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CHANGE & CHANCE EMBRACED:

Achieving Agility with Demand Forecasting in the Supply Chain

ISBN-10:0692945989

ISBN-13:978-069294588

by Hans Levenbach, PhD

Executive Director: CPDF Training and Certification

TABLE OF CONTENTS Contents

PART I. FRAMING THE FORECASTING PROCESS

Chapter 1. Embracing Change and Chance: Demand Forecasting Explained

Inside the Crystal Ball. Is Forecasting Worthwhile? Creating a Structured Forecasting Process.  Establishing an Effective Demand Forecasting Strategy. Takeaway

Chapter 2. Demand Forecasting is Mostly about Data: Improving Data Quality through Data Exploration and Visualization

Chapter 3. Predictive Analytics: Selecting Useful Forecasting Techniques for Demand Forecasting

Chapter 4. Taming Uncertainty: What You Need to Understand About Measuring Forecast Accuracy

PART II. EXPLORING HISTORICAL DATA

Chapter 5. Characterizing Demand Variability: Seasonality, Trend and the Uncertainty Factor

Chapter 6. Dealing with Seasonal Fluctuations

Chapter 7. Forecasting Trend-Cycles with Turning Points

PART III. AUTOMATED FORECASTING TECHNIQUES: THE STATE SPACE APPROACH

Chapter 8. Big Data: Baseline Forecasting with Exponential Smoothing Models

Chapter 9. Short-term Forecasting With ARIMA Models

PART IV: CREATING CAUSAL FORECASTING MODELS

Chapter 10. Demand Forecasting with Regression Models

Chapter 11. Gaining Credibility through Root Cause Analysis and Exception Handling

PART V: IMPROVING FORECASTING AGILITY: THE PEER PROCESS

Chapter 12. The Final Forecast Numbers: Reconciling Change and Chance

Chapter 13. Creating a Data Framework for Agile Forecasting and Demand Management

Chapter 14.Blending Agile Forecasting with an Integrated Business Planning Process

Forecasting, Practice and Process for Demand Management

(Class Exercises, Problem Sets, Cases, References, Glossary)

by Hans Levenbach, PhD and James P. Cleary, MBA

 © 2006 Duxbury Press/Cengage Learning

 (ISBN 0-534-26286-6)

PART I. INTRODUCING THE FORECASTING PROCESS.

PART II. EXPLORING TIME SERIES.

PART III. FORECASTING THE AGGREGATE.

PART IV: APPLYING BOTTOM-UP TECHNIQUES.

PART V: FORECASTING WITH CAUSAL FORECASTING MODELS.

PART VI: FORECASTING WITH ARIMA MODELS.

PART VII: IMPROVING FORECASTING EFFECTIVENESS.

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