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Bot Log Mining: Using Logs from Robotic Process Automation for Process Mining

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Conceptual Modeling (ER 2020)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12400))

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Abstract

Robotic Process Automation (RPA) is an emerging technology for automating tasks using bots that can mimic human actions on computer systems. Most existing research focuses on the earlier phases of RPA implementations, e.g. the discovery of tasks that are suitable for automation. To detect exceptions and explore opportunities for bot and process redesign, historical data from RPA-enabled processes in the form of bot logs or process logs can be utilized. However, the isolated use of bot logs or process logs provides only limited insights and not a good understanding of an overall process. Therefore, we develop an approach that merges bot logs with process logs for process mining. A merged log enables an integrated view on the role and effects of bots in an RPA-enabled process. We first develop an integrated data model describing the structure and relation of bots and business processes. We then specify and instantiate a ‘bot log parser’ translating bot logs of three leading RPA vendors into the XES format. Further, we develop the ‘log merger’ functionality that merges bot logs with logs of the underlying business processes. We further introduce process mining measures allowing the analysis of a merged log.

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References

  1. van der Aalst, W.: Process Mining: Discovery, Conformance and Enhancement of Business Processes, vol. 2. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-19345-3

    Book  MATH  Google Scholar 

  2. van der Aalst, W., et al.: Process mining manifesto. In: Daniel, F., Barkaoui, K., Dustdar, S. (eds.) BPM 2011. LNBIP, vol. 99, pp. 169–194. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-28108-2_19

    Chapter  Google Scholar 

  3. van der Aalst, W.M., Bichler, M., Heinzl, A.: Robotic process automation. Bus. Inf. Syst. Eng. 60, 269–272 (2018). https://doi.org/10.1007/s12599-018-0542-4

    Article  Google Scholar 

  4. Agostinelli, S., Marrella, A., Mecella, M.: Towards intelligent robotic process automation for BPMers. arXiv preprint arXiv:2001.00804 (2020)

  5. Andrews, R., et al.: Quality-informed semi-automated event log generation for process mining. In: DSS, p. 113265 (2020)

    Google Scholar 

  6. Bayomie, D., Di Ciccio, C., La Rosa, M., Mendling, J.: A probabilistic approach to event-case correlation for process mining. In: Laender, A.H.F., Pernici, B., Lim, E.-P., de Oliveira, J.P.M. (eds.) ER 2019. LNCS, vol. 11788, pp. 136–152. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-33223-5_12

    Chapter  Google Scholar 

  7. Deloitte: The robots are ready. are you? Untapped advantage in your digital workforce (2017). https://www2.deloitte.com/content/dam/Deloitte/tr/Documents/technology/deloitte-robots-are-ready.pdf

  8. van Dongen, B.F., de Medeiros, A.K.A., Verbeek, H.M.W., Weijters, A.J.M.M., van der Aalst, W.M.P.: The ProM framework: a new era in process mining tool support. In: Ciardo, G., Darondeau, P. (eds.) ICATPN 2005. LNCS, vol. 3536, pp. 444–454. Springer, Heidelberg (2005). https://doi.org/10.1007/11494744_25

    Chapter  Google Scholar 

  9. Enríquez, J., et al.: Robotic process automation: a scientific and industrial systematic mapping study. IEEE Access 8, 39113–39129 (2020)

    Article  Google Scholar 

  10. Gao, J., van Zelst, S.J., Lu, X., van der Aalst, W.M.P.: Automated robotic process automation: a self-learning approach. In: Panetto, H., Debruyne, C., Hepp, M., Lewis, D., Ardagna, C.A., Meersman, R. (eds.) OTM 2019. LNCS, vol. 11877, pp. 95–112. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-33246-4_6

    Chapter  Google Scholar 

  11. Geyer-Klingeberg, J., Nakladal, J., Baldauf, F., Veit, F.: Process mining and robotic process automation: a perfect match. In: BPM (Dissertation/Demos/Industry), pp. 124–131 (2018)

    Google Scholar 

  12. Günther, C., Verbeek, H.: XES v2.0 (2014). http://www.xes-standard.org/

  13. Halpin, T.: ORM 2 graphical notation. Technical Report ORM2-02 (2005)

    Google Scholar 

  14. Ivančić, L., Vugec, D.S., Vukšić, V.B.: Robotic process automation: systematic literature review. In: Di Ciccio, C., et al. (eds.) BPM 2019. LNBIP, vol. 361, pp. 280–295. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-30429-4_19

    Chapter  Google Scholar 

  15. Jimenez-Ramirez, A., Reijers, H.A., Barba, I., Del Valle, C.: A method to improve the early stages of the robotic process automation lifecycle. In: Giorgini, P., Weber, B. (eds.) CAiSE 2019. LNCS, vol. 11483, pp. 446–461. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-21290-2_28

