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| examples of artificial intelligence in supply chain management: The Art of Structuring Katrin Bergener, Michael Räckers, Armin Stein, 2019-01-25 Structuring, or, as it is referred to in the title of this book, the art of structuring, is one of the core elements in the discipline of Information Systems. While the world is becoming increasingly complex, and a growing number of disciplines are evolving to help make it a better place, structure is what is needed in order to understand and combine the various perspectives and approaches involved. Structure is the essential component that allows us to bridge the gaps between these different worlds, and offers a medium for communication and exchange. The contributions in this book build these bridges, which are vital in order to communicate between different worlds of thought and methodology – be it between Information Systems (IS) research and practice, or between IS research and other research disciplines. They describe how structuring can be and should be done so as to foster communication and collaboration. The topics covered reflect various layers of structure that can serve as bridges: models, processes, data, organizations, and technologies. In turn, these aspects are complemented by visionary outlooks on how structure influences the field. |
| examples of artificial intelligence in supply chain management: The Oxford Handbook of Supply Chain Management Thomas Y. Choi, Julie Juan Li, Dale S. Rogers, Tobias Schoenherr, Stephan M. Wagner, This handbook is currently in development, with individual articles publishing online in advance of print publication. At this time, we cannot add information about unpublished articles in this handbook, however the table of contents will continue to grow as additional articles pass through the review process and are added to the site. Please note that the online publication date for this handbook is the date that the first article in the title was published online. |
| examples of artificial intelligence in supply chain management: Data Analytics and Artificial Intelligence for Inventory and Supply Chain Management Dinesh K. Sharma, Madhu Jain, 2022 This book considers new analytics and AI approaches in the areas of inventory control, logistics, and supply chain management. It provides valuable insights for the retailers and managers to improve business operations and make more realistic and better decisions. It also offers a number of smartly designed strategies related to inventory control and supply chain management for the optimal ordering and delivery policies. The book further uses detailed models and AI computing approaches for demand forecasting to planning optimization and digital execution tracking. One of its key features is use of real-life examples, case studies, practical models to ensure adoption of new solutions, data analytics, and AI-lead automation methodologies are included. The book can be utilized by retailers and managers to improve business operations and make more accurate and realistic decisions. The AI-based solution, agnostic assessment, and strategy will support the companies for better alignment and inventory control and capabilities to create a strategic road map for supply chain and logistics. The book is also useful for postgraduate students, researchers, and corporate executives. It addresses novel solutions for inventory to real-world supply chain and logistics that retailers, practitioners, educators, and scholars will find useful. It provides the theoretical and applicable subject matters for the senior undergraduate and graduate students, researchers, practitioners, and professionals in the area of artificial intelligent computing and its applications in inventory and supply chain management, inventory control, and logistics. . |
| examples of artificial intelligence in supply chain management: Artificial Intelligence Harvard Business Review, 2019 Companies that don't use AI to their advantage will soon be left behind. Artificial intelligence and machine learning will drive a massive reshaping of the economy and society. What should you and your company be doing right now to ensure that your business is poised for success? These articles by AI experts and consultants will help you understand today's essential thinking on what AI is capable of now, how to adopt it in your organization, and how the technology is likely to evolve in the near future. Artificial Intelligence: The Insights You Need from Harvard Business Review will help you spearhead important conversations, get going on the right AI initiatives for your company, and capitalize on the opportunity of the machine intelligence revolution. Catch up on current topics and deepen your understanding of them with the Insights You Need series from Harvard Business Review. Featuring some of HBR's best and most recent thinking, Insights You Need titles are both a primer on today's most pressing issues and an extension of the conversation, with interesting research, interviews, case studies, and practical ideas to help you explore how a particular issue will impact your company and what it will mean for you and your business. |
| examples of artificial intelligence in supply chain management: Artificial Intelligence in Supply Chain Management Calvin Klein, 2023-10-06 As Artificial Intelligence (AI) continues to revolutionize industries worldwide, its omnipresence becomes increasingly evident in Supply Chain Management (SCM). This Consortium Study, conducted by the Institute of Supply Chain Management (ISCMHSG) at the University of St.Gallen and its promotional association, examines the integration of AI in SCM and aims to address the gap between expectations and reality. The study provides a knowledge foundation to assist supply chain managers in developingrealistic expectations of this technology. Considering the rapid advancement of AI technologies and their potential impact on SCM, this study explores the current state of AI in SCM and analyzes the disparity between expectations and reality. Through a comprehensive market analysis of AI solutions offered in SCM, opportunities for improvement are identified. The study focuses on aligning expectations and reality by fostering a better understanding of the capabilities of AI in SCM. Additionally, the study investigates obstacles to successful AI integration, including data quality, integration challenges, and unrealistic expectations of potential benefits. Through the collaborative efforts of the participating organizations, this Consortium Study offers a collective understanding of the current state of AI in SCM. It serves as a valuable resource for industry professionals, and academia facilitating the successful integration of AI and driving operational excellence in SCM. |
