This paper addresses the problem of quantifying the parallelism in a business process. Having a synthetic metric to quantify the parallelism of a process may provide an assessment of the complexity of the process and guide certain design choice. In the present paper we discuss the advantages and disadvantages of two metrics presented in the literature, as well of two novel metrics that leverage on the notion of Instance Graph. Analysis is performed by means of use cases that are representative of operational business processes. The proposed metrics show to provide a sensible way to evaluate the overall parallel complexity of a process model.
Metrics of Parallel Complexity of Operational Business Processes / Potena, Domenico; Mircoli, Alex; Diamantini, Claudia; Chiorrini, Andrea. - 2:(2022), pp. 561-566. [10.5220/0011084200003179]
Metrics of Parallel Complexity of Operational Business Processes
Potena, Domenico;Mircoli, Alex;Diamantini, Claudia;Chiorrini, Andrea
2022-01-01
Abstract
This paper addresses the problem of quantifying the parallelism in a business process. Having a synthetic metric to quantify the parallelism of a process may provide an assessment of the complexity of the process and guide certain design choice. In the present paper we discuss the advantages and disadvantages of two metrics presented in the literature, as well of two novel metrics that leverage on the notion of Instance Graph. Analysis is performed by means of use cases that are representative of operational business processes. The proposed metrics show to provide a sensible way to evaluate the overall parallel complexity of a process model.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
