Key performance indicators (KPIs) express the company’s strategy and vision in terms of goals and enable alignment with stakeholder expectations. In business intelligence, forecasting KPIs is pivotal for strategic decision-making. For this reason, in this work we focus on forecasting KPIs. We built a transformer model architecture that outperforms conventional models like Multi-Layer Perceptrons (MLP), Long Short-Term Memory (LSTM) networks, Convolutional Neural Networks (CNN), and Recurrent Neural Networks (RNN) in KPI forecasting over the Rossmann Store, supermarket 1, and 2 datasets. Our results highlight the revolutionary potential of using cutting-edge deep learning models such as the Transformer.
Forecasting of Key Performance Indicators Based on Transformer Model / Diamantini, Claudia; Khan, Tarique; Mircoli, Alex; Potena, Domenico. - (2024).
Forecasting of Key Performance Indicators Based on Transformer Model
Diamantini;Tarique Khan;Alex Mircoli;Domenico Potena
2024-01-01
Abstract
Key performance indicators (KPIs) express the company’s strategy and vision in terms of goals and enable alignment with stakeholder expectations. In business intelligence, forecasting KPIs is pivotal for strategic decision-making. For this reason, in this work we focus on forecasting KPIs. We built a transformer model architecture that outperforms conventional models like Multi-Layer Perceptrons (MLP), Long Short-Term Memory (LSTM) networks, Convolutional Neural Networks (CNN), and Recurrent Neural Networks (RNN) in KPI forecasting over the Rossmann Store, supermarket 1, and 2 datasets. Our results highlight the revolutionary potential of using cutting-edge deep learning models such as the Transformer.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.