and member responsibilities. The MOU also included access rules via requirements for adding new members and permitting existing members to leave. Design and use of courts Some provisions of the MOU envisioned Synergy serving as a court for resolving residual conflicts and sanctioning conduct of its members. The conflict management and sanctioning capabilities will reside in the group as a whole. The norms that seem prominent in the relevant MOU provisions are fairness and due process. The jurisdiction would be disagreements among members or actions of members that impeded Synergy’s progress. The MOU prescribes ‘cooperative resolution’ as the conflict management method for disagreements among members. The MOU essentially outlines a focused, yet informal approach to accountability (Romzek et al, 2013). Effects of design and use of forums, arenas and courts in the later collaboration stage The formation of Synergy as an organisation bound by a clear purpose, guiding principles, norms and decision-​making rules is the most important outcome of this stage. As Thomson and Perry (2006) have observed, the governance of collaborations typically emerges through frequent, structured exchanges that develop network-​level values, norms and trust, which enable 208

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coordination and monitoring of behaviour. Synergy has been no exception and has now added structural and processual features to formalise governance. The interpretive scheme of a collaborative approach to ecosystem change is firmly in place among Synergy members. Tangible products include the joint MOU and branding. Others, such as the case for funding, are close to completion. Some partners are struggling to participate fully, but the collaborative governance system for Synergy specifies their equality in policy-making and commits all members to building the capacity of each.

Conclusions Gash (2016: 455–​456), in a recent review of the collaborative governance literature, asserts, ‘Overall, [collaboration as a] demand-​driven approach to policy problems is marked more by procedural elasticity than by fixed policy structures or procedures. The primary goal is, through a unified front of diverse interests that collectively diagnose and address policy shortfalls, to develop a set of problem-​driven solutions with sustainable benefits.’ This statement captures the Synergy approach to overcoming the fragmentation in the policy field of support for minority-​owned businesses. Synergy’s move to formal collaborative governance arrangements has been an emergent process in which clarification of the group’s ends, means and approach to governance has developed over time. As is evident in our case analysis, design choices nested within a developmental process of designing and using forums, arenas and courts for each stage provided a platform for the next stage. The approach of the MBDA CEO and staff, the consultants and the developmental evaluation team has been design-​oriented and become more collaborative over time. The approach has encompassed the design of the collaboration process, the settings within which that work has occurred, the objects produced by the process (for example, guiding principles, MOU, IT platform prototype and marketing approach) and the outputs and desired outcomes to be produced (for example, ecosystem change and significantly increased minority business success). The approach has mirrored the practice of how successful designers think and engage with clients by actively exploring the interplay of possible ends and means and, in situations involving substantial political and cultural dimensions, gradually gaining clarity about purposes and how they might be achieved (van Aken et al, 2007; Cross, 2011). Consistent with design science characteristics, the approach has been driven by purposes (that can change over time) to ‘produce systems that do not yet exist –​that is, change existing organisational [and inter-​organisational] systems and situations into desired ones’ (Romme, 2003: 559). The approach has been emergent, pragmatic and reliant on systems thinking, participation 209

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and discourse. The objects that have been the focus of design work have been ‘artificial’ in the sense that they did not yet exist (for example, a collaboration process, new settings, the IT platform, the MOU). Finally, the design and development of the process, settings and products have moved beyond the boundaries of the initial definition of the situation and the existing knowledge of the participants (Cross, 2011; Bason, 2017). At this stage, Synergy’s governance approach enables the collaboration to better address the fragmentation in the minority-​business support field that policies of governments, foundations and businesses helped create. The illustrative case highlights the importance of leaders and leadership in the design and use of a collaboration process and governance structure, along with other collaboration products, so that agreed directions, alignments and commitments are achieved (Drath et al, 2008). The MBDA CEO’s role as a collaboration sponsor and champion has been particularly important, but all of the CEOs have made a difference, as have some key MBDA staff, the consultants and developmental evaluation team. This finding concurs with virtually all of the collaboration literature (for example, Gray and Purdy, 2018; Innes and Booher, 2018). This chapter adds to the literature on collaborative governance in its explicit attention to the three dimensions of power (action, structure and their dynamic linkages); the settings that shape and guide what emerges as action, issues, conflict and policy preferences (forums, arenas and courts); and the settings’ interconnections as part of a governance approach that may or may not work well. Previous work (for example, Bryson et al, 2006; 2015; Ansell and Gash, 2008; 2018; Provan and Kenis, 2008; Romzek et al, 2013; Emerson and Nabatchi, 2015; Gray and Purdy, 2018; Innes and Booher, 2018) makes important contributions, but none is as explicit or comprehensive in addressing the dimensions, settings and their interconnections as part of a governance approach. In other words, whatever the governance design created for specific circumstances, it must pay attention to how forums, arenas and courts, plus their constituting elements and their interrelationships, are designed, if it is to be effective.

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Appendix Table A.9.1: Policies for minority-​owned businesses in Minnesota Programme

Operating organisation

Description

Contribution to policy field and ecosystem fragmentation

Minority-​ owned businesses

Disadvantaged Business Enterprise (DBE)

Federal US Department of Transportation

• Requires any state and local transportation agencies that benefit from DOT federal financial assistance, or participate in DOT-​assisted contracts, to establish goals for the participation of disadvantaged entrepreneurs.

Use of multiple different certification systems despite the similarity of the two programmes. Lack of information on which certification provides what benefits.

211 Organisations that provide support services to minority-​ owned businesses

Targeted Group (TG) Minnesota and Economically Department of Disadvantaged Administration (ED) Small Business Procurement Programme

• Supports disadvantaged businesses by offering them price preferences in selling their products or services, or in bidding on construction projects for the State of Minnesota. • Very similar to the DBE programme except that it is operated by the Materials Management Division (MMD) in the Minnesota Department of Administration.

Community Reinvestment Act (CRA)

Federal Financial Institutions Examination Council

• Encourages commercial banks and savings associations to address the needs of borrowers in their communities, and especially those in low-​and moderate-​income neighbourhoods. • Requires all banking institutions that receive Federal Deposit Insurance Corporation (FDIC) insurance to be evaluated by federal banking agencies to determine if the bank offers credit in safe and sound ways in all communities, including low-​and moderate-​income communities, in which they are chartered to do business.

Community Advantage (CA)

Small Business Administration

• Provides access to loans from mission-​oriented lenders, primarily nonprofit financial intermediaries focused on economic development to meet the needs of small businesses in underserved markets.

A variety of initiatives and funding from state and local governments

State and local governments

Implementation by individual financial institutions without coordination.

Most funding is one-​time spending that usually lasts for one or two years, which is detrimental to the sustainability or continuity • Example: in March 2016, the governor of Minnesota announced a $100 million programme to reduce economic and racial disparities. As a part of the programmes run by the service organisations. of the programme, some organisations that provide service to Different streams of short-​term minority-​owned businesses received grants from the state. funding resulting in confusion.

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Target

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Table A.9.2: Development of collaborative governance: forums, arenas, and courts in the early stage, 2014–​2015 Arenas

Courts

Effects of design and the use of forums, arenas, and courts

Design focus: • Understanding the situation MBDA faced and what can be done about it; • Organisational redesign; • Process of forming ‘strategic partnerships’ and gaining funding. Key design choices: • Engage outside analysts or not? • How to redesign MBDA’s structures and processes? • MBDA to go it alone or pursue ‘strategic partnerships’?

