Abstract
Organizational data repositories are recognized as critical resources for supporting a large variety of decision tasks and for enhancing business capabilities. As investments in data resources increase, there is also a growing concern about the economic aspects of data resources. While the technical aspects of data management are well examined, the contribution of data management to economic performance is not. Current design and implementation methodologies for data management are driven primarily by technical and functional requirements, without considering the relevant economic factors sufficiently. To address this gap, this study proposes a framework for optimizing data management design and maintenance decisions. The framework assumes that certain design characteristics of data repositories and data manufacturing processes significantly affect the utility of the data resources and the costs associated with implementing them. Modeling these effects helps identify design alternatives that maximize net-benefit, defined as the difference between utility and cost. The framework for the economic assessment of design alternatives is demonstrated for the optimal design of a large data set
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