<p><i>Congestion</i> is a state in which, as inputs increases, outputs tend to decrease. In this regard, identification and assessment of congestion are critical for every management system. Sustainable supply chain management (SSCM) has emerged to address economic, environmental, and social requirements in supply chain planning. This paper evaluates congestion in sustainable supply chains characterized by undesirable outputs. We introduce a novel axiomatic approach in Data Envelopment Analysis (DEA) that assesses both congestion and weak congestion, marking a significant advancement in the field. This innovative method not only enhances theoretical understanding but also has practical implications for professionals involved in sustainable supply chain research. We present new processes for evaluating congestion and weak congestion specifically within the sustainable supply chain context. These processes are grounded in empirical analysis and offer actionable insights for the water and wastewater industry in Iran. In the initial stage, we identified evaluation indicators through interviews with industry experts. Subsequently, we analyzed data from suppliers to assess their congestion levels using our proposed methodologies. The results indicate that 4 out of 21 suppliers were found to be congested. Additionally, we detail the wasted input and output values of these congested suppliers, providing a model for addressing and mitigating congestion effectively. The practicality of our method is evident in its simultaneous detection of the amount of wastage in desirable and undesirable outputs. This feature empowers scholars in this research era to model sustainability indicators when evaluating supply chain suppliers, making it easier to implement our findings. Notably, the remarkable contribution and originality of the current study is to evaluate the types of congestion in the sustainable supply chain, considering sustainability indicators.</p>