Case Study Phase 3

Dr. Karmaveer Koonjbearry

August 13, 2021

Case Study Phase 2

Generally speaking, a risk is defined as the chance that a certain loss would occur. These losses are the result of attacks that expose weaknesses in the system (Lave, 2013). Every business organization is exposed to risks, and the consequences of these risks differ from one company to the next. Some dangers are of significant size and have the potential to bring the company to its knees (Lave, 2013). Other risks are insignificant in terms of their effect, and they may be disregarded since the cost of providing a remedy is more than the cost that would be paid if the risk event happens. Risk assessment methodologies are used to quantify the related risk that may arise once components have been identified and classified separately.

In conducting a risk assessment technique, two types of data are collected: quantitative and qualitative (Lave, 2013). It is necessary to apply the quantitative approach when data can be entered into preset formulae. At the same time, the qualitative methodology is necessary when we do not have access to real facts related to the danger we are investigating (Lave, 2013). To calculate costs and the two main data points, likelihood and impact, we would need subject matter experts to establish averages or views, which we would then have to use in conjunction with the other data points.

To apply our technique to the example of the General Motors Corporation, we shall use a quantitative methodology. We can see that when we look at a company as large as General Motors, there would be a significant quantity of data to analyze (Williams, 2020). Inside the quantitative method, we will focus on the annual loss expectation (ALE), which is a tool for determining how much money might be lost in a year if a problem is not immediately managed. More than 10 million vehicles are produced by General Motors each year, and the company gets more than 100,000 unique components from 5,500 supplier locations across the globe (O’Byrne & Young, 2017).

The company sells its vehicles in more than 100 countries (O’Byrne & Young, 2017). It is sufficient to state that General Motors' global manufacturing organization runs like a well-oiled machine. However, like with any automobile manufacturer, there is a lot that may go wrong. Manufacturers such as General Motors are subjected to various interruptions, ranging from political upheavals to severe weather occurrences to worker strikes and supply shortages.

The earlier the SCRM team can communicate issue information to General Motors' worldwide crisis managers, the sooner the business can address such problems before consumers are adversely impacted (O’Byrne & Young, 2017). Rossi depended on a geographic information system (GIS) to map the relationships between GM's hundreds of tier 1, tier 2, and tier 3 suppliers to do this. The technology allows the team to concentrate on a particular component and track it from its source to its destination plant and vehicle programs in an emergency, such as a factory fire or a storm.

To comprehend how a certain event would affect GM's supply chain, Rossi believes that knowing the company's supply network is critical to the company's success (Chiappinelli, 2019). Knowing which cars might be affected by an event—which part numbers, particularly which plants—allows us to develop a more effective approach strategy. It took days or weeks to fully grasp the effect of a crisis on providers, components, projects, and cars before implementing the location intelligence system. Still, the procedure was very comparable to what it is today.

References

Chiappinelli, C. (2019). GM Uses Location Technology to Mitigate Its Supply Chain Risk. Esri. Retrieved from https://www.esri.com/about/newsroom/publications/wherenext/gm-maps-supply-chain-risk/

Lave, L. B. (2013). Risk Assessment and Management. Springer Publishing.

O’Byrne, S. F., & Young, S. D. (2017). The Evolution of Executive Pay Policy at General Motors, 1918–2008. Journal of Applied Corporate Finance, 29(1), 36–49. https://doi.org/10.1111/jacf.12219

Williams, C. (2020). Identifying Future Risks - 7 Techniques Used by One of the World’s Largest Automakers. Carol Williams. Retrieved from https://www.erminsightsbycarol.com/techniques-for-identifying-future-risks/