Business Decision Making Report: Data Analysis and Interpretation

This report delves into business decision-making, utilizing statistical tools to analyze data and evaluate projects. It begins with an introduction to statistical methods, including mean, median, and mode, and their application to business data. Task 1 outlines the plan for data collection, sampling design, and a detailed questionnaire used for market research. Task 2 focuses on the calculation and interpretation of representative statistical values, measures of dispersion, and correlation. Task 3 presents a graphic representation of the collected data, trend line creation for prediction, and a formal business report summarizing the findings. Finally, Task 4 covers information processing tools, project planning, and evaluation techniques, including payback period, ARR, NPV, and IRR calculations, to determine the most viable project for the firm. The report provides charts, graphs, and tables to support the analysis and recommendations.

BUSINESS DECISION
MAKING

TABLE OF CONTENTS
INTRODUCTION...........................................................................................................................4
TASK 1............................................................................................................................................4
1.1 Plan for collection of primary and secondary data...........................................................4
1.2 Sampling design for research...........................................................................................4
1.3 Questionnaire for research................................................................................................5
TASK 2............................................................................................................................................6
2.1 Representative values of statistical tools..........................................................................6
2.2 Analysis of results of mean median and mode.................................................................7
2.3 Measures of dispersion.....................................................................................................7
2.4 Calculation of quartile, percentile and correlation...........................................................8
TASK 3............................................................................................................................................9
3.1 Graphic representation of collected data..........................................................................9
3.2 Creation of trend line for prediction...............................................................................12
3.3 Covered in PPT...............................................................................................................12
3.4 Formal business report...................................................................................................12
TASK 4..........................................................................................................................................13
4.1 Information processing tools for business......................................................................13
4.2 Project plan for business project ....................................................................................14
4.3 Project evaluation techniques.........................................................................................15
CONCLUSION..............................................................................................................................17
INDEX OF TABLES
Table 1: Calculation of mean, median and mode............................................................................6
Table 2: Measures of dispersion......................................................................................................7
Table 3: Calculation of quartile and percentile................................................................................8
Table 4: Calculation of correlation..................................................................................................8
Table 5: Sales, cost and profit data..................................................................................................9
Table 6: Calculation of pay back period method...........................................................................16
Table 7: Calculation of ARR.........................................................................................................17
Table 8: Calculation of NPV..........................................................................................................17
Table 9: Calculation of IRR...........................................................................................................17

ILLUSTRATION INDEX
Illustration 1: Chart on sales, cost and profit data...........................................................................9
Illustration 2: People opinion on factors that greatly affect their purchase decisions...................10
Illustration 3: People opinion on Syngenta pricing policy.............................................................11
Illustration 4: Trend line for Sygenta.............................................................................................12
Illustration 5: GANTT chart..........................................................................................................14
Illustration 6: Network diagram.....................................................................................................15

INTRODUCTION
Statistics is tool that is commonly used by the business firms to analyze huge set of data.
In this report, statistical tools like mean, median and mode is applied on data and results are
interpreted. In the middle part of the report primary data is analyzed by preparing a charts. In end
part of the report, project evaluation methods are described and their results are interpreted. On
the basis of calculation most viable project is selected for the firm.
TASK 1
1.1 Plan for the collection of primary and secondary data
In order to conduct research for Amitsar, data will be collected from USA. This nation is
selected for data collection because in USA, huge quantity of crops are produced. In order to
conduct research, sample of 30 people will be taken who reside in different boroughs of London.
In respect to research, both the primary and secondary data will be collected by the researcher.
Primary data is the facts collected by research himself (March and Bourne, 2011). Whereas,
secondary data refers to the evidences that have been already collected by someone and printed
in any source of information. For the present research, both types of data will be equally helpful.
Primary data will be collected by distributing questionnaire among the respondents. Whereas,
secondary data will be collected from books and journals. Hence, in this way, entire research will
be carried out.
1.2 Sampling design for research
There are many sampling methods and some of them are as follows. Simple random sampling- Under this method of sampling, all the sample units will be
taken on the random basis from population (Jordà, Schularick and Taylor, 2011). This
means that in this sampling method, there is no specific criteria considered to select
sample units from population. Stratified random sampling- This method is appropriate for research because in this, all
the sample units are taken from population on the basis of specific factors. In order to
collect appropriate data, it is important to collect answers from respondents that are
different from each other on the basis of income and age. Hence, this sampling method is
selected for the research.

