Consumer Preferences and Pricing Analysis

This assignment delves into the analysis of consumer preferences for various dishes and their influence on pricing decisions. It examines factors consumers consider when making purchasing choices, analyzes trends in consumer behavior, and utilizes statistical tools to present findings effectively. Visual aids such as trend line graphs, bar charts illustrating preference, and network diagrams are included to enhance understanding.

BUSINESS DECISION
MAKING

TABLE OF CONTENTS
INTRODUCTION...........................................................................................................................3
TASK 1............................................................................................................................................3
1.1 Plan for collection of primary and secondary data................................................................3
1.2 Sampling method..................................................................................................................3
1.3 Questionnaire for research ..................................................................................................4
TASK 2............................................................................................................................................7
2.1 Information for decision making..........................................................................................7
2.2 Analysis of results to draw conclusion..................................................................................7
2.3 Calculation of standard deviation .........................................................................................8
2.4 Calculation of quartile, percentile and correlation................................................................8
TASK 3............................................................................................................................................9
3.1 Charts on collected data........................................................................................................9
3.2 Trend analysis.....................................................................................................................12
3.3 Covered in PPT...................................................................................................................12
3.4 Formal business report........................................................................................................12
TASK 4..........................................................................................................................................13
4.1 Information processing tools for the business ....................................................................13
4.2 Network diagram.................................................................................................................14
4.3 Project evaluation methods.................................................................................................15
CONCLCUSION ..........................................................................................................................17
REFERENCES..............................................................................................................................18
INDEX OF TABLES
Table 1: Calculation of mean, median and mode............................................................................8
Table 2: Calculation of standard deviation......................................................................................9
Table 3: Calculation of percentile....................................................................................................9
Table 4: Calculation of correlation................................................................................................10
Table 5: Calculation payback period ............................................................................................17
Table 6: Calculation of ARR.........................................................................................................17
Table 7: Calculation of NPV..........................................................................................................18
Table 8: Calculation of IRR...........................................................................................................18

ILLUSTRATION INDEX
Illustration 1: People preferences on dishes...................................................................................11
Illustration 2: People response on factors they often consider while making pricing decisions.. .12
Illustration 3: Trend analysis chart................................................................................................13
Illustration 4: GANTT chart..........................................................................................................15
Illustration 5: Network diagram.....................................................................................................16

INTRODUCTION
In today business world managers are giving great importance to the use of statistical tool
as it help in analyzing business conditions in legitimate way. They usually apply statistical tools
like correlation, standard deviation and percentile on available data and make business decisions.
In this report these mentioned tools are applied practically on the data. Apart from this, methods
like NPV and IRR are used to identify best viable project for the firm which is taken in the report
understanding broad application of the mentioned tools. At end CPM diagram is also enclosed
and sequence for performance of activities is determined.
TASK 1
1.1 Plan for collection of primary and secondary data
It is inevitable to collect both sort of data because both help in understanding research
topic in much better way. Primary data refers to data that is gathered by one at his own level. On
other hand, secondary data indicate the facts and figures that are already collected by some one
and are printed in books and journals. There is significance of both type of data in relation to
performance of research. It has been find out that researchers often collect secondary data before
conducting a research because be evaluating various literature's they comes to know about
various things that happened in past related to research topic (Blake and Isard, 2012). Such kind
of knowledge of research topic help an individual in determining a direction in which research
must be conducted. Hence, it can be said that understanding of secondary data help an individual
in drafting a questionnaire for the research. Hence, it can be said that there is great significance
of primary and secondary data in research. As per plan prepared from sources like books and
magazines relevant facts and figures will be collected by the researcher. On other hand, for
collecting new facts and figures questionnaire will be circulated between 50 people that live in
the London. These ways will be followed to collect data for the research.
1.2 Sampling method
There are many sampling methods and some of them are described below. Simple random sampling- This is widely used methods of sampling and under this all
sampling units are taken on random basis from population. This method can be easily
used by any person. Simple random sampling method is used in any research when for
data collection specific type of respondents are not required.

 Stratified random sampling- Under this method all sampling units are taken by dividing
population in several parts. From these sub divisions of population sample units are taken
by the researcher. Hence, this method is appropriate for research because by using same
data can be collected from different type of people in relation to present study. Convenience sampling- This is a method in which one according to his comfort take
sample units from sample (Ackermann, 2012). This method is used by many researchers
instead of simple random sampling.
 Cluster sampling- In this technique specific area is separated in various parts. All
sample units are picked up from these divided areas. The mentioned technique can not be
employed in the research because for research specific type of respondents are required
that vary from each other in terms of demographic features.
1.3 Questionnaire for research
Name : ___________________
Age : ____________________
Marital status
 Married
 Unmarried
 Transgender
Gender
 Male
 Female
 Transgender
1. In which of following category of income below given you fall.
 2000 - 3000
 3100 - 4000
 4100- 5000
 More than 5000
2. How many times you visit to Murano restaurant in a month?
 1- 2
 3 - 4
 5 - 6

