Policy Making and the Digitalization of the Public Sector
Marco Di Giulio, Giancarlo Vecchi
- Year
- 2025
- Citations
- 2
- Access
- Open access
Abstract
The digital transformation of the public sector is one of the biggest chal-lenges for contemporary governments and administrations. There is no area of public policy in which policymakers avoid promising enhanced effectiveness and efficiency due to digitalization. At the same time, the diffusion of digital services in the private sector, such as banking and payments, is raising citizens’ and businesses’ expectations for cheaper, fairer, and safer services. Academics, intellectuals, and pundits puzzle over the opportunities for more rational decision-making: The large quantity of granular information and the increasing capacity to compute them feeds the hope (but also fear in some cases) for policy design that can be perfectly calibrated on the needs of beneficiaries. In this sense, digital transformation is a process that aims to produce a paradigmatic change in the way governmental activities have been structured and worked since their inception. However significant the cross-country variance may be, large and siloed organizations based on standardization of procedures represent a model of success because such a structure travelled around the world and resisted over decades. Nonethe-less, changes did take place and pulled public sector organizations in different directions. Bureaucracies have integrated (but not dissolved) professionalism as governments have undertaken complex and case-specific decision-making. Moreover, public administrations have progres-sively lost their direct connection with national governments. Agencies, regional and local bureaucratic structures, public-private partnerships, vii viii INTRODUCTION quangos, and third-sector organizations constitute a constellation of actors that public policy scholars and administrations are already familiar with, as they are stably part of policy processes. Besides, administrations flourished also beyond national states. International organizations have large apparatuses; the same goes for the European Union. Hence, bureau-cracy, as a model, is trapped by its success. On the one hand, it provides control through standardization of procedures and such control also grants efficiency. Conversely, replicating such a model in any circumstance produces incoherence and entropy. Policymakers and academics have always looked at machines as a solu-tion to the problems of bureaucracy. Cybernetic at the beginning, then Information and Communication Technologies (ICTs), and currently Artificial Intelligence (AI) have framed a significant part of the discourse about improving administrative processes. Digital technologies may refine coordination mechanisms based on standardization, which bureaucracies already do relatively well. At the same time, they enhance the capacity to store and process information to support decision-making; in some cases, machines will also provide substitutes for decisions currently assigned to professionals. It is no surprise that, in Europe, a significant share of the Next Generation EU fund has been directed to this area, and national governments have channelled such resources to support old and new projects in this area. Policymakers and stakeholders have ideas precise enough about what should be reformed in the way administrations work, and technolo-gists know precisely what digital artifacts could complement humans in decision-making. There is plenty of elaboration about administrations as to what they will look like when the potential of digital technolo-gies is deployed. However, how public sector digitalization should be designed to effectively realize our image of the future is not a fashionable topic in the literature, and few studies have tried to analyse the imple-mentation processes needed to get there. This gap is, to some extent, surprising because scholars who addressed the issue showed how techno-logical change in government (as for any kind of organization) is not a linear process in which machines substitute humans, hopefully doing the s
Keywords
Related papers
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Fractional Differential Equations
Igor Podlubný
2025
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
Genetic Programming: On the Programming of Computers by Means of Natural Selection
John R. Koza
1992