The IIF provides links to these sites that we believe will be useful to forecasters but does not control the sites nor take a position on the views they express.
- Applied Forecasting is an independent forecasting portal that contains up-to-date news and upcoming events for researchers, practitioners and students.
- The Conference Board – This site provides economic and business cycle indicators.
- Decision Sciences Journal of Innovative Education is a peer-reviewed journal published by the Decision Sciences Institute. Its mission is to publish significant research relevant to teaching, learning, and education in the decision sciences – quantitative and behavioral approaches to managerial decision making. For more details, contact the editor
- Demand Forecasting – Provides global training and endorsed IIF certification curriculum for corporate demand forecasters/planners/managers
- Demand Planning - Provides consulting and training in Demand Planning, Sales Forecasting, business forecasting and S&OP.
- Econometric Links – Marius Ooms provides links to econometrics courses, conferences, and data.
- FAIRMODEL – Ray Fair enables you to interact online with U.S. and multicountry econometric models.
- Forecasting models for symbolic data – This site covers the investigation and study of different forecasting methods applied to symbolic data such as intervals, histograms or distributions.
- Forecasting Principles – An excellent resource for finding forecasting related data, research, links, and other information, this site is provided as a public service by the International Institute of Forecasters. Created in 1997 by Professor J. Scott Armstrong, The Wharton School, University of Pennsylvania, it is managed by Scott Armstrong and Kesten C. Green of the Business and Economic Forecasting Unit at Monash.
- George Washington University – The Research Program on Forecasting supports research, teaching, and dissertation supervision in forecasting as part of the Department of Economics and the Center for Economic Research at The George Washington University. Our website includes information on our current activities, research, and members. It also provides links to our current working papers and other useful links.
- INFORMS - The Institute for Operations Research and the Management Sciences (INFORMS) is the largest professional society in the world for professionals in the field of operations research (O.R.), management science, and business analytics.
- Lancaster Centre for Forecasting – The Lancaster Centre for Forecasting is the pre-eminent focus of academic and corporate forecasting research in Europe. As a non-profit research-driven organisation, we provide unbiased services to the corporate and public sector – independent of methods, techniques, software products and vendors. The Centre offers 15 years of expertise in over 20 corporate projects per year on the complete range of predictive analytics, from demand planning to market modelling, from statistical methods to artificial intelligence and from public sector to corporations in telecommunications, fast moving consumer goods, insurances and manufacturing.
- Monash University Business and Economic Forecasting Unit
- The Portal on Forecasting with Neural Networks
- NEP-FOR report
- Lancaster University
- Goodwin,P., Fildes, R., Lawrence, M. and Nikolopoulos,K., 2006, The Process of Using a Forecasting Support System (pdf)
J. Scott Armstrong, ed., Principles of Forecasting, 2001. This summary of knowledge from experts and empirical studies provides guidelines that apply to economics, sociology, psychology and other fields. It addresses problems related to finance (How much is this company worth?), marketing (Will a new product be successful?), personnel (How can we identify the best job candidates?), and production (What level of inventories should be kept?). Edited by Professor J. Scott Armstrong of the Wharton School, University of Pennsylvania, this book contains contributions by 40 leading experts in forecasting. The 30 chapters cover all types of forecasting methods: judgmental methods, such as Delphi, role-playing, and intentions studies and quantitative methods, including econometric methods, expert systems, and extrapolation. Some methods, such as conjoint analysis, analogies, and rule-based forecasting, integrate quantitative and judgmental procedures. In each area, the authors identify what is known in the form of “if-then principles” and summarize evidence on these principles. The book also includes the first comprehensive forecasting dictionary. Developed over a four-year period, the book presents knowledge in the form of principles that can be used by researchers and practitioners. To ensure accuracy, the authors reviewed one another’s papers. In addition, 122 external reviewers made suggestions.
J. Scott Armstrong, Long-Range Forecasting: From Crystal Ball to Computer, John Wiley and Sons, 1985 (second edition). Designed to answer the question “Which forecasting method is the best to use in a given situation?” this book covers judgmental, extrapolation, and econometric methods. It shows how to combine forecasts and describes how to evaluate and compare different forecasting methods. The conclusions are based on the author’s research as well as on over 1050 books and papers on forecasting in economics, sociology, medicine, politics, weather, finance, personnel, marketing, and other areas. The book describes this vast array of literature. This second edition is out of print but is available online in a pdf of the full text.
Michael Bell and Dr. Ulrich Kustes, The Forecasting Report, IT Research, 1999. This report provides detailed knowledge about 43 systems that are used for forecasting.
