Hello everyone. I believe that most of you recall the earthquake and resulting destruction in Nepal last month. As risk managers, it is your responsibility to identify, assess, mitigate and manage risk to avoid your company’s potential loss. We have been asked by RoboCanada to assist the company in selecting a new assembly and distribution hub to better serve the needs of its emerging markets in Kazakhstan, Pakistan and South Korea. With this engagement, we have selected the three most suitable countries for this new assembly and distribution hub.
We have identified ways to mitigate potential risks and pinpointed several additional risk areas outside what is covered in Zurich Risk Room for RoboCanada to consider before it makes its final decision.
We selected Malaysia, Thailand and China from seven countries on the list we were given. We came to this conclusion based on data from the Risk Room ranking and our in-depth analysis of the Risk Floor. We also created our own statistical model to value the potential loss of each country caused by risk factors.
Our initial evaluation indicates that Russia and China are close to each other in terms of overall risk. We then tracked the risk trends from the period 2007 to 2014, and found that China’s overall risk has been decreasing, while Russia’s overall risk has been rising. Moreover, with further analysis of each country’s risk factors adjusting for potential risk mitigation which we will discuss more in depth later in this presentation, we conclude that China would be the better candidate than Russia.
Compared with existing hubs in Canada and UK, it’s easy to tell different countries have different weight on various risk factors. The top three countries are selected based on the overall expected losses which we calculated using data and tools in the Zurich Risk Room. In addition, we argue several factors support our conclusion that these three selected countries can enhance RoboCanada’s supply chain. For example, a hub in the Asia will be closer to the customers in its emerging markets, i.e., Kazakhstan, Pakistan and South Korea and will help to improve customer service. It may also be closer to RoboCanada’s existing factories in Southern Europe and Northern Africa. Additionally, the new hub has advantages in cost of labor, national economy, and transportation.
Is there a way to avoid the risks and potential losses associated with these risks? We certainly believe so. My colleague will introduce the strategies to mitigate the risks.
According to our analysis of data in Zurich Risk Room, we conclude that several risks are seemingly high on the surface but could be potentially mitigated, such as the risks of earthquake, storms and floods, and human rights. We will illustrate this point using China as an example. Raw data in the Zurich Risk Room suggests that China has a higher than normal exposure for all three of these risks mentioned above. But we can mitigate these risks in several ways and thus reduce the overall country risk for China. China is a big country. Not every province has earthquake exposure, so we can avoid and/or substantially reduce the risk of earthquake by locating the hub to an area in China with less severe earthquake exposure. Also buildings can be designed to be earthquake resistant to reduce the severity of losses in the event of earthquakes.
Storm and flood risks can be mitigated by carefully selecting the route of transit and building multiple warehouses in different geographic areas. Human rights risks can be mitigated by seeking higher quality of workplace conditions, better employment practices and hiring procedures. Based on our analysis by using the Zurich Risk Room, we find that mitigation of certain risks reduces both other risks and the overall country risk. For example, lower earthquake risk leads to lower risks of epidemic and infrastructure in China.
In this mitigation process, we analyze over and over again by using our own risk model. The results show that China has lower overall country risk than Russia after taking into account such mitigation. We also have proven that the Zurich Risk Room is a powerful and reliable tool for senior management to analyze risks in a more effective and efficient manner. However, risk room is not a Panacea; it does not consider the risk interactions among countries.
One solution to make the Zurich Risk Room more complete is to use the Mixed Effect Model as this model considers both risk interactions and country interactions at the same time. Moreover, we also recommend our client, RoboCananda assess several additional concerns that my colleague would like to address at this time.
Below we discuss some further concerns that we want to bring to RoboCanada’s attention before a final decision is made. We identified six areas that are significant to RoboCanada and we will highlight those that are of the utmost concern. Over the next five years, cyber attack can cause the highest impact business disruption throughout the world. With the potential loss of customer data, company trade secrets, information about research and development projects, and the damage to the reputation of an organization, this risk can be devastating to a company like RoboCanada and in some extreme cases might put a company out of business.
Next, we looked at additional political issues that RoboCanada must take into consideration. These include government confiscation, seizure under eminent domain doctrines and corruption that is more prominent in some of the countries recommended. RoboCanada also must consider potential supply disruptions due to adverse weather events, volatility of financial markets including the cost of working capital, exchange rate fluctuation and access to credit. Without having undertaken due diligence of these factors facing RoboCanada, we would not have been able to narrow our selection down to these three countries for the location of its new assembly and distribution hub.
We are very much looking forward to working alongside RoboCanada in finding the solutions to address these issues. Our team would like to thank Zurich for your time and the invitation to participate in this challenge and we look forward to assisting Zurich in the next phase of this challenge. Thank you.
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(Mixed Effect Model)
D, David. (2008). Random Effect and Latent Variable Model Selection. Retrieved from :http://www.springer.com/us/book/9780387767208