Business Forecasting - (Wiley and SAS Business) by Michael Gilliland & Len Tashman & Udo Sglavo (Hardcover)
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<p/><br></br><p><b> About the Book </b></p></br></br>"Forecasting is the process of making predictions of the future based on past and present data and most commonly by analysis of trends. A commonplace example might be estimation of some variable of interest at some specified future date. Prediction is a similar, but more general term 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"--<p/><br></br><p><b> Book Synopsis </b></p></br></br><p><b>Discover the role of machine learning and artificial intelligence in business forecasting from some of the brightest minds in the field</b></p> <p>In <i>Business Forecasting: The Emerging Role of Artificial Intelligence and Machine Learning</i> accomplished authors Michael Gilliland, Len Tashman, and Udo Sglavo deliver relevant and timely insights from some of the most important and influential authors in the field of forecasting. You'll learn about the role played by machine learning and AI in the forecasting process and discover brand-new research, case studies, and thoughtful discussions covering an array of practical topics. The book offers multiple perspectives on issues like monitoring forecast performance, forecasting process, communication and accountability for forecasts, and the use of big data in forecasting.</p> <p>You will find: </p> <ul> <li>Discussions on deep learning in forecasting, including current trends and challenges</li> <li>Explorations of neural network-based forecasting strategies</li> <li>A treatment of the future of artificial intelligence in business forecasting</li> <li>Analyses of forecasting methods, including modeling, selection, and monitoring</li> </ul> <p>In addition to the Foreword by renowned researchers Spyros Makridakis and Fotios Petropoulos, the book also includes 16 opinion/editorial Afterwords by a diverse range of top academics, consultants, vendors, and industry practitioners, each providing their own unique vision of the issues, current state, and future direction of business forecasting.</p> <p>Perfect for financial controllers, chief financial officers, business analysts, forecast analysts, and demand planners, <i>Business Forecasting</i> will also earn a place in the libraries of other executives and managers who seek a one-stop resource to help them critically assess and improve their own organization's forecasting efforts.</p><p/><br></br><p><b> From the Back Cover </b></p></br></br><p>Over the last six decades, business forecasting has demonstrated a remarkable ability to keep executives and managers informed of likely trends in a huge variety of industries and businesses around the world. And while most forecasters didn't see the unfolding COVID-19 pandemic or its effects coming, more typical and mundane scenarios provide plenty of opportunity for forecasters to show their talent.</p> <p><i>Business Forecasting: The Emerging Role of Artificial Intelligence and Machine Learning</i> delivers a curated collection of insightful papers designed to shed light on the growing role of artificial intelligence (AI) and machine learning (ML) in the crucial field of business forecasting. The book discusses new and varied techniques and technologies, like cross learning, big data, judgmental model selection, and error analysis, to provide an illuminating view of the rapidly evolving world of forecasting.</p> <p>The resources included contain academic research, case studies, and thoughtful discussions of important business forecasting topics. The articles are influential, informative, and provocative, eliciting new considerations and ideas, as well as practical insights and strategies.</p> <p>Readers will also enjoy a collection of original "Afterwords" from recognized forecasting thought leaders in academics, industry, and consulting. These Afterwords--written specifically for this book--cover a variety of topics relating to the issues, current state, and future direction of business forecasting.</p> <p>Perfect for financial controllers, chief financial officers, business analysts, and forecast analysts and managers, <i>Business Forecasting</i> is also an invaluable resource for demand planners and other professionals whose job relies on predicting future states of variables. It will also be of interest to machine learning and artificial intelligence professionals who seek a one-stop and up-to-date resource on the application of those technologies to business and finance.</p><p/><br></br><p><b> About the Author </b></p></br></br><p><b>MICHAEL GILLILAND</b> is Marketing Manager for SAS forecasting software and Associate Editor of <i>Foresight: The International Journal of Applied Forecasting</i>. He is author of <i>The Business Forecasting Deal</i>.<br /><b><br />LEN TASHMAN</b> is the founding editor of <i>Foresight: The International Journal of Applied Forecasting</i>. He is emeritus professor of business administration at the University of Vermont and Director of the Center for Business Forecasting.<br /><b><br />UDO SGLAVO</b> is Vice President of Analytics R&D at SAS and holds several patents in the area of advanced analytics. His writings have appeared in <i>Analytics</i> magazine and the book <i>Big Data and Business Analytics</i>.</p>
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