Forecast Accuracy Measurement:
Pitfalls to Avoid & Practices to Adopt

From the Editors of Foresight: The International Journal for Applied Forecasting

Introduction

Dos and Don’ts of Forecast Accuracy Measurement
Len Tashman

Part I: Metrics

Chapter 1: How to Define the Average Percentage Error: Two Surveys
Kesten Green & Len Tashman

Chapter 2: Advantages of the MAD/MEAN Ratio Over the MAPE
Stephan Kolassa & Wolfgang Schutz

Chapter 3: Measuring Forecast Accuracy: Omissions in Today’s Forecasting Software
Jim Hoover

Chapter 4: Forecast-Accuracy Metrics for Intermittent Demand
Rob Hyndman

Chapter 5: An Expanded Prediction-Realization Diagram for Assessing Forecast Errors
Roy Pearson

Part II: Benchmarking and Forecastability

Chapter 6: Can We Obtain Valid Benchmarks from Published Surveys of Forecast Accuracy?
Stephan Kolassa

Chapter 7: Measuring Improvement in Forecast Accuracy: A Case Study
Robert Reig

Chapter 8: How to Track Forecast Error to Guide Forecast Process Improvement
Jim Hoover

Chapter 9: Forecastability: Insights from Physics, Graphical Decomposition, and Information Theory
Peter Catt

Chapter 10: Toward a More Precise Definition of Forecastability
John Boylan

Chapter 11: How to Assess Forecastability
Stephan Kolassa

Part III: Costs of Forecast Error

Chapter 12: Assessing the Costs of Forecast Error — A Practical Example
Peter Catt

Chapter 13: Key Assumptions in Calculating the Cost of Forecast Error
John Boylan

Chapter 14: Use of the Normal Distribution in Calculating the Cost of Forecast Error
Tom Willemain

Chapter 15: Reply to Commentaries
Peter Catt

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