Chemicals production is responsible for 10% of global energy consumption and 7% of greenhouse gas emissions. Material and energy efficiency are the focus of industrial and policy decision-makers but are often pursued as separate strategies. In addition, the solutions investigated are often localised without exploring the dynamics and efficiency relationships between different areas of a chemical site. Past studies have applied network analysis to study large complex systems such as national economies. The applicability to complex systems at the scale of a chemical site are clear but unexplored so far. This paper uses an integrated energy and materials metric to study an ammonia site and a steam methane reforming (SMR) plant in detail. Exergy flow maps are constructed using Sankey diagrams to illustrate the resource (material and energy) flows around the site and the principal sources of exergy loss and destruction. Exergy efficiencies and exergy destruction values are calculated for every plant, equipment within the SMR plant and mechanism of exergy destruction. This information can guide improvement interventions. The site is then modelled using a network analysis approach to improve the understanding of the energy and material interactions within it. The SMR plant is the main source of exergy destruction with an exergy efficiency of 68% and exergy destruction of 600 GJ/h, followed by the ammonia synthesis and water gas shift (WGS) plants with 99 and 59 GJ/h respectively. Within the SMR plant, the two main burners contributed the most destruction with a total of 190 GJ/h. Combustion and heat exchange are the main exergy destruction mechanisms with 206 and 141 GJ/h respectively, a result that could guide higher-level improvement efforts. More realistic transit and fuel-product exergy efficiencies definitions are found to be consistently lower than conventional efficiency definitions, an effect most pronounced in heat exchangers. The network analysis detected communities of tightly connected plants in the ammonia site and can indicate groups where cascading effects of resource efficiency improvements could materialise. The different network metrics quantifying the importance of individual plants ranked some plants, such as the steam and ammonia synthesis plant, consistently highly. Other plants, like the tail gas stripping, ranked highly on some metrics and low on others. Further work can be undertaken to better tailor some of the network metrics for the purposes of a chemical site modelled as a network. This study’s focus is ammonia production and the SMR process, but the methodology can be applied to any industrial process, particularly chemical sites, with minimal adjustments.