 Greater than 6 times
3. When you go to the Murano restaurant for lunch or dinner how many times you place order
for food items?
 1
 2
 3
 More than 3 time
4. Which type of dishes given below you prefers for lunch or dinner?
 European
 Italian
 Mexican
 Chinese
5. Which of these factors you highly consider for taking lunch or dinner at restaurant?
 Price
 Taste
 Staff service
 Waiting time
6. Do you think that Murano restaurant is providing products at high price.
 Yes

 No
7. In which of below given categories services offered by Murano comes?
 Exceptional
 Very good
 Good
 Average
 Poor
8. On which of special occasions you like to visit Murano restaurant?
 Birthday
 Wedding anniversary
 New year
 Valentine day
 Working holidays
9. Your feedback on our services.
___________________________________________________________________________
TASK 2
2.1 Information for decision making
Table 1: Calculation of average, median and mode
1 30000
2 35000

3 40000
4 45000
5 50000
Mean 40000
Median 40000
Mode #VALUE! Mean- It indicate mean value of the particular variable. In order to measure whether firm
perform good or bad mean value is compared to current figure of the variable. This tool is
commonly used by data analyst and researchers because it reflects the average
performance of the specific variable (du Plessis and Van Niekerk, 2014). Hence, by using
this tool managers get an overview of the variable. Due to this reason this tool is very
famous among the researchers. Median- It is a method that separate entire data set in two parts. It is used to identify
pattern in which variable is moving in relation to the specific variable. If we compare
both divided data set with each other then trends can be identified more easily. Hence,
this tool is also very popular among the researchers.
 Mode- Mode is another important statistical tool that is used to identify specific number
that is observed in the data set frequently (Neumark, Wall and Zhang, 2011). This tool
helps in analyzing trend or pattern in which specific variable is moving. Hence, by using
this tool data analysts often make prediction about future movement that may takes place
in the variable.
2.2 Analysis of output of statistical tools mean, median and mode Mean- From above table it may be observed that average figure of the sales is 40,000
and current number of same variable is 50000. It may be observed that firm book a sale
above its sale that firm made on average basis. Hence, it may be state the Murano give a
magnificent performance in its concern. If mean sales value is greater then current sales
then it can be said that firm is giving good performance in its business. Median- The value 40000 is separating data in to two parts. It can be observed from the
figures that there is same trend in both data sets and sales of the firm is changing at same
pace every years. Hence, firm sales is growing at static growth rate.

 Mode- In this case there is no value of mode which means that none of the value is
repeating frequently in the data set. Firm sales is elevating consistently and there is no
issue of concern for top managers of the firm.
2.3 Calculation of standard deviation
Table 2: Calculation of standard deviation
1 30000
2 35000
3 40000
4 45000
5 50000
STDEV 7905.6
Interpretation
It is a tool that indicate the extent to which values of the variables are moving from
average value of the variable (Ellis, 2012). Value of standard deviation is 7905.6 and it is very
high. On this basis it can be said that there is huge difference between current and average sale of
the firm. If in future gap between current sales and average sales will be contracted then it will
be a matter of concern for the managers.
2.4 Calculation of quartile, percentile and correlation
Table 3: Calculation of percentile
1 30000
2 35000
3 40000
4 45000
5 50000
Q1 35000
Q2 40000
Q3 45000
Interpretation

The tools on which calculation is done on above table are computing same thing and both
of them are dividing entire data in to three parts. There is different method of calculation in case
of both tools but values of these tools also remain same (Braitenberg and Schüz, 2013). It can be
said that values of qaurtile is increasing continuously and it indicate that revenue is elevating
consistently. There is equal gap in Q1,Q2 and Q3 values of quartile and it can be said that there
is a equal gap in values of sales in all years. Percentile helps in analyzing data in better way then
median. This is because in case of median data set is separated in two parts. Contrary to this, in
case of percentile data set is separated in to various parts. Hence, it can be assumed that
percentile helps in analyzing data set in better way then median.
Table 4: Calculation of correlation
1 30000 3000
2 35000 3500
3 40000 4000
4 45000 4500
5 50000 5000
Correlation 1
Interpretation
Correlation is a statistical tool which reflects the extent to which variables that are taken
in to consideration are connected to each other. It is observed that value of correlation always
remain in boundary of negative value one to zero and positive value of one. If value of
correlation is between 0 and 1 then it means that values of variable are positively correlated to
each other (Stock, Wright and Yogo, 2012). If value of correlation is nearby to 1 then it will be
interpreted that there is strong relationship between variables. In case if mentioned statistical
value is find out negative that if value of one variable is increasing then same of other variable is
declining. Here, value of correlation is positive and it is one which means that firm profit on
sales is entirely dependent on sales. Hence, if Murano restaurant sales will decline by 10% then
its profit will also increase by 10%.

