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Reconciling complex organizations and data management

Author

Listed:
  • Eric Buffenoir

    (Théorie des Champs & Physique Mathématique - L2C - Laboratoire Charles Coulomb - UM - Université de Montpellier - CNRS - Centre National de la Recherche Scientifique)

  • Isabelle Bourdon

    (Système d'Information - MRM - Montpellier Research in Management - UM1 - Université Montpellier 1 - UPVM - Université Paul-Valéry - Montpellier 3 - UM2 - Université Montpellier 2 - Sciences et Techniques - UPVD - Université de Perpignan Via Domitia - Groupe Sup de Co Montpellier (GSCM) - Montpellier Business School)

Abstract

These last years, main IT companies have build software solutions and change management plans promoting data quality management within organizations concerned by the enhancement of their business intelligence system. These offers are closely similar data governance schemes based on a common paradigm called Master Data Management. These schemes appear generally inappropriate to the context of complex extended organizations. On the other hand, the community-based data governance schemes have shown their own efficiency to contribute to the reliability of data in digital social networks, as well as their ability to meet user expectations. After a brief analysis of the very specific constraints weighting on extended organization's data governance, and of peculiarities of monitoring and regulatory processes associated to management control and IT within these, we propose a new scheme inspired by Foucaldian analysis on governmentality: the Panopticon data governance paradigm.

Suggested Citation

  • Eric Buffenoir & Isabelle Bourdon, 2012. "Reconciling complex organizations and data management," Working Papers hal-00744410, HAL.
    • Handle: RePEc:hal:wpaper:hal-00744410
    Note: View the original document on HAL open archive server: https://hal.science/hal-00744410v2
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    References listed on IDEAS

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    Cited by:

    1. Majid Al-Ruithe & Elhadj Benkhelifa & Khawar Hameed, 2018. "Data Governance Taxonomy: Cloud versus Non-Cloud," Sustainability, MDPI, vol. 10(1), pages 1-26, January.
    2. Haneem, Faizura & Kama, Nazri & Taskin, Nazim & Pauleen, David & Abu Bakar, Nur Azaliah, 2019. "Determinants of master data management adoption by local government organizations: An empirical study," International Journal of Information Management, Elsevier, vol. 45(C), pages 25-43.

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