MBDA CEO and board make key decisions. Redesign of leadership team changes decision-​ making approach: • More delegation. New organisational design in response to lack of clear staff roles, responsibilities.

City, state, federal policies in place that legitimised support for minority-​owned business. Informal court of public opinion at MBDA in need of change. MBDA CEO worked legitimately within his authority. Collaboration legitimisation –​ as a form and process –​aided by MBDA CEO’s reputation for integrity and effectiveness.

Picture of organisation began to emerge: • Limits to growth; • Need to tackle limiting loops, build on positive loops Identification of ‘identity crisis’. Staffing reorganised; this remedied misalignment between MBDA staff skills/​positions and what it needed via clarification of roles, responsibilities; helped change shared mental models. Stage set for implementing Accenture recommendations. Move from charity frame to investment frame initiated. Focus on ecosystem: • Fragmentation; • Lack of capital and capacity.

One-​on-​one board and staff meetings. Meetings with auditors, attorneys, existing consultants. Meetings with clients and funders. Staff did trend analysis. Accenture meetings and report. Meetings with potential partners. Staff meetings aimed at mutual understanding.

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Design focus and key design Forums choices

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Table A.9.3: Development of collaborative governance: forums, arenas, and courts in the intermediate (Cohort) stage, 2016–​mid-​2017 Forums

Arenas

Courts

Effects of design and the use of forums, arenas, and courts

Design focus: • Continued organisational redesign and transformation at MBDA; • Process of forming a collaboration and funding it. Key design choices: • What MBDA programmes to drop and which to add? • Should MBDA move from downtown Minneapolis? • How to pursue collaboration? • Use consultants to manage development? • Which organisations to include? • Build in a developmental evaluation?

Feedback that staff overworked, questioning changes. Internal inclusion. Office redesign, planning for move as way to shake up culture, connect with clients. MBDA CEO works to increase the awareness of the ecosystem issue and garner support. Consulting staff holds reconnaissance meetings with potential collaboration partners. Cohort meetings: • CEOs agree to meet and explore collaboration; • Work programme created; • Work group meetings; • Learning tour; • Understanding desirability of developmental evaluation; • Welcoming evaluators.

Adding projects (Junior Achievement Fellows, MBDA Mini-MBA). Ending programmes by transferring to other organisations. More participatory decision making, internally and externally. Local corporation agreed to support MBDA’s move to new and better facility. Foundation funders make favourable decisions. Cohort as decision maker about work plans and how to proceed, including decision to be Catalyst. Lending institutions’ decisions often apparently affected by institutional racism.

National and local legitimacy fostered by obtaining grants from major foundations. Progress on forming new norm favouring collaboration and ecosystem change in MBDA and partners.

Staff confusion, but growing appreciation of and pleasure in the success of projects. More sophisticated operation visible internally and externally. Possibility of move adds to change momentum. ‘One MBDA’ boosted by ending programmes that were not central. Learning tour builds hope, team ties. Cohort gels, that is, trust built along with shared understanding of the ecosystem and direction.

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Design focus and key design choices

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Table A.9.4: Development of collaborative governance: forums, arenas, and courts in the later (Synergy) stage, mid-​2017–​mid-​2018 Forums

Arenas

Courts

Effects of design and the use of forums, arenas, and courts

Design focus: • Further growth of the collaboration; • IT platform development and marketing study; • Development of agreed approach to collaborative governance; • Development of agreed approach to joint fundraising. Key design choices: • How to pursue marketing study? • How to pursue IT, platform development? • Which consultants? • Project management approach? • Integration with other systems? • Content of MOU? • Content of joint case for funding?

Work groups continue meeting. Formation of Synergy: • Brainstorming meeting to determine name. Progress reports at Synergy meetings. New Orleans learning trip. Developmental evaluators interviews of CEOs, staff and consultants; reveals: • Increasing consensus on hopes and concerns; • Some worries about power imbalances; • Frustration with capacity gap; • Frustration with pace of progress. Discussions among evaluators, consultants, and MBDA CEO regarding how best to help the collaboration make progress.

Technology and Intake group choose vendor to design and build IT platform; groups plays interactive role in design of platform. Decisions made to integrate Synergy IT platform with some existing platforms. Marketing study completed. Synergy MOU outlines details of approach to collaborative governance. Case for joint funding progress.

Court of public opinion increasingly favors collaboration and ecosystem change. MBDA guiding principles identify norms to guide direction of work and how to work together. Guiding principles included in MOU and case for joint funding.

Advances change in interpretive schemes in favour of deeper collaboration and ecosystem change. Progress made on tangible products, for example, IT platform, new financial instruments, Synergy branding. Struggles of some partners to participate fully are clarified. Formalisation of collaborative governance arrangements.

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Stage and design focus

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Provan, K.G. and Kenis, P. (2008) Modes of network governance: structure, management, and effectiveness, Journal of Public Administration Research and Theory, 18(2): 229–​52. doi: 10.1093/​jopart/​mum015 Romme, A.G.L. (2003) Making a difference: organisation as design, Organization Science, 14(5): 558–​73. doi: 10.1287/​orsc.14.5.558.16769 Romzek, B., LeRoux, K., Johnston, J., Kempf, R.J., and Piatak, J.S. (2013) Informal accountability in multisector service delivery collaborations, Journal of Public Administration Research and Theory, 24(4): 813–​42. doi: 10.1093/​jopart/​mut027 Schutz, A. (1967) The phenomenology of the social world, Evanston, IL: Northwestern University Press. Senge, P.M. (2006) The fifth discipline: The art and of practice of the learning organization, New York: Doubleday. Simon, H.A. (1996) Sciences of the artificial, Cambridge, MA: MIT Press. Stone, M.M. and Sandfort, J. (2009) Building a policy fields framework to inform research on nonprofit organisations, Nonprofit and Voluntary Sector Quarterly, 38(6): 1054–​75. doi: 10.1177/​0899764008327198 Thomson, A.M. and Perry, J.L. (2006) Collaboration processes: inside the black box, Public Administration Review, 66: 20–​32. doi: 10.1111/​ j.1540-​6210.2006.00663.x Van Aken, J.E. and Romme, A.G.L. (2012) A design science approach to evidence-​based management, In D. Rousseau (ed) The Oxford handbook of evidence-​based management, Oxford: Oxford University Press, pp 43–​57. Van Aken, J.E., Berends, H. and van der Bij, H. (2007) Problem solving in organizations, Cambridge: Cambridge University Press. Yin, R.K. (2017) Case study research and applications: Design and methods, Thousand Oaks, CA: Sage.

