Abstract

Businesses have adopted diverse process management approaches such as business process re-engineering (BPR) and Six Sigma for their survival and growth. Even though these approaches have partially made a contribution to the improvement of organizational performances such as cost reduction and value innovation, they have a high possibility of failure. In particular, the failure probability of BPR and process innovation (PI) is as high as 60-70%. Most process management approaches include traditional interviews and observation-dependent business process analysis (BPA). This conventional BPA requires a lot of time. However, it derives subjective and incomplete analysis results and has no tool to measure improvement effects. As a way to overcome this kind of limitation of conventional BPA, this study introduces a process mining technique through the analysis and utilization of a huge amount of process data kept almost unused in domestic information systems. Processing mining is a process management technique which helps users figure out business processes in a fast and objective manner by analyzing these data and automatically visualizing actual process flows. In particular, this study derives a process improvement plan and offers academic and practical implications through analysis on municipality data in the Netherlands.

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