How Close to Reality is the „as-is” Business Process Simulation Model?

• Authors: Bartlomiej Gawin , Bartosz Marcinkowski
• Languages of publication: EN

Abstracts

EN

Background and Purpose: Business process simulation (BPS) model is based on real-life data form sources like databases, observations and interviews. It acts as “as-is” business scenario can used for reengineering. The main challenge is to gather relevant data and to develop simulation model. Research aims to elaborate BPS model and to systematically assess how close to reality it is. Design/Methodology/Approach: The research has been performed in Polish telecommunications company. Authors investigate technical process of expanding cellular network. After elaborating “as-is” model, authors use ADONIS simulation tool to run a series simulations and confront simulation results with actual historical events. After this, assessment whether computer simulation model can precisely map real-life business process - and consequently act as credible basis for process improvement - is made. Results: The simulation model has been constructed with data from the WfMS database, observations, staff knowledge and their experience. Fully equipped simulation model is found to allow reconstructing the historical execution of business activity with low margin for error. Some limitation were identified and discussed. Conclusion: BPS is not a popular approach for process reengineering and improvement yet. Data collection issues for BPS that require adopting process mining techniques and additional information sources are among the reasons for that. In our study, computer simulation outputs are compatible with historical events. Hence the model reflects the business reality and can be taken as a reference model while redesigning the process.

Keywords

EN

business process; business process simulations; data acquisition; workflow systems

• Publisher: Sciendo
• Journal: Organizacija
• Year: 2015
• Volume: 48
• Issue: 3
• Pages: 155-175

Dates

published

2015-08-01

received

2015-05-25

revised

2015-06-27

accepted

2015-07-10

online

2015-08-14

Contributors

author

Bartlomiej Gawin

• University of Gdansk, Department of Business Informatics, Piaskowa 9, 81-864 Sopot, Poland

author

Bartosz Marcinkowski

• University of Gdansk, Department of Business Informatics, Piaskowa 9, 81-864 Sopot, Poland