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Policy-​making as designing: taking stock and looking forward Arwin van Buuren, Jenny M. Lewis and B. Guy Peters

Introduction Policy-​making is in essence a matter of design. It is essentially about creating or constructing a means (for example, a plan, set of rules, instruments, interventions) for a certain end (to manage or to solve a societal problem). However, as this volume shows, we can witness an interesting shift in the logic or kind of design that is applied in policy processes. The traditional, more rational deductive, or ‘closed’, design approach is complemented with a more designerly way of policy-​making, based upon the principles of modern design sciences and design thinking. Public sector organisations all over the world are experimenting with more open and creative ways of formulating policies and public services in order to do justice to the complexities of today’s societal challenges. In this volume, this new approach to how policies are designed is described and illustrated. This proliferation in ways of designing policies within the public domain raises interesting questions, which have been explored throughout this volume. In this final chapter we reflect upon the application of more designerly, and thus creative or playful, ways of making policy, the ‘second face of public sector design’ (Clarke and Craft, 2019), how they relate to the more traditional forms of design, and what their pitfalls and promises are. Moreover, we reflect upon the consequences of this transition for the way in which public organisations should be designed and managed. In this chapter, we first sketch the potentials of designerly ways of making policies, as well as their pitfalls. We then reflect upon the relation between ‘old’ and ‘new’ approaches of policy design and the evolution we can witness. It seems that traditional and more recent approaches are combined or blended together in many ways. The interesting question then is which conjecture, or tentative theory, does traditional policy-​making really face in relation to more designerly approaches? Inspired by Klijn and Skelcher (2007), we distinguish between four conjectures that place traditional and more designerly ways of policy design in relation to each other and reflect upon the conjecture which reflects the current situation most accurately. Based upon that analysis, we formulate some perspectives on how to proceed, both 218

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in practice and in theory. What are the interesting questions we should try to answer? We conclude with some final reflections, also about the potential for using design as a research approach in the field of the policy sciences.

Potentials and promises From the chapters in this volume, as well as the increasing numbers of experiments applying design in the context of public policy-​making, we can deduce several insights about the added value of the approach and the various promises a more designerly way of policy-​making brings with it. We summarise these potentials in five main clusters (Table 10.1). The different characteristics of designerly approaches enable policy-​makers to deal with the complexity and multifaceted character of societal issues. It helps them to include the perspectives of citizens and stakeholders and to

Table 10.1: The potentials of designerly approaches for policy-​making 1. Human-​centredness Design departs from the lived, experienced world of the persons who form the target group as well as the context they live in. Designers want to empathise, they try to see the world through other people’s eyes, to come up with a deep understanding of the problems and realities of the people they are designing for. 2. Reframing

Traditional designing may take the frame of a policy as a given, whereas the designerly approach will explore the problem space in depth, question assumptions, and consider reframing the problem, perhaps as a means of addressing fundamental differences among participants (Schön and Rein, 1994).

3. User-​orientation and co-​creation

A designerly approach tends to involve stakeholders and (end-​) users in the process to a much greater extent than do traditional approaches. This tends to produce designs that are more compatible with the thinking of the final ‘consumers’ of the design.

4. Creativity and anticipation

Traditional policy design may be somewhat backward-​looking, attempting to utilise established modes of thinking about the policy domain. Designerly approaches use more explicitly methods to foster creativity, and are more forward-​thinking about policy options.

5. Integration and wholeness

A designerly approach tends to involve greater cogitation among the participants in the process, and an openness to a wide range of views. Furthermore, design tends to use a holistic, more systemic approach in understanding an issue and its context together, as well as when it comes to designing solutions.

6. Experimentation and prototyping

Policy-​making is to some extent inherently experimental (Kimbell and Bailey, 2017), but designerly approaches to design may be more explicit about the experimental nature of the process, and the possibilities of trial-​and-​error (rapid prototyping) in the process of developing a new intervention, tool or approach.

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do justice to the various perspectives and values regarding these issues. It also gives room to allow for uncertainty and to focus on outcomes instead of decisions (Christiansen and Bunt, 2012). Applying design approaches helps to adopt a view that is open to learning and in which complexity is acknowledged instead of neglected (as is often the case in the public sphere; Mintrom and Luetjens, 2016; Bason and Austin, 2022; Blomkamp 2022). It helps to bring together different sources and types of knowledge and expertise, to think ‘out-​of-​the-​box’ and to empathise with the issue and the values connected to it. Design can help to open up policy processes for wider (public) participation (Seravalli et al, 2017). At the same time, it is far too simple to see designerly approaches as a panacea for the challenges today’s societal issues pose for policy-​makers. Just simply applying the tools and approaches designers use can help to overcome some of the limitations traditional policy design approaches have, but at the same time these limitations are often deeply ingrained in the structure of public sector organisations and the legal, administrative context in which they function. We will reflect upon this in what follows.

Pitfalls and problems While there are thus many promises, there are also serious problems that come with a more designerly way of policy-​making. We will focus upon three important issues. First of all, there is an important challenge when it comes to applying design within the context of public bureaucracies: is this context ‘ready for design’ and also ready for the solutions it generates? Second, there is a quite problematic relationship between designerly approaches and politics, as design asks for open, creative explorations, while politics expect policy-​makers to solve predefined problems within predefined boundaries. Third, applying designerly ways of policy-​making within the context of the rule of law brings serious limitations with it. First of all, applying more designerly approaches in policy-​making does have profound consequences for how public sector organisations are organised (Bason and Austin, 2022). Vaz-Canosa (2021) speaks about the many Trojan horses design brings with it. Designers sometimes assume that institutions, organisations and policy designs can be cleanly and clearly separated, but in reality attempting to alter one element in a design will involve challenges to all elements (Fontaine and Peters, 2022). In other words, applying designerly ways of policy-​making puts high demands on the institutional context of policy-​making, while their results often do the same: they presuppose that this context is able to accommodate the implementation of (holistic, human-​ centred) designs, which is often at odds which how this context is organised. Clarke and Craft (2019) described several shortcomings that arise from the application of design thinking in policy processes. An important element 220

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of what they state is the fact that design thinking is difficult to align with a political context in which existing structures and path-​dependencies tend to pre-​structure a problem beforehand, as well as to limit the solution space. Politicians often want to sell their favourite solutions and to realise predefined targets in the most efficient way, instead of engaging in time-​ consuming, goal-​seeking processes of problem framing and empathising. Moreover, designers and design organisations have to win an unfair struggle, because they have to survive in a context that favours rational, technical expertise and scientific evidence above creativity and imagination (Chapter 6, this volume). We have to rethink the relationship between policy and politics when we really want to make the shift from traditional policy-​making –​within the predefined margins and mandates of politics –​towards more innovative policy design which inherently is unpredictable, creative and open-​ended. That rethinking must be both in terms of its input (the perceived problem), its course of events and its participants as well as its results. This has serious consequences for the way in which the administrative and political system operates and how that relates to processes of policy-​making. For example, the current hierarchical way of goal-​setting and the focus on accountability based upon predefined performance indicators is at odds with designerly approaches. Moreover, we have to take into account the politics within existing bureaucracies and the power dependencies that play a role in preventing change. Many governments are experimenting with designerly approaches to policy-​making and service delivery and are developing design labs or centres to introduce design methods and tools within their own context. One of the most surprising observations with regard to this trend has to do with the fact that very little attention is paid to the peculiarities of that context. Within a public context other conditions play a role compared to a private, market-​oriented context. Politics, but also legal principles, the need for accountability and the hierarchy of public bureaucracies, not only set specific conditions on processes of co-​creation and co-​design but also limit the room for creativity. Media scrutiny of public contexts makes risk-​taking more potentially (politically) dangerous. This also makes a more experimental approach to policy-​making and service formulation difficult. In other words, the design space in a public context has its own unique boundaries which are often more restrictive compared to a private context in which design thinking is commonly used to develop products and services. For example, the rule of law poses limitations on the exploratory, goal-​searching and creative habits of designers. That means, among other things, that the room for prototyping with policy instruments is seriously limited as it raises all kinds of ethical and legal concerns about equity, legality and equality. 221

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Reflecting upon what a public context implies for applying design-​ oriented methods and how these methods can become allied with the more rational, closed and analytical design tradition in the field are important challenges to be tackled in the future.