| examples of artificial intelligence in supply chain management: AI and Machine Learning Impacts in Intelligent Supply Chain Pandey, Binay Kumar, Kanike, Uday Kumar, George, A. Shaji, Pandey, Digvijay, 2024-01-29 Businesses are facing an unprecedented challenge - the urgent need to adapt and thrive in a world where intelligent factories and supply chains are the new norm. The digital transformation of supply chains is essential for staying competitive, but it is a complex journey fraught with uncertainties. How can organizations harness the power of emerging technologies like Artificial Intelligence (AI) and Machine Learning (ML) to increase profitability, cut supply chain costs, elevate customer service, and optimize their networks? The answers to these questions are crucial for business survival and success. AI and Machine Learning Impacts in Intelligent Supply Chain is a groundbreaking book that offers a comprehensive solution to the challenges posed by the Industry 4.0 revolution. This book is your indispensable guide to navigating the intricate world of supply chain digital transformation using innovative technologies. It provides real-world examples and insights that illustrate how AI and ML are the keys to solving complex supply chain problems, from inventory management to route optimization and beyond. Whether you are an academic scholar seeking to delve into the impact of AI and ML on supply chain management or a business leader striving to gain a competitive edge, this book is tailored to meet your needs. |
| examples of artificial intelligence in supply chain management: ICICCT 2019 – System Reliability, Quality Control, Safety, Maintenance and Management Vinit Kumar Gunjan, Vicente Garcia Diaz, Manuel Cardona, Vijender Kumar Solanki, K. V. N. Sunitha, 2019-06-27 This book discusses reliability applications for power systems, renewable energy and smart grids and highlights trends in reliable communication, fault-tolerant systems, VLSI system design and embedded systems. Further, it includes chapters on software reliability and other computer engineering and software management-related disciplines, and also examines areas such as big data analytics and ubiquitous computing. Outlining novel, innovative concepts in applied areas of reliability in electrical, electronics and computer engineering disciplines, it is a valuable resource for researchers and practitioners of reliability theory in circuit-based engineering domains. |
| examples of artificial intelligence in supply chain management: Innovative Supply Chain Management via Digitalization and Artificial Intelligence Kumaresan Perumal, Chiranji Lal Chowdhary, Logan Chella, 2022-04-06 This book focuses on the impact of artificial intelligence (AI) and machine learning (ML) models on supply chain operations in industry 4.0. The chapters illustrate the AI and ML models for all functional areas of operations in SCM. The book also includes examples using ML models like handling supply-to-demand imbalances, triggering automated responses, and reinforcing customer relationships. It describes the evolution of blockchain technology coupled with the ability to automate business logic for the transparency of goods, infrastructure, products, and licenses in software. The book also includes case studies that provide a problem statement and industry overcome by applying ML and AI technologies. This book is suitable for undergraduates, postgraduates, industrial professionals, business executives, entrepreneurs, and freelancers to encourage practical learning on AI and ML algorithms in SCM 4.0. Additionally, this book will provide computer science and information system professionals with the latest technologies embedded in the corporate world. |
| examples of artificial intelligence in supply chain management: Artificial Intelligence in Industrial Applications Steven Lawrence Fernandes, Tarun K. Sharma, 2021-12-07 This book highlights the analytics and optimization issues in industry, to propose new approaches, and to present applications of innovative approaches in real facilities. In the past few decades there has been an exponential rise in the application of artificial intelligence for solving complex and intricate problems arising in industrial domain. The versatility of these techniques have made them a favorite among scientists and researchers working in diverse areas. The book is edited to serve a broad readership, including computer scientists, medical professionals, and mathematicians interested in studying computational intelligence and their applications. It will also be helpful for researchers, graduate and undergraduate students with an interest in the fields of Artificial Intelligence and Industrial problems. This book will be a useful resource for researchers, academicians as well as professionals interested in the highly interdisciplinary field of Artificial Intelligence. |
| examples of artificial intelligence in supply chain management: Blockchain and Supply Chain Management Nir Kshetri, 2021-03-03 Blockchain and Supply Chain Management combines discussions of blockchain and supply chains, linking technologies such as artificial intelligence, Internet of Things, satellite imagery, and machine vision. The book examines blockchain's basic concepts, relevant theories, and its roles in meeting key supply chain objectives. The book addresses problems related to inefficiency, opacity, and fraud, helping the digitization process, simplifying the value creation process, and facilitating collaboration. The book is balanced between blockchain and supply chain application and theory, covering the latest technological, organizational and regulatory developments in blockchain from a supply chain perspective. The book discusses the opportunities, barriers, and enablers of blockchain in supply chain policy, along with legal and ethical implications. Supply chain management faces massive disruption with the dynamic changes in global trade, the impact of Covid-19, and technological innovation. Entire industries are also being transformed by blockchain, with some of the most promising applications in supply chain management. - Provides theoretical and practical insights into both blockchain and supply chains - Features numerous illustrative case studies, boxes, tables, and figures - Examines blockchain's impacts on supply chains in four key industries: Food and beverage, healthcare, pharmaceuticals, and finance |
