Big Data Driven Supply Chain Management
Big Data Driven Supply Chain Management

Author: Nada R. Sanders

Publisher: Pearson Education

Published: 2014-05-07

Total Pages: 273

ISBN-13: 0133762823

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Master a complete, five-step roadmap for leveraging Big Data and analytics to gain unprecedented competitive advantage from your supply chain. Using Big Data, pioneers such as Amazon, UPS, and Wal-Mart are gaining unprecedented mastery over their supply chains. They are achieving greater visibility into inventory levels, order fulfillment rates, material and product delivery… using predictive data analytics to match supply with demand; leveraging new planning strengths to optimize their sales channel strategies; optimizing supply chain strategy and competitive priorities; even launching powerful new ventures. Despite these opportunities, many supply chain operations are gaining limited or no value from Big Data. In Big Data Driven Supply Chain Management, Nada Sanders presents a systematic five-step framework for using Big Data in supply chains. You'll learn best practices for segmenting and analyzing customers, defining competitive priorities for each segment, aligning functions behind strategy, dissolving organizational boundaries to sense demand and make better decisions, and choose the right metrics to support all of this. Using these techniques, you can overcome the widespread obstacles to making the most of Big Data in your supply chain — and earn big profits from the data you're already generating. For all executives, managers, and analysts interested in using Big Data technologies to improve supply chain performance.

Supply Chain Management in the Big Data Era
Supply Chain Management in the Big Data Era

Author: Chan, Hing Kai

Publisher: IGI Global

Published: 2016-11-04

Total Pages: 319

ISBN-13: 1522509577

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Technological advancements in recent years have led to significant developments within a variety of business applications. In particular, data-driven research provides ample opportunity for enterprise growth, if utilized efficiently. Supply Chain Management in the Big Data Era is an authoritative reference source for the latest scholarly material on the implementation of big data analytics for improved operations and supply chain processes. Highlighting emerging strategies from different industry perspectives, this book is ideally designed for managers, professionals, practitioners, and students interested in the most recent research on supply chain innovations.

Exploring the Potentials of Automation in Logistics and Supply Chain Management
Exploring the Potentials of Automation in Logistics and Supply Chain Management

Author: Benjamin Nitsche

Publisher:

Published: 2021-10-31

Total Pages: 146

ISBN-13: 9783036519050

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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.

Fundamentals of Production Logistics
Fundamentals of Production Logistics

Author: Peter Nyhuis

Publisher: Springer Science & Business Media

Published: 2008-09-19

Total Pages: 320

ISBN-13: 3540342117

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At last, here is what logistics researchers have been waiting for: a book that comprehensively encapsulates for the first time the fundamentals of modeling Logistic Operating Curves for production and storage processes. The text includes information on how they can be derived and calculated based on standard operating data. In doing so, the authors clearly demonstrate the mutual dependencies between the often contradictory logistic objectives, i.e. on the one hand low throughput times and high delivery reliability and on the other hand low WIP levels and high rates of utilization. Moreover, they also explain how these objectives can be improved using the Logistic Operating Curve Theory and why this method thus provides an interesting alternative to simulations.

Data-Driven Technologies and Artificial Intelligence in Supply Chain
Data-Driven Technologies and Artificial Intelligence in Supply Chain

Author: Mahesh Chand

Publisher: CRC Press

Published: 2023-11-22

Total Pages: 319

ISBN-13: 1003802397

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This book highlights the importance of data-driven technologies and artificial intelligence in supply chain management. It covers important concepts such as enabling technologies in Industry 4.0, the impact of artificial intelligence, and data-driven technologies in lean manufacturing. "Provides solutions to solve complex supply chain management issues using artificial intelligence and data-driven technologies. " Emphasizes the impact of a data-driven supply chain on quality management. "Discusses applications of artificial intelligence, and data-driven technologies in the service industry, and lean manufacturing. " Highlights the barriers to implementing artificial intelligence in small and medium enterprises. Presents a better understanding of different risks such as procurement risks, process risks, demand risks, transportation risks, and operational risks. The book comprehensively discusses the applications of artificial intelligence and data-driven technologies in supply chain management for diverse fields such as service industries, manufacturing industries, and healthcare. It further covers the impact of artificial intelligence and data-driven technologies in managing the FMGC supply chain. It will be a valuable resource for senior undergraduate, graduate students, and academic researchers in diverse fields including electrical engineering, electronics and communications engineering, industrial engineering, manufacturing engineering, production engineering, and computer engineering.

Information Orientation
Information Orientation

Author: Donald A. Marchand

Publisher: Oxford University Press

Published: 2001

Total Pages: 332

ISBN-13: 9780199252213

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This book presents the results of an international research project designed to evaluate how effectively people use information and IT to improve business performance. In particular it looks at three dimensions - information behavior and values; information management practices; and IT practices - and their relationship to business performance. The book combines a focus on business relevance with strong empirical research.

Big Data Analytics in Supply Chain Management
Big Data Analytics in Supply Chain Management

Author: Iman Rahimi

Publisher: CRC Press

Published: 2020-12-20

Total Pages: 211

ISBN-13: 1000326918

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In a world of soaring digitization, social media, financial transactions, and production and logistics processes constantly produce massive data. Employing analytical tools to extract insights and foresights from data improves the quality, speed, and reliability of solutions to highly intertwined issues faced in supply chain operations. From procurement in Industry 4.0 to sustainable consumption behavior to curriculum development for data scientists, this book offers a wide array of techniques and theories of Big Data Analytics applied to Supply Chain Management. It offers a comprehensive overview and forms a new synthesis by bringing together seemingly divergent fields of research. Intended for Engineering and Business students, scholars, and professionals, this book is a collection of state-of-the-art research and best practices to spur discussion about and extend the cumulant knowledge of emerging supply chain problems.