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| business analytics in supply chain management: Big Data Analytics in Supply Chain Management Iman Rahimi, Amir H. Gandomi, Simon James Fong, M. Ali Ülkü, 2020-12-20 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. |
| business analytics in supply chain management: Big Data Driven Supply Chain Management Nada R. Sanders, 2014-05-07 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. |
| business analytics in supply chain management: Supply Chain Analytics Peter W. Robertson, 2020-11-25 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. |
| business analytics in supply chain management: The Applied Business Analytics Casebook Matthew J. Drake, 2014 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 |
| business analytics in supply chain management: Emerging ICT for Bridging the Future - Proceedings of the 49th Annual Convention of the Computer Society of India (CSI) Volume 1 Suresh Chandra Satapathy, A. Govardhan, K. Srujan Raju, J. K. Mandal, 2014-11-30 This volume contains 73 papers presented at CSI 2014: Emerging ICT for Bridging the Future: Proceedings of the 49th Annual Convention of Computer Society of India. The convention was held during 12-14, December, 2014 at Hyderabad, Telangana, India. This volume contains papers mainly focused on Fuzzy Systems, Image Processing, Software Engineering, Cyber Security and Digital Forensic, E-Commerce, Big Data, Cloud Computing and ICT applications. |
| business analytics in supply chain management: Supply Chain Analytics and Modelling Nicoleta Tipi, 2021-04-03 An incredible volume of data is generated at a very high speed within the supply chain and it is necessary to understand, use and effectively apply the knowledge learned from analyzing data using intelligent business models. However, practitioners and students in the field of supply chain management face a number of challenges when dealing with business models and mathematical modelling. Supply Chain Analytics and Modelling presents a range of business analytics models used within the supply chain to help readers develop knowledge on a variety of topics to overcome common issues. Supply Chain Analytics and Modelling covers areas including supply chain planning, single and multi-objective optimization, demand forecasting, product allocations, end-to-end supply chain simulation, vehicle routing and scheduling models. Learning is supported by case studies of specialist software packages for each example. Readers will also be provided with a critical view on how supply chain management performance measurement systems have been developed and supported by reliable and accurate data available in the supply chain. Online resources including lecturer slides are available. |
| business analytics in supply chain management: Global Business Analytics Models Hokey Min, 2016-03-05 THE COMPLETE GUIDE TO USING ANALYTICS TO MANAGE RISK AND UNCERTAINTY IN COMPLEX GLOBAL BUSINESS ENVIRONMENTS Practical techniques for developing reliable, actionable intelligence–and using it to craft strategy Analytical opportunities to solve key managerial problems in global enterprises Written for working managers: packed with realistic, useful examples This guide helps global managers use modern analytics to gain reliable, actionable, and timely business intelligence–and use it to manage risk, build winning strategies, and solve urgent problems. Dr. Hokey Min offers a practical, easy-to-understand overview of business analytics in a global context, focusing especially on managerial and strategic implications. After demystifying today’s core quantitative tools, he demonstrates them at work in a wide spectrum of global applications. You’ll build models to help segment global markets, forecast demand, assess risk, plan financing, optimize supply chains, and more. Along the way, you’ll find practical guidance for developing analytic thinking, operationalizing Big Data in global environments, and preparing for future analytical innovations. Whether you’re a global executive, strategist, analyst, marketer, supply chain professional, student or researcher, this book will help you drive real value from analytics–in smarter decisions, improved strategy, and better management. In today’s global business environments characterized by growing complexity, volatility, and uncertainty, business analytics has become an indispensable tool for managing these challenges. Specifically, global managers need analytics expertise to solve problems, identify opportunities, shape strategy, mitigate risk, and improve their day-to-day operational efficiency. Now, for the first time, there’s an analytics guide designed specifically for decision-makers in global organizations. Leveraging his experience teaching a number of students and training hundreds of managers and executives, Dr. Hokey Min demystifies the principles and tools of modern business analytics, and demonstrates their real-world use in global business. First, Dr. Min identifies key success factors and mindsets, helping you establish the preconditions for effective analysis. Next, he walks you through the practicalities of collecting, organizing, and analyzing Big Data, and developing models to transform them into actionable insight. Building on these foundations, he illustrates core analytical applications in finance, healthcare, and global supply chains. He concludes by previewing emerging trends in analytics, including the newest tools for automated decision-making. Compare today’s key quantitative tools Stats, data mining, OR, and simulation: how they work, when to use them Get the right data... ...and get the data right Predict the future... ...and sense its arrival sooner than others can |
| business analytics in supply chain management: Big Data Analytics in Supply Chain Management Iman Rahimi, Amir H. Gandomi, Simon James Fong, M. Ali Ülkü, 2020-12-20 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. |
| business analytics in supply chain management: Logistics, Supply Chain and Financial Predictive Analytics Kusum Deep, Madhu Jain, Said Salhi, 2018-08-06 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. |