| examples of artificial intelligence in supply chain management: Logistics 4.0 Turan Paksoy, Cigdem Gonul Kochan, Sadia Samar Ali, 2020-12-17 Industrial revolutions have impacted both, manufacturing and service. From the steam engine to digital automated production, the industrial revolutions have conduced significant changes in operations and supply chain management (SCM) processes. Swift changes in manufacturing and service systems have led to phenomenal improvements in productivity. The fast-paced environment brings new challenges and opportunities for the companies that are associated with the adaptation to the new concepts such as Internet of Things (IoT) and Cyber Physical Systems, artificial intelligence (AI), robotics, cyber security, data analytics, block chain and cloud technology. These emerging technologies facilitated and expedited the birth of Logistics 4.0. Industrial Revolution 4.0 initiatives in SCM has attracted stakeholders’ attentions due to it is ability to empower using a set of technologies together that helps to execute more efficient production and distribution systems. This initiative has been called Logistics 4.0 of the fourth Industrial Revolution in SCM due to its high potential. Connecting entities, machines, physical items and enterprise resources to each other by using sensors, devices and the internet along the supply chains are the main attributes of Logistics 4.0. IoT enables customers to make more suitable and valuable decisions due to the data-driven structure of the Industry 4.0 paradigm. Besides that, the system’s ability of gathering and analyzing information about the environment at any given time and adapting itself to the rapid changes add significant value to the SCM processes. In this peer-reviewed book, experts from all over the world, in the field present a conceptual framework for Logistics 4.0 and provide examples for usage of Industry 4.0 tools in SCM. This book is a work that will be beneficial for both practitioners and students and academicians, as it covers the theoretical framework, on the one hand, and includes examples of practice and real world. |
| examples of artificial intelligence in supply chain management: Applications of Artificial Intelligence in Process Systems Engineering Jingzheng Ren, Weifeng Shen, Yi Man, Lichun Dong, 2021-06-05 Applications of Artificial Intelligence in Process Systems Engineering offers a broad perspective on the issues related to artificial intelligence technologies and their applications in chemical and process engineering. The book comprehensively introduces the methodology and applications of AI technologies in process systems engineering, making it an indispensable reference for researchers and students. As chemical processes and systems are usually non-linear and complex, thus making it challenging to apply AI methods and technologies, this book is an ideal resource on emerging areas such as cloud computing, big data, the industrial Internet of Things and deep learning. With process systems engineering's potential to become one of the driving forces for the development of AI technologies, this book covers all the right bases. - Explains the concept of machine learning, deep learning and state-of-the-art intelligent algorithms - Discusses AI-based applications in process modeling and simulation, process integration and optimization, process control, and fault detection and diagnosis - Gives direction to future development trends of AI technologies in chemical and process engineering |
| examples of artificial intelligence in supply chain management: The Digital Supply Chain Bart L. MacCarthy, Dmitry Ivanov, 2022-06-09 The Digital Supply Chain is a thorough investigation of the underpinning technologies, systems, platforms and models that enable the design, management, and control of digitally connected supply chains. The book examines the origin, emergence and building blocks of the Digital Supply Chain, showing how and where the virtual and physical supply chain worlds interact. It reviews the enabling technologies that underpin digitally controlled supply chains and examines how the discipline of supply chain management is affected by enhanced digital connectivity, discussing purchasing and procurement, supply chain traceability, performance management, and supply chain cyber security. The book provides a rich set of cases on current digital practices and challenges across a range of industrial and business sectors including the retail, textiles and clothing, the automotive industry, food, shipping and international logistics, and SMEs. It concludes with research frontiers, discussing network science for supply chain analysis, challenges in Blockchain applications and in digital supply chain surveillance, as well as the need to re-conceptualize supply chain strategies for digitally transformed supply chains. |
| examples of artificial intelligence in supply chain management: Technology in Supply Chain Management and Logistics Anthony M. Pagano, Matthew Liotine, 2019-09-07 Technology in Supply Chain Management and Logistics: Current Practice and Future Applications analyzes the implications of these technologies in a variety of supply chain settings, including block chain, Internet of Things (IoT), inventory optimization, and medical supply chain. This book outlines how technologies are being utilized for product planning, materials management and inventory, transportation and distribution, workflow, maintenance, the environment, and in health and safety. Readers will gain a better understanding of the implications of these technologies with respect to value creation, operational effectiveness, investment level, technical migration and general industry acceptance. In addition, the book features case studies, providing a real-world look at supply chain technology implementations, their necessary training requirements, and how these new technologies integrate with existing business technologies. - Identifies emerging supply chain technologies and trends in technology acceptance and utilization levels across various industry sectors - Assists professionals with technology investment decisions, procurement, best values, and how they can be utilized for logistics operations - Features videos showing technology application, including optimization software, cloud computing, mobility, 3D printing, autonomous vehicles, drones and machine learning |