TASK 3
3.1 Charts on collected data
Which type of dishes given below you prefers for lunch or dinner?
European 20
Italian 17
Mexican 7
Chinese 6
Interpretation
It can be seen from the chart given above that out of 50 respondents 20 prefer to eat
European dishes and 17 prefer to consume Italian dishes. Whereas, only 7 and six respondents
like to eat Mexican and Chinese dishes in London. Hence, will be beneficial for Murano
restaurant if it will give more importance to European and Italian dishes then Mexican and
Chinese food items.
Which of these factors you highly consider for taking lunch or dinner at restaurant?
European Italian Mexican Chinese
0
5
10
15
20
25
20
17
7 6
Column C
Illustration 1: People preferences on dishes

Price 20
Taste 15
Staff service 10
Waiting time 5
Interpretation
From figures it is clear that most of respondents think that price is an important factor
that people highly consider while taking lunch or dinner at the hotel. Apart from this taste and
staff service are another factor to which people are giving due importance while visiting a
restaurant. People does not give too much importance to waiting time in making their purchase
decisions. 20 respondents state that they give importance to price and 15 state that they give
priority to taste while taking lunch or dinner in any restaurant. 10 respondents give importance to
staff service and 5 give priority to waiting time. Hence, it can be said that Murano restaurant
must focus on making available tasty food at cheaper price and with good service quality.
20
15
10
5
Price
Taste
Staff service
Waiting time
Illustration 2: People response on factors they often consider while making pricing decisions

3.2 Trend analysis
1 2 3 4 5
0
10000
20000
30000
40000
50000
60000
Column B
Column C
Power (Column C)
Illustration 3: Trend line graph for firm

Interpretation
It is a technique which is employed to make forecast about upcoming years. It may be
observed from the image above that revenue will elevate back to back in upcoming years
(Slowiński, 2012). This prediction is made because trend line is moving upward. Managers can
not completely rely on this method because it is not necessary that past trends remain continue in
future. Hence, managers must should make use of simulation method in order to make reliable
prediction about the future time period.
3.3 Covered in PPT
3.4 Formal business report
To
The Board of Directors of Murano restaurant Date: 5th May 2016
Sir/ Mam
Present study was conducted to find out whether there is opportunity in the London market.
This research was also conducted to understand consumer behavior of the people. On study it is
find out that there is good business opportunities in the London market and firms must enter in
to this market. People are highly sensitive to price, quality of food and service quality. Hence,
1 2 3 4 5
0
10000
20000
30000
40000
50000
60000
f(x) = 5000x + 25000
Column C
Linear (Column C)
Illustration 4: Trend analysis chart

firm must try to make available products at low price and of good quality to the customer's. For
preparing research report in systematic way every type of data is taken in to consideration.
Same are analyzed by charting of collected data and applying statistical tools like quartile and
percentile etc. In this way entire research is completed.
TASK 4
4.1 Information processing tools for the business
Following are the information processing tools that can be used in business. Decision support system- It is one of the most important information system that is used
by business organizations. It is observed that in most of the organizations CEO and CFO
use this information system. In DSS large number of facts and figures are stored and
prepared by managers. By processing a data report is prepared which is used by managers
for making business decisions. Management information system- MIS is used by departmental heads and branch
mangers of an organization that operate at middle level of management (Ruppert, 2011).
In MIS also big number of figures data is saved and processed by the managers. On the
basis of generated report managers makes their business decisions.
 Transaction processing system- TPS is used by supervisors that works at the production
place. In the mentioned system data related to transactions is stored and processed. On
the basis of generated report managers prepare cost curtailment strategy that directly
benefits an organization.
 Microsoft software's- There are many software's of Microsoft like MS word, excel,
PowerPoint and access. On these software huge data can be recorded and analyze as well
as present in systematic way before key stakeholders. Hence, there is great use of
Microsoft software's.

4.2 Network diagram
Illustration 5: GANTT chart

Interpretation
It is a method that indicate the number of days within which project should be completed
by the project manager. Contrary to this, if project will not be executed within stipulated time
period cost of same will increase (Ellis, 2012). It is inevitable to perform project activities in
series that is revealed by the above given chart. From review of chart critical path is identified
and chronological set of activity for the project is 1-5-8-9-10 that means project must be
completed in 22 days.
4.3 Project evaluation methods
Table 5: Calculation payback period
Initial
investment -190000
1 50000 -140000
2 64000 -76000
3 58000 -18000
4 70000 52000
Interpretation
Illustration 6: Network diagram

