An Economics-Driven Decision Model for Data Quality Improvement - A Contribution to Data Currency

As poor data quality usually leads to high costs, managing data quality is essential for organizations. Thereby, comparing the current with the required data quality level is necessary for an effective and economics-driven data quality management. Otherwise decision makers might decide in favor of unsuitable or inefficient data quality improvement measures with respect to cost and benefit. Existing methodologies for assessing and improving data quality often neglect providing methods for determining the required data quality level or argue on a managerial rather than an operational level. As a consequence, an economics-driven and context-dependent decision model for updating data at the level of attribute values is presented. This model contains a metric for currency, errors and error costs, and a currency threshold for attribute values. The decision model is illustrated using a direct marketing example.