| business analytics in supply chain management: Supply Chain Planning and Analytics Gerald Feigin, 2011-08-31 Every company must continually wrestle with the problem of deciding the right quantity and mix of products or services that it should produce as well as when and where to produce them. The problem is challenging because the decision must be made with uncertain and conflicting information about future demand, available production capacity, and sources of supply. The decision is in fact a highly complex balancing act, involving tradeoffs along many dimensions - for example, inventory targets vs. customer service levels, older products vs. newer ones, direct customers vs. channel partners - and requiring the compromise of constituents - sales, marketing, operations, procurement, product development, finance, as well as suppliers and customers - with varied objectives. The ability of a company to nimbly navigate this decision process without giving too much influence to any of the parties involved largely determines how well the company can respond to changing market conditions and ultimately whether the company will continue to thrive. This book focuses on the complex challenges of supply chain planning - the set of business processes that companies use for planning to meet future demand. Supply chain planning comprises a variety of planning processes within an organization: demand planning, sales & operations planning, inventory planning, promotion planning, supply planning, production planning, distribution planning, and capacity planning. Of course, not all companies engage in all of these planning activities and they may refer to these activities by other names but they all struggle with the on-going effort of matching demand with supply. Many textbooks address supply chain planning problems and present mathematical tools and methods for solving certain classes of problems. This book is intended to complement these texts by focusing not on the mathematical models but on the problems that arise in practice that either these models do not adequately address or that make applying the models difficult or impossible. The book is not intended to provide pat solutions to these problems, but more to highlight the complexities and subtleties involved and describe ways to overcome practical issues that have worked for some companies. |
| business analytics in supply chain management: The Effect of Supply Chain Management on Business Performance Milan Frankl, 2018-03-22 Supply chain management (SCM) is the process of managing the operations of a system of organizations, people, activities, information, and resources involved in efficiently moving products or services from suppliers to customers. SCM can effectively conduct the movements of physical items, knowledge, and information from the original supplier to the final end-user. In this book, we explore the systemic analysis of SCM and its effect on business development performance. We identify the structural problems in the supply chain, clarify how they influence the functioning of business development, and suggest elaboration of strategic approaches to address those problems. The author includes professional perspectives and insights from experts including various SCM sources. |
| business analytics in supply chain management: Logistics Management Tan Miller, Matthew J. Liberatore, 2020-04-08 This book illustrates and explains a wide range of practical logistics strategies and analytic techniques to facilitate decision-making across functions such as manufacturing, warehousing, transportation, and inventory management. Logistics professionals must utilize a broad array of analytic techniques and approaches for decision-making. Effective use of analytics requires an understanding of both fundamental and advanced logistics decision-making techniques and methodologies. Further, logistics professionals must organize and view these analytics-based decision support tools through well-structured planning frameworks. In this book, we illustrate and explain a wide range of practical logistics strategies and analytic techniques to facilitate decision-making across functions such as manufacturing, warehousing, transportation and inventory management. We also describe how to organize these analytics-based tools and strategies through logistics frameworks that span strategic, tactical and operational planning and scheduling decisions. This book is intended for logistics professionals to use as a reference document that offers ideas and guidance for addressing specific logistics management decisions and challenges, and it will also serve as a valuable resource or secondary text for graduate and advanced undergraduate students. |
| business analytics in supply chain management: Supply Chain Analytics Kurt Y. Liu, 2022-04-07 This innovative new core textbook, written by an experienced professor and practitioner in supply chain management, offers a business-focused overview of the applications of data analytics and machine learning to supply chain management. Accessible yet rigorous, this text introduces students to the relevant concepts and techniques needed for data analysis and decision making in modern supply chains and enables them to develop proficiency in a popular and powerful programming software. Suitable for use on upper-level undergraduate, postgraduate and MBA courses in supply chain management, it covers all of the major supply chain processes, including managing supply and demand, warehousing and inventory control, transportation and route optimization. Each chapter comes with practical real-world examples drawn from a range of business contexts, including Amazon and Starbucks, case study discussion questions, computer-assisted exercises and programming projects. |
| business analytics in supply chain management: Supply Chain Management in the Big Data Era Chan, Hing Kai, Subramanian, Nachiappan, Abdulrahman, Muhammad Dan-Asabe, 2016-11-04 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. |
| business analytics in supply chain management: Encyclopedia of Organizational Knowledge, Administration, and Technology Khosrow-Pour D.B.A., Mehdi, 2020-09-29 For any organization to be successful, it must operate in such a manner that knowledge and information, human resources, and technology are continually taken into consideration and managed effectively. Business concepts are always present regardless of the field or industry – in education, government, healthcare, not-for-profit, engineering, hospitality/tourism, among others. Maintaining organizational awareness and a strategic frame of mind is critical to meeting goals, gaining competitive advantage, and ultimately ensuring sustainability. The Encyclopedia of Organizational Knowledge, Administration, and Technology is an inaugural five-volume publication that offers 193 completely new and previously unpublished articles authored by leading experts on the latest concepts, issues, challenges, innovations, and opportunities covering all