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| business analytics in manufacturing industry: Reinventing Manufacturing and Business Processes Through Artificial Intelligence Geeta Rana, Alex Khang, Alok Kumar Goel, Ravindra Sharma, Ashok Kumar Dubey, 2024-10-07 This book describes how newly emerging Artificial Intelligence (AI) technologies will provide unprecedented opportunities to penetrate technology and automation into everything we do, and at the same time, provide a huge playing field for businesses to develop newer models to capture market share. |
| business analytics in manufacturing industry: Business Analytics Using SAS Enterprise Guide and SAS Enterprise Miner Olivia Parr-Rud, 2014-10 This tutorial for data analysts new to SAS Enterprise Guide and SAS Enterprise Miner provides valuable experience using powerful statistical software to complete the kinds of business analytics common to most industries. This beginnner's guide with clear, illustrated, step-by-step instructions will lead you through examples based on business case studies. You will formulate the business objective, manage the data, and perform analyses that you can use to optimize marketing, risk, and customer relationship management, as well as business processes and human resources. Topics include descriptive analysis, predictive modeling and analytics, customer segmentation, market analysis, share-of-wallet analysis, penetration analysis, and business intelligence. -- |
| business analytics in manufacturing industry: Advances in Business, Operations, and Product Analytics Matthew J. Drake, 2015-08-13 If you're seeking to master business analytics, case studies offer invaluable help: they expose you to the entire decision-making process, helping you practice an active role in both performing analysis and using its output to recommend optimal decisions. Now, drawing on his extensive teaching and consulting experience, Prof. Matthew Drake has created the ideal new casebook for all analytics students and practitioners. Drake, author of the widely-praised Applied Business Analytics Casebook, now presents a collection of up-to-date cases that are longer and more detailed than those typically presented in undergraduate texts, but concise and focused enough to be taught in a single classroom session. Organized by analytical technique, Advances in Business, Operations, and Product Analytics covers: Descriptive analytics: descriptive statistics, sampling/inferential statistics, statistical quality control, and probability Predictive analytics: forecasting, demand managing, data and text mining Prescriptive analytics: optimization-based modeling, simulation-based modeling, decision analysis, and multi-criteria decision making Industry-specific analytics: HR and managerial analytics, financial analytics, and healthcare/life sciences In addition to practitioners, this casebook will be especially valuable to students and faculty in undergraduate and masters' courses that cover topics in business analytics, and courses applying analytics to specific industries such as healthcare, or specific business functions such as marketing. |
| business analytics in manufacturing industry: Business Analytics for Professionals Alp Ustundag, Emre Cevikcan, Omer Faruk Beyca, 2022-05-09 This book explains concepts and techniques for business analytics and demonstrate them on real life applications for managers and practitioners. It illustrates how machine learning and optimization techniques can be used to implement intelligent business automation systems. The book examines business problems concerning supply chain, marketing & CRM, financial, manufacturing and human resources functions and supplies solutions in Python. |
| business analytics in manufacturing industry: Big Data Applications in Industry 4.0 P. Kaliraj, T. Devi, 2022-02-10 Industry 4.0 is the latest technological innovation in manufacturing with the goal to increase productivity in a flexible and efficient manner. Changing the way in which manufacturers operate, this revolutionary transformation is powered by various technology advances including Big Data analytics, Internet of Things (IoT), Artificial Intelligence (AI), and cloud computing. Big Data analytics has been identified as one of the significant components of Industry 4.0, as it provides valuable insights for smart factory management. Big Data and Industry 4.0 have the potential to reduce resource consumption and optimize processes, thereby playing a key role in achieving sustainable development. Big Data Applications in Industry 4.0 covers the recent advancements that have emerged in the field of Big Data and its applications. The book introduces the concepts and advanced tools and technologies for representing and processing Big Data. It also covers applications of Big Data in such domains as financial services, education, healthcare, biomedical research, logistics, and warehouse management. Researchers, students, scientists, engineers, and statisticians can turn to this book to learn about concepts, technologies, and applications that solve real-world problems. Features An introduction to data science and the types of data analytics methods accessible today An overview of data integration concepts, methodologies, and solutions A general framework of forecasting principles and applications, as well as basic forecasting models including naïve, moving average, and exponential smoothing models A detailed roadmap of the Big Data evolution and its related technological transformation in computing, along with a brief description of related terminologies The application of Industry 4.0 and Big Data in the field of education The features, prospects, and significant role of Big Data in the banking industry, as well as various use cases of Big Data in banking, finance services, and insurance Implementing a Data Lake (DL) in the cloud and the significance of a data lake in decision making |
