Business Forecasting: Practical Problems and Solutions

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.

About the Authors

MICHAEL GILLILAND is Marketing Manager for SAS forecasting software, editor of the Forecasting Practice section of Foresight: The International Journal of Applied Forecasting, and author of The Business Forecasting Deal. He has published articles in Supply Chain Management Review, Journal of Business Forecasting, Analytics, Supply Chain Forecasting Digest, APICS Magazine, Swiss Analytics Magazine, and Foresight. 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, The Business Forecasting Deal, at blogs.sas.com/content/forecasting.

LEN TASHMAN is the founding editor of Foresight: The International Journal of Applied Forecasting, 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.

UDO SGLAVO 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 Analytics, and is a contributor to The Business Forecasting Deal blog. Udo has served on the practitioner advisory board of Foresight, and holds a diploma in mathematics from University of Applied Sciences, Darmstadt, Germany.