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| forecasting in operations management: Forecasting Systems for Operations Management Stephen A. DeLurgio, Carl Bhame, 1991 |
| forecasting in operations management: Principles of Forecasting J.S. Armstrong, 2001 This handbook summarises knowledge from experts and empirical studies. It provides guidelines that can be applied in fields such as economics, sociology, and psychology. Includes a comprehensive forecasting dictionary. |
| forecasting in operations management: Forecasting Fundamentals Nada Sanders, 2016-11-14 This book is for everyone who wants to make better forecasts. It is not about mathematics and statistics. It is about following a well-established forecasting process to create and implement good forecasts. This is true whether you are forecasting global markets, sales of SKUs, competitive strategy, or market disruptions. Today, most forecasts are generated using software. However, no amount of technology and statistics can compensate for a poor forecasting process. Forecasting is not just about generating a number. Forecasters need to understand the problems they are trying to solve. They also need to follow a process that is justifiable to other parties and be implemented in practice. This is what the book is about. Accurate forecasts are essential for predicting demand, identifying new market opportunities, forecasting risks, disruptions, innovation, competition, market growth and trends. Companies can navigate this daunting landscape and improve their forecasts by following some well-established principles. This book is written to provide the fundamentals business leaders need in order to make good forecasts. These fundamentals hold true regardless of what is being forecast and what technology is being used. It provides the basic foundational principles all companies need to achieve competitive forecast accuracy. |
| forecasting in operations management: Demand Forecasting for Managers Stephan Kolassa, Enno Siemsen, 2016-08-17 Most decisions and plans in a firm require a forecast. Not matching supply with demand can make or break any business, and that's why forecasting is so invaluable. Forecasting can appear as a frightening topic with many arcane equations to master. For this reason, the authors start out from the very basics and provide a non-technical overview of common forecasting techniques as well as organizational aspects of creating a robust forecasting process. The book also discusses how to measure forecast accuracy to hold people accountable and guide continuous improvement. This book does not require prior knowledge of higher mathematics, statistics, or operations research. It is designed to serve as a first introduction to the non-expert, such as a manager overseeing a forecasting group, or an MBA student who needs to be familiar with the broad outlines of forecasting without specializing in it. |
| forecasting in operations management: Neural Networks in Business Forecasting G. Peter Zhang, 2004-01-01 Forecasting is one of the most important activities that form the basis for strategic, tactical, and operational decisions in all business organizations. Recently, neural networks have emerged as an important tool for business forecasting. Neural Networks in Business Forecasting provides researchers and practitioners with some recent advances in applying neural networks to business forecasting. A number of case studies demonstrating the innovative or successful applications of neural networks to many areas of business as well as methods to improve neural network forecasting performance are presented. |
| forecasting in operations management: Operations Management Jay Heizer, Barry Render, 2014 This package includes a physical copy of 'Operations Management' as well as access to the eText and MyOMLab. The edition has been edited to include enhancements making it more relevant to students outside the United States. The book presents a broad introduction to the field of operations in a realistic and practical manner, while offering the largest and most diverse collection of problems on the market. |
| forecasting in operations management: Operations Management Robert Dan Reid, Nada R. Sanders, 2010 With its abundance of step-by-step solved problems, concepts, and examples of major real-world companies, this text brings unparalleled clarity and transparency to the course. |
| forecasting in operations management: Sales Forecasting Management John T. Mentzer, Mark A. Moon, 2004-11-23 Incorporating 25 years of sales forecasting management research with more than 400 companies, Sales Forecasting Management, Second Edition is the first text to truly integrate the theory and practice of sales forecasting management. This research includes the personal experiences of John T. Mentzer and Mark A. Moon in advising companies how to improve their sales forecasting management practices. Their program of research includes two major surveys of companies′ sales forecasting practices, a two-year, in-depth study of sales forecasting management practices of 20 major companies, and an ongoing study of how to apply the findings from the two-year study to conducting sales forecasting audits of additional companies. The book provides comprehensive coverage of the techniques and applications of sales forecasting analysis, combined with a managerial focus to give managers and users of the sales forecasting function a clear understanding of the forecasting needs of all business functions. New to This Edition: The author′s well-regarded Multicaster software system demo, previously available on cassette, has been updated and is now available for download from the authors′ Web site New insights on the critical area of qualitative forecasting are presented The results of additional surveys done since the publication of the first edition have been added The discussion of the four dimensions of forecasting management has been significantly enhanced Significant reorganization and updating has been done to strengthen and improve the material for the second edition. Sales Forecasting Management is an ideal text for graduate courses in sales forecasting management. Practitioners in marketing, sales, finance/accounting, production/purchasing, and logistics will also find this easy-to-understand volume essential. |
