In a recent HBR piece, Find the weak link in your supply chain, David Simchi-Levi introduces the concept of Time to Survive (TTS). It is the maximum duration that the supply chain can match supply with demand after a node disruption. To determine TTS associated with a specific node, remove the node from the supply chain and calculate how long, using inventory in the pipeline and other available supply sources, you can serve customer demand without that node.
This concept complements Time to Recovery (TTR) which is the time it would take for a particular node, a supplier facility, a distribution center, or a transportation hub, to be restored to full functionality after a disruption. If a node has a TTS greater than TTR all is well, but if it has less it may require a mitigation plan. As you can see from the graph below of [Name Redacted] supplier TTS that appears in HBR - there is a wide range of possible TTS values. Therefore, suppliers with very high TTS are obviously no problem at all but those with TTS around zero can be a potential serious problem that [Name Redacted] is not adequately prepared for.
A common mitigation strategy is to increase inventory—what we call strategic inventory. This should not be confused with other types of inventory which are meant to cover for variability in demand and lead time or are part of the order period process as described in what drives inventory in your supply chain.
Determining the right level of strategic inventory requires understanding:
As we describe in Why do you need more than one optimization tool? this cannot be done using traditional network design or inventory optimization as they do not address these issues. You need to use an optimization process that is specific for assessing disruption in the supply chain as described in From Superstorms to Factory Fires: Managing Unpredictable Supply-Chain Disruptions. This method was the winner of the 2014 Daniel H. Wagner Prize for Excellence in Operations Research Practice.
Many organizations do not think that investing in supply chain risk is worthwhile, as it is hard to show the impact on the bottom line. However, a proven optimization method that quantifies risks may be more palatable to them. Going through this assessment and optimization process could end up saving inventory and other risk mitigation costs currently being practiced without real knowledge of their impact. In addition, the impact of various events and changes in the supply chain can be evaluated on an ongoing basis once the model is set up.
Therefore, deploying risk optimization can provide both cost savings and peace of mind to those responsible for the supply chain.
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