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
- Cover
- Series
- Title Page
- Copyright
- Foreword
- Preface
- Acknowledgments
- About the Author
-
Chapter 1: Demystifying Forecasting: Myths versus Reality
- DATA COLLECTION, STORAGE, AND PROCESSING REALITY
- ART-OF-FORECASTING MYTH
- END-CAP DISPLAY DILEMMA
- REALITY OF JUDGMENTAL OVERRIDES
- OVEN CLEANER CONNECTION
- MORE IS NOT NECESSARILY BETTER
- REALITY OF UNCONSTRAINED FORECASTS, CONSTRAINED FORECASTS, AND PLANS
- NORTHEAST REGIONAL SALES COMPOSITE FORECAST
- HOLD-AND-ROLL MYTH
- THE PLAN THAT WAS NOT GOOD ENOUGH
- PACKAGE TO ORDER VERSUS MAKE TO ORDER
- “DO YOU WANT FRIES WITH THAT?”
- SUMMARY
- NOTES
-
Chapter 2: What Is Demand-Driven Forecasting?
- TRANSITIONING FROM TRADITIONAL DEMAND FORECASTING
- WHAT'S WRONG WITH THE DEMAND-GENERATION PICTURE?
- FUNDAMENTAL FLAW WITH TRADITIONAL DEMAND GENERATION
- RELYING SOLELY ON A SUPPLY-DRIVEN STRATEGY IS NOT THE SOLUTION
- WHAT IS DEMAND-DRIVEN FORECASTING?
- WHAT IS DEMAND SENSING AND SHAPING?
- CHANGING THE DEMAND MANAGEMENT PROCESS IS ESSENTIAL
- COMMUNICATION IS KEY
- MEASURING DEMAND MANAGEMENT SUCCESS
- BENEFITS OF A DEMAND-DRIVEN FORECASTING PROCESS
- KEY STEPS TO IMPROVE THE DEMAND MANAGEMENT PROCESS
- WHY HAVEN'T COMPANIES EMBRACED THE CONCEPT OF DEMAND-DRIVEN?
- SUMMARY
- NOTES
- Chapter 3: Overview of Forecasting Methods
- Chapter 4: Measuring Forecast Performance
- Chapter 5: Quantitative Forecasting Methods Using Time Series Data
-
Chapter 6: Regression Analysis
- REGRESSION METHODS
- SIMPLE REGRESSION
- CORRELATION COEFFICIENT
- COEFFICIENT OF DETERMINATION
- MULTIPLE REGRESSION
- DATA VISUALIZATION USING SCATTER PLOTS AND LINE GRAPHS
- CORRELATION MATRIX
- MULTICOLLINEARITY
- ANALYSIS OF VARIANCE
- F-TEST
- ADJUSTED R2
- PARAMETER COEFFICIENTS
- t-TEST
- P-VALUES
- VARIANCE INFLATION FACTOR
- DURBIN-WATSON STATISTIC
- INTERVENTION VARIABLES (OR DUMMY VARIABLES)
- REGRESSION MODEL RESULTS
- KEY ACTIVITIES IN BUILDING A MULTIPLE REGRESSION MODEL
- CAUTIONS ABOUT REGRESSION MODELS
- SUMMARY
- NOTES
-
Chapter 7: ARIMA Models
- PHASE 1: IDENTIFYING THE TENTATIVE MODEL
- PHASE 2: ESTIMATING AND DIAGNOSING THE MODEL PARAMETER COEFFICIENTS
- PHASE 3: CREATING A FORECAST
- SEASONAL ARIMA MODELS
- BOX-JENKINS OVERVIEW
- EXTENDING ARIMA MODELS TO INCLUDE EXPLANATORY VARIABLES
- TRANSFER FUNCTIONS
- NUMERATORS AND DENOMINATORS
- RATIONAL TRANSFER FUNCTIONS
- ARIMA MODEL RESULTS
- SUMMARY
- NOTES
- Chapter 8: Weighted Combined Forecasting Methods
- Chapter 9: Sensing, Shaping, and Linking Demand to Supply: A Case Study Using MTCA
-
Chapter 10: New Product Forecasting: Using Structured Judgment
- DIFFERENCES BETWEEN EVOLUTIONARY AND REVOLUTIONARY NEW PRODUCTS
- GENERAL FEELING ABOUT NEW PRODUCT FORECASTING
- NEW PRODUCT FORECASTING OVERVIEW
- WHAT IS A CANDIDATE PRODUCT?
- NEW PRODUCT FORECASTING PROCESS
- STRUCTURED JUDGMENT ANALYSIS
- STRUCTURED PROCESS STEPS
- STATISTICAL FILTER STEP
- MODEL STEP
- FORECAST STEP
- SUMMARY
- NOTES
- Chapter 11: Strategic Value Assessment: Assessing the Readiness of Your Demand Forecasting Process
- Index
Product information
- Title: Demand-Driven Forecasting: A Structured Approach to Forecasting, 2nd Edition
- Author(s):
- Release date: August 2013
- Publisher(s): Wiley
- ISBN: 9781118669396
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