| business analytics in manufacturing industry: 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 manufacturing industry: Big Data Analytics in the Insurance Market Kiran Sood, Balamurugan Balusamy, Simon Grima, Pierpaolo Marano, 2022-07-18 Big Data Analytics in the Insurance Market is an industry-specific guide to creating operational effectiveness, managing risk, improving financials, and retaining customers. A must for people seeking to broaden their knowledge of big data concepts and their real-world applications, particularly in the field of insurance. |
| business analytics in manufacturing industry: 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 manufacturing industry: Technical, Economic and Societal Effects of Manufacturing 4.0 Mikael Collan, Karl-Erik Michelsen, 2020-10-01 This open access book is among the first cross-disciplinary works about Manufacturing 4.0. It includes chapters about the technical, the economic, and the social aspects of this important phenomenon. Together the material presented allows the reader to develop a holistic picture of where the manufacturing industry and the parts of the society that depend on it may be going in the future. Manufacturing 4.0 is not only a technical change, nor is it a purely technically driven change, but it is a societal change that has the potential to disrupt the way societies are constructed both in the positive and in the negative. This book will be of interest to scholars researching manufacturing, technological innovation, innovation management and industry 4.0. |
| business analytics in manufacturing industry: 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 manufacturing industry: Business Analytics and Intelligence in Digital Era Dr K. Kumuthadevi , Dr G Vengatesan, Dr Niraj Kumar, 2022-12-30 The International Conference on“Business Analytics and Intelligence in Digital Era” on the 4th and 5th of November 2022. Organized by the Department of B.Com Business Analytics, KPR College of Arts Science and Research (KPRCAS) promoted by the KPR group,is an eminent institution that offers a unique learning experience and equips the young generation with the accurate skill set necessary to meet the unprecedented future challenges in the field of Commerce Specialized with Business Analytics perspectives. ICBA’22 emphases encouraging and promote high-quality research on “AdvancedResearch in Business Analytics and Intelligence in Digital Era across the globeforAcademicians, Researchers,Industrialiststopresenttheirnovelresearchideasandresultsintheirdomain.AnotablenumberofresearchpapershavebeenreceivedinthedisciplinesofMarketing Analytics, HR Analytics, Banking Analytics, and Cybercrime Analytics, Health Care Analytics, Social Media Analytics, Sports Analytics, Web Analytics, Data Visualization, Cluster and Sentimental Analytics and many more relevant fields |
| business analytics in manufacturing industry: Analytics Across the Enterprise Brenda L. Dietrich, Emily C. Plachy, Maureen F. Norton, 2014-05-15 How to Transform Your Organization with Analytics: Insider Lessons from IBM’s Pioneering Experience Analytics is not just a technology: It is a better way to do business. Using analytics, you can systematically inform human judgment with data-driven insight. This doesn’t just improve decision-making: It also enables greater innovation and creativity in support of strategy. Your transformation won’t happen overnight; however, it is absolutely achievable, and the rewards are immense. This book demystifies your analytics journey by showing you how IBM has successfully leveraged analytics across the enterprise, worldwide. Three of IBM’s pioneering analytics practitioners share invaluable real-world perspectives on what does and doesn’t work and how you can start or accelerate your own transformation. This book provides an essential framework for becoming a smarter enterprise and shows through 31 case studies how IBM has derived value from analytics throughout its business. Coverage Includes Creating a smarter workforce through big data and analytics More effectively optimizing supply chain processes Systematically improving financial forecasting Managing financial risk, increasing operational efficiency, and creating business value Reaching more B2B or B2C customers and deepening their engagement Optimizing manufacturing and product management processes Deploying your sales organization to increase revenue and effectiveness Achieving new levels of excellence in services delivery and reducing risk Transforming IT to enable wider use of analytics “Measuring the immeasurable” and filling gaps in imperfect data Whatever your industry or role, whether a current or future leader, analytics can make you smarter and more competitive. Analytics Across the Enterprise shows how IBM did it--and how you can, too. Learn more about IBM Analytics |
| business analytics in manufacturing industry: The Fourth Industrial Revolution: Implementation of Artificial Intelligence for Growing Business Success Allam Hamdan, Aboul Ella Hassanien, Anjum Razzaque, Bahaaeddin Alareeni, 2021-04-11 This book focuses on the implementation of AI for growing business, and the book includes research articles and expository papers on the applications of AI on decision-making, health care, smart universities, public sector and digital government, FinTech, and RegTech. Artificial Intelligence (AI) is a vital and a fundamental driver for the Fourth Industrial Revolution (FIR). Its influence is observed at homes, in the businesses and in the public spaces. The embodied best of AI reflects robots which drive our cars, stock our warehouses, monitor our behaviors and warn us of our health, and care for our young children. Some researchers also discussed the role of AI in the current COVID-19 pandemic, whether in the health sector, education, and others. On all of these, the researchers discussed the impact of AI on decision-making in those vital sectors of the economy. |
