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The Sixth Edition of Business Forecasting is the most practical forecasting book on the market with the most powerful software—Forecast X. This edition presents a broad-based survey of business forecasting methods including subjective and objective approaches. As always, the author team of Wilson and Keating deliver practical how-to forecasting techniques, along with dozens of real world data sets while theory and math are held to a minimum. This Sixth Edition includes Forecast X software updated for Excel 2007 and Vista. Forecast X is the most comprehensive software tool available in this market and the new version is also backwards compatible for XP Excel 2003 systems. This Excel-based tool effectively uses wizards and many tools to make forecasting easy and understandable.
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.
The recent crisis in the financial markets has exposed serious flaws in management methods. The failure to anticipate and deal with the consequences of the unfolding collapse has starkly illustrated what many leaders and managers in business have known for years; in most organizations, the process of forecasting is badly broken. For that reason, forecasting business performance tops the list of concerns for CFO's across the globe. It is time to rethink the way businesses organize and run forecasting processes and how they use the insights that they provide to navigate through these turbulent times. This book synthesizes and structures findings from a range of disciplines and over 60 years of the authors combined practical experience. This is presented in the form of a set of simple strategies that any organization can use to master the process of forecasting. The key message of this book is that while no mortal can predict the future, you can take the steps to be ready for it. ’Good enough’ forecasts, wise preparation and the capability to take timely action, will help your organization to create its own future. Written in an engaging and thought provoking style, Future Ready leads the reader to answers to questions such as: What makes a good forecast? What period should a forecast cover? How frequently should it be updated? What information should it contain? What is the best way to produce a forecast? How can you avoid gaming and other forms of data manipulation? How should a forecast be used? How do you ensure that your forecast is reliable? How accurate does it need to be? How should you deal with risk and uncertainty What is the best way to organize a forecast process? Do you need multiple forecasts? What changes should be made to other performance management processes to facilitate good forecasting? Future Ready is an invaluable guide for practicing managers and a source of insight and inspiration to leaders looking for better ways of doing things and to students of the science and craft of management. Praise for Future Ready "Will make a difference to the way you think about forecasting going forward" —Howard Green, Group Controller Unilever PLC "Great analogies and stories are combined with rock solid theory in a language that even the most reading-averse manager will love from page one" —Bjarte Bogsnes, Vice President Performance Management Development at StatoilHydro "A timely addition to the growing research on management planning and performance measurement." —Dr. Charles T. Horngren, Edmund G. Littlefield Professor of Accounting Emeritus Stanford University and author of many standard texts including Cost Accounting: A Managerial Emphasis, Introduction to Management Accounting, and Financial Accounting "In the area of Forecasting, it is the best book in the market." —Fritz Roemer. Leader of Enterprise Performance Executive Advisory Program, the Hackett Group
In this book we are concerned with Bayesian learning and forecast ing in dynamic environments. We describe the structure and theory of classes of dynamic models, and their uses in Bayesian forecasting. The principles, models and methods of Bayesian forecasting have been developed extensively during the last twenty years. This devel opment has involved thorough investigation of mathematical and sta tistical aspects of forecasting models and related techniques. With this has come experience with application in a variety of areas in commercial and industrial, scientific and socio-economic fields. In deed much of the technical development has been driven by the needs of forecasting practitioners. As a result, there now exists a relatively complete statistical and mathematical framework, although much of this is either not properly documented or not easily accessible. Our primary goals in writing this book have been to present our view of this approach to modelling and forecasting, and to provide a rea sonably complete text for advanced university students and research workers. The text is primarily intended for advanced undergraduate and postgraduate students in statistics and mathematics. In line with this objective we present thorough discussion of mathematical and statistical features of Bayesian analyses of dynamic models, with illustrations, examples and exercises in each Chapter.
Risk analysis has become critical to modern financial planning Financial Forecasting, Analysis and Modelling provides a complete framework of long-term financial forecasts in a practical and accessible way, helping finance professionals include uncertainty in their planning and budgeting process. With thorough coverage of financial statement simulation models and clear, concise implementation instruction, this book guides readers step-by-step through the entire projection plan development process. Readers learn the tools, techniques, and special considerations that increase accuracy and smooth the workflow, and develop a more robust analysis process that improves financial strategy. The companion website provides a complete operational model that can be customised to develop financial projections or a range of other key financial measures, giving readers an immediately-applicable tool to facilitate effective decision-making. In the aftermath of the recent financial crisis, the need for experienced financial modelling professionals has steadily increased as organisations rush to adjust to economic volatility and uncertainty. This book provides the deeper level of understanding needed to develop stronger financial planning, with techniques tailored to real-life situations. Develop long-term projection plans using Excel Use appropriate models to develop a more proactive strategy Apply risk and uncertainty projections more accurately Master the Excel Scenario Manager, Sensitivity Analysis, Monte Carlo Simulation, and more Risk plays a larger role in financial planning than ever before, and possible outcomes must be measured before decisions are made. Uncertainty has become a critical component in financial planning, and accuracy demands it be used appropriately. With special focus on uncertainty in modelling and planning, Financial Forecasting, Analysis and Modelling is a comprehensive guide to the mechanics of modern finance.
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.
This book emphasizes the rationale, application, and interpretation of the most commonly used forecasting techniques in business.
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.
Exponential smoothing methods have been around since the 1950s, and are still the most popular forecasting methods used in business and industry. However, a modeling framework incorporating stochastic models, likelihood calculation, prediction intervals and procedures for model selection, was not developed until recently. This book brings together all of the important new results on the state space framework for exponential smoothing. It will be of interest to people wanting to apply the methods in their own area of interest as well as for researchers wanting to take the ideas in new directions. Part 1 provides an introduction to exponential smoothing and the underlying models. The essential details are given in Part 2, which also provide links to the most important papers in the literature. More advanced topics are covered in Part 3, including the mathematical properties of the models and extensions of the models for specific problems. Applications to particular domains are discussed in Part 4.