Type of paper: Essay

Topic: Risk, Project, Tree, Decision, Fault, Management, Commerce, Failure

Pages: 7

Words: 1925

Published: 2021/02/11

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Decision Tree Analysis
Discussion of Decision Tree
Fault Tree
Discussion of Fault Tree
Works Cited
House flipping, which is the buying, renovating and selling of property for profit, is a lucrative are of business and has attracted a number of entrepreneurs over the years. Profits can be realized quickly by the simple act of purchasing and reselling the undervalued property. Profits can also be realized by purchasing properties, carrying out renovations and then reselling them at higher prices. However, despite the avenues by which profits can be realized, house flipping is a risky venture. Some of the risks involved in in the business include overpaying for the property, underestimating the costs for repair and renovations, under-estimating the holding time, over-estimating the reselling value and underestimating the cost of buying and reselling the property. Based on the volatility of the industry, risk management has become an integral part in the house flipping industry (ARIMIC, 14). The variety of risks faced in the industry is vast and as a result there are various techniques available to respond to the serious situations. Quantitative risk analysis techniques hold the promise of a thorough measurement and quantification of the risk, which is very vital in the designing of the response mechanism. A project manager may not be able to conclusively plan a response effectively without a comprehensive knowledge of the volume of the risk.
Quantitative risk analysis is an effort to identify the risks carried by a project and predict the critical areas where time and commitment should be dedicated (Mulcahy, 133). It is a process that aims at numerically analyzing the probability of each risk and its consequences on the project’s objectives. Different quantitative risk analysis methods exist and they include: the scenario analysis, decision tree analysis, fault tree analysis and event tree analysis among many others. This paper would discuss the decision tree analysis and the fault tree analysis of risks in the house flipping industry. The decision tree analysis is a simple method used in the process of quantification of risks and often produces features of high clarity. The decision tree analysis takes into account the risk probabilities and the costs or rewards of each logical path of the events or decisions to be taken in future (Aven, 12). It is a method that supports the decision-making process in many businesses. The fault tree, on the other hand, is a graphical method of quantitative analysis that determines the probability and cause of failure. It is an analysis in which the undesired state of a system or project is analyzed in order to identify why projects or systems fail and identify the best ways to reduce risk. The fault tree analysis assumes that all system failures are binary in nature.
11. Decision Tree Analysis
A decision tree analysis is a method that can be used by project managers to make good decisions especially in the cases where the decisions to be made involve high risks and costs. A decision tree uses a graphical approach to compare the competing alternatives and assign values to those alternatives through the combination of costs, uncertainties and payoffs into particular numeric values. The decision tree analysis is well suited for risk analysis in project management and has been extensively used with additional efforts being made to solve the problem of interrelated risks. Through the use of this method, a number of decision alternatives can be taken into consideration and also taking into account the probability of different scenarios of events. While the process of decision making is usually a difficult one, the specific difficulty in making these decisions is that the results of choosing from the available possible alternatives may be unknown. The bottom line in this method is that project managers can choose one alternative from very many possible alternatives.
With regards to investment activities, such as house flipping, a decision tree would describe an action; describe its outcomes and the probability of possible result achievement. Decision trees would include the cost of each choice and the probability of occurrence, and as a result it would assign a value and an outcome. From these values and outcomes, a decision can easily be arrived at based on which risks are likely to occur and result in huge costs to the project. Decision trees are able to help in the formation of a balanced picture of the risks and rewards that are associated with every possible course of action taken. Decision trees can be applied in different project management situations such as project risk management. This method is an effective quantitative risk analysis approach for risks that are sequential (Aven, 13).
In relation to the project, house flipping, a number of risks are present that may have a significant effect on the projects goals; which is making profits. The project is exposed to a number of risks that include: the likeliness to underestimate the level and cost of repairs required, underestimating the holding time, overestimating the reselling value, overpaying the contractor before the completion of a sufficient level of work and the likeliness to underestimate the costs of buying and reselling. All these risks have a significant effect on the project and may lead to the collapse or failure of the project if appropriate measures are not taken to mitigate them. In carrying out a risk analysis using the decision tree, the risks would be categorized in terms of their probability of occurrence, area of impact (cost, scope, schedule, and quality) and the level of impact. Under the category of probability of occurrence, the risks would fall into frequent (will occur occasionally unless measures are taken to mitigate), likely (could occur less frequently if mitigation actions are taken), occasional (occur sporadically), seldom (rarely would they occur) and improbable (not likely to occur). The area of impact would relate to the risks effect to the cost of the project, scope, schedule or quality. The level of impact of the risk is categorized in terms of catastrophic (would lead to collapse of the project), critical (may not lead to a collapse of the project but may harm huge parts of it), moderate (might harm but can be corrected easily), minor and negligible. A simple logical path on the decision tree would reveal that the major risk related decision would be the one that is most likely to occur, may have a huge impact on the projects budget, schedule and scope, and may hurt or lead to the project’s collapse.
111. Decision Tree Discussion
The decision tree reveals a number of logical paths that a person engaging in the house flipping business can use in the management of risks. All these paths indicate the impact, cost and probability of the risks likely to be encountered in house flipping industry. The risk of likeliness to underestimate the costs of repairs may occur frequently, would impact cost and quality its level of impact is critical. Underestimation of holding time occurs occasionally, impacts the project’s schedule and would moderately impact the project. Overestimation of the reselling value is an occasional risk, would affect the project’s performance and would be catastrophic to the project if not mitigated. The risk of overpayment to a contractor before completion of a project seldom occurs, would affect the projects budget and would critically impact the project if appropriate measures are not taken to mitigate it. Lastly, the likeliness to underestimate the costs of buying and reselling is a risk that frequently occurs in the industry, would affect the project’s performance and is catastrophic to the project if not mitigated.
The logical path to be taken by a project manager or the major risk related to the project that requires much time and commitment as revealed by the decision tree is the likeliness to underestimate the costs of buying and reselling of the property (Hullermeir, 8). From the number of risks mentioned in the decision tree, the risk of underestimating the costs of buying and reselling falls under the category of frequent. This means that the risk would occur occasionally and would continue to occur unless the project manager takes the appropriate steps to mitigate it. On the level of impact path, this particular risk impacts the performance or quality of the project; meaning that the project may fail or experience losses if this particular risk is not mitigated. With regards to the level of impact, the risk falls under the category of catastrophic. This would imply that if appropriate measures are not put into place to mitigate it, the project would most likely collapse. As a result, underestimation of the costs of buying or reselling is the major risk related to the project. In as much as the other risks have a significant impact on the project, mitigating and dedicating time and commitment on the risk of underestimation of the value of buying and reselling is the best decision in relation to house flipping.

