Course Work On Management Decision Making

Published: 2021-06-18 06:10:32
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Category: Company, Internet, Water, Oil, Model, Decision Making, Decision, Sea

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A multinational oil company is faced with the dilemma of either investing in a new oil rig which is currently open for bidding, or refurbishing its existing oil rigs. For the company to make the right decision, it must first start by computing the Expected Value of each of the available options. According to Hardman (2013, pg. 56), the Expected Value of a given variable is defined as the weighted-probability average of its possible outcomes. This definition implies that the Expected Value of a variable is the total product of the variable and the given probability of a specified outcome taking place at a specified period.

- Bid for new oil rig with the probability of high reserves

According to this option, the corresponding Expected Value is equal to 1500 * 0.6 = 900M Pounds. This Expected Value implies that the company would earn a total of 900M Pounds if it was to invest 750M Pounds in the new oil rig, and that the reserves turned out to be high.

- Bid for new oil rig with the probability of low reserves

According to this option, the corresponding Expected Value is equal to 500 * 0.4 = 200M Pounds. This Expected Value implies that the company would earn a total of 200M Pounds if it was to invest 750M Pounds in the new oil rig and the reserves turned out to be low.

- Build New Oil Rig

This option would require the company to invest 250M Pounds in a new oil rig which is expected to boost production by 150M. This option implies that the maximum bid the company can place would be 500M for the bid, and 250M for the oil rig if the oil reserves turn out to be high.

- Move an existing oil rig

This option would cost the company 100M Pounds but it would not yield any additional benefits to the company other than improving its operational efficiency. In this regard, the company would be able to place a bid of 650M Pounds and remain with the 100M pounds required for the oil rig move. This higher bid would further increase the company`s chances of acquiring the new oil rig.

- Refurbish its existing oil rigs before making the new bid

According to this option, the company has a 50% probability of generating 5% return on its 750M Pounds investment and a 50% chance of generating a 10% return on the same investment. In this regard, the Expected Value of this alternative is equal to (0.5 * 750 * 0.05) + (0.5 * 750 * 0.1) = 56.25.Therefore, this option implies that the company would be able to earn 56.2M Pounds as the return on its 750M Pounds investment in the refurbishment of its existing oil rigs.

- Refurbish its existing oil rig after the bid has been made

According to the above alternatives, the company should choose the option that yields the highest Expected Value. In this regard, this option is the bidding for the new oil rig with a probability of a high level of reserves. Accordingly, the company is expected to generate 900M Pounds through this alternative.

Multiple Criteria Decision Analysis (MCDA)

According to Ishizaka (2013, p.200), the Multiple Criteria Decision Analysis approach entails the process of putting into consideration several factors and criteria in the decision making process. This approach is characterized by the consideration of each of the available criteria to determine their impact on the underlying subject matter. Once these considerations are made, a conclusive decision which incorporates all these criteria is subsequently arrived at by the parties involved in the decision making process.
There are several methods that are used in the Multiple Criteria Decision Analysis approach. Some of these main methods are discussed in detail below. Their suitability in regards to the North Sea project is also highlighted in the discussions.

- Value Engineering

According to Hermes (2012, pg. 189), Value Engineering is a MCDA method which entails the process of improving the value of goods and services produced by a business entity through the statistical and scientific examination of its production function. Pries (2013, pg. 306) adds that this value is computed as a ratio of the production function to the corresponding production cost. Therefore, according to AASHT (2010, pg. 16), value engineering entails the increasing of this value through the dual process of either improving the production function, or reducing the production costs.

According to Hermes (2012, g. 193), the Value Engineering method is characterized by a job plan which is comprised of four main components. The first component is information gathering, which entails the collection of all the relevant information relating to the available option. The second component is the creation of alternatives that may be applied instead of the current option under consideration. The third component entails the evaluation of the chosen alternative to determine its overall suitability to the given scenario. Finally, the fourth component entails the presentation and implementation of the chosen alternative (Hermes, 2012, pg. 193).