 Cluster sampling- In this method, geographic area is divided into several parts and
sample units are taken from same. This method is used in population census.
1.3 Questionnaire for research
Name:
Age:
Gender:
1. Are you familiar with Sygenta's products?
 Yes
 No
2. According to you, Sygenta's products are working effectively in pest control.
 Strongly agree
 Agree
 Somewhat agree
 Disagree
 Highly disagree
3. Which of these factors put huge impact on your purchasing decision?
 Cheaper price
 Good quality
 Discount rates
4. Do you agree that Sygenta’s pricing policy is good in comparison to its competitors?
 Strongly agree
 Agree
 Somewhat agree
 Disagree
 Highly disagree
5. According to you, Sygenta's products are more effective than its competitors.
 Strongly agree
 Agree
 Somewhat agree
 Disagree
 Highly disagree

7. Syngenta is going to launch its product Amitsar in USA. Do you think, it will be acceptable
by USA people?
 Yes
 No
11. Do you think that increase or decrease in the price of product affects people’s demand for
pesticides?
 Yes
 No
12. If you want to give any suggestion to Sygenta in respect to its product then please specify
here.
_______________________________________________________
TASK 2
2.1 Representative values of statistical tools
Table 1: Calculation of mean, median and mode
Annual expenses
No. of countries
(F) M. V. (x) CF FX
0-10 13 5 13 65
10-20 25 15 38 375
20-30 37 25 75 925
30-40 22 35 97 770
40-50 21 45 118 945
50-60 20 55 138 1100
60-70 12 65 150 780
150 4960
Mean = ∑FX/∑F = 4960/150 = 33.07

Median = L1 + (N/2-C)/F * Class Interval
= 20 + (150/2 – 38)/37*10
= 30
Mode = L1 + (F1-F0)/ [(2F1-F0-F2)*Class interval
= 24.44 Mean- It refers to the average value of the variable (Berlinet and Thomas-Agnan, 2011).
By comparing value of variable with average value, it is find out that performance given
by variable is good or bad. Median- It is a value that divides entire data into two parts. Hence, it can be said that this
tool helps in trend analysis of variable.
 Mode- It is a statistical tool that indicates value which is repeatedly occurring in the data
set. Thus, this tool helps in analyzing data in a systematic way.
2.2 Analysis of results of mean, median and mode Mean- In this case, mean value is 33.07 and it means that most of the counties invest 33
million of amount annually. Hence, Syngenta needs to invest an amount near to 33
million in a year in order to cover more cities of USA. Median- It can be seen that up to median value, annual expenditure of Amitsar is
increasing but after this value, same is declining. This means that Syngenta must make its
annual expenditure maximum up to 30-33 million.
 Mode- Value of mode is 24 and here, frequency is also high. It means that most of the
counties are repeatedly making an expense of 10-20 million in a year. On the basis of
mean, median and mode, it can be said that firm can make investment of 10-30 million in
a year on Amitsar.
2.3 Measures of dispersion
Table 2: Measures of dispersion
Annual
expenses
No. of
countries (F) M. V. (x) FX X^2 F*X^2
0-10 13 5 65 25 325

