Content
2024, Issue 72
- 1-68 Spotlight: Interview with Ruben Crevits
by Foresight Staff - 5-7 J. Scott Armstrong (1937 - 2023): Iconoclast and Champion of Science for Practical Purposes
by Kesten C. Green - 8-8 Lessons from a Mentor and Friend
by Andreas Graefe - 9-9 Scott Armstrong's Scientific Legacy
by Arch Woodside - 10-14 The Forecaster's Evaluation Dilemma
by Malte Tichy - 15-20 Combining Probability Predictions
by Ville A. Satop?? - 21-28 Estimating Predictive Probability of Success
by Shaun Comfort - 29-32 Accuracy vs. Runtime with Multiple Seasonalities
by Stephan Kolassa - 35-39 Linear Regression with a Time Series View, Part 1: Simple Linear Regression
by Ken Fordyce - 40-46 How Well Can Social Scientists Forecast Societal Change?
by Igor Grossmann & Christoph Bergmeir & Peter Slattery - 47-51 A Case for a More Decision-centric IBP
by Niels van Hove - 52-57 How Decision Intelligence Integrates Forecasting, AI, and Data into Complex Decisions
by Lorien Pratt & David Roberts & Nadine Malcolm & Brian Fisher & Katie Barnhill & Daniela Jones & Michael Kudenov - 58-59 Book Review: Sales & Operations Planning -An Executive Update by Robert A. Stahl
by Patrick Bower - 60-63 Book Review: Power and Prediction: The Disruptive Economics of Artificial Intelligence, by Ajay Agrawal, Joshua Gans, and Avi Goldfarb
by Ira Sohn - 64-65 Book Review: Demand Forecasting for Executives and Professionals, by Stephan Kolassa, Bahman Rostami-Tabar, and Enno Siemsen
by Simon Spavound - 66-67 Spotlight: Interview with Sevvandi Kandanaarachchi
by Foresight Staff - 69-71 In Pursuit of Consumption-Based Forecasting
by Charles Chase & Kenneth B. Kahn
2023, Issue 71
- 10-17 20 Years of FVA: A Critical Retrospective
by Michael Gilliland - 18-24 Enhancements to the Forecast Value Added Framework
by Jeff Baker - 25-27 A Critical Review of Forecast Value Added
by Stefan de Kok - 28-28 Two Process Changes Based on FVA Findings
by Fazlur Rahman - 29-30 The Potential of FVA for Driving Process Improvement
by Marina Sologubova - 31-37 Judgmental Adjustments in Demand Planning: Their Motivation and Success
by Robert Fildes & Paul Goodwin & Shari De Baets - 40-41 The Effective Use of External Signals and Human Inputs
by Anne-Flore Elard - 42-47 The Need for Risk Management in Forecasting Software
by Johann Robette - 48-49 Entering the Golden Age of Mixed Frequency Forecasting
by Gareth Thomas - 50-54 A Glimpse into the Future of Forecasting Software
by Spiros Potamitis & Michele Trovero & Joe Katz - 55-61 How Will Generative AI Influence Forecasting Software?
by Michele Trovero & Spiros Potamitis - 62-65 What Do We Learn from Forecasting Software Surveys?
by Oliver Schaer & Ivan Svetunkov & Robert Fildes - 66-68 Book Review- Escape from Model Land by Erica Thompson
by Robert Fildes - 69-70 The Scientific Method: A Guide to Finding Useful Knowledge by J. Scott Armstrong & Kesten C. Green
by George Karamatzanis & Kostas Nikolopoulos - 71-72 Spotlight: Shari De Baets
by Foresight Interviewer - 73-74 Spotlight: Joe McConnell
by Foresight Interviewer - 75-76 Sustainability in Forecasting
by Stephan Kolassa - 77-79 Forecasts for Infrastructure -A Crisis Confronting the Economy
by Ira Sohn
2023, Issue 70
- 5-12 Common Pitfalls and Better Practices in Forecast Evaluation for Data Scientists
by Christoph Bergmeir - 13-14 Commentary: A Practitioner's View on the Common Pitfalls
by Zeynep Erkin Baz - 15-16 Commentary: Idealism - Make Way for Realism
by Shari De Baets - 17-23 Cross-Learning with Short Seasonal Time Series
by Huijing Chen & John Boylan & Ivan Svetunkov - 24-25 Commentary: PICS, or, Why Stop at PIC?
