Digital Supply Chain Transformation: Implementing Technology, Analytics, and Data-Driven Solutions delves into the intricate world of supply chain management, emphasizing the role of digital transformation in modern supply chains. Through a blend of theoretical learning and practical applications, readers will gain a deep understanding of foundational supply chain principles while exploring emerging trends and technologies reshaping the industry. Topics such as system dynamics modelling, machine learning, artificial intelligence, and end-to-end visibility are explored in-depth, equipping readers with the tools and knowledge needed to excel in the rapidly evolving landscape of supply chain management.
Readers will learn how comprehend core principles and elements of supply chain management and its pivotal role in businesses and industries, recognize the significance of digital transformation in supply chains, understand the tools, technologies, and strategies essential for a successful transformation, evaluate the importance of end-to-end supply chain visibility, employ methods and technologies to enhance this visibility in practical scenarios, and apply system dynamics modeling techniques to address complex supply chain problems to optimize supply chain processes, and much more.
1. Title of Book - p. i 2. Cover image - p. i 3. Title page - p. ii 4. Table of Contents - p. iii 5. Copyright - p. iv 6. Dedication - p. v 7. About the author - p. xi 8. Foreword - p. xiii 9. Preface - p. xv 10. Acknowledgments - p. xix 11. 1. Foundations in Supply chain management - p. 1 12. 2. Framework for digital supply chain transformation - p. 35 13. 3. End-to-end supply chain visibility - p. 65 14. 4. System dynamics modeling for supply chain - p. 93 15. 5. Supply chain analytics and tools - p. 125 16. 5.1 Supply chain analytics - p. 125 17. 5.2 Types of supply chain analytics - p. 125 18. 5.3 Optimization in supply chain analytics - p. 133 19. 5.4 Simulation in supply chain - p. 148 20. 5.5 Forecasting in supply chain - p. 157 21. 5.6 Limitations and pitfalls of supply chain analytics - p. 166 22. Discussion questions - p. 167 23. Multiple-choice questions - p. 168 24. Answer key - p. 171 25. Numerical problems - p. 172 26. 6. Machine learning in supply chains - p. 175 27. 7. Artificial Intelligence applications in supply chain - p. 213 28. 8. Emerging trends in supply chain management - p. 259 29. Glossary - p. 321 30. Index - p. 327
Digital Supply Chain Transformation: Implementing Technology, Analytics, and Data-Driven Solutions delves into the intricate world of supply chain management, emphasizing the role of digital transformation in modern supply chains. Through a blend of theoretical learning and practical applications, readers will gain a deep understanding of foundational supply chain principles while exploring emerging trends and technologies reshaping the industry. Topics such as system dynamics modelling, machine learning, artificial intelligence, and end-to-end visibility are explored in-depth, equipping readers with the tools and knowledge needed to excel in the rapidly evolving landscape of supply chain management.
Readers will learn how comprehend core principles and elements of supply chain management and its pivotal role in businesses and industries, recognize the significance of digital transformation in supply chains, understand the tools, technologies, and strategies essential for a successful transformation, evaluate the importance of end-to-end supply chain visibility, employ methods and technologies to enhance this visibility in practical scenarios, and apply system dynamics modeling techniques to address complex supply chain problems to optimize supply chain processes, and much more.
1. Title of Book - p. i 2. Cover image - p. i 3. Title page - p. ii 4. Table of Contents - p. iii 5. Copyright - p. iv 6. Dedication - p. v 7. About the author - p. xi 8. Foreword - p. xiii 9. Preface - p. xv 10. Acknowledgments - p. xix 11. 1. Foundations in Supply chain management - p. 1 12. 2. Framework for digital supply chain transformation - p. 35 13. 3. End-to-end supply chain visibility - p. 65 14. 4. System dynamics modeling for supply chain - p. 93 15. 5. Supply chain analytics and tools - p. 125 16. 5.1 Supply chain analytics - p. 125 17. 5.2 Types of supply chain analytics - p. 125 18. 5.3 Optimization in supply chain analytics - p. 133 19. 5.4 Simulation in supply chain - p. 148 20. 5.5 Forecasting in supply chain - p. 157 21. 5.6 Limitations and pitfalls of supply chain analytics - p. 166 22. Discussion questions - p. 167 23. Multiple-choice questions - p. 168 24. Answer key - p. 171 25. Numerical problems - p. 172 26. 6. Machine learning in supply chains - p. 175 27. 7. Artificial Intelligence applications in supply chain - p. 213 28. 8. Emerging trends in supply chain management - p. 259 29. Glossary - p. 321 30. Index - p. 327
