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Pacific Rim Knowledge Acquisition Workshop

PKAW 2018: Knowledge Management and Acquisition for Intelligent Systems pp 170–183Cite as

Automated Business Process Discovery and Analysis for the International Higher Education Industry

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11016))

Abstract

The international education sector in Australia expects a rise in demand for higher education programs in the future. This increase drives universities to monitor and continuously improve their business processes. Automated Business Process Discovery or Process Mining helps organisations create a business process graphical representation or process model, leveraging data from their information systems. The lack of a business process model and inefficiency in harnessing process data deters fact-based process improvement decision-making, impacting a company’s operations. Within the international education context, Process Mining can help discover, analyze, manage and improve processes efficiently and deal with increasing market demand of international student enrolments. Here we have used the Process Mining Methodology Framework for Discovery Analysis focusing on Control-flow and Case Data perspectives. We highlight challenges encountered in process data extraction and preparation as well as performance analysis to identify potential bottlenecks.

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References

  1. van der Aalst, W.M.P., ter Hofstede, A.H.M., Weske, M.: Business process management: a survey. In: van der Aalst, W.M.P., Weske, M. (eds.) BPM 2003. LNCS, vol. 2678, pp. 1–12. Springer, Heidelberg (2003). https://doi.org/10.1007/3-540-44895-0_1

    Chapter  MATH  Google Scholar 

  2. Tiwari, A., Turner, C.J., Majeed, B.: A review of business process mining: state-of-the-art and future trends. Bus. Process Manag. J. 14, 5–22 (2008)

    Article  Google Scholar 

  3. van der Aalst, W., et al.: Process mining manifesto. In: IEEE Task Force on Process Mining, pp. 1–19 (2012)

    Google Scholar 

  4. van der Aalst, W.M.P.: Getting the data. In: van der Aalst, W.M.P. (ed.) Process Mining: Discovery, Conformance and Enhancement of Business Processes, pp. 95–123. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-19345-3_4

    Chapter  MATH  Google Scholar 

  5. De Weerdt, J., Schupp, A., Vanderloock, A., Baesens, B.: Process Mining for the multi-faceted analysis of business processes—a case study in a financial services organization. Comput. Ind. 64, 57–67 (2013)

    Article  Google Scholar 

  6. van der Aalst, W.M.P., Reijers, H.A., Weijters, A.J.M.M., van Dongen, B.F., Alves de Medeiros, A.K., Song, M., Verbeek, H.M.W.: Business process mining: an industrial application. Inf. Syst. 32, 713–732 (2007)

    Article  Google Scholar 

  7. Deloitte Access Economics, Growth and Opportunity in Australian International Education, pp. 1–95. Austrade, Melbourne (2015)

    Google Scholar 

  8. Davenport, T.H., Short, J.E.: The new industrial engineering: information technology and business process redesign. Sloan Manag. Rev. 31, 11 (1990)

    Google Scholar 

  9. Papazoglou, M.P., Ribbers, P.: e-Business: Organizational and Technical Foundations. Wiley, Chichester (2006)

    Google Scholar 

  10. Hammer, M.: What is business process management? In: Vom Brocke, J., Rosemann, M. (eds.) Handbook on Business Process Management, pp. 3–16. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-00416-2_1

    Chapter  Google Scholar 

  11. Hung, R.Y.-Y.: Business process management as competitive advantage: a review and empirical study. Total Qual. Manag. Bus. Excell. 17, 21–40 (2006)

    Article  Google Scholar 

  12. Harrington, H.J.: Business Process Improvement: The Breakthrough Strategy for Total Quality, Productivity, and Competitiveness. McGraw-Hill, New York (1991)

    Google Scholar 

  13. van der Aalst, W.M.P., Weijters, T., Maruster, L.: Workflow mining: discovering process models from event logs. IEEE Trans. Knowl. Data Eng. 16, 1128–1142 (2004)

    Article  Google Scholar 

  14. van der Aalst, W.M.P.: Extracting event data from databases to unleash process mining. In: vom Brocke, J., Schmiedel, T. (eds.) BPM - Driving Innovation in a Digital World, pp. 105–128. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-14430-6_8

    Chapter  Google Scholar 

  15. Mans, R., Reijers, H., Berends, H., Bandara, W., Rogier, P.: Business process mining success. In: Proceedings of the 21st European Conference on Information Systems, AIS Electronic Library (AISeL), Utrecht University, The Netherlands (2013)

    Google Scholar 

  16. Jutten, M.G.: The Fit Between Business Processes and Process Mining Related Activities: A Process Mining Success Model (2015)

    Google Scholar 

  17. van der Aalst, W.: Business alignment: using process mining as a tool for Delta analysis and conformance testing. Requir. Eng. 10, 198–211 (2005)

    Article  Google Scholar 

  18. Porter, M.E.: The Value Chain and Competitive Advantage (Extract). Free Press, New York (1985)

    Google Scholar 

  19. Burattin, A.: Introduction to business processes, BPM, and BPM systems. In: Burattin, A. (ed.) Process Mining Techniques in Business Environments: Theoretical Aspects, Algorithms, Techniques and Open Challenges in Process Mining. LNBIP, vol. 207, pp. 11–21. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-17482-2_2

    Chapter  Google Scholar 

  20. Siha, S.M., Saad, G.H.: Business process improvement: empirical assessment and extensions. Bus. Process Manag. J. 14, 778–802 (2008)

    Article  Google Scholar 

  21. van der Aalst, W.M.P., La Rosa, M., Santoro, F.M.: Business process management. Bus. Inf. Syst. Eng. 58, 1–6 (2016)