by Stefan de Kok - 26-27 Commentary: Exponential Smoothing in the Spotlight Again
by Malvina Marchese - 28-30 The Limitations of Forecasts and Plans on Decision Making
by Niels van Hove - 31-37 The Organizational Politics of Forecasting Revisited: Collaborative Budget Forecasting Meets the COVID-19 Pandemic
by Elaine Deschamps - 40-42 Book Review of Change & Chance Embraced and Four P's in a Pod, by Hans Levenbach
by Sara Barradas - 43-44 Book Review of Demand Forecasting Best Practices by Nicolas Vandeput
by Stephan Kolassa - 45-48 Book Review of Megathreats: Ten Dangerous Trends that Imperil Our Future, and How to Survive Them, by Nouriel Roubini
by Ira Sohn - 49-52 The 10 Lies Told in Consensus Meetings
by Patrick Bower & Chip Gretok - 53-55 What Is Wrong with Demand Planning Software?
by Igor Gusakov - 56-57 Spotlight: Mark Chockalingam
by Foresight Staff - 58-59 Spotlight: Malvina Marchese
by Foresight Staff - 60-61 Forecasting: A Critical Enabler of the Circular Economy
by Thanos Goltsos & Aris Syntetos - 62-63 All Hail the Flatline Forecast!
by Stephan Kolassa - 64-65 The Technological Limits to Forecasting
by Malte Tichy - 66-67 Minitutorial: Forecasting New Product Adoption Using S-Curves
by Lawrence Vanston
2023, Issue 69
- 5-12 Time to Retire the MAPE
by Malte Tichy - 13-16 Commentary: How We Deal with Zero Actuals Has a Huge Impact on the MAPE and Optimal Forecasts
by Stephan Kolassa - 17-19 Commentary: MAPE, What Else?
by Flavio von Rickenbach - 20-22 Should We Always Use Forecasts when Facing the Future?
by Paul Goodwin - 23-24 Commentary: To Forecast or Not to Forecast?
by Fotios Petropoulos - 25-27 Commentary: When to Be Careful about Forecasting
by Stephan Kolassa - 28-29 There Is More Uncertainty than Just Demand
by Argiris Mokios - 30-31 Supply Chain Forecasting - Is the Juice Worth the Squeeze?
by Nico Sprotti - 32-33 You Think You're Measuring Accuracy?
by Stefan De Kok - 34-35 Be Kind
by Patrick Bower - 39-42 Policy Predictability: The Case of Forward Guidance by Central Banks
by Marcin Klucznik & Jakub Rybacki - 43-47 Long-term Projections of Water Supply and Demand
by Hua Xie & Claudia Ringler - 49-55 Reducing Forecast Instability with Global Deep Learning Models
by Jente Van Belle & Ruben Crevits & Wouter Verbeke - 56-57 Spotlight: Elaine Deschamps
by Foresight Staff - 58-58 Spotlight: Niles Perera
by Foresight Staff - 59-60 How to Increase Forecast Accuracy
by Stephan Kolassa - 61-62 The Impact of Large Language Models like ChatGPT on Forecasting
by Spyros Makridakis & Fotios Petropoulos & Yanfei Kang - 64-65 Comparing Artificial Intelligence and Nonlinear Regression Models: The Issue of Test Design
by Gordon Reikard - 66-66 How Overfitting Destroys Forecast Quality
by Steve Morlidge - 67-67 RAE Measures Value Added and Allows for Forecastability
by Steve Morlidge
2023, Issue 68
- 12-19 Does Improved Forecast Accuracy Translate to Business Value?
by Johann Robette - 20-24 Using Simulation to Determine When Forecast Accuracy Matters
by Stephan Kolassa - 25-30 Increased Bullwhip in Retail: A Side Effect of Improving Forecast Accuracy with More Data?
by Arnoud P. Wellens & Robert N. Boute & Maximiliano Udenio - 31-35 Measuring the Cost of Forecast Error
by Steve Morlidge - 36-39 Why Does Forecast Accuracy Matter?
by John Boylan & Aris Syntetos - 40-44 Better Forecasts or More Appropriate Stock Control Policies?
by Evangelos Theodorou & Evangelos Spilioti - 45-46 Accuracy and Usefulness in Applied Forecasting
by Sinisa Vukovic - 50-51 Why Do We Talk about Forecast Accuracy Measures (So Much)?
