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Forecasting is required in many situations. Stocking an inventory may require forecasts of demand months in advance. Telecommunication routing requires traffic forecasts a few minutes ahead. Whatever the circumstances or time horizons involved, forecasting is an important aid in effective and efficient planning. This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly.
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 is an integral part of almost all business enterprises. This book provides readers with the tools to analyze their data, develop forecasting models and present the results in Excel. Progressing from data collection, data presentation, to a step-by-step development of the forecasting techniques, this essential text covers techniques that include but not limited to time series-moving average, exponential smoothing, trending, simple and multiple regression, and Box-Jenkins. And unlike other products of its kind that require either high-priced statistical software or Excel add-ins, this book does not require such software. It can be used both as a primary text and as a supplementary text. Highlights the use of Excel screen shots, data tables, and graphs. Features Full Scale Use of Excel in Forecasting without the Use of Specialized Forecast Packages Includes Excel templates. Emphasizes the practical application of forecasting. Provides coverage of Special Forecasting, including New Product Forecasting, Network Models Forecasting, Links to Input/Output Modeling, and Combination of Forecasting.
Numerical models have become essential tools in environmental science, particularly in weather forecasting and climate prediction. This book provides a comprehensive overview of the techniques used in these fields, with emphasis on the design of the most recent numerical models of the atmosphere. It presents a short history of numerical weather prediction and its evolution, before describing the various model equations and how to solve them numerically. It outlines the main elements of a meteorological forecast suite, and the theory is illustrated throughout with practical examples of operational models and parameterizations of physical processes. This book is founded on the author's many years of experience, as a scientist at Météo-France and teaching university-level courses. It is a practical and accessible textbook for graduate courses and a handy resource for researchers and professionals in atmospheric physics, meteorology and climatology, as well as the related disciplines of fluid dynamics, hydrology and oceanography.
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.
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.
Accurate predictions are essential in many areas such as corporate decision making, weather forecasting and technology forecasting. Prediction markets help to aggregate information and gain a better understanding of the future by leveraging the wisdom of the crowds. Trading prices in prediction markets thus reflect the traders’ aggregated expectations on the outcome of uncertain future events and can be used to predict the likelihood of these events. This book demonstrates that markets are accurate predictors. Results from several empirical studies reported in this work show the importance of designing such markets properly in order to derive valuable predictions. Therefore, the findings are valuable for designing future prediction markets.
Comprehensively teaches the fundamentals of supply chain theory This book presents the methodology and foundations of supply chain management and also demonstrates how recent developments build upon classic models. The authors focus on strategic, tactical, and operational aspects of supply chain management and cover a broad range of topics from forecasting, inventory management, and facility location to transportation, process flexibility, and auctions. Key mathematical models for optimizing the design, operation, and evaluation of supply chains are presented as well as models currently emerging from the research frontier. Fundamentals of Supply Chain Theory, Second Edition contains new chapters on transportation (traveling salesman and vehicle routing problems), integrated supply chain models, and applications of supply chain theory. New sections have also been added throughout, on topics including machine learning models for forecasting, conic optimization for facility location, a multi-supplier model for supply uncertainty, and a game-theoretic analysis of auctions. The second edition also contains case studies for each chapter that illustrate the real-world implementation of the models presented. This edition also contains nearly 200 new homework problems, over 60 new worked examples, and over 140 new illustrative figures. Plentiful teaching supplements are available, including an Instructor’s Manual and PowerPoint slides, as well as MATLAB programming assignments that require students to code algorithms in an effort to provide a deeper understanding of the material. Ideal as a textbook for upper-undergraduate and graduate-level courses in supply chain management in engineering and business schools, Fundamentals of Supply Chain Theory, Second Edition will also appeal to anyone interested in quantitative approaches for studying supply chains.
Synoptic Analysis and Forecasting: An Introductory Toolkit provides the bridge between the introductory fundamentals of a meteorology course and advanced synoptic-dynamic analysis for undergraduate students. It helps students to understand the principles of weather analysis, which will complement computer forecast models. This valuable reference also imparts qualitative weather analysis and forecasting tools and techniques to non-meteorologist end users, such as emergency/disaster managers, aviation experts, and environmental health and safety experts who need to have a foundational knowledge of weather forecasting. - Presents the fundamentals of weather analysis and forecasting - Offers clear accessible writing aimed at students from a variety of mathematical backgrounds - Discusses the reading and interpretation of surface observations and METAR code, processes associated with the motion and intensity of cyclones and anticyclones, and quantitative and/or qualitative diagnosis of processes associated with ascent and descent