Business process modelling with stochastic networks

Aytulun S. K., GÜNERİ A. F.

INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, vol.46, no.10, pp.2743-2764, 2008 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 46 Issue: 10
  • Publication Date: 2008
  • Doi Number: 10.1080/00207540701543601
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.2743-2764
  • Keywords: business process modelling, business process reengineering, business process analysis, stochastic networks, FRAMEWORK
  • Yıldız Technical University Affiliated: Yes


Modelling and analysis of business processes is critical to identify current business processes and to understand the contributions of new processes to the system. The quality of the results obtained by modelling and analysis significantly influences the success of business process reengineering (BPR). Therefore, a constant development in techniques used in business process modelling (BPM) and business process analysis (BPA) is necessary. However, when these proposed techniques are analysed it becomes obvious that they repeat the same basic approach, although a few offer different visions. In BPM development studies, the use of time-activity scheduling is often considered secondary (even neglected). The reason for this is that process modelling may be considered as project management and remain under this label. Many organizations may use these techniques in managing their daily activities if the maturity level and the simplicity of project management techniques are considered. It also enables the modelling of stochastic situations, otherwise not possible to do by any BPM method. In this study an existing business process with network properties is analysed using project scheduling techniques. Thus, business processes are described as networks, modelled and timed by network properties and stochastically analysed using GERT, a project based process scheduling method. Finally the results obtained by GERT are examined using the PERT-path approach.