Fildes, Robert and Ord, Keith, Principles of Business Forecasting, July 2012 by Cengage, is a new book by Lancaster University Management School’s Robert Fildes and Keith Ord of Georgetown University.
The Ord/Fildes book serves both as a textbook for students and as a reference book for experienced forecasters in the many fields where forecasting is applied. The book introduces both standard and advanced forecasting methods and their underlying models, and also includes general principles to guide and simplify forecasting practice. The overall aim remains one of ensuring the techniques can be applied. A key strength of the book is its emphasis on real data sets, taken from government and business sources and used in each chapter’s examples and exercises. Forecasting techniques are demonstrated using a variety of software platforms and the companion website provides easy-to-use Excel® macros to support the basic methods.
Robert Fildes, et al., A Bibliography of Business and Economic Forecasting. This work is available in full text and as a searchable index on the Forecasting principles site. The authors provide keywords to describe each study allowing the reader to search for relevant studies not available on other electronic searches. It covers literature from 1965 through 1981 from over 50 journals and a number of books, describing 5,436 papers on forecasting.
Hyndman, R.J. and G. Athanasopoulos Forecasting Principles and Practice
This textbook is intended to provide a comprehensive introduction to forecasting methods and present enough information about each method for readers to use them sensibly. We don’t attempt to give a thorough discussion of the theoretical details behind each method, although the references at the end of each chapter will fill in many of those details. The entire book is available online and free-of-charge.
Hyndman, R.J., Koehler A.B., Ord, J.K., Snyder, R.D. Forecasting with Exponential Smoothing: The State Space Approach, Springer-Verlag, 2008.. Exponential smoothing methods have been around since the 1950s, and are still the most popular forecasting methods used in business and industry. Recently, exponential smoothing has been revolutionized with the introduction of a complete modeling framework incorporating innovations state sapce models, likelihood calculation, prediction intervals and procedures for model selection. In this book, all of the important results are brought together in a coherent manner with consistent notation. In addition, many new results and extensions are introduced and several application areas are examined in detail.
Levenbach, H. and Cleary, James P., Forecasting: Practice and Process for Demand Management, Thomson/Brooks-Cole, 2006.This text introduces students to the forecasting principles, applications, and methods of demand forecasting. L&C stress applications in their book, presenting concepts in the context of real examples drawn from their own broad experience as forecasting practitioners in industry, consultants to organizations, and educators. It also addresses the macroeconomic forecasting procedures used by economists as well as the specific product-level forecasting techniques now widely used by corporate sales and operations planning organizations—providing comprehensive coverage of traditional and advanced forecasting tools. Throughout, the authors focus more on training students to perform accurate data analysis than on modeling sophistication. The text incorporates computing throughout the book, featuring Microsoft® Excel applications and including a free copy of anl Excel add-in, called PEERForecaster.xla and data sets on CD.
Makridakis, Spyros, Wheelwright, Steven and Hyndman, Rob, Forecasting: methods and applications, John Wiley and Sons, 1998 (third edition). This book, sometimes known as the “Bible of forecasting”, is the best-selling introductory text in business forecasting. It covers the full range of major forecasting methods and provides a complete description of their essential characteristics including the steps needed for their practical application. The book avoids getting bogged down in the theoretical details that are not essential to understanding how the various methods work, and provides a systematic comparison of the advantages and drawbacks of various methods so that the most appropriate method can be selected for each forecasting situation. It covers a comprehensive set of forecasting horizons (from the immediate to the long term) and approaches to forecasting (time series, explanatory, judgemental, mixed).
Wilson, J. Holton and Keating, Barry, Business Forecasting, Richard D. Irwin, Inc., 1984 (second edition). Using realistic problem sets with actual data, this applied forecasting book covers standard techniques such as exponential smoothing, regression, and ARIMA models, as well as some newer procedures such as bootstrapping and combinatorial forecasting. Special attention is paid to model selection criteria. The book includes techniques actually used by Fortune 500 companies and presents sidebar examples from several companies. 101 CitiBase data sets are included with the book as well as a sampler version of the SORITEC statistical package (on included diskette).
Nash, John and Mary, Practical Forecasting for Managers, Arnold Publisher, 2001. This book is an introductory guide to business forecasting for managers and MBA students. Details about the book, as well as datasets, exercises, and forecasting links, can be found on the supporting website. It’s also possible to purchase copies through the website. Inspection copies of the book are available to academics who teach relevant courses with 15 or more students. For inspection copies, please email , with your name, college address, and course details. (Please note: Inspection copies are sent to lecturers for 28 days. After this period, the lecturer may adopt the copy as a core text, return the text with no obligation, or purchase the text for personal use.)
