While PCA has been used in the past to determine reaction coordinates, we have demonstrated that it is insufficient for a highly complex system, with many degrees of freedom. To yield any separation between the three states in the PCA, we had to transform cartesian coordinates to a set of internal coordinates, which we further reduced to minimize the number of highly correlated coordinates in the data set, thus reducing noise. Although this single step of our workflow is not fully automated at the moment, we used clear guidelines for introducing our reduced coordinate set, usage of internal coordinates, representation of rigid groups such as phenyl by their centre of mass, which are applicable to any chemical system. While product states could be separated from educts and transition states, the latter two still showed overlap. In contrast, standard PCA on the cartesian coordinates resulted in no separation of the three states. We suspect the poor performance stems from failure to fully eliminate rotational and translational degrees of freedom from the system. Complementary to PCA, tICA was used to identify slow movements of the system. While the analysis revealed some structural insights into the product conformer ensemblerevealing, through the changes in the product-cage/phenanthroline distances indicating π-π stacking interactions between the coupling product, phenanthroline, and calixarene -it was not able to separate educts from transition states. Hence, tICA could not fully identify the reaction coordinate.