Organising Accountabilities for Data Quality Management A Data Governance Case Study
ABSTRACT Enterprises need corporate data quality management (DQM) that combines business-driven and technical perspectives to respond to strategic and operational challenges that demand high-quality corporate data. Hitherto, companies have assigned accountabilities for DQM mostly to IT departments. They have thereby ignored the organisational issues 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 study examines a large organisation that has adopted an ad-hoc data governance model to manage its data. It was found that its DQM efforts were hampered mainly by the lack of clear roles and responsibilities and the lack of mandate to carry out data quality improvement initiatives. In order to promote effective DQM, this research identifies a data governance structure with the emphasis on collaboration between business and IT to support organisations.
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ABSTRACT: An organization depends on quality information for effective operations and decision-making. However, fundamental questions still remain as to how quality should be defined and the specific criteria that should be used to evaluate information quality. Previous work adopted either an intuitive, empirical, or theoretical approach to address this problem; however, we believe that an integrated research approach is required to ensure both rigour and scope. This paper presents an information quality framework based on semiotic theory, the linguistic theory of sign-based communication, to describe the form-, meaning-, and use-related aspects of information. This provides a sound theoretical basis both for defining quality categories, previously defined in an ad-hoc manner, based on these different information aspects and for integrating the different research approaches required to derive quality criteria for each category. The goal of our work is to provide an approach to defining information quality that is both theoretically grounded and practical that can serve as a basis for further research in data quality assessment and decision support.01/2005;
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ABSTRACT: The dominant market for enterprise resource planning (ERP) vendors has traditionally been the largest of multinational corporations. Until recently, most vendors (SAP, PeopleSoft, Oracle, etc.) have promoted a “one size fits all” solution built on “industry best practices.” This approach forced organizations to either conform to the “best practices” and configurations suggested by vendors and implementation consultants or embark on extremely costly reconfiguration of their ERP package. The study reviews the concepts of control, coordination, and their trade-offs plus Bartlett and Ghoshal’s topology of firm strategy. Human resource issues are introduced as examples of organization elements that may or may not conform to the enterprise design structure within coordination and control. Finally, the concepts of control and coordination and the Bartlett and Ghoshal topology are combined to create a firm strategic orientation which is then matched to an ideal ERP configuration or enterprise information architecture.Business Process Management Journal 07/2001; 7(3):205-215.
- The Academy of Management Review. 01/1989; 14(4):532-550.