aspects of modern organizations. Moreover, it is comprised of content that highlights major breakthroughs, discoveries, and authoritative research results as they pertain to all aspects of organizational growth and development including methodologies that can help companies thrive and analytical tools that assess an organization’s internal health and performance. Insights are offered in key topics such as organizational structure, strategic leadership, information technology management, and business analytics, among others. The knowledge compiled in this publication is designed for entrepreneurs, managers, executives, investors, economic analysts, computer engineers, software programmers, human resource departments, and other industry professionals seeking to understand the latest tools to emerge from this field and who are looking to incorporate them in their practice. Additionally, academicians, researchers, and students in fields that include but are not limited to business, management science, organizational development, entrepreneurship, sociology, corporate psychology, computer science, and information technology will benefit from the research compiled within this publication. |
| business analytics in supply chain management: Supply Chain 4.0 Emel Aktas, Michael Bourlakis, Ioannis Minis, Vasileios Zeimpekis, 2021-02-03 Supply Chain 4.0 has introduced automation into logistics and supply chain processes, exploiting predictive analytics to better match supply with demand, optimizing operations and using the latest technologies for the last mile delivery such as drones and autonomous robots. Supply Chain 4.0 presents new methods, techniques, and information systems that support the coordination and optimization of logistics processes, reduction of operational costs as well as the emergence of entirely new services and business processes. This edited collection includes contributions from leading international researchers from academia and industry. It considers the latest technologies and operational research methods available to support smart, integrated, and sustainable logistics practices focusing on automation, big data, Internet of Things, and decision support systems for transportation and logistics. It also highlights market requirements and includes case studies of cutting-edge applications from innovators in the logistics industry. |
| business analytics in supply chain management: Business Analytics Principles, Concepts, and Applications with SAS Marc J. Schniederjans, Dara G. Schniederjans, Christopher M. Starkey, 2014-10-07 Responding to a shortage of effective content for teaching business analytics, this text offers a complete, integrated package of knowledge for newcomers to the subject. The authors present an up-to-date view of what business analytics is, why it is so valuable, and most importantly, how it is used. They combine essential conceptual content with clear explanations of the tools, techniques, and methodologies actually used to implement modern business analytics initiatives. Business Analytics Principles, Concepts, and Applications with SAS offers a proven step-wise approach to designing an analytics program, and successfully integrating it into your organization, so it effectively provides intelligence for competitive advantage in decision making. Using step-by-step examples, the authors identify common challenges that can be addressed by business analytics, illustrate each type of analytics (descriptive, prescriptive, and predictive), and guide users in undertaking their own projects. Illustrating the real-world use of statistical, information systems, and management science methodologies, these examples help readers successfully apply the methods they are learning. Unlike most competitive guides, Business Analytics Principles, Concepts, and Applications with SAS demonstrates the use of SAS software, permitting instructors to spend less time teaching software and more time focusing on business analytics itself. |
| business analytics in supply chain management: Business Process Orientation Kevin P. McCormack, William C. Johnson, 2001-01-24 Business Process Orientation: Gaining the E-Business Competitive Advantage provides the why and the how for building the horizontal organization - an essential component of the e in e-commerce and business. This book shows you how to weave your business processes into hard-to-imitate strategic capabilities that distinguish you from your competition. The book explores the impact that well-defined and carefully integrated processes have on organizational performance. Using the results of extensive research conducted among consumer, business-to-business, and services-based companies, the authors demonstrate that adopting a business process orientation (BPO) has a positive impact on the organizational culture and business performance. The resulting process oriented e-corporation is now positioned as a necessity not only to thrive but also to survive. The old ways of conducting business are out: pushing costs and compromising quality in order to achieve the lowest possible price. The emerging paradigm focuses on the core processes. The hallmarks of a great business still include high customer relevance, internally consistent decisions about scope and value chain activities performed, value capture mechanisms, a source of differentiation and strategic control, a sound operational system, and carefully designed processes. Business Process Orientation: Gaining the E-Business Competitive Advantage shows you how to balance your functional and horizontal orientation to create and maintain a healthy organization. |
| business analytics in supply chain management: Supply Chain Optimization, Management and Integration: Emerging Applications Wang, John, 2010-11-30 Our rapidly changing world has forced business practitioners, in corporation with academic researchers, to respond quickly and develop effective solution methodologies and techniques to handle new challenges in supply chain systems. Supply Chain Optimization, Management and Integration: Emerging Applications presents readers with a rich collection of ideas from researchers who are bridging the gap between the latest in information technology and supply chain management. This book includes theoretical, analytical, and empirical research, comprehensive reviews of relevant research, and case studies of effective applications in the field of SCM. The use of new technologies, methods, and techniques are emphasized by those who have worked with supply chain management across the world for those in the field of information systems. |
