Business Decision Making


In the current business environment, decision making play crucial role in establishing the operations of business as well as ensuring long term sustainability. In general, business decision making refers to the process of selecting best among the alternatives (Hedgebeth, 2007). In the present report, researcher focuses on evaluating different scenarios and accordingly makes decisions for the suitable results and outcomes. Further, it includes range of statistical tools and techniques by the means of which different requirement will be satisfied. Along with this, graphical presentation has been indulged to present the collected data in effective and efficient manner. Lastly, with the help of investment appraisal techniques decision will be made regarding selection of suitable and reliable investment proposals.



According to the given case study, Government of UK is planning to start a Crossrail Project with the aim of enhancing the local transport within London. The main purpose of this project is provide travelling facilities to 1.5 million people so that it can generate key employment, leisure and other business activities. Furthermore, it will enhance the journey times across London to easing congestion and offering better and affordable connections (Badenhorst-Weiss and, 2008). Along with this, through the help of this project, Government of UK will change the way of people travel around the capital.


The main purpose of conducting this project is to enhance the level of travelling for the local people and the visitors. Along with this, to minimize the road traffic so that level of pollution can be managed and controlled. Furthermore, researcher focuses on evaluating the benefits of Crossrail project for the local community. Therefore, researcher through the help of this study will investigate different aspects about the project and provide detailed information to the government officials.

Objectives of the research

The main objective of this study is to determine the benefits of Cross Rail project for the local community of London. Along with this, to estimate budget and time frame for carrying out the whole project. The three main objective of research are as follows.

  • To identify the benefits that this project will give to general public.
  • To identify whether this project will contribute to growth of economy of London.
  • To identify that this whether this project will help in controlling congestion on railway station.


According to the present given scenario, researcher is focusing on using both primary and secondary information to collect data regarding Crossrail project and accordingly build understanding regarding benefits of the project to local community. Furthermore purposive sampling technique has been selected because managers associated with the Crossrail project are required to generate wide range of information. Sample size of will be 30 senior managers. Firstly, through the means of qualitative techniques researcher will be able to enhance the understanding regarding the perception of local people towards the project (Day, 2005). Along with this, using quantitative techniques will assist in collecting numerical data for the benefits to the people. In primary section, people of London will be provided questionnaire and accordingly reliable and valuable information will be collected.

Data Analysis

In the present study, investigator will use thematic as well as statistical approaches to analyse the collected information. However, thematic analysis will assist in evaluating the subjective or qualitative information generated through the means of different sources (4 Decision Making Methods, 2011). On the other hand, statistical approach will assist in interpreting the numerical information so that benefits of Crossrail projects for local community of London can be identified effectively.

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In order to collect data, researcher focuses on using survey methodology in which questionnaire will be distributed to local people of community:


Ques1: Gender

  • Male
  • Female

Ques2: Age:

  • 16-20 years
  • 21-25 years
  • 26-30 years
  • 31-35 years
  • 36-40 years
  • 41-45 years
  • >46 years

Ques3: Are you aware about the “Crossrail” project of the government of UK?

  • Yes
  • No

Ques4: According to you what are the major benefits of  the cited project of the UK Government?

  • Enhancing travel experience
  • Improved connectivity
  • New experience of travelling around the capital
  • Easy Overcrowding

Ques5: Do you think, Crossrail project have increased the employment opportunities?

  • Yes
  • No

Ques6: Please tick as appropriate, Crossrail project will ensure future economic growth in the London?

  • Strongly Agree
  • Agree
  • Neutral
  • Disagree
  • Strongly Disagree

Ques7: Are you interested in using the services offered by Crossrail Project?

  • Yes
  • No

Ques8: Do you believed that, Crossrail project will improve the rail transportation and cut journey time across city?

  • Yes
  • No

Ques9: Will “Cross Rail” improve the congestion on London Central roads?

  • Yes
  • No
  • Maybe

Measure of dispersion refers to the process by the means of which investigator evaluate how wide spread the set of given data is in the defined variables. There are three major elements of measure of dispersion such as: Standard deviation, Range and variance. Following are the computation of these elements:

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Standard Deviation: With help of standard deviation, researcher can easily identify the variation between given set of information (Byrne, McAllister and Wyatt, 2011). In the present study, standard deviation assist owner of Carmen clothing shop to whether stick below 40 price range or increase it above 40.

