Foresight: The International Journal of Applied Forecasting

2005 - 2025

From International Institute of Forecasters
Contact information at EDIRC.
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A Modern Retail Forecasting System in Production pp. 5-15: Phillip Yelland
Commentary: It's the Soft Problems that Are Hard to Overcome pp. 16-19: Simon Clarke
Response to Commentary of Simon Clarke pp. 20-25: Phillip Yelland and Zeynep Erkin Baz
After Shock: The World's Foremost Futurists Reflect on 50 Years of Future Shock pp. 29-31: Ira Sohn
Dealing with "Deepfakes": How Synthetic Media Will Distort Reality, Corrupt Data, and Impact Forecasts pp. 32-37: John Wood and Nada Sanders
U.S. Presidential Election Forecasting: The Economist Model pp. 38-44: Colin Lewis-Beck and Michael Lewis-Beck
The Benefits of Systematic Forecasting for Organizations: The UFO Project pp. 45-56: Spyros Makridakis, Ellen Bonnell, Simon Clarke, Robert Fildes, Mike Gilliland, Jim Hoover and Len Tashman

Hello World: How to Be Human in the Age of the Machine by Hannah Fry pp. 4-6: Shari De Baets
How to Choose among Three Forecasting Methods: Machine Learning, Statistical Models, and Judgmental Forecasts pp. 7-14: Yue Li, Diane Berry and Jason Lee
Commentary on "How to Choose among Three Forecasting Methods: Machine Learning, Statistical Models, and Judgmental Forecasts" pp. 15-16: Stephan Kolassa
The M5: A Preview from Prior Competitions pp. 17-23: Casper Bojer and Jens Peder Meldgaard
Medical Errors in the Age of the Intelligent Machine pp. 27-35: Michael Tremblay
How Stagger Charts Can Improve Forecast Accuracy pp. 36-41: Agneta Ramosaj and Marino Widmer
Commentary: Another Use of the Stagger Chart pp. 42-42: Mike Gilliland
Technology Support in Business Planning: Automation, Augmentation, and Human Centricity pp. 43-48: Niels van Hove

The M4 Forecasting Competition-Takeaways for the Practitioner pp. 5-10: Michael Gilliland
Commentary: The M4 Competition and a Look to the Future pp. 11-12: Fotios Petropoulos
Will Deep and Machine Learning Solve Our Forecasting Problems? pp. 13-18: Stephan Kolassa
Interview with Tim Januschowski, Manager, Machine Learning Science at Amazon Web Services pp. 19-20: Len Tashman
Two Cheers for Rebooting AI: Building Artificial Intelligence We Can Trust pp. 21-23: Stephan Kolassa
Developing a Modern Retail Forecasting System: People and Processes pp. 27-38: Phillip Yelland and Zeynep Erkin Baz
Environmental Conundrum-Projections to 2050 pp. 39-45: Ira Sohn

Could These Recent Findings Improve Your Judgmental Forecasts? pp. 7-9: Paul Goodwin
Operations decisions in circular economic contexts, like remanufacturing, face dual uncertainties. They not only rely on demand forecasts but also on forecasts of returned items. It is net demand (demand minus returns) that drives replenishment. So how does this dual-source uncertainty affect the forecasting task? In this article, Thanos and Aris discuss the circular economy and the challenges of forecasting returns in a remanufacturing context. They show that serialization, the ability to link the timing of returns and sales, can substantially improve forecasts of returns, and hence of net demand pp. 10-17: Thanos Goltsos and Aris SyntetoS
Commentary: Why Is Forecasting for Remanufacturing Hard? pp. 18-19: Ram Ganeshan
Monitoring Forecast Models Using Control Charts pp. 20-25: Joseph H. Katz
Smarter Supply Chains through AI pp. 30-35: Duncan Klett
Strategic IBP: Driving Profitable Growth in Complex Global Organizations pp. 36-45: Dean Sorensen
Commentary on Strategic IBP pp. 46-47: Pete Alle
Response to Pete Alle's Commentary pp. 48-48: Dean Sorensen