| business analytics in supply chain management: Inventory Analytics Horst Tempelmeier, 2020-06-02 This textbook provides a practice-oriented introduction into Analytics-based inventory management in complex supply chains. In the context of Business Analytics, we concentrate on Prescriptive Analytics. In addition to standard single-level inventory models also multi-level approaches for the optimal allocation of safety inventory are presented. Moreover, dynamic lot sizing problems under random demand and random yield and their relationship to Material Requirements Planning (MRP) are discussed.The models and algorithms are illustrated with the help of numerous examples. The book has been written for students of Supply Chain Management and Operations Management as well as for practitioners who are confronted with inventory management in their daily work. |
| business analytics in supply chain management: The Profit Impact of Business Intelligence Steve Williams, Nancy Williams, 2010-07-27 The Profit Impact of Business Intelligence presents an A-to-Z approach for getting the most business intelligence (BI) from a company's data assets or data warehouse. BI is not just a technology or methodology, it is a powerful new management approach that – when done right – can deliver knowledge, efficiency, better decisions, and profit to almost any organization that uses it. When BI first came on the scene, it promised a lot but often failed to deliver. The missing element was the business-centric focus explained in this book. It shows how you can achieve the promise of BI by connecting it to your organization's strategic goals, culture, and strengths while correcting your BI weaknesses. It provides a practical, process-oriented guide to achieve the full promise of BI; shows how world-class companies used BI to become leaders in their industries; helps senior business and IT executives understand the strategic impact of BI and how they can ensure a strong payoff from their BI investments; and identifies the most common mistakes organizations make in implementing BI. The book also includes a helpful glossary of BI terms; a BI readiness assessment for your organization; and Web links and extensive references for more information. - A practical, process-oriented book that will help organizations realize the promise of BI - Written by Nancy and Steve Williams, veteran consultants and instructors with hands-on, in the trenches experience in government and corporate business intelligence applications - Will help senior business and IT executives understand the strategic impact of BI and how they can help ensure a strong payoff on BI investments |
| business analytics in supply chain management: Encyclopedia of Business Analytics and Optimization Wang, John, 2014-02-28 As the age of Big Data emerges, it becomes necessary to take the five dimensions of Big Data- volume, variety, velocity, volatility, and veracity- and focus these dimensions towards one critical emphasis - value. The Encyclopedia of Business Analytics and Optimization confronts the challenges of information retrieval in the age of Big Data by exploring recent advances in the areas of knowledge management, data visualization, interdisciplinary communication, and others. Through its critical approach and practical application, this book will be a must-have reference for any professional, leader, analyst, or manager interested in making the most of the knowledge resources at their disposal. |
| business analytics in supply chain management: Competing on Analytics Thomas H. Davenport, Jeanne G. Harris, 2007-03-06 You have more information at hand about your business environment than ever before. But are you using it to “out-think” your rivals? If not, you may be missing out on a potent competitive tool. In Competing on Analytics: The New Science of Winning, Thomas H. Davenport and Jeanne G. Harris argue that the frontier for using data to make decisions has shifted dramatically. Certain high-performing enterprises are now building their competitive strategies around data-driven insights that in turn generate impressive business results. Their secret weapon? Analytics: sophisticated quantitative and statistical analysis and predictive modeling. Exemplars of analytics are using new tools to identify their most profitable customers and offer them the right price, to accelerate product innovation, to optimize supply chains, and to identify the true drivers of financial performance. A wealth of examples—from organizations as diverse as Amazon, Barclay’s, Capital One, Harrah’s, Procter & Gamble, Wachovia, and the Boston Red Sox—illuminate how to leverage the power of analytics. |
| business analytics in supply chain management: Integrating Blockchain Technology Into the Circular Economy Khan, Syed Abdul Rehman, 2022-03-11 In recent decades, the industrial revolution has increased economic growth despite its immersion in global environmental issues such as climate change. Researchers emphasize the adoption of circular economy practices in global supply chains and businesses for better socio-environmental sustainability without compromising economic growth. Integrating blockchain technology into business practices could promote the circular economy as well as global environmental sustainability. Integrating Blockchain Technology Into the Circular Economy discusses the technological advancements in circular economy practices, which provide better results for both economic growth and environmental sustainability. It provides relevant theoretical frameworks and the latest empirical research findings in the applications of blockchain technology. Covering topics such as big data analytics, financial market infrastructure, and sustainable performance, this book is an essential resource for managers, operations managers, executives, manufacturers, environmentalists, researchers, industry practitioners, students and educators of higher education, and academicians. |
