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Demand-Driven Forecasting: A Structured Approach to Forecasting, 2nd Edition

Book Description

An updated new edition of the comprehensive guide to better business forecasting

Many 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 forecasts

Accurate 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.

Table of Contents

  1. Cover
  2. Series
  3. Title Page
  4. Copyright
  5. Foreword
    1. A JOURNEY DOWN MEMORY LANE
    2. QUALIFIED TO DEFINE DEMAND-DRIVEN FORECASTING
    3. PRIMER ON ADVANCED FORECASTING
  6. Preface
    1. NEW IN THIS EDITION
    2. UNIQUE FEATURES
  7. Acknowledgments
  8. About the Author
  9. Chapter 1: Demystifying Forecasting: Myths versus Reality
    1. DATA COLLECTION, STORAGE, AND PROCESSING REALITY
    2. ART-OF-FORECASTING MYTH
    3. END-CAP DISPLAY DILEMMA
    4. REALITY OF JUDGMENTAL OVERRIDES
    5. OVEN CLEANER CONNECTION
    6. MORE IS NOT NECESSARILY BETTER
    7. REALITY OF UNCONSTRAINED FORECASTS, CONSTRAINED FORECASTS, AND PLANS
    8. NORTHEAST REGIONAL SALES COMPOSITE FORECAST
    9. HOLD-AND-ROLL MYTH
    10. THE PLAN THAT WAS NOT GOOD ENOUGH
    11. PACKAGE TO ORDER VERSUS MAKE TO ORDER
    12. “DO YOU WANT FRIES WITH THAT?”
    13. SUMMARY
    14. NOTES
  10. Chapter 2: What Is Demand-Driven Forecasting?
    1. TRANSITIONING FROM TRADITIONAL DEMAND FORECASTING
    2. WHAT'S WRONG WITH THE DEMAND-GENERATION PICTURE?
    3. FUNDAMENTAL FLAW WITH TRADITIONAL DEMAND GENERATION
    4. RELYING SOLELY ON A SUPPLY-DRIVEN STRATEGY IS NOT THE SOLUTION
    5. WHAT IS DEMAND-DRIVEN FORECASTING?
    6. WHAT IS DEMAND SENSING AND SHAPING?
    7. CHANGING THE DEMAND MANAGEMENT PROCESS IS ESSENTIAL
    8. COMMUNICATION IS KEY
    9. MEASURING DEMAND MANAGEMENT SUCCESS
    10. BENEFITS OF A DEMAND-DRIVEN FORECASTING PROCESS
    11. KEY STEPS TO IMPROVE THE DEMAND MANAGEMENT PROCESS
    12. WHY HAVEN'T COMPANIES EMBRACED THE CONCEPT OF DEMAND-DRIVEN?
    13. SUMMARY
    14. NOTES
  11. Chapter 3: Overview of Forecasting Methods
    1. UNDERLYING METHODOLOGY
    2. DIFFERENT CATEGORIES OF METHODS
    3. HOW PREDICTABLE IS THE FUTURE?
    4. SOME CAUSES OF FORECAST ERROR
    5. SEGMENTING YOUR PRODUCTS TO CHOOSE THE APPROPRIATE FORECASTING METHOD
    6. SUMMARY
    7. NOTE
  12. Chapter 4: Measuring Forecast Performance
    1. “WE OVERACHIEVED OUR FORECAST, SO LET'S PARTY!”
    2. PURPOSES FOR MEASURING FORECASTING PERFORMANCE
    3. STANDARD STATISTICAL ERROR TERMS
    4. SPECIFIC MEASURES OF FORECAST ERROR
    5. OUT-OF-SAMPLE MEASUREMENT
    6. FORECAST VALUE ADDED
    7. SUMMARY
    8. NOTES
  13. Chapter 5: Quantitative Forecasting Methods Using Time Series Data
    1. UNDERSTANDING THE MODEL-FITTING PROCESS
    2. INTRODUCTION TO QUANTITATIVE TIME SERIES METHODS
