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Updated in [June 30th, 2023]

This course, Modelling and Analytics for Supply Chain Management, focuses on the application of analytical techniques for determining effective solutions to problems associated with supply networks considering the constraints of demand and supply. The objectives of the course are to understand the nature of supply networks, the goals of supply networks, and explain the impact of analytics-based supply chain decisions on the success of a firm. The coverage includes key metrics that track the performance of the supply network in terms of each driver, identification of the key factors to be considered when designing a distribution network, and use of analytical techniques for developing a framework for network design. Emphasis is laid on the use of optimization techniques for facility location, capacity allocation, and evaluation of supply chain design decisions under uncertainty. Along with these objectives, this course is also aimed at understanding the concepts of multi-criterion decision making in supplier selection and rating, inventory management techniques under uncertain demand and supply environment, mathematical models for design of transportation networks, and the role of soft computing techniques for matching supply with demand.

This course is intended for students from Management, Industrial and Systems Engineering, Mechanical Engineering, and related disciplines. No prerequisites are required. The course is supported by the Tata Group of Industries, Multinationals, L&T, and similar such manufacturing and service organizations including IT companies.

[Applications]
The application of the course Modelling and Analytics for Supply Chain Management can be seen in the various industries such as Tata Group of Industries, Multinationals, L&T, and similar such manufacturing and service organizations including IT companies. The course provides the students with the knowledge and skills to understand the nature of supply networks, goal of supply networks and explain the impact of analytics based supply chain decisions on the success of a firm. It also helps them to identify the key factors to be considered when designing a distribution network and use of analytical techniques for developing a framework for network design. The course also provides the students with the knowledge of optimization techniques for facility location, capacity allocation and evaluation of supply chain design decisions under uncertainty. Furthermore, the course also helps the students to understand the concepts of multi-criterion decision making in supplier selection and rating, inventory management techniques under uncertain demand and supply environment, mathematical models for design of transportation networks, and the role of soft computing techniques for matching supply with demand.

[Career Paths]
[Job Position Path]
The job position path recommended for learners of this course is Supply Chain Analyst. Supply Chain Analysts are responsible for analyzing and optimizing the supply chain of an organization. They use data-driven techniques to identify areas of improvement and develop strategies to increase efficiency and reduce costs. They also develop and implement systems to track and monitor the performance of the supply chain.

The development trend of Supply Chain Analysts is towards the use of advanced analytics and artificial intelligence (AI) to improve the efficiency of the supply chain. AI-driven solutions are being used to automate processes, reduce costs, and improve customer experience. Additionally, Supply Chain Analysts are increasingly being asked to develop strategies to reduce the environmental impact of the supply chain. This includes developing strategies to reduce waste, increase energy efficiency, and reduce emissions.

[Education Paths]
The recommended educational path for learners of this course is a Bachelor's degree in Supply Chain Management. This degree program typically covers topics such as supply chain strategy, logistics, operations management, inventory management, and supply chain analytics. Students will learn how to analyze and optimize supply chain operations, develop strategies to improve efficiency and reduce costs, and use data-driven decision-making to improve supply chain performance. Additionally, students will gain an understanding of the latest technologies and trends in supply chain management, such as artificial intelligence, blockchain, and the Internet of Things.

The development trend of this degree program is to focus on the application of analytics and technology to supply chain management. This includes the use of predictive analytics, machine learning, and artificial intelligence to improve supply chain operations. Additionally, the degree program will focus on the use of emerging technologies such as blockchain and the Internet of Things to improve supply chain visibility and efficiency. Finally, the degree program will emphasize the importance of sustainability and ethical practices in supply chain management.