A Metadata-based Approach to Leveraging the Information Supply of Business Intelligence Systems

Ensuring adequate information provision continues to be a key challenge of corporate decision making and the usage of business intelligence systems. As a matter of fact, the situation becomes increasingly paradox: Whereas decision makers struggle to specify their information requirements and spend much time on obtaining the information they believe to require, the amount of information supplied by business intelligence systems grows at a speed that makes it hard to keep track. Thus, it is very likely that the required information or suitable alternatives are available, but neither found nor used. Instead, manual searching causes considerable opportunity cost. Existing approaches to information requirements analysis pay attention to incorporate information supply, but do not provide means for leveraging it in a systematic and IT supported manner. As a first step to close this research gap, we propose a metadata-based approach consisting of a procedure model and formalism that help identify a suitable subset of the information supplied by an existing business intelligence system. The formalism is specified using set theory and first-order logic to provide a general foundation that may be integrated into different conceptual modelling approaches.