| business analytics in supply chain management: Applied Business Analytics Nathaniel Lin, 2015 Now that you've collected the data and crunched the numbers, what do you do with all this information? How do you take the fruit of your analytics labor and apply it to business decision making? How do you actually apply the information gleaned from quants and tech teams? Applied Business Analytics will help you find optimal answers to these questions, and bridge the gap between analytics and execution in your organization. Nathaniel Lin explains why analytics value chains often break due to organizational and cultural issues, and offers in the trenches guidance for overcoming these obstacles. You'll learn why a special breed of analytics deciders is indispensable for any organization that seeks to compete on analytics; how to become one of those deciders; and how to identify, foster, support, empower, and reward others who join you. Lin draws on actual cases and examples from his own experience, augmenting them with hands-on examples and exercises to integrate analytics at every level: from top-level business questions to low-level technical details. Along the way, you'll learn how to bring together analytics team members with widely diverse goals, knowledge, and backgrounds. Coverage includes: How analytical and conventional decision making differ -- and the challenging implications How to determine who your analytics deciders are, and ought to be Proven best practices for actually applying analytics to decision-making How to optimize your use of analytics as an analyst, manager, executive, or C-level officer |
| business analytics in supply chain management: Supply Chain Network Design Michael Watson, 2013 Introduction and basic building blocks. Adding costs to two echelon supply chains. Advanced modeling and expanding to multiple echelons. How to get industrial streng results. Case study wrap up. |
| business analytics in supply chain management: Towards Supply Chain Risk Analytics Iris Heckmann, 2016-07-20 In this thesis, Iris Heckmann develops a profound conceptual basis of supply chain risk analytics. She transfers the newly defined concepts for the modelling and operationalization of supply chain risk within simulation and optimization approaches, in order to ease unexpected deviations and disruptions, which are subsumed under the notion of supply chain risk, increasingly aggravating the planning and optimization of supply chains. |
| business analytics in supply chain management: Customer Loyalty and Supply Chain Management Ivan Russo, Ilenia Confente, 2017-08-03 Many business-to-business (B2B) managers think that customers act rationally and base decisions mostly on price, customer loyalty isn’t considered. Companies outsource various activities, which enable them to improve efficiency, reduce costs, focus more on core competencies and improve their innovation capabilities. Supply Chain Management synchronizes the efforts of all parties—particularly suppliers, manufacturers, retailers, dealers, customers—involved in achieving customer’s needs. Despite much research, the relationship between customer loyalty and the supply chain strategy remains insufficiently explored and understood by practitioners and academics, while the theme has been extensively developed within marketing literature. Customer Loyalty and Supply Chain Management is the result of years of work by the authors on different projects concerning the overlapping areas of supply chains, logistics and marketing, drawing a connection between the literature to provide a holistic picture of the customer loyalty framework. Emphasis is given to the B2B context, where recent research has provided some clues to support the fact that investment in operations, new technologies and organizational strategy have had a significant role in understanding B2B loyalty, particularly in the context of global supply chains. Moreover, the book provides a modernized and predictive model of B2B loyalty, showing a different methodological approach that aims at capturing the complexity of the phenomenon. This book will be a useful resource for professionals and scholars from across the supply chain who are interested in exploring the dimension of customer loyalty in the challenging supplier and customer context. |
| business analytics in supply chain management: Analytics in a Big Data World Bart Baesens, 2014-04-15 The guide to targeting and leveraging business opportunities using big data & analytics By leveraging big data & analytics, businesses create the potential to better understand, manage, and strategically exploiting the complex dynamics of customer behavior. Analytics in a Big Data World reveals how to tap into the powerful tool of data analytics to create a strategic advantage and identify new business opportunities. Designed to be an accessible resource, this essential book does not include exhaustive coverage of all analytical techniques, instead focusing on analytics techniques that really provide added value in business environments. The book draws on author Bart Baesens' expertise on the topics of big data, analytics and its applications in e.g. credit risk, marketing, and fraud to provide a clear roadmap for organizations that want to use data analytics to their advantage, but need a good starting point. Baesens has conducted extensive research on big data, analytics, customer relationship management, web analytics, fraud detection, and credit risk management, and uses this experience to bring clarity to a complex topic. Includes numerous case studies on risk management, fraud detection, customer relationship management, and web analytics Offers the results of research and the author's personal experience in banking, retail, and government Contains an overview of the visionary ideas and current developments on the strategic use of analytics for business Covers the topic of data analytics in easy-to-understand terms without an undo emphasis on mathematics and the minutiae of statistical analysis For organizations looking to enhance their capabilities via data analytics, this resource is the go-to reference for leveraging data to enhance business capabilities. |
| business analytics in supply chain management: Supply Chain Excellence Peter Bolstorff, Robert G. Rosenbaum, 2012 In this latest edition of Supply Chain Excellence, the authors provide tools for measuring financial gains linked to value chain optimisation. (Business Digest, March 2012). To keep your sales, manufacturing, distribution, and inventory moving in perfect synchronization, you need a flawless, repeatable supply chain improvement approach that maximizes process efficiency, eliminates dysfunction, and aligns disparate organizations-globally. |
| business analytics in supply chain management: Big Data Driven Supply Chain Management Nada Sanders, 2018-09-15 |
