Comparative analysis of data quality and utility inequality assessments

Given that the volumes of organizational data resources are rapidly increasing, achieving and sustaining high data quality are becoming much more challenging tasks. In the face of this growing challenge, this study posits the need to introduce a robust economic thinking into the process of improving and maintaining data quality. Economic thinking requires investigating and assessing the business-value contribution of data resources, conceptualized as utility. We show that quantitative assessments of inequality in the utility of data resources, together with assessments that reflect the presence and the impact of defects, can provide key insights into the current state of data quality. A comparative analysis of such assessments can also direct the development of data quality maintenance policies and help prioritize quality improvement efforts. In this study, we demonstrate the application of such a comparative analysis in a real-life CRM context, using samples from a large data repository used for managing alumni relations. We show that the results of such a comparative analysis have important managerial implications for data quality management within the evaluated environment. We also discuss its applicability in other data management contexts.