Whitepaper: Risk, Resiliency, and Supply Chain Modeling

In the face of ongoing supply network disruptions, it is more important than ever to reassess the risks your organization faces and to prepare for any circumstance. Download this white paper to learn how design and analytics can better equip your organization to understand and prepare for any risk scenario and to give it the flexibility and readiness it needs to weather unforeseen disruptions ahead.  

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Existing Supply Chain Management practices are insufficient to create supply chain resilience

Download this whitepaper to learn:

  • Why most supply chains are susceptible to high-impact-low-probability (HILP) incidents
  • How to evaluate, rank, and prioritize risks and how to determine the implications of risks in the supply chain
  • What type of response your organization should take to mitigate this risk
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In a few short months, the COVID-19 pandemic demonstrated what can go wrong when a prolonged disruption causes sudden swings in supply and demand. From the stockout of commodity items like paper products and canned goods to supply shortages and factory shutdowns, many businesses have endured what is perhaps the most challenging single event in the collective memory. 

As businesses continue working toward a normal state of operations, the lessons learned from COVID-19 bring about the opportunity for many business leaders to reassess and rethink their approach to risk – especially across the supply chain, where proper preparation can go a long way to driving the appropriate response to a disruptive event.

Modern supply chain networks are complex, and their components are highly interdependent. Resiliency and risk analyses – and the selection of effective responses to identified risk scenarios – must be supported with advanced analytics.
Risk, Resiliency, and Supply Chain Modeling White Paper


How is supply chain risk identified?

The general approach to distinguishing risks is to cluster them by impact and probability. Supply chain risk factors include: probability, impact, source, and predictability. After the risks are identified they are then ranked using the SMAUG model and appropriate responses are formulated to terminate, transfer, treat or tolerate the risk.

How can a supply chain model help with risk analysis?

A supply chain model can uncover hidden breaking points in unexpected places – in commodity suppliers, for example, at small nodes, in the network or in ostensibly minor components. Among other insights, such a model can point at assets and processes that are being utilized at capacity, spot single-sourced materials inbound and products outbound, show volume or value concentration at particular nodes, identify bottlenecks in lead times, or quantify the impact of foreign exchange fluctuations on revenue and cost. Such analyses may lead to the discovery of measures to increase the resiliency of the supply chain that are independent of risks and their identified implications. Hence, these may be implemented even if no disruptions to the supply chain are assumed.

What does it mean to have a resilient supply chain?

Supply chain resiliency defines to what extent a supply chain can withstand disruptions. The most common definition of a resilient supply chain is its ability to quickly recover from disruptive events, ideally emerging stronger than before. With disruptions piling up and impacting supply chains more frequently, however, the definition of the resilient supply chain will have to change – it likely will be impossible to recover to an ante-disruption state. Rather, resilient supply chains of the future should have the capacity to continuously morph into new states that enable them to operate under the new (but also temporary) conditions prevailing post-disruption – and do so repeatedly.