It is a tool which reflect the duration after which project can start earning profit for the
firm (Tohidi, 2011). Here, values are negative for three years and project life is four years. Thus,
it can be assumed that project is not viable for the firm. The merit of mentioned method is that it
can be applied by any person as knowledge of finance is not require to apply this method.
Table 6: Calculation of ARR
Project
Initial
investment 190000
1 50000
2 64000
3 58000
4 70000
Total 242000
Average 48400
ARR 25.47%
Interpretation
ARR is also known as average rate of return and value of same is 25.47% which is also
very low (Patton, 2011). On average basis each project have 30% ARR and proposed project can
not be considered profitable for the firm. The plus point of this technique is that it reflect mean
performance of the project. Weak point of this technique is that present value method is not use
in this method.
Table 7: Calculation of NPV
Project PV @12% Present value
Initial
investment 190000 `
1 50000 0.893 44643
2 64000 0.797 51020
3 58000 0.712 41283
4 70000 0.636 44486

Total 181433
NPV -8567
Interpretation
NPV indicate current value of the project which comes in existence when initial
investment is deducted from the total of present values of cash flows (Nguyen and et.al., 2013).
It is seen that in many projects NPV value is in plus and in some its value is in minus. If NPV is
positive then it means that project is viable for the firm. So, if net present value of project is in
minus then it can be interpreted that same is not profitable for the firm. From table it can be
observed that net present value is in minus. Thus, it can be state that project is not viable for the
firm. Plus point of NPV technique is that it reflect actual value of the project that comes in
existence when initial investment value is deducted from present value of cash flows (Catalani
and Minkler, 2010). Limitation is that in this technique in order to calculate current value of the
project discount rate is employed in calculation. If in correct interest rate will be used in
calculation then non profitable project may be picked up by the managers.
Table 8: Calculation of IRR
Project A
Initial
investment -190000
1 50000
2 64000
3 58000
4 70000
IRR 9.94%
Interpretation
IRR is also known as internal rate of return and it indicate actual return that is earned by
the project (Schmidt, 2016). The only difference between ARR and IRR is that former method
indicate average return of the specific variable but latter method indicate actual return of the
project. Hence, latter method is often preferred by the managers then latter firm. Here, IRR of
project is 9.94% and it may be state that project is not viable for the firm. Plus point of this

technique is that it indicate actual return that is earned by the project. On other hand, main weak
point of this technique is that it is hard to use this method.
CONCLCUSION
In above part from start to end detail discussion is carried out on various statistical tools
like quartile, percentile and correlation on the specific data. By using these methods data can be
analyzed in proper manner from different sides. Hence, those who are managing the firm may
make wise business decisions by making best use of these tools. On the basis of above discussion
it is inferred that project department of an organization must apply techniques like payback
period, NPV, IRR and ARR for selecting most profitable project for the business. This is because
only by looking at figures most viable project can not be selected for the firm. Thus, in order to
choose most profitable project for the firm managers must use methods like IRR, NPV, ARR and
pay back methods.

REFERENCES
Books & journal
Ackermann, S.J., 2012. Are small firms important? Their role and impact. Springer Science &
Business Media.
Blake, A. and Isard, M., 2012. Active contours: the application of techniques from graphics,
vision, control theory and statistics to visual tracking of shapes in motion. Springer
Science & Business Media.
Braitenberg, V. and Schüz, A., 2013. Anatomy of the cortex: statistics and geometry (Vol. 18).
Springer Science & Business Media.
Catalani, C. and Minkler, M., 2010. Photovoice: A review of the literature in health and public
health. Health Education & Behavior. 37(3). pp.424-451.
du Plessis, H. and Van Niekerk, A., 2014. A new GISc framework and competency set for
curricula development at South African universities. South African Journal of
Geomatics. 3(1). pp.1-12.
Ellis, R.S., 2012. Entropy, large deviations, and statistical mechanics (Vol. 271). Springer
Science & Business Media.
Neumark, D., Wall, B. and Zhang, J., 2011. Do small businesses create more jobs? New
evidence for the United States from the National Establishment Time Series. The Review
of Economics and Statistics. 93(1). pp.16-29.
Nguyen, P. and et.al., 2013. Sexual health promotion on social networking sites: a process
evaluation of The FaceSpace Project. Journal of Adolescent Health. 53(1). pp.98-104.
Patton, M.Q., 2011. Developmental evaluation: Applying complexity concepts to enhance
innovation and use. Guilford Press.
Ruppert, D., 2011. Statistics and data analysis for financial engineering (pp. 183-216). New
York, NY: Springer.
Slowiński, R., 2012. Fuzzy sets in decision analysis, operations research and statistics (Vol. 1).
Springer Science & Business Media.
Stock, J.H., Wright, J.H. and Yogo, M., 2012. A survey of weak instruments and weak
identification in generalized method of moments. Journal of Business & Economic
Statistics.