Impact of deep-tier visibility on effective resilience assessment of supply networks

The COVID-19 pandemic further underscored the importance of effectively managing supply chains' resilience, which is particularly important for companies facing complex and global deep-tiered supply networks. While most disruptions originate upstream to a firm's immediate suppliers, unfortunately, most firms still lack visibility into the deeper tiers of the supply network. Beyond this, the extant literature on network resilience is mostly focused on simplistic static network analysis methods. We propose an effective method for resilience assessment of deep-tier supply networks. The proposed framework relies on discrete-event simulation informed by secondary data sources and global supply risk assessment/metric databases for improving the assessment of resilience for a firm. We also demonstrate that deep-tier visibility can be critical for effective resilience assessment of global networks. We validate the efficiency of the proposed method using a case-study informed by a real-world automotive supply network. Additionally, a sensitivity analysis approach is proposed to provide better directional guidance to decision-makers on the means to improve network resilience.

Automated summary

The COVID-19 pandemic highlighted the importance of effectively managing supply chain resilience, especially for companies with complex global networks. Most existing literature on network resilience focuses on simplistic static analysis methods, but a proposed framework aims to improve resilience assessment by utilizing deep-tier visibility and global supply risk assessment databases. Furthermore, a case study involving a real-world automotive supply network validates the efficiency of the proposed method, which also includes a sensitivity analysis approach for decision-makers.