A Guidance System for Business Process Flexibility

Asma Mejri, Sonia Ayachi Ghannouch, Ricardo Martinho

2017

Abstract

During the last decades, flexibility has gained a strong presence, in a variety of disciplines, mainly in the BPM field. The real challenge for BPM consists in providing modeling paradigms and BPMSs with adequate information and features to deal with the often conflicting requirements of flexibility. In this setting, we focus on providing a guidance approach for enhancing business process flexibility. Our purpose is therefore to perceive which modeling paradigm(s) and/or business process management system(s) (BPMS(s)) are the most adequate to the specific organization needs in terms of flexibility. This approach was implemented in a plug-in named BPFlexGuide. To evaluate this approach, we have studied the emergency care (EC) process. Users interested in the EC process were guided to use the AristaFlow BPM suite BPMS. The results of this study would help designers to choose the best paradigms and BPMS that best fit their needs on flexibility.

References

  1. Barba, I., Weber, B., Del Valle, C., and Jiménez-Ramírez, A. (2013). User recommendations for the optimized execution of business processes. Data & Knowledge Engineering, 86:61-84.
  2. Cingil, I., Ozturan, M., and Erdem, A. S. (2012). A decision support system for evaluation of business process management systems. International Information Institute (Tokyo). Information, 15(2):537.
  3. Conforti, R., de Leoni, M., La Rosa, M., van der Aalst, W. M., and ter Hofstede, A. H. (2015). A recommendation system for predicting risks across multiple business process instances. Decision Support Systems, 69:1-19.
  4. Günther, C. W. and Rozinat, A. (2012). Disco: Discover your processes. BPM (Demos), 940:40-44.
  5. Huang, Z., Lu, X., and Duan, H. (2012). Using recommendation to support adaptive clinical pathways. Journal of medical systems, 36(3):1849-1860.
  6. Kirchner, K., Herzberg, N., Rogge-Solti, A., and Weske, M. (2013). Embedding conformance checking in a process intelligence system in hospital environments. In Process Support and Knowledge Representation in Health Care, pages 126-139. Springer.
  7. Koschmider, A., Hornung, T., and Oberweis, A. (2011). Recommendation-based editor for business process modeling. Data & Knowledge Engineering, 70(6):483-503.
  8. Lenz, R. and Reichert, M. (2007). It support for healthcare processes-premises, challenges, perspectives. Data & Knowledge Engineering, 61(1):39-58.
  9. Mendling, J., Reijers, H. A., and van der Aalst, W. M. (2010). Seven process modeling guidelines (7pmg). Information and Software Technology, 52(2):127- 136.
  10. Mertens, S., Gailly, F., and Poels, G. (2014). Generating business process recommendations with a populationbased meta-heuristic. In Business Process Management Workshops, pages 516-528. Springer.
  11. Pesic, M. (2008). Constraint-based workflow management systems: shifting control to users. PhD thesis, Technische Universiteit Eindhoven.
  12. Raj Kumar, R. V. (2012). Classification algorithms for data mining: A survey. International Journal of Innovations in Engineering and Technology (IJIET).
  13. Regev, G., Soffer, P., and Schmidt, R. (2006). Taxonomy of flexibility in business processes. In BPMDS.
  14. Schonenberg, H., Weber, B., Van Dongen, B., and Van der Aalst, W. (2008). Supporting flexible processes through recommendations based on history. In Business process management, pages 51-66. Springer.
  15. Setiawan, M. A., Sadiq, S., and Kirkman, R. (2011). Facilitating business process improvement through personalized recommendation. In Business Information Systems, pages 136-147. Springer.
  16. Sun, X., Liu, X.-Z., Jiao, W.-P., Huang, G., and Mei, H. (2006). A rule-based approach to supporting adaptable web service composition. CHINESE JOURNAL OF COMPUTERS-CHINESE EDITION-, 29(7):1084.
  17. Thomas, K., Oliver, M., Jens, P., Maximilian, R., vom Brocke, J., Schmiedel, T., Recker, J., Trkman, P., Mertens, W., and Viaene, S. (2014). Ten principles of good business process management. Business Process Management Journal, 20(4):530-548.
  18. Van der Aalst, W. M., Weske, M., and Grünbauer, D. (2005). Case handling: a new paradigm for business process support. Data & Knowledge Engineering, 53(2):129-162.
  19. Verbeek, H., Buijs, J. C., Van Dongen, B. F., and Van Der Aalst, W. M. (2010a). Xes, xesame, and prom 6. In Information Systems Evolution, pages 60-75. Springer.
  20. Verbeek, H. M. W., Buijs, J. C. A. M., van Dongen, B. F., and van der Aalst, W. M. P. (2010b). Prom 6: The process mining toolkit. In Proc. of BPM Demonstration Track 2010, volume 615, pages 34-39. CEURWS.org.
  21. Yao, W. and Kumar, A. (2013). Conflexflow: Integrating flexible clinical pathways into clinical decision support systems using context and rules. Decision Support Systems, 55(2):499-515.
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Paper Citation


in Harvard Style

Mejri A., Ayachi Ghannouch S. and Martinho R. (2017). A Guidance System for Business Process Flexibility . In Proceedings of the 12th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE, ISBN 978-989-758-250-9, pages 210-217. DOI: 10.5220/0006316902100217


in Bibtex Style

@conference{enase17,
author={Asma Mejri and Sonia Ayachi Ghannouch and Ricardo Martinho},
title={A Guidance System for Business Process Flexibility},
booktitle={Proceedings of the 12th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE,},
year={2017},
pages={210-217},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006316902100217},
isbn={978-989-758-250-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 12th International Conference on Evaluation of Novel Approaches to Software Engineering - Volume 1: ENASE,
TI - A Guidance System for Business Process Flexibility
SN - 978-989-758-250-9
AU - Mejri A.
AU - Ayachi Ghannouch S.
AU - Martinho R.
PY - 2017
SP - 210
EP - 217
DO - 10.5220/0006316902100217