Human vs. machines

Abstract

“If you ask ten experts, you will get ten different opinions.” This common proverb illustrates the common association of expert forecasts with personal bias and lack of consistency. On the other hand, digitization promises consistency and explainability through data-driven forecasts employing machine learning (ML) and statistical models. Despite the importance of the semiconductor industry being widely recognized, little research has gone into forecasting the whole semiconductor market including all major product categories. Instead, analysts have generally relied on expert forecasts such as those provided by the World Semiconductor Trade Statistics (WSTS). In the following, we generate data-driven forecasts and evaluate whether existing industry expert forecasts can be further enhanced through statistical and ML models. This study contributes by systematically evaluating the accuracy of expert forecasts, examining comprehensive multi-granularity forecasts for the entire semiconductor market, and offering performance insights through out-of-sample error measures to guide future forecasting practitioners.