Wow! eBook
Applied Data Science and AI In Supply Chain Optimization and Enterprise Transformation
Author(s): Shreya Jain (Author)
- Publisher: AG Publishing House
- Publication Date: 29 Jun. 2026
- Language: English
- Print length: 306 pages
- ISBN-10: B0H6XLJSG2
- ISBN-13: 9789376404261
Book Description
Applied Data Science and AI in Supply Chain Optimization and Enterprise Transformation serves as a comprehensive guide to navigating the technological and structural shifts in modern logistics. This book is structured to provide both a theoretical foundation and practical applications, beginning with an exploration of data-driven models, including descriptive, predictive, prescriptive, and adaptive approaches. It details the critical infrastructure required to support these models, such as data lakes, data warehouses, and hybrid cloud architectures. To support these infrastructures, the book discusses specialized platforms and tools, including Apache Hadoop, Snowflake, SAP IBP, Microsoft Power BI, TensorFlow, Apache Kafka, and Amazon Redshift.
A significant portion of the book is dedicated to the core pillars of supply chain management, covering Predictive Analytics through the mastery of demand forecasting using time series methods and machine learning models like Random Forests and Neural Networks to reduce uncertainty. It further explores Optimization through the application of linear programming, network design, and vehicle routing to enhance inventory control. The book details the role of AI in Procurement, specifically leveraging Natural Language Processing (NLP) for contract analytics, spend optimization, and supplier performance evaluation. Additionally, it focuses on Intelligent Automation, utilizing Digital Twins, IoT sensors, and real-time monitoring systems to create self-healing supply networks. The book also addresses the complexities of change management, offering strategies like Lewin’s Three-Step Model, Kotter’s Eight-Step Process, and the ADKAR Model to ensure successful technology adoption. Finally, it looks toward future trends, discussing emerging AI technologies such as Generative AI, edge analytics, and sustainable supply chain strategies. By providing a strategic roadmap for future readiness, this book empowers organizations to synchronize global operations and achieve a sustainable competitive advantage through scalable intelligence and resilient systems.
A significant portion of the book is dedicated to the core pillars of supply chain management, covering Predictive Analytics through the mastery of demand forecasting using time series methods and machine learning models like Random Forests and Neural Networks to reduce uncertainty. It further explores Optimization through the application of linear programming, network design, and vehicle routing to enhance inventory control. The book details the role of AI in Procurement, specifically leveraging Natural Language Processing (NLP) for contract analytics, spend optimization, and supplier performance evaluation. Additionally, it focuses on Intelligent Automation, utilizing Digital Twins, IoT sensors, and real-time monitoring systems to create self-healing supply networks. The book also addresses the complexities of change management, offering strategies like Lewin’s Three-Step Model, Kotter’s Eight-Step Process, and the ADKAR Model to ensure successful technology adoption. Finally, it looks toward future trends, discussing emerging AI technologies such as Generative AI, edge analytics, and sustainable supply chain strategies. By providing a strategic roadmap for future readiness, this book empowers organizations to synchronize global operations and achieve a sustainable competitive advantage through scalable intelligence and resilient systems.