| examples of artificial intelligence in supply chain management: Applications of Machine Learning Prashant Johri, Jitendra Kumar Verma, Sudip Paul, 2020-05-04 This book covers applications of machine learning in artificial intelligence. The specific topics covered include human language, heterogeneous and streaming data, unmanned systems, neural information processing, marketing and the social sciences, bioinformatics and robotics, etc. It also provides a broad range of techniques that can be successfully applied and adopted in different areas. Accordingly, the book offers an interesting and insightful read for scholars in the areas of computer vision, speech recognition, healthcare, business, marketing, and bioinformatics. |
| examples of artificial intelligence in supply chain management: Artificial Intelligence in Healthcare Adam Bohr, Kaveh Memarzadeh, 2020-06-21 Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data |
| examples of artificial intelligence in supply chain management: Next Generation Supply Chains Rosanna Fornasiero, Saskia Sardesai, Ana Cristina Barros, Aristides Matopoulos, 2020-12-31 This open access book explores supply chains strategies to help companies face challenges such as societal emergency, digitalization, climate changes and scarcity of resources. The book identifies industrial scenarios for the next decade based on the analysis of trends at social, economic, environmental technological and political level, and examines how they may impact on supply chain processes and how to design next generation supply chains to answer these challenges. By mapping enabling technologies for supply chain innovation, the book proposes a roadmap for the full implementation of the supply chain strategies based on the integration of production and logistics processes. Case studies from process industry, discrete manufacturing, distribution and logistics, as well as ICT providers are provided, and policy recommendations are put forward to support companies in this transformative process. |
| examples of artificial intelligence in supply chain management: E-Logistics and E-Supply Chain Management Deryn Graham, Ioannis Manikas, Dimitris Folinas, 2013-04-30 This book explores the creation of integrated supply chains, the developments of virtual business, and the processes of re-engineering for business development--Provided by publisher. |
| examples of artificial intelligence in supply chain management: The AI-First Company Ash Fontana, 2021-05-04 Artificial Intelligence is transforming every industry, but if you want to win with AI, you have to put it first on your priority list. AI-First companies are the only trillion-dollar companies, and soon they will dominate even more industries, more definitively than ever before. These companies succeed by design--they collect valuable data from day one and use it to train predictive models that automate core functions. As a result, they learn faster and outpace the competition in the process. Thankfully, you don't need a Ph.D. to learn how to win with AI. In The AI-First Company, internationally-renowned startup investor Ash Fontana offers an executable guide for applying AI to business problems. It's a playbook made for real companies, with real budgets, that need strategies and tactics to effectively implement AI. Whether you're a new online retailer or a Fortune 500 company, Fontana will teach you how to: • Identify the most valuable data; • Build the teams that build AI; • Integrate AI with existing processes and keep it in check; • Measure and communicate its effectiveness; • Reinvest the profits from automation to compound competitive advantage. If the last fifty years were about getting AI to work in the lab, the next fifty years will be about getting AI to work for people, businesses, and society. It's not about building the right software -- it's about building the right AI. The AI-First Company is your guide to winning with artificial intelligence. |
| examples of artificial intelligence in supply chain management: OECD Business and Finance Outlook 2021 AI in Business and Finance OECD, 2021-09-24 The OECD Business and Finance Outlook is an annual publication that presents unique data and analysis on the trends, both positive and negative, that are shaping tomorrow’s world of business, finance and investment. |
| examples of artificial intelligence in supply chain management: The Fourth Industrial Revolution Klaus Schwab, 2017-01-03 World-renowned economist Klaus Schwab, Founder and Executive Chairman of the World Economic Forum, explains that we have an opportunity to shape the fourth industrial revolution, which will fundamentally alter how we live and work. Schwab argues that this revolution is different in scale, scope and complexity from any that have come before. Characterized by a range of new technologies that are fusing the physical, digital and biological worlds, the developments are affecting all disciplines, economies, industries and governments, and even challenging ideas about what it means to be human. Artificial intelligence is already all around us, from supercomputers, drones and virtual assistants to 3D printing, DNA sequencing, smart thermostats, wearable sensors and microchips smaller than a grain of sand. But this is just the beginning: nanomaterials 200 times stronger than steel and a million times thinner than a strand of hair and the first transplant of a 3D printed liver are already in development. Imagine “smart factories” in which global systems of manufacturing are coordinated virtually, or implantable mobile phones made of biosynthetic materials. The fourth industrial revolution, says Schwab, is more significant, and its ramifications more profound, than in any prior period of human history. He outlines the key technologies driving this revolution and discusses the major impacts expected on government, business, civil society and individuals. Schwab also offers bold ideas on how to harness these changes and shape a better future—one in which technology empowers people rather than replaces them; progress serves society rather than disrupts it; and in which innovators respect moral and ethical boundaries rather than cross them. We all have the opportunity to contribute to developing new frameworks that advance progress. |