How old and new design approaches relate to each other What can we say about the relation between more traditional forms of designing public policy and the recent, more designerly ways described in this volume? A similar question was answered by Klijn and Skelcher (2007) in an examination of the relationship between representative democracy and governance networks. In their article, the authors presented four different conjectures as hypotheses about the relationship between the traditional representative system of party politics and parliamentary democracy and the upcoming system of arenas, networks and deliberative or participatory democracy. In their words: We present the relationship between representative democracy and governance network as ‘conjectures’. Conjectures are tentative theories designed to offer provisional solutions to problems. The value of a conjecture is to generate fresh thinking, investigation and insight. They are more akin to informed speculations that provide a framework from which more detailed empirical and theoretical research questions can be established, and investigations undertaken. The conjectures are heuristic tools to structure the discussion about the relation between governance networks and representational democracy. They organise the literature on this topic and can be used to highlight particular themes or tensions that impact on theory or practice. In this way, the conjectures can be used to develop propositions for empirical research. (Klijn and Skelcher, 2007, p 589) We use the four conjectures Klijn and Skelcher presented in their article to sketch the potential relation between the classical, more rational approach to policy-​making and the recent, more creative approach to policy-​making. Table 10.2 summarises the four conjectures. In this volume, several contributors have pointed to some answers in relation to these conjectures. Lewis et al, for example, examined the incompatibility of the conceptual bases underpinning traditional, participatory and design thinking approaches to policy-​making. However, they also argued that these two approaches can be complementary, with traditional approaches demonstrating a greater grasp of political institutions and the politics of policy-​making than designerly approaches. Olejniczak et al stress the same point: ‘To conclude, policy labs are not an alternative development to 222

Policy-making as designing Table 10.2: Conjectures between modes of design in policy-​making Conjecture Incompatible

Traditional and designerly approaches to policy-​making are based on completely different paradigms and are thus not compatible.

Complementary

Traditional and designerly approaches to policy-​making are applicable in different circumstances and each has its own merits.

Instrumental

Designerly approaches are strategically used in some cases to help ‘the traditional system’ to survive.

Transitional

Gradually, designerly approaches will become more popular, will set the new normal and take over from traditional approaches.

established practices of public policy. They are rather a promising addition that, when combined with existing evaluation practices, can allow both entities to mutually benefit one another and create synergies to improve the craft of public policy’ (Chapter 5, this volume). The complementarity thesis is even more plausible when we consider differences among policy domains, and the specifics of policy problems. For well-​structured problems, and problems with clearly defined methodologies for solutions (Dunn, 2017), the more traditional form of design may work well. The designerly approach, on the other hand, is more appropriate for ill-​structured problems that may benefit from consideration of a wider-​range of alternative policies, as well as a wider range of conceptualisations of the problem itself. At the same time, and from a more critical perspective, there is also reason to suppose a more instrumental stance. The contribution of Lewis et al highlights the tensions designerly approaches encounter when applied in an essentially political context. Such approaches focus on creativity, on imagination and on innovation and abduction, and are often organised at a distance from the ‘regime’. This distance at the same time hinders the uptake of what is designed and often limits its impact significantly. The same problem is witnessed by Olejniczak et al in their analysis of policy labs. That points also in the direction of a more instrumental conjecture between traditional and new ways of policy design. More novel design approaches are experimented with at a safe distance from the ‘regime’ (in a policy lab or another pilot environment) so as to leave the existing mode of operation untouched. This more instrumental stance limits the impact of more designerly ways of working significantly: by keeping this way of working at a distance, it is also quite easy to prevent them from making a more systemic impact on current ways of policy-​making (McGann et al, 2018). This point resembles the observation that Villa Alvarez et al (2022) made. They point to the fact that design approaches are much more often applied 223

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in the phases of policy implementation, rather than in the early phases of the policy process. This can also be seen as evidence for the instrumental conjecture: the principal departing points of policy-​making remain the same, and more designerly ways of working are mainly used to translate policies into action instead of defining (the departing points of) policies. For now, most evidence seems to be available to support the complementary conjecture, with the critical side note that there is a legitimate fear that new design approaches are used instrumentally. We see both logics of design applied simultaneously, often in hybrid combinations and sometimes with fluid transitions. The majority of the contributions to this volume support this thesis. This also fits well with the literature on institutional layering, hybridity, bricolage and other similar terms that are used in examinations of how policy changes (Mahoney and Thelen, 2009). It is very rare for existing approaches to completely disappear, they are far more likely to be slowly changed by recombinations of even quite incompatible approaches. The interesting question then is how this hybrid configurations function and under which conditions fruitful combinations between both approaches can emerge.

Perspectives and proceedings Based upon the overview of potentials and pitfalls, we are now able to think about how to proceed in applying and studying designerly ways of policy-​making. The limitations and problems sketched make the application of designerly approaches difficult, but they certainly do not prohibit it completely. Based upon the contributions to this volume there are at least two important directions for further exploration and research. First of all, there is a need for exploring the increasing hybridity in modes of policy design and the question of how to organise this hybridity effectively. Second, it is important to explore how the capability of public sector organisations to apply and accommodate designerly approaches of policy-​making, and to adopt its outcomes, can be enhanced. Organising hybridity Regarding the first direction, the current wave of more designerly ways of policy-​making results in all kinds of hybrid practices in which these new approaches are combined. This can be seen as an attempt to combine the best of both worlds. At the same time, hybridity comes with its own problems. It is always about combining conflicting value systems, practices and competences. From the literature we know various ways of working with hybridity. Skelcher and Smith (2015) distinguish five types of hybrids: the segmented, 224