10-20 25 15 375 225 5625
20-30 37 25 925 625 23125
30-40 22 35 770 1225 26950
40-50 21 45 945 2025 42525
50-60 20 55 1100 3025 60500
60-70 12 65 780 4225 50700
150 4960 11375 209750
Variance = ∑Fx2 – ((∑Fx) 2/n)/ n – 1 = 208649.257
Standard deviation =
= 456.7814
Interpretation
It is a tool that reflects the extent to which value of variable is far from its mean value
(Kuznetsov, 2013). In this case, value of standard deviation is 456 which means that difference
between current annual expenditure and average annual expenditure is not high. This also means
that most of the counties are making annual expenditure nearby the average value of expense
which is 33.07 million. Hence, Syngenta must maintain its expenditure nearby to its average
annual expenditure.
2.4 Calculation of quartile, percentile and correlation
Table 3: Calculation of quartile and percentile
Quartile 1 20.2 percentile 25 20.2
Quartile 2 24.44 percentile 50 24.44
Quartile 3 47.38 percentile 75 47.38
Interpretation
Quartile and percentile are same type of statistical tool and they divide data into three
parts (Suh and et.al., 2011). Value of percentile is increasing which means that expenditure on
Amitsar is also increasing. This reflects that there is good demand for Amitsar in the market.

Table 4: Calculation of correlation
Particular Sales Units (£’m) Profits (£’m)
Sales (Units) (£’m) 1 0.888030143
Profits (£’m) 0.888030143 1
Interpretation
Correlation is an important statistical that is used by research analysts to measure
relationship between two variables. This statistical tool reflects the degree of relationship
between the two variables. Hence, impact of change in one variable on other variables can easily
be identified by using this tool. This tool reflects correlation between two variables (Shun-ichi,
2012). In this case, value of correlation is one and this indicates that sales and profit are
completely related to each other. If sales will plunge by 6% then profit will also be elevated by
same percent.
TASK 3
3.1 Graphic representation of collected data
Table 5: Sales, cost and profit data
Year Sales (£’000) Cost (£'000) Profit (£’000)
2005 270 200 70
2006 310 220 90
2007 320 220 100
2008 400 250 150
2009 380 250 130
2010 350 240 110
2011 330 220 110
2012 330 230 100
2013 340 230 110
2014 480 240 140

Illustration 1: Chart on sales, cost and profit data
Interpretation
From the graph, it can be seen that in most of the years, sales of Amitsar increased. In FY
2009 and 2010, this trend was inverse but after that, again sales of Amitsar maximized. Hence, it
can be said that in future, there will be great demand for Amitsar.
Which of these factors put a huge impact on your purchasing decisions?
Cheaper price 10
Good quality 15
Discount rates 5

Interpretation
From the above given chart, it can be seen that most of the respondents think that they
prefer to purchase products of good quality. 10 out of 30 respondents think that they prefer to
purchase products which are available at cheaper price. Only 5 state that they prefer relevant
items that are available on discount. Hence, it can be said that Syngenta needs to make available
products at low price and of good quality.
Sygenta’s pricing policy is good in comparison to its competitors. Do you agree?
Strongly agree 15
Agree 8
Somewhat agree 2
Disagree 3
Highly disagree 2
Cheaper price Good quality Discount rates
0
2
4
6
8
10
12
14
16
10
15
5
Column C
Illustration 2: People opinion on factors that greatly affect their purchase decisions

Interpretation
Most of the people are agree on the fact that Syngenta pricing policy is better than its
competitors. 15 respondents are strongly agree with this fact and 8 are agree with same fact. 2
are somewhat agree followed by 3 disagree and 2 highly disagree with the fact that syngenta
pricing policy is better than its competitors. Hence, it can be said that people are satisfied from
its product in terms of price.
3.2 Creation of trend line for prediction
Illustration 4: Trend line for Sygenta
Interpretation
15
8
2
3
2
Strongly agree
Agree
Somewhat agree
Disagree
Highly disagree
Illustration 3: People opinion on Syngenta pricing policy

