Business forecasting : the emerging role of artificial intelligence and machine learning /: the emerging role of artificial intelligence and machine learning. (2021)

• Record Type: Book
• Further Information: Note: Michael Gilliland, Len Tashman, Udo Sglavo.
• Authors: Gilliland, Michael; Tashman, Len, 1942-; Sglavo, Udo, 1968-
• Contents: Foreword ix Preface xiii State Of The Art xvii Forecasting in Social Settings: The State of the Art xvii Chapter 1 Artificial Intelligence and Machine Learning in Forecasting 1 1.1 Deep Learning for Forecasting 2 1.2 Deep Learning for Forecasting: Current Trends and Challenges 11 1.3 Neural Network–Based Forecasting Strategies 18 1.4 Will Deep and Machine Learning Solve Our Forecasting Problems? 35 1.5 Forecasting the Impact of Artificial Intelligence: The Emerging and Long-Term Future 42 1.6 Forecasting the Impact of Artificial Intelligence: Another Voice 54 1.7 Smarter Supply Chains through AI 64 1.8 Continual Learning: The Next Generation of Artificial Intelligence 73 1.9 Assisted Demand Planning Using Machine Learning 80 1.10 Maximizing Forecast Value Add through Machine Learning and Behavioral Economics 85 1.11 The M4 Forecasting Competition – Takeaways for the Practitioner 94 Chapter 2 Big Data in Forecasting 105 2.1 Is Big Data the Silver Bullet for Supply-Chain Forecasting? 106 2.2 How Big Data Could Challenge Planning Processes across the Supply Chain 125 Chapter 3 Forecasting Methods: Modeling, Selection, and Monitoring 133 3.1 Know Your Time Series 134 3.2 A Classification of Business Forecasting Problems 141 3.3 Judgmental Model Selection 151 3.4 A Judgment on Judgment 168 3.5 Could These Recent Findings Improve Your Judgmental Forecasts? 177 3.6 A Primer on Probabilistic Demand Planning 181 3.7 Benefits and Challenges of Corporate Prediction Markets 185 3.8 Get Your CoV On . . . 195 3.9 Standard Deviation Is Not the Way to Measure Volatility 200 3.10 Monitoring Forecast Models Using Control Charts 202 3.11 Forecasting the Future of Retail Forecasting 213 Chapter 4 Forecasting Performance 229 4.1 Using Error Analysis to Improve Forecast Performance 230 4.2 Guidelines for Selecting a Forecast Metric 241 4.3 The Quest for a Better Forecast Error Metric: Measuring More Than the Average Error 247 4.4 Beware of Standard Prediction Intervals from Causal Models 260 Chapter 5 Forecasting Process: Communication, Accountability, and S&OP 267 5.1 Not Storytellers But Reporters 268 5.2 Why Is It So Hard to Hold Anyone Accountable for the Sales Forecast? 273 5.3 Communicating the Forecast: Providing Decision Makers with Insights 280 5.4 An S&OP Communication Plan: The Final Step in Support of Company Strategy 287 5.5 Communicating Forecasts to the C-Suite: A Six-Step Survival Guide 295 5.6 How to Identify and Communicate Downturns in Your Business 301 5.7 Common S&OP Change Management Pitfalls to Avoid 308 5.8 Five Steps to Lean Demand Planning 312 5.9 The Move to Defensive Business Forecasting 316 About the Editors 321 Afterwords 323 Index 373
• Edition: 1st
• Publisher Details: Hoboken : John Wiley & Sons, Inc
• Publication Date: 2021
• Extent: 1 online resource
• Subjects: 658.40355; Business forecasting; Artificial intelligence -- Industrial applications
• Languages: English
• ISBNs: 9781119782582
• Related ISBNs: 9781119782476
• Notes: Note: Description based on CIP data; resource not viewed.
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
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