A Contingency Approach To Data Governance.

Abstract

Enterprises need data quality management (DQM) to respond to strategic and operational challenges demanding high-quality corporate data. Hitherto, companies have assigned accountabilities for DQM mostly to IT departments. They have thereby ignored the organizationalissues that are critical to the success of DQM. With data governance, however, companies implement corporate-wide accountabilities for DQM that encompass professionals from business and IT. This paper outlines a data governance model comprised of three components that build a matrix comparable to an RACI chart: data quality roles, decision areas, and responsibilities. The data governance model documents the data quality roles and their type of interaction with DQM activities. In addition, the paper identifies contingency factors that impact the model configuration. Companies can structure their company-specific data governance model based on these findings.

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