| forecasting in operations management: Forecasting Methods for Management Steven C. Wheelwright, Spyros G. Makridakis, 1977 Outlines the full range of qualitative and quantitative forecasting methods. Discusses forecasting challenges, including learning the difference between explaining the past and predicting the future, and the impact of judgmental biases; and forecasting applications for short, medium, and long-term horizons. Annotation copyrighted by Book News, Inc., Portland, OR |
| forecasting in operations management: Business Forecasting Michael Gilliland, Len Tashman, Udo Sglavo, 2021-05-11 Discover the role of machine learning and artificial intelligence in business forecasting from some of the brightest minds in the field In Business Forecasting: The Emerging Role of Artificial Intelligence and Machine Learning accomplished authors Michael Gilliland, Len Tashman, and Udo Sglavo deliver relevant and timely insights from some of the most important and influential authors in the field of forecasting. You'll learn about the role played by machine learning and AI in the forecasting process and discover brand-new research, case studies, and thoughtful discussions covering an array of practical topics. The book offers multiple perspectives on issues like monitoring forecast performance, forecasting process, communication and accountability for forecasts, and the use of big data in forecasting. You will find: Discussions on deep learning in forecasting, including current trends and challenges Explorations of neural network-based forecasting strategies A treatment of the future of artificial intelligence in business forecasting Analyses of forecasting methods, including modeling, selection, and monitoring In addition to the Foreword by renowned researchers Spyros Makridakis and Fotios Petropoulos, the book also includes 16 opinion/editorial Afterwords by a diverse range of top academics, consultants, vendors, and industry practitioners, each providing their own unique vision of the issues, current state, and future direction of business forecasting. Perfect for financial controllers, chief financial officers, business analysts, forecast analysts, and demand planners, Business Forecasting will also earn a place in the libraries of other executives and managers who seek a one-stop resource to help them critically assess and improve their own organization's forecasting efforts. |
| forecasting in operations management: Advances in Business and Management Forecasting Kenneth D. Lawrence, Michael D. Geurts, 2006-02-17 Aims to present state-of-the-art studies in the application of forecasting methodologies to such areas as sales, marketing, and strategic decision making. The topics in this title include: sales and marketing, forecasting, new product forecasting, judgmentally based forecasting, the application of surveys to forecasting, and more. |
| forecasting in operations management: Fundamentals of Demand Planning and Forecasting Chaman L. Jain, Jack Malehorn, 2012 |
| forecasting in operations management: Manager's Guide to Forecasting David M. Georgoff, Robert G. Murdick, 1986-01-01 |
| forecasting in operations management: Intermittent Demand Forecasting John E. Boylan, Aris A. Syntetos, 2021-06-02 INTERMITTENT DEMAND FORECASTING The first text to focus on the methods and approaches of intermittent, rather than fast, demand forecasting Intermittent Demand Forecasting is for anyone who is interested in improving forecasts of intermittent demand products, and enhancing the management of inventories. Whether you are a practitioner, at the sharp end of demand planning, a software designer, a student, an academic teaching operational research or operations management courses, or a researcher in this field, we hope that the book will inspire you to rethink demand forecasting. If you do so, then you can contribute towards significant economic and environmental benefits. No prior knowledge of intermittent demand forecasting or inventory management is assumed in this book. The key formulae are accompanied by worked examples to show how they can be implemented in practice. For those wishing to understand the theory in more depth, technical notes are provided at the end of each chapter, as well as an extensive and up-to-date collection of references for further study. Software developments are reviewed, to give an appreciation of the current state of the art in commercial and open source software. “Intermittent demand forecasting may seem like a specialized area but actually is at the center of sustainability efforts to consume less and to waste less. Boylan and Syntetos have done a superb job in showing how improvements in inventory management are pivotal in achieving this. Their book covers both the theory and practice of intermittent demand forecasting and my prediction is that it will fast become the bible of the field.” —Spyros Makridakis, Professor, University of