| business analytics in manufacturing industry: Handbook of Research on Integrating Industry 4.0 in Business and Manufacturing Karabegovi?, Isak, Kova?evi?, Ahmed, Banjanovi?-Mehmedovi?, Lejla, Daši?, Predrag, 2020-03-27 In Industry 4.0, industrial productions are adjusted to complete smart automation, which means introducing self-automation methods, self-configuration, self-diagnosis of problems and removal, cognition, and intelligent decision making. This implementation of Industry 4.0 brings about a change in business paradigms and production models, and this will be reflected at all levels of the production process including supply chains and will involve all workers in the production process from managers to cyber-physical systems designers and customers as end-users. The Handbook of Research on Integrating Industry 4.0 in Business and Manufacturing is an essential reference source that explores the development and integration of Industry 4.0 by examining changes and innovations to manufacturing processes as well as its applications in different industrial areas. Featuring coverage on a wide range of topics such as cyber physical systems, integration criteria, and artificial intelligence, this book is ideally designed for mechanical engineers, electrical engineers, manufacturers, supply chain managers, logistics specialists, investors, managers, policymakers, production scientists, researchers, academicians, and students at the postgraduate level. |
| business analytics in manufacturing industry: Business Intelligence and Performance Management Peter Rausch, Alaa F. Sheta, Aladdin Ayesh, 2013-02-15 During the 21st century business environments have become more complex and dynamic than ever before. Companies operate in a world of change influenced by globalisation, volatile markets, legal changes and technical progress. As a result, they have to handle growing volumes of data and therefore require fast storage, reliable data access, intelligent retrieval of information and automated decision-making mechanisms, all provided at the highest level of service quality. Successful enterprises are aware of these challenges and efficiently respond to the dynamic environment in which their business operates. Business Intelligence (BI) and Performance Management (PM) offer solutions to these challenges and provide techniques to enable effective business change. The important aspects of both topics are discussed within this state-of-the-art volume. It covers the strategic support, business applications, methodologies and technologies from the field, and explores the benefits, issues and challenges of each. Issues are analysed from many different perspectives, ranging from strategic management to data technologies, and the different subjects are complimented and illustrated by numerous examples of industrial applications. Contributions are authored by leading academics and practitioners representing various universities, research centres and companies worldwide. Their experience covers multiple disciplines and industries, including finance, construction, logistics, and public services, amongst others. Business Intelligence and Performance Management is a valuable source of reference for graduates approaching MSc or PhD programs and for professionals in industry researching in the fields of BI and PM for industrial application. |
| business analytics in manufacturing industry: Industrial Engineering in the Age of Business Intelligence Fethi Calisir, 2022-08-24 This book gathers extended versions of the best papers presented at the Global Joint Conference on Industrial Engineering and Its Application Areas (GJCIE), held virtually on October 30–31, 2021, from Istanbul Technical University. Continuing the tradition of previous volumes, it highlights recent developments of industrial engineering at the purpose of using and managing digital and intelligent technologies for application to a wide range of field, including manufacturing, healthcare, e-commerce and mobility. |
| business analytics in manufacturing industry: Handbook of Research on Foundations and Applications of Intelligent Business Analytics Sun, Zhaohao, Wu, Zhiyou, 2022-03-11 Intelligent business analytics is an emerging technology that has become a mainstream market adopted broadly across industries, organizations, and geographic regions. Intelligent business analytics is a current focus for research and development across academia and industries and must be examined and considered thoroughly so businesses can apply the technology appropriately. The Handbook of Research on Foundations and Applications of Intelligent Business Analytics examines the technologies and applications of intelligent business analytics and discusses the foundations of intelligent analytics such as intelligent mining, intelligent statistical modeling, and machine learning. Covering topics such as augmented analytics and artificial intelligence systems, this major reference work is ideal for scholars, engineers, professors, practitioners, researchers, industry professionals, academicians, and students. |
| business analytics in manufacturing industry: Intelligent Analytics for Industry 4.0 Applications Avinash Chandra Pandey, Abhishek Verma, Vijaypal Singh Rathor, Munesh Singh, Ashutosh Kumar Singh, 2023-06-06 The advancements in intelligent decision-making techniques have elevated the efficiency of manufacturing industries and led to the start of the Industry 4.0 era. Industry 4.0 is revolutionizing the way companies manufacture, improve, and distribute their products. Manufacturers are integrating new technologies, including the Internet of Things (IoT), cloud computing and analytics, and artificial intelligence and machine learning, into their production facilities throughout their operations. In the past few years, intelligent analytics has emerged as a solution that examines both historical and real-time data to uncover performance insights. Because the amount of data that needs analysis is growing daily, advanced technologies are necessary to collect, arrange, and analyze incoming data. This approach enables businesses to detect valuable connections and trends and make decisions that boost overall performance. In Industry 4.0, intelligent analytics has a broader scope in terms of descriptive, predictive, and prescriptive subdomains. To this end, the book will aim to review and highlight the challenges faced by intelligent analytics in Industry 4.0 and present the recent developments done to address those challenges. |
