Big data in the policy cycle: Policy decision making in the digital era

Höchtl, Johann; Parycek, Peter; Schöllhammer, Ralph

doi:10.1080/10919392.2015.1125187

Cited by 232 publications

(199 citation statements)

References 54 publications

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“…It may foster governance battlegrounds dotted by advocacy coalitions and instrument constituencies who clash on the basis of digital or non‐digital problem definitions, policy options, or instrumentation and implementation preferences (Howlett, Wellstead, and Craft ; Weible ; Voss and Simons ). We know already that in some cases digital information and communication technologies expedite or slow the very pace of decision‐making, altering the nature and place of advisory work as a component of the policymaking process (Höchtl, Parycek, and Schöllhammer ).…”

Section: Introductionmentioning

confidence: 99%

Digital era policy advising: Clouding ministerial perspectives?

Marando¹,

Craft²

2017

Can Public Adm

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The growing body of literature on digital governance, and policy advisory systems, often neglects the perspective of elected decision makers. What types of policy advice do ministers need in the digital governance era? Is digitization of government and policymaking reshaping supply and demand dynamics, the content of policy advice, or how advice is used within the policy process? This article borrows existing theoretical frames on digital governance to examine these and other questions from the perspective of ministers. The digital governance era will undoubtedly introduce novel disruptions and dilemmas, but it will also intensify longstanding tensions inherent in advisory work linked to questions of influence, capacity, and how well advisory systems adapt to serve ministers. We use information processing dynamics, policy entrepreneurship, and control and coordination to ground analysis of ministers' advisory demand in the digital governance era. We highlight unique considerations that apply to ministers as well as reflection on their place within the broader context of advisory work. We employ vignettes from the perspective of ministers throughout the article as a useful way to personalize the digital era disruptions and dilemmas particular to ministers.Sommaire : Le point de vue des d ecideurs elus est souvent n eglig e par l'ensemble croissant d'ouvrages portant sur la gouvernance num erique et les systèmes de consultation sur la politique. De quels types de conseils strat egiques les ministres ontils besoin a l'ère de la gouvernance num erique? Est-ce que la num erisation du gouvernement et de la prise de d ecisions remodèle les dynamiques de l'offre et de la demande, le contenu des conseils en matière de politique, ou la manière dont la consultation est utilis ee au sein du processus de politiques? En empruntant les cadres th eoriques existants sur la gouvernance num erique, cet article etudie ces questions parmi d'autres, du point de vue des ministres. L'ère de la gouvernance num erique engendrera sans nul doute de nouveaux dilemmes et perturbations; elle intensifiera aussi les tensions de longue date qui sont inh erentes au travail consultatif et li ees aux questions d'influence, de comp etences, et a la manière dont les systèmes consultatifs s'adaptent pour servir les ministres. Afin de baser l'analyse de demande consultative des ministres a l'ère de la gouvernance num erique, nous utilisons les dynamiques du traitement de l'information, l'entrepreneuriat en politiques, le contrôle et la coordination. Nous soulignons les consid erations particulières qui s'appliquent aux ministres, ainsi que la r eflexion sur la place qu'elles occupent au sein du contexte elargi du travail consultatif. Tout au long de cet article, nous utilisons des vignettes dans

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Section: Introductionmentioning

confidence: 99%

Digital era policy advising: Clouding ministerial perspectives?

Marando¹,

Craft²

2017

Can Public Adm

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“…Based on big data, more sophisticated climate change models have been developed to reduce the uncertainty surrounding decisions linked to mitigating and adapting to environmental changes (Larson, White, Gober, & Wutich, 2015). But the models also add information that might expose policy-makers to largely irrelevant information or contradictory aspects and result in prolonged decision-making processes (Höchtl et al, 2016;Trenberth, 2010). Beyond data-based information, there are further multiple forms of policy-relevant knowledge that is vital to understanding climate change issues, and thus several evidence bases need consideration (Davies, 2004;Head, 2008;Pawson, Boaz, Grayson, Long, & Barnes, 2003;Schorr, 2003).…”

