A data quality management framework to support delivery and consultancy of CRM platforms

Abstract

CRM platforms heavily depend on high-quality data, where poor-quality data can negatively influence its adoption. Additionally, these platforms are increasingly interconnected and complex to meet growing needs of customers. Hence, delivery and consultancy of CRM platforms becomes highly complex. In this study, we propose a CRM data quality management framework that supports CRM delivery and consultancy firms to improve data quality management practices within their projects. The framework should also improve data quality within CRM solutions for their clients. We extract best practices for CRM data quality management by means of a literature study on data quality definition and measurement, data quality challenges, and data quality management methods. In a case study at an IT consultancy company, we investigate how CRM delivery and consultancy projects can benefit from the incorporation of data quality management practices. The design of the framework is validated by means of confirmatory focus groups and a questionnaire. The results translate into a framework that provides a high-level overview of data quality management practices incorporated in CRM delivery and consultancy projects. It includes the following components: Client profiling, project definition, preparation, migration/integration, data quality definition, assessment, and improvement.