BUSN11079 Analytical Thinking and Decision Making Assignment Sample 2023
Introduction
The present report will provide an outline of practical decision scenarios and the limitations and strengths of the analysis. In this report, there will be four segments as the significance of decision making and the implementation of decision analysis, decision problem relating multiple objectives, application of SMART on the outline of a decision problem, and The limitations and Strengths on the analysis of decision problem.
The present report will discuss the key objectives and the importance of decision-making. The study will focus on the technique of multi-attribute rating on discussing the multiple objectives that are related to the topic of the report.
Question 1: Significance of decision-making and the implementation of decision analysis
The matters that are relating to organizing, planning, control, coordination, and directions are resolved through decisions by managers in an organization. As per the opinion of DeRousseau et al. (2018), decision-making is an important part for all organizations to achieve their success. The total managerial process and management system are based on decisions.
There are few principles in decision making such as decision making of subject matter, the structure of an organization, analysis of policies and the objectives, alternative analytical study, proper communication. Understanding the impact of a decision, sufficient time, and flexibility of mind are also few important principles in decision-making (Dileep, 2020).
In any organization, decisions are an important factor for growth and success. In the process of planning, decision plays an important role. Effective decision-making is always important in the managerial process (Duan et al. 2018). Making good decisions is the most effective is the skill and the key to business growth.
Decision-making is always an important factor to build a better environment of success. The work process can run smoothly and a company can achieve its goal by making the right decision. As stated by Guarini et al. (2018), making accurate decisions enables and increases the scope for an organization.
Tools of decision-making
Figure 1: Tools of decision-making
(Source: Duan et al. 2018)
SWOT Diagram
The diagram of SWOT stands for threats, weaknesses, opportunities, and strengths. In any organization, this diagram helps to measure their current situation. The organization can use this diagram in decision-making by analysing its current situation. Any organization can use the SWOT diagram by using the tool of Creately.
Create is the easiest way to create the diagram of SWOT. In the tool created, an organization can keep its almost 100 SWOT diagrams and can customize their diagrams at any time (Kumar et al. 2017).
Decision-making diagram
Decision-making diagrams work as a graph that enables an organization to design the decisions that they have taken. That diagram helps an organization to analyse its decisions and can measure the outcome and risks. An organization can use this diagram for planning its team strategy. The important tool of decision-making diagrams in lucid chart.
It helps an organization to examine the outcomes and to identify the potential paths. As stated by Liao et al. (2018), any organization can use this tool of lucid chart in making their decisions and in analysing them. Examining the outcomes and measurement of risk will enhance the probability of success of any organization.
Decision matrix
The technique of decision matrix helps an organization to analyse and identify the performance of the system. This technique shows results based on a few specific criteria. The tool that helps an organization to use a decision matrix is MindTools. MindTools convert the data of any organization into rows and columns (Mardani et al. 2017).
This tool helps an organization in making appropriate decisions and enables a company to provide scores in every segment from zero to five. In MindTools, the score of zero indicates poor and the score of five indicates very well.
Pareto Analysis
The method of Pareto analysis helps an organization for possible changes in their decisions by identifying their problems and analyse them. An organization can use this method by using the tool of visual paradigm. As stated by Marttunen et al. (2017), it helps an organization to put their data in a Pareto chart easily to make decisions.
Cause and effect diagram
The diagram of cause and effect helps an organization to find out the causes of any particular event. In the design of any product and measuring its quality to recognize the possible factors of causing, any organization can use this diagram. Any company can use this diagram though using the stool of Smart Draw. Smart draw helps an organization to draw the diagram of cause and effect online or on any desktop.
The tool also provides support for windows and Mac operating systems (Mardani et al. 2017). The diagram of cause and effect helps an organization to find out the approximate effect in making decisions. Any organization can use this diagram in making approximate right decisions.
Force Field analysis
Force Field analysis helps an organization to examine its project. This analysis provides the influencing factors of a particular situation. The analysis helps an organization to understand its process in a better way. As stated by Liao et al. (2018), a company can use force field analysis by using the toll of Smart draw. Smart draw is a decision-making tool and provides templates of force field analysis.
Break-even Analysis
Break-even analysis helps an organization in understanding the most profitable stage of a new business product. It helps in measuring the number of services that the company has to cover for profit. As stated by Liao et al. (2018), any company can use this analysis by using the tool of good calculators.