| business analytics in manufacturing industry: Integrated Science in Digital Age 2020 Tatiana Antipova, 2020-05-26 This book presents the proceedings of the 2020 International Conference on Integrated Science in Digital Age, which was jointly supported by the Institute of Certified Specialists (Russia) and Springer, and was held on May 1–3, 2020. The conference provided an international forum for researchers and practitioners to present and discuss the latest innovations, trends, results, experiences and concerns in the various areas of integrated science in the digital age. The main goal of the conference was to efficiently disseminate original findings in the natural and social sciences, covering topics such as blockchain & cryptocurrency; computer law & security; digital accounting & auditing; digital business & finance; digital economics; digital education; digital engineering; machine learning; smart cities in the digital age; health policy & management; and information management. |
| business analytics in manufacturing industry: Strengthening Industrial Cybersecurity to Protect Business Intelligence Saeed, Saqib, Azizi, Neda, Tahir, Shahzaib, Ahmad, Munir, Almuhaideb, Abdullah M., 2024-02-14 In the digital transformation era, integrating business intelligence and data analytics has become critical for the growth and sustainability of industrial organizations. However, with this technological evolution comes the pressing need for robust cybersecurity measures to safeguard valuable business intelligence from security threats. Strengthening Industrial Cybersecurity to Protect Business Intelligence delves into the theoretical foundations and empirical studies surrounding the intersection of business intelligence and cybersecurity within various industrial domains. This book addresses the importance of cybersecurity controls in mitigating financial losses and reputational damage caused by cyber-attacks. The content spans a spectrum of topics, including advances in business intelligence, the role of artificial intelligence in various business applications, and the integration of intelligent systems across industry 5.0. Ideal for academics in information systems, cybersecurity, and organizational science, as well as government officials and organizations, this book serves as a vital resource for understanding the intricate relationship between business intelligence and cybersecurity. It is equally beneficial for students seeking insights into the security implications of digital transformation processes for achieving business continuity. |
| business analytics in manufacturing industry: Systems Engineering in the Fourth Industrial Revolution Ron S. Kenett, Robert S. Swarz, Avigdor Zonnenshain, 2019-12-24 An up-to-date guide for using massive amounts of data and novel technologies to design, build, and maintain better systems engineering Systems Engineering in the Fourth Industrial Revolution: Big Data, Novel Technologies, and Modern Systems Engineering offers a guide to the recent changes in systems engineering prompted by the current challenging and innovative industrial environment called the Fourth Industrial Revolution—INDUSTRY 4.0. This book contains advanced models, innovative practices, and state-of-the-art research findings on systems engineering. The contributors, an international panel of experts on the topic, explore the key elements in systems engineering that have shifted towards data collection and analytics, available and used in the design and development of systems and also in the later life-cycle stages of use and retirement. The contributors address the issues in a system in which the system involves data in its operation, contrasting with earlier approaches in which data, models, and algorithms were less involved in the function of the system. The book covers a wide range of topics including five systems engineering domains: systems engineering and systems thinking; systems software and process engineering; the digital factory; reliability and maintainability modeling and analytics; and organizational aspects of systems engineering. This important resource: Presents new and advanced approaches, methodologies, and tools for designing, testing, deploying, and maintaining advanced complex systems Explores effective evidence-based risk management practices Describes an integrated approach to safety, reliability, and cyber security based on system theory Discusses entrepreneurship as a multidisciplinary system Emphasizes technical merits of systems engineering concepts by providing technical models Written for systems engineers, Systems Engineering in the Fourth Industrial Revolution offers an up-to-date resource that contains the best practices and most recent research on the topic of systems engineering. |
| business analytics in manufacturing industry: Business Analytics: Turning Data into Decisions Cybellium, Welcome to the forefront of knowledge with Cybellium, your trusted partner in mastering the cutting-edge fields of IT, Artificial Intelligence, Cyber Security, Business, Economics and Science. Designed for professionals, students, and enthusiasts alike, our comprehensive books empower you to stay ahead in a rapidly evolving digital world. * Expert Insights: Our books provide deep, actionable insights that bridge the gap between theory and practical application. * Up-to-Date Content: Stay current with the latest advancements, trends, and best practices in IT, Al, Cybersecurity, Business, Economics and Science. Each guide is regularly updated to reflect the newest developments and challenges. * Comprehensive Coverage: Whether you're a beginner or an advanced learner, Cybellium books cover a wide range of topics, from foundational principles to specialized knowledge, tailored to your level of expertise. Become part of a global network of learners and professionals who trust Cybellium to guide their educational journey. www.cybellium.com |
