Published Nov 26, 2015



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Hugo Santiago Aguirre Mayorga

Nicolas Rincón García

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Abstract

Process mining is the discipline that aims at discovering, monitoring
and improving business processes by analyzing event logs recorded
by an information system. In this paper, the evolution of the concepts
involved in process mining is presented along with the analysis of three
case studies in order to understand the critical success factors in its implementation. Starting from this point, the future challenges that might
be present in its application on organizations are discussed along with
the required research to provide solutions to the industry in a discipline
that has been considered as the most promising in the field of Business
Process Management.

Keywords

critical success factors, process analysis., process miningminería de procesos, factores críticos, análisis de procesos.mineração de processos, fatores críticos, análise de processos.

References
Agrawal R., Gunopulos D., and Leymann F. (1998). Mining Process Models from Workflow Logs. En: Sixth International Conference on Extending Database Technology, (pp 469–483). Londres: Springer

Aguirre, S. (2015). Metodología para la aplicación de minería de procesos. Tesis doctoral. Pontificia Universidad Javeriana. Bogotá. 127 p.

Aguirre, S., Parra, C. y Alvarado, J. (2013), Combination of process mining and simulation techniques for business process redesign: a methodology approach, Lecture Notes in Business Information Processing, 162, 24-43.

Bozkaya M., Gabriels J. y van der Werf J. (2009), Process Diagnostics: A Method Based on Process Mining, En: Proceedings International Conference on Information, Process and Knowledge Management 2009, Cancun: IEEE

Cook J., Wolf A. (1998). Discovering models of software processes from event-based data, ACM Transactions on Software Engineering and Methodology. 7 (3),215–249.

Dumas, M. et al (2013). Fundamentals of Business Process Management. Berlin: Springer.

Dumas M, van der Aalst W.M.P y Hofstede A. (2005) Process-Aware Information Systems: Bridging People and Software Through Process Technology. New Jersey: Willey.

Grigori, D. et al. (2004), Business Process Intelligence. Computers in Industry, 53 (3), 321-343.

Herbst J. y Karagiannisb D. (2004). Workflow mining with InWoLvE. Computers in Industry. 53 (3), 245–264.

Hwang S., Wei C. y Yang W. (2004). Discovery of temporal patterns from process instances. Computers in Industry. 53 (3), 345–364.

Jans M., et al. (2011). A business process mining application for internal transaction fraud mitigation. Expert Systems with Applications, 38 (10), 13351–13359

Maruster L. y Van Beest L (2009). Redesigning business processes: a methodology based on simulation and process mining techniques. Knowledge and Information Systems, 21 (3), 267-297

Mans R., et al. (2008). Application of Process Mining in Healthcare - A Case Study in a Dutch Hospital. En: A. Fred, J. Filipe, and H. Gamboa (Eds.): BIOSTEC 2008 (pp. 425-438). Madeira: IEEE

Pinter S., Golani M. (2004). Discovering workflow models from activities’ lifespans. Computers in Industry, 53 (3), 283–296

Rebuge A., Ferreira D. (2012), Business process analysis in healthcare environments: A methodology based on process mining. Journal Information Systems. 37 (2), 99-116

Rozinat A. (2008). Discovering colored Petri nets from event logs. International Journal of Software Tools for Technology Transfer, 10 (1), 57-74.

Rozinat A., Jong I., Gunther C. (2010). Process Mining Applied to the Test Process of Wafer Steppers in ASML. IEEE Transactions on Systems Man and Cybernetics, 1-6.

Schimm G. (2004). Mining exact models of concurrent workflows. Computers in Industry. 53 (3), 265–281

Van der Aalst W.M.P et al. (2012). Process Mining Manifesto, En: Daniel, K. Barkaoui and S. Dustdar, Eds. Business Process Management Workshops (pp. 169-174), Berlin: Springer.

Van der Aalst W.M.P et al (2007). Business Process Mining: an industrial application. Information Systems, 32 (5), 713-732

Van der Aalst WMP (2015) Extracting event data from databases to unleash process mining. En: Broke J and Schmiedel T (ed) BPM-Driving innovation in a digital world. (pp. 105-128). Heidelberg: Springer.

Van der Aalst W.M.P, Schonenberg M., Song M. (2011), Time prediction based on process mining. Information Systems, 36 (2), 450–475

Van der Aalst W.M.P. (2011). Process Mining: Discovery, Conformance and Enhancement of Business Process. Berlin :Springer.
Van der Aalst, W.M.P. y Weijters A.J.M.M. (2004), Process mining: a research agenda. Computers in Industry, 53 (3), 231-244.

Van der Aalst W.M.P., Weijters A. y Maruster L. (2004), Workflow mining: discovering process models from event logs. IEEE Transactions on Knowledge and and Data Engineering. 16 (9), 1128-1142.

Van der Aalst W.M.P. and Song M. (2008). Towards comprehensive support for organizational mining. Decision Support Systems. 46 (1), 300-317.

Van Eck M., Xixi, L, Leemans S., van der Aalst WMP (2015). PM2 : A Process Mining Project Methodology. Lecture Notes in Computer Science. 9097, 297-313.

Weerdt J., Schuppa A., Vanderloock A., Baesensa 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.
How to Cite
Aguirre Mayorga, H. S., & Rincón García, N. (2015). Process mining: development, applications and critical factors. Cuadernos De Administración, 28(50), 137–157. https://doi.org/10.11144/Javeriana.cao28-50.mpda
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