Overview

Forecasting is required in many situations. Deciding whether to build another power generation plant in the next five years requires forecasts of future demand. Scheduling staff in a call center next week requires forecasts of call volumes. Stocking an inventory requires forecasts of stock requirements. Telecommunication routing requires traffic forecasts a few minutes ahead. Whatever the circumstances or time horizons involved, forecasting is an important aid in effective and efficient planning. This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly. Examples use R with many data sets taken from the authors' own consulting experience. In this third edition, all chapters have been updated to cover the latest research and forecasting methods. The book offers clear explanations, practical examples, and end-of-chapter exercises and cases. Readers will learn to use forecasting methods using the free open-source R software to develop effective forecasting solutions that extract business value from time-series data. Featuring improved organization and new material, this book also includes: Popular forecasting methods including smoothing algorithms, regression models, and neural networks A practical approach to evaluating the performance of forecasting solutions A business-analytics exposition focused on linking time-series forecasting to business goals Guided cases for integrating the acquired knowledge using real data End-of-chapter problems to facilitate active learning The book is also designed for practitioners in the fields of operations research, supply chain management, marketing, economics, finance and management

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