The Value Engineering method can be applied in the North Sea project since it primarily focusses on the reduction of production costs such as those highlighted in the setting-up of the oil rigs in the North Sea project.

- Weighted Sum Model (WSM)

The Weighted Sum Model is the preferred method which will be applied in the North Sea project. It is discussed in more detail in a subsequent section below.

- Measuring Attractiveness by Categorical Based Evaluation Techniques (MACBETH)

According to Bouyssou (2013, pg. 87), the MACBETH method is a qualitative MCDA approach which entails the making of objective judgments about the main factors or criteria that characterizes the main available options of a decision making process. Lytras (2010, pg. 412) adds that this method interrogates and questions two of the available elements of the decision at a time. According to Gomez (2012, pg. 323), the MACBETH method is mainly based on software applications that subsequently conduct the evaluations and questioning of the elements.

The interactive nature of this method and its approach to question pairs of alternatives sequentially enables it to effectively gauge the suitability of each of the available options and to generate decisions that best reflect the given characteristics and factors of the scenario at hand. The fact that this method is software-based also implies that it enables its users to conduct further statistical tests that may be used to provide more information needed to choose the most suitable option (Gomez, 2012, p. 328).
This method may not be the most suitable for the North Sea project due to the limited decision elements associated with this project.

- Analytical Network Process (ANP)

The Analytical Network Process is a MCDA method which structures a pre-existing decision problem into a network which is characterized of alternatives, criteria of decisions and overriding goals (Zhou, 2012). Subsequently, the available alternatives are then ranked based on the findings of the pairwise comparisons that are used to measure each of the components of the network (Desheng, 2010, pg. 350). The Analytical Network Process is similar to the Analytical Network Hierarchy method, with the main distinction between the two methods being that the former is based on a network while the latter is based on a defined hierarchy (Zhou, 2012).

According to Saaty (2013, pg. 256), one of the main advantages of this method is the interdependent nature of each of the elements that are considered in the decision making process. This feature is also a significant difference between this model and the Analytical Network Hierarchy method, which considers each of its elements to be independent of one another (Desheng, 2010, pg. 354). Therefore, this method may be suitable for application in the North Sea context.

- Evidental Reasoning Approach (ER)

Evidental Reasoning is a MCDA method that is used to solve problems that contain both qualitative and quantitative elements in their core structure (Sun, 2013, pg. 614). As the name suggests, this method mainly relies on the ability to collect strong evidence related to the underlying elements of the problem at hand (Lederman, 2014, pg. 888).
According to Lederman (2014, pg. 890) and Sun (2013, pg. 616), there are several advantages that are associated with the use of this method in the Multi Criteria Decision Analysis process. The first advantage is the increased reliability associated with this method due to its application of a decision belief matrix. Secondly, this model is capable of accepting different formats of data and can therefore, be used in a wide variety of contexts. Thirdly, this method enables its users to incorporate any available information into the on-going decision making process. Finally, this method has the ability to enable information to be presented in a more informative format when compared to the other alternative MCDA methods.

According to Doumpous (2013, pg. 232), this method is the most suitable for problems that are faced with uncertainty since it applies a belief decision matrix to resolve such problems. As a result, this method may not be suitable for the North Sea project since the project is not faced by high levels of uncertainty.

North Sea Project – Weighted Sum Model (WSM)

As previously mentioned, the Weighted Sum Model is one of the most suitable methods of Multi Criteria Decision Analysis which can be applied to the North Sea project decision making process. According to Albright (2010), pg. 980), the main basis of suitability of this method is the fact that it is applied in contexts where all the elements involved are expressed in the same units of measurement. This criterion applies to the North Sea project because all the variables are expressed in millions of British Pounds as the underlying measurement scale.

According to Silva (2013, pg. 369), the Weighted Sum Model allocates corresponding weights to the variables in question so as to determine the effect that such weights will have on the overall decisions made. These weights are based on various factors such as probability distributions. In the North Sea project context, these weighs are represented by the various probabilities given in the case. These probabilities include the likelihood of high oil reserves, the likelihood of successful bids and the likelihood of generating a return on investment among many other such probabilities.