| business analytics in manufacturing industry: 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 manufacturing industry: Data Driven Smart Manufacturing Technologies and Applications Weidong Li, Yuchen Liang, Sheng Wang, 2021-02-20 This book reports innovative deep learning and big data analytics technologies for smart manufacturing applications. In this book, theoretical foundations, as well as the state-of-the-art and practical implementations for the relevant technologies, are covered. This book details the relevant applied research conducted by the authors in some important manufacturing applications, including intelligent prognosis on manufacturing processes, sustainable manufacturing and human-robot cooperation. Industrial case studies included in this book illustrate the design details of the algorithms and methodologies for the applications, in a bid to provide useful references to readers. Smart manufacturing aims to take advantage of advanced information and artificial intelligent technologies to enable flexibility in physical manufacturing processes to address increasingly dynamic markets. In recent years, the development of innovative deep learning and big data analytics algorithms is dramatic. Meanwhile, the algorithms and technologies have been widely applied to facilitate various manufacturing applications. It is essential to make a timely update on this subject considering its importance and rapid progress. This book offers a valuable resource for researchers in the smart manufacturing communities, as well as practicing engineers and decision makers in industry and all those interested in smart manufacturing and Industry 4.0. |
| business analytics in manufacturing industry: Next Generation Demand Management Charles W. Chase, 2016-08-01 A practical framework for revenue-boosting supply chain management Next Generation Demand Management is a guidebook to next generation Demand Management, with an implementation framework that improves revenue forecasts and enhances profitability. This proven approach is structured around the four key catalysts of an efficient planning strategy: people, processes, analytics, and technology. The discussion covers the changes in behavior, skills, and integrated processes that are required for proper implementation, as well as the descriptive and predictive analytics tools and skills that make the process sustainable. Corporate culture changes require a shift in leadership focus, and this guide describes the necessary champion with the authority to drive adoption and stress accountability while focusing on customer excellence. Real world examples with actual data illustrate important concepts alongside case studies highlighting best-in-class as well as startup approaches. Reliable forecasts are the primary product of demand planning, a multi-step operational supply chain management process that is increasingly seen as a survival tactic in the changing marketplace. This book provides a practical framework for efficient implementation, and complete guidance toward the supplementary changes required to reap the full benefit. Learn the key principles of demand driven planning Implement new behaviors, skills, and processes Adopt scalable technology and analytics capabilities Align inventory with demand, and increase channel profitability Whether your company is a large multinational or an early startup, your revenue predictions are only as strong as your supply chain management system. Implementing a proven, more structured process can be the catalyst your company needs to overcome that one lingering obstacle between forecast and goal. Next Generation Demand Management gives you the framework for building the foundation of your growth. |
| business analytics in manufacturing industry: Predictive Maintenance in Smart Factories Tania Cerquitelli, Nikolaos Nikolakis, Niamh O’Mahony, Enrico Macii, Massimo Ippolito, Sotirios Makris, 2021-08-26 This book presents the outcome of the European project SERENA, involving fourteen partners as international academics, technological companies, and industrial factories, addressing the design and development of a plug-n-play end-to-end cloud architecture, and enabling predictive maintenance of industrial equipment to be easily exploitable by small and medium manufacturing companies with a very limited data analytics experience. Perspectives and new opportunities to address open issues on predictive maintenance conclude the book with some interesting suggestions of future research directions to continue the growth of the manufacturing intelligence. |
| business analytics in manufacturing industry: Reinventing the Product Eric Schaeffer, David Sovie, 2019-03-03 Create the personalized and compelling experiences that today's customers expect by harnessing AI and digital technologies to create smart connected products, with this cutting-edge guide from senior leaders at Accenture. Digital technology is both friend and foe: highly disruptive, yet it cannot be ignored. As traditional products transform into smart connected products faster than ever before, companies that fail to make use of it now put themselves in the firing line for disintermediation or even eradication. However, digital technology is also the biggest opportunity for product-making businesses to create the next generation of goods in the marketplace. In Reinventing the Product, Eric Schaeffer and David Sovie, both Senior Managing Directors at Accenture, show how this reinvention is made possible, to deliver truly intelligent, and often even autonomous, products. Reinventing the Product makes the case for companies to rethink their product strategy, innovation and engineering processes, including: - How to harness the opportunities of AI and digital technologies, such as IoT sensors, blockchain, advanced analytics, cloud and edge computing - Practical advice on transforming their entire culture to build the future of successful 'living products' - Features case studies from global organizations such as Faurecia, Signify, Symmons and Haier and interviews with thought leaders from top companies including Amazon, ABB, Tesla, Samsung and Google This book provides the only advice any product-making company needs as it embarks on, or accelerates, its digitization journey. |
