The purpose of this paper is regarding the execution of business processes by Business Process Management Systems (BPMS), during design-time modelers have to specify the potential performers of a work activity according to their organizational position or role. Once several workers may share the same role, at run-time all of them (indistinctively) can be assigned by BPMS to execute a work activity. However, distinct individuals have different personality traits and, for certain instances of work (requiring, for example, specific soft skills) some of them might perform better. A new approach to work distribution in business processes supported by BPMS, which takes into account the psychological characteristics of workers was proposed.
As stated in Section 3 of the paper, in this work the Design Science Research (DSR) methodology, as proposed by Kuechler and Vaishnavi (2008) was used. All the five steps, from the “Awareness of problem” to the “Conclusion” were accomplished, being described in the paper.
It is demonstrated that, by using the proposed approach, BPMS might deliver work to people in a more effective way, by selecting those workers that seem to be more suitable to accomplish each particular piece of work, taking into account the characteristics of the work itself and the specific profiles of the workers eligible to execute it.
BPMSs are responsible for the execution of business process models, by delivering work activities to suitable agents (human or artificial), which execute them. Addressing a gap in the BPM literature, this paper presents a new approach for improving work distribution in business processes supported by BPMS, enabling to assign (in run-time) the most suitable workers to perform specific work activities, grounded on the concept of psychological profile and taking into account technical, human and social aspects.
Pereira, J., Varajão, J. and Uahi, R. (2020), "A new approach for improving work distribution in business processes supported by BPMS", Business Process Management Journal, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/BPMJ-05-2019-0184Download as .RIS
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