    Chapter  Google Scholar 

  16. Kirchmer, M., Franz, P.: Value-driven robotic process automation (RPA). In: Shishkov, B. (ed.) BMSD 2019. LNBIP, vol. 356, pp. 31–46. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-24854-3_3

    Chapter  Google Scholar 

  17. Lacity, M., Willcocks, L.P., Craig, A.: Robotic process automation at Telefonica O2 (2015)

    Google Scholar 

  18. Le Clair, C., UiPath, A.A., Prism, B.: The Forrester wave™: robotic process automation, Q2 2018. Forrester Research (2018)

    Google Scholar 

  19. Leemans, S.J., Poppe, E., Wynn, M.T.: Directly follows-based process mining: exploration & a case study. In: ICPM, pp. 25–32 (2019)

    Google Scholar 

  20. Leno, V., Polyvyanyy, A., Dumas, M., La Rosa, M., Maggi, F.M.: Robotic process mining: vision and challenges. In: BISE, pp. 1–14 (2020)

    Google Scholar 

  21. Leno, V., et al.: Action logger: enabling process mining for robotic process automation. In: BPM Demos, pp. 124–128 (2019)

    Google Scholar 

  22. Leopold, H., van der Aa, H., Reijers, H.A.: Identifying candidate tasks for robotic process automation in textual process descriptions. In: Gulden, J., Reinhartz-Berger, I., Schmidt, R., Guerreiro, S., Guédria, W., Bera, P. (eds.) BPMDS/EMMSAD -2018. LNBIP, vol. 318, pp. 67–81. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-91704-7_5

    Chapter  Google Scholar 

  23. Linn, C., Zimmermann, P., Werth, D.: Desktop activity mining-a new level of detail in mining business processes. In: APSN Workshops (2018)

    Google Scholar 

  24. Madakam, S., Holmukhe, R.M., Jaiswal, D.K.: The future digital work force: robotic process automation (RPA). JISTEM 16, 1–17 (2019)

    Article  Google Scholar 

  25. Pourmirza, S., et al.: Correlation miner: mining business process models and event correlations without case identifiers. IJCIS 26(02), 1742002 (2017)

    Google Scholar 

  26. Slaby, J.R.: Robotic automation emerges as a threat to traditional low-cost outsourcing. HfS Res. Ltd 1(1), 3 (2012)

    Google Scholar 

  27. Syed, R., et al.: Robotic process automation: contemporary themes and challenges. CI 115, 103162 (2020)

    Google Scholar 

  28. Tornbohm, C., Dunie, R.: Gartner market guide for robotic process automation software. Report G00319864. Gartner (2017)

    Google Scholar 

  29. Willcocks, L.P., Lacity, M., Craig, A.: Robotic process automation at Xchanging (2015)

    Google Scholar 

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Author information

Authors and Affiliations

  1. FIM Research Center, University of Augsburg, Project Group Business and Information Systems Engineering of the Fraunhofer FIT, Augsburg, Germany

    Andreas Egger

  2. FIM Research Center, University of Bayreuth, Project Group Business and Information Systems Engineering of the Fraunhofer FIT, Bayreuth, Germany

    Wolfgang Kratsch & Maximilian Röglinger

  3. Queensland University of Technology, Brisbane, Australia

    Arthur H. M. ter Hofstede, Sander J. J. Leemans & Moe Thandar Wynn

Authors
  1. Andreas Egger
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  2. Arthur H. M. ter Hofstede
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  3. Wolfgang Kratsch
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  4. Sander J. J. Leemans
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  5. Maximilian Röglinger
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  6. Moe Thandar Wynn
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Corresponding author

Correspondence to Andreas Egger .

Editor information

Editors and Affiliations

  1. University of Auckland, Auckland, New Zealand

    Gillian Dobbie

  2. University of Duisburg-Essen, Essen, Germany

    Ulrich Frank

  3. TU Wien, Vienna, Austria

    Gerti Kappel

  4. Brigham Young University, Provo, UT, USA

    Stephen W. Liddle

  5. University of Klagenfurt, Klagenfurt am Wörthersee, Austria

    Heinrich C. Mayr

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Egger, A., ter Hofstede, A.H.M., Kratsch, W., Leemans, S.J.J., Röglinger, M., Wynn, M.T. (2020). Bot Log Mining: Using Logs from Robotic Process Automation for Process Mining. In: Dobbie, G., Frank, U., Kappel, G., Liddle, S.W., Mayr, H.C. (eds) Conceptual Modeling. ER 2020. Lecture Notes in Computer Science(), vol 12400. Springer, Cham. https://doi.org/10.1007/978-3-030-62522-1_4

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  • DOI: https://doi.org/10.1007/978-3-030-62522-1_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-62521-4

  • Online ISBN: 978-3-030-62522-1

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