| business analytics in manufacturing industry: 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 manufacturing industry: Data Analytics and Artificial Intelligence for Predictive Maintenance in Smart Manufacturing Amit Kumar Tyagi, Shrikant Tiwari, Gulshan Soni, 2024-10-23 Today, in this smart era, data analytics and artificial intelligence (AI) play an important role in predictive maintenance (PdM) within the manufacturing industry. This innovative approach aims to optimize maintenance strategies by predicting when equipment or machinery is likely to fail so that maintenance can be performed just in time to prevent costly breakdowns. This book contains up-to-date information on predictive maintenance and the latest advancements, trends, and tools required to reduce costs and save time for manufacturers and industries. Data Analytics and Artificial Intelligence for Predictive Maintenance in Smart Manufacturing provides an extensive and in-depth exploration of the intersection of data analytics, artificial intelligence, and predictive maintenance in the manufacturing industry and covers fundamental concepts, advanced techniques, case studies, and practical applications. Using a multidisciplinary approach, this book recognizes that predictive maintenance in manufacturing requires collaboration among engineers, data scientists, and business professionals and includes case studies from various manufacturing sectors showcasing successful applications of predictive maintenance. The real-world examples explain the useful benefits and ROI achieved by organizations. The emphasis is on scalability, making it suitable for both small and large manufacturing operations, and readers will learn how to adapt predictive maintenance strategies to different scales and industries. This book presents resources and references to keep readers updated on the latest advancements, tools, and trends, ensuring continuous learning. Serving as a reference guide, this book focuses on the latest advancements, trends, and tools relevant to predictive maintenance and can also serve as an educational resource for students studying manufacturing, data science, or related fields. |
| business analytics in manufacturing industry: Business Analytics: Step-by-Step Tutorial Narcyz Roztocki, 2016-11-05 Business Analytics refers to utilizing existing data to make business decisions. Often, however, the decision-makers lack the knowledge and skill to process the existing documents and retrieve information that is useful for their decision-making. The objective of this tutorial is to improve basic skills on how to process existing data by providing a collection of simplified, but realistic, hands-on-examples. In essence, this tutorial is a collection of business mini cases. It starts with relatively simple cases and then progresses step-by-step by adding complexity to each of the following business cases. Its intent is to encourage effective and efficient use of application software to help the decisions-makers. There are three major changes to the second edition. First, several additional mini case studies are added. Second, the case studies are rearranged to allow a more systematic progress. Third, in addition to a solution key, detailed solutions to 35 exercises by using MS Excel are added. |
| business analytics in manufacturing industry: Practical Business Analytics Using SAS Shailendra Kadre, Venkat Reddy Konasani, 2015-02-07 Practical Business Analytics Using SAS: A Hands-on Guide shows SAS users and businesspeople how to analyze data effectively in real-life business scenarios. The book begins with an introduction to analytics, analytical tools, and SAS programming. The authors—both SAS, statistics, analytics, and big data experts—first show how SAS is used in business, and then how to get started programming in SAS by importing data and learning how to manipulate it. Besides illustrating SAS basic functions, you will see how each function can be used to get the information you need to improve business performance. Each chapter offers hands-on exercises drawn from real business situations. The book then provides an overview of statistics, as well as instruction on exploring data, preparing it for analysis, and testing hypotheses. You will learn how to use SAS to perform analytics and model using both basic and advanced techniques like multiple regression, logistic regression, and time series analysis, among other topics. The book concludes with a chapter on analyzing big data. Illustrations from banking and other industries make the principles and methods come to life. Readers will find just enough theory to understand the practical examples and case studies, which cover all industries. Written for a corporate IT and programming audience that wants to upgrade skills or enter the analytics field, this book includes: More than 200 examples and exercises, including code and datasets for practice. Relevant examples for all industries. Case studies that show how to use SAS analytics to identify opportunities, solve complicated problems, and chart a course. Practical Business Analytics Using SAS: A Hands-on Guide gives you the tools you need to gain insight into the data at your fingertips, predict business conditions for better planning, and make excellent decisions. Whether you are in retail, finance, healthcare, manufacturing, government, or any other industry, this book will help your organization increase revenue, drive down costs, improve marketing, and satisfy customers better than ever before. |
| business analytics in manufacturing industry: Business Analytics: Data-Driven Decision Making , Welcome to the forefront of knowledge with Cybellium, your trusted partner in mastering the cutting-edge fields of IT, Artificial Intelligence, Cyber Security, Business, Economics and Science. Designed for professionals, students, and enthusiasts alike, our comprehensive books empower you to stay ahead in a rapidly evolving digital world. * Expert Insights: Our books provide deep, actionable insights that bridge the gap between theory and practical application. * Up-to-Date Content: Stay current with the latest advancements, trends, and best practices in IT, Al, Cybersecurity, Business, Economics and Science. Each guide is regularly updated to reflect the newest developments and challenges. * Comprehensive Coverage: Whether you're a beginner or an advanced learner, Cybellium books cover a wide range of topics, from foundational principles to specialized knowledge, tailored to your level of expertise. Become part of a global network of learners and professionals who trust Cybellium to guide their educational journey. www.cybellium.com |
