Transcript Net Profit Margin

BY
ANITHA .C
ASHA V
DEEPTHI .J
SHALINI
OBJECTIVE:
The main objective of our project is collection, classification, analysis and interpretation of data for
making effective decisions and to show an understanding of the basic concepts of Statistics.
DATA COLLECTION:
The data base includes 28 Global out sourcing companies from both India and abroad.
The data was collected from
www.sourcingmag.com
NASSCOM site and individual web sites of the company.
VARIABLES
The variables used are Name of Companies, Services and Location.
The other variables are Revenue, Net profit Margin, Net Profit and No of Employees.
Revenue (M)
Net Profit
Margin
Net Profit
(M)
Employees
Services
Location
886
18.34
162.49
25000
Both
FOREIGN
Perot Systems
2000
5.20
104.00
18000
ITO
FOREIGN
Infosys
2200
26.02
572.44
58000
Both
INDIA
TATA Consulting Services
2900
21.97
637.13
54000
ITO
INDIA
757
2.57
19.45
13000
ITO
INDIA
Genpact
1000
12.25
122.50
30000
BPO
INDIA
Mellon
4300
18.88
811.84
17000
BPO
FOREIGN
86700
4.07
3528.69
150000
ITO
FOREIGN
Convergys
2600
4.89
127.14
66000
BPO
FOREIGN
Capgemini
6900
2.03
140.07
60000
Both
FOREIGN
i-Flex Solutions
323
16.65
53.78
6000
ITO
INDIA
Larsen & Toubro
InfoTech
2100
8.32
174.72
24000
ITO
INDIA
Fiserv
4060
11.66
473.40
23000
BPO
FOREIGN
17100
7.18
1227.78
123000
Both
FOREIGN
1460
9.57
139.65
9000
BPO
FOREIGN
123
8.99
11.06
8500
BPO
FOREIGN
1100
22.81
250.91
29000
Both
INDIA
IBM Global Services
46200
9.33
4310.46
20000
Both
FOREIGN
Oracle
11800
23.51
2774.18
50000
ITO
FOREIGN
30
14.84
4.50
2000
BPO
FOREIGN
19700
1.52
299.44
117000
Both
FOREIGN
Wipro
2300
18.95
435.85
55000
Both
INDIA
ADP
8500
12.38
1052.30
44000
BPO
FOREIGN
14600
3.95
576.70
79000
ITO
FOREIGN
Xansa
376
3.67
13.80
6000
BPO
FOREIGN
MphasiS
205
15.94
32.68
12000
Both
FOREIGN
62
32.27
20.04
4000
BPO
FOREIGN
2900
4.76
138.04
22000
BPO
FOREIGN
NAME OF COMPANIES
Cognizant
HCL
Hewlett Packard
Accenture
Ceridian
ICICI One Source
Satyam
Datamatics
EDS
Computer Sciences Corp
Peoplesupport
Hewitt
Revenue: For a company, this is the total amount of money received by the
company for goods sold or services provided during a certain time period.
Net Profit: It shows what the company has earned (or lost) in a given period of
time.
Net Profit Margin: It is the net profit divided by net revenue, often expressed
as a percentage. The higher the net profit margin is, the more effective the
company is at converting revenue into actual profit.
Employee: It is the total employee strength of the firm.
Location: Location of the company’s head quarter.
DATA TYPES
Qualitative data: Data are non numeric in nature and can’t be measured.
Here services and location of outsourcing companies are the qualitative data.
Quantitative data: Data are numerical in nature and can be measured.
Here revenue, net profit, net profit margin and employees are taken as
quantitative data.
QUALITATIVE DATA ANALYSIS
INDIAN
29%
INDIAN
Foreign
Foreign
71%
The pie chart shows that most of the companies are
foreign companies compared to the Indian companies.
Out of the 28 out sourcing companies 71% are foreign
and 29% are Indian companies.
b) DISTRIBUTION OF COMPANIES BASED ON SERVICES PROVIDED
Both
32%
BPO
39%
BPO
ITO
Both
ITO
29%
Out of the 28 outsourcing companies most of the companies
are involved in Business process outsourcing.
c) NET PROFIT DISTRIBUTION
BPO
16%
Both
41%
BPO
ITO
Both
ITO
43%
From this it can be inferred that of the 28 out
sourcing venders, ITO Companies contributes
the most (43%) followed by the companies
which outsource both ITOs and BPOs.
On comparing the above pie charts, it can be
inferred that though BPO’s are more in
numbers the net profit is mainly contributed
by the ITO sector.