by Patrick Bower - 52-56 A New Approach to Business Planning during Crises
by Niels van Hove - 57-59 Commentary on "A New Approach to Business Planning during Crises"
by Vaishal Patel & George Monokroussos & Jason Chen - 60-60 Spotlight: Oyebimpe Adeniji
by Foresight Interviewer - 61-61 Spotlight: Anne-Flore Elard
by Foresight Interviewer - 62-64 Business Forecasting: Issues, Current State, and Future Direction
by Simon Clarke - 65-65 Minitutorial: Forecast Value Added
by Michael Gilliland - 66-67 Minitutorial: The Pinball Loss for Quantile Forecasts
by Stephan Kolassa
2022, Issue 67
- 8-15 To Share or Not to Share? The Future of Collaborative Forecasting
by Pierre Pinson - 16-17 Commentary on "To Share or Not to Share": Asymmetry of Data Ownership
by Niels van Hove - 18-19 Commentary on "To Share or Not to Share": Legal Ramifications and FVA of Data Sharing
by Robert Stevens - 20-21 Commentary on "To Share or Not to Share": Federated Data and Learning in the Supply Chain
by Ram Ganeshan - 22-22 Commentary on "To Share or Not to Share": Third-Party Data Providers
by Sujit Singh - 23-25 Histories of the Future by Jonathon P. Karelse
by Mark Little - 26-26 Atlas of Forecasts by Katy B?rner
by Lawrence Vanston - 27-27 Review of Data Science for Supply Chain Forecasting
by Nicolas Vandeput - 32-38 Toward a One-Number Forecast: Cross-Temporal Hierarchies
by Nikolaos Kourentzes - 39-39 Commentary on "Toward a One-Number Forecast": The Software Gap
by Simon Clarke - 40-40 Reply to Simon Clarke Commentary
by Nikolaos Kourentzes - 41-47 The IIF Forecasting Impact Podcast
by Shari De Baets & Mahdi Abolghasemi & Sarah Van Der Auweraer & Anna Sroginis & Michael Chojnowski
2022, Issue 66
- 5-10 Konfessions of a Kibitzer
by Roy Batchelor - 11-12 Batchelor Party
by Mike Gilliland & Len Tashman - 13-20 The Demand Forecasting Project at Target: Improving Collaboration and Adoption
by Mahdi R. Yousefi & Stacey Faulkenberg Larsen & Subramanian Iyer - 21-25 Making Forecasts More Trustworthy
by Simon Spavound & Nikolaos Kourentzes - 26-29 Commentary on "Making Forecasts More Trustworthy"
by Paul Goodwin & M. Sinan Gonul & Dilek Onkal - 34-37 Subsampling Seasonal Series - A Simple Approach to Forecasting Complex Patterns
by Paul Goodwin - 38-44 Long-Term Projections of Food Production and Demand
by Keith Wiebe & Timothy Sulser & Nicola Cenacchi - 45-48 A Picture Is Worth a Thousand Words: Atlas of Forecasts: Modeling and Mapping Desirable Futures by Katy B?rner
by Ira Sohn (reviewer)
2022, Issue 65
- 5-12 Representativeness: A New Criterion for Selecting Forecasts
by Fotios Petropoulos & Enno Siemsen - 13-16 Commentary on Representativeness
by Nigel Harvey & Shari De Baets - 17-22 An Extension of Possibility Distributions in Fuzzy Forecasting
by Stefan de Kok - 23-26 STR: A Flexible New Decomposition Method for Analyzing and Forecasting Complex Time Series
by Paul Goodwin - 27-29 More Thoughts on STR
by Stephan Kolassa - 34-38 One-Number Forecasting: A Solution for Silo Behavior?
by Simon Clarke - 39-40 Commentary: One-Number Forecast: How Will It Be Used?
by Richard Herrin - 41-47 The UFO Project (Usage of Forecasting in Organizations): Final Survey Results
by Jim Hoover & Len Tashman
2022, Issue 64
- 4-8 Advances in Intermittent-Demand Forecasting
by John Boylan & Aris Syntetos - 9-11 Intermittent Demand Forecasting: Context, Methods and Applications (2021) by John Boylan and Aris Syntetos
by Jim Hoover - 12-15 Commentary on Intermittent Demand Forecasting: Let's Look Next at Dynamics!
