A rule-based approach to business-IT misalignment symptom detection

In this paper, an analytical solution is built to approach the topic of strategic misalignment from an EA-based perspective. The study aims to accomplish an EA-based, systematic analysis of mismatches between business and information systems. The research takes a rule-based approach to reveal the symptoms of malfunctioning alignment areas. In this study, the analytical potential of rule generation and rule testing are utilized in complex EA environment. Misalignment symptoms — defined as formal rules — are detected in the underlying EA models by using XML analysis tools. Rule construction and rule testing are supported by Schematron, a pattern-based XML validation language. The operation, the correctness and the significance of the approach is validated via a compound case study at a road management authority. The proposed research has the potential to extend our understanding on assessing the state of misalignment in a complex EA model structure by applying rule testing and XML validation techniques in EA environment.