Nicosia, and Director, Institute for the Future and the Makridakis Open Forecasting Center (MOFC). “We have been able to support our clients by adopting many of the ideas discussed in this excellent book, and implementing them in our software. I am sure that these ideas will be equally helpful for other supply chain software vendors and for companies wanting to update and upgrade their capabilities in forecasting and inventory management.” —Suresh Acharya, VP, Research and Development, Blue Yonder. “As product variants proliferate and the pace of business quickens, more and more items have intermittent demand. Boylan and Syntetos have long been leaders in extending forecasting and inventory methods to accommodate this new reality. Their book gathers and clarifies decades of research in this area, and explains how practitioners can exploit this knowledge to make their operations more efficient and effective.” —Thomas R. Willemain, Professor Emeritus, Rensselaer Polytechnic Institute. |
| forecasting in operations management: Service Parts Management Nezih Altay, Lewis A. Litteral, 2011-03-24 With the pressure of time-based competition increasing, and customers demanding faster service, availability of service parts becomes a critical component of manufacturing and servicing operations. Service Parts Management first focuses on intermittent demand forecasting and then on the management of service parts inventories. It guides researchers and practitioners in finding better management solutions to their problems and is both an excellent reference for key concepts and a leading resource for further research. Demand forecasting techniques are presented for parametric and nonparametric approaches, and multi echelon cases and inventory pooling are also considered. Inventory control is examined in the continuous and periodic review cases, while the following are all examined in the context of forecasting: • error measures, • distributional assumptions, and • decision trees. Service Parts Management provides the reader with an overview and a detailed treatment of the current state of the research available on the forecasting and inventory management of items with intermittent demand. It is a comprehensive review of service parts management and provides a starting point for researchers, postgraduate students, and anyone interested in forecasting or managing inventory. |
| forecasting in operations management: Forecasting in Business and Economics C. W. J. Granger, 1989-04-28 Describes the major techniques of forecasting used in economics and business. This book focuses on the forecasting of economic data and covers a range of topics, including the description of the Box-Jenkins single series modeling techniques; forecasts from purely statistical and econometric models; nonstationary and nonlinear models; and more. |
| forecasting in operations management: Demand Forecasting and Order Planning in Supply Chains and Humanitarian Logistics Taghipour, Atour, 2020-09-18 In a decentralized supply chain, most of the supply chain agents may not share information due to confidentiality policies, quality of information, or different system incompatibilities. Every actor holds its own set of information and attempts to maximize its objective (minimizing costs/minimizing inventory holdings) based on the available settings. Therefore, the agents control their own activities with the objective of improving their own competitiveness, which leads them to make decisions that maximize their local performance by ignoring the other agents or even the final consumer. These decisions are myopic because they do not consider the performance of all the partners to satisfy the consumer. Demand Forecasting and Order Planning in Supply Chains and Humanitarian Logistics is a collection of innovative research that focuses on demand anticipation, forecasting, and order planning as well as humanitarian logistics to propose original solutions for existing problems. While highlighting topics including artificial intelligence, information sharing, and operations management, this book is ideally designed for supply chain managers, logistics personnel, business executives, management experts, operation industry professionals, academicians, researchers, and students who want to improve their understanding of supply chain coordination in order to be competitive in the new era of globalization. |
| forecasting in operations management: Forecasting for Economics and Business Gloria González-Rivera, 2016-12-05 For junior/senior undergraduates in a variety of fields such as economics, business administration, applied mathematics and statistics, and for graduate students in quantitative masters programs such as MBA and MA/MS in economics. A student-friendly approach to understanding forecasting. Knowledge of forecasting methods is among the most demanded qualifications for professional economists, and business people working in either the private or public sectors of the economy. The general aim of this textbook is to carefully develop sophisticated professionals, who are able to critically analyze time series data and forecasting reports because they have experienced the merits and shortcomings of forecasting practice. |
| forecasting in operations management: Advances in Business and Management Forecasting Kenneth D. Lawrence, Michael D. Geurts, 2006-02-17 Aims to present state-of-the-art studies in the application of forecasting methodologies to such areas as sales, marketing, and strategic decision making. The topics in this title include: sales and marketing, forecasting, new product forecasting, judgmentally based forecasting, the application of surveys to forecasting, and more. |
