In a chemical supply chain, simple molecules are transformed into more functionalised molecules along specific reaction paths. These reaction paths can be illustrated in a network of nodes and edges. The all-to-all wiring scheme, connecting all reactants to all products, and the one-to-one mapping scheme, where only the heaviest reactant is mapped to the heaviest product, have shown to give comparable properties. Different representations of the all-to-all wiring scheme have been introduced in the literature, from which we outline some in Figure . With the objective to identify strategic molecules in the network we find the simplified directed network without parallel edges most suited. When practical intersections are desired, information on reaction partners are not required, which leads us to the first simplification from (b) to (c) in Figure . Further, duplicate parts of reactions as shown in (a) where molecule A can lead to product B in reaction (1) and in reaction (3) do not enclose additional insight. Thus, we perform the second simplification from (c) to (d) in Figure . Networks are used to capture real-world problems that often have interactions between large numbers of objects or subjects. A chemical supply chain is a good example of such interacting system. A simple illustration of a graph is seldom sufficient to understand the relationships within a complex system. In network science a set of metrics is commonly used to describe networks on global and local scales. There are different types of networks and many metrics to characterise them. In this work we describe networks based on their degree distribution and we consider centrality measures to label nodes. For a more profound understanding of network types and theories of network science, we refer the reader to further literature. The main characteristic of a node is its linkage in the network. The number of edges leaving one node is called 'out degree', while the number of incoming edges is called 'in degree'. In