by Stephan Kolassa - 16-17 Reply to Stephan Kolassa Commentary
by John Boylan & Aris Syntetos - 18-18 Forecasters in the Field
by Foresight Editor Len Tashman - 19-25 Into the (Largely) Unknown, Part 2: Uses of Fuzzy Forecasting
by Steve Morlidge & Paul Goodwin - 30-44 Decision Trees for Time-Series Forecasting
by Evangelos Spiliotis - 45-48 Decision Trees in Automatic Forecasting Algorithms: The Implementation in Forecast Pro
by Sarah Darin
2021, Issue 63
- 7-11 Noise: A Flaw in Human Judgment
by Stephan Kolassa & Len Tashman - 12-13 Can Biases and Heuristics Be Unconscious?
by Christopher Plummer - 14-20 Into the (Largely) Unknown: A Simple Way to Handle Uncertainty
by Steve Morlidge & Paul Goodwin - 21-24 Can We Reconcile Narrativist and Probabilistic Modes of Thinking?
by Philip E. Tetlock & J. Peter Scoblic - 29-35 The Impact of COVID-19 on the Economy and Strategic Environment of the United States: A Review of Two New Studies
by Ira Sohn - 36-45 Beyond Error Measures to the Utility and Cost of the Forecasts
by Elizabeth Yardley & Fotios Petropoulos - 46-52 Integrated Business Planning: A New Narrative for an Old Process
by Niels van Hove & Hein Regeer
2021, Issue 62
- 4-7 Resurrecting Retail: The Future of Business in a Post-Pandemic World by Doug Stephens
by Stephan Kolassa - 8-13 Forecasting Demand during COVID-The Case of Wayfair
by Alexei Alexandrov & Philip Brooks & I-Chen Lee & George Monokroussos - 14-21 Strategy in Uncertain Times: Lenses to Approach Decision Making, Forecasting, and Planning
by Chris Turner - 27-32 A Better Crystal Ball: The Right Way to Think About the Future
by J. Peter Scoblic & Philip E. Tetlock - 33-35 Scenarios and Probabilities: Incompatible or Complementary?
by Paul Goodwin - 36-39 Risk vs. Uncertainty
by Steve Morlidge - 40-42 Scenarios with Probabilities for Financial Forecasting
by Roy Batchelor - 43-46 Probabilistic Scenarios in Demand and Supply Planning
by Stefan De Kok - 47-49 Uncertainty Is the Human Condition
by Mike Tremblay - 50-51 Near-Term Questions for Long-Term Uncertainties
by Robert Fildes
2021, Issue 61
- 5-14 Mitigating Unconscious Bias in Forecasting
by Jonathon Karelse - 15-17 Commentary: The Case for Parsimonious Intervention
by Paul Goodwin - 18-19 Commentary: Cross-Disciplinary Approaches to Supply-Chain Issues
by Jeff Baker - 20-23 The Great Toilet Paper Buy: Lessons for the Supply Chain
by Tonya Boone & Ram Ganeshan - 28-35 Combining Humans and Machines in an Emerging Form of Enterprise: the Humachine
by Nada Sanders & John Wood - 36-38 Commentary: AI Is Here to Automate the Knowledge Worker
by Niels van Hove - 39-40 Commentary: ML Must Be Used with Care
by David Orrell - 41-44 Commentary: A Brief Historical Perspective on Integrating New Technology
by Ken Fordyce - 45-48 The Data Detective: Ten Easy Rules to Make Sense of Statistics by Tim Harford
by Ira Sohn
2021, Issue 60
- 5-7 How to Harness the Wisdom of Crowds
by Paul Goodwin - 8-15 Maximizing Forecast Value Added through Machine Learning and "Nudges"
by Jeff Baker - 16-17 Commentary: Managing FVA
by Robert Fildes - 18-19 Commentary: Another Role for ML in Forecasting
by Michael Gilliland - 20-24 A Peek at the Next Century: Population Projections to 2100 and Their Economic and Geopolitical Consequences
by Ira Sohn - 28-32 Can We Profit from Trading on Predictions of High-Low Stock Prices?
by Clive Jones - 33-37 The M5 Competition and the Future of Human Expertise in Forecasting
by Spyros Makridakis & Evangelos Spiliotis - 38-38 Commentary: We'll Still Need Expertise
by Stephan Kolassa - 39-39 Commentary: Will the Value of Forecasting Knowledge and Experience Diminish?
