Data-Driven Decision Making in Supply Chain Management
DOI:
https://doi.org/10.36676/irt.v9.i5.1487Keywords:
Data-driven decision-making, supply chain management, predictive analytics, real-time data, operational efficiencyAbstract
The importance of making decisions in supply chain management (SCM) based on data has grown significantly in recent years due to the quickly changing nature of the modern corporate environment. Within the scope of this abstract, the transformational influence of data analytics on supply chain management is investigated. Particular attention is paid to the ways in which data-driven strategies improve decision-making processes, increase operational efficiency, and boost competitive advantage.
The coordination of a number of operations, including as distribution, manufacturing, inventory management, and procurement, is an essential part of supply chain management. In the past, these processes were handled by the use of intuition and facts from the past. But the introduction of sophisticated data analytics tools has completely changed the way that this approach is taken. Organisations are able to improve their operations, acquire deeper insights into the dynamics of their supply chains, and more correctly estimate demand when they make use of real-time data, predictive analytics, and machine learning algorithms.
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