The digital twin of the business process model

Abstract

Abstract In this paper, we propose a solution to the problem of organizational management based on high-precision simulation models designed for numerical forecasting of the parameters of business process models - duration, labor intensity and resource intensity, cost. The solution is implemented as a prototype twin of the business process system model. To solve the problem of predicting the numerical indicators of a business process model, the formula and algorithmic apparatus of stochastic GERT networks is used. BPMS ELMA was used as a technical platform for the implementation of a digital twin prototype. To solve this problem, the apparatus of stochastic GERT networks is used. An edge of the GERT network is associated with the operation of the business process, and the node of the GERT network with an event or gateway of the business process. An algorithm for translating a model of a business process into an equivalent GERT network, as well as calculating the parameters of the law of distribution of the cost of a business process based on the obtained GERT network, is given. The proposed tool, implemented in the digital twin modeling module, allows solving the problems of predicting the dynamics of discrete-event models described in BPMN notation without using statistical simulation models. Continuous updating of the structure of the GERT-model in accordance with the modification of the process in the ELMA system and clarification of the parameters of probabilities, the type of distribution laws and their parameters based on the accumulated data of the digital shadow of the business process allows us to talk about the implementation of a high-precision forecasting model of the business process in the proposed digital twin model.