| examples of artificial intelligence in supply chain management: Intelligent Decision Making: An AI-Based Approach Gloria Phillips-Wren, Nikhil Ichalkaranje, 2008-03-04 Intelligent Decision Support Systems have the potential to transform human decision making by combining research in artificial intelligence, information technology, and systems engineering. The field of intelligent decision making is expanding rapidly due, in part, to advances in artificial intelligence and network-centric environments that can deliver the technology. Communication and coordination between dispersed systems can deliver just-in-time information, real-time processing, collaborative environments, and globally up-to-date information to a human decision maker. At the same time, artificial intelligence techniques have demonstrated that they have matured sufficiently to provide computational assistance to humans in practical applications. This book includes contributions from leading researchers in the field beginning with the foundations of human decision making and the complexity of the human cognitive system. Researchers contrast human and artificial intelligence, survey computational intelligence, present pragmatic systems, and discuss future trends. This book will be an invaluable resource to anyone interested in the current state of knowledge and key research gaps in the rapidly developing field of intelligent decision support. |
| examples of artificial intelligence in supply chain management: Data Science for Supply Chain Forecast Nicolas Vandeput, 2018-11-12 Data Science for Supply Chain Forecast Data Science for Supply Chain Forecast is a book for practitioners focusing on data science and machine learning; it demonstrates how both are closely interlinked in order to create an advanced forecast for supply chain. As one will discover in this book, artificial intelligence (AI) & machine learning (ML) are not simply a question of coding skills. Using data science in order to solve a problem requires a scientific mindset more than coding skills. The story behind these models is one of experimentation, of observation and of constant questioning; a true scientific method must be applied to supply chain. In the data science field as well as that of the supply chain, simple questions do not come with simple answers. In order to resolve these questions, one needs to be both a scientist as well as to use the correct tools. In this book, we will discuss both. Is this Book for me? This book has been written for supply chain practitioners, forecasters and analysts who are looking to go the extra mile. You do not need technical IT skills to start using the models of this book. You do not need a dedicated server or expensive software licenses: you solely need your own computer. You do not need a PhD in mathematics: mathematics will only be utilized as a tool to tweak and understand the models. In the majority of the cases - especially when it comes to machine learning - a deep understanding of the mathematical inner workings of a model will not be necessary in order to optimize it and understand its limitations. Reviews In an age where analytics and machine learning are taking on larger roles in the business forecasting, Nicolas' book is perfect solution for professionals who need to combine practical supply chain experience with the mathematical and technological tools that can help us predict the future more reliably. Daniel Stanton - Author, Supply Chain Management For Dummies Open source statistical toolkits have progressed tremendously over the last decade. Nicolas demonstrates that these toolkits are more than enough to start addressing real-world forecasting challenges as found in supply chains. Moreover, through its hands-on approach, this book is accessible to a large audience of supply chain practitioners. The supply chain of the 21st century will be data-driven and Nicolas gets it perfectly. Joannes Vermorel - CEO Lokad This book is unique in its kind. It explains the basics of Python using basic traditional forecasting techniques and shows how machine learning is revolutionizing the forecasting domain. Nicolas has done an outstanding job explaining a technical subject in an easily accessible way. A must-read for any supply chain professional. Professor Bram Desmet - CEO Solventure This book is before anything a practical and business-oriented DIY user manual to help planners move into 21st-century demand planning. The breakthrough comes from several tools and techniques available to all, and which thanks to Nicolas' precise and concrete explanations can now be implemented in real business environments by any normal planner. I can confirm that Nicolas' learnings are based on real-life experience and can tremendously help on improving top and bottom lines. Henri-Xavier Benoist - VP Supply Chain Bridegstone EMEA |
| examples of artificial intelligence in supply chain management: Utilization of AI Technology in Supply Chain Management Pandey, Digvijay, Pandey, Binay Kumar, Kanike, Uday Kumar, George, A. Shaji, Kaur, Prabjot, 2024-03-01 The surge in digital transformation and the integration of innovative technologies into manufacturing processes have given rise to a pressing issue in supply chain management. Businesses are in dire need of solutions to navigate this complexity and harness the true potential of intelligent supply chains. Utilization of AI Technology in Supply Chain Management is a comprehensive guide tailored for academic scholars seeking to unravel the mysteries of artificial intelligence (AI) and machine learning (ML) in the context of supply chain management. Amid the hype surrounding AI and ML, there exists a critical need to bridge the gap between human expertise and technological advancements. Utilization of AI Technology in Supply Chain Management addresses this necessity by delving into real-world instances where teams have successfully employed these innovative technologies to enhance supply chain performance, reduce inventory, and optimize routes. The adoption of AI and ML is not just a trend; it is the cornerstone of digital acceleration initiatives, making it imperative for scholars to understand and leverage these technologies effectively. |
