Len Tashman
Founding Editor, Foresight

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.

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Business Forecasting: The Emerging Role of Artificial Intelligence and Machine Learning

By Michael Gilliland, Udo Sglavo, and Len Tashman

This book provides ideas from the most important and influential authors in the field of forecasting on an array of topics that are highly relevant. It provides multiple perspectives on relevant issues like monitoring forecast performance, forecasting process, communication and accountability for the forecast, the use of big data in forecasting, and the role of AI/ML in enhancing traditional time series forecasting methods. Note: Content is mostly material previously published in "practitioner" journals (Foresight and Journal of Business Forecasting), with a few articles from the academic International Journal of Forecasting. Some articles report on academic research, or include case studies, but most are thoughtful discussion of important business forecasting topics, such as the role of the sales force in forecasting, or the value of judgmental overrides to a statistical forecast, or how to determine what forecast error is "avoidable." Articles were chosen for their importance, influence, informativeness, and for being provocative -- leading the reader to new considerations and ideas.

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Business Forecasting Practical Problems and Solutions

By Mike Gilliland, Udo Sglavo and Len Tashman

Business Forecasting provides an expert's-eye view of the field's latest developments to help you achieve your desired business outcomes. This book delivers an array of new tools and research that can enable more efficient processes and more accurate results. 

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