Demand-Driven Forecasting - A Structured Approach to Forecasting

Informationen zum Autor CHARLES W. CHASE JR. is the Chief Industry Consultant in SAS's Manufacturing & Supply Chain Global Practice, where he is the principal architect and strategist for delivering demand planning and forecasting solutions to improve SAS customers' supply chain efficiencies. He has more than twenty-six years of experience in the consumer packaged goods industry, and is an expert in sales forecasting, market response modeling, econometrics, and supply chain management. Klappentext An updated new edition of the comprehensive guide to better business forecastingMany companies still look at quantitative forecasting methods with suspicion, but a new awareness is emerging across many industries as more businesses and professionals recognize the value of integrating demand data (point-of-sale and syndicated scanner data) into the forecasting process. Demand-Driven Forecasting equips you with solutions that can sense, shape, and predict future demand using highly sophisticated methods and tools. From a review of the most basic forecasting methods to the most advanced and innovative techniques in use today, this guide explains demand-driven forecasting, offering a fundamental understanding of the quantitative methods used to sense, shape, and predict future demand within a structured process. Offering a complete overview of the latest business forecasting concepts and applications, this revised Second Edition of Demand-Driven Forecasting is the perfect guide for professionals who need to improve the accuracy of their sales forecasts.* Completely updated to include the very latest concepts and methods in forecasting* Includes real case studies and examples, actual data, and graphical displays and tables to illustrate how effective implementation works* Ideal for CEOs, CFOs, CMOs, vice presidents of supply chain, vice presidents of demand forecasting and planning, directors of demand forecasting and planning, supply chain managers, demand planning managers, marketing analysts, forecasting analysts, financial managers, and any other professional who produces or contributes to forecastsAccurate forecasting is vital to success in today's challenging business climate. Demand-Driven Forecasting offers proven and effective insight on making sure your forecasts are right on the money. Zusammenfassung From a review of basic forecasting methods to the advanced and innovative techniques in use today, this book offers a fundamental understanding of the quantitative methods used to sense, shape, and predict future demand within a structured process. It is suitable for professionals who need to improve the accuracy of their sales forecasts. Inhaltsverzeichnis Foreword xi Preface xv Acknowledgments xix About the Author xx Chapter 1 Demystifying Forecasting: Myths versus Reality 1 Data Collection, Storage, and Processing Reality 5 Art-of-Forecasting Myth 8 End-Cap Display Dilemma 10 Reality of Judgmental Overrides 11 Oven Cleaner Connection 13 More Is Not Necessarily Better 16 Reality of Unconstrained Forecasts, Constrained Forecasts, and Plans 17 Northeast Regional Sales Composite Forecast 21 Hold-and-Roll Myth 22 The Plan that Was Not Good Enough 23 Package to Order versus Make to Order 25 "Do You Want Fries with That?" 26 Summary 28 Notes 28 Chapter 2 What Is Demand-Driven Forecasting? 31 Transitioning from Traditional Demand Forecasting 33 What's Wrong with The Demand-Generation Picture? 34 Fundamental Flaw with Traditional Demand Generation 37 Relying Solely on a Supply-Driven Strategy Is Not the Solution 39 What Is Demand-Driven Forecasting? 40 What Is Demand Sensing and Shaping? 41 Changing the Demand Management Process Is Essential 57 Communication Is Key 65 Mea...

List of contents

Foreword xi
 
Preface xv
 
Acknowledgments xix
 
About the Author xx
 
Chapter 1 Demystifying Forecasting: Myths versus Reality 1
 
Data Collection, Storage, and Processing Reality 5
 
Art-of-Forecasting Myth 8
 
End-Cap Display Dilemma 10
 
Reality of Judgmental Overrides 11
 
Oven Cleaner Connection 13
 
More Is Not Necessarily Better 16
 
Reality of Unconstrained Forecasts, Constrained Forecasts, and Plans 17
 
Northeast Regional Sales Composite Forecast 21
 
Hold-and-Roll Myth 22
 
The Plan that Was Not Good Enough 23
 
Package to Order versus Make to Order 25
 
"Do You Want Fries with That?" 26
 
Summary 28
 
Notes 28
 
Chapter 2 What Is Demand-Driven Forecasting? 31
 
Transitioning from Traditional Demand Forecasting 33
 
What's Wrong with The Demand-Generation Picture? 34
 
Fundamental Flaw with Traditional Demand Generation 37
 
Relying Solely on a Supply-Driven Strategy Is Not the Solution 39
 
What Is Demand-Driven Forecasting? 40
 
What Is Demand Sensing and Shaping? 41
 
Changing the Demand Management Process Is Essential 57
 
Communication Is Key 65
 
Measuring Demand Management Success 67
 
Benefits of a Demand-Driven Forecasting Process 68
 
Key Steps to Improve the Demand
 
Management Process 70
 
Why Haven't Companies Embraced the Concept of Demand-Driven? 71
 
Summary 74
 
Notes 75
 
Chapter 3 Overview of Forecasting Methods 77
 
Underlying Methodology 79
 
Different Categories of Methods 83
 
How Predictable Is the Future? 88
 
Some Causes of Forecast Error 91
 
Segmenting Your Products to Choose the Appropriate Forecasting Method 94
 
Summary 101
 
Note 101
 
Chapter 4 Measuring Forecast Performance 103
 
"We Overachieved Our Forecast, So Let's Party!" 105
 
Purposes for Measuring Forecasting Performance 106
 
Standard Statistical Error Terms 107
 
Specific Measures of Forecast Error 111
 
Out-of-Sample Measurement 115
 
Forecast Value Added 118
 
Summary 122
 
Notes 123
 
Chapter 5 Quantitative Forecasting Methods Using Time Series Data 125
 
Understanding the Model-Fitting Process 127
 
Introduction to Quantitative Time Series Methods 130
 
Quantitative Time Series Methods 135
 
Moving Averaging 136
 
Exponential Smoothing 142
 
Single Exponential Smoothing 143
 
Holt's Two-Parameter Method 147
 
Holt's-Winters' Method 149
 
Winters' Additive Seasonality 151
 
Summary 156
 
Notes 158
 
Chapter 6 Regression Analysis 159
 
Regression Methods 160
 
Simple Regression 160
 
Correlation Coefficient 163
 
Coefficient of Determination 165
 
Multiple Regression 166
 
Data Visualization Using Scatter Plots and Line Graphs 170
 
Correlation Matrix 173
 
Multicollinearity 175
 
Analysis of Variance 178
 
F-test 178
 
Adjusted R2 180
 
Parameter Coefficients 181
 
t-test 184
 
P-values 185
 
Variance Inflation Factor 186
 
Durbin-Watson Statistic 187
 
Intervention Variables (or Dummy Variables) 191
 
Regression Model Results 197
 
Key Activities in Building a Multiple Regression Model 199
 
Cautions about Regression Models 201
 
Summary 201
 
Notes 202
 
Chapter 7 ARIMA Models 2

Product details

• Authors: Chase, Charles W Chase, Charles W. Chase, Cw Chase, Chase Charles W.
• Publisher: Wiley, John and Sons Ltd
• Languages: English
• Product format: Hardback
• Released: 04.10.2013
• EAN: 9781118669396
• ISBN: 978-1-118-66939-6
• No. of pages: 384
• Series: SAS Institute Inc; Wiley and SAS Business Series; Wiley and SAS Business; SAS Institute Inc; Wiley and SAS Business Series; Wiley & SAS Business
• Subjects: Social sciences, law, business > Business > Management; Strategisches Management, Business & management, Strategic management, Wirtschaft u. Management