Business Forecasting - (Wiley and SAS Business) by Len Tashman & Udo Sglavo & Michael Gilliland (Hardcover)
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<p/><br></br><p><b> About the Book </b></p></br></br>"A comprehensive collection of the field's most provocative, influential new work Business Forecasting compiles some of the field's important and influential literature into a single, comprehensive reference for forecast modeling and process improvement. It is packed with provocative ideas from forecasting researchers and practitioners, on topics including accuracy metrics, benchmarking, modeling of problem data, and overcoming dysfunctional behaviors. Its coverage includes often-overlooked issues at the forefront of research, such as uncertainty, randomness, and forecastability, as well as emerging areas like data mining for forecasting. The articles present critical analysis of current practices and consideration of new ideas. With a mix of formal, rigorous pieces and brief introductory chapters, the book provides practitioners with a comprehensive examination of the current state of the business forecasting field. Forecasting performance is ultimately limited by the 'forecastability' of the data. Yet failing to recognize this, many organizations continue to squander resources pursuing unachievable levels of accuracy. This book provides a wealth of ideas for improving all aspects of the process, including the avoidance of wasted efforts that fail to improve (or even harm) forecast accuracy. Analyzes the most prominent issues in business forecasting Investigates emerging approaches and new methods of analysis Combines forecasts to improve accuracy Utilizes Forecast Value Added to identify process inefficiency The business environment is evolving, and forecasting methods must evolve alongside it. This compilation delivers an array of new tools and research that can enable more efficient processes and more accurate results. Business Forecasting provides an expert's-eye view of the field's latest developments to help you achieve your desired business outcomes"--<p/><br></br><p><b> Book Synopsis </b></p></br></br><b>A comprehensive collection of the field's most provocative, influential new work</b> <p><i>Business Forecasting</i> compiles some of the field's important and influential literature into a single, comprehensive reference for forecast modeling and process improvement. It is packed with provocative ideas from forecasting researchers and practitioners, on topics including accuracy metrics, benchmarking, modeling of problem data, and overcoming dysfunctional behaviors. Its coverage includes often-overlooked issues at the forefront of research, such as uncertainty, randomness, and forecastability, as well as emerging areas like data mining for forecasting. <p>The articles present critical analysis of current practices and consideration of new ideas. With a mix of formal, rigorous pieces and brief introductory chapters, the book provides practitioners with a comprehensive examination of the current state of the business forecasting field. <p>Forecasting performance is ultimately limited by the 'forecastability' of the data. Yet failing to recognize this, many organizations continue to squander resources pursuing unachievable levels of accuracy. This book provides a wealth of ideas for improving all aspects of the process, including the avoidance of wasted efforts that fail to improve (or even harm) forecast accuracy. <ul> <li>Analyzes the most prominent issues in business forecasting</li> <li>Investigates emerging approaches and new methods of analysis</li> <li>Combines forecasts to improve accuracy</li> <li>Utilizes Forecast Value Added to identify process inefficiency</li> </ul> <p>The business environment is evolving, and forecasting methods must evolve alongside it. This compilation delivers an array of new tools and research that can enable more efficient processes and more accurate results. <i>Business Forecasting</i> provides an expert's-eye view of the field's latest developments to help you achieve your desired business outcomes.<p/><br></br><p><b> From the Back Cover </b></p></br></br><p>In <i>Business Forecasting</i>, editors Michael Gilliland, Len Tashan, and Udo Sglavo have assembled in one comprehensive resource the most influential studies and writings in applied forecasting. The expert contributors focus on recent discoveries and reveal new methds and approaches in forecasting as well as touch on many controversial topics. Throughout the book, the authors emphasize the fact that enlightened forecasting management (not just fancy new algorithms) is the best way to improve forecasting practice. This valuable collection gives forecast analysts, demand planners, and anyone involved in the forecasting process a practical and thought-provoking guide for forecast modeling and process improvement. <p>Designed to be practical, <i>Business Forecasting</i> explores the fundamental issues of forecasting and contains approaches for avoiding errors, methods for obtaining valid benchmarks, and shows how to use forecasting to steer business on the right course. The authors include information on methods of statistical forecasting and reveal how to select a statistical forecasting level and enhance forecasting by using the data mining tactic. In addition, the text puts the spotlight on performance evaluation and reporting and offers suggestions for tracking forecast accuracy and applying the use of scaled errors in addition to percentage errors in order to monitor forecasting accuracy. The text also contains a thorough review of the overall forecasting process and information on the inevitable politics involved in business forecasting. <p>To help hone forecasting skills, this vital resource covers a wide range of essential tools and topics such as employing accuracy metrics, applying quality assessments, modeling problem data, and overcoming dysfunctional behaviors. The authors also review typically overlooked issues including uncertainty, randomness, and forecastability, as well as offer an examination of emerging areas like forecast value added analysis. <p><i>Business Forecasting</i> is your hands-on guide to the latest developments in the field and contains an array of tools that can enable better processes and improved results.<p/><br></br><p><b> About the Author </b></p></br></br><p><b>MICHAEL GILLILAND</b> is Marketing Manager for SAS forecasting software, editor of the Forecasting Practice section of <i>Foresight: The International Journal of AppliedForecasting</i>, and author of <i>The Business Forecasting Deal</i>. He has published articles in <i>Supply Chain Management Review, Journal of Business Forecasting, Analytics, Supply Chain Forecasting Digest, APICS Magazine, Swiss Analytics Magazine</i>, and <i>Foresight</i>. Mike holds a BA in Philosophy from Michigan State University, and Master's degrees in Philosophy and Mathematical Sciences from Johns Hopkins University. Follow his blog, <i>The Business Forecasting Deal, </i> at blogs.sas.com/content/forecasting. <p><b>LEN TASHMAN</b> is the founding editor of <i>Foresight: The International Journal of Applied Forecasting</i>, now in its 10th year of publication. He serves on the Board of Directors of the International Institute of Forecasters and is organizer and chair of the Forecasting in Practice Track at the annual International Symposium on Forecasting. Len is an emeritus professor of business administration at the University of Vermont and Director of the Center for Business Forecasting. <p><b>UDO SGLAVO</b> is Senior Director of Predictive Modeling R&D at SAS Institute. His team develops industry-leading and award-winning software for data mining, machine learning, and large scale automatic forecasting. He has published articles in <i>Analytics</i>, and is a contributor to <i>The Business Forecasting Deal</i> blog. Udo has served on the practitioner advisory board of <i>Foresight</i>, and holds a diploma in mathematics from University of Applied Sciences, Darmstadt, Germany.
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