| business analytics in supply chain management: Artificial Intelligence. An International Perspective Max Bramer, 2009-09-19 Artificial Intelligence (AI) is a rapidly growing inter-disciplinary field with a long and distinguished history that involves many countries and considerably pre-dates the development of computers. It can be traced back at least as far as Ancient Greece and has evolved over time to become a major subfield of computer science in general. This state-of-the-art survey not only serves as a position paper on the field from the viewpoint of expert members of the IFIP Technical Committee 12, its Working Groups and their colleagues, but also presents overviews of current work in different countries. The chapters describe important relatively new or emerging areas of work in which the authors are personally involved, including text and hypertext categorization; autonomous systems; affective intelligence; AI in electronic healthcare systems; artifact-mediated society and social intelligence design; multilingual knowledge management; agents, intelligence and tools; intelligent user profiling; and supply chain business intelligence. They provide an interesting international perspective on where this significant field is going at the end of the first decade of the twenty-first century. |
| business analytics in supply chain management: Recent Developments in Data Science and Business Analytics Madjid Tavana, Srikanta Patnaik, 2018-03-27 This edited volume is brought out from the contributions of the research papers presented in the International Conference on Data Science and Business Analytics (ICDSBA- 2017), which was held during September 23-25 2017 in ChangSha, China. As we all know, the field of data science and business analytics is emerging at the intersection of the fields of mathematics, statistics, operations research, information systems, computer science and engineering. Data science and business analytics is an interdisciplinary field about processes and systems to extract knowledge or insights from data. Data science and business analytics employ techniques and theories drawn from many fields including signal processing, probability models, machine learning, statistical learning, data mining, database, data engineering, pattern recognition, visualization, descriptive analytics, predictive analytics, prescriptive analytics, uncertainty modeling, big data, data warehousing, data compression, computer programming, business intelligence, computational intelligence, and high performance computing among others. The volume contains 55 contributions from diverse areas of Data Science and Business Analytics, which has been categorized into five sections, namely: i) Marketing and Supply Chain Analytics; ii) Logistics and Operations Analytics; iii) Financial Analytics. iv) Predictive Modeling and Data Analytics; v) Communications and Information Systems Analytics. The readers shall not only receive the theoretical knowledge about this upcoming area but also cutting edge applications of this domains. |
| business analytics 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. |
| business analytics in supply chain management: Digital Transformation of the Economy: Challenges, Trends and New Opportunities Svetlana Ashmarina, Anabela Mesquita, Marek Vochozka, 2019-02-05 This book gathers the best contributions from the conference “Digital Transformation of the Economy: Challenges, Trends and New Opportunities”, which took place in Samara, Russian Federation, on May 29–31, 2018. Organized by Samara State University of Economics (Samara), Russia, the conference was devoted to issues of the digital economy.Presenting international research on the impact of digitalization on economic development, it includes topics such as the transformation of the institutional environment under the influence of informatization, the comparative analysis of the digitalization development in different countries, and modeling the dependence of the rate of change in the economy on the level of the digitalization penetration into various spheres of human activity. It also covers business-process transformation in the context of digitalization and changes in the structure of employment and personnel training for the digital economy. Lastly, it addresses the issue of ensuring information security and dealing with information risks for both individual enterprises and national economies as a whole. The book appeals to both students and researchers whose interests include the development of the digital economy, as well as to managers and professionals who integrate digital solutions into real-world business practice. |
| business analytics in supply chain management: Applying Business Intelligence Initiatives in Healthcare and Organizational Settings Miah, Shah J., Yeoh, William, 2018-07-13 Data analysis is an important part of modern business administration, as efficient compilation of information allows managers and business leaders to make the best decisions for the financial solvency of their organizations. Understanding the use of analytics, reporting, and data mining in everyday business environments is imperative to the success of modern businesses. Applying Business Intelligence Initiatives in Healthcare and Organizational Settings incorporates emerging concepts, methods, models, and relevant applications of business intelligence systems within problem contexts of healthcare and other organizational boundaries. Featuring coverage on a broad range of topics such as rise of embedded analytics, competitive advantage, and strategic capability, this book is ideally designed for business analysts, investors, corporate managers, and entrepreneurs seeking to advance their understanding and practice of business intelligence. |
| business analytics in supply chain management: Supply Chain Management Bowon Kim, 2018-02-22 This edition of Supply Chain Management (SCM) was revised to appeal to a wider readership besides students taking SCM courses. Global supply chain managers and researchers in the fields of SCM and operations strategy would find it a useful reference. Rather than discuss the technical issues of SCM, the book focuses on the strategic perspectives and approaches of SCM. Students learn to identify SCM issues from the top management's perspective. The book also presents real-world managerial problems and incorporates case studies for connecting theories with practices. By exploring the fundamental issues of SCM, managers acquire a new learning perspective that enables them to solve problems in a more sustainable and innovative manner rather than use short-term, ad hoc solutions. Finally, it distils various theoretical concepts to allow researchers to observe real SCM issues in a managerial context which allows for practical, meaningful and impactful research to be carried out. |