References

• Barnett, M. (2003). Modeling & simulation in business process management. Austin: Gensym Corporation.
• Becker, J., Kugeler, M., & Rosemann, M. (eds.). (2013). Process management: a guide for the design of business processes. Berlin Heidelberg: Springer.
• BOC Group (2012), Adonis 5.0. Part 2: User Manual. Vienna: BOC Group.
• Bosilj-Vuksic, V., Ceric, V., & Hlupic, V. (2007). Criteria for the evaluation of business process simulation tools. Interdisciplinary Journal of Information, Knowledge, and Management, 2, 73-88.
• Bradley, P., Browne, J., Jackson, S., & Jagdev, H. (1995). Business process re-engineering (BPR) - a study of the software tools currently available. Computers in Industry, 25(3), 309-330, http://dx.doi.org/10.1016/0166-3615(94)00044-Q
• De Medeiros, A. A., Van Dongen, B. F., Van der Aalst, W. M., & Weijters, A. J. (2004). Process mining: extending the alpha-algorithm to mine short loops. BETA Working Paper Series, WP 113, Eindhoven: Eindhoven University of Technology.
• De Weerdt, J., Schupp, A., Vanderloock, A., & Baesens, B. (2013). Process Mining for the multi-faceted analysis of business processes-A case study in a financial services organization. Computers in Industry, 64(1), 57-67, http://dx.doi.org/10.1016/j.compind.2012.09.010
• Gawin, B. (2009). Processes Mining Techniques and Organizational Aspects of a Workflow Database. In Aidemark, J., Carlsson, S., & Cronquist, B. (eds.) Perspectives in Business Informatics Research, The Eight International Conference on, 01-02 October (pp. 167-174). Kristianstad: Kristianstad Academic Press.
• Gawin, B., & Marcinkowski, B. (2013). Symulacja procesów biznesowych. Standardy BPMS i BPMN w praktyce [Simulating Business Processes. BPMS and BPMN Standards Applied] Gliwice: Helion.
• Gray, D. E. (2013). Doing research in the real world. Third Edition. Los Angeles: Sage.
• Gunther, C. W., & Van der Aalst, W. M. (2006). A generic import framework for process event logs. In Eder, J., & Dustdar, S. (eds.). Business Process Management Workshops, September 4-7 (pp. 81-92). Berlin Heidelberg: Springer.
• Gunther, C. W., & Van der Aalst, W. M. (2007). Fuzzy mining-adaptive process simplification based on multi-perspective metrics. In Alonso, G., Dadam, P., & Rosemann, M. (eds). Business Process Management (pp. 328-343). Berlin Heidelberg: Springer.
• Hammer, M., & Champy, J. (1993). Reengineering the corporation: A manifesto for business revolution. Business Horizons, 36(5), 90-91, http://dx.doi.org/10.1016/S0007-6813(05)80064-3
• Hauser, K. (2007). Simulation of business re-engineering processes: Case study of a United States motor manufacturing company. International Journal of Management, 24(4), 676.
• Hlupic, V., & De Vreede, G. J. (2005). Business process modelling using discrete-event simulation: current opportunities and future challenges. International Journal of Simulation and Process Modelling, 1(1-2), 72-81, http://dx.doi.org/10.1504/IJSPM.2005.007115
• Jaklic, J., & Stemberger, M. I. (2005). A methodology for a business process change in public sector. In: Vorisek, J. (ed.). Proceedings of 13th International Conference Systems Integration 2005, June 13 (pp. 38-47). Prague: Prague University of Economics.
• Jansen-Vullers, M., & Netjes, M. (2006). Business process simulation - a tool survey. In Jensen, K. (ed.). Seventh Workshop and Tutorial on Practical Use of Coloured Petri Nets and the CPN Tools, October 24-26 (pp. 77-96). Aarhus: University of Aarhus.
• Johnston, S. (2004). Rational UML Profile for business modeling. IBM Developer Works. Retrieved from http://www.ibm.com/developerworks/rational/library/5167.html
• Marcinkowski, B., & Gawin, B. (2014). Enterprise Processes Simulated - Prerequisites, Data Acquisition Methods and Tool Support. Journal of Management and Finance, 12(3/2), 287-303.
• Mayer, R. J., Menzel, C. P., Painter, M. K., Dewitte, P. S., Blinn, T., & Perakath, B. (1995). Information integration for concurrent engineering (IICE) IDEF3 process description capture method report (No. KBSI-IICE-90-STR-01-0592-02). Knowledge Based Systems Inc.
• Moen, R., & Norman, C. (2006). Evolution of the PDCA cycle. Retrieved from http://pkpinc.com/files/NA-01MoenNormanFullpaper.pdf
• Object Management Group (2013). Business Process Model and Notation (BPMN). Version 2.0.1, http://www.omg.org/spec/BPMN
• Rozinat, A., Wynn, M. T., Van der Aalst, W. M., Ter Hofstede, A. H., & Fidge, C. J. (2009). Workflow simulation for operational decision support. Data & Knowledge Engineering, 68(9), 834-850, http://dx.doi.org/10.1016/j.datak.2009.02.014
• Russell, N., Van der Aalst, W. M., Ter Hofstede, A. H., & Edmond, D. (2005). Workflow resource patterns: Identification, representation and tool support. In Pastor, O., Falcao e Cunha, J. (eds.). Advanced Information Systems Engineering (pp. 216-232). Berlin Heidelberg: Springer.
• Scheer, A. W. (1993). Architecture of integrated information systems (ARIS). In Proceedings of the JSPE/IFIP TC5/WG5. 3 Workshop on the Design of Information Infrastructure Systems for Manufacturing (pp. 85-99). Amsterdam: North-Holland Publishing Co.
• Song, M., & Van der Aalst, W. M. (2008). Towards comprehensive support for organizational mining. Decision Support Systems, 46(1), 300-317, http://dx.doi.org/10.1016/j.dss.2008.07.002
• Srivastava S. (2010). Process Modeling & Simulation. Wipro Technologies, Retrieved from http://www.wipro.com/Documents/resource-center/library/process-modeling-simulation.pdf
• Suzuki, Y., Yahyaei, M., Jin, Y., Koyama, H., & Kang, G. (2012). Simulation based process design: Modeling and applications. Advanced Engineering Informatics, 26(4), 763-781, http://dx.doi.org/10.1016/j.aei.2012.06.002
• Sztumski J. (2010), Wstęp do metod i technik badań społecznych. Wydanie 7 [Introduction to Methods and Techniques of Social Research. 7th Edition], Silesia Science Publishing.
• Tarumi, H., Matsuyama, T., & Kamabayashi, Y. (1999). Evolution of business processes and a process simulation tool. In Software Engineering Conference, 1999. (APSEC’99) Proceedings. Sixth Asia Pacific, December 07-10 (pp. 180-187). IEEE.
• Teubner, C., McNabb, K., & Levitt, D. (2008). Case study: quest uses process simulation to move at the speed of business change. Forrester Research.
• Van der Aalst, W. (2007). BPM and Workflow Analysis. BPTrends, 5(4), 1-2.
• Van der Aalst, W. M. (2010). Business process simulation revisited. In Barjis , J. (ed). Enterprise and Organizational Modeling and Simulation (pp. 1-14). Berlin Heidelberg: Springer.
• Van der Aalst, W. M., Reijers, H. A., & Song, M. (2005). Discovering social networks from event logs. Computer Supported Cooperative Work (CSCW), 14(6), 549-593, http://dx.doi.org/10.1007/s10606-005-9005-9
• Van der Aalst, W. M., Reijers, H. A., Weijters, A. J., Van Dongen, B. F., De Medeiros, A. A., Song, M., & Verbeek, H. M. W. (2007). Business process mining: An industrial application. Information Systems, 32(5), 713-732, http://dx.doi.org/10.1016/j.is.2006.05.003
• Van der Aalst, W. M., Ter Hofstede, A. H., & Weske, M. (2003). Business process management: A survey. In Van der Aalst, W. M., Ter Hofstede, A. H., & Weske, M. (eds.).Business process management (pp. 1-12). Berlin Heidelberg : Springer.
• Van der Aalst, W., Weijters, T., & Maruster, L. (2004). Workflow mining: Discovering process models from event logs. Knowledge and Data Engineering, IEEE Transactions on, 16(9), 1128-1142, http://dx.doi.org/10.1109/TKDE.2004.47
• Weijters, A. J. M. M., & Ribeiro, J. T. S. (2011). Flexible heuristics miner (FHM). In Computational Intelligence and Data Mining (CIDM), 2011 IEEE Symposium on, Paris, April 11-15 (pp. 310-317). IEEE.

Identifiers

DOI

10.1515/orga-2015-0013