DPA 2.0: Rethinking Deliberative Policy Analysis

Twenty years ago, Deliberative Policy Analysis: Understanding Governance in the Network Society (Hajer & Wagenaar 2003) redefined the epistemic foundations of policy analysis. The book argued that policy analysis should be interpretive, reconstructing the meaning that social problems and public policy have for people. It also suggested that it should be practice-oriented and deliberative. What necessitated a reorientation of the discipline of policy analysis was that society, and thus the systems of governance, had changed since the early days of policy analysis. They had become more pluralistic, harder to understand, and more conflict-prone, while trust in politics and administration had decreased (Hajer and Wagenaar 2003). The authors argued that DPA would prove a better epistemic fit with this policy environment than rationalist, technocratic policy analysis. The book became an academic bestseller, one of those books that (re-) defined a field. Many of the authors who had a chapter in the book continued to develop DPA in the years that followed (Healey, 2010; Fischer 2003, Torgerson et. al. 2015; Schwartz-Shea and Yanow 2011; Hajer 2009; Cook and Wagenaar, 2012). A younger generation of scholars picked up and developed the message of the book (Bartels and Wittmayer 2018, Boswell 2022, Hendriks, et. al. 2020) DPA was adopted and developed by scholars in China and the global south and (Li 2015; Boossabong and Chamsong 2019). New innovative DPA methods such as Designed Deliberative Platforms, Enhancing the Deliberative Capacity of a Policy System, Systematic Utopian imagination, and Progressive Government as Design-in-Practice were put forward in the literature (Wagenaar 2022, Li and Wagenaar 2020, Bartels, Li and Wagenaar 2021, Wagenaar and Prainsack 2021). From this short overview of twenty years of DPA it seems that it is in rude health. So, why then, a Section on DPA now? We argue that DPA's key argument, the epistemic fit between policy analysis and its object, needs to be revised given the series of sharp shocks and developments that the world has undergone since 2003. The dislocating effects of the financial crisis of 2008 and the SARS-CoV-2 pandemic still reverberate through our financial, economic, and political systems. The accelerating climate crisis and the failing transition to renewable energy, the eroding financial position of the middle class, the precarisation of work, the poisonous effects of social media platforms on the public sphere, and the rise of illiberal and autocratic parties, are testing the limits of governance power worldwide. In light of these developments DPA needs to recognize the ubiquitous role of political and economic power in policy making beyond a general sociology of the network society. It urgently needs a dose of political realism. Or to be more precise, DPA needs to be firmly anchored into realist political philosophy (Galston 2010; Geuss 2008; Honig and Stears 2011; Tully 2008). This would provide DPA with more fundamental concepts, values, and strategies of inquiry to design appropriate responses to the mechanisms of power in concrete situations of policy making and political-economic conflict and oppression. In addition, DPA needs to become more epistemically realistic. The impasses, implementation crises, and perverse unintended consequences that afflict administrations worldwide are not just the result of the network society. Underneath these problems sits the human predicament of complexity (Connolly 2011; Wagenaar and Prainsack 2021). Complexity is the designation of the deep structure of the word we face when engaging in collective problem solving. Complexity describes our world as consisting of a series of nested complex systems in different timescales. Complex systems are characterized by dense interactions between elements, resulting in emergent outcomes, nonlinear effects caused by positive and negative feedback, and above all co-evolution. Co-evolution means that each agent in a system finds itself in an environment produced by its interactions with the other agents in the system. This means that agents are always an integral part of the system that they try to change. The taken-for-granted epistemic move in policy analysis to describe or model a system from an external perspective is limited and misguided. Ours is a world of becoming (Connolly 2011). Co-evolution compels us to an inclusive and relational approach to policy analysis that acknowledges the intrinsic and constitutive entanglement of people, materiality, and the natural environment (Cruikshank 2005; Shove et. al. 2012; Kimmerer 2013; Dryzek 2013; Ingold 2022). Although we cannot hope to control complexity, there are different strategies of harnessing it (Axelrod and Cohen 2000). These strategies must be approached with an attitude of aspirational humility and a ‘positive ethos of engagement’ (Connolly 2011). This we see as the mission of DPA 2.0. With its three methodological orientations, its repertoire of methodical approaches, and guided by a foundation in political realism and relationality, DPA 2.0 is in an excellent position to support authorities, civil society actors and businesses in collective problem solving. And to do that in a way that acknowledges the predicament of complexity and aims at deepening democracy and societal flourishing.