| business analytics in supply chain management: Handbook of Quantitative Supply Chain Analysis David Simchi-Levi, S. David Wu, Zuo-Jun Shen, 2004-05-31 The Handbook is a comprehensive research reference that is essential for anyone interested in conducting research in supply chain. Unique features include: -A focus on the intersection of quantitative supply chain analysis and E-Business, -Unlike other edited volumes in the supply chain area, this is a handbook rather than a collection of research papers. Each chapter was written by one or more leading researchers in the area. These authors were invited on the basis of their scholarly expertise and unique insights in a particular sub-area, -As much attention is given to looking back as to looking forward. Most chapters discuss at length future research needs and research directions from both theoretical and practical perspectives, -Most chapters describe in detail the quantitative models used for analysis and the theoretical underpinnings; many examples and case studies are provided to demonstrate how the models and the theoretical insights are relevant to real situations, -Coverage of most state-of-the-art business practices in supply chain management. |
| business analytics in supply chain management: Supply Chain Management For Dummies Daniel Stanton, 2017-11-29 Everyone can impact the supply chain Supply Chain Management For Dummies helps you connect the dots between things like purchasing, logistics, and operations to see how the big picture is affected by seemingly isolated inefficiencies. Your business is a system, made of many moving parts that must synchronize to most efficiently meet the needs of your customers—and your shareholders. Interruptions in one area ripple throughout the entire operation, disrupting the careful coordination that makes businesses successful; that's where supply chain management (SCM) comes in. SCM means different things to different people, and many different models exist to meet the needs of different industries. This book focuses on the broadly-applicable Supply Chain Operations Reference (SCOR) Model: Plan, Source, Make, Deliver, Return, and Enable, to describe the basic techniques and key concepts that keep businesses running smoothly. Whether you're in sales, HR, or product development, the decisions you make every day can impact the supply chain. This book shows you how to factor broader impact into your decision making process based on your place in the system. Improve processes by determining your metrics Choose the right software and implement appropriate automation Evaluate and mitigate risks at all steps in the supply chain Help your business function as a system to more effectively meet customer needs We tend to think of the supply chain as suppliers, logistics, and warehousing—but it's so much more than that. Every single person in your organization, from the mailroom to the C-suite, can work to enhance or hinder the flow. Supply Chain Management For Dummies shows you what you need to know to make sure your impact leads to positive outcomes. |
| business analytics in supply chain management: Research Anthology on Big Data Analytics, Architectures, and Applications Information Resources Management Association, 2022 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. |
A Review on Data Analytics for Supply Chain Management: A …
Abstract—The present study bridges the gap between the two intersecting domains, data science and supply chain management. The data can be analyzed for inventory management, …
The impact of big data and business analytics on supply chain …
This article therefore endeavours to expose supply chain managers to these changes and to highlight, define and discuss the various concepts and trends around ‘big data’
Reviewing predictive analytics in supply chain management: …
By synthesizing existing research, case studies, and real-world examples, this paper aims to offer valuable insights into the practical implications of integrating predictive analytics into various …
Big data and the supply chain: The big supply chain analytics …
Big supply chain analytics uses data and quantitative methods to improve decision making for all activities across the supply chain. In particular, it does two new things. First, it expands the …
The impact of business analytics on supply chain performance
Supply chain management Analytical capabilities Information systems Business process management Performance SCOR The paper investigates the relationship between analytical …
THE POWER OF PREDICTIVE ANALYTICS IN SUPPLY CHAIN …
In today's fast-paced business environment, supply chain management (SCM) is a critical pillar for success, but is ridden with complexities and uncertainties. The integration of predictive …
Understanding Supply Chain Analytics - Dun & Bradstreet
Supply chain analytics rely on data and algorithms to help government agencies manage risk, save money, and make the entire procurement process more efficient. Supply chain data can …
PREDICTIVE ANALYTICS AND ITS ROLE IN OPTIMIZING …
By incorporating predictive analytics into supply chain management, businesses can enhance decision-making, reduce waste, improve resource efficiency, and forecast potential disruptions …
Analytics in Supply Change Management: Is There a Dark Side?
an overview of supply chain management and the critical role of analytics to enhance supply chain processes and, subsequently, performance. While efficiency and effectiven
Big Data Analytics in Supply Chain Management: Applications …
It examined the big data analytics and its processes; supply chain management; big data analytics methods in supply chain management; applications of big data analytics in supply chain …
Supply Chain Analytics The three-minute guide - Deloitte …
If your supply chain management models are based only on past demand, supply, and business cycles, you could be missing big opportunities to put analytics to work.
Predictive Analytics in Supply Chain Management using SAP …
predictive analytics in optimizing supply chain processes. The introductory section sets the stage by elucidating the complexities of modern supply chain management. It introduces the …
Big Data Analytics for Supply Chain Management: A Literature …
analyze the “5 Vs data-related dimensions (i.e., volume, variety, velocity, veracity and ” value) in order to create actionable insights for sustained value delivery, measuring performance and …
BUSINESS ANALYTICS FOR SUPPLY CHAIN: A DYNAMIC
This paper proposes a framework of business analytics for supply chain analytics (SCA) as IT-enabled, analytical dynamic capabilities composed of data management capability, analytical...
