The problem of insufficient quality of data and information is widespread and is a critical issue for all those organisations whose activity is based on information and knowledge. Insufficient quality of information and data often leads to numerous negative effects: it can disrupt business processes and delay or interfere with decisions; it can lead to confused communications between organisations, or might block creativity within organisations. Ensuring sufficient data quality guarantees the availability of correct and updated as well as relevant data and information in processing activities. Consequently, high data and information quality improves customer satisfaction and decision-making, decreases operational costs and thus ensures competitive advantage and business success. High data and information quality is becoming the decisive factor for networked organisations in the information economy.

In order to ensure and manage high-level data quality in business information systems, Markus Helfert's research focuses on analysing and understanding causes and impacts of poor data and information quality. Dr. Helfert aims to develop a comprehensive method for proactive data quality management in networked economies. His research includes the development of tools, metrics and cost-benefit analysis, as well as reference models for defining, assessing and managing data and information quality in various applications. Examples include financial institutions, healthcare information systems, logistics and multi-organisational information systems as well as web environments.