Introduction The modern growingly complex word introduces diverse tasks for individuals working in different spheres. The given complexity stipulates the increased sophistication of relations between numerous variables comprising one or another phenomenon. For this reason, the approach known as systems thinking becomes one of the most potent tools to analyze peculiarities of relations and make conclusions about their interaction. It could also be described as the specific set of practices used by managers to consider objects and their interdependence as the system that has its peculiarities and evolves in a particular way (Dalio, 2017). Systems thinking might also demand visualization to ensure an enhanced understanding of processes (Dalio, 2017). In this regard, loop diagrams become one of the most powerful methods to present a correlation and provide a credible and reliable conclusion about its further evolution. In this regard, the given paper is devoted to the in-depth investigation of the given method, its nature, the way it is applied, and how it now helps managers to achieve particular goals. Discussion A causal loop diagram (CLD) could be defined as a specific visualization tool that is aimed at demonstrating how different variables in a particular system interact and precondition the emergence of diverse alterations (“Causal loop diagrams,” n.d.). The traditional CLD could be considered a rather simple thought effective way to explain the behavior of different processes, and how specific responses trigger diverse reactions. The given diagram consists of a set of nodes and edges. (Kim, 1992). These are introduced to represent a connection and relation between the most important variables that can be found in every case. Specifically, nodes are used to visualize all variables or aspects of the system that impact each other (“Causal loop diagrams,” n.d.). Edges stand for links that describe connections or relations between variables that are studied at the moment (Kim, 1992). Additionally, because there are different kinds of bonds between all aspects of the system, there are positive (+ or s) and negative (- or o) links (Kim, 1992). The positive causal link means that two nodes of a particular correlation move or change in the same direction (Kim, 1992). In other words, the increase in the state of the first variable is also followed by an increase in the state of another. Alternatively, a negative causal link shows that nodes presented in the diagram move in opposite directions (Kim, 1992). If one node is associated with the link increase, another will start to decrease. Additionally, every loop diagram has closed cycles depicted as loops, or circles. These are very important aspects of every scheme of this sort as they describe peculiarities of every process within the analyzed system and could be united in bigger entities to demonstrate how they interact and what kind of bond exists between them (Lannon, n.d.). These closed cycles could also be referred to as balancing feedback loops in which the alteration of any of the presented variables moves through the created link and returns to the original process reinforcing its initial growth or other meaningful aspects (“System behavior and causal loop diagrams,” n.d.). In such a way, the loop diagram becomes a simple and efficient way to describe diverse processes and how their basic aspects might vary due to their interconnection and mutual dependence. There are multiple