| business analytics in manufacturing industry: Business Intelligence Strategy and Big Data Analytics Steve Williams, 2016-04-08 Business Intelligence Strategy and Big Data Analytics is written for business leaders, managers, and analysts - people who are involved with advancing the use of BI at their companies or who need to better understand what BI is and how it can be used to improve profitability. It is written from a general management perspective, and it draws on observations at 12 companies whose annual revenues range between $500 million and $20 billion. Over the past 15 years, my company has formulated vendor-neutral business-focused BI strategies and program execution plans in collaboration with manufacturers, distributors, retailers, logistics companies, insurers, investment companies, credit unions, and utilities, among others. It is through these experiences that we have validated business-driven BI strategy formulation methods and identified common enterprise BI program execution challenges. In recent years, terms like big data and big data analytics have been introduced into the business and technical lexicon. Upon close examination, the newer terminology is about the same thing that BI has always been about: analyzing the vast amounts of data that companies generate and/or purchase in the course of business as a means of improving profitability and competitiveness. Accordingly, we will use the terms BI and business intelligence throughout the book, and we will discuss the newer concepts like big data as appropriate. More broadly, the goal of this book is to share methods and observations that will help companies achieve BI success and thereby increase revenues, reduce costs, or both. - Provides ideas for improving the business performance of one's company or business functions - Emphasizes proven, practical, step-by-step methods that readers can readily apply in their companies - Includes exercises and case studies with road-tested advice about formulating BI strategies and program plans |
| business analytics in manufacturing industry: BASIC BUSINESS ANALYTICS USING R Dr. Mahavir M. Shetiya, Prof. Snehal V. Bhambure, 2023-11-10 Buy BASIC BUSINESS ANALYTICS USING R e-Book for Mba 2nd Semester in English language specially designed for SPPU ( Savitribai Phule Pune University ,Maharashtra) By Thakur publication. |
| business analytics in manufacturing industry: Data-Driven Business Intelligence Systems for Socio-Technical Organizations Keikhosrokiani, Pantea, 2024-04-09 The convergence of modern technology and social dynamics have shaped the very fabric of today’s organizations, making the role of Business Intelligence (BI) profoundly significant. Data-Driven Business Intelligence Systems for Socio-Technical Organizations delves into the heart of this transformative realm, offering an academic exploration of the tools, strategies, and methodologies that propel enterprises toward data-driven decision-making excellence. Socio-technical organizations, with their intricate interplay between human and technological components, require a unique approach to BI. This book embarks on a comprehensive journey, revealing how BI tools empower these entities to decipher the complexities of their data landscape. From user behavior to social interactions, technological systems to environmental factors, this work sheds light on the multifaceted sources of information that inform organizational strategies. Decision-makers within socio-technical organizations leverage BI insights to discern patterns, spot trends, and uncover correlations that influence operations and the intricate social dynamics within their entities. Research covering real-time monitoring and predictive analytics equips these organizations to respond swiftly to demands and anticipate future trends, harnessing the full potential of data. The book delves into their design, development, and architectural nuances, illuminating these concepts through case studies. This book is ideal for business executives, entrepreneurs, data analysts, marketers, government officials, educators, and researchers. |
| business analytics in manufacturing industry: Industry 4.0 Technologies for Business Excellence Shivani Bali, Sugandha Aggarwal, Sunil Sharma, 2021-12-30 This book captures deploying Industry 4.0 technologies for business excellence and moving towards Society 5.0. It addresses applications of Industry 4.0 in the areas of marketing, operations, supply chain, finance, and HR to achieve business excellence. Industry 4.0 Technologies for Business Excellence: Frameworks, Practices, and Applications focuses on the use of AI in management across different sectors. It explores the benefits through a human-centered approach to resolving social problems by integrating cyberspace and physical space. It discusses the framework for moving towards Society 5.0 and keeping a balance between economic and social gains. This book brings together researchers, developers, practitioners, and users interested in exploring new ideas, techniques, and tools and exchanging their experiences to provide the most recent information on Industry 4.0 applications in the field of business excellence. Graduate or postgraduate students, professionals, and researchers in the fields of operations management, manufacturing, healthcare, supply chain, marketing, finance, and HR will find this book full of new ideas, techniques, and tools related to Industry 4.0. |