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the segregated, the assimilated, the blended and the blocked hybrid (which leads to organisational dysfunction because the competing logics cannot be combined). For the purpose of this chapter it is especially interesting to delve into the blended type because in this type elements of existing logics become synergistically incorporated into new and contextually specific logics. Various chapters in this volume provide insight on how to come to such a blended style of policy design. Howlett (Chapter 3) stresses the importance of designerly approaches learning from more traditional approaches and incorporating the lessons learned within the traditional policy design studies. These lessons have to do with informing the design process with considerations of administrative and political feasibility, the limited degrees of freedom there are for policy choices, the importance of considering the ‘goodness of fit’ between design and context, and the many issues that come into play when policies have to be implemented. According to Howlett, the designerly approaches of policy design can become much more impactful when they take stock of the many lessons developed over the past decades in which more informational forms of policy design have come to maturity. The same point is made by Romme and Meijer (Chapter 8) when they make the case for integrating traditional validation-​oriented research with intervention-​oriented design approaches. They see such an inclusive methodology as a way to combine rigorous theoretical understanding of policies and the development of interventions to tackle problems or improve administrative practices. Iterative cycles of creating, assessing, theorising and justifying activities can help to develop interventions at the same time as coming up with new theoretical understandings. This resonates with the observation by Olejniczak et al, who argue that more traditional forms of policy evaluation and more innovative forms of policy labs can improve the design and implementation of public policies and programmes. The motto, then, is bringing together the best of both worlds. Although that sounds quite obvious, the question of how to do so is much more difficult and ultimately asks for new forms of ambidexterity in which traditional ways of doing (focused upon optimisation and exploitation) are combined with inventing and exploring new ways of doing. From previous research we know that organising ambidexterity is a complex challenge, especially when it comes to the role of leadership and management in public sector organisations (Gieske et al, 2020). At the same time, the rich literature on ambidexterity also offers many insights in how to organise ambidexterity in time (sequential), in organisational structures, in teams, processes and persons. Accommodating design Strengthening the design readiness of public sector organisations is the second and more fundamental issue we want to put on the agenda. The design 225

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readiness has at least two appearances. First of all, it is about the ability to apply and to accommodate designerly approaches of policy-​making. This has to do with the competencies and mindsets of involved actors, the institutional rules of the game and the incentives that are in place. Designers themselves play an important role in fostering design practice to realise organisational change (Kim et al, 2022), by, for example, showcasing its added value via best practices and by familiarising others with the principles and practices of design. That task will not be easy, given the tendency of these organisations to fall back into their familiar ways of thinking about policy, but neither is it impossible. The case studies contained in this volume point to some successes in changing attitudes and behaviours, but also the institutional context. With regard to the latter, Chapter 4 of this volume by Waardenburg et al is of particular interest. They delve into the question of how to organise a design environment in which more designerly approaches of policy-​making can flourish. They underline the importance of space and time for experimentation, the role of external facilitation, the importance of involving the superiors of collaborators in periodic progress review discussions and the inclusion of future collaborators in the phases of problem selection and definition. But design readiness also has to do with the ability of public sector organisations to adopt the outcomes of designerly processes, their absorptive capacity. From the various chapters within this volume we can conclude that it is important to avoid the pilot paradox (Van Buuren et al, 2018): when the distance between the space of innovation and the context of application becomes too large, the adoption of its results becomes more difficult. Such a distance can be beneficial, in order to create room for experimentation and to go beyond the limiting conditions within public sector organisations, but this distance also hinders the uptake of results. Applying designerly ways of working thus has to be embedded within the core of public organisations, although they need protection and backing to flourish.

Conclusions Following Herbert Simon, the public administration discipline has been repeatedly labelled as a design science, but it has often failed to live up to that promise. Until now, the same holds true for the more designerly ways of policy-​making in public sector organisations. Although there is growing attention for this new kid on the block, both in practice and in academia, the results are so far not very impressive. We still see a lot of reluctance among civil servants and politicians to apply it and it also sits uncomfortably in the institutional context of administrations. As a consequence, design is often conducted at a distance from the primary processes and often applied from an instrumental logic where the new ways of policy design are used 226

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to complement old ones. The resulting hybridity poses new questions in terms of organising ambidexterity and redesigning the institutional context of public organisations in order to enhance their design literacy and readiness. In this volume there was less attention for the role of design as a research approach. From an academic point of view, applying designerly ways of formulating policies is a promising route. If done systematically we can think of a policy design as a hypothesis and about policy-​making as a kind of prototyping (Kimbell and Bailey, 2017). Clear assumptions about the nature of the problem and the possibilities of interventions can be tested through implementation. Evidence-​based policy-​making, as an ancillary to design ab initio, provides sources of previously tested modes of intervention. The important question here is to what extent the rise of current design thinking approaches in the field can contribute to the potency of public administration and public policy as scientific disciplines that combine both analytical rigour and societal relevance. Doing design-​based research is, for policy scientists, maybe not directly part of their comfort zone. It asks them to do their research as an action-​ oriented designer. By creating, testing and refining designs, they can get a deeper understanding of policy problems, the context in which they are located, the needs that actors identify, and the impact of certain solutions. The latter asks also for more advanced experimental methods and ways to systematically analyse how solutions work out in practice, and which dynamics they cause. It also asks for a more systematic approach to applying design elements in more classical ways of doing research. This is a challenging endeavour because of the focus of design on abductive reasoning instead of induction or deduction, and the role it gives to intuition, creativity and imagination. Bringing these worlds together, and giving both of them the place they deserve, requires methodological innovation beyond existing methods of action research and design experiments. There seems to be a long way to go before a more ‘design-​inspired’ way of doing research in public administration will be settled as a normal way of doing rigorous research in a societally relevant way. However the various contributions in this volume show that it is a promising next step in thinking about public administration as a design science. This also presupposes that there are opportunities to find new combinations of the traditional ways of doing design (the informational approach, in the tradition of Simon) along with ways of doing design from a more inspirational stance. This volume also makes clear that there are many unanswered questions about the peculiarities of design remaining. We already mentioned the problematic relation between design and politics. But we could also mention the politics of design: who are the actors that benefit from design and who are the actors that are disadvantaged? And how does that help or obstruct the design of legitimate policy and/​or public services? To what extent is 227

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design a way to come to collaborative decision-​making? Is it used as a way to depoliticise sensitive issues in a way that ignores the values at stake? There is also the question of what type of context the application of a design approach is helpful for and in what contexts it is less effective? To what extent are successful (in a particular context) methods of design transferable to other contexts and policy levels? Moreover, how can we more rigorously assess design efforts and their effectiveness relative to other approaches of problem solving? Ultimately, this volume asks for a more thorough understanding of the (potentially) negative impact of design. As Vaz and Ferreira (2021) argue, the application of designerly ways of policy-​making can easily contribute to the reinforcement of existing power relations and the encroachment of market logics into government. The latter point is also made by Kimbell and Bailey (2017). When design is only used as an instrumental device to run government like a business, in which citizens are reduced to customers, and public goods and services to products for users, applying it easily results in less legitimacy and public value instead of more. To realise the promises of design, an open eye for its pitfalls is essential. Acknowledgements We are very grateful to Geert Brinkman for his critical and helpful feedback on an earlier version of this chapter.

References Bason, C. and Austin, R.D. (2022) Design in the public sector: Toward a human centred model of public governance, Public Management Review, 24(11), 1727–​1757. Blomkamp, E. (2022) Systemic design practice for participatory policymaking, Policy Design and Practice, 5(1), 12–​31. Christiansen, J. and Bunt, L. (2012) Innovation in policy: Allowing for creativity. In C. Bason (ed), Design for policy. London: Routledge. Clarke, A. and Craft, J. (2019) The twin faces of public sector design, Governance, 32(1), 5–​21. Dunn, W.N. (2017) Public policy analysis: An integrated approach. London: Routledge. Fontaine, G. and Peters, B.G. (2022) Introduction. In B.G. Peters and G. Fontaine (eds), Research handbook on policy design. Cheltenham: Edward Elgar, pp 1–38. Gieske, H., Duijn, M. and Van Buuren, A. (2020) Ambidextrous practices in public service organisations: Innovation and optimisation tensions in Dutch water authorities, Public Management Review, 22(3), 341–​363.

