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A*STAR develops new analytic method to identify supply chain vulnerability

Singapore's A*STAR announces new report on increasing resilience to disruption in the supply chain

“The resilience of supply chain networks to major disruptions can now be measured using a multi-factor test”.

The Agency for Science, Technology and Research (A*STAR), Singapore’s largest public sector agency for economically-oriented research, announced today its new analytic measure that allows companies to determine its vulnerability to disruptions within the supply chain.

According to the company’s researchers at the Institute of High Performance Computing, “the measure has the potential to dramatically improve decision-making in supplier management and lower financial risk across many sectors.”

The consequences of disruption in the supply chain, either by removing critical supplies or suppliers from the downstream elements of the network, “the economic fallout can be catastrophic and widespread.”

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According to Rick Goh, team leader at the Institute of High Performance Computing, “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".

Goh continues, explaining that the Institute of High Performance Computing 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 realize that it is too late when it comes to them due to the loss of time across the supply chain network.”

A*STAR’s new analytic method tracks the ripple effects of a production pause throughout the supply chain. By using “generalized mathematical models of both perfect tree and randomly constructed networks”, researchers showed that “risks in a supply chain network are determined by both the resilience of companies and the structure of the supply chain network, and that mapping out and understanding these risk factors is essential to risk minimization.”

Jesus Felix Bayta Valenzuela, first author of the study, concludes that “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”.

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