A data-centric approach to designing control-enabled business processes

Operational risk management is one of the most important management issues for business entities. Despite the enabling role operational risk played in a series of business failures since the mid 90s, little effort has been spent on developing principles or guidelines for controlling operational risk. As of today, operational risk management still relies heavily on after-the-fact operations auditing or capital reserves against predicted operational and business loss. In this dissertation I propose a data-centric approach to controlling operational risk in business process. It is aimed to complement current approaches by proactively managing operational risk events before or nearly immediately after business activities are carried out, which reduces potential losses. The proposed approach draws from artifact-centric business process management concepts and business object centered process modeling techniques. It is constructed based on the method engineering discipline.