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The article “When it comes to risk management, think small” was authored by Patrick Burnson in January 2014. He discusses risk management in supply chains. The article explores the insights from different persons including Massachusetts Institute of Technology (MIT) Professor David Simchi-Levi. Others are Stanford University Professor Hau Lee and Rose Kelly-Falls of Rapid Ratings International in Indiana. Among the topics covered is solvency, supply chain management, supply chain risks, and the automobile company Ford Motor Co.
US firms are largely focused on protecting asset-concentrated suppliers in the effort to mitigate risks in the supply chain. However, contemporary studies indicate that a correlation may not exist between the net amount the firm spends with a supplier and the profit loss the firm would incur if the supply were unexpectedly disrupted. The discovery challenges the typical business principle that likens the greatest supply chain risk to suppliers of maximum annual spending. According to Simchi-Levi (2014), the highest spending suppliers pose lesser risk to manufacturers compared to low-spending suppliers. In essence, suppliers that provide firms with comparatively low-cost components (smaller firms) are likely to cause the greatest impact when disruption occurs.
Typical methods for the identification of suppliers and actions that present the greatest risks depend on the knowledge of the possibility that a particular type of risk circumstance will occur (Alexandru, 2014). Risks that arise from short work stoppage to a major disruption of supply exist on a range of rate of recurrence and inevitability (Burnson, 2014). In this regard, origins of low-probability with high-impact risk are challenging to calculate despite the fact that small risks are diverse, many and result in high losses to the manufacturer.
The risk mitigation options are similar regardless of the kind of problem that occurs. Therefore, a statistical representation of the inherent risks ought determining the impact to the manufacturer’s operations if supply is disrupted as opposed to approximation of the probability of particular risks (Burnson, 2014). In this regard, Simchi-Levi develops a model that involves bill-of-material data, numerous layers of supplier relationships, operational and financial impacts, and recovery time for suppliers after disruptions.
The removal of the nodes in the delivery chain results in the determination of the most appropriate substitutes in stock reallocation and the financial repercussions. The consequent analysis classifies suppliers into 3 divisions corresponding to the cost of individual components they offer and the financial outcome arising from their shortages. Simchi-Levi’s model indicates that extreme interruptions (over 50%) of the tier one suppliers will not result in loss. On the other hand, a disruption from 2% of small firms would result in large financial loss for the manufacturers. Interestingly, the 2% of firms fall within organizations that supply low-cost components. By using the Ford illustration, Simchi-Levi sought to demonstrate that when contemplating supply risk management, it is essential to consider small factors that most organizations take for granted yet they have far-reaching financial implications for manufacturers.
Manufacturers should create back-up plans for smaller suppliers (Machowiak, 2012). The supplier solvency should be at the core of risk management consideration. Manufacturers should be more concerned with smaller suppliers hence establish mitigation measures. Good relationship with small suppliers cannot be overemphasized.
The article provides a quantitative analysis by Professor David Simchi-Levi, Massachusetts Institute of Technology (MIT) Department of Civil and Environmental Engineering and Engineering Systems Division. The author with insight from Simchi-Levi showed that a manufacturer’s total spending and the supply disruption cost are not correlated. He discusses the significance of risk assessment to enable plan updates such as tariffs, labor costs, and fuel prices. He also illustrates a manufacturer’s risk exposure index.
Alexandru, C. (2014). A confirmatory approach to measuring risks in supply chains. Management and marketing Journal, 10(54), 1135-1142.
Burnson, P. (2014). When it comes to risk management, think small. Supply Chain Management Review, 1(1), 8-10.
Machowiak, W. (2012). Risk management: Unappreciated instrument of supply chain management strategy. Scientific Journal of Logistics, 8(4), 277-285.