Section: Data-based Policy-makingmentioning

confidence: 99%

“…Recent examples show that local governments struggle with the integration of data knowledge, because of their dependence on additional data from other government levels or departments and outside stakeholders. The discrepancies of how data are collected at different levels and the legal framework for private companies compiling and analysing city data pose some of these challenges (Höchtl, Parycek, & Schöllhammer, 2016;Letouzé & Jütting, 2014). So far, there is however limited research on the intended use of big data in urban governments for specific goals, such as carbon emission reduction and the actual implementation of a data-based structure.…”

Section: Introductionmentioning

confidence: 99%

Big data analytics for mitigating carbon emissions in smart cities: opportunities and challenges

Giest

2017

European Planning Studies

110

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The paper addresses the growing scepticism around big data use in the context of smart cities. Big data is said to transform city governments into being more efficient, effective and evidencebased. However, critics point towards the limited capacity of government to overcome the siloed structure of data storage and manage the diverse stakeholders involved in setting up a data ecosystem. On the basis of this, the paper investigates the challenges city governments face when dealing with big data in the context of carbon emission reduction. Through the lens of the evidence-based policy and policy capacity literature, the cities of Copenhagen (Denmark), London (UK), Malmö (Sweden), Oxford (UK) and Vienna (Austria) are analysed. The cases reveal that the institutional complexity underlying big data integration limits local government capacity to set up data management structures that would allow further utilization of big data and that current solutions focus on local pilot sites and outsourcing of data analytics. ARTICLE HISTORY

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“…This way, MENTA integrates personal attitudes with relevant background data. In addition, tracking social media can assist policymakers in understanding how people experience a certain policy and drive their decisions for more responsive and resilient policies [9]. What is now realized with MENTA should be available on a broader scale via HDC, and information obtained via social media should be fed into the HDC system.…”

Section: Hdc For Policy Empowermentmentioning

confidence: 99%

“…Most governmental organizations are not prepared to apply big data analytics to their strategic benefit, that is, to optimize their way of working, to redefine their role or actions, to consider the disruptive nature of technological changes, and to investigate the topic at large and find benefits for policy development, definition, and evaluation [8]. For governmental actions, technology is still regarded as a complementary tool to the existing organizational and administrative practices, but it is hardly viewed as capable of triggering changes to the actual structures of decision-making processes [9]. An important reason for the slow process of big data adaption in healthcare lies in the nature of big data: many players, providers, and facilities are unable to share data, not even within one organization, due to concerns and regulations pertaining to privacy and data protection.…”

Section: Status Quomentioning

confidence: 99%

Big Data for Public Health Policy-Making: Policy Empowerment

Mählmann

Reumann

Evangelatos

et al. 2017

Public Health Genomics

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Digitization is considered to radically transform healthcare. As such, with seemingly unlimited opportunities to collect data, it will play an important role in the public health policy-making process. In this context, health data cooperatives (HDC) are a key component and core element for public health policy-making and for exploiting the potential of all the existing and rapidly emerging data sources. Being able to leverage all the data requires overcoming the computational, algorithmic, and technological challenges that characterize today’s highly heterogeneous data landscape, as well as a host of diverse regulatory, normative, governance, and policy constraints. The full potential of big data can only be realized if data are being made accessible and shared. Treating research data as a public good, creating HDC to empower citizens through citizen-owned health data, and allowing data access for research and the development of new diagnostics, therapies, and public health policies will yield the transformative impact of digital health. The HDC model for data governance is an arrangement, based on moral codes, that encourages citizens to participate in the improvement of their own health. This then enables public health institutions and policymakers to monitor policy changes and evaluate their impact and risk on a population level.

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Big data in the policy cycle: Policy decision making in the digital era

Cited by 232 publications

References 54 publications

Digital era policy advising: Clouding ministerial perspectives?

Digital era policy advising: Clouding ministerial perspectives?

Big data analytics for mitigating carbon emissions in smart cities: opportunities and challenges

Big Data for Public Health Policy-Making: Policy Empowerment

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