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Author: Iman Rahimi
Publisher: CRC Press
ISBN: 1000326918
Category : Computers
Languages : en
Pages : 211
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Book Description
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.
Author: Iman Rahimi
Publisher: CRC Press
ISBN: 1000326918
Category : Computers
Languages : en
Pages : 211
Get Book
Book Description
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.
Author: Chan, Hing Kai
Publisher: IGI Global
ISBN: 1522509577
Category : Business & Economics
Languages : en
Pages : 299
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Book Description
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.
Author: Nada R. Sanders
Publisher: Pearson Education
ISBN: 0133762823
Category : Business & Economics
Languages : en
Pages : 273
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Book Description
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.
Author: Iman Rahimi
Publisher: CRC Press
ISBN: 1000326918
Category : Computers
Languages : en
Pages : 211
Get Book
Book Description
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.
Author: Peter W. Robertson
Publisher: Routledge
ISBN: 1000280500
Category : Business & Economics
Languages : en
Pages : 298
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Book Description
Supply Chain Analytics introduces the reader to data analytics and demonstrates the value of their effective use in supply chain management. By describing the key supply chain processes through worked examples, and the descriptive, predictive and prescriptive analytic methods that can be applied to bring about improvements to those processes, the book presents a more comprehensive learning experience for the reader than has been offered previously. Key topics are addressed, including optimisation, big data, data mining and cloud computing. The author identifies four core supply chain processes – strategy, design, execution and people – to which the analytic techniques explained can be applied to ensure continuous improvement. Pedagogy to aid learning is incorporated throughout, including an opening section for each chapter explaining the learnings designed for the chapter; worked examples illustrating how each analytic technique works, how it is applied and what to be careful of; tables, diagrams and equations to help ‘visualise’ the concepts and methods covered; chapter case studies; and end-of-chapter review questions and assignment tasks. Providing both management expertise and technical skills, which are essential to decision-makers in the supply chain, this textbook should be essential reading for advanced undergraduate and postgraduate students of supply chain analytics, supply chain leadership, and supply chain and operations management. Its practice-based and applied approach also makes it valuable for operating supply chain practitioners and those studying for professional qualifications. Online resources include chapter-by-chapter PowerPoint slides, tutorial exercises, written assignments and a test bank of exam questions.
Author: Thomas Davenport
Publisher: Harvard Business Review Press
ISBN: 1422168174
Category : Business & Economics
Languages : en
Pages : 241
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Book Description
Go ahead, be skeptical about big data. The author was—at first. When the term “big data” first came on the scene, bestselling author Tom Davenport (Competing on Analytics, Analytics at Work) thought it was just another example of technology hype. But his research in the years that followed changed his mind. Now, in clear, conversational language, Davenport explains what big data means—and why everyone in business needs to know about it. Big Data at Work covers all the bases: what big data means from a technical, consumer, and management perspective; what its opportunities and costs are; where it can have real business impact; and which aspects of this hot topic have been oversold. This book will help you understand: • Why big data is important to you and your organization • What technology you need to manage it • How big data could change your job, your company, and your industry • How to hire, rent, or develop the kinds of people who make big data work • The key success factors in implementing any big data project • How big data is leading to a new approach to managing analytics With dozens of company examples, including UPS, GE, Amazon, United Healthcare, Citigroup, and many others, this book will help you seize all opportunities—from improving decisions, products, and services to strengthening customer relationships. It will show you how to put big data to work in your own organization so that you too can harness the power of this ever-evolving new resource.
Author: Kusum Deep
Publisher: Springer
ISBN: 9811308721
Category : Business & Economics
Languages : en
Pages : 254
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Book Description
This book addresses a broad range of problems commonly encountered in the fields of financial analysis, logistics and supply chain management, such as the use of big data analytics in the banking sector. Divided into twenty chapters, some of the contemporary topics discussed in the book are co-operative/non-cooperative supply chain models for imperfect quality items with trade-credit financing; a non-dominated sorting water cycle algorithm for the cardinality constrained portfolio problem; and determining initial, basic and feasible solutions for transportation problems by means of the “supply demand reparation method” and “continuous allocation method.” In addition, the book delves into a comparison study on exponential smoothing and the Arima model for fuel prices; optimal policy for Weibull distributed deteriorating items varying with ramp type demand rate and shortages; an inventory model with shortages and deterioration for three different demand rates; outlier labeling methods for medical data; a garbage disposal plant as a validated model of a fault-tolerant system; and the design of a “least cost ration formulation application for cattle”; a preservation technology model for deteriorating items with advertisement dependent demand and trade credit; a time series model for stock price forecasting in India; and asset pricing using capital market curves. The book offers a valuable asset for all researchers and industry practitioners working in these areas, giving them a feel for the latest developments and encouraging them to pursue further research in this direction.
Author: Information Resources Management Association
Publisher: Engineering Science Reference
ISBN: 9781668436622
Category : Big data
Languages : en
Pages : 0
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Book Description
Society is now completely driven by data with many industries relying on data to conduct business or basic functions within the organization. With the efficiencies that big data bring to all institutions, data is continuously being collected and analyzed. However, data sets may be too complex for traditional data-processing, and therefore, different strategies must evolve to solve the issue. The field of big data works as a valuable tool for many different industries. The Research Anthology on Big Data Analytics, Architectures, and Applications is a complete reference source on big data analytics that offers the latest, innovative architectures and frameworks and explores a variety of applications within various industries. Offering an international perspective, the applications discussed within this anthology feature global representation. Covering topics such as advertising curricula, driven supply chain, and smart cities, this research anthology is ideal for data scientists, data analysts, computer engineers, software engineers, technologists, government officials, managers, CEOs, professors, graduate students, researchers, and academicians.
Author: Nada R. Sanders
Publisher: Pearson Education
ISBN: 0133801284
Category : Business & Economics
Languages : en
Pages : 273
Get Book
Book Description
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.
Author: Matthew J. Drake
Publisher: Pearson Education
ISBN: 0133407365
Category : Business & Economics
Languages : en
Pages : 217
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Book Description
The first collection of cases on "big data" analytics for supply chain, operations research, and operations management, this reference puts readers in the position of the analytics professional and decision-maker. Perfect for students, practitioners, and certification candidates in SCM, OM, and OR, these short, focused, to-the-point case studies illustrate the entire decision-making process. They provide realistic opportunities to perform analyses, interpret output, and recommend an optimal course of action. Contributed by leading "big data" experts, the cases in The Applied Business Analytics Casebook covers: Forecasting and statistical analysis: time series forecasting models, regression models, data visualization, and hypothesis testing Optimization and simulation: linear, integer, and nonlinear programming; Monte Carlo simulation and risk analysis; and stochastic optimization Decision analysis: decision making under uncertainty; expected value of perfect information; decision trees; game theory models; AHP; and multi-criteria decision making Advanced business analytics: data warehousing/mining; text mining; neural networks; financial analytics; CRM analytics; and revenue management models
