Next Generation Demand Management: People, Process, Analytics, and Technology(Wiley and SAS Business Series)

A practical framework for revenue-boosting supply chain management Next Generation Demand Management is a guidebook to next generation Demand Management, with an implementation framework that improves revenue forecasts and enhances profitability. This proven approach is structured around the four key catalysts of an efficient planning strategy: people, processes, analytics, and technology. The discussion covers the changes in behavior, skills, and integrated processes that are required for proper implementation, as well as the descriptive and predictive analytics tools and skills that make the process sustainable. Corporate culture changes require a shift in leadership focus, and this guide describes the necessary "champion" with the authority to drive adoption and stress accountability while focusing on customer excellence. Real world examples with actual data illustrate important concepts alongside case studies highlighting best-in-class as well as startup approaches. Reliable forecasts are the primary product of demand planning, a multi-step operational supply chain management process that is increasingly seen as a survival tactic in the changing marketplace. This book provides a practical framework for efficient implementation, and complete guidance toward the supplementary changes required to reap the full benefit. Learn the key principles of demand driven planning Implement new behaviors, skills, and processes Adopt scalable technology and analytics capabilities Align inventory with demand, and increase channel profitability Whether your company is a large multinational or an early startup, your revenue predictions are only as strong as your supply chain management system. Implementing a proven, more structured process can be the catalyst your company needs to overcome that one lingering obstacle between forecast and goal. Next Generation Demand Management gives you the framework for building the foundation of your growth.

Table of Contents:
Foreword xiii Preface xv Acknowledgments xxi About the Author xxiii Chapter 1 The Current State 1 Why Demand Management Matters More Than Ever 4 Current Challenges and Opportunities 14 Primary Obstacles to Achieving Demand Management Planning Goals 21 Why Do Companies Continue to Dismiss the Value of Demand Management? 23 Summary 28 Key Learnings 29 Notes 30 Further Reading 30 Chapter 2 The Journey 31 Starting the Supply Chain Journey 32 Introducing Sales & Operations Planning (S&OP) into the Supply Chain Journey 34 Sales & Operations Planning Connection 34 Transitioning to a Demand-Driven Supply Chain 40 The Digitalization of the Supply Chain 46 Leveraging New Scalable Technology 51 Benefits 52 Summary 53 Key Learnings 54 Notes 57 Chapter 3 The Data 59 What Is Big Data? 60 Why Is Downstream Data Important? 68 Demand Management Data Challenges 71 CPG Company Case Study 75 Does Demand History Really Need to Be Cleansed? 78 How Much Data Should Be Used? 81 Demand-Signal Repositories 82 What Is Demand Signal Analytics? 86 Demand Signal Analytics Key Benefits 87 Summary 89 Key Learnings 91 Notes 92 Further Reading 93 Chapter 4 The Process 95 Centers of Forecasting Excellence 97 Demand Management Champion 99 Demand-Driven Planning 100 What Is Demand Sensing and Shaping? 100 A New Paradigm Shift 113 Large-Scale Automatic Hierarchical Forecasting 115 Transactional Data 116 Time Series Data 117 Forecasting Models 117 Skill Requirements 120 Summary 121 Key Learnings 123 Further Reading 125 Chapter 5 Performance Metrics 127 Why MAPE Is Not Always the Best Metric 128 Why In-Sample/Out-of-Sample Measurement Is So Important 131 Forecastability 135 Forecast Value Added 137 Ho: Your Forecasting Process Has No Effect 138 Summary 144 Key Learnings 145 Notes 146 Further Reading 146 Chapter 6 The Analytics 147 Underlying Fundaments of Statistical Models 148 How Predictable Is the Future? 153 Importance of Segmentation of Your Products 157 Consumption-Based Modeling 167 Consumption-Based Modeling Using Multi-Tiered Causal Analysis 168 Consumption-Based Modeling Case Study 170 Summary 179 Key Learnings 180 Notes 181 Further Reading 181 Chapter 7 The Demand Planning Brief 183 Demand Planning Brief 186 Overview 187 Background 188 Recommended Forecast Methodology 188 Model Hierarchy 190 Model Selection Criteria 190 Supporting Information 192 Analytic Snapshot 194 Model Selection and Interpretation 199 Scenario Analysis 205 Summary 212 Key Learnings 213 Chapter 8 The Strategic Roadmap 215 Current State versus Future State 216 Current State 223 Future State 226 Gaps and Interdependencies 237 Strategic Roadmap 245 Summary 252 Index 253

About the Author :
CHARLES W. CHASE is an advisory industry consultant at SAS and the principal solutions architect and thought leader for delivering demand planning and forecasting solutions to improve supply chain efficiencies for SAS customers. He is the author of Demand-Driven Forecasting, Second Edition, and coauthor of Bricks Matter, both by Wiley.