Variance = s2 = ∑Fx2 – ((∑Fx)2 /n)/ n – 1

Variance = 511.48

Standard Deviation = S= √s2

Standard Deviation = 22.61

Range: Range helps in computing the different between highest value and lowest value in the collected information or data (Sucky, Aksoy and Ozturk, 2012).

Range = (100-(10/ (20+1))-(10/ (4+1)))

Range = 97.52

25th Percentile (Lower 25th Percentile (Lower Quartile) and 75th Percentile (Upper Quartile) and use of Percentile

Quartile: In general, quartile refers to the statistical approach of dividing set of numbers into four different quarters. All the quarters are denoted with: Q1, Q2, Q3, and Q4. In this, first quartile (Q1) illustrates the middle number between smallest number and the median of the defined set of data (Morato, 2013). While second quartile (Q2) denotes median of the data and Third quartile (Q3) refers to the middle number between highest number and the median of the defined set of data.

Percentile: This statistical measure helps in defining the value that falls under a below given set of percentage. For instance: 25th percentile falls under the observation of 25 percentage of total value.

  • Lower quartile/25th percentile 24.5
  • Upper quartile/75th percentile 58.8

Interquartile range: In general, inter-quartile range can be defined as the measure of variability which depends upon dividing given set of data into four different quarters. In other words, it is the difference between upper quartile and lower quartile.

Internal rate of return: In regard to evaluate the feasibility of an investment proposal, managers often use internal rate of return method. Likewise NPV, this method also considers time value for money and due to which it also possess great importance in making the decisions (Swart, 2004). Furthermore, through the means of IRR, managers can analyze the potential profit of the investment in terms of percentage. Following is computation of IRR for the present projects:

Internal rate of return = lower discount rate + NPV at lower discount rate/ NPV at lower rate - NPV at higher rate* (Higher discount rate – discount rate)

  • Project A = 0.10+69939/ (69939-(-32700))*(0.30-0.10) = 23.63%
  • Project B = 0.10 + 26474/ (26474-(-54190) * (0.30-0.10) = 16.56%


With the help of above computation of appraisal techniques researcher has been able to evaluate that, NPV at 10% discount factors illustrate that, Project A (69939) is showing high outcomes as compared to Project B (26474). Therefore, on the basis of 10% discount factor management is recommended to invest in project A. while on the other part of it, NPV at 20% discounted rate, Project A is showing positive outcome of 8741 in comparison to the negative value of Project B -21050. Along with this, internal rate of return is of Project A is also higher than project B. Thus, it is recommended to top level management of the company to invest in Project A as it will help in generating higher results and outcomes.


In conclusion to the above report it has been evaluated that, operating the present corporate market it is crucial for the managers to make smart and effective decisions regarding executing business operations. Therefore, present report illustrated that, through the help of descriptive analysis managers can develop accurate understanding regarding the position of business and then make suitable decisions. Along with this, graphical presentation assist owner of Carmen Clothing Company in showing the sales growth. Lastly, through the help of investment appraisal techniques Project A has been recommended to the company for the potential future investment.

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  • Byrne, P., McAllister, P. and Wyatt, P., 2011. Precisely wrong or roughly right? An evaluation of development viability appraisal modelling. Journal of Financial Management of Property and Construction.
  • Day, A., 2005. Mastering Financial Mathematics with Excel: A Practical Guide for Business Calculations. Financial Times/Prentice Hall.
  • Hedgebeth, D., 2007. Data-driven decision making for the enterprise: an overview of business intelligence applications.
  • Ho, J. C. L., Liu, S. C. and Tsay, J., 2008. "Further evidence on financial analysts' reaction to enterprise resource planning implementation announcements". Review of Accounting and Finance.
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  • Schraeder, M. and Morrison, R, 2005. Commander's evaluation in the context of business decision-making: a multi-perspective approach. Development and Learning in Organizations.
  • Sucky, E., Aksoy, A., and Ozturk, N.  2012. A decision support system for demand forecasting in the clothing industry. International Journal of Clothing Science and Technology.
  • Swart, N., 2004. Personal Financial Mangement. Juta and Company Ltd.
  • Williams, S., 2001. Making Better Business Decisions: Understanding and Improving Critical Thinking and Problem Solving Skills, SAGE.
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