Abstract
Existing techniques for the redesign of business processes are mostly concerned with optimizing efficiency and productivity, but do not take social considerations into account. In this paper, we represent social business process redesign (SBPR) as a constrained optimization problem (COP). Assuming a workforce of human and computer resources, SBPR considers two types of decisions: (1) how to allocate tasks among this workforce and (2) which skills it should acquire. The latter decision can be used to control for the amount of automation (by setting an upper bound), which may ensure, for example, that disadvantaged workers are included. We discuss scenarios inspired by real-world considerations where the COP representation of SBPR can be used as a decision support tool. Furthermore, we present an extensive computational analysis that demonstrates the applicability of our COP-based solution to large SBPR instances, as well as a detailed analysis of the factors that influence the performance of the approach. Our work shows that it is feasible to incorporate multiple considerations into redesign decision making, while providing meaningful insights into the trade-offs involved.
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Automating a task is not the same as completely automating an occupation or job. Most human jobs involve a range of tasks.
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One can easily generalize the applicability analysis that follows to sets of M automation types and D disadvantaged employee types.
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Counter-intuitively, some automation procedures can be extremely costly, while training disadvantaged employees could be sponsored by the government and thus have negligible costs.
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Senderovich, A., Schippers, J.J., Reijers, H.A. (2020). Socially-Aware Business Process Redesign. In: Fahland, D., Ghidini, C., Becker, J., Dumas, M. (eds) Business Process Management. BPM 2020. Lecture Notes in Computer Science(), vol 12168. Springer, Cham. https://doi.org/10.1007/978-3-030-58666-9_5
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