Nown, Graham, The World’s Worst Predictions, London: Arrow, 1985.
Wright, George and Goodwin, Paul, eds., Forecasting with Judgment, John Wiley and Sons, 1998. This collection of ten papers brings together recent research on the role of judgment in forecasting and methods for improving its application.
- “Judgment: Its Role and Value for Strategy,” Spyros Makridakis and Anil Gaba
- “Scenario Planning: Scaffolding Disorganized ideas about the Future,” Kees van der Heijden
- “Judgmental Forecasting and the Use of Available Information”, Marcus O’Connor and Michael Lawrence
- “Enhancing Judgmental Sales Forecasting: The Role of Laboratory Research,” Paul Goodwin
- “Heuristics and Biases in Judgmental Forecasting,” Fergus Bolger and Nigel Harvey
- “Financial Forecasting with Judgment,” Dilek Ínkal-Atay
- “Reasoning with Category Knowledge in Probability Forecasting: Typicality and Perceived Variability Effects,” Glenn J. Browne and Shawn P. Curley
- “The Use of Structured Groups to Improve Judgmental Forecasting,” Gene Rowe
- “How Bad is Human Judgment?” Peter Ayton
- “Integration of Statistical Methods and Judgment for Time Series Forecasting: Principles from Empirical Research,” J. Scott Armstrong and Fred Collopy
Advanced Analytics Group produces Auguri, a data analysis, manipulation and forecasting application with emphasis in nonlinear dynamical methods.
Automatic Forecasting Systems features David Reilly’s AutoBox, an automatic ARIMA-modelling system.
Business Forecast Systems, Inc. is the publisher of Dr. Robert Goodrich’s Forecast Pro.
Data Perceptions develops and distributes Prophecy, a multi-user sales forecasting solution for Windows which integrates volume and financial forecasting in a single, easy to use application. It is particularly suited to helping business forecasters develop better, more defensible judgemental forecasts and business plans.
Delphus Inc. features PEER Planner®, a forecast support system for demand analysis and replenishment planning, as well as a PEERForecaster, an Excel Add-in for ad-hoc time series forecasting applications based on the ARIMA and exponential smoothing modeling techniques.
Demand Works offers the Smoothie(tm) suite of solutions for forecasting, demand planning and supply policy optimization. Smoothie’s forecasting features a multi-dimensional technology called Pivot Forecasting(tm) that dynamically aggregates and synchronizes adjustments to any product, plant, channel or other dimensions in real time.
Forecaster XL is a neural network Excel add-in for data analysis and forecasting. It is the obvious choice for users, who need a reliable and easy-to-learn forecasting tool embedded into the familiar MS Office framework.
Forecasting Principles offers an extensive list of available, commercial software, as well as software reviews.
Host Analytics produces Sales Forecasting software.
NeuroXL (Neural Network Software Add-Ins for Excel) offers add-ins for Microsoft Excel that solve forecasting and classification problems using neural networks.
ParkerSoft produces ezForecaster, an Excel time series forecasting add-in.
SAS Institute provides a variety of forecasting and econometrics tools, as well as large-scale automatic forecasting, as part of their comprehensive analytics framework.
Scientific Computing Associates Corp. develops the SCA Statistical System for cross-industry applications in forecasting and time series analysis. Automatic modeling and forecasting for both univariate and multivariate time series make it suitable for large-scale implementations.
Smart Software, Inc. develops and distributes SmartForecasts for Windows 95/98/NT/2000, a sales and demand forecasting software system used by manufacturing, marketing, and financial planners worldwide.
Spredgar Software makes an Excel add-in to permit rapid calculation and graphing of 30 standard financial rations from the 10-K and 10-Q filings stored on the Securities and Exchange Commission’s EDGAR database.
Tableau Software The new Forecasting capability allows you to estimate future values by projecting data values based on the historical data. Tableau 8.0 provides built-in statistical models to forecast your data including models that account for seasonality and trends.
Technology Futures, Inc. offers technology forecasting guides and technology forecasts.
TIA GmbH produces sales forecasting software, System A3.
If you are interested in adding software to this list, please send your submission to and title your email “resources.”
Disclaimer: The brief descriptions were provided by the developers. The fact that programs are listed does not imply that they are endorsed by the IIF.