Reconfigurable Intelligent Surfaces (RIS) are envisioned to become a pivotal transformative technology within the realm of 6G mobile networks. In this study, we introduce three heuristic algorithms designed to optimize radio resource management, ultimately enhancing throughput within a RIS-enhanced mobile network. Our findings demonstrate that the algorithm which holistically optimizes user scheduling, RIS-UE association, cell precoding matrices, and RIS configuration matrices outperforms alternative strategies. Moreover, our investigation delves into uncovering the most effective applications of RIS. This involves a thorough performance comparison of the algorithms across diverse scenarios, encompassing varying RIS deployment configurations (position and orientation), number of users in a network, and number of RIS elements. Additionally, we model the influence of blocker loss—characterized by blocker presence probability and strength—on throughput performance. In the wake of our study, it becomes evident that RIS exhibits the most promising potential in scenarios involving MU-MIMO configurations, whether within single-cell or multi-cell layouts, and for both indoor and outdoor user settings. However, for SU-MIMO cases, RIS-induced throughput enhancement manifests exclusively in single-cell layouts, and particularly benefits outdoor users in environments marked by substantial blocker strength.