Project Viability Analysis

This assignment involves evaluating the feasibility of two projects, A and B, based on their Net Present Value (NPV) and Internal Rate of Return (IRR). With initial investments of -150 each, projects differ in cash inflows over five periods. Calculate NPV using a discount rate of 20% and determine IRR for both projects to make an informed investment decision.

UNIT 6:
Business Decision
Making
Student name and ID number Assessor name

Assignment title Business Decision Making

Instructions
 An electronic copy of your
assessment must be fully uploaded
by the deadline date and time.
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relevant images or screenshots
must be included within the same
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the one that is marked. Your paper
will be marked if you have
indicated this as your final
submission.
 Review the mitigating
circumstances policy for
information relating to extensions.
 The file size must not exceed
20MB.
 Answer the criteria in order, clearly
indicating the pass criteria number.
 Ensure that all work has been
proof-read and checked prior to
submission.
 Ensure that the layout of your
documents are in a professional
FEEDBACK SHEET
(Item Report Form)

Assessment Title
Business Decision Making
Task Criteria
assessed
Criteria
achieved
Evidence and comments:
1
AC 1.1 Y The student was required to choose a country for the
launch of Amistar giving valid reasons and prepare a
plan explaining the ways that will be used to collect data
for the project.
AC 1.2 Y The student should have explained the survey
methodology and its 2 types, presented a choice of
sampling technique that would be used for the research.
The student is also advised to explain different sampling
techniques available before choosing one.
AC 3.4 Y The student should have presented the task in the form
of a formal report.
M2 N Not attempted
AC 1.3 Y The student has presented a survey questionnaire for
given business scenario. AC achieved.
M1 Y Student has explained the measure of skewness.
2
AC 2.1 N Your entire calculation was wrong due to using the wrong
data set. Contact academic support to provide you the
correct data or pay particular attention to the data
provided.
AC 2.2 N Your entire calculation was wrong due to using the wrong
data set. Contact academic support to provide you the
correct data or pay particular attention to the data
provided.
AC 2.3 N Your entire calculation was wrong due to using the wrong
data set. Contact academic support to provide you the
correct data or pay particular attention to the data

provided.
AC 2.4 Y You have demonstrated a good knowledge of quartiles
and percentiles through the explanation provided.
D2 N Not attempted
3
AC 3.1 Y The student has presented a column graph for the case
given in the assignment with explanation of the graph.
AC 3.2 Y The student has presented a line graph for the case
given in the assignment
AC 3.3 Y The student has presented a Power Point presentation
for given business case.
M3 N Not attempted
D1 N More details were required.
4
AC 4.1 N You have failed to discuss the Management Information
System (MIS) as required on 4.1
AC 4.2 Y You have demonstrated a good knowledge of the
network diagram.
AC 4.3 N Not attempted
D3 N Not attempted.
Feedback:
You have failed to
demonstrate
sufficient
knowledge to pass
the module, you
have failed to use
the correct details
for Task 2 hence
your entire
calculation was

wrong.
Grade indicator: Referral
Tasks #1
Q1: Country Selection and Plan
The paper has selected India as a country where Amistar can be launched and there are various
reasons behind this selection. Amistar is fungicide dedicated towards Integrated Pest
Management and India being an agrarian economy it will require lots of such new products
(Tomlinson, 2013). Therefore, selecting this country for the launch of this product seems logical.
Collection of Primary Data

The collection of primary data for the research will be based on certain set of questionnaires
targeted towards the subject (McQuarrie, 2015).
Collection of Secondary Data
The secondary data will be collected through the various secondary sources such as the Indian
government portals where the data related to country’s economy, population, total land that is
still can be used for agriculture and the land those require some pesticide processing (McQuarrie,
2015).
Survey Methodology
The survey methodology concerned with understanding the possibility of launching Amistar in
the country consists of various elements (Hippler et al, 2012). Those are mentioned below:
Eligible Respondent: The respondent selected for the survey will be those who have some prior
experience in the agricultural arena. These respondents will be from the governmental
department of agriculture of India and some of those who have spent their substantial amount of
time growing agricultural products in the country and understand the soil and environment very
well.
Sampling Method: The sampling method applied for this process will be purposive sampling
where the respondents will be selected on the understanding and conscience of the researchers.
The researchers for this project will have substantial experience in selecting right set of
candidates for the research.
Q2: Questionnaire for the survey

1. How many years you have spent in growing, understanding or studying the agricultural
produce in India?
i) 0-5 years ii) 5-10 years iii) 10-15 years iv) 15 years and above
2. What changes you want to see in terms of pesticide development in this country for the
agricultural lands?
3. Would it be beneficial for us to bring a pesticide that can help the farmers tackle pests
effectively in the country?
4. At what price you will prefer this product?
5. Can you state some reason behind your choice of price?
6. What distance you can travel or you think others can travel to get this pesticide product from
their current location?
7. What preferred mode of advertisement would be suitable for the consumer of India?
8. What packaging would be most preferred by the consumers?
9. How you see the acceptance of new pesticide products in the Indian consumers?
10. Can you name few of the most used pesticide products in the country?
11. What are the reasons they might reject this product?
12. What you see as the biggest hurdle for this product to reach the consumer’s hand?
13. Any further suggestions?

