Abstract
Business process management and improvement are vital for enterprises in competitive environments. Understanding of a process is a pre-requisite and important step for improvement. Interaction between humans, computers, and business objects provide excellent opportunities for knowledge extraction. However, the specification of a framework is required for business process improvement, which extends from data collection, analytical methods, storage, and representation of knowledge. The process models conceived for information system development are not sufficient for post execution analysis and improvement. In this paper, we specify such a framework briefly and focus on providing representational support for business process improvement. The main objective is to improve the overall improvement process by providing enriched graphical process models. Furthermore, we use a case study to explain the proposed usage and extensions of an existing modeling language for business process improvement.
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References
van der Aalst, W., Weijters, A.: Process mining: A research agenda. Comput. Ind. 53, 231–244 (2004)
Kassem, G., Rautenstrauch, C.: Application usage mining to improve enterprise workflows: ERP systems SAP R/3 as example. In: Khosrow-Pour, M. (eds.) Managing Modern Organizations Through Information Technology. Information Resources Management Association pp. 358–362. (2005)
Lodhi, A., Köppen, V., Saake, G.: Business process modeling: Active research areas and challenges. Technical Report 1, University of Magdeburg, Germany (2011)
Vergidis, K., Tiwari, A., Majeed, B.: Business process analysis and optimization: Beyond reengineering. IEEE Trans. Syst. Man Cybern. Part C Appl. Rev. 38(1), 69–82 (2008)
Lodhi, A., Köppen, V., Saake, G.: Post execution analysis of business processes: Taxonomy and challenges. Technical Report 9, University of Magdeburg, Germany (2010)
BPMI.org, OMG: Business Process Modeling Notation Specification, Final Adopted Specification (2006)
Khan, A., Lodhi, A., Köppen, V., Kassem, G., Saake, G.: Applying process mining in SOA environments. In: Dan, A., Gittler, F., Toumani, F. (eds.) Service-Oriented Computing ICSOC Service Wave 2009 Workshops. Volume 6275 of Lecture Notes in Computer Science. pp. 293–302. Springer, New York (2010)
Ingvaldsen, J., Gulla, J.: Preprocessing support for large scale process mining of SAP transactions. Business Process Manag. Workshops 4928, 30–41 (2008)
van Dongen, B., van der Aalst, W.: A meta model for process mining data. In: Missikoff, M., Nicola, A.D. (eds.) Proceedings of the Open Interop Workshop on Enterprise Modelling and Ontologies for Interoperability, Co-located with CAiSE. Volume 160 of CEUR Workshop Proceedings. Porto, Portugal (2005). CEUR-WS.org
Günther, C., van der Aalst, W.: A generic import framework for process event logs. In: Eder, J., Dustdar, S. (eds.) Business Process Management Workshops, Workshop on Business Process Intelligence. vol. 4103, pp. 81–92. Springer, Berlin (2006)
zur Muehlen, M.: Business process analytics format (BPAF) Document Number WFMC-TC-1015. Workflow Management Coalition, USA (2008)
Grigori, D., Casati, F., Castellanos, M., Dayal, U., Sayal, M., Shan, M.C.: Business process intelligence. Comput. Ind. 53(3), 321–343 (2004)
Rozinat, A., van der Aalst, W.: Decision mining in ProM. In: International Conference on Business Process Management (BPM 2006), vol. 4102, pp. 420–425. Springer, Berlin (2006)
van der Aalst, W.: Business alignment: Using process mining as a tool for delta analysis and conformance testing. Requirement Eng. 10(3), 198–211 (2005)
van der Aalst, W., Reijers, H.A., Song, M.: Discovering social networks from event logs. Comput. Support. Coop. Work 14(6), 549–593 (2005)
Lodhi, A., Kassem, G., Köppen, V., Saake, G.: Investigation of graph mining for business processes. In: Proceedings of The International Conference on Intelligence and Information Technology ICIIT. vol. 2, pp. 293–297. IEEE Computer Society Lahore, Pakistan (2010)
Cumberlidge, M.: Business Process Management with JBoss jBPM: A Practical Guide for Business Analysts. Packt Publishing, Birmingham, UK (2007)
Scheer, A.W.: ARIS-Business Process Modeling. 2 edn. Springer, New York (1998)
IBM: Flowcharting techniques. Technical report, IBM Data Processing Techniques. Yorktown Heights, New York (1969)
Booch, G., Rumbaugh, J., Jacobson, I.: Unified Modeling Language User Guide. 2 edn. Addison-Wesley, Boston, MA (2005)
Vullers, M.J., Kleingeld, P., Loosschilder, M., Reijers, H.A.: Performance measures to evaluate the impact of best practices. In: Proceedings of Workshops and Doctoral Consortium of the 19th International Conference on Advanced Information Systems Engineering (BPMDS), pp. 359–368. Tapir Academic Press, Trondheim (2007)
Acknowledgments
Azeem Lodhi is supported by a grant from the federal state of Saxony-Anhalt in Germany. This work is partially supported by the German Ministry of Education and Science (BMBF), within the ViERforES-II project No. 01IM10002B.
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Lodhi, A., Köppen, V., Saake, G. (2013). Business Process Improvement Framework and Representational Support. In: Kudělka, M., Pokorný, J., Snášel, V., Abraham, A. (eds) Proceedings of the Third International Conference on Intelligent Human Computer Interaction (IHCI 2011), Prague, Czech Republic, August, 2011. Advances in Intelligent Systems and Computing, vol 179. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31603-6_14
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DOI: https://doi.org/10.1007/978-3-642-31603-6_14
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