Purpose - In literature, there is not agreement on the relevant data quality dimensions in an enterprise Accepted 7 February 2009 resource planning (ERP) system context. The purpose of this paper is to provide some clarification of this topic, by answering two important questions: What are the most relevant dimensions for assessing ERP data quality? What are the causal relationships between these data quality dimensions? Design/methodology/approach - Based on a discussion of existing literature on data quality, a classification model of ERP system data quality is proposed and the relationships between the defined categories of data quality dimensions are defined. The validity of the classification model and the relationships between categories of data quality dimensions are investigated in three case studies. Findings - The three case studies confirm that the classification model captures the most important aspects of describing ERP data quality and that the defined causalities between categories of data quality dimensions correspond with practice. Research limitations/implications - Besides being relevant in an ERP system context, the contribution of this paper may also be applicable for the evaluation of data quality in other types of information systems. Practical implications - The defined classification model of ERP system data quality may support companies in improving their ERP data quality, thereby achieving greater benefits from their ERP systems. Originality/value - A clarification of the most important data quality aspects in an ERP context is provided. Furthermore, some of the most important causalities between categories of data quality are defined.