1V. Fault Tree Analysis

The fault tree analysis (FTA) represents a deductive approach that is used to determine the causes contributing to a designated failure in a system or project. FTA begins with the definition of a top or the undesired event and branches further into intermediate events until the undesired event can be conclusively be defined by the basic events. Hence, a can be defined as the event for which a development further in it would not be successful to the project goal or purpose (Cepin, 4). For example, a fault tree may show that the probability of failure can be determined without the development further of the failure logic and hence there would be no reason further development. In FTA, the undesired event is usually defined in terms of its immediate causes. The immediate causes are continually resolved until the basic causes of failure are identified. The logical diagram, the fault tree, is drawn to show the logical relationships in the events. The fault tree clearly shows the all the different types of relationships that are necessary to create the undesired event, the top event. For a fault tree to be constructed, a detailed and thorough understanding of the logic and the basic causes leading to the undesired event. The fault tree provides a good way of carrying out a quantitative and qualitative evaluation of the undesired event (Cepin, 6).
An FTA analysis is usually carried out to identify the causes of failure in a project and also identify the specific weaknesses in the system. It further goes on to identify the likely effects of human error, identify the greatest contributors of failure in a system and identify the key areas that would need an upgrade. An FTA analysis also optimizes test and maintenance to a system or project. In project risk management, an FTA is usually carried out to identify the causes of failure in a project. Through the usage of data on the probability of causes of failure, the probability of a projects failure is determined. With regards to the project in question, house flipping, a number of potential risks may be involved in the collapse of the project. Such risks include overestimating the reselling value and the likeliness to underestimate the costs of buying and reselling the property.
A simple logical analysis to the causes of failure of house flipping projects identify the risks of overestimating the reselling value and the likeliness to underestimate the costs of buying and reselling as the ones that would have a catastrophic level of impact on the project. This means that in the event that these two risks occur without any mitigation, the resultant effect is the collapse of the project. As a result, the undesired event or the top event on the fault tree would be the failure of the project which would be brought about by the project’s exposure to these two catastrophic risks. The two catastrophic risks are the immediate events that lead to the failure of the project and hence a fault tree would identify the basic events that lead to these risks which ultimately lead to the collapse of the project.
V. Fault Tree Analysis Discussion
VI. Conclusion
As discussed above, the ability to identify the root causes of particular events and the ability to predict the likelihood of occurrence of particular happenings is a key component in the process of risk management. Quantitative risk analysis methods, such as the decision tree analysis and fault tree analysis, measure and quantify the risk hence enabling the designing of a sound response (Zio, 13). A decision tree would inform a project manager of the correct and best course of action to pursue in relation to risk management. A fault tree, on the other hand, provides the mechanisms of identifying the best ways of limiting and avoiding the risks that may be catastrophic to a project. House flipping, being a very volatile industry can turn out to be a more lucrative business venture for entrepreneurs if they took measures to analyze the risks using the quantitative risk analysis methods.
Works Cited
AIRMIC. A Structured Approach to Enterprise Risk Management (ERM) and the
Requirements of ISO 31000. 2010. Web.
Aven, Terje. Risk Analysis: Assessing Uncertainties Beyond Expected Values and Probabilities. Chichester, England: Wiley, 2008. Internet resource.
Čepin, Marko. "Fault Tree Analysis of Substations." Advances in Safety, Reliability and Risk Management. (2012): 1307-1370. Print.
Hullermeier, E. "Experience-based Decision Making: a Satisficing Decision Tree Approach." Ieee Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans. 35.5 (2005): 641-653. Print.
Mulcahy R. Risk Management. Tricks of the Trade for Project Managers. RMC Publications, Inc., Minneapolis (2003). Print.
Zio, Enrico. An Introduction to the Basics of Reliability and Risk Analysis. Singapore: World Scientific, 2007. Internet resource.

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Risk Management Essay Samples. Free Essay Examples - WePapers.com. https://www.wepapers.com/samples/risk-management-essay-samples/. Published Feb 11, 2021. Accessed May 12, 2021.

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