| forecasting in operations management: Demand Forecasting and Inventory Control Colin Lewis, 2012-05-23 This practical book covers the forecasting- and inventory control methods used in commercial, retail and manufacturing companies. Colin Lewis explains the theory and practice of current demand forecasting methods, the links between forecasts produced as a result of analysing demand data and the various methods by which this information, together with cost information on stocked items, is used to establish the controlling parameters of the most commonly used inventory control systems. The demand forecasting section of the book concentrates on the family of short-term forecasting models based on the exponentially weighted average and its many variants and also a group of medium-term forecasting models based on a time series, curve fitting approach. The inventory control sections investigate the re-order level policy and re-order cycle policy and indicate how these two processes can be operated at minimum cost while offering a high level of customer service. |
| forecasting in operations management: Strategic Business Forecasting: A Structured Approach to Shaping the Future of Your Business Simon Ramo, Ronald Sugar, 2009-03-07 “A helpful read not just for corporate strategists but for almost anyone looking ahead.” Los Angeles Times What's Your Next Big Move? At the turn of the century, Western Union passed on the chance to dominate the telephone industry. Later, General Electric concluded that a new invention called television was doomed to fail. And very recently, decision makers at the highest level were taken off-guard when the global economy dropped from under their feet--and took their companies with it. Today, only those business leaders with the power of long-term foresight will seize and hold true competitive advantage. But can managers really predict the future? Yes, to a greater extent than one might expect. Strategic Business Forecasting shows how to identify and quantify possible events that may affect your business. Applying creativity, personal experience, and the lessons of history, you can use such forecasting to develop plans that will help your organization compete. Drs. Simon Ramo and Ronald Sugar, two giants of the aerospace industry, share their Four-Measures Rating system to help you explore the world of possibilities--thoroughly and systematically. Under their tutelage, you will be equipped to: Create a comprehensive list of possible scenarios concerning your business Utilize a scoring system to rate each scenario's merit as a serious and useful prediction Develop an effective plan that strategically shapes the future of your organization The authors provide vivid illustrations of the Four-Measures system at work with real-world examples of both forecasting failures and successes. No one can predict perfectly, and the authors don't promise magic. With the approach described in Strategic Business Forecasting, however, you can ensure your organization is better poised to seize future opportunities, avoid pitfalls, and handle anything the increasingly volatile global economy throws your way. |
| forecasting in operations management: Encyclopedia of Production and Manufacturing Management Paul M. Swamidass, 2000-06-30 Production and manufacturing management since the 1980s has absorbed in rapid succession several new production management concepts: manufacturing strategy, focused factory, just-in-time manufacturing, concurrent engineering, total quality management, supply chain management, flexible manufacturing systems, lean production, mass customization, and more. With the increasing globalization of manufacturing, the field will continue to expand. This encyclopedia's audience includes anyone concerned with manufacturing techniques, methods, and manufacturing decisions. |
| forecasting in operations management: Operations Management R. Dan Reid, Nada R. Sanders, 2005-06-24 This 2nd Value Edition features all the content of Operations Management, 2nd Edition in a paperback format for a new low price. Taking a balanced, integrative approach, Operations Management, 2nd Value Edition demonstrates the critical impact OM has in today's business environments, and shows how it relates to every department in an organization. Authors R. Dan Reid and Nada R. Sanders provide clear, focused, and highly engaging coverage of key operations management topics, and make strong connections across concepts and chapters. |
| forecasting in operations management: Operations Management For Dummies Mary Ann Anderson, Edward J. Anderson, Geoffrey Parker, 2013-07-09 Score your highest in Operations Management Operations management is an important skill for current and aspiring business leaders to develop and master. It deals with the design and management of products, processes, services, and supply chains. Operations management is a growing field and a required course for most undergraduate business majors and MBA candidates. Now, Operations Management For Dummies serves as an extremely resourceful aid for this difficult subject. Tracks to a typical course in operations management or operations strategy, and covers topics such as evaluating and measuring existing systems' performance and efficiency, materials management and product development, using tools like Six Sigma and Lean production, designing new, improved processes, and defining, planning, and controlling costs of projects. Clearly organizes and explains complex topics Serves as an supplement to your Operations Management textbooks Helps you score your highest in your Operations Management course Whether your aim is to earn an undergraduate degree in business or an MBA, Operations Management For Dummies is indispensable supplemental reading for your operations management course. |
