In this work, we use a portfolio of graph theoretical measures to identify strategic molecules in the NOC. If a molecule is a bulk chemical itself, or directly connected to one, its degree, pagerank and HITS y-hubs value will be different to the values of most other nodes. The betweenness centrality is used to measure the efficiency of reaction paths through a molecule. An isolation forest algorithm is applied to identify potential strategic molecules based on a vector of graph metrics. The strategic molecules are evaluated by comparison with common industrial intermediates. Further, we propose a method of reaction path screening over the strategic molecules. Based on these tools, we developed a case study of integration of crude sulphate terpentine (CST) into a supply chain of sample high-value end products, e.g.