Abstract
Simulating organizational processes characterized by interacting human activities, resources, business rules and constraints, is a challenging task, because of the inherent uncertainty, inaccuracy, variability and dynamicity. With regard to this problem, currently available business process simulation (BPS) methods and tools are unable to efficiently capture the process behavior along its lifecycle. In this paper, a novel approach of BPS is presented. To build and manage simulation models according to the proposed approach, a simulation system is designed, developed and tested on pilot scenarios, as well as on real-world processes. The proposed approach exploits interval-valued data to represent model parameters, in place of conventional single-valued or probability-valued parameters. Indeed, an interval-valued parameter is comprehensive; it is the easiest to understand and express and the simplest to process, among multi-valued representations. In order to compute the interval-valued output of the system, a genetic algorithm is used. The resulting process model allows forming mappings at different levels of detail and, therefore, at different model resolutions. The system has been developed as an extension of a publicly available simulation engine, based on the Business Process Model and Notation (BPMN) standard.
Highlights
Introduction and MotivationInadequate process design increases inefficiency and yields ineffectiveness
We propose a novel approach of business process simulation (BPS) consisting of the use of interval-valued parameters as an alternative to conventional single-valued or probability-valued parameters
The approach is based on the representation of business process parameters in terms of intervals, to efficiently characterize human-driven processes
Summary
Introduction and MotivationInadequate process design increases inefficiency and yields ineffectiveness. Modeling is a learning process allowing business analysts to make clear requirements, express domain knowledge and provide rough solutions. Formal models do not allow ambiguity and increase the potential for analysis [25]. A BP model should be understood by all the involved stakeholders. This important requirement can be achieved through the use of visual notations. Once consensus among stakeholders has been reached, the BP model can be deployed on BP management platforms and, if a formal language was used, its behavior can be unambiguously implemented by vendors. The analysis of BP models is important to reduce the risk of costly corrections at a later stage, as well as to investigate ways of improving processes. Visual models act as communication channels between business managers and technicians and provide documentation to manage post-project activities
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