A framework for economics-driven assessment of data quality decisions

Economic perspectives have raised growing attention in recent data quality (DQ) literature, as studies have associated DQ decisions with major cost-benefit tradeoffs. Despite the growing interest, DQ research has not yet developed a robust, agreed-upon view for assessing and studying the link between DQ and economic outcome. As a contribution, this study proposes a framework, which links costs to the decisions made in managing the information process and improving the DQ, and benefits to the use of information-product outcomes by data consumers. Considering past research contributions, we develop this framework further into a high-level optimization model that permits quantitative assessment of cost-benefit tradeoffs, towards economically-optimal DQ decisions. We demonstrate a possible use of the proposed framework and the derived model, and highlight their potential contribution to an economics-driven view of DQ issues in both research and practice.