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Professor, Department of Management Studies, St. Joseph’s Institute of Technology, OMR , Chennai, Tamil Nadu , India
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Associate Professor, Faculty of Management, SRM Institute of Science and Technology, Vadapalani , Chennai, Tamil Nadu , India
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Associate Professor, Department of Management Studies, SRM Valliammai Engineering College, Chengalpattu , Chennai, Tamil Nadu , India
Assistant Professor, Department of Management Studies, SRM Valliammai Engineering College, Chengalpattu , Chennai, Tamil Nadu , India
In the dynamic environment of the high-technology production, the supply chain and financial risks management have become more important to maintain the continuity of the operations and profitability. Although a large amount of data is available, most industries continue to struggle to use this data to optimize all risks holistically. In this paper, an innovative Data-Driven Supply Chain and Financial Management Framework model is proposed that will help to optimize the risk management of the high-technology manufacturing industries. The framework incorporates real-time data analytics, machine learning models, and sophisticated financial management methods to develop a comprehensive approach to risk identification, assessment, and reduction. The structure would allow both operational and financial variables to be taken into account in making decisions by merging financial and supply chain information. It is based on the implementation of predictive models to predict and prescribe proactive actions to improve the resilience and financial stability of supply chains. The outcomes of the implementation of this framework in a manufacturing environment prove a substantial decrease in the number of operational issues, enhanced cost control, and the forecasting of financial risks. The real-time analytics of the framework also deliver actionable insights that will help in enhancing decision-making throughout the organization at different levels. This study illustrates how a data-driven approach can be used to revolutionize risk management in high-tech manufacturing, providing a scalable solution to industries aiming to increase efficiency, decrease risk exposure, and maximize financial performance. The results indicate that a more agile, resilient, and financially sound manufacturing process may be achieved through the introduction of such a framework.
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