Simulation and SCOR: Performance Metrics Integration to Supply Chain Performance Measurement
2019 60th International Scientific Conference on Information Technology and Management Science of Riga Technical University (ITMS 2019): Proceedings 2019
Andrejs Girjatovics, Santhosh Somashekaraiah Shekar, Oksana Kuznecova, Jeļena Pečerska

Supply Chain Operations Reference (SCOR) model introduced by Supply Chain Council and now owned by APICS is a well-known tool among companies, whose focus is led on supply chain performance improvements. It elaborates four components such as library of standards SC processes, performance metrics, practices and skills required for the particular process. In spite of plenty of articles and references to SCOR, integration of SCOR framework to companies process and performance assessment is challenging due to a variety of managerial elements to be changed or implemented into ongoing business processes, including changes in information system data structure, reporting dashboards changes and daily routines adjustments. With the adequate respect to SCOR model from practitioners and consultancies, there is still a concern about practical value of the metrics against keeping business continuity during SCOR metrics implementation into company’s business processes. The paper discusses the progress of implementation of the SCOR model in the enterprise, indicates the respective challenges, as well as highlights the advantages of quantitative simulation analysis of business processes in the enterprise based on the system of metrics of the SCOR model.


Keywords
SCOR, simulation, performance metrics
DOI
10.1109/ITMS47855.2019.8940657
Hyperlink
https://ieeexplore.ieee.org/document/8940657

Girjatovics, A., Shekar, S., Kuznecova, O., Pečerska, J. Simulation and SCOR: Performance Metrics Integration to Supply Chain Performance Measurement. In: 2019 60th International Scientific Conference on Information Technology and Management Science of Riga Technical University (ITMS 2019): Proceedings, Latvia, Riga, 10-11 October, 2019. Piscataway: IEEE, 2019, pp.1-6. ISBN 978-1-7281-5710-8. e-ISBN 978-1-7281-5709-2. Available from: doi:10.1109/ITMS47855.2019.8940657

Publication language
English (en)
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