| forecasting in operations management: Global Supply Chain and Operations Management Dmitry Ivanov, Alexander Tsipoulanidis, Jörn Schönberger, 2021-11-19 The third edition of this textbook comprehensively discusses global supply chain and operations management (SCOM), combining value creation networks and interacting processes. It focuses on operational roles within networks and presents the quantitative and organizational methods needed to plan and control the material, information, and financial flows in supply chains. Each chapter begins with an introductory case study, while numerous examples from various industries and services help to illustrate the key concepts. The book explains how to design operations and supply networks and how to incorporate suppliers and customers. It examines how to balance supply and demand, a core aspect of tactical planning, before turning to the allocation of resources to meet customer needs. In addition, the book presents state-of-the-art research reflecting the lessons learned from the COVID-19 pandemic, and emerging, fast-paced developments in the digitalization of supply chain and operations management. Providing readers with a working knowledge of global supply chain and operations management, with a focus on bridging the gap between theory and practice, this textbook can be used in core, specialized, and advanced classes alike. It is intended for a broad range of students and professionals in supply chain and operations management. |
| forecasting in operations management: Introduction to Financial Forecasting in Investment Analysis John B. Guerard, Jr., 2013-01-04 Forecasting—the art and science of predicting future outcomes—has become a crucial skill in business and economic analysis. This volume introduces the reader to the tools, methods, and techniques of forecasting, specifically as they apply to financial and investing decisions. With an emphasis on earnings per share (eps), the author presents a data-oriented text on financial forecasting, understanding financial data, assessing firm financial strategies (such as share buybacks and R&D spending), creating efficient portfolios, and hedging stock portfolios with financial futures. The opening chapters explain how to understand economic fluctuations and how the stock market leads the general economic trend; introduce the concept of portfolio construction and how movements in the economy influence stock price movements; and introduce the reader to the forecasting process, including exponential smoothing and time series model estimations. Subsequent chapters examine the composite index of leading economic indicators (LEI); review financial statement analysis and mean-variance efficient portfolios; and assess the effectiveness of analysts’ earnings forecasts. Using data from such firms as Intel, General Electric, and Hitachi, Guerard demonstrates how forecasting tools can be applied to understand the business cycle, evaluate market risk, and demonstrate the impact of global stock selection modeling and portfolio construction. |
| forecasting in operations management: Essentials of Operations Management Scott T. Young, 2009-02-20 Discusses the major topics and strategies that relate to operations management. Covers “modern” subjects such as human resources in operations, facility location, green operations, and the balanced scorecard approach to operations. Includes end-of-chapter projects and exercises, plus review questions and summary points. |
| forecasting in operations management: Demand Forecasting for Inventory Control Nick T. Thomopoulos, 2014-12-04 This book describes the methods used to forecast the demands at inventory holding locations. The methods are proven, practical and doable for most applications, and pertain to demand patterns that are horizontal, trending, seasonal, promotion and multi-sku. The forecasting methods include regression, moving averages, discounting, smoothing, two-stage forecasts, dampening forecasts, advance demand forecasts, initial forecasts, all time forecasts, top-down, bottom-up, raw and integer forecasts, Also described are demand history, demand profile, forecast error, coefficient of variation, forecast sensitivity and filtering outliers. The book shows how the forecasts with the standard normal, partial normal and truncated normal distributions are used to generate the safety stock for the availability and the percent fill customer service methods. The material presents topics that people want and should know in the work place. The presentation is easy to read for students and practitioners; there is little need to delve into difficult mathematical relationships, and numerical examples are presented throughout to guide the reader on applications. Practitioners will be able to apply the methods learned to the systems in their locations, and the typical worker will want the book on their bookshelf for reference. The potential market is vast. It includes everyone in professional organizations like APICS, DSI and INFORMS; MBA graduates, people in industry, and students in management science, business and industrial engineering. |