| business analytics in manufacturing industry: Digital Disruptive Innovation Joe Tidd, 2019-08-21 'Its focus is the major theme of digital innovation and it tries to go beyond the hype associated with much of the discussion of this important area … The discussion in the book stresses the need to move our thinking about innovation beyond the level of enterprise to consider ecosystems and complementary assets … Overall this is a useful book, not least because in addition to opening up key lines for further research enquiry the book also has a strong international flavour with contributions from a wide and diverse set of contexts.'International Journal of Innovation ManagementThere is no doubt that digital technologies have the potential for disruptive innovation in a wide range of sectors, both in manufacturing and services, and the commercial and social domains. However, popular commentaries on the potential of digital innovation to disrupt have suffered from two extreme positions: either, simplistic technological determinism, often promoted by technology vendors, claiming that the impending widespread automation of products and services will provide step-changes in productivity and new products and services; or alternatively, very high-level broad discussions of business model innovation in traditional sectors, private and public. However, the impacts will not be universal, and the outcomes will be highly-differentiated. More fundamentally, neither a narrow technological perspective or broad business view adequately captures the appropriate level of granularity necessary to understand the potential and challenges presented by digital innovation. In this book, Digital Disruptive Innovation, we apply innovation concepts, models and research to provide greater insights into strategies for, and management of, digital innovation. |
| business analytics in manufacturing industry: Guide to Industrial Analytics Richard Hill, Stuart Berry, 2021-09-27 This textbook describes the hands-on application of data science techniques to solve problems in manufacturing and the Industrial Internet of Things (IIoT). Monitoring and managing operational performance is a crucial activity for industrial and business organisations. The emergence of low-cost, accessible computing and storage, through Industrial Digital Technologies (IDT) and Industry 4.0, has generated considerable interest in innovative approaches to doing more with data. Data science, predictive analytics, machine learning, artificial intelligence and general approaches to modelling, simulating and visualising industrial systems have often been considered topics only for research labs and academic departments. This textbook debunks the mystique around applied data science and shows readers, using tutorial-style explanations and real-life case studies, how practitioners can develop their own understanding of performance to achieve tangible business improvements. All exercises can be completed with commonly available tools, many of which are free to install and use. Readers will learn how to use tools to investigate, diagnose, propose and implement analytics solutions that will provide explainable results to deliver digital transformation. |
| business analytics in manufacturing industry: 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 manufacturing industry: Technology Innovation for Business Intelligence and Analytics (TIBIA) Haitham M. Alzoubi, |
BUSINESS | English meaning - Cambridge Dictionary
BUSINESS definition: 1. the activity of buying and selling goods and services: 2. a particular company that buys and….
VENTURE | English meaning - Cambridge Dictionary
VENTURE definition: 1. a new activity, usually in business, that involves risk or uncertainty: 2. to risk going….
ENTERPRISE | English meaning - Cambridge Dictionary
ENTERPRISE definition: 1. an organization, especially a business, or a difficult and important plan, especially one that….
INCUMBENT | English meaning - Cambridge Dictionary
INCUMBENT definition: 1. officially having the named position: 2. to be necessary for someone: 3. the person who has or….
AD HOC | English meaning - Cambridge Dictionary
AD HOC definition: 1. made or happening only for a particular purpose or need, not planned before it happens: 2. made….
LEVERAGE | English meaning - Cambridge Dictionary
LEVERAGE definition: 1. the action or advantage of using a lever: 2. power to influence people and get the results you….
ENTREPRENEUR | English meaning - Cambridge Dictionary
ENTREPRENEUR definition: 1. someone who starts their own business, especially when this involves seeing a new opportunity….
CULTIVATE | English meaning - Cambridge Dictionary
CULTIVATE definition: 1. to prepare land and grow crops on it, or to grow a particular crop: 2. to try to develop and….
EQUITY | English meaning - Cambridge Dictionary
EQUITY definition: 1. the value of a company, divided into many equal parts owned by the shareholders, or one of the….
LIAISE | English meaning - Cambridge Dictionary
LIAISE definition: 1. to speak to people in other organizations, etc. in order to work with them or exchange….
BUSINESS | English meaning - Cambridge Dictionary
BUSINESS definition: 1. the activity of buying and selling goods and services: 2. a particular company that buys and….
VENTURE | English meaning - Cambridge Dictionary
VENTURE definition: 1. a new activity, usually in business, that involves risk or uncertainty: 2. to risk going….
ENTERPRISE | English meaning - Cambridge Dictionary
ENTERPRISE definition: 1. an organization, especially a business, or a difficult and important plan, especially one that….
INCUMBENT | English meaning - Cambridge Dictionary
INCUMBENT definition: 1. officially having the named position: 2. to be necessary for someone: 3. the person who has or….
AD HOC | English meaning - Cambridge Dictionary
AD HOC definition: 1. made or happening only for a particular purpose or need, not planned before it happens: 2. made….
LEVERAGE | English meaning - Cambridge Dictionary
LEVERAGE definition: 1. the action or advantage of using a lever: 2. power to influence people and get the results you….
ENTREPRENEUR | English meaning - Cambridge Dictionary
ENTREPRENEUR definition: 1. someone who starts their own business, especially when this involves seeing a new opportunity….
CULTIVATE | English meaning - Cambridge Dictionary
CULTIVATE definition: 1. to prepare land and grow crops on it, or to grow a particular crop: 2. to try to develop and….
EQUITY | English meaning - Cambridge Dictionary
EQUITY definition: 1. the value of a company, divided into many equal parts owned by the shareholders, or one of the….
LIAISE | English meaning - Cambridge Dictionary
LIAISE definition: 1. to speak to people in other organizations, etc. in order to work with them or exchange….
