Business Forecasting: Practical Problems And Solutions

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.

MICHAEL GILLILAND is Marketing Manager for SAS forecasting software, editor of the Forecasting Practice section ofForesight: The International Journal of Applied Forecasting, and author ofThe 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, andForesight. 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 inAnalytics, and is a contributor to The Business Forecasting Deal blog. Udo has served on the practitioner advisory board ofForesight, and holds a diploma in mathematics from University of Applied Sciences, Darmstadt, Germany.