Demand-Driven Forecasting : A Structured Approach to Forecasting

by Charles Chase

• ISBN13: 9780470531013
• ISBN10: 0470531010
• Format: eBook
• Copyright: 2009-07-01
• Publisher: Wiley

Summary

Praise for Demand-Driven ForecastingA Structured Approach to Forecasting"There are authors of advanced forecasting books who take an academic approach to explaining forecast modeling that focuses on the construction of arcane algorithms and mathematical proof that are not very useful for forecasting practitioners. Then, there are other authors who take a general approach to explaining demand planning, but gloss over technical content required of modern forecasters. Neither of these approaches is well-suited for helping business forecasters critically identify the best demand data sources, effectively apply appropriate statistical forecasting methods, and properly design efficient demand planning processes. In Demand-Driven Forecasting, Chase fills this void in the literature and provides the reader with concise explanations for advanced statistical methods and credible business advice for improving ways to predict demand for products and services. Whether you are an experienced professional forecasting manager, or a novice forecast analyst, you will find this book a valuable resource for your professional development." -Daniel Kiely, Senior Manager, Epidemiology, Forecasting & Analytics, Celgene Corporation"Charlie Chase has given forecasters a clear, responsible approach for ending the timeless tug of war between the need for 'forecast rigor' and the call for greater inclusion of 'client judgment.' By advancing the use of 'domain knowledge' and hypothesis testing to enrich base-case forecasts, he has empowered professional forecasters to step up and impact their companies' business results favorably and profoundly, all the while enhancing the organizational stature of forecasters broadly." -Bob Woodard, Vice President, Global Consumer and Customer Insights, Campbell Soup Company

Table of Contents

Foreword

Preface

Acknowledgments

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 Equation

Hold and Roll, Myth

The Plan That Wasn't Good Enough

Summary

Notes

What Is Demand-Driven Forecasting?

Do You Want Fries with That?

Definition of Demand-Driven Forecasting

What Is Demand Sensing?

Data Requirements

Role of Sales and Marketing

What Is Demand Shaping?

Integrating Demand-Driven Forecasting into the Consensus Forecasting Process

Importance of Business Intelligence (BI) Portals/Dashboards

Role of the Finance Department

Demand-Driven Forecasting Process Flow Model

Key Process Participants

Benefits of Demand-Driven Forecasting

Summary

Overview of Forecasting Methods

Underlying Methodology

Different Categories of Methods

How Predictable Is the Future?

Some Causes of Forecast Error

Segmenting Your Products to Choose the Appropriate Forecasting Method

Summary

Note

Measuring Forecast Performance

We Overachieved Our Forecast, So Lets Party!

Purposes for Measuring Forecasting Performance

Standard Statistical Error Terms

Specific Measures of Forecast Error

Out-of-Sample Measurement

Forecast Value Added

Summary

Notes

Quantitative Forecasting methods using time series data

Understanding Model Fitting Process

Introduction to Quantitative Time Series Methods

Quantitative Time Series Methods

Moving Averaging

Exponential Smoothing

Single Exponential Smoothing

Holt's Two Parameter Method

Holt's-Winter's Method

Winters' Additive Seasonality

Summary

Notes

Quantitative Forecasting Methods Using Causal Data

Regression Methods

Simple Regression

Multiple Regression

Box-Jenkins Approach to ARIMA Models

Box-Jenkins Overview

Extending ARIMA Models to Include Explanatory Variables

Unobserved Component Models

Summary

Notes

Weighted Combined Forecasting Methods

What Is Weighted Combined Forecasting?

Developing a Variance Weighted Combined Forecast

Summary

Notes

Sensing, Shaping, and Linking Demand to Supply: A Case Study Using MTCA

Linking Demand to Supply Using Multi-tiered Causal Analysis

Case Study: The Carbonated Soft Drink Story

Summary

Consumer Packaged Goods Terminology

Adstock Transformations for Advertising GRP/TRPs

Notes

Strategic Value Assessment: Assessing the Readiness of Your Demand Forecasting Process

Strategic Value Assessment Framework

Strategic Value Assessment Process

A SVA Case Study: XYZ Company

Summary

Suggested Reading

Notes

Index

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