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

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dc.contributor.authorSchilling, Raphael
dc.contributor.authorAier, Stephan
dc.contributor.authorWinter, Robert
dc.contributor.authorHaki, Kazem
dc.date.accessioned2020-01-04T08:23:37Z
dc.date.available2020-01-04T08:23:37Z
dc.date.issued2020-01-07
dc.description.abstractTo 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.extent10 pages
dc.identifier.doi10.24251/HICSS.2020.714
dc.identifier.isbn978-0-9981331-3-3
dc.identifier.urihttp://hdl.handle.net/10125/64456
dc.language.isoeng
dc.relation.ispartofProceedings of the 53rd Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectPractice-based IS Research
dc.subjectcase study
dc.subjectchief data officer
dc.subjectdesign dimensions
dc.subjectenterprise-wide data management
dc.titleDesign Dimensions for Enterprise-Wide Data Management: A Chief Data Officer’s Journey
dc.typeConference Paper
dc.type.dcmiText

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