A Framework for Cost-Aware Process Management: Cost Reporting and Cost Prediction
Moe Thandar Wynn (Queensland University of Technology, Australia)
Wei Zhe Low (Queensland University of Technology, Australia)
Arthur H. M. ter Hofstede (Queensland University of Technology, Australia)
Wiebe Nauta (Eindhoven University of Technology, The Netherlands)
Abstract: Organisations are constantly seeking efficiency gains for their business processes in terms of time and cost. Management accounting enables detailed cost reporting of business operations for decision making purposes, although significant effort is required to gather accurate operational data. Process mining, on the other hand, may provide valuable insight into processes through analysis of events recorded in logs by IT systems, but its primary focus is not on cost implications. In this paper, a framework is proposed which aims to exploit the strengths of both fields in order to better support management decisions on cost control. This is achieved by automatically merging cost data with historical data from event logs for the purposes of monitoring, predicting, and reporting process-related costs. The on-demand generation of accurate, relevant and timely cost reports, in a style akin to reports in the area of management accounting, will also be illustrated. This is achieved through extending the open-source process mining framework ProM.
Keywords: business process management, cost prediction, cost reporting, management accounting, process mining