Abstract
Organizational mining aims at gaining insights for business process improvement by discovering organizational knowledge relevant to the performance of business processes. A key topic of organizational mining is the discovery of organizational models from event logs. While it is common for modern organizations to have employees sharing roles and responsibilities across different internal groups, most of the existing methods for organizational model discovery are unable to identify such overlaps. The overlapping resources are likely to be generalists in an organization. Existing findings in process redesign best practices have proven that generalists can help increase the flexibility of a business process (similarly to the flexibility of the role of “libero” in certain team sports). In this paper we propose an approach capable of discovering organizational models with overlaps and thus helping identify generalists in an organization. The approach builds on existing cluster analysis techniques to address the underlying technical challenges. Through experiments on real-life event logs the applicability and effectiveness of the proposed method are evaluated.
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Notes
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For illustration purposes, resource name is used in the example in Table 1.
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Acknowledgements
This work is supported by the National Key Research and Development Program of China (Grant No. 2017YFB0202200); the National Natural Science Foundation of China (Grant No. 61572539); the Research Foundation of Science and Technology Plan Project in Guangdong Province (Grant No. 2016B050502006); and the Research Foundation of Science and Technology Plan Project in Guangzhou City (Grants No. 2016201604030001, 201704020092).
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Yang, J., Ouyang, C., Pan, M., Yu, Y., ter Hofstede, A.H.M. (2018). Finding the “Liberos”: Discover Organizational Models with Overlaps. In: Weske, M., Montali, M., Weber, I., vom Brocke, J. (eds) Business Process Management. BPM 2018. Lecture Notes in Computer Science(), vol 11080. Springer, Cham. https://doi.org/10.1007/978-3-319-98648-7_20
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