Question 2: Decision problem relating multiple objectives
Every organization or business faces many challenges, risks, and difficulties while making any decisions regarding its managerial process. Making good decisions helps an organization to reach its goal and by making poor decisions a company can reach its downfall (Mardani et al. 2017).
Computer System
The authority of an organization faces challenges in computer systems like in software, updating the strategy. As stated by Liao et al. (2018), nowadays every industry does its job through the desktop, and making poor decisions in the computer system enables the organization to reach its downfall. In an organization, the expertise of decision-making takes their decision by analysing and understanding their issue.
Suppliers of Raw material
In any organization, management faces many challenges in deciding on choosing the suppliers of raw material. Many suppliers did not provide the raw material of an organization in time. This fact affected the service of production and the work process (Kumar et al. 2017).
Software packages
The expertise of decision-making faces many challenges while deciding on software packages. For further growth, every organization, every company, or industry needs updating software. As stated by Liao et al. (2018), the use of updated software enables the management in monitoring the work process. Making any poor decisions regarding software packages affected the entire work process including the managerial process as well in a company.
New service provider
The expertise in an organization takes any decisions by analysing the issue. In making decisions regarding the fact of a new service provider, sometimes the expertise makes poor decisions. The news service providers sometimes did not provide service effectively (Kumar et al. 2017).
Question 3: Application of SMART on the outline of a decision problem
Simple Multi-Attribute Rating Technique or SMART is a broad model of a decision-maker to put end things that are qualitative and quantitative. The Decision-making model with help of SMART tries to cover previous downfalls from any previous decision model, without the help of computerization. Broadly, SMART tries to identify and assess best project path alternatives (Siregar, 2017).
This identification and assessment will be done with the help of an existing list of relevant criteria. This technique provides a very simple and understandable method for decision-makers. SMART is also used as a supplementary technique to other tools like CBA. SMART can be achieved with the help of following steps. In this case, the main decision-making scenario will be to decide on a good raw material supplier.
1. Identification of decision-maker: The first stage tries to identify the decision-maker. However, identifying the decision-maker is the most responsible job as it will affect the decision analysis. In this case, resource manager of a project team will be the decision-maker.
- Alternatives identification: This stage is quite straightforward. It tries to identify multiple alternative ways to achieve the same goal. such as choosing alternative project models to optimize a certain project (Oktavianti et al. 2019). There may be many raw material suppliers in the market; it is the work of resources manager to get info of every raw material supplier to gain more insights into it.
- Evaluation Criteria identification: A criterion is needed in order to assess alternative decision paths. A criterion is a set of constraints, which will help the decision-maker to assess their decision. In this case, the main criteria will be cost of materials, distance from supplier, and quality of raw materials and responsiveness of supplier
- Numerical assessment of each alternative: After evaluation criteria, one must evaluate performance of each alternative decision. For this, the decision-maker needs to identify variables linked with criteria. Then these variables should be evaluated if those are quantitative or not. If the required variable of criteria is quantitative then evaluation can be done by value function (Risawandi and Rahim, 2016). Other than this, Direct Rating method can be used both by quantitative and non-quantitative variables.
On behalf of the case, it can be said that currency as a variable of cost and KM. as variables of distance will be quantitative and the quality of raw materials and responsiveness is non-quantitative.
Direct rating: In the Direct Rating method, decision-makers are asked to rank the alternative from 0 to 100. The least preferred alternatives are ranked 0 and most preferred alternatives are ranked 100. This ranking is based on certain criteria and its variables. After getting ranked list, another ranking process is repeated based on other criteria. Though direct rating can be used on quantitative and non-quantitative variables, still responsiveness and quality of product will go through direct rating (Fahlepi, 2020).
Value Function: When a quantified variable of criteria is dealt with, then the value function is used instead of the quantified value (Slamet et al. 2019). Like direct rating, rating of alternatives is done. Zero is assigned to least preferred alternatives and hundred is assigned to most preferred alternatives. Using bisection methods, it is possible to get five points; ‘minimum (0)’, ‘the 25th percentile’, ’50th percentile’, ‘the 75th percentile’ and ‘100th percentile’.
This will be used to plot, function and scores each alternative. Like Direct Rating this will be done repetitively to get a desirable outcome. Cost of the material and distance from the supplier is used by value function to understand assessment of each alternative
- Assigning weights to evaluation criteria:
The importance of criteria is based on the decision-maker. Before putting or assigning weights, a fictional alternative is chosen which will perform worst in all criteria. Then each and every alternative is assessed based on its maximum performance under certain criteria. For each assessment, a number is assigned based on decision makers’ preferences.