| examples of artificial intelligence in supply chain management: No Ordinary Disruption Richard Dobbs, James Manyika, Jonathan Woetzel, 2016-08-30 Our intuition on how the world works could well be wrong. We are surprised when new competitors burst on the scene, or businesses protected by large and deep moats find their defenses easily breached, or vast new markets are conjured from nothing. Trend lines resemble saw-tooth mountain ridges. The world not only feels different. The data tell us it is different. Based on years of research by the directors of the McKinsey Global Institute, No Ordinary Disruption: The Four Forces Breaking all the Trends is a timely and important analysis of how we need to reset our intuition as a result of four forces colliding and transforming the global economy: the rise of emerging markets, the accelerating impact of technology on the natural forces of market competition, an aging world population, and accelerating flows of trade, capital and people. Our intuitions formed during a uniquely benign period for the world economy -- often termed the Great Moderation. Asset prices were rising, cost of capital was falling, labour and resources were abundant, and generation after generation was growing up more prosperous than their parents. But the Great Moderation has gone. The cost of capital may rise. The price of everything from grain to steel may become more volatile. The world's labor force could shrink. Individuals, particularly those with low job skills, are at risk of growing up poorer than their parents. What sets No Ordinary Disruption apart is depth of analysis combined with lively writing informed by surprising, memorable insights that enable us to quickly grasp the disruptive forces at work. For evidence of the shift to emerging markets, consider the startling fact that, by 2025, a single regional city in China -- Tianjin -- will have a GDP equal to that of the Sweden, of that, in the decades ahead, half of the world's economic growth will come from 440 cities including Kumasi in Ghana or Santa Carina in Brazil that most executives today would be hard-pressed to locate on a map. What we are now seeing is no ordinary disruption but the new facts of business life -- facts that require executives and leaders at all levels to reset their operating assumptions and management intuition. |
| examples of artificial intelligence in supply chain management: The AI Advantage Thomas H. Davenport, 2019-08-06 Cutting through the hype, a practical guide to using artificial intelligence for business benefits and competitive advantage. In The AI Advantage, Thomas Davenport offers a guide to using artificial intelligence in business. He describes what technologies are available and how companies can use them for business benefits and competitive advantage. He cuts through the hype of the AI craze—remember when it seemed plausible that IBM's Watson could cure cancer?—to explain how businesses can put artificial intelligence to work now, in the real world. His key recommendation: don't go for the “moonshot” (curing cancer, or synthesizing all investment knowledge); look for the “low-hanging fruit” to make your company more efficient. Davenport explains that the business value AI offers is solid rather than sexy or splashy. AI will improve products and processes and make decisions better informed—important but largely invisible tasks. AI technologies won't replace human workers but augment their capabilities, with smart machines to work alongside smart people. AI can automate structured and repetitive work; provide extensive analysis of data through machine learning (“analytics on steroids”), and engage with customers and employees via chatbots and intelligent agents. Companies should experiment with these technologies and develop their own expertise. Davenport describes the major AI technologies and explains how they are being used, reports on the AI work done by large commercial enterprises like Amazon and Google, and outlines strategies and steps to becoming a cognitive corporation. This book provides an invaluable guide to the real-world future of business AI. A book in the Management on the Cutting Edge series, published in cooperation with MIT Sloan Management Review. |
| examples of artificial intelligence in supply chain management: Big Data, Cloud and Applications Youness Tabii, Mohamed Lazaar, Mohammed Al Achhab, Nourddine Enneya, 2018-08-13 This book constitutes the thoroughly refereed proceedings of the Third International Conference on Big Data, Cloud and Applications, BDCA 2018, held in Kenitra, Morocco, in April 2018.The 45 revised full papers presented in this book were carefully selected from 99 submissions with a thorough double-blind review process. They focus on the following topics: big data, cloud computing, machine learning, deep learning, data analysis, neural networks, information system and social media, image processing and applications, and natural language processing. |
| examples of artificial intelligence in supply chain management: Automated Planning Malik Ghallab, Dana Nau, Paolo Traverso, 2004-05-03 Publisher Description |
| examples of artificial intelligence in supply chain management: Information Technology Innovation National Academies of Sciences, Engineering, and Medicine, Division on Engineering and Physical Sciences, Computer Science and Telecommunications Board, Panel on Artificial Intelligence, Committee on Depicting Innovation in Information Technology, 2020-11-30 Information technology (IT) is widely understood to be the enabling technology of the 21st century. IT has transformed, and continues to transform, all aspects of our lives: commerce and finance, education, energy, health care, manufacturing, government, national security, transportation, communications, entertainment, science, and engineering. IT and its impact on the U.S. economyâ€both directly (the IT sector itself) and indirectly (other sectors that are powered by advances in IT)â€continue to grow in size and importance. IT’s impacts on the U.S. economyâ€both directly (the IT sector itself) and indirectly (other sectors that are powered by advances in IT)â€continue to grow. IT enabled innovation and advances in IT products and services draw on a deep tradition of research and rely on sustained investment and a uniquely strong partnership in the United States among government, industry, and universities. Past returns on federal investments in IT research have been extraordinary for both U.S. society and the U.S. economy. This IT innovation ecosystem fuels a virtuous cycle of innovation with growing economic impact. Building on previous National Academies work, this report describes key features of the IT research ecosystem that fuel IT innovation and foster widespread and longstanding impact across the U.S. economy. In addition to presenting established computing research areas and industry sectors, it also considers emerging candidates in both categories. |
| examples of artificial intelligence in supply chain management: Digital Business Strategies in Blockchain Ecosystems Umit Hacioglu, 2019-11-09 This book analyzes the effects of the latest technological advances in blockchain and artificial intelligence (AI) on business operations and strategies. Adopting an interdisciplinary approach, the contributions examine new developments that change the rules of traditional management. The chapters focus mainly on blockchain technologies and digital business in the Industry 4.0 context, covering such topics as accounting, digitalization and use of AI in business operations and cybercrime. Intended for academics, blockchain experts, students and practitioners, the book helps business strategists design a path for future opportunities. |