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Kim, A., van der Bijl Brouwer, M., Mulder, I. and Lloyd, P. (2022) A study on strategic activities to foster design practices in a local government organisation. In D. Lockton, S. Lenzi, P. Hekkert, A. Oak, J. Sádaba and P. Lloyd (eds), DRS2022: Bilbao, 25 June–​3 July, Bilbao, Spain. https://​ doi.org/​10.21606/​drs.2022.528 Kimbell, L. and Bailey, J. (2017) Prototyping and the new spirit of policy-​ making, CoDesign, 13(3), 214–​226. Klijn, E.H. and Skelcher, C. (2007) Democracy and governance networks: Compatible or not?, Public Administration, 85(3), 587–​608. Mahoney, J. and Thelen, K. (eds) (2009) Explaining institutional change: Ambiguity, agency, and power. Cambridge: Cambridge University Press. McGann, M., Blomkamp, E. and Lewis, J.M. (2018) The rise of public sector innovation labs: Experiments in design thinking for policy, Policy Sciences, 51(3), 249–​267. Mintrom, M. and Luetjens, J. (2016) Design thinking in policymaking processes: Opportunities and challenges, Australian Journal of Public Administration, 75(3), 391–​402. Schön, D. and Rein, M. (1994) Frame reflection: Toward the resolution of intractable policy controversies. New York: Basic Books. Seravalli, A., Agger Eriksen, M. and Hillgren, P.-​A. (2017) Co-​design in co-​ production processes: Jointly articulating and appropriating infrastructuring and commoning with civil servants, CoDesign, 13(3), 187–​201. Skelcher, C. and Smith, S.R. (2015) Theorising hybridity: Institutional logics, complex organisations, and actor identities – The case of nonprofits, Public Administration, 93(2), 433–​448. Van Buuren, A., Vreugdenhil, H., Van Popering-​Verkerk, J., Ellen, G.J., van Leeuwen, C. and Breman, B. (2018) The pilot paradox: Exploring tensions between internal and external success factors in Dutch climate adaptation projects. In B. Turnheim, P. Kivimaa and F. Berkhout (eds), Innovating climate governance: Moving beyond experiments. Cambridge: Cambridge University Press, pp 145–​165. Vaz, F. and Ferreira, M. (2021) Assessing design approaches’ political role in the public sector, Journal of Design Research, 19(4–​6), 197–​212. Vaz-​Canosa, F. (2021) Policy innovation by design: Understanding the role of design in the development of innovative public policies. PhD thesis, Loughborough University. https://​doi.org/​10.26174/​the​sis.lboro.14339​ 249.v1 Villa Alvarez, D.P., Auricchio, V. and Mortati, M. (2022) Mapping design activities and methods of public sector innovation units through the policy cycle model, Policy Sciences, 55(1), 89–​136.

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Index References to figures and tables appear in italic type.

A abductive reasoning  20, 75–​76, 128, 130 Abrams, H.C.  30 access rules  194–​195, 200, 204, 205, 207, 208 accountability  92–​93, 138–​141 action research  77, 184 actors  see participants/​stakeholders Adaman, F.  27 adaptability  155 agendas, in arenas  201, 204–​205, 208 algorithms  4 Alkin, M.C.  101 ambiguity  155 ambitions dilemma  165–​166 analysis, in policy labs  112, 113, 114, 116 Anderson, G.L.  80 Ansell, C.  76, 93, 197 arenas  195, 197 Synergy collaboration  201, 204–​205, 207–​208 argumentation  194, 200, 203, 207 artificial sciences  19 see also design science assessing, in PPA research  174, 177–​178, 180–​181, 182 Australia, PSI labs in  135–​141

B Babovic, V.  28, 29 Bailey, J.  77 Balogh, S.  197 barriers/​constraints  59–​60, 158–​161 Bason, C.  73, 134 behavioural change  102–​103, 116 behavioural insights  114, 116 behavioural PA  3 Bekkers, Victor  18 black box approach  103 Blomkamp, Emma  125 Booher, D.E.  198 Borkowska-​Waszak, Sylwia  98 bottom-​up approach  91, 126, 130 Brown, T.  21 Bryson, John M.  75, 76, 191, 196–​197 see also Crosby–​Bryson framework of power Buchanan, R.  138

bureaucracies  133, 151–​152, 157, 158–​159, 160–​161, 221 Buuren, Arwin van  1, 18, 218 Buurman, J.  28, 29

C causality  102, 115 change-​oriented design  34 Clarke, A.  131, 144, 220–​221 climate policy  28–​29 Cloutier, G.  28–​29, 32 co-​creation, design as  9, 11–​12, 13 co-​design  5–​6, 9, 56–​57, 130, 144 see also collaboration; participation coaching  see Organised Crime Field Lab coherence  59 collaboration  conditions facilitating  90–​11 in contemporary design  5–​6, 154–​155 and Crosby–​Bryson framework  193 and decision-​making paradox  162 in design thinking  126 in policy labs  109–​110, 113–​114, 119, 134 see also participation; partnerships collaborative governance  concept of  191, 209 Crosby–​Bryson framework  196 Synergy example  198–​209 design approach  74–​75, 192–​193, 209–​210 design environment  72–​74, 76–​77, 93–​94 facilitative conditions  86–​93 OCFL evolution  81–​86, 87–​88 research approach  77–​81 design processes  75–​76 DS research framework  176–​183, 184 literature review  196–​198 collaborative platforms  197 communicative capability  194, 200, 202–​203, 206 complementarity of approaches  61–​62, 145, 222–​223, 224 see also public policy and administration research configurationist perspective  102 conflict management  195–​196, 208 congruence  59 consensus-​driven design  33

230

Index consent-​based policy-​making  180–​183 consistency  59 context  for design approach  60, 228 and design environment  94 and evaluation  115 and implementation  21, 30, 31 institutional field  162, 167 political  30, 54, 55, 111, 133, 143–​144, 158–​159, 221 public sector  7–​8, 109, 133, 138–​141, 220–​221, 225–​226 Cook, B.J.  28, 29 courts  195–​196, 197, 198 Synergy collaboration  201, 205, 208 Craft, J.  131, 144, 220–​221 creating  in policy labs  112, 113, 114, 116 in PPA research  174, 177, 178, 180, 181–​182 creativity  5, 9, 129–​130, 131–​132, 172, 221 and design dilemmas  161, 163, 164–​165 see also innovation crime-​fighting collaborations  73, 84 facilitative conditions  86–​93 OCFL evolution  81–​86, 87–​88 research approach  77–​81 critical approaches  130 Crosby, Barbara  191 Crosby–​Bryson framework of power  193–​196 applied  see Synergy collaboration Crow, M.M.  19, 74