M1
The coefficient of skewness that has been discussed here is developed by Karl Pearson (Hine,
2012). He used to methods of developing the coefficient of skewness one was using the mode
and the other was using the median. Mentioned below are both the methods.
a) Based on mode the formula is:
The x bar is the mean and Mo is the mode. The s in the formula stands for the standard deviation
of the collected sample.
b) Based on median the formula is:
Skewness helps to understand the symmetry in the distribution of the data. The business
researches can use above stated formulas to calculate the same to understand that whether the
data collected is symmetrical or the data lacks the symmetric orientation. Other than the method
of Pearson mentioned above, the skewness can be calculated using the Bowley, Kelly’s Measure
or the Momental method (Miles, Huberman and Saldana, 2013). The application of these
methods depends on what is known about the data. If all the central deviation, namely, mode,
median, and mode are known then the use of Pearson Coefficient is suitable. However, if only
the mean of the data is known then the use of Momentalskewness would be the suitable method
(Grbich, 2012. ).

References (M2)
Tomlinson, B. R. (2013). The economy of modern India: from 1860 to the twenty-first century
(Vol. 3). Cambridge University Press.
McQuarrie, E. F. (2015). The market research toolbox: a concise guide for beginners. Sage
Publications.
Hippler, H. J., Schwarz, N., &Sudman, S. (Eds.). (2012). Social information processing and
survey methodology.Springer Science & Business Media.
Hine, J. (2012). A Programmed Text in Statistics Book 4: Tests on Variance and Regression.
Springer Science & Business Media.
Grbich, C., 2012. Qualitative data analysis: An introduction. Sage.
Miles, M. B., Huberman, A. M. and Saldana, J., 2013. Qualitative data analysis. Sage
Task #2
Q1:
Mean refers to the average of the data set (Field, 2013). It is calculated by adding the numbers
and then dividing the sum with the total number of numbers. From the table below we can say
the 22 countries can spend sum of £33.07m.
Mode refers to the number that has occurred most frequently within a data set (McKenzie, 2014).
the mode to the data which is calculated below is £24.44m.

The median refers to the central or middle value of the data set (Samuels et al, 2012). the value
to the middle of the overall expenditure is £30m, which is illustrated in the table below.
The mean, median and mode calculated below will help the Amistar understand the central
tendency of the whole sample and will help it understand the overall inclination of the whole
population. The central tendency of the data set help the company makes decisions as per the
current inclination of the population (Ary et al, 2013).
Annual
Expenditure /£m
Mid
value
No. of
Countie
s
Mid value * No. of
countries
0-10 5 13 65
10-20 15 25 375
20-30 25 37 925
30-40 35 22 770
40-50 45 21 945
50-60 55 20 1100
60-70 65 12 780
SUM 150 4960
Mean 33.07
Mode #N/A
Median 21
Q2
The range will help the company understand the premise to which a particular data set of the
sample belongs. The standard deviation helps in understanding the extent to which a data set is
deviating from the mean. As per this business is concerned the standard deviation will help it to

understand the deviation of the annual expenditure from its central point. It will help the
company decide the countries that would be most suitablebased on the stability in the annual
expenditure. The standard deviation and the variance provide the measure of stability. The
variance helps the business in assessing the relationships between the variables and in
forecasting the various aspects of the business which can allow the company to make current and
future decisions.
The range of the data set = 55-5 = 50. Variance = 4320/150 = +/- 5.3.
Q3
The quartiles help the business categorize the data into various areas such as first quartile, second
or others. The percentiles help in understanding the percentage of the sample belonging to
certain category. The correlation coefficient helps in understanding the extent of relationship
between the two variables. It helps business understand the dependence of one on another.
The quartile helps the business identify the investment the amount of expenditure that lies in the
defined percentiles (Doane and Seward, 2005). It can be stated that as 90 percentile of the data
set lies in the 20-30 million then it can be stated that the business can consider this aspect to
make certain decisions. The percentiles of a data set help the business understand the segment to
which the investment can be made the segment that can be ignored. The interquartile range
shows the difference between the value that lies below the first quartile and the value that lies
above the third quartile. The quartile calculation of the data helps the business understand the

sensitivity of the data sets and estimate the variability. Moreover it can be stated that the
variations provide significant support to the business in making right decision.
From the table above we can interpret that at the quartile 1 the value is £20.2 and at the quatile 2
£24.44m and £47.38m at the 3. From this we can say that the consumers expenses at the
company are increases. Which indicates that the company is selling more goods, i.e. the sales are
in a increasing trend.
Illustration 1: calculation of quartile
Illustration 1: calculation of percentile

