Importance Of Decision Making: Application Of Decision Analysis Tools

Question 1: Importance of Decision Making

Analytics thinking and decision making are referred to the ability for analysing and collecting information, problem-solving and decision making in a great manner. According to Yates and de Oliveira (2016), the individuals use the analytical data at the time of brainstorming, detecting patterns, observing, decision making and data interpretation. As per the multiple options and factors, such analytical skills allow individuals in identifying the solutions to the various problems. As a result, concrete decisions are made, including making action plans for solving those issues.

The current study aims to discuss the significance of decision making as well as its application of it. Taking into account several examples, the study will apply the SMART techniques in this regard, and in the end, both strengths and weaknesses will be analysed as well.

In relation to the business, it can be stated that the approach of the decision making is considered as significant as it aims to achieve the organisation’s objectives or goals within the given budget and time. As expressed by Bruch and Feinberg (2017), in terms of effective decision making, it tends to identify the appropriate alternatives by utilising its resources in a proper manner. Also, the approach of decision making also aims to satisfy its employees in the workplace. As a result, both the organisational objectives and goals are being achieved in accordance with the desired result. Another research by Li and Chapman (2020), stated that in relation to the features of effective decision making, the concept is basically used for motivating its employees within the context of an organisation. Also, the decision making helps to provide an overall framework for operation in accordance with the guidelines of the operating staff. It is noteworthy that decision making helps to enhance the various types of benefits and the facilities considering which a large base of the employees can perform their job in accordance with the organisational requirements.

As argued by Osadchy et al. (2018), in order to support organisational performance, decision-makers tend to use the proper use of resources. As for example, an organisation can have different types of resources such as method, money, man, machine, material, information and market. Such types of resources can be properly used without any wastage and league with the assistance of the approach decision making. As a result, the concerned organisation can be operated at a very minimal cost. The research by Mohamad et al. (2017), disclosed that managerial performance could be evaluated by the approach of decision making. Herein, the research reveals that decision making can be a significant factor in order to select the appropriate alternatives, which is not essential in order to evaluate managerial performance. The success of the manager herein can broadly depend upon the number of appropriate decisions that can embrace the success of the organisation. On that note, decision making can be considered as an important factor for judging the performance of the high level of management (Meidell and Kaarbøe 2017). Based on the discussion made above, it can be stated that decision making can be considered as an indispensable component for the success of an organisation as without taking the appropriate decision at the correct time, nothing is possible in accordance with the plan.

Question 1: Application of Decision Analysis Tools

In terms of the application of the decision analysis tools, it can be stated that the decision-making tools help in mapping out all the probable alternatives to the appropriate decision making. Based on the chances of failure, success and the effectiveness of the cost (Guarini, Battisti and Chiovitti 2017). The decision analysis tools can be considered as a very useful way for making the appropriate choice by simplifying the process of decision making. According to Vafadarnikjoo (2020), a SWOT diagram can be an effective tool in this regard as it stands for the threats, opportunities, weaknesses, strengths. The tool can be considered as a significant application of the management that helps the organisation in assessing the present situation. As described in the research, the concerned tool can be worked as a fundamental guide for strategic planning. As agreed by Saki et al. (2020), the SWOT tool can act in a creative manner for creating diagrams. Here, it can be considered one of the significant tools for decision making that enhances the user-friendly interface for enabling or customising the approach of collaboration across real time organisational strategies.

As argued by Bajaj, Garg and Sethi (2018), as a part of the decision-making tool, Pareto analysis appears as an appropriate tool for the decision making that embraces 20% of the activities, for accounting the 80% of the results. It is noteworthy that the concerned tool can be used for prioritising the probable changes through identifying the issues as well as resolving them n a great manner. The concerned research revealed that in order to do the Pareto tool, a visual paradigm is required to be created in order to add as well as input the data to the Pareto chart in an easy manner. It can be considered as one of the right tools of the decision making through which chart can generate in an automatic way in Google Sheet. It is worth to mention that the approach of the visual paradigm allows resizing the chart in any type of dimension.

The decision problem that will be discussed in this section is a car purchasing for the company staff. Here it can be stated that the car purchasing for the staff of the company can lead to certain tax related advantages for the owner. However, before purchasing the car, the owner needs to be aware of certain cons and pros for having the organisation or the staff own the car. On that note, the implications of the tax, as well as the other related factors, need to be considered in regard to the decision.

