Until recently, conventional time series forecasting methods have been predominantly used for forecasting in demand planning. A majority of demand forecasting tools in the market leverage these methods in their solutions. With advances in technology and computing power, the sophistication of these time series algorithms has increased thereby increasing forecast accuracy.
However, with the advent of machine learning (ML) tools and increased interest in exploring them to improve forecasting approaches and methods, many vendors are increasingly incorporating ML-based forecasting methods in their tools. A key aspect to remember is that most of the frequently used ML algorithms have been around for decades now. Technology and computing power today allow us to leverage them easily in a variety of ways and applications. This article shares some Machine Learning approches that are being used by SAPinsiders.