The above correlation table suggests that the sales and profit have a solid relationship. As the
sales of the company increases the profit also takes a hike. When the consumers buy buy more
products of the company, the sales increases a rapid manner, as the profit increase in the same
manner.
References (D2)
Ary, D., Jacobs, L. C., Sorensen, C. K., & Walker, D. 2013. Introduction to research in
education.Cengage Learning.
Illustration 1: calculation of percentile
Illustration 1: calculation of correlation

Barsalou, L. W. 1985. Ideals, central tendency, and frequency of instantiation as determinants of
graded structure in categories.Journal of experimental psychology: learning, memory, and
cognition, 11(4), 629.
Dalkey, N. C., Brown, B. B., & Cochran, S. W. 1970.The delphi method, IV: Effect of percentile
feedback and feed-in of relevant facts. Rand Corporation.
Doane, D. P., & Seward, L. E. 2005. Applied statistics in business and economics.USA: Irwin.
Field, A. 2013. Discovering statistics using IBM SPSS statistics.Sage.
Fife, D., & Mendoza, J. Central Tendency Measures.Corsini Encyclopedia of Psychology.
McKenzie, S. 2014. Vital statistics: an introduction to health science statistics. Elsevier Health
Sciences.
Samuels, M. L., Witmer, J. A., &Schaffner, A. 2012. Statistics for the life sciences.Pearson
education.
Smothers, C. D., Sun, F., & Dayton, A. D. 1999. Comparison of arithmetic and geometric means
as measures of a central tendency in cattle nematode populations. Veterinary Parasitology,
81(3), 211-224.
Weisburd, D., & Britt, C. 2014.Describing the Typical Case: Measures of Central Tendency.In
Statistics in Criminal Justice (pp. 65-93).Springer US.
Task 3

Q1
The figure above shows the column graph of the data. The data shows the all these three
elements are moving almost parallel. When one rises others rise and when one falls others fall in
conjunction. The bar graph of the data helps the business understand the relationship between
various data sets. It helps the business understand the overall trend in the data set. As it can be
observed from the given graph that the all the data is falling and rising simultaneously which
shows the strong relationship between these factors.

Q2
The figure above shows the line graphs of the sales and profit with the equation of each
separately. The data set shows that the sales and profit is rising together and a positive trend
shows for the years to come. The line graph can help the business understand that the prices of
the products have been set well which is bringing in right amount of profit to the business and it
is expected to do the same in the future (which can be stated after observing the trend).

Q3

D1
Time series helps the businesses use the various data points on a timeline to understand the
future trend of the area or action under study. Time series data points are considered on a definite
spaced timeline. Time series can be best plotted using the line charts. The time series can be used
to numerous areas such as in the statistics, recognizing certain pattern of an event, forecasting the
weather, and other similar areas. Time series analysis provides meaning to the range of random
historical data sets which is then used to take useful business decisions. The time series data
considers the historical orientation of the data to find out the future trend of the situation. The
data taken to create time lien mus be discrete in nature. The time series helps to forecast the
future to the company. Firstly the data is collected which needs to be discrete in nature. Then the

team of analysts, analyses the data to give frequency to the table. The table is prepared with a
most concentration. The data take is then interpreted for the chart preparation. Then the data
table can be used to create the time series. The data gathered is from the previous years or
quarters to show the company's growth or depletion with the use of a line graph. The graph can
be used to interpret the trend from in the last years. From the trend found, and the graph the
future situation can be interpreted.
A Time Series Data is a grouping of information focuses set aside a few minutes interim out of
progressive estimations over that interim utilizing meet dispersing between each two back to
back estimations with every time unit inside the time interim having at most one information
point. Time series data have a characteristic transient requesting. This sets aside a few minutes
arrangement investigation unmistakable from cross-sectional studies, in which there is no
characteristic requesting of the perceptions (e.g. clarifying individuals' wages by reference to
their separate training levels, where the people's information could be entered in any request).
Time series analysis is likewise particular from spatial information investigation where the
perceptions commonly identify with topographical areas (e.g. representing house costs by the
area and additionally the inborn qualities of the houses). A stochastic model for a period
arrangement will by and large mirror the way that perceptions near one another in the truth will
surface eventually more firmly related than perceptions promote separated. Likewise, time
arrangement models will regularly make utilization of the common one-route requesting of time
so that qualities for a given period will be communicated as getting somehow from past qualities;
instead of from future qualities.
Time series data helps in arranging the data in sequential successive order. It helps in
keeping a track of movement of data points. For instance, time series analysis can help in

assessing the change in the price of a particular product over a period of time. The forecasters
and policy makers can use this analysis in assessing the change in prices and make policies
according to it.