The highest rank is given as 100, and the lowest rank is given as 0. This is dependent on the decision-maker how he thinks it is important. After this, it is easier to assign weights regarding their prioritization. In this case, a fictional alternate will be a non-responsive raw material supplier, who provides poor quality of material regarding high price.
- Weighted average of alternatives calculation or performance score for total alternatives:
Alternatives are defined, evaluation criteria are identified, the performance of each alternative is evaluated, and importance of criteria is assigned. Now to get total performance of each alternative, SMART will be used as an additive model. However, this model has its own limitations.
- Evaluating a provisional decision based on performance score:
After getting a calculated performance score for all the alternatives, a rough decision can be made. Necessary adjustments can be needed for implementable decisions. For this scenario, a probationer decision is to have a raw material supplier who will provide good materials at a cheaper price
- Final Decision and analysis of sensitivity
The robustness of decision needs to be checked, and it is implemented by sensitive analysis. The robustness of a solution depicts how much it is sensitive to certain small changes of decision variables, weights of criteria. If the model is robust, immune to minor changes then a final decision is made.
Nevertheless, if the model is not robust, and suffers changes due to minor adjustments, then a revision is required before drawing the final decision. This decision solution is fully robust, as minor or changes in supplier’s responsiveness are ignorable with the fact of material supply.
Question 4: The limitations and Strengths on the analysis of decision problem
Analysing the following report, it can be pointed out that decision making is hefty work regarding the project. Time is a great factor for any big or small project. On the contrary, decision making takes a huge amount of time. A decision should be made by taken care of every variable, and criteria. This process is time-consuming. After taking the decision, a manager must focus on the merits and demerits of that decision, which is also time eating process.
For a group decision, it is hard to tell how much time it will require to get an outcome as a decision (Finck and Biega, 2021). Differences of people and ideas make it harder and time-consuming to get a final decision. Sometimes, in a group, it may happen that the final decision is not well built and proper. This might happen due to appeasement of all the members of the group.
Different ideas and poor ideas make decisions weaker and improper; on the contrary, it should be a bold and correct decision (Borissova and Keremedchiev, 2019). Though it is hard to make mistakes via any decision-making model, inaccurate data and time constraints may affect the final decision outcome. Inaccurate data is the outcome of an improper way of collecting data, identifying the factor, taking records of other variables.
The main advantage of its decision of the following analysis is that outcome is desirable for the decision-maker (Rumeser and Emsley, 2019). The main goal of the decision was to select a raw material supplier and it was met. One of the biggest advantages of decision analysis will be to optimize resource usage and problem solution.
Conclusion
Based on the above discussion it can be concluded that decision making is an important fact in any organization for their success. There are many signs and many tools in decision making such as create, lucid chart, MindTools, good calculators, and smart draw. The expertise of making decisions in an organization faces many challenges and their decisions affect the whole work process.
Many objectives are relating to decision problems such as choosing new service providers, computer systems, software packages, and suppliers of raw material. The study focused on the possibilities of accurate results followed by SMART. There are different strengths and limitations in the process of decision making like axioms.