    Article  Google Scholar 

  22. van der Aalst, W.M.P.: Trends in business process analysis: from verification to process mining. In: Cardoso, J., Cordeiro, J., Filipe, J. (eds.) Proceedings of the 9th International Conference on Enterprise Information Systems (ICEIS 2007), pp. 12–22. Institute for Systems and Technologies of Information, Control and Communication, INSTICC, Medeira, Portugal (2007)

    Google Scholar 

  23. Medeiros, A.K.A.: Process mining: extending the α-algorithm to mine short loops. In: Beta, Research School for Operations Management and Logistics (2004)

    Google Scholar 

  24. van der Aalst, W.M.P.: Process mining: overview and opportunities. ACM Trans. Manag. Inf. Syst. (TMIS) 3, 1–17 (2012)

    Article  Google Scholar 

  25. Ly, L.T., Indiono, C., Mangler, J., Rinderle-Ma, S.: Data transformation and semantic log purging for process mining. In: Ralyté, J., Franch, X., Brinkkemper, S., Wrycza, S. (eds.) CAiSE 2012. LNCS, vol. 7328, pp. 238–253. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-31095-9_16

    Chapter  Google Scholar 

  26. Bozkaya, M., Gabriels, J., van der Werf, J.M.: Process diagnostics: a method based on process mining. In: 2009 International Conference on Information, Process, and Knowledge Management, pp. 22–27 (2009)

    Google Scholar 

  27. Jans, M., van der Werf, J.M., Lybaert, N., Vanhoof, K.: A business process mining application for internal transaction fraud mitigation. Expert Syst. Appl. 38, 13351–13359 (2011)

    Article  Google Scholar 

  28. Department of Education Employment and Workplace Relations, National Code of Practice for Registration Authorities and Providers of Education and Training to Overseas Students 2007. In: Australian Government (ed.) ACT, pp. 1–34 (2007)

    Google Scholar 

  29. Agresti, A., Franklin, C.A. (eds.): Statistics: The Art and Science of Learning from Data, 2nd edn. Pearson Prentice Hall, Upper Saddle River (2009)

    Google Scholar 

  30. Medeiros, A.K.A., Weijters, A.J.M.M.: ProM Framework Tutorial, p. 41. Technische Universiteit Eindhoven, Eindhoven, The Netherlands (2009)

    Google Scholar 

  31. Verbeek, H.M.W., Buijs, J.C.A.M., van Dongen, B.F., van der Aalst, Wil M.P.: XES, XESame, and ProM 6. In: Soffer, P., Proper, E. (eds.) CAiSE Forum 2010. LNBIP, vol. 72, pp. 60–75. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-17722-4_5

    Chapter  Google Scholar 

  32. Burattin, A.: data mining for information system data. In: Burattin, A. (ed.) Process Mining Techniques in Business Environments: Theoretical Aspects, Algorithms, Techniques and Open Challenges in Process Mining. LNBIP, vol. 207, pp. 27–32. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-17482-2_4

    Chapter  Google Scholar 

  33. De Weerdt, J., De Backer, M., Vanthienen, J., Baesens, B.: A multi-dimensional quality assessment of state-of-the-art process discovery algorithms using real-life event logs. Inf. Syst. 37, 654–676 (2012)

    Article  Google Scholar 

  34. van Dongen, B.F., Alves de Medeiros, A.K., Wen, L.: Process mining: overview and outlook of petri net discovery algorithms. In: Jensen, K., van der Aalst, W.M.P. (eds.) Transactions on Petri Nets and Other Models of Concurrency II: Special Issue on Concurrency in Process-Aware Information Systems. LNCS, vol. 5460, pp. 225–242. Springer, Heidelberg (2009). https://doi.org/10.1007/978-3-642-00899-3_13

    Chapter  Google Scholar 

  35. Han, J., Kamber, M. (eds.): Data Mining: Concepts and Techniques, 2nd edn. Elsevier/Morgan Kaufmann, Amsterdam, Boston/San Francisco (2006)

    MATH  Google Scholar 

  36. van der Aalst, W.M., Van Dongen, B.F., Günther, C.W., Mans, R.S., de Medeiros, A.A., Rozinat, A., Song, M., Verbeek, H.M.W., Weijters, A.J.M.M.: Process mining with ProM. In: Proceedings of the 19th Belgium-Netherlands Conference on Artificial Intelligence, Belgium-Netherlands (2007)

    Google Scholar 

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Author information

Authors and Affiliations

  1. AlphaSys Pty Ltd., Sydney, NSW, 2000, Australia

    Juan Gonzalez-Dominguez

  2. Department of Computing, Macquarie University, Marsfield, NSW, 2109, Australia

    Peter Busch

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  1. Juan Gonzalez-Dominguez
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  2. Peter Busch
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Correspondence to Juan Gonzalez-Dominguez .

Editor information

Editors and Affiliations

  1. University of Tsukuba , Tokyo, Japan

    Kenichi Yoshida

  2. Shih Chien University, Taipei City, Taiwan

    Maria Lee

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Gonzalez-Dominguez, J., Busch, P. (2018). Automated Business Process Discovery and Analysis for the International Higher Education Industry. In: Yoshida, K., Lee, M. (eds) Knowledge Management and Acquisition for Intelligent Systems. PKAW 2018. Lecture Notes in Computer Science(), vol 11016. Springer, Cham. https://doi.org/10.1007/978-3-319-97289-3_13

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  • DOI: https://doi.org/10.1007/978-3-319-97289-3_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-97288-6

  • Online ISBN: 978-3-319-97289-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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