Forecasting at Scale: The Architecture of a Modern Retail Forecasting System pp. 10-18: Phillip Yelland, Zeynep Erkin Baz and David Serafini
Interview with Dr. Phillip Yelland pp. 19-19: Foresight Staff
Open-Source Forecasting Tools in Python pp. 20-26: Tim Januschowski, Jan Gasthaus and Yuyang Wang
Autonomous or "Lights Out" Supply-Chain Planning: What New Technology Is Required pp. 31-34: Niels van Hove
Commentary: Close the Loop, Stabilize, and Respond pp. 35-38: Stefan De Kok
Book review of Forecasting: An Essential Introduction pp. 39-42: Michael Gilliland
Continual Learning: The Next Generation of Artificial Intelligence pp. 43-47: Daniel G. Philps

Judgmental Model Selection pp. 4-10: Fotios Petropoulos
Commentary: A Surprisingly Useful Role for Judgment pp. 11-12: Paul Goodwin
Commentary: Algorithmic Aversion and Judgmental Wisdom pp. 13-14: Nigel Harvey
Commentary: Model Selection in Forecasting Software pp. 15-16: Eric Stellwagen
Commentary: Exploit Information from the M4 Competition pp. 17-17: Spyros Makridakis
Book Review: Data Science for Supply Chain Forecast, by Nicolas Vandeput pp. 18-20: Shaun Snapp
State Space Modeling for Practitioners pp. 21-25: Diego Pedregal
Benefits and Challenges of Corporate Prediction Markets pp. 29-36: Thomas Wolfram
Interview with Thomas Wolfram pp. 37-37: Len Tashman
Why Is It So Hard to Hold Anyone Accountable for the Sales Forecast? pp. 38-43: Chris Gray
Communicating the Forecast: Providing Decision Makers with Insights pp. 44-48: Alec Finney

Will You Become a Victim of Your Models? pp. 5-7: Thomas R. Willemain
Commentary: The More Basic Questions for Forecasting the Supply Chain pp. 8-9: Chris Gray
Commentary: Love and Disdain for Forecasting Models pp. 10-11: Paul Goodwin
Commentary: Models Are Easy to Abuse pp. 12-12: David Orrell
Commentary: The Benefits of Advanced Modeling Techniques pp. 13-14: Henry Canitz
Commentary: Testing Models Is Critical pp. 15-16: John Boylan and Aris Syntetos
Will You Become a Victim of Your Models? Response to Comments pp. 17-18: Thomas R. Willemain
The Ten Commandments of Economic Forecasting pp. 19-25: Azhar Iqbal and John Silvia
Medical Science and Practice: Does Anyone Want to Fix Them? pp. 28-30: John P. A. Ioannidis
Medicine and Risk Transfer pp. 31-32: Nassim Nicholas Taleb
Monetized Forecast-Error Comparisons pp. 33-38: Shaun Snapp
Forecasting the Impact of Artificial Intelligence: Another Voice pp. 39-45: Lawrence Vanston
Response to Lawrence Vanston pp. 46-47: Spyros Makridakis
Interview with Lawrence Vanston, President, Technology Futures, Inc pp. 48-48: Foresight Editor

The Little (Illustrated) Book of Operational Forecasting pp. 5-6: Simon Clarke
Scenarios and Forecasts: Complementary Ways of Anticipating the Future? pp. 7-10: Paul Goodwin
Forecasting the Future of Retail Forecasting pp. 11-19: Stephan Kolassa
Interview with Stephan Kolassa, Foresight Associate Editor pp. 20-21: Foresight Editor
Commentary on "Forecasting the Future of Retail Forecasting" pp. 22-23: Brian Seaman
Predicting Medical Risks and Appreciating Uncertainty pp. 28-35: Spyros Makridakis, Ann Wakefield and Richard Kirkham
A Classification of Business Forecasting Problems pp. 36-43: Tim Januschowski and Stephan Kolassa
Commentary on Spyros Makridakis's article "Forecasting the Impact of Artificial Intelligence" pp. 44-47: Owen Davies