Next Generation Demand Management

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.

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