Business forecasting : practical problems and solutions / edited by Michael Gilliland, Udo Sglavo, Len Tashman.

Format:

Book

Contributor:

Gilliland, Michael, editor.

Sglavo, Udo, 1968- editor.

Tashman, Len, 1942- editor.

Series:

Wiley and SAS business series.

Wiley and SAS Business Series

Language:

English

Subjects (All):

Business forecasting.

Physical Description:

1 online resource (442 p.)

Edition:

1st edition

Place of Publication:

Hoboken, New Jersey : Wiley, 2015.

Language Note:

English

System Details:

text file

Summary:

"This title provides many of the most important and though-provoking articles by the leading business forecasting practitioners and academics. It exposes the reader to many of the best minds (and most provocative ideas) in the forecasting profession, with thorough referencing to related material for further reading. It provides: - A critical look at many of the vexing problems in business forecasting, such as volatility, forecastability, performance metrics, and human interaction in the forecasting process. - Introduces emerging new approaches such as combining data mining with forecasting and aggregating/reconciling across time hierarchies. - Addresses the often overlooked topic of data preparation and data quality (part of the "pre-processing" of data prior to forecasting. - Covers the proven (yet rarely used) method of combining forecasts to improve accuracy. Contains a mix of more formal/rigorous pieces, with brief chapters (adapted from blog posts) dealing narrowly with very specific topics"-- Provided by publisher.

Contents:

Intro

Praise

Series

Title page

Copyright

Foreword

Preface

Chapter 1 Fundamental Considerations in Business Forecasting

1.1 Getting Real about Uncertainty

1.2 What Demand Planners Can Learn from the Stock Market

1.3 Toward a More Precise Definition of Forecastability

1.4 Forecastablity: A New Method for Benchmarking and Driving Improvement

1.5 Forecast Errors and Their Avoidability

1.6 The Perils of Benchmarking

1.7 Can We Obtain Valid Benchmarks from Published Surveys of Forecast Accuracy?

1.8 Defining "Demand" for Demand Forecasting

1.9 Using Forecasting to Steer the Business: Six Principles

1.10 The Beauty of Forecasting

Chapter 2 Methods of Statistical Forecasting

2.1 Confessions of a Pragmatic Forecaster

2.2 New Evidence on the Value of Combining Forecasts

2.3 How to Forecast Data Containing Outliers

2.4 Selecting Your Statistical Forecasting Level

2.5 When Is a Flat-line Forecast Appropriate?

2.6 Forecasting by Time Compression

2.7 Data Mining for Forecasting: An Introduction

2.8 Process and Methods for Data Mining for Forecasting

2.9 Worst-Case Scenarios in Forecasting: How Bad Can Things Get?

2.10 Good Patterns, Bad Patterns

Chapter 3 Forecasting Performance Evaluation and Reporting

3.1 Dos and Don'ts of Forecast Accuracy Measurement: A Tutorial

3.2 How to Track Forecast Accuracy to Guide Forecast Process Improvement

3.3 A "Softer" Approach to the Measurement of Forecast Accuracy

3.4 Measuring Forecast Accuracy

3.5 Should We Define Forecast Error as e = F - A or e = A - F?

3.6 Percentage Error: What Denominator?

3.7 Percentage Errors Can Ruin Your Day

3.8 Another Look at Forecast-Accuracy Metrics for Intermittent Demand

3.9 Advantages of the MAD/Mean Ratio over the MAPE.

3.10 Use Scaled Errors Instead of Percentage Errors in Forecast Evaluations

3.11 An Expanded Prediction-Realization Diagram for Assessing Forecast Errors

3.12 Forecast Error Measures: Critical Review and Practical Recommendations

3.13 Measuring the Quality of Intermittent Demand Forecasts: It's Worse than We've Thought!

3.14 Managing Forecasts by Exception

3.15 Using Process Behavior Charts to Improve Forecasting and Decision Making

3.16 Can Your Forecast Beat the Naïve Forecast?

Chapter 4 Process and Politics of Business Forecasting

4.1 FVA: A Reality Check on Forecasting Practices

4.2 Where Should the Forecasting Function Reside?

4.3 Setting Forecasting Performance Objectives

4.4 Using Relative Error Metrics to Improve Forecast Quality in the Supply Chain

4.5 Why Should I Trust Your Forecasts?

4.6 High on Complexity, Low on Evidence: Are Advanced Forecasting Methods Always as Good as They Seem?

4.7 Should the Forecasting Process Eliminate Face-to-Face Meetings?

4.8 The Impact of Sales Forecast Game Playing on Supply Chains

4.9 Role of the Sales Force in Forecasting

4.10 Good and Bad Judgment in Forecasting: Lessons from Four Companies

4.11 Worst Practices in New Product Forecasting

4.12 Sales and Operations Planning in the Retail Industry

4.13 Sales and Operations Planning: Where Is It Going?

About the Editors

Index

EULA.

Notes:

Description based upon print version of record.

Includes bibliographical references at the end of each chapters and index.

Description based on print version record.

ISBN:

9781119228295

1119228298

9781119228271

1119228271

OCLC:

930364177