Question 2: Business Car Ownership

It is noteworthy that basically, the key benefits from the employee or the company to own a business car can lead to the savings from the deductions of the tax. However, such deduction can come in two parts that are as follows:

• Deduction in regard to the act to owe the car
• Deduction for the costs for driving the car for the purpose of the business

Here it is noteworthy that for the owner, the price of the vehicles can be considered as an asset of the business. The utilisation of the cost of the cars can be entirely deducted from the tax of the business. On the other hand, the cost of the vehicles can be appeared as an asset that is not needed to be deductible. In accordance with the expense of the car loan, herein, the employees can no longer be dedicated to the expenses of the unreimbursed business.

The scenario here is that the XYZ company is deciding to choose a bank where they can open salary account for their new joiners’ employees. While deciding for the banks the company has taken five main attributes which provide benefits to the employees and the costs of maintenance is the major cost. The major five attributes of the company considered are distance of the bank from the company, APR on loans taken by the employees, the customer support system of the banks, online banking and feasibility of virtual transaction and offers and investment opportunities provide by the bank. So the application of the SMART is taken here to first rate the banks, their services and overall rating is given to the attributes (Segura, M. and Maroto, C., 2017).

In the step 1 a value tree is shown where costs and benefits are shown. The five benefits attributes are also shown. 

From most preferred to worst preferred

1. Bank 2
2. Bank 1
3. Bank 4
4. Bank 5
5. Bank 3

In step 2 of the SMART, we take up for a singular attribute how the banks can be rated. Here hence from the perspective of customer support system Bank 2 is most preferred while bank 3 has the worst customer support system. 

Accordingly in Step 3 below we take up assigning values to the ratings or ranks of the banks on a scale of 100 to 0 where (100 refers to most preferred and 0 is least preferred). So here in customer support, bank 2 has 100 value, bank 3 take the 0 value and the middle values are shown for the rest of the banks. This exercise is taken for all the attributes and the banks and that is presented in the Matrix, (table ). 

Question 3: Bank Selection

value	banks
100	bank 2
90
80	bank 1
70
60	bank 4
50
40
30	bank 5
20
10
0	bank 3

In this step the value function is plotted for the attribute distance of the bank from the company (Vafaei et al. 2016). 

In this step the Matrix is tabulated which shows the values of the ratings given to all the banks for all the attributes. For example, we find that for Bank 1, in terms of offers and investment opportunities it is most preferred while it is least preferred when it comes to ARP on loans. Similarly all the values for all the attributes mean the same.

Matrix for assigning the values to the rating for all the attributes
	Banks
Attributes	Bank 1	Bank 2	Bank 3	Bank 4	Bank 5
Customer support 3	80	100	0	60	30
APR on loans 5	0	100	75	56	20
Offers and investment opportunities 4	100	20	0	55	86
Distance of the bank 2	20	30	100	60	0
Online Banking and Virtual Transaction feasibility 1	80	40	0	100	52

The Swing weights are a major aspect for the SMART analysis. Here mainly the weights are given for the attributed as a whole. As such customers have a higher preference while they chose a bank. For example the below image shows, that online banking and virtual transaction feasibility is given the most importance while customers while they chose to select a bank. Online transaction is an important aspect of banking because as technology advanced and UK being one of the advanced nations, the banks too transformed their operation which easily allow customers to deposit money and withdraw money according to their needs. Moreover online banking is open for 24*7 which allows the bank to free their important resources into other business.  The customers, too, find online banking highly effective where they do not have to spend much time of their busy schedule (Marsh, et al. 2016). So the employees of XYZ prefers those banks where the online banking is provided. Next they prefer distance of the company from the banks as the second most important attribute. This is because in case the employees are having issues with the account and facing transaction issues they can take short break from their office to visit the bank and resolve their issues. Moreover closer the banks are to their office less would be spend on transport. Likewise they feel APR on loans are not much important to them, but offers and investment opportunities are far more important for them. 

The step involve the normalizing the weights given to the attributes. For example, customer support has 70 as its weight and that is normalized to 22. This normalizing process is similar to the calculations of the percentage share. The total value of the weights is 320, and this total is taken as 100. So share of each attributed to normalized to 100. Here we see that since online banking and virtual transaction feasibility is the main aspect for the employees, among 100 the share is 32. 