    3. QUANTITATIVE TIME SERIES METHODS
    4. MOVING AVERAGING
    5. EXPONENTIAL SMOOTHING
    6. SINGLE EXPONENTIAL SMOOTHING
    7. HOLT'S TWO-PARAMETER METHOD
    8. HOLT'S-WINTERS' METHOD
    9. WINTERS' ADDITIVE SEASONALITY
    10. SUMMARY
    11. NOTES
  14. Chapter 6: Regression Analysis
    1. REGRESSION METHODS
    2. SIMPLE REGRESSION
    3. CORRELATION COEFFICIENT
    4. COEFFICIENT OF DETERMINATION
    5. MULTIPLE REGRESSION
    6. DATA VISUALIZATION USING SCATTER PLOTS AND LINE GRAPHS
    7. CORRELATION MATRIX
    8. MULTICOLLINEARITY
    9. ANALYSIS OF VARIANCE
    10. F-TEST
    11. ADJUSTED R2
    12. PARAMETER COEFFICIENTS
    13. t-TEST
    14. P-VALUES
    15. VARIANCE INFLATION FACTOR
    16. DURBIN-WATSON STATISTIC
    17. INTERVENTION VARIABLES (OR DUMMY VARIABLES)
    18. REGRESSION MODEL RESULTS
    19. KEY ACTIVITIES IN BUILDING A MULTIPLE REGRESSION MODEL
    20. CAUTIONS ABOUT REGRESSION MODELS
    21. SUMMARY
    22. NOTES
  15. Chapter 7: ARIMA Models
    1. PHASE 1: IDENTIFYING THE TENTATIVE MODEL
    2. PHASE 2: ESTIMATING AND DIAGNOSING THE MODEL PARAMETER COEFFICIENTS
    3. PHASE 3: CREATING A FORECAST
    4. SEASONAL ARIMA MODELS
    5. BOX-JENKINS OVERVIEW
    6. EXTENDING ARIMA MODELS TO INCLUDE EXPLANATORY VARIABLES
    7. TRANSFER FUNCTIONS
    8. NUMERATORS AND DENOMINATORS
    9. RATIONAL TRANSFER FUNCTIONS
    10. ARIMA MODEL RESULTS
    11. SUMMARY
    12. NOTES
  16. Chapter 8: Weighted Combined Forecasting Methods
    1. WHAT IS WEIGHTED COMBINED FORECASTING?
    2. DEVELOPING A VARIANCE WEIGHTED COMBINED FORECAST
    3. GUIDELINES FOR THE USE OF WEIGHTED COMBINED FORECASTS
    4. SUMMARY
    5. NOTES
  17. Chapter 9: Sensing, Shaping, and Linking Demand to Supply: A Case Study Using MTCA
    1. LINKING DEMAND TO SUPPLY USING MULTI-TIERED CAUSAL ANALYSIS
    2. CASE STUDY: THE CARBONATED SOFT DRINK STORY
    3. SUMMARY
    4. APPENDIX 9A CONSUMER PACKAGED GOODS TERMINOLOGY
    5. APPENDIX 9B ADSTOCK TRANSFORMATIONS FOR ADVERTISING GRP/TRPs
    6. NOTES
  18. Chapter 10: New Product Forecasting: Using Structured Judgment
    1. DIFFERENCES BETWEEN EVOLUTIONARY AND REVOLUTIONARY NEW PRODUCTS
    2. GENERAL FEELING ABOUT NEW PRODUCT FORECASTING
    3. NEW PRODUCT FORECASTING OVERVIEW
    4. WHAT IS A CANDIDATE PRODUCT?
    5. NEW PRODUCT FORECASTING PROCESS
    6. STRUCTURED JUDGMENT ANALYSIS
    7. STRUCTURED PROCESS STEPS
    8. STATISTICAL FILTER STEP
    9. MODEL STEP
    10. FORECAST STEP
    11. SUMMARY
    12. NOTES
  19. Chapter 11: Strategic Value Assessment: Assessing the Readiness of Your Demand Forecasting Process
    1. STRATEGIC VALUE ASSESSMENT FRAMEWORK
    2. STRATEGIC VALUE ASSESSMENT PROCESS
    3. SVA CASE STUDY: XYZ COMPANY
    4. SUMMARY
    5. SUGGESTED READING
    6. NOTES
  20. Index