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A Multi-criteria Approach for Team Recommendation

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Business Process Management Workshops (BPM 2016)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 281))

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Abstract

Team recommendation is a key and little-explored aspect within the area of business process management. The efficiency with which the team is conformed may influence the success of the process execution. The formation of work teams is often done manually, without a comparative analysis based on multiple criteria between the individual performance of the resources and their collective performance in different teams. In this article, we present a multi-criteria framework to allocate work teams dynamically. The framework considers four elements: (i) a resource request characterization, (ii) historical information on the process execution and expertise information, (iii) different metrics which calculate the suitability of the work teams taking into account both individual performance as well as collective performance of the resources, and (iv) a recommender system based on the Best Position Algorithm (BPA2) to obtain a ranking for the recommended work teams. A software development process was used to test the usefulness of our approach.

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Notes

  1. 1.

    https://svn.win.tue.nl/trac/prom/browser/Packages/ResourceRecommendation/ Trunk/src/org/processmining/resourcerecommendation/utils/resrecxes.

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Acknowledgments

This project was partially funded by the Ph.D. Scholarship Program of CONICYT Chile (Doctorado Nacional/2014-63140181), Universidad de Costa Rica and by Fondecyt (Chile) Project No.1150365.

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Authors and Affiliations

  1. Department of Computer Science, School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile

    Michael Arias, Jorge Munoz-Gama & Marcos Sepúlveda

Authors
  1. Michael Arias
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  2. Jorge Munoz-Gama
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  3. Marcos Sepúlveda
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Correspondence to Michael Arias .

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Editors and Affiliations

  1. Institute of Computer Science, University of Tartu, Tartu, Estonia

    Marlon Dumas

  2. School of Arts, Sciences and Humanities, University of São Paulo, Sao Paulo, São Paulo, Brazil

    Marcelo Fantinato

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Arias, M., Munoz-Gama, J., Sepúlveda, M. (2017). A Multi-criteria Approach for Team Recommendation. In: Dumas, M., Fantinato, M. (eds) Business Process Management Workshops. BPM 2016. Lecture Notes in Business Information Processing, vol 281. Springer, Cham. https://doi.org/10.1007/978-3-319-58457-7_28

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  • DOI: https://doi.org/10.1007/978-3-319-58457-7_28

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