International Conference on Supply Chain Management Analytics with Big Data (ICSCMBDA - 27)

This track focuses on the application of predictive analytics to enhance decision-making in supply chain management. Participants will explore methodologies and tools that leverage big data to forecast demand and optimize inventory levels.

This session will delve into the transformative role of artificial intelligence in logistics operations. Attendees will discuss case studies and frameworks that illustrate how AI can streamline processes and improve efficiency.

This track examines the critical importance of data integration in achieving a cohesive supply chain strategy. Presentations will highlight best practices and technologies that facilitate seamless data flow across various supply chain functions.

This session will investigate the use of machine learning algorithms to analyze supply chain data. Researchers will present innovative approaches that enhance predictive capabilities and operational performance.

This track focuses on the development and implementation of intelligent systems designed to optimize inventory management. Discussions will center around the integration of big data analytics and automation in inventory processes.

This session will explore the role of data visualization in interpreting complex supply chain data. Participants will learn about tools and techniques that enhance data storytelling and facilitate informed decision-making.