Attributes	Original Weights	Normalized weights
Customer support	70	22
APR on loans	20	6
Offers and investment opportunities	50	15
Distance of the bank	80	25
Online Banking and Virtual Transaction feasibility	100	32
Total	320	100

In this step the aggregate benefits of the attributes for each five banks. The aggregate benefit for each attribute is done by the following formula,

Benefit from a single attribute = value of rating* weights

The aggregate benefit have been found out by adding up the benefits for all the five attributes for all the five banks.

In this table, we find that the highest benefit is acquired from Bank 4 while the lowest benefit is obtained from Bank 3. The aggregate benefit is then normalized by dividing the value by 100 so that within 100 the ranking can be made.  

			Banks
Attributes	Weights	Bank 1	Bank 2	Bank 3	Bank 4	Bank 5
Customer support	22	80	100	0	60	30
APR on loans	6	0	100	75	56	20
Offers and investment opportunities	15	100	20	0	55	86
Distance of the bank	25	20	30	100	60	0
Online Banking and Virtual Transaction feasibility	32	80	40	0	100	52
		6320	5130	2950	7181	3734
Aggregate benefits		63.2	51.3	29.5	71.81	37.34

The table below shows the aggregate costs that the employees have to incur for each bank. It shows that aggregate costs in terms of the annual charges to be incurred for maintenance of the accounts in bank 1 and 2 are the highest while in bank 5 and 3 are lowest. So the benefits are plotted against the costs. The diagram shows the efficient frontier and the other points for which the benefits are plotted. Among them the point for Bank 4 is the most efficient lying in the middle of the cost incurred while the benefit derived is very high when other banks are compared. The efficient frontier is the limiting point for which the decision has to be made (Yoshimoto, Alves and Caetano 2018).

Bank	Annual charges	Aggregate benefits
5	4.33	37.34
3	5.00	29.5
4	6.99	71.81
2	10.31	51.3
1	13.56	63.2

In conclusion it can be said the Bank 4 would be the optimal bank to be chosen by the XYZ organization as the benefit is very high when compared against the costs. The other banks either have very high costs and fall below the efficient frontier. So the choice is Bank 4.

In order to analyse the strengths, it is to be stated that both the introduction as well as the entire discussion has been appeared as a strong method. Here the part introduction opens with a wide emphasises on the decision making features as well as the tools for the decision making. Here, the introduction, as well as the discussion part, has contextualised the findings of the study. The elements such as decision-making tools, decision-making features and their significance have been appropriately addressed for utilising the position of the reader in accordance with the current state of the decision problem (Horvat and Mojzer 2019). It is noteworthy that such discussed elements have been used for interpreting the findings of the study. Also, the introduction part has possessed the background of the current study, and the discussion has been made in providing the relevance of the introduction part.

The limitation of the current discussion has been that the information has been written based on some specific examples such as opening an account for the staff of the organisation and purchasing cars for the staff. Apart from that, considering the credibility level of the study, it can be stated that all the analysis has been done based on some published techniques or research. Herein, the current study has failed to list both the direction as well as the magnitude of the random validity and the systematic issues.

Conclusion

It can be concluded that the capacity to analyse and gather information, solve problems, and make excellent decisions is referred to as an analytical approach to decision making. Individuals use statistical information while thinking, identifying trends, monitoring, making decisions, and interpreting data. Such reasoning skills enable individuals to discover answers to varied situations based on a variety of possibilities and considerations. As a consequence, specific decisions are made, along with the development of action plans to address the challenges. The purpose of this research is to highlight the importance of decision making as well as its applicability. The study has used SMART methodologies in this respect, taking various examples into consideration, and in conclusion, both strengths and weaknesses have been examined.

As per the scenario of the stated cases, the hierarchical department can give some economic rewards to its workers by enhancing the current rules, therefore challenging the employees’ alternatives. Nevertheless, the employees must be given time to consider the decision’s potential consequences. The examined value tree framework can improve the quantification of outcomes as well as the attainment of probability based on the available data. However, it is worth noting that, in terms of decision-making methods, value tree analysis will need to be used in conjunction with a significant part of the decision-making toolbox in the upcoming weeks.

References 

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