تجزیه و تحلیل کمی اختلال ریسک در زنجیره تامین چند رده ای

We demonstrate how system resilience can be improved by focusing on a supply chain network as a whole. We analyze inventory placement and back-up methodologies in a multi-echelon network and view their effect on reducing supply chain risk. We focus on risk from both supply disruptions and demand uncertainty and compare their impacts and mitigating strategies. A simulation model developed to capture an actual network for a consumer packaged goods company is used for the analysis. We present analysis and insights for multi-echelon networks and show how network utilization and proactive planning enable reductions in supply chain disruption impact.

While disruptions in the supply chain are a realistic possibility that companies must address, most supply chain models fail to capture them sufficiently. Most literature that includes the possibility for disruption in supply focuses on single facilities or pairs of echelons in a supply chain, even though disruptions can have long and lasting effects throughout the supply chain. In this paper, we consider a real supply chain and realistic estimates for disruption possibilities in that supply chain to examine the impacts of those disruptions and how they can best be mitigated. Examples of disruptions are not difficult to find. For instance, one consumer packaged goods company told us about a customs strike that led to a breakdown of their supply chain. When customs went on strike in a South American country, no raw materials could be shipped to their plant there. While the plant had planned to carry 3 weeks worth of raw material inventory, they happened to only have 1 week's worth on hand because additional material was in transit. Thus after a week, production shut down at that facility. This was a serious issue, as facility fixed costs and labor costs were still incurred. The product could not be manufactured elsewhere, either; while the same functional product was made at another plant in the company's global network, it was found that packaging and labeling issues meant that plant could not back up the South American plant. When the strike ended after the second week, employees were paid overtime to try to catch upon production. In all, only a few days’ worth of production was not shipped on time, but the total cost to the company was estimated at a million dollars. This example highlights the importance of advanced planning for supply chain continuity, not just individual facility continuity. Aside from having extra raw material inventory, there was no way the South American plant could have continued production. However, if plans had been put in place for the other plants in the company's network to be able to successfully back each other up, the company might have prevented the stoppage in material flow and reduced the overtime needed at the disrupted facility. In the final analysis, what matters is the company's ability to serve its customers. Consequently, supply chains must be examined on a network-level in order to understand their true level of risk-exposure. At the same time, the goal of firm's management efforts should not necessarily be to eliminate risks, it should be to become more risk-informed. In the financial arena, analysts are expected to make investment decisions based on risk, and riskier investments often have the potential for higher returns. Similarly, firms who maintain operations with higher risk levels (low redundancy and lean inventories, for example), may have higher opportunities for being competitive. It is important for a firm to be aware of its supply chain risk levels so that it can evaluate its investments and make decisions based on its own level of risk tolerance.

We presented numerical analysis conducted using a simulation model motivated by an actual consumer packaged goods supply chain in this paper. This supply chain has multiple echelons and facilities and the insights found can be reasonably extended to more complex supply chains. We focused on supply chain disruption risk and tested different strategies for mitigating that risk. The model and tests reflect realistic risks that the firm we worked with faces, and the conclusions are generalizable to all firms that are concerned with maintaining supply chain flow in the face of disruption risk. The results demonstrate the importance of considering risk quantitatively so that management can make risk-informed decisions. This will allow the company to make decisions that better fit their risk appetite. We demonstrated that a systematic approach is required to control the downside of a disruption. Reducing risk at a single location in the network may not be helpful if the rest of the network is too vulnerable; only improving the strength of the weakest links in a chain will increase a chain's strength overall. To minimize the impact of a disruption to their network, firms should invest the time proactively to understand how they could and should react if a disruption were to occur. This will allow them to improve the overall resilience of their system. Future research focusing on establishing practical policies for coping with disruptions in complex systems is needed. Threshold levels for performance indicators that guide when firms should switch into emergency-operations mode would be useful. Systems with tight production constraints at multiple levels could be studied to see how the disruption amplification effect is magnified even more than the results presented in this paper. Multi-echelon supply chains are complex systems, but insights can and should continue to be developed to provide useful guidance on coping with supply chain risk.