| forecasting in operations management: Principles of Business Forecasting--2nd Ed Keith Ord, Robert Fildes, Nikos Kourentzes, 2017-06 This second edition of Principles of Business Forecasting by Keith Ord, Robert Fildes, and newest author Nikolaos Kourentzes serves as both a textbook for students and as a reference book for experienced forecasters in a variety of fields. The authors' motivation for writing this book, is to give users the tools and insight to make the most effective forecasts drawing on the latest research ideas, without being overly technical. The book is unique in its design, providing an introduction to both standard and advanced forecasting methods, as well as a focus on general principles to guide and simplify forecasting practice for those with little or no professional experience. One of the book's key strengths is the emphasis on real data sets, which have been updated in this second edition. These data sets are taken from government and business sources and are used throughout in the chapter examples and exercises. Forecasting techniques are demonstrated using a variety of software platforms beyond just R, and a companion website provides easy-to-use Excel(R) macros that users can access to conduct analyses. Another important innovation in the second edition is the tutorial support for using open-source R programs, making all the methods available for use both in courses and practice. After the introductory chapters, the focus shifts to using extrapolative methods (exponential smoothing and ARIMA), then to statistical model-building using multiple regression. The authors also cover more novel techniques including data mining and judgmental methods, which are gaining increasing attention in applications. The second edition also offers expanded material on data analytics, in particular neural nets together with software, and applications that include new research findings relevant and immediately applicable to operations, such as hierarchical modeling and temporal aggregation. Finally, the authors examine organizational issues of implementation and the development of a forecasting support system within an organization; relevant to every manager, or future manager, who must make plans or decisions based on forecasts. Please take a moment to review the companion website for additional content in the Appendices (Basic Statistical Concepts, overview of Forecasting Software, and Forecasting in R: Tutorial and Examples) the many data sets referenced in the chapters, macros such as the Exponential Smoothing and Trend Curve Marcos and Time Series Neural Network Analysis and student study materials. |
| forecasting in operations management: Inventory Planning with Forecasting Expenditure Sanjay Sharma, 2022-03-06 In industrial or business cases, purchasing and procurement are significant functions. Usually, a procurement plan is prepared based on certain predictions of consumption patterns or demand. When this plan is implemented, the benefit is obtained corresponding to forecast accuracy. In the available literature, forecasting accuracy is frequently discussed. A need is established to link forecasting accuracy with forecasting expenditures. After an explicit inclusion of the forecasting expenditure, this book describes inventory planning for procurement and production. FEATURES Discusses forecasting expenditure in detail Provides an analysis of reduction and increase in forecasting expenditures Highlights advanced concepts that include procurement inventory, production planning, and priority planning in detail Examines an approach in relation to the inclusion of an explicit cost of forecasting Covers total cost formulation, modified total cost, relevant index, threshold value, and cost of forecasting in a comprehensive manner with the help of examples Inventory Planning with Forecasting Expenditure is useful for undergraduate and postgraduate students in engineering and management and has potential for elective and supplementary core courses. |
| forecasting in operations management: Market Operations in Electric Power Systems Mohammad Shahidehpour, Hatim Yamin, Zuyi Li, 2003-05-28 An essential overview of post-deregulation market operations inelectrical power systems Until recently the U.S. electricity industry was dominated byvertically integrated utilities. It is now evolving into adistributive and competitive market driven by market forces andincreased competition. With electricity amounting to a $200 billionper year market in the United States, the implications of thisrestructuring will naturally affect the rest of the world. Why is restructuring necessary? What are the components ofrestructuring? How is the new structure different from the oldmonopoly? How are the participants strategizing their options tomaximize their revenues? What are the market risks and how are theyevaluated? How are interchange transactions analyzed and approved?Starting with a background sketch of the industry, this hands-onreference provides insights into the new trends in power systemsoperation and control, and highlights advanced issues in thefield. Written for both technical and nontechnical professionals involvedin power engineering, finance, and marketing, this must-haveresource discusses: * Market structure and operation of electric power systems * Load and price forecasting and arbitrage * Price-based unit commitment and security constrained unitcommitment * Market power analysis and game theory applications * Ancillary services auction market design * Transmission pricing and congestion Using real-world case studies, this timely survey offers engineers,consultants, researchers, financial managers, university professorsand students, and other professionals in the industry acomprehensive review of electricity restructuring and how itsradical effects will shape the market. |
