Practitioners often complain about the huge gap between practice and research related to the estimation of risks. In theory all is easy: A disruptive event just gets a probability and outcome assigned. But in practice these figures most often have to be estimated.
Todays article by Knemeyer et al. (2009) covers exactly this dilemma and tries to answer the question of how to plan for a catastrophe.
This article presents a comprehensive practice oriented framework for managing supply chain disruptions by Sunil Chopra and ManMohan S. Sodhi. The article has been published in the MIT Sloan Management Review in 2004. The framework covers everything from risk analysis to the selection of the risk mitigation strategy.
There are several scientific research centers on supply chain risks in the US (as around the world): The east coast has several researcher on this topic e.g.
In the United States May 2008 was declared to be “Resilience Month” with several congressional hearings on the topic of how to improve organizational resilience on a societal level.
Yossi Sheffi from the MIT is one of the leading researchers on supply chain resilience and he was part of the hearings as well.
Today I want to describe yet another supply chain case study where Monte Carlo simulation is used as decision support for strategic / tactical supply chain decisions.
I am often astounded by the fact how many great articles I haven’t read yet. A good scientific paper contains an comprehensive description of the methodologies used, a theoretical foundation and literature review from which hypothesis are drawn, which are then confirmed or rejected in the course of the paper. And of course, it is always a plus to actually find some results in the course of the analysis.
Today I just want to highlight a short article from “The Conversation” blog at the Harvard Business Review for you to read. The article, which can be found here, was written by Harold Sirkin, senior parter at the Boston Consulting Group.
