Root causes affecting data quality in CRM

An important field of application of business intelligence tools is in Customer Relationship Management (CRM). Especially analyses of a firm’s customers’ behavior and believes are a prerequisite to develop and realize innovative concepts to initiate and tighten customer relationships. So the quality of available customer data is a decisive factor for companies applying this customer focused strategy. Data quality (DQ) problems often hinder the implementation and cause major negative consequences (Redman 1996, pp. 6-7). To address this problem from a quality management point of view a systematic management, based on a definition of data quality, a continuous quality measurement, and processes to find improvement measures for identified and prioritized problems should be implemented (Wang 1998, pp. 61-65). A root cause analysis is necessary to identify useful and effective improvement measures. Based on a review of literature in quality management we propose a model to identify possible reasons for data quality problems. The evaluation of this model is based on an empirical study. The remainder of this article is structured as follows: Section 2 provides a brief introduction to data quality management as well as an outline of the relation between CRM and data quality. Section 3 presents a gap model for data quality to systematically derive causes for data quality problems. Section 4 gives a short description of the deduction of the proposed hypotheses. In the following section these are evaluated and the results will be discussed. Finally, Section 6 presents a short discussion of managerial implications and proposes aspects for further research.