Rethinking Supply Chain Analytics with Cognitive Technology
Supply chain (SC) improvements have been a key opportunity for many companies to enhance their bottom line as well as top line. Cognitive technologies can be leveraged to target …
Big Data Analytics in Logistics and Supply Chain Management: …
Realizing the importance of big data business analytics (BDBA), we review and classify the literature on the application of BDBA on logistics and supply chain management (LSCM) –that …
Data Science, Predictive Analytics, and Big Data in Supply …
A topic that is on the minds of many supply chain management (SCM) professionals is how to deal with massive amounts of data, and how to leverage and apply predictive analytics.
Insights from Big Data Analytics in Supply Chain …
When supply chain management (SCM) intersects with Big Data Analytics (BDA), uncountable opportunities for research emerge. Unfortunately, how analytics can
Artificial intelligence and big data analytics for supply chain ...
Artificial Intelligence (AI) and Big Data Analytics (BDA) have the potential to signifi-cantly improve resilience of supply chains and to facilitate more efective management of supply chain resources.
Big Data Analytics in Supply Chain Management: A Systematic …
From the organizational perspective, this study examines the theoretical foundations and research models that explain the sustainability and performances achieved through the use of big data …
A Review on Data Analytics for Supply Chain Management: …
Abstract—The present study bridges the gap between the two intersecting domains, data science and supply chain management. The data can be analyzed for inventory management, forecasting …
The impact of big data and business analytics on supply …
This article therefore endeavours to expose supply chain managers to these changes and to highlight, define and discuss the various concepts and trends around ‘big data’
Reviewing predictive analytics in supply chain management: …
By synthesizing existing research, case studies, and real-world examples, this paper aims to offer valuable insights into the practical implications of integrating predictive analytics into various …
Big data and the supply chain: The big supply chain …
Big supply chain analytics uses data and quantitative methods to improve decision making for all activities across the supply chain. In particular, it does two new things. First, it expands the …
The impact of business analytics on supply chain performance
Supply chain management Analytical capabilities Information systems Business process management Performance SCOR The paper investigates the relationship between analytical …
THE POWER OF PREDICTIVE ANALYTICS IN SUPPLY CHAIN …
In today's fast-paced business environment, supply chain management (SCM) is a critical pillar for success, but is ridden with complexities and uncertainties. The integration of predictive analytics …
Understanding Supply Chain Analytics - Dun & Bradstreet
Supply chain analytics rely on data and algorithms to help government agencies manage risk, save money, and make the entire procurement process more efficient. Supply chain data can be …
PREDICTIVE ANALYTICS AND ITS ROLE IN OPTIMIZING …
By incorporating predictive analytics into supply chain management, businesses can enhance decision-making, reduce waste, improve resource efficiency, and forecast potential disruptions …
Analytics in Supply Change Management: Is There a Dark …
an overview of supply chain management and the critical role of analytics to enhance supply chain processes and, subsequently, performance. While efficiency and effectiven
Big Data Analytics in Supply Chain Management: …
It examined the big data analytics and its processes; supply chain management; big data analytics methods in supply chain management; applications of big data analytics in supply chain …
Supply Chain Analytics The three-minute guide - Deloitte …
If your supply chain management models are based only on past demand, supply, and business cycles, you could be missing big opportunities to put analytics to work.
Predictive Analytics in Supply Chain Management using …
predictive analytics in optimizing supply chain processes. The introductory section sets the stage by elucidating the complexities of modern supply chain management. It introduces the …
Big Data Analytics for Supply Chain Management: A …
analyze the “5 Vs data-related dimensions (i.e., volume, variety, velocity, veracity and ” value) in order to create actionable insights for sustained value delivery, measuring performance and …
BUSINESS ANALYTICS FOR SUPPLY CHAIN: A DYNAMIC
This paper proposes a framework of business analytics for supply chain analytics (SCA) as IT-enabled, analytical dynamic capabilities composed of data management capability, analytical...
Rethinking Supply Chain Analytics with Cognitive Technology
Supply chain (SC) improvements have been a key opportunity for many companies to enhance their bottom line as well as top line. Cognitive technologies can be leveraged to target improvements …
Big Data Analytics in Logistics and Supply Chain …
Realizing the importance of big data business analytics (BDBA), we review and classify the literature on the application of BDBA on logistics and supply chain management (LSCM) –that we define as …
Data Science, Predictive Analytics, and Big Data in Supply …
A topic that is on the minds of many supply chain management (SCM) professionals is how to deal with massive amounts of data, and how to leverage and apply predictive analytics.
Insights from Big Data Analytics in Supply Chain …
When supply chain management (SCM) intersects with Big Data Analytics (BDA), uncountable opportunities for research emerge. Unfortunately, how analytics can
Artificial intelligence and big data analytics for supply chain ...
Artificial Intelligence (AI) and Big Data Analytics (BDA) have the potential to signifi-cantly improve resilience of supply chains and to facilitate more efective management of supply chain resources.
Big Data Analytics in Supply Chain Management: A …
From the organizational perspective, this study examines the theoretical foundations and research models that explain the sustainability and performances achieved through the use of big data …