| examples of artificial intelligence in supply chain management: Application of Artificial Intelligence in Government Practices and Processes José Ramón Saura, Felipe Debasa, 2022 This book identifies the main uses that governments make of artificial intelligence and outlines define citizens' concerns about their privacy, covering topics that are essential to understanding how governments should use artificial intelligence in their practices and processes-- |
| examples of artificial intelligence in supply chain management: Supply Chain Management Pengzhong Li, 2011-04-26 The purpose of supply chain management is to make production system manage production process, improve customer satisfaction and reduce total work cost. With indubitable significance, supply chain management attracts extensive attention from businesses and academic scholars. Many important research findings and results had been achieved. Research work of supply chain management involves all activities and processes including planning, coordination, operation, control and optimization of the whole supply chain system. This book presents a collection of recent contributions of new methods and innovative ideas from the worldwide researchers. It is aimed at providing a helpful reference of new ideas, original results and practical experiences regarding this highly up-to-date field for researchers, scientists, engineers and students interested in supply chain management. |
| examples of artificial intelligence in supply chain management: Artificial Intelligence Stuart Russell, Peter Norvig, 2016-09-10 Artificial Intelligence: A Modern Approach offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. Number one in its field, this textbook is ideal for one or two-semester, undergraduate or graduate-level courses in Artificial Intelligence. |
| examples of artificial intelligence in supply chain management: Constraint Processing Rina Dechter, 2003-05-05 Constraint reasoning has matured over the last three decades with contributions from a diverse community of researchers in artificial intelligence, databases and programming languages, operations research, management science, and applied mathematics. In Constraint Processing, Rina Dechter synthesizes these contributions, as well as her own significant work, to provide the first comprehensive examination of the theory that underlies constraint processing algorithms. |
| examples of artificial intelligence in supply chain management: The Executive Guide to Artificial Intelligence Andrew Burgess, 2017-11-15 This book takes a pragmatic and hype–free approach to explaining artificial intelligence and how it can be utilised by businesses today. At the core of the book is a framework, developed by the author, which describes in non–technical language the eight core capabilities of Artificial Intelligence (AI). Each of these capabilities, ranging from image recognition, through natural language processing, to prediction, is explained using real–life examples and how they can be applied in a business environment. It will include interviews with executives who have successfully implemented AI as well as CEOs from AI vendors and consultancies. AI is one of the most talked about technologies in business today. It has the ability to deliver step–change benefits to organisations and enables forward–thinking CEOs to rethink their business models or create completely new businesses. But most of the real value of AI is hidden behind marketing hyperbole, confusing terminology, inflated expectations and dire warnings of ‘robot overlords’. Any business executive that wants to know how to exploit AI in their business today is left confused and frustrated. As an advisor in Artificial Intelligence, Andrew Burgess regularly comes face–to–face with business executives who are struggling to cut through the hype that surrounds AI. The knowledge and experience he has gained in advising them, as well as working as a strategic advisor to AI vendors and consultancies, has provided him with the skills to help business executives understand what AI is and how they can exploit its many benefits. Through the distilled knowledge included in this book business leaders will be able to take full advantage of this most disruptive of technologies and create substantial competitive advantage for their companies. |
| examples of artificial intelligence in supply chain management: Data Science for Supply Chain Forecasting Nicolas Vandeput, 2021-03-22 Using data science in order to solve a problem requires a scientific mindset more than coding skills. Data Science for Supply Chain Forecasting, Second Edition contends that a true scientific method which includes experimentation, observation, and constant questioning must be applied to supply chains to achieve excellence in demand forecasting. This second edition adds more than 45 percent extra content with four new chapters including an introduction to neural networks and the forecast value added framework. Part I focuses on statistical traditional models, Part II, on machine learning, and the all-new Part III discusses demand forecasting process management. The various chapters focus on both forecast models and new concepts such as metrics, underfitting, overfitting, outliers, feature optimization, and external demand drivers. The book is replete with do-it-yourself sections with implementations provided in Python (and Excel for the statistical models) to show the readers how to apply these models themselves. This hands-on book, covering the entire range of forecasting—from the basics all the way to leading-edge models—will benefit supply chain practitioners, forecasters, and analysts looking to go the extra mile with demand forecasting. |
