Profiling event logs to configure risk indicators for process delays

Risk identification is one of the most challenging stages in the risk management process. Conventional risk management approaches provide little guidance and companies often rely on the knowledge of experts for risk identification. In this paper we demonstrate how risk indicators can be used to predict process delays via a method for configuring so-called Process Risk Indicators(PRIs). The method learns suitable configurations from past process behaviour recorded in event logs. To validate the approach we have implemented it as a plug-in of the ProM process mining framework and have conducted experiments using various data sets from a major insurance company

Towards a Goal-Driven Approach for Business Process Improvement Using Process-Oriented Data Warehouse

An emerging approach for business process analysis is to use business intelligence practices by employing data warehouse and decision-making techniques. However, little work has been done on developing core methods and tools to guide process analysis and improvement. Our research addresses this issue by introducing a goal-driven approach for business process improvement using process warehouse. In this paper, we present our three step method and its evaluation through an empirical study. The results showed that the impact of applying our method for process improvement has been perceived positively