Granger causality is a method often used in time series analysis, but its interpretation in cause-effect relationships is unclear. A new approach has been developed to uncover the causal structures behind Granger causality, providing a better understanding of the relationships between variables. This method helps to give more meaning to the causal connections identified by Granger causality tests, moving beyond just forecasting techniques.