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Business Process Simulation Focusing Supply Chain Risk Management Aspects

Authors:
Frank Schätter
Frank Morelli

Keywords: decision support systems; data-based supply chain model; consequence-driven risk simulation; resilient supply chains

Abstract:
Decision support systems refer to computable models that assist decision-makers in the identification and/or the estimation of consequences of decision alternatives. In this regard, model-driven decision support systems have been proven successfully, which use simulation models to analyze business processes and respective decision situations based on parameters and a limited amount of data. The focus of this contribution is on the opportunities of using such a business processes simulation in the field of supply chain risk management. Therefore, we present a novel approach that couples a data-based supply chain model with a consequence-driven risk simulation. Our simulation approach reverses the standard risk management cycle by identifying vulnerable parts within the supply chain – in terms of a data-based model – and subsequently backtracking possible triggering risk events instead of predicting such possible events first. The result of our approach is an easy-applicable procedure that allows companies to analyze and to improve the resilience status of their supply chains.

Pages: 38 to 43

Copyright: Copyright (c) IARIA, 2021

Publication date: October 3, 2021

Published in: conference

ISSN: 2308-4537

ISBN: 978-1-61208-898-3

Location: Barcelona, Spain

Dates: from October 3, 2021 to October 7, 2021