| examples of artificial intelligence in supply chain management: Exploring the Potentials of Automation in Logistics and Supply Chain Management Benjamin Nitsche, 2021-10-31 The automation of physical and information logistics processes is one of the most challenging developments in logistics but is increasingly necessary in order to adequately deal with the increasing dynamics and uncertainties arising in logistics networks. If the automation of processes in logistics is systematically driven forward today, autonomous logistics systems are even conceivable in the future if the potential of digitalization is exploited. While some companies are already innovating in this area, the majority are still in the early stages of development. This book comprises the articles of a Special Issue on the application areas and potentials of automation in logistics on the path to autonomous logistics systems. The scientific contributions intend to contribute to a lively discourse in practice. The articles cover a broad spectrum of physical and informational automation applications with high practical relevance in individual subareas of logistics (e.g., production and transport) or in connection with the entire logistics network. Topics of IoT applications in intralogistics or holistic approaches of data-driven production logistics as well as autonomous driving or digital twin approaches for intermodal transport chains are covered. The implications for the human factor in logistics networks are also examined, and future research and action areas are identified. |
| examples of artificial intelligence in supply chain management: Supply Chain Secrets Rob O'Byrne, 2011 How to save your business millions!!! The international expert and author Rob O’Byrne gives his powerful and essential tips and insights based on over 1,200 client assignments across 22 countries. This book shows you how to find the greatest potential for massive savings and increased bottom line. You’ll Learn:* How to access the big ticket items to reduce costs* 5 critical tips on measuring for superior performance* Balancing cost and service for more effective distribution* How to stop inventory investment blow outs* 3 key steps to developing a game winning supply chain strategy* The 5 key steps to improving warehousing effectiveness* Avoiding the stuff that screws your supply chain performance |
| examples of artificial intelligence in supply chain management: Supply Chain Risk Management Gregory L. Schlegel, Robert J. Trent, 2014-10-14 You don’t have to outrun the bear ... you just have to outrun the other guy. Often in business we only have to run a bit faster than our competitors to be successful. The same is true in risk management. While we would always like to anticipate and prevent risk from happening, when risk events do occur being faster, flexible, and more responsive than others can make a world of difference. Supply Chain Risk Management: An Emerging Discipline gives you the tools and expertise to do just that. While the focus of the book is on how you can react better and faster than the others, the text also helps you understand how to prevent certain risks from happening in the first place. The authors detail a risk management framework that helps you reduce the costs associated with risk, protect your brand and reputation, ensure positive financial outcomes, and develop visible, predictable, resilient, and sustainable supply chains. They provide access to a cloud-based, end-to-end supply chain risk assessment Heat Map that illustrates the maturity of the chain through the various stages. It should not come as a surprise to anyone that the world is a riskier place than it was just 15 years ago. A survey used to calculate the Allianz Risk Barometer recently concluded for the first time that supply chain risk is now the top concern of global insurance providers. For most organizations this new reality requires major adjustments, some of which will not be easy. This book helps you understand the emerging discipline called supply chain risk management. It explains the relevant concepts, supplies a wide variety of tools and approaches to help your organization stay ahead of its competitors, and takes a look at future directions in risk management—all in a clear, concise presentation that gives you practical advice and helps you develop actionable strategies. |
| examples of artificial intelligence in supply chain management: Integration of Information Flow for Greening Supply Chain Management Adam Kolinski, Davor Dujak, Paulina Golinska-Dawson, 2020-09-03 This book provides a framework for integrating information management in supply chains. Current trends in business practice have made it necessary to explore the potential held by information integration with regard to environmental aspects. Information flow integration provides an opportunity to focus on the creation of a more “green” supply chain. However, it is currently difficult to identify the impact of information integration on greening a supply chain in a wide range of practical applications. Accordingly, this book focuses on the potential value of information integration solutions in terms of greening supply chain management. It covers the following major topics: Application of information flow standards in the supply chain Information systems and technological solutions for integrating information flows in supply chains The Internet of Things and the industry 4.0 concept, with regard to the integration of supply chains Modeling and simulation of logistics processes Decision-making tools enabling the greening of supply chains |
Examples - Apache ECharts
Apache ECharts，一款基于JavaScript的数据可视化图表库，提供直观，生动，可交互，可个性化定制的数据可视化图表。
Examples - Apache ECharts
Examples; Resources. Spread Sheet Tool; Theme Builder; Cheat Sheet; More Resources; Community. Events; Committers; Mailing List; How to Contribute; Dependencies; Code …
Examples - Apache ECharts
Examples; Resources. Spread Sheet Tool; Theme Builder; Cheat Sheet; More Resources; Community. Events; Committers; Mailing List; How to Contribute; Dependencies; Code …
Apache ECharts
ECharts: A Declarative Framework for Rapid Construction of Web-based Visualization. 如果您在科研项目、产品、学术论文、技术报告、新闻报告、教育、专利以及其他相关活动中使用了 …
Events - Apache ECharts
Examples; Resources. Spread Sheet Tool; Theme Builder; Cheat Sheet; More Resources; Community. Events; Committers; Mailing List; How to Contribute; Dependencies; Code …
Examples - Apache ECharts
Apache ECharts，一款基于JavaScript的数据可视化图表库，提供直观，生动，可交互，可个性化定制的数据可视化图表。
Examples - Apache ECharts
Examples; Resources. Spread Sheet Tool; Theme Builder; Cheat Sheet; More Resources; Community. Events; Committers; Mailing List; How to Contribute; Dependencies; Code Standard; …
Examples - Apache ECharts
Examples; Resources. Spread Sheet Tool; Theme Builder; Cheat Sheet; More Resources; Community. Events; Committers; Mailing List; How to Contribute; Dependencies; Code Standard; …
Apache ECharts
ECharts: A Declarative Framework for Rapid Construction of Web-based Visualization. 如果您在科研项目、产品、学术论文、技术报告、新闻报告、教育、专利以及其他相关活动中使用了 Apache …
Events - Apache ECharts
Examples; Resources. Spread Sheet Tool; Theme Builder; Cheat Sheet; More Resources; Community. Events; Committers; Mailing List; How to Contribute; Dependencies; Code Standard; …