by Simon Clarke - 40-41 Commentary: The M5 Competition: A Critical Appraisal
by Tim Januschowski & Jan Gasthaus & Yuyang Wang - 42-42 Commentary: The M5 and the Future Role of Expertise
by Michael Gilliland - 43-43 Commentary: Academicians and Practitioners Will Thrive
by Lawrence Vanston - 44-44 Reply to the Commentaries
by Spyros Makridakis & Evangelos Spiliotos - 45-48 The UFO Project: Initial Survey Results
by Jim Hoover & UFO Project Team
2020, Issue 59
- 5-15 A Modern Retail Forecasting System in Production
by Phillip Yelland - 16-19 Commentary: It's the Soft Problems that Are Hard to Overcome
by Simon Clarke - 20-25 Response to Commentary of Simon Clarke
by Phillip Yelland & Zeynep Erkin Baz - 29-31 After Shock: The World's Foremost Futurists Reflect on 50 Years of Future Shock
by Ira Sohn - 32-37 Dealing with "Deepfakes": How Synthetic Media Will Distort Reality, Corrupt Data, and Impact Forecasts
by John Wood & Nada Sanders - 38-44 U.S. Presidential Election Forecasting: The Economist Model
by Colin Lewis-Beck & Michael Lewis-Beck - 45-56 The Benefits of Systematic Forecasting for Organizations: The UFO Project
by Spyros Makridakis & Ellen Bonnell & Simon Clarke & Robert Fildes & Mike Gilliland & Jim Hoover & Len Tashman
2020, Issue 58
- 4-6 Hello World: How to Be Human in the Age of the Machine by Hannah Fry
by Shari De Baets - 7-14 How to Choose among Three Forecasting Methods: Machine Learning, Statistical Models, and Judgmental Forecasts
by Yue Li & Diane Berry & Jason Lee - 15-16 Commentary on "How to Choose among Three Forecasting Methods: Machine Learning, Statistical Models, and Judgmental Forecasts"
by Stephan Kolassa - 17-23 The M5: A Preview from Prior Competitions
by Casper Bojer & Jens Peder Meldgaard - 27-35 Medical Errors in the Age of the Intelligent Machine
by Michael Tremblay - 36-41 How Stagger Charts Can Improve Forecast Accuracy
by Agneta Ramosaj & Marino Widmer - 42-42 Commentary: Another Use of the Stagger Chart
by Mike Gilliland - 43-48 Technology Support in Business Planning: Automation, Augmentation, and Human Centricity
by Niels van Hove
2020, Issue 57
- 5-10 The M4 Forecasting Competition-Takeaways for the Practitioner
by Michael Gilliland - 11-12 Commentary: The M4 Competition and a Look to the Future
by Fotios Petropoulos - 13-18 Will Deep and Machine Learning Solve Our Forecasting Problems?
by Stephan Kolassa - 19-20 Interview with Tim Januschowski, Manager, Machine Learning Science at Amazon Web Services
by Len Tashman - 21-23 Two Cheers for Rebooting AI: Building Artificial Intelligence We Can Trust
by Stephan Kolassa - 27-38 Developing a Modern Retail Forecasting System: People and Processes
by Phillip Yelland & Zeynep Erkin Baz - 39-45 Environmental Conundrum-Projections to 2050
by Ira Sohn
2020, Issue 56
- 7-9 Could These Recent Findings Improve Your Judgmental Forecasts?
by Paul Goodwin - 10-17 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
by Thanos Goltsos & Aris SyntetoS - 18-19 Commentary: Why Is Forecasting for Remanufacturing Hard?
by Ram Ganeshan - 20-25 Monitoring Forecast Models Using Control Charts
by Joseph H. Katz - 30-35 Smarter Supply Chains through AI
by Duncan Klett - 36-45 Strategic IBP: Driving Profitable Growth in Complex Global Organizations
by Dean Sorensen - 46-47 Commentary on Strategic IBP
by Pete Alle - 48-48 Response to Pete Alle's Commentary
by Dean Sorensen
2019, Issue 55
- 10-18 Forecasting at Scale: The Architecture of a Modern Retail Forecasting System
by Phillip Yelland & Zeynep Erkin Baz & David Serafini - 19-19 Interview with Dr. Phillip Yelland
by Foresight Staff - 20-26 Open-Source Forecasting Tools in Python
by Tim Januschowski & Jan Gasthaus & Yuyang Wang - 31-34 Autonomous or "Lights Out" Supply-Chain Planning: What New Technology Is Required
by Niels van Hove