| forecasting in operations management: Handbook of Operations Research and Management Science in Higher Education Zilla Sinuany-Stern, 2021-09-09 This handbook covers various areas of Higher Education (HE) in which operations research/management science (OR/MS) techniques are used. Key examples include: international comparisons, university rankings, and rating academic efficiency with Data Envelopment Analysis (DEA); formulating academic strategy with balanced scorecard; budgeting and planning with linear and quadratic models; student forecasting; E-learning evaluation; faculty evaluation with questionnaires and multivariate statistics; marketing for HE; analytic and educational simulation; academic information systems; technology transfer with systems analysis; and examination timetabling. Overviews, case studies and findings on advanced OR/MS applications in various functional areas of HE are included. |
| forecasting in operations 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. |
| forecasting in operations management: Operations Management B. Mahadevan, 2010 Covers the core concepts and theories of production and operations management in the global as well as Indian context. Includes boxes, solved numerical examples, real-world examples and case studies, practice problems, and videos. Focuses on strategic decision making, design, planning, and operational control--Provided by publisher. |
| forecasting in operations management: Demand and Supply Integration Mark A. Moon, 2013-01-14 Supply chain professionals: master pioneering techniques for integrating demand and supply, and create demand forecasts that are far more accurate and useful! In Demand and Supply Integration, Dr. Mark Moon presents the specific design characteristics of a world-class demand forecasting management process, showing how to effectively integrate demand forecasting within a comprehensive Demand and Supply Integration (DSI) process. Writing for supply chain professionals in any business, government agency, or military procurement organization, Moon explains what DSI is, how it differs from approaches such as SandOP, and how to recognize the symptoms of failures to sufficiently integrate demand and supply. He outlines the key characteristics of successful DSI implementations, shows how to approach Demand Forecasting as a management process, and guides you through understanding, selecting, and applying the best available qualitative and quantitative forecasting techniques. You'll learn how to thoroughly reflect market intelligence in your forecasts; measure your forecasting performance; implement state-of-the-art demand forecasting systems; manage Demand Reviews, and much more. For wide audiences of supply chain, logistics, and operations management professionals at all levels, from analyst and manager to Director, Vice President, and Chief Supply Chain Officer; and for researchers and graduate students in the field. |
| forecasting in operations management: Production & Operations Management Essentials Sai Kolli, 1999-12 REA’s Essentials provide quick and easy access to critical information in a variety of different fields, ranging from the most basic to the most advanced. As its name implies, these concise, comprehensive study guides summarize the essentials of the field covered. Essentials are helpful when preparing for exams, doing homework and will remain a lasting reference source for students, teachers, and professionals. Topics include quality management, quality control, forecasting, product/service design, process selections, aggregate planning, scheduling, advanced manufacturing, material purchasing and maintenance, and decision making. |
| forecasting in operations management: Foreign-Exchange-Rate Forecasting with Artificial Neural Networks Lean Yu, Shouyang Wang, Kin Keung Lai, 2010-02-26 This book focuses on forecasting foreign exchange rates via artificial neural networks (ANNs), creating and applying the highly useful computational techniques of Artificial Neural Networks (ANNs) to foreign-exchange rate forecasting. The result is an up-to-date review of the most recent research developments in forecasting foreign exchange rates coupled with a highly useful methodological approach to predicting rate changes in foreign currency exchanges. |
| forecasting in operations management: Business Intelligence in Economic Forecasting: Technologies and Techniques Wang, Jue, Wang, Shouyang, 2010-06-30 With the rapid development of economic globalization and information technology, the field of economic forecasting continues its expeditious advancement, providing business and government with applicable technologies. This book discusses various business intelligence techniques including neural networks, support vector machine, genetic programming, clustering analysis, TEI@I, fuzzy systems, text mining, and many more. It serves as a valuable reference for professionals and researchers interested in BI technologies and their practical applications in economic forecasting, as well as policy makers in business organizations and governments. |
