Machine learning may be hyped as the way of the future, but as a forecasting method, it works best when combined with standard...
Spyros Makridakis is an INSEAD Emeritus Professor of Decision Sciences and a Professor at the University of Nicosia. Following the attainment of a place in the Greek Sailing Team in the Olympics of 1960, he set sail for the New York University where in 1969 he obtained a PhD. Since then, he has advised numerous international organisations and government agencies and consulted worldwide. Professor Makridakis has held teaching and research positions at several European and American institutions and served as a research fellow at IIM Berlin, an ICAME fellow at Stanford University, and a visiting scholar at MIT and Harvard. He joined INSEAD in 1970.
In addition to teaching and consulting expertise, Professor Makridakis has authored, or co-authored, twenty-six books including Forecasting, Planning and Strategy for the 21st Century (The Free Press), Forecasting: Methods and Applications (Wiley, now in its 3rd Edition), and Forecasting Methods for Management (Wiley) which reached its 5th edition and sold more than 120 thousand copies in twelve languages. He has also published more than 150 articles and book chapters. His paper "The Accuracy of Extrapolative (Time Series) Methods: Results of a Forecasting Competition" was voted as the best paper published in the field of forecasting during the last 25 years. He was the founding chief editor of the Journal of Forecasting and the International Journal of Forecasting. He has won twice the Best Teacher Award at INSEAD. He is the organiser of the renowned Makridakis (or M) Competitions that have fundamentally transformed the field of forecasting.
Professor Makridakis' current research interests centre around how the emerging technologies of Artificial Intelligence (AI) and Intelligence Augmentation (IA) will affect business firms (and societies in general) and the strategies that will be required in order to anticipate and exploit emerging opportunities while steering clear of the dangers associated with such technologies.