IDEAS home Printed from https://ideas.repec.org/p/oec/govaaa/33-en.html
   My bibliography  Save this paper

A data-driven public sector: Enabling the strategic use of data for productive, inclusive and trustworthy governance

Author

Listed:
  • Charlotte van Ooijen
  • Barbara Ubaldi
  • Benjamin Welby

Abstract

Over the last decade the Open Government Data movement has successfully highlighted the value of data and encouraged governments to open up information for reuse both inside, and outside the public sector. This Working Paper argues that governments now need to go further and put the role and value of data at the core of thinking about the digital transformation of government. A data-driven public sector (DDPS) recognises that data are an asset, integral to policy making, service delivery, organisational management and innovation. The strategic approach governments take to building a DDPS can have a positive impact on the results they deliver by promoting evidence-led policy making and data-backed service design as well as embedding good governance values of integrity, openness and fairness in the policy cycle. After framing the concept the paper presents the opportunities offered by embracing the DDPS approach and identifies some of the challenges that governments may face in establishing a DDPS before concluding with the discussion of the need for coherent strategic approaches that reflect the role of data across the entire public sector, not only from a policy point of view but from an operational and practical perspective.

Suggested Citation

  • Charlotte van Ooijen & Barbara Ubaldi & Benjamin Welby, 2019. "A data-driven public sector: Enabling the strategic use of data for productive, inclusive and trustworthy governance," OECD Working Papers on Public Governance 33, OECD Publishing.
    • Handle: RePEc:oec:govaaa:33-en
    DOI: 10.1787/09ab162c-en
    as

    Download full text from publisher

    File URL: https://doi.org/10.1787/09ab162c-en
    Download Restriction: no
    File URL: https://libkey.io/10.1787/09ab162c-en?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Maxwell Haurovi & Alouis Chilunjika, 2024. "Fourth industrial revolution and social innovation dynamics in South Africa: a review," Insights into Regional Development, VsI Entrepreneurship and Sustainability Center, vol. 6(2), pages 103-116, June.
    2. Abuljadail, Mohammad & Khalil, Ashraf & Talwar, Shalini & Kaur, Puneet, 2023. "Big data analytics and e-governance: Actors, opportunities, tensions, and applications," Technological Forecasting and Social Change, Elsevier, vol. 193(C).
    3. Gabor Izsak & Alexandr Palicz & Katinka Szasz & Balazs Varga, 2022. "The Role of Data Assets in the Financial Sector," Financial and Economic Review, Magyar Nemzeti Bank (Central Bank of Hungary), vol. 21(1), pages 164-173.
    4. Dubey, Rameshwar & Bryde, David J. & Dwivedi, Yogesh K. & Graham, Gary & Foropon, Cyril & Papadopoulos, Thanos, 2023. "Dynamic digital capabilities and supply chain resilience: The role of government effectiveness," International Journal of Production Economics, Elsevier, vol. 258(C).
    5. MISURACA Gianluca & BARCEVICIUS Egidijus & CODAGNONE Cristiano, 2020. "Exploring Digital Government transformation in the EU – Understanding public sector innovation in a data-driven society," JRC Research Reports JRC121548, Joint Research Centre.
    6. Cordella, Antonio & Gualdi, Francesco & van de Laar, Mindel, 2024. "Digital skills within the public sector: a missing link to achieve the Sustainable Development Goals (SDGs)," LSE Research Online Documents on Economics 122256, London School of Economics and Political Science, LSE Library.
    7. Brandt, Tobias & Wagner, Sebastian & Neumann, Dirk, 2021. "Prescriptive analytics in public-sector decision-making: A framework and insights from charging infrastructure planning," European Journal of Operational Research, Elsevier, vol. 291(1), pages 379-393.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:oec:govaaa:33-en. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/teoecfr.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.