Evaluating a model for cost-effective data quality management in a real-world CRM setting

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Managing data resources at high quality is usually viewed as axiomatic. However, we suggest that, since the process of improving data quality should attempt to maximize economic benefits as well, high data quality is not necessarily economically-optimal. We demonstrate this argument by evaluating a microeconomic model that links the handling of data quality defects, such as outdated data and missing values, to economic outcomes: utility, cost, and net-benefit. The evaluation is set in the context of Customer Relationship Management (CRM) and uses large samples from a real-world data resource used for managing alumni relations. Within this context, our evaluation shows that all model parameters can be measured, and that all model-related assumptions are, largely, well supported. The evaluation confirms the assumption that the optimal quality level, in terms of maximizing net-benefits, is not necessarily the highest possible. Further, the evaluation process contributes some important insights for revising current data acquisition and maintenance policies.

论文关键词:Data quality,Utility,Cost–benefit analysis,Data warehouse,CRM

论文评审过程:Received 12 October 2009, Revised 27 July 2010, Accepted 27 July 2010, Available online 6 August 2010.

论文官网地址:https://doi.org/10.1016/j.dss.2010.07.011