| forecasting in operations management: Demand and Supply Integration Mark A. Moon, 2018-04-09 Supply chain professionals: master pioneering techniques for integrating demand and supply, and create demand forecasts that are far more accurate and useful! In Demand and Supply Integration, Dr. Mark Moon presents the specific design characteristics of a world-class demand forecasting management process, showing how to effectively integrate demand forecasting within a comprehensive Demand and Supply Integration (DSI) process. Writing for supply chain professionals in any business, government agency, or military procurement organization, Moon explains what DSI is, how it differs from approaches such as S&OP, and how to recognize the symptoms of failures to sufficiently integrate demand and supply. He outlines the key characteristics of successful DSI implementations, shows how to approach Demand Forecasting as a management process, and guides you through understanding, selecting, and applying the best available qualitative and quantitative forecasting techniques. You'll learn how to thoroughly reflect market intelligence in your forecasts; measure your forecasting performance; implement state-of-the-art demand forecasting systems; manage Demand Reviews, and much more. |
| forecasting in operations management: Time Series Analysis and Adjustment Haim Y Bleikh, Professor Warren L Young, 2014-07-28 In Time Series Analysis and Adjustment the authors explain how the last four decades have brought dramatic changes in the way researchers analyze economic and financial data on behalf of economic and financial institutions and provide statistics to whomsoever requires them. Such analysis has long involved what is known as econometrics, but time series analysis is a different approach driven more by data than economic theory and focused on modelling. An understanding of time series and the application and understanding of related time series adjustment procedures is essential in areas such as risk management, business cycle analysis, and forecasting. Dealing with economic data involves grappling with things like varying numbers of working and trading days in different months and movable national holidays. Special attention has to be given to such things. However, the main problem in time series analysis is randomness. In real-life, data patterns are usually unclear, and the challenge is to uncover hidden patterns in the data and then to generate accurate forecasts. The case studies in this book demonstrate that time series adjustment methods can be efficaciously applied and utilized, for both analysis and forecasting, but they must be used in the context of reasoned statistical and economic judgment. The authors believe this is the first published study to really deal with this issue of context. |
Forecasting - Wikipedia
Forecasting is the process of making predictions based on past and present data. Later these can be compared with what actually happens. For example, a company might estimate their …
What Is Forecasting? - IBM
Jul 22, 2024 · Forecasting is a method of predicting a future event or condition by analyzing patterns and uncovering trends in previous and current data. It employs mathematical …
Forecasting - Overview, Methods and Features, Steps
Forecasting refers to the practice of predicting what will happen in the future by taking into consideration events in the past and present. Basically, it is a decision-making tool that helps …
Six Rules for Effective Forecasting - Harvard Business Review
In describing what forecasters are trying to achieve, Saffo outlines six simple, commonsense rules that smart managers should observe as they embark on a voyage of discovery with …
Forecasting: Meaning, Nature, Planning and Forecasting, …
Jun 5, 2024 · What is Forecasting? Forecasting involves making educated guesses about future events that could affect a company. Businesses can predict sales, finances, customer …
Forecasting | Definition, Methods, Steps, & Limitations
Sep 7, 2023 · Financial forecasting is the act of estimating future financial outcomes for a business or an investment. It is a critical process in financial planning and decision-making. It …
Q&A: What Is Forecasting? Definition, Methods and Examples
Jun 6, 2025 · Forecasting is a method of making informed predictions by using historical data as the main input for determining the course of future trends. Companies use forecasting for …
Top 6 Types of Forecasting Models (+ Examples) - 10XSheets
Jul 12, 2023 · Forecasting models provide valuable insights into future trends and patterns, enabling organizations to allocate resources effectively, optimize inventory levels, manage …
What is Forecasting? Modern Techniques & AI Solutions | ketteQ
Feb 12, 2025 · Forecasting has come a long way in the last few decades, with gut feelings and educated guesses giving way to data-driven insights based on complex algorithms. …
What is a Forecast? - Forecasting Models Explained - AWS
Forecasting acts as a planning tool to help enterprises prepare for the uncertainty that can occur in the future. It helps managers respond confidently to changes, control business operations, …
Forecasting - Wikipedia
Forecasting is the process of making predictions based on past and present data. Later these can be compared with what actually happens. For example, a company …
What Is Forecasting? - IBM
Jul 22, 2024 · Forecasting is a method of predicting a future event or condition by analyzing patterns and uncovering trends in previous and current data. It employs …
Forecasting - Overview, Methods and Features, Steps
Forecasting refers to the practice of predicting what will happen in the future by taking into consideration events in the past and present. Basically, it is a decision …
Six Rules for Effective Forecasting - Harvard Business Review
In describing what forecasters are trying to achieve, Saffo outlines six simple, commonsense rules that smart managers should observe as they embark on a …
Forecasting: Meaning, Nature, Planning and Forecasting, Import…
Jun 5, 2024 · What is Forecasting? Forecasting involves making educated guesses about future events that could affect a company. Businesses can predict sales, finances, …