From the chart, it can be observed that sales of the firm is increasing consistently. Trend
line is moving upward and it means that sales of the firm will increase in future time period
(Slowiński, 2012). The main limitation of time series analysis method is that it makes prediction
on the basis of past data. Present data can be different from past. Hence, it is not necessary that
this method will always make accurate prediction. Managers can use simulation method to make
accurate prediction about future.
3.3 Covered in PPT
3.4 Formal business report
To
The Directors of Synzenta
Date: 23rd May 2016
Sir/Mam
Introduction
The aim of this research is to find out viability of the project in the chosen nation. In this report,
USA is selected for the launch of new product and viability of this decision in the selected
nation is measured. In this regard, deep analysis of facts and figures is done in this report.
Research methodology
In order to conduct research, both the primary and secondary data are collected by the
researcher. Stratified random sampling method is used to collect sample from population.
Statistical tools are also applied on data and their interpretation is done in the report.
Conclusion
It is concluded that launch of new product will be profitable for the firm. This is because people
are satisfied with firm’s pricing policy and think that firm products are of better quality than its
competitors. Hence, Syngenta must launch its product in USA.
TASK 4
4.1 Information processing tools for business
Some of the important information processing tools are given below. MIS- It is also known as management information system and is used to store as well as
process huge set of information (Willcocks, 2013). On the basis of processed

information, report is generated which is used by managers for their day to day decision
making. DIS- Full form of DIS is decision information system and it contains all features of MIS.
Additional feature that DIS has is simulation facility. By using this, accurate prediction
can be made. Hence, this information system is used by top level managers in an
organization.
 TPS- It is also known as transaction processing system and in this record of business
expenses is maintained (Sinha and Labi, 2011). On the basis of processed information
report is generated that is used for preparing cost curtailing strategy for the business.

4.2 Project plan for business project
Illustration 5: GANTT chart

Illustration 6: Network diagram
Interpretation
It is an important method of project evaluation and under this series of activities is
planned that needs to be performed in sequence to complete project on time (Jacobsen and et.al.,
2010). If project activities will not be completed in sequence then project cost will increase. In
this case sequence of activities is 1+5+7+10+11 and it means that project must be completed in
261 days.
4.3 Project evaluation techniques
Table 6: Calculation of pay back period method
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
Interpretation

Payback period indicate the time period within which project can be completed. It can be
seen from the above table that project A can be completed in three days. Whereas, project B can
be completed in three years. Pay back period is same in case of both projects and it can be said
that none of the project on the basis of this parameter can be assumed viable for the firm.
Table 7: Calculation of ARR
Project A Project B
Initial
investment 150 150
1 30 30
2 40 50
3 60 50
4 30 40
5 50 40
Total 210 210
Average 42 42
ARR 28.00 28.00
Interpretation
ARR indicate average rate of return on the project. In other words it can be said that this
tool reflects the average return that can be earned on the project (Hernández-Lerma and Lasserre,
2012). In this case ARR of both project is same and none of project can be assumed viable for
the firm.
Table 8: Calculation of NPV
Project A PV@10% Present value Project B PV @10%
Present
value
Initial
investment 150 150
1 30 0.909 27.27 30 0.909 27.27
2 40 0.826 33.04 50 0.826 41.3
3 60 0.751 45.06 50 0.751 37.6
4 30 0.683 20.49 40 0.683 27.3

5 50 0.621 31.05 40 0.621 24.84
Total 156.91 158.28
NPV 6.91 8.28
Interpretation
NPV refers to the residual value of the project that originate when annual expenditure is
deducted from the present value of cash flows. NPV gives more clear overview of project
viability then pay back period method. This is because in payback period and ARR concept of
present value is not used but in NPV present value is used to discount firm cash flows of the
project. NPV of both project is positive but project B have higher NPV then project A. Hence, on
this basis former project is assumed viable for the firm.
Table 9: Calculation of 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% 12.09%
Interpretation
IRR indicate actual return that can be earned on the project (Internal rate of return,
2014). IRR reflects actual return and ARR indicate average return that can be earned on the
project. Hence, most of project manages prefer to use IRR instead of ARR. In this case IRR of
project B is higher then project A and on this basis former project is assumed viable for the firm.
CONCLUSION
On the basis of above discussion it is concluded that launching of new product in USA
will be profitable for the firm. It is also concluded that managers must time to time use statistical
tools like mean, median and mode in order to analyze data in systematic way. Along with this
they must also use project evaluation method in order to select most profitable project for the

firm. If project will be selected only by viewing a figures then non viable project can be selected
by the firm. Hence, it is very important to use project evaluation method.