D data (open)  177–​179 De Jong, Jorrit  72 decision-​making capabilities  195, 201, 204 decision-​making paradox  162 design  compared with science  20 conceptualisations  20–​22, 174, 192 institutional barriers to  158–​161 politics of  227–​228 design applications  and design readiness  225–​226 literature review  research strategy  22–​24 results  25–​32 typology  32–​34 design approaches  accommodating in public sector  225–​226 collaborative governance context  74–​75, 192–​193, 209–​210 see also Crosby–​Bryson framework of power combined and complementary  61–​62, 145, 172, 222–​223, 225

see also public policy and administration research compared with problem-​solving  192 in design institutions  156–​157 further research  35, 224–​226 hybridity in  224–​225 informational  8, 21, 26–​27, 28, 29, 30, 32–​33, 34 inspirational  8, 21, 26, 27, 28–​30, 32, 33–​34 new/​designerly  1–​2, 5–​8, 154–​156 compared with traditional  128–​132, 141–​143, 152–​154 pitfalls and problems  220–​222 potentials and promises  219–​220 relation to traditional  61–​62, 222–​224 see also design thinking old/​traditional  1, 3–​4, 6, 52, 53–​54, 172 compared with new  128–​132, 141–​143, 152–​154 relation to new  61–​62, 222–​124 see also informational approach; validation-​oriented PPA research over-​design  156 in PPA research  see public policy and administration research promise/​contribution of  12–​13, 18, 35–​36, 219–​220, 227 in public administration  3–​4, 5–​10, 32–​34, 153 in public policy  4–​10, 52, 53–​62 typologies  8–​10, 32–​34 design as co-​creation and dialogue approach  9, 11–​12, 13 design environment  76, 226 of collaborative governance  72–​74, 76–​77, 93–​94 facilitative conditions  86–​93 OCFL evolution  81–​86, 87–​88 research approach  77–​81 see also institutional field design experiments  172 design as exploration approach  8–​9, 11, 12–​13 ‘design-​for-​policy’  5–​6 ‘design-​for-​policy’ entrepreneurs  127, 132–​135 design institutions  151 barriers to design  158–​161 and design approaches  156–​157 difficulties of  166 dilemmas in designing  161–​166 see also policy/​PSI labs design of policy  6 design as optimisation approach  8, 10–​11, 12 design-​oriented (prospective) PPA research  171–​172, 173 DS framework  174–​176, 183–​186 research examples  176–​183, 184–​185

231

Policy-​Making as Designing design processes  for collaborative governance  75–​76 see also iterative processes design readiness  225–​226 design science (DS)  growth of  171–​172 public administration as  1, 3–​4, 19, 74 public policy as  4–​5 research framework  174–​176, 183–​186 research examples  176–​183, 184–​185 design thinking  compared with other approaches  54–​62, 128–​132, 141–​143 concept of  52, 125 contribution of  227 impact of PSI labs and  135–​141, 143–​144 impacts on policy-​making  126–​127, 144–​145 levels of operation  136–​138, 139 problems of applying  220–​121 PSI labs as example of  132–​135 rejection of non-​design processes  53–​54 rise of  19, 125–​126 discursive approaches  130 domain, in arenas  201, 204 Domaradzka-​Widła, Anna  98 double diamond model  7 DS  see design science

forums  194–​195, 197, 198 Synergy collaboration  200, 202–​204, 206–​207 frameworks  90

G Gash, A.  197, 209 generativist perspective  102 Giddens, A.  193 governance context  60 see also collaborative governance government  relationship with policy labs  109, 138–​141 see also political context Gray, B.  197 Groenleer, Martijn  72

H Habermas, J.  130 Hajkowicz, S.  29 Hartley, J.  134–​135 Hermus, Margot  18 Herr, K.  80 hierarchical organisations  164 Hillgren, P.A.  76, 90 Howlett, Michael  51, 74, 91, 225 hybridity  224–​225

I

E Emerson, K.  191, 197 emotion  130–​131 entrepreneurs  see ‘design-​for-​policy’ entrepreneurs; innovation entrepreneurs environment  see design environment EU Policy Lab  104 evaluation practice  98–​99 challenges  101–​104, 115–​117 nature of  100–​101 and policy labs  115–​117, 118–​119 evidence-​based policies  12, 129 evidence-​driven design  33 experimental approach  3–​4, 134 experimentation, conditions for  see design environment experiments  172 expertise  56–​57 exploration  design as  8–​9, 11, 12–​13 in policy labs  112, 113, 114, 116 external dilemma  161–​162 external validity  80–​81

F feasibility  59–​60 feedback  89–​90, 111, 161, 201 Ferreira, M.  228 flexibility  155

ideation space  21, 27–​30 implementation  barriers to  59–​60 and inspirational approach  21–​22 implementation space  21, 30–​32 inclusion  see participation incremental design  165–​166 industrial design  125–​126 information processes  177–​179 information windows  179 informational approach  8, 21, 26–​17, 28, 29, 30, 32–​33, 34 infrastructuring  76, 90 Innes, J.E.  198 innovation  conditions for  see design environment design approaches to  55–​56 increased focus on  7–​8, 125 institutional barriers to  158–​159 and institutional design dilemmas 161–​162, 163, 165–​166 and institutions  157 in public sector context  7–​8, 125 public sector innovation labs  see policy/​PSI labs innovation cycle  138, 140 innovation entrepreneurs  179 insider–​outsider research  184–​185 inspiration space  21, 25–​27

232

Index inspirational approach  8, 21, 26, 27, 28–​30, 32, 33–​4 institutional field  162, 167 institutionalisation dilemma  164–​165 institutions  see design institutions instrumental relations between approaches  223–​224 interactive arena  76, 93 internal dilemma  163 internal validity  80 interpretive schemes  194, 200, 203, 206 Iskander, N.  126 iterative processes  75–​76, 89–​90, 94, 112, 128, 130, 175, 176 research examples  176–​183, 184

J justifying, in PPA research  175, 178, 179, 182–​183

K Kellie, J.  31 Kenis, P.  197 Klauer, B.  30 Klijn, E.H.  222

L Lasswell, Harold  4 laws  196, 221 leadership  210 learning  104 conditions for  see design environment see also exploration Lewis, Jenny M.  1, 125, 218, 222, 223 literature review  research strategy  22–​24 results  25–​32 typology  32–​34 Lloyd, P.  77 Luetjens, J.  73, 75 Lukes, S.  193

M managerialism  160–​161 March, S.T.  174, 175 market structures  163–​164 McGann, Michael  125 Meijer, Albert  171, 225 methods/​tools, used by policy labs 113–​114, 134, 136, 137 Minnesota  see minority-​owned business support Minority Business Development Association (MBDA)  199–​205, 206, 207, 208 minority-​owned business support 198–​199, 211 Synergy example  198, 209–​210 pre-​collaboration phase  199–​201, 212

intermediate collaboration phase 201–​205, 213 later collaboration phase  205–​209, 214 Mintrom, M.  73, 75

N Nabatchi, T.  191, 197 NESTA  104 Netherlands  PPA research examples  176–​183, 184–​185 see also crime-​fighting collaborations networks  164 New Public Governance  176–​177 New Public Management (NPM)  6, 160 New Zealand, PSI labs in  135–​141 norms of pragmatic communication  194, 200, 203, 207

