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A Measured Approach to Resilience

Risk mitigation planning is often based on “gut feeling” or intuition.
By Jaspar Siu and Santosh Stephen
January 26, 2016

Editor’s Note: Every year, 40 or so students in the MIT Center for Transportation & Logistics’ (MIT CTL) Master of Supply Chain Management (SCM) program complete one-year thesis research projects. The students are early-career business professionals from multiple countries with 2 to 10 years of experience in the industry. The research projects are sponsored by and carried out in collaboration with multinational corporations. Joint teams of company people, MIT SCM students, and MIT CTL faculty work on real-world problems chosen by sponsor companies. In this monthly series, we summarize a selection of the latest SCM research. The researchers for the project described below, Jaspar Siu and Santosh Stephen, developed a framework for assessing supply chain resiliency for their MIT Supply Chain Management Program master’s thesis. The project was supervised by James B. Rice Jr., Deputy Director, MIT CTL.  For more information on the program, visit http://scm.mit.edu/program.

Companies are generally aware of the importance of building resilience into their supply chains, but often find it difficult to actually quantify this increasingly important characteristic. As a result, risk mitigation planning is often based on “gut feeling” or intuition.

A framework for quantitatively assessing the resiliency of each supplier, facility, and location in the supply chain would provide a more systematic approach to resiliency. Such a framework would also give companies a better sense of where to focus their efforts to increase the resilience of their supply chains.

Hybrid approach

Some frameworks already exist, such as the Risk Exposure Index and Value-At-Risk. However, these focus on the loss of revenue incurred when disruptions hit and do not consider the resulting costs.

This research project took a hybrid approach to creating a framework or model that combines quantitative and qualitative of the sponsor company’s supply chain resiliency, and synthesizes these values into a balanced scorecard. The analysis included an in-depth evaluation of the impact of major and minor disruptions at each node in the supply chain on both the demand and supply sides.

For example, when a disruptive event such a tornado or supplier bankruptcy occurs, the productive capacity of the affected node(s) is lost and the company has to rely on downstream inventory for a certain time. When the inventory runs out the company faces sales losses until another supplier comes on stream, and the cost of this exposure was included in the model.

A measure of resilience

The model was used to assess supply chain resiliency for one commodity handled by the sponsor company. The expected business impacts for the company’s suppliers, facilities, and locations were aggregated, and the riskiest entities were identified. Finally, response curves were generated for key parameters such as downstream inventory, and the probability of each node being disrupted was calculated.

Using the Balanced Scorecard of Resiliency (BSR) model, a partial supply chain network resiliency assessment of one commodity was carried out successfully. Moreover, the BSR methodology can be refined by, for example, incorporating other analytical methods, and could yield other insights into the resiliency of the sponsor company’s supply chain.

More broadly, the model can be used to identify supply chain entities that bear the highest risk, evaluate the best mitigation options, and make a business case for investments in improving resiliency.

For further information on the thesis “A Supply Network Resiliency Assessment Framework” and the SCM program contact Dr. Bruce Arntzen, Executive Director, MIT Supply Chain Management Program, at: .(JavaScript must be enabled to view this email address).


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