Measuring risks to supply chain disruptions
Companies may be able to determine their vulnerability to major supply chain disruptions thanks to a new analytic measure developed by A*STAR researchers.
Disruptions in supply chain networks can have immediate effects downstream in the network, as well as knock-on effects on other businesses dependent on the network for survival. The consequences can be severe, causing widespread economic fallout — especially for those who are unprepared.
Rick Goh and his team at A*STAR’s Institute of High Performance Computing aimed to measure supply chain risk that takes into account the loss profile of the originating node, the structure of the supply network and the resilience of the network components.
They developed an analytical measure by tracking the propagation of a production pause through a network of nodes using generalised mathematical models of both perfect tree and randomly constructed networks. The measure has the potential to improve decision-making in supplier management and lower financial risk.
“When a man-made or natural disaster or disruption is happening somewhere, a company may not capture the impact to its production line as the disruption may apply to its second- or third-tier suppliers directly, rather than to its first-tier partner,” said Goh. “We wanted to capture the propagation of supply chain disruption risks far beyond their immediate connection to a focal company, which may reach to the company later on but they usually realise that it is too late when it comes to them due to the loss of time across the supply chain network.”
A*STAR stated a better understanding of how disruption-caused losses spread through a company’s supply chain network could help companies improve their supplier network structure, but it is difficult to do and is rarely subjected to quantitative analysis. Goh and his team wanted to develop a more reliable measure that can capture the key factors contributing to sensitivity or resilience to disruption across a multi-tier supply chain network.
“Beyond only looking at the propagation effects from one company to another, in our study, we also consider individual companies’ resilience capability to overcome the disruption risks and manage the situation internally,” said Goh.
The researchers showed that mapping out and understanding risk factors is essential to risk minimisation, and highlighted the need for supply chain managers to build risk profiles of each component of a supply chain network.
“The modelling confirms that having multiple redundant suppliers, both direct and indirect, will help cushion, or even remove, any impact on one’s own production, and may help prevent chained domino-effect disruptions,” concluded Jesus Felix Bayta Valenzuela, first author of the study.
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