Artificial intelligence-based strategies for supply chain inventory management

被引:0
作者
Bravo-Arroyave, Johan Sebastian [1 ]
Riascos-Guerrero, Jhoan Andres [1 ]
Galvan-Colonia, Esteban [1 ]
Pincay-Lozada, Jorge Luis [2 ]
机构
[1] Univ Cooperat Colombia, Estudiante Programa Ingenieri Sistemas, Campus Cali, Cali, Colombia
[2] Univ Cooperat Colombia, Fac Ingn, Ingeniero Mecatron, Campus Cali, Cali, Colombia
来源
TECNOLOGIA EN MARCHA | 2024年 / 37卷
关键词
Artificial intelligence; supply chain management; business productivity; demand forecasting; operational efficiency;
D O I
10.18845/tm.v37i6.7271
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Inventory management stands as an essential component in the supply chain of any company, playing a crucial role in reducing costs and ensuring customer satisfaction. In the current business environment, characterized by its rapid evolution and high competitiveness, artificial intelligence or AI emerges as an innovative tool capable of transforming the way companies approach this management. The application of advanced machine learning algorithms makes it possible to process large volumes of historical sales data, purchasing patterns, market trends and economic conditions, contributing significantly through the accurate prediction of future demand. This analytical capability enables companies to anticipate market needs and adjust their inventory levels effectively, avoiding shortages or overstock situations. In addition to optimizing the supply chain, artificial intelligence identifies bottlenecks and suggests improvements in logistics and distribution, improving operational efficiency and ultimately increasing customer satisfaction. In this scenario, the strategic application of artificial intelligence consolidates the competitive position of companies by proactively adapting their inventory management practices to the demands of today's market.
引用
收藏
页码:88 / 97
页数:10
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