Making decision process knowledge explicit using the decision data model

In this paper we present an approach for mining decisions. We show that through the use of a Decision Data Model (DDM) we can make explicit the knowledge employed in decision making. We use the DDM to provide insights into the data view of a business decision process. To support our claim we introduce our complete, functional decision mining approach. First, a ‘decision-aware system’ introduces the decision maker to a simulated environment containing all data needed for the decision. We log the user’s interaction with the system (focusing on data manipulation and aggregation). The log is mined and a DDM is created. The advantage of our approach is that, when needed to investigate a large number of subjects, it is much faster, less expensive and produces more objective results than classical knowledge acquisition methods such as interviews and questionnaires. The feasibility and usability of our approach is shown by a case study and experiments.