Design Dimensions for Enterprise-Wide Data Management: A Chief Data Officer’s Journey

dc.contributor.author Schilling, Raphael
dc.contributor.author Aier, Stephan
dc.contributor.author Winter, Robert
dc.contributor.author Haki, Kazem
dc.date.accessioned 2020-01-04T08:23:37Z
dc.date.available 2020-01-04T08:23:37Z
dc.date.issued 2020-01-07
dc.description.abstract To unlock additional business value, most enterprises are intensifying their enterprise-wide data management. In the case of the globally operating bank, we base this article on, a Chief Data Officer (CDO) organization is established for providing data governance and, in a second step, pushing data driven innovation forward. As many employees of the bank were not yet familiar with (or did not acknowledge) the need for enterprise-wide data management, this evolution exhibits characteristics of an organizational learning process. CDOs may want to actively steer this learning process by purposefully designing and adjusting their data management approach over time. Based on the major controversies the CDO has been confronted with, we propose four design dimensions for enterprise-wide data management and discuss the considerations for their configuration: (I) objective, (II) governance, (III) organization of data analytics, and (IV) expertise.
dc.format.extent 10 pages
dc.identifier.doi 10.24251/HICSS.2020.714
dc.identifier.isbn 978-0-9981331-3-3
dc.identifier.uri http://hdl.handle.net/10125/64456
dc.language.iso eng
dc.relation.ispartof Proceedings of the 53rd Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Practice-based IS Research
dc.subject case study
dc.subject chief data officer
dc.subject design dimensions
dc.subject enterprise-wide data management
dc.title Design Dimensions for Enterprise-Wide Data Management: A Chief Data Officer’s Journey
dc.type Conference Paper
dc.type.dcmi Text
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