Supply Chain Analytics

Course Overview

This course provides an overview of Supply Chain Analytics and its applications in the present time of intense global competition. It is an elective course for PG students and working professionals. The course covers the basics of Business Analytics and Optimization, Supply Chain Analytics and Optimization, Descriptive Analytics, Predictive Analytics, Prescriptive Analytics, and Modeling through R Language. It also covers the level of uncertainty associated with the supply of products and services to targeted customer segments and how to justify the choice of a supply chain strategy and its fit with competitive strategy. Companies already in the business of Supply Chain Analytics and may recognize the online course include IBM, Mu-Sigma, Genpact, Accenture, Capgemini, Wipro, and Deloitte. Basic knowledge of Operations management is desirable.

[Applications]
Upon completion of this course, students should be able to apply the knowledge and skills acquired to analyze the level of uncertainty associated with the supply of products and services to targeted customer segments and justify the choice of a supply chain strategy and its fit with competitive strategy. They should also be able to explain the role and applications of Descriptive, Predictive, and Prescriptive Analytics in a Supply Chain, as well as learn the basics of Modeling through R Language. This knowledge and skillset can be applied to various industries, such as IBM, Mu-Sigma, Genpact, Accenture, Capgemini, Wipro, and Deloitte.

[Career Paths]

Career Path: Supply Chain Analytics is a growing field and offers a wide range of job opportunities. The job positions include Supply Chain Analyst, Supply Chain Manager, Supply Chain Consultant, Supply Chain Planner, Supply Chain Coordinator, Logistics Analyst, Logistics Manager, Logistics Consultant, Logistics Planner, Logistics Coordinator, etc. The job roles involve analyzing the supply chain data, developing strategies to optimize the supply chain, and managing the supply chain operations.

The development trend of Supply Chain Analytics is towards the use of advanced analytics and Artificial Intelligence (AI) to improve the efficiency of the supply chain. Companies are increasingly using AI-based solutions to automate the supply chain process and reduce costs. AI-based solutions are also being used to predict customer demand and optimize inventory management. Companies are also using AI-based solutions to improve customer service and reduce delivery times. With the increasing use of AI-based solutions, the demand for professionals with expertise in Supply Chain Analytics is expected to grow in the coming years.

[Education Paths]

Educational Path:


The educational path for learners interested in Supply Chain Analytics is to pursue a degree in Supply Chain Management. This degree typically requires a minimum of a Bachelor's degree in Business Administration or a related field. The degree program will cover topics such as supply chain strategy, logistics, operations management, and analytics. Students will learn how to analyze data, develop supply chain strategies, and optimize operations. They will also learn how to use analytics to make decisions and improve supply chain performance. Additionally, students will gain an understanding of the latest trends in supply chain analytics and how to apply them to their own organizations.

The development trend of Supply Chain Analytics is to focus on the use of data and analytics to improve supply chain performance. Companies are increasingly using analytics to gain insights into their supply chain operations and make better decisions. This includes using predictive analytics to forecast demand, optimize inventory levels, and improve customer service. Additionally, companies are using prescriptive analytics to identify opportunities for cost savings and process improvements. As technology advances, companies are also leveraging artificial intelligence and machine learning to automate and optimize supply chain operations.