A Mathematical Framework for Data Quality Management in Enterprise Systems

This paper addresses the issue of data quality management in information systems within an enterprise. Motivated by legislative mandates such as the Sarbanes-Oxley Act of 2002 on the reliability and integrity of the data and the enterprise systems from which the data are produced, we propose a process-based modeling framework to assess the impact of data errors in the business process information flow and the resulting data quality metrics. This framework is then integrated with a business control framework in which the placement and effectiveness of control procedures alter the propagation of errors and, ultimately, the quality of the data in the business process. This integrated framework enables mathematical formulations of managerial problems that lead to effective data quality control strategies. We develop a two-stage multiple-choice knapsack model as a special case, and we illustrate the model and analysis through a revenue realization process.