Business Forecasting: The Emerging Role of Artificial Intelligence and Machine Learning

ISBN-13: 9781119782476 / Angielski / Twarda / 2021 / 432 str.

Michael Gilliland; Len Tashman; Udo Sglavo

Spis treści

Foreword (Spyros Makridakis and Fotios Petropoulos) xiPreface (Michael Gilliland, Len Tashman, and Udo Sglavo) xvState of the Art 1Forecasting in Social Settings: The State of the Art (Spyros Makridakis, Rob J. Hyndman, and Fotios Petropoulos) 1Chapter 1 Artificial Intelligence and Machine Learning in Forecasting 311.1 Deep Learning for Forecasting (Tim Januschowski and colleagues) 321.2 Deep Learning for Forecasting: Current Trends and Challenges (Tim Januschowski and Colleagues) 411.3 Neural Network--Based Forecasting Strategies (Steven Mills and Susan Kahler) 481.4 Will Deep and Machine Learning Solve Our Forecasting Problems? (Stephan Kolassa) 651.5 Forecasting the Impact of Artificial Intelligence: The Emerging and Long-Term Future (Spyros Makridakis) 72Commentary: Spyros Makridakis's Article "Forecasting The Impact Of Artificial Intelligence" (Owen Davies) 801.6 Forecasting the Impact of Artificial Intelligence: Another Voice (Lawrence Vanston) 84Commentary: Response to Lawrence Vanston (Spyros Makridakis) 921.7 Smarter Supply Chains through AI (Duncan Klett) 941.8 Continual Learning: The Next Generation of Artificial Intelligence (Daniel Philps) 1031.9 Assisted Demand Planning Using Machine Learning (Charles Chase) 1101.10 Maximizing Forecast Value Add through Machine Learning and Behavioral Economics (Jeff Baker) 1151.11 The M4 Forecasting Competition -- Takeaways for the Practitioner (Michael Gilliland) 124Commentary --The M4 Competition and a Look to the Future (Fotios Petropoulos) 132Chapter 2 Big Data in Forecasting 1352.1 Is Big Data the Silver Bullet for Supply-Chain Forecasting? (Shaun Snapp) 136Commentary: Becoming Responsible Consumers of Big Data (Chris Gray) 142Commentary: Customer versus Item Forecasting (Michael Gilliland) 146Commentary: Big Data or Big Hype? (Stephan Kolassa) 148Commentary: Big Data, a Big Decision (Niels van Hove) 150Commentary: Big Data and the Internet of Things (Peter Catt) 1522.2 How Big Data Could Challenge Planning Processes across the Supply Chain (Tonya Boone, Ram Ganeshan, and Nada Sanders) 155Chapter 3 Forecasting Methods: Modeling, Selection, and Monitoring 1633.1 Know Your Time Series (Stephan Kolassa and Enno Siemsen) 1643.2 A Classification of Business Forecasting Problems (Tim Januschowski and Stephan Kolassa) 1713.3 Judgmental Model Selection (Fotios Petropoulos) 181Commentary: A Surprisingly Useful Role for Judgment (Paul Goodwin) 192Commentary: Algorithmic Aversion and Judgmental Wisdom (Nigel Harvey) 194Commentary: Model Selection in Forecasting Software (Eric Stellwagen) 195Commentary: Exploit Information from the M4 Competition (Spyros Makridakis) 1973.4 A Judgment on Judgment (Paul Goodwin) 1983.5 Could These Recent Findings Improve Your Judgmental Forecasts? (Paul Goodwin) 2073.6 A Primer on Probabilistic Demand Planning (Stefan de Kok) 2113.7 Benefits and Challenges of Corporate Prediction Markets (Thomas Wolfram) 2153.8 Get Your CoV On . . . (Lora Cecere) 2253.9 Standard Deviation Is Not the Way to Measure Volatility (Steve Morlidge) 2303.10 Monitoring Forecast Models Using Control Charts (Joe Katz) 2323.11 Forecasting the Future of Retail Forecasting (Stephan Kolassa) 243 Commentary (Brian Seaman) 255Chapter 4 Forecasting Performance 2594.1 Using Error Analysis to Improve Forecast Performance (Steve Morlidge) 2604.2 Guidelines for Selecting a Forecast Metric (Patrick Bower) 2714.3 The Quest for a Better Forecast Error Metric: Measuring More Than the Average Error (Stefan de Kok) 2774.4 Beware of Standard Prediction Intervals from Causal Models (Len Tashman) 290Chapter 5 Forecasting Process: Communication, Accountability, and S&OP 2975.1 Not Storytellers But Reporters (Steve Morlidge) 2985.2 Why Is It So Hard to Hold Anyone Accountable for the Sales Forecast? (Chris Gray) 3035.3 Communicating the Forecast: Providing Decision Makers with Insights (Alec Finney) 3105.4 An S&OP Communication Plan: The Final Step in Support of Company Strategy (Niels van Hove) 3175.5 Communicating Forecasts to the C-Suite: A Six-Step Survival Guide (Todd Tomalak) 3255.6 How to Identify and Communicate Downturns in Your Business (Larry Lapide) 3315.7 Common S&OP Change Management Pitfalls to Avoid (Patrick Bower) 3385.8 Five Steps to Lean Demand Planning (John Hellriegel) 3425.9 The Move to Defensive Business Forecasting (Michael Gilliland) 346Afterwords: Essays on Topics in Business Forecasting 351Observations from a Career Practitioner: Keys to Forecasting Success (Carolyn Allmon) 351Demand Planning as a Career (Jason Breault) 354How Did We Get Demand Planning So Wrong? (Lora Cecere) 357Business Forecasting: Issues, Current State, and Future Direction (Simon Clarke) 358Statistical Algorithms, Judgment and Forecasting Software Systems (Robert Fildes) 361The > for Forecasting (Igor Gusakov) 364The Future of Forecasting Is Artificial Intelligence Combined with Human Forecasters (Jim Hoover) 367Quantile Forecasting with Ensembles and Combinations (Rob J. Hyndman) 371Managing Demand for New Products (Chaman L. Jain) 376Solving for the Irrational: Why Behavioral Economics Is the Next Big Idea in Demand Planning (Jonathon Karelse) 380Business Forecasting in Developing Countries (Bahman Rostami-Tabar) 382Do the Principles of Analytics Apply to Forecasting? (Udo Sglavo) 387Groupthink on the Topic of AI/ML for Forecasting (Shaun Snapp) 390Taking Demand Planning Skills to the Next Level (Nicolas Vandeput) 392Unlock the Potential of Business Forecasting (Eric Wilson) 394Building a Demand Plan Story for S&OP: The Business Value of Analytics (Dr. Davis Wu) 396About the Editors 401Index 403

O autorze

MICHAEL GILLILAND is Marketing Manager for SAS forecasting software and Associate Editor of Foresight: The International Journal of Applied Forecasting. He is author of The Business Forecasting Deal.LEN TASHMAN is the founding editor of Foresight: The International Journal of Applied Forecasting. He is emeritus professor of business administration at the University of Vermont and Director of the Center for Business Forecasting.UDO SGLAVO is Vice President of Analytics R&D at SAS and holds several patents in the area of advanced analytics. His writings have appeared in Analytics magazine and the book Big Data and Business Analytics.