References
Borissova, D. and Keremedchiev, D., 2019. Group decision making in evaluation and ranking of students by extended simple multi-attribute rating technique. Cybernetics and Information Technologies, 18(3), pp.45-56. Available at: https://cit.iict.bas.bg/CIT_2019/v-19-3/10341-Vol-19_Issue_3-04_paper.pdf
DeRousseau, M.A., Kasprzyk, J.R. and Srubar III, W.V., 2018. Computational design optimization of concrete mixtures: A review. Cement and Concrete Research, 109, pp.42-53. Available at: https://www.sciencedirect.com/science/article/pii/S0008884617313601
Dileep, G., 2020. A survey on smart grid technologies and applications. Renewable Energy, 146, pp.2589-2625. Available at: https://www.sciencedirect.com/science/article/pii/S0960148119312790
Duan, Y., Edwards, J.S. and Dwivedi, Y.K., 2019. Artificial intelligence for decision making in the era of Big Data–evolution, challenges and research agenda. International Journal of Information Management, 48, pp.63-71. Available at: https://www.sciencedirect.com/science/article/pii/S0268401219300581
Fahlepi, R., 2020. Decision Support Systems Employee Discipline Identification Using The Simple Multi Attribute Rating Technique (SMART) Method. Journal of Applied Engineering and Technological Science (JAETS), 1(2), pp.103-112. Available at: https://journal.yrpipku.com/index.php/jaets/article/view/67
Finck, M. and Biega, A., 2021. Reviving Purpose Limitation and Data Minimisation in Personalisation, Profiling and Decision-Making Systems. Max Planck Institute for Innovation & Competition Research Paper, (21-04). Available at: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3749078
Guarini, M.R., Battisti, F. and Chiovitti, A., 2018. A methodology for the selection of multi-criteria decision analysis methods in real estate and land management processes. Sustainability, 10(2), p.507. Available at: https://www.mdpi.com/263560
Kumar, A., Sah, B., Singh, A.R., Deng, Y., He, X., Kumar, P. and Bansal, R.C., 2017. A review of multi criteria decision making (MCDM) towards sustainable renewable energy development. Renewable and Sustainable Energy Reviews, 69, pp.596-609. Available at: https://www.sciencedirect.com/science/article/pii/S1364032116309479
Liao, H., Xu, Z., Herrera-Viedma, E. and Herrera, F., 2018. Hesitant fuzzy linguistic term set and its application in decision making: a state-of-the-art survey. International Journal of Fuzzy Systems, 20(7), pp.2084-2110. Available at: https://link.springer.com/article/10.1007/s40815-017-0432-9
Mardani, A., Zavadskas, E.K., Khalifah, Z., Zakuan, N., Jusoh, A., Nor, K.M. and Khoshnoudi, M., 2017. A review of multi-criteria decision-making applications to solve energy management problems: Two decades from 1995 to 2015. Renewable and Sustainable Energy Reviews, 71, pp.216-256. Available at: https://www.sciencedirect.com/science/article/pii/S1364032116311078
Marttunen, M., Lienert, J. and Belton, V., 2017. Structuring problems for Multi-Criteria Decision Analysis in practice: A literature review of method combinations. European Journal of Operational Research, 263(1), pp.1-17. Available at: https://www.sciencedirect.com/science/article/pii/S0377221717303880
Oktavianti, E., Komala, N. and Nugrahani, F., 2019, April. Simple multi attribute rating technique (SMART) method on employee promotions. In Journal of Physics: Conference Series (Vol. 1193, No. 1, p. 012028). IOP Publishing. Available at: https://iopscience.iop.org/article/10.1088/1742-6596/1193/1/012028/meta
Risawandi, R.R. and Rahim, R., 2016. Study of the simple multi-attribute rating technique for decision support. Decision-making, 4, p.C4. Available at: https://www.researchgate.net/profile/Robbi-Rahim/publication/311986644_Study_of_the_Simple_Multi-Attribute_Rating_Technique_For_Decision_Support/links/5867986508ae8fce49156e71/Study-of-the-Simple-Multi-Attribute-Rating-Technique-For-Decision-Support.pdf
Rumeser, D. and Emsley, M., 2019. Can serious games improve project management decision making under complexity?. Project Management Journal, 50(1), pp.23-39. Available at: https://journals.sagepub.com/doi/abs/10.1177/8756972818808982
Sánchez-Monedero, J., Dencik, L. and Edwards, L., 2020, January. What does it mean to’solve’the problem of discrimination in hiring? Social, technical and legal perspectives from the UK on automated hiring systems. In Proceedings of the 2020 conference on fairness, accountability, and transparency (pp. 458-468). Available at: https://dl.acm.org/doi/abs/10.1145/3351095.3372849
Siregar, D., Arisandi, D., Usman, A., Irwan, D. and Rahim, R., 2017, December. Research of simple multi-attribute rating technique for decision support. In Journal of Physics: Conference Series (Vol. 930, No. 1, p. 012015). IOP Publishing. Available at: https://iopscience.iop.org/article/10.1088/1742-6596/930/1/012015/meta
Slamet, C., Maliki, F.M., Syaripudin, U., Amin, A.S. and Ramdhani, M.A., 2019, December. Thesis topic recommendation using simple multi attribute rating technique. In Journal of Physics: Conference Series (Vol. 1402, No. 6, p. 066105). IOP Publishing. Available at: https://iopscience.iop.org/article/10.1088/1742-6596/1402/6/066105/meta
Vidal, T., Laporte, G. and Matl, P., 2020. A concise guide to existing and emerging vehicle routing problem variants. European Journal of Operational Research, 286(2), pp.401-416. Available at: https://www.sciencedirect.com/science/article/pii/S0377221719308422