Through the Weighted Sum Model, these probabilities will be applied to their corresponding events respectively and this process generates a weighted average value of the underlying decision element (Eiselt, 2013, pg. 407). In the North Sea oil rig project, this weighted computation is best reflected by the calculation of the Expected Value of the project`s return, given a scenario of high oil reserves and a corresponding scenario of low oil reserves. The weighted values are then cumulated together to generate values whose weights when summed together are equal to 100%. These values represent the total value of the project, given the probability of different events taking place in a mutually-exclusive fashion.

According to Albright (2010, pg.980), the Weighted Sum Model is characterized by several alternatives that are represented by the character m, and several decision criteria that are represented by the character n. In this regard, the formula for a decision denoted as A1, given m alternatives and n decision criteria is given as:
(Silva, 2013, pg. 370)

As a general rule, the Weighted Sum Model requires that the most suitable alternative which will be chosen among the available alternatives should be the option that yields the highest performance value according to the above formula. This proposition implies that the Weighted Sum Model is a quantitative method whose overall basis of the suitability of an option is a higher quantitative value when two available options are compared to one another (Eiselt, 2013, pg. 408).

The application of the Weighted Sum Model in the North Sea project context implies that the best alternative which the company should choose is to bid for the oil well and to acquire a new oil rig if this bid succeeds. This alternative is informed by the fact that it has the highest maximum value in quantitative terms when compared to all the other available options for the company.

In general, the decision making process in the North Sea project context and in other business scenarios is largely dependent on the decision makers ability to collect, interpret and analyze the available information relating to the underlying problem. This proposition implies that the above MCDA methods only play a limited role in the decision making process. Ultimately, the ability of the decision-maker to decipher this available information and to apply it appropriately within a business context determines the effectiveness and quality of the decisions made using the above methods. Therefore, the concerned decision makers must take all the necessary steps to ensure that their decisions reflect all the available information, and that the decisions are suitable for the specific business context currently at hand.

Reference List

Albright, S., 2010. Data Analysis and Decision Making. London: Cengage Learning.
American Association of State Highway and Transportation Officials., 2010. Guidelines for Value Engineering. New York: AASHT.
Bouyssou, D., 2013. Decision Making Process: Concepts and Methods. New York: John Willey and Sons.
Desheng, D. W., 2010. Modeling Risk Management in Sustainable Construction. New York: Springer Science and Business Media
Doumpos, M., 2013. Multi-criteria Decision Aid and Artificial Intelligence: Links, Theory and Applications. New York: John Willey and Sons
Eiselt, H. A., 2013. Decision Analysis, Location Models, and Scheduling Problems. New York: Springer Science and Business Media
Gomez, J. F., 2012. Maintenance Management in Network Utilities: Framework and Practical Implementation. New York: Springer Science and
Business Media
Hardman, D., 2013. Judgment and Decision Making: Psychological Perspectives. New York: John Willey and Sons
Hermes, A., 2012. Value Engineering Synergies with Lean Six Sigma: Combining Methodologies for Enhanced Results. NJ: CRC Press
Ishizaka, A., 2013. Multi-criteria Decision Analysis: Methods and Software. New York: John Willey and Sons.
Lederman, N, G., 2014. Handbook of Research in Science Education. New York: Routledge
Lytras, M. D., 2010. Organizational, Business, and Technological Aspects of the Knowledge Society. New York: Springer Science and Business
Media
Pries, K. H., 2013. Reducing Process Costs with Lean, Six Sigma, and Value Engineering Techniques. NJ: CRC Press
Saaty, T. L., 2013. Decision Making with the Analytic Network Process: Economic, Political, Social and Technological Applications with Benefits,
Opportunities, Costs and Risks. New York: Springer Science and Business Media
Silva, R. N., 2013. Intelligent Decision Technologies. NJ: IOS Press
Sun, F., 2013. Knowledge Engineering and Management. New York: Springer Science and Business Media
Zhou, X., 2012. Fuzzy Analytical Network Process Implementation with Matlab. NJ: INTECH Open Access Publisher

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