O OCFL  see Organised Crime Field Lab Olejniczak, Karol  98, 222–​223, 225 open data  177–​179 optimisation, design as  8, 10–​11, 12 organisational cultures  159, 201 organisational learning  104 organisational structure  163–​164 Organised Crime Field Lab (OCFL)  73–​74 collaboration examples  84 conditions facilitating collaboration  86–​93 data collection and analysis  79–​80 evolution of  81–​86, 87–​8 Ostrom, Vincent  3 over-​design  156

P Park, Yaerin  98 participants/​stakeholders  in bottom-​up approach  91, 126 in co-​design approach  9 collaborative governance examples  177–​183 designing links with  160 and evaluation  115 in informational and inspirational approaches  21–​22, 29–​32, 33–​34 in policy design  5–​6 in policy lab processes  113–​114, 134–​135, 143 participation  approaches to  56–​57 designing linkages  160 network structure for  164 participatory approach  5–​6, 9, 154–​155 of design thinking  126, 129, 130–​131, 144 of PSI labs  134–​135, 143

233

Policy-​Making as Designing partnerships  insider–​outsider research  184–​185 with policy labs  109–​110, 138–​141 see also collaboration Peters, B. Guy  1, 131, 151, 218 policy cycle  6, 128–​129 policy feasibility  59–​60 policy instruments  4, 57–​59, 153, 164–​165 policy labs  see policy/​PSI labs policy-​making  consent-​based  180–​183 context of  see context impact of design thinking on  126–​127, 144–​145 impact of PSI labs on  135–​141, 143–​144 institutions  see design institutions and PSI labs  132–​135 see also design approaches; public policy policy-​making process  6, 128–​129 policy/​PSI labs  8–​9 and challenges of evaluation  115–​117 contribution of evaluation practice to  118–​119 design environment of  77 as ‘design-​for-​policy’ entrepreneurs  127, 132–​135 further research on  117–​118 impacts  111, 135–​141, 143–​144 level of operation  109, 136–​138, 139 number and nature of  98, 109–​110, 127–​128, 132–​135 operations  110–​111 ownership/​accountability  109, 138–​141, 142 partnerships/​networks  109–​110, 138–​141 processes  111–​115 relationship to government  138–​141 research study findings  106–​115, 135–​141, 143 research study strategies  104–​106, 135–​136 tools/​methods  113–​114, 136, 137 political context  and design thinking  221 and implementation  30 of policy-​making  54, 55, 158–​159 of policy/​PSI labs  111, 133, 143–​144 see also government politics of design  227–​228 politics of evaluation  102 power  and policy-​making approaches  130, 131 in PPA research  185 and PSI labs  138–​141, 142 triple three-​dimensional view (Crosby–​Bryson framework)  193–​196 applied  see Synergy collaboration

PPA  see public policy and administration research pragmatic communication (norms of)  194, 200, 203, 207 principles, approaches to  57–​59 problem-​solving  89–​90, 128, 192 progress, in collaborations  92–​93 prospective approach  see design-​oriented PPA research prototyping  92 Provan, K.G.  197 PSI labs  see policy/​PSI labs public administration (PA)  concept of design in  20–​22 design applications review  research strategy  22–​24 results  25–​32 typology  32–​34 design approaches  3–​4, 5–​10, 32–​34, 153 as design science  1, 3–​4, 19, 74 and managerialism  160–​161 promise of design approaches in  12–​13, 18, 35–​36, 227 see also public policy and administration research public policy  concept of policy design  20, 51–​52, 152–​158 design approaches  4–​10, 52, 53–​54, 61–​62, 152–​156 traditional compared with design thinking  54–​62 as design science  4–​5 and evaluation  see evaluation practice institution influence on  151 ‘non-​design’ policy formulation  51, 52–​54 promise of design approaches in 12–​13, 227 use of research in  103–​104, 117 see also policy-​making; policy/​PSI labs public policy and administration (PPA) research  design and validation orientations  171–​173 diverse nature of  173–​174 DS framework  174–​176, 183–​186 research examples  176–​183, 184–​185 synthesis of design approaches  172 public sector context  design in  220–​221 design readiness  225–​226 innovation in  7–​8 and policy/​PSI labs  109, 133, 138–​141 public sector design ladder  138 public sector innovation (PSI) labs  see policy/​PSI labs Purdy, J.  197

234

Index

R racial inequality  198–​199 Radnor, Z.  27 rational approach  3, 6, 8, 172 see also informational approach; validation-​oriented PPA research rational choice theory  103 rational-​process models  128–​129 REACT process, in policy labs  112–​113, 114, 116 redefining, in policy labs  112, 113, 114 regimes  197 relevance, in forums  194, 200, 203 research  application of  103–​104, 117 see also public policy and administration research research strategy  for collaborative governance study  199 for design applications review  22–​24 for policy labs studies  104–​106, 135–​136 retrospective approach  see validation-​oriented PPA research Romme, A. Georges L.  171, 180–​183, 225 Romzek, B.  198 Ruijer, E.  177 rules  see access rules; laws

S sanctioning  195–​196, 208 Sanders, E.B.N.  21, 32 scaffolding  90 Scharpf, Fritz  162 Schneider, A.  134 Schott, S.  28 science  compared with design  20 see also design science Scott, D.R.  27 self-​reflectiveness  54–​55 Seo, Danbi  191 Shangraw, R.F.  19, 74 side effects  102 Simon, Herbert  1, 3, 4, 19, 74, 172, 173, 192 situated reasoning  130 Skelcher, C.  222, 224–​225 Smith, G.F.  174, 175 Smith, S.R.  224–​5 social actors  see participants/​stakeholders solution-​focused approach  20 Sørensen, E.  134–​135 stakeholders  see participants/​stakeholders strategic agility  155 ‘structural dilemma’  163–​164 structuration  193

substantive problem-​solving  89–​90 successionist perspective  102 Synergy collaboration  209–​210 background  198–​199 pre-​collaboration phase  199–​201, 212 intermediate collaboration phase 201–​205, 213 later collaboration phase  205–​209, 214 synthesis-​oriented design  33 systemic design  155–​156, 159

T teaming  91 testing  concept of  174, 175 in policy labs  112, 113, 114, 116 theorising, in PPA research  175, 178–​179, 182–​183 theory, concept of  173–​174 theory-​driven approach  32–​33, 116 Tõnurist, P.  143 Torfing, J.  76, 93, 134–​135 traditional policy design  1, 3–​4, 6, 52, 53–​54, 172 compared with new design thinking 54–​62, 128–​132, 141–​143 relation to new design thinking  61–​62, 222–​224 see also informational approach; validation-​oriented PPA research training  see Organised Crime Field Lab triple three-​dimensional view of power (Crosby–​Bryson framework)  193–​196 applied  see Synergy collaboration Trischler, J.  27

U UK Design Council  136–​138 user-​oriented design  33 user participation  see participants/​stakeholders

V validation, concept in PPA research  174, 175 validation-​oriented (retrospective) PPA research  171–​173 DS framework  174–​176, 183–​186 research examples  176–​183, 184–​185 validity  80–​81 Van de Kerkhof, M.  28, 32 Vaz, F.  228 Villa Alvarez, D.P.  223–​224 Voorberg, William  1

W Waardenburg, Maurits  72, 226 wicked problems  7, 18, 78, 89, 153

235