Our solution consists in the implementation of a recurrent neuronal network algorithm (DeepAR) using Sagemaker.
The output corresponds to a probabilistic distribution of predictions for each one of the forecasted time series (unique combination of products and locations), which facilitates the management and optimization of the relationship between stock-break and over-stock, without the need to incorporate a greater complexity when making decisions, nor additional human resources.