Research Article
A Predictive Performance Measurement System for Decision Making in the Supply Chain
@INPROCEEDINGS{10.1007/978-3-030-87495-7_15, author={Loraine Sanchez-Jimenez and Tom\^{a}s E. Salais-Fierro}, title={A Predictive Performance Measurement System for Decision Making in the Supply Chain}, proceedings={Computer Science and Engineering in Health Services. 5th EAI International Conference, COMPSE 2021, Virtual Event, July 29, 2021, Proceedings}, proceedings_a={COMPSE}, year={2021}, month={9}, keywords={Supply chain Predictive performance measurement Models Fuzzy logic techniques Logistics KPIs}, doi={10.1007/978-3-030-87495-7_15} }- Loraine Sanchez-Jimenez
Tomás E. Salais-Fierro
Year: 2021
A Predictive Performance Measurement System for Decision Making in the Supply Chain
COMPSE
Springer
DOI: 10.1007/978-3-030-87495-7_15
Abstract
Increasing business competitiveness forces companies to develop strategies in search of operational excellence. The supply chain aims to increase its efficiency by reducing costs without neglecting quality and service levels. The implementation of predictive performance evaluation systems as a management practice has increased in recent years because in addition to measuring the efficiency and effectiveness of processes under certain scenarios, it includes artificial intelligence techniques that anticipate future events and allow taking advantage of behavioral patterns of historical data and current information to identify risks and opportunities. This paper proposes a fuzzy logic-based performance measurement system to help predict purchasing behavior through the impact of attributes of the SCOR supply chain operations reference model. The SCOR level 1 indicators are used as a standard for benchmarking against other supply chains. The proposed model is applied through an illustrative case and, according to the results obtained, it facilitates performance prediction and allows scenario analysis. In addition, it is adaptive to any industry and cyclical in search of the desired result, therefore, it helps decision makers to anticipate situations under uncertainty parameters and conditions by determining through simulations the performance attributes with the greatest impact on purchasing and facilitating decision making.
