Friday 15 December 2023, 2:00pm to 3:00pm
Why you should care about exponential smoothing
Abstract: In the age of Machine Learning, many data scientists have started using more complicated approaches for forecasting, such as XGBoost, k-NN, Artificial Neural Networks etc. Due to the increased interest in these methods, the simpler and robust approaches might look less attractive than the more innovative ones and as a result tend to be neglected. However, the good old exponential smoothing still works well in many situations and is still widely used in practice, especially in demand planning. In this talk, Ivan will give a short overview of the history of exponential smoothing, show how it has evolved over time, explain why it has been so popular and discuss how it can be used in the modern demand forecasting in a variety of situations, including intermittent demand forecasting and high frequency data.
Management Science, Lancaster University
Ivan Svetunkov is a Lecturer of Marketing Analytics at Lancaster University, UK and a Marketing Director of the Lancaster Centre for Marketing Analytics and Forecasting. He has PhD in Management Science from Lancaster University and a candidate degree in economics from Saint Petersburg State University of Economics and Finance. His main area of interest is in developing statistical methods for forecasting.
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