University of the Cumberlands Enterprise Risk Management Discussion


Please read below student posts ,reply each in 150 words.
Surrender – ERM at General Motors
1. How could GM use game theory to identify and assess the major risks to this decision?
GM will use the game theory to combine and assess both the previous ideas of the
traditional vehicles and the electrical ones and with this information, the game theory
will enable them to check the strengths and weakness of both sides and thus be able to
make better decisions on what to choose from (Fraser et al., 2014). This form of
evaluation will enable them to discover the risks associated with both decisions and
thus if switching one of their traditional models to an electric one is associated with
higher-level risks then most definitely the game theory will help the company to avoid
making such decision mainly because it may lead to serious consequences at the end
of everything.
2. Identify two major risks that would result from GM converting an existing line to an allelectric line.
There is a risk to financial strain mainly because it means that the company will have to
use a lot of money to convert the traditional line to an all-electric line and if the idea
does to work or does not produce the intended benefits then it means that the company
would have incurred serious losses (Fraser et al., 2014). The second major risk is the
fact that there would exist a collision or differences in ideas from the two lines which
might make the process of conversion too long or the process might experiences some
form of delays mainly because these are two kinds of vehicles and it requires an indepth analysis in order to understand the necessary steps to take so as to make the
overall process successful.
3. Provide a brief discussion of each risk, and your assessment of the levels of inherent, current,
and residual risk, using GM’s five-point scale.
The risk of financial strain would be brought about due to the actuality that the process
of conversion might require a lot of money to be made success and because when it
comes to inherent, I believe it would be a permanent loss mainly because it will not be
easy to recover the money that and because of this I will assign it a critical scale mainly
because when the process has begun it means the finances used will not be recovered
(Fraser et al., 2014). When it comes to the current or present-day financial risk I will
assign it a minimal level scale mainly because the process has not yet begun and finally
when it comes to the residual financial risk, I will assign it the critical risk scale mainly
because the risk would have taken place and cannot easily be reversed. The difference
in ideas is a risk that may lead to delays when converting from one line to another and
thus because of this, when it comes to inherent I would assign this risk as critical mainly
because if the process had been performed it cannot be reversed. When it comes to
current risk I would assign it a minimal scale mainly because the process has not yet
taken place and finally, when it comes to residual I would assign it a critical scale mainly
because the process has already taken place and thus cannot be reversed.
4. Would these risks be the same for an educational institution? Why or why not?
These risks would not be the same for an educational institution mainly because
education is fixed, there is normally no need to convert from one thing to another
(Fraser et al., 2014). Education has actually remained the same for a very long time.
Hammad – How could GM use game theory to identify and assess the major risks to its decision?
Each decision is influenced by the cost benefit analysis. While changing one product line to
electric vehicle, GM could see the existing market share of current product line and the potential
of electric vehicle market. It should also look at the profitability being offered by existing
product line. It should look at the contribution in total revenue of the product line which is being
replaced. It could also see if the current product is market leader, which is being replaced
(Hopkin, 2018).
Two major risks from GM converting an existing line to all product line.
There could be a major operational risk while changing from the current to the new product line.
If the existing conditions are not able to handle the new technology which will come in place of
existing, operational efficiency will go for a toss. Another type of major risk could be the
strategic risk which the organization could face. If the market is not yet ready to pay the cost as
an electric vehicle demands, this could be a strategic failure (Hopkin, 2018).
Description of each risk.
The operational risk could arise from the fact that the current systems are not able to handle the
load of the new products and are not operationally efficient.
The strategic risk is a risk which general motors could deal with due to changing strategy. If the
strategy does not fall right, it is a failure. In changing to EV, the level of residual risk is very
high and level of inherent risk is low. If we analyse against the five forces, we can see that threat
of new entrants is not very high initially. Bargaining power of both buyers and supplier is low.
Threat from substitute products may be high since people may not be ready to pay premium and
rivalry among existing players is low since its new to market product. So, all factors seem
favourable except threat of substitute products (Fraser & Simkins, 2016).
Would risks be same for educational institution.
The risks would not be the same for an educational institution. The risk for an education would
be high in terms of overall cost and infrastructure requirements and faculty requirements (Fraser
& Simkins, 2016).
Manasa – General Motors Case Study
General motors company is a multinational corporation that dominates that has
dominated the automotive industry for many years. General motors have concentrated
on designing, manufacturing marketing and distributing vehicles and the process seems
never-ending. General motors company is not only the largest automobile in America
but also in the whole world. The idea to redesign the traditional lines to electric can
leads to various benefits and risks as well.
However, General Motors can apply the concept of game theory to analyze
potential risks that emerge from the introduction of electric vehicle models. Game theory
is a branch of algorithm concerned with evaluating competitive situations. Game theory
deals purely with rational decisions. General Motors can use game theory in
announcing a sustainable electric vehicle power-driven by electric emission. Through
game theory, the company enlightens customers’ performance of the electric model that
would surpass the ordinary traditional vehicles.
The typical risk that may emerge as a result of designing the electric vehicles is
customers failing the purchase the new models. Customers may not trust the electric
models. They may fear engine malfunction hence refraining from purchasing the new
cars. Moreover, customers may disregard electric models because of their small sizes.
Customers not purchasing the vehicles can result in significant losses in the company
Cost is also a significant risk to consider. Many individuals may perceive the
electric cars to be extra expensive comparing its size. People may not realize the
benefit of saving gas expenses. Moreover, other people may presume the cost of
charging a vehicle e are more than fuel expenses.
Risks in General Motors differ with those in the educational institutions because
the two sectors have different objectives. General motors focus on making profits.
Therefore, the risk related to the company is revenue-related. In contrast, risk in
educational institutions focuses on academics.
Nikhitha- Ethics:
It is defined as a set of moral principles or the process of governing a group or as an individual. There is an impact
of human behavior with the introduction of new technologies, where these new technologies give us the ability,
which is not there before, that make the surroundings and the situations which are not particularly mentioned in

