Impartial versus Utility-driven Assessment of Data Quality: Methodology, Insights, and Implications for Managing Customer Data

This study presents a methodology for dual assessments of data. Impartial assessment measures the extent to which data is defective. Utility-driven assessments of data quality measure the extent to which the presence of quality defects degrades data utility – the benefit gained from using that data in a specific business setting. The dual assessment methodology is demonstrated in a real-world setting using alumni data – a large data resource for managing alumni relations and initiating pledge campaigns. Dual-assessment results provide important inputs that can direct the implementation and management of quality improvement policies in this data resource.