New technologies like the internet of things (IoT) and point-of-sale tools are helping us capture, harvest, and harness masses of data and information. But if collating and correlating this material takes a great deal of effort, making sense of it is an even bigger challenge. Traditional forecasting techniques simply don't cut it in this context.
That's where artificial neural network (ANN) models come into play. These differ significantly from traditional forecasting methods because they don't rely solely on a demand planner's expertise and experience to identify relationships and patterns in variables. Instead, they self-learn using observational data to identify regularities, relationships, and patterns between variables.