ethical terms. For example, digital technologies have shown us the capability to collect information to create profiles
for people from various sources. Whenever we want to access our information, it will be made available using
digital technologies.
Big data is one of the new technologies that cause ethical issues, particularly when the companies start to externally
monitor their data for the purpose which is different from the data that is collected initially. By conducting analytics,
the ethical framework will be changed completely. There are some of the principles which are still confused to agree
with or not.
Based on legal requirements, private data should be audited, but the data should not be shared or exposed to other
business organizations, which is collected from the individuals to trace their identity.
Third-party organizations share some of the personal data such as, medical or financial information that should be
kept confidential. They must have some restrictions on how the information needs to be shared.
Customers should have the knowledge of how their data is used and the capability to maintain their information over
the third-party systems.
Big data can view and determine how we make up our minds. Business organizations should start thinking about
what type of inferences and predictions need to be allowed and which are not to be.
Similarly, there are a few more principles which we need to build as the biggest technology to become available.
People, in the long run, go away when they did not find ethics are following in their organizations.
Sharubala – Ethics in Information Technology
The term ethics is best described as a “set of moral principles” or “the principles of conduct governing an individual
or a group” (Bourgeois, 2019), a fix is not only needed for the normal companies or for the society, with the
increased nature of information technology ethics is also needed to be followed for protecting our customers
information as well. This is important is because people in the current era using computers to do all the regular
activities more than in the previous decade, meaning people purchase/shop everything online, so it is very important
for every information technology firm to protect their own customer’s data. If the data is not being protected well it
may lead to a breach of privacy of their customer to a specific firm, in order to emphasize this privacy protection
there are a lot of ethics and code of ethics has been developed recently to protect the sensitive information.
Talking about Big data, it receives a lot of attention the big data is best described as the combination of
greater size and complexity of data with advanced analytics, and it has been effective and improving the national
security marketing more effective, reducing the risk of credit, improving the research and facilitating the urban of the observable characteristics of big data combines information from diverse sources in a new way
to create knowledge, to make better prediction and also help improve services. Big data help the government to
better serve their citizens make the hospital as a safer place make field firms extend credit to those previously
excluded from the market, they also help in law enforcers to catch more criminals and nations are safer. YET big
data has also been criticized as a breach of privacy as potentially discriminatory as distorting the power relationship
and is just creepy, so in general, companies create this big data from complex data set and using new prediction and
generalizations firms making use of big data have targeted individuals for product they did not know they needed to
ignore the citizens when repairing states informed friends and family that someone is pregnant or engaged and
charged consumers more based on their computer type.
I suggest big data is analyzed as if as an industry in whole in order to identify the systemic risk in current big data
practices such an approach that route situates big data within a larger system of forms organizations processes on
norms for analysis the volume variety in velocity of the data plus the novel analytics required to produce actionable
information renders big data at difference in kind rather than a degree to create and use this large datasets to
maximum effort many firms aggregate data to create a new whole data set and still access to their new data
set(Martin, 2015).

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