Task #4
Q1
The figure below shows the Gantt chart. Gantt chart is used to display the project activities along
a timeline. This helps the project manager to get a bird’s eye view of all the data together. The
Gantt chart helps the users to understand the number of days that need to be invested on certain
activity and the resources that need to be employed for the same. Moreover, the Gantt chart
displays the critical tasks that need to be considered while moving ahead with the project. The
critical path consists of activities that are mandatory to be finished within the set timeline to
ensure that the whole project finishes on time and within the defined budget.
Management information system : MIS refers to management of data with the use of computers
to support decision making in an organization. The MIS uses systems such as transaction
processing system, decision support system, expert system, or executive information system. A
report on the regular operations created for all the levels of management through the use MIS. It
shows data which is actual against the standards set before to achieve the goal and the data from
previous years, as a whole it shows comparison of progress against goals. Management

information system further helps in making the process of accounting easy. Various software can
be adopted by the company such as inventory management system, cost accounting system etc. It
helps in making the process easy as well as effective for the top-level management.
Q2
The given image shows the network diagram that has been taken from the MS Project. The
project timeline utilized the automated calculation system and, therefore none of the manual
calculations had been employed to develop the network diagram. The network diagram helps the
project manager in understanding the project activities that are dependent on each of the other
activities. The network diagram more detailed picture than the Gantt chart.
Q3 (D3) and 4.3

Project A Project B
Initial investment -150 -150
1 30 -120 30 -120
2 40 -80 50 -70
3 60 -20 50 -20
4 30 10 40 20
5 50 60 40 60
6 60 60
This table suggests that both the projects that both projects A and B take more than 3 years to
initiate profit, therefore both are projects are concluded to be not viable to start the venture.
ARR :
Project A Project B 0
Initial investment 150 150 10000
1 30 30 3000
2 40 50 4000
3 60 50 5000
4 30 40 6000
5 50 40 0
0 0 0
Total 210 210 18000

Average 53 42 4500
ARR 35.00% 28.00% 45.00%
ARR for the project A is more than is project B so we consider that project A is more profitable
for the company to persuade.
NPV :
Project A Pv @ 10% Present value Project B PV @ 15% Present value
Initial
investment 150 150
1 30 0.909 27 30 0.870 26.09
2 40 0.826 33 50 0.756 37.81
3 60 0.751 45 50 0.658 32.88
4 30 0.683 20 40 0.572 22.87
5 50 0.621 31 40 0.497 19.89
6 0 0.564 0 0 0.432 0.00
Total 157 140
NPV 7 -10.47
The table above suggests that the NPV for the project A is in positive 7, as the NPV for project
B is negative -10.47 respectively. Therefore, it can be said that project A is more viable to
persuade in terms of NPV.
IRR:
Project A Project B
Initial investment -150 -150

1 30 30
2 40 50
3 60 50
4 30 40
5 50 40
IRR 11.70% 5.01%
The IRR for project A, 11.70%, is comparatively more than 5.01% of project B, thus it can be
concluded that project A is more viable than project B.
References
Box, G. E., Jenkins, G. M., Reinsel, G. C., &Ljung, G. M. (2015).Time series analysis:
forecasting and control. John Wiley & Sons.
Clark, W., Polakov, W. N., &Trabold, F. W. (1922).The Gantt chart: A working tool of
management. Ronald Press Company.
Durbin, J., &Koopman, S. J. (2012).Time series analysis by state space methods (No. 38).Oxford
University Press.
Li, T., Qiu, W. G., Wang, L. C., & Man, S. (2013). study of project duration risk in the network
diagram based on matrix algorithm. In Applied Mechanics and Materials (Vol. 405, pp. 3401-
3405).Trans Tech Publications.
Mohammad, I., van den Broek, H., Boots, M. L., & Wong, R. (2016).U.S. Patent No. 9,336,502.
Washington, DC: U.S. Patent and Trademark Office.

Ogles, C. C., Fuhrmann, B. J., Williams, S., & Charles, D. W. I. (2015).U.S. Patent No.
9,041,716. Washington, DC: U.S. Patent and Trademark Office.
Sarantakos, S. (2012). Social research. Palgrave Macmillan.