QUANTITATIVE DATA ANALYSIS
a) FIVE NUMBER SUMMARY
1)
Minimum
30
2)
Lower Quartile Q1
3)
Median
2250
4)
upper Quartile Q3
7300
5)
Maximum
854
86700
b) REVENUE DISTRIBUTION
REVENUE
No. of
companies
Q1
853.75
7
Q2
2250
7
Q3
7300
8
Q4
86700
6
Pie Chart
Q4, 6, 21%
Q1, 7, 25%
Q1
Q2
Q3
Q4
Q3, 8, 29%
Q2, 7, 25%
The above given table shows the quartiles of revenue .The pie chart
shows the graphical representation of the number of companies coming
under Q1,Q2,Q3 and Q4. Quartile1 has 7 companies coming within it
and constitutes 25% total revenue. Quartile2 includes 7 companies
within it and constitutes 25% of total revenue.Quartile3 includes8
companies and constitutes 29% of total revenue. Quartile4 includes 6
companies and constitutes 21%of the total revenue.
c) FREQUENCY DISTRIBUTION TABLE
Bin
Mid
value
Frequen
cy
RF
PF
CF
0
250
15
0.54
53.57
53.57
500
750
7
0.25
25.00
78.57
1000
1250
3
0.11
10.71
89.29
1500
1750
0
0.00
0.00
89.29
2000
2250
0
0.00
0.00
89.29
2500
2750
0
0.00
0.00
89.29
3000
3250
1
0.04
3.57
92.86
3500
3750
1
0.04
3.57
96.43
4000
4250
0
0.00
0.00
96.43
4500
4750
1
0.04
3.57
100.00
5000
28
100.00
From the frequency distribution table we can construct
Histogram, Percentage Frequency Curve and Ogive Curve.
HISTOGRAM
Histogram is snapshot of the frequency distribution. Here the x axis
represents the class (net profit) and y axis represents the frequency.
Histogram
16
14
12
Series1
frequency
10
8
6
4
2
0
250
750
1250
1750
2250
2750
3250
3750
4250
4750
net profit
PERCENTAGE FREQUENCY CURVE
Here the Relative frequency is expressed in percentages.
Percentage Frequency Curve
Percentage Frequency
60.00
50.00
40.00
30.00
Series1
20.00
10.00
0.00
250
750
1250 1750 2250 2750 3250 3750 4250 4750
Net Profit
OGIVE CURVE
The Ogive Curve is a graphical representation of the cumulative frequency distribution using numbers
or percentages. Here the net profit values are on x axis and cumulative frequency in percentages are
on y axis. A line graph in the form of a curve is plotted connecting the cumulative frequency. The net
profit is the highest when the cumulative frequency is 100.
From the above Ogive curve it is observed that the frequency first increases, then remains constant
and slowly increases again.
From the Ogive curve, any value on the X axis can be found just by dropping a line.
Ogive Curve
cumulative Frequency
120.00
100.00
80.00
60.00
Series1
40.00
20.00
0.00
250
750
1250 1750 2250 2750 3250 3750 4250 4750
netprofit
d) CORRELATION AND REGRESSION
Correlation is a study that focuses on the strength of association or relationship
between variables.
Correlation coefficient: It measures the degree to which two interval scaled
variables are linearly associated.
It is a pure number that lies in the interval -1 - +1. There could be zero correlation,
positive correlation or negative correlation.
Regression is a process of predicting the value of the response variable that
depends on one or more number of independent variable.
CORRELATION BETWEEN REVENUE AND EMPLOYEES
100000
90000
80000
70000
Revenue
60000
50000
Series1
y = 0.31x - 3596
2
R = 0.4222
40000
Linear (Series1)
30000
20000
10000
0
0
50000
100000
-10000
Employee
150000
200000
Karl Pearson’s correlation measures quantitatively the extent to which two variables are
correlated .
For a set of n pairs of value of x and y, Pearson’s correlation coefficient is given by,
r= Cov(x, y)/ (σx *σy)
Here coefficient of correlation between Revenue and Employee is 0.65.From this it can be
inferred that there is substantial correlation between Revenue and Employee.
Intercept
-3596.04
Slope
0.31
Regression eqn
y=0.31x-3596
CORRELATION BETWEEN REVENUE AND PROFIT
Revenue Vs Net profit
5000.00
4500.00
4000.00
Net Profit
3500.00
3000.00
Series1
2500.00
Linear (Series1)
2000.00
1500.00
1000.00
500.00
0.00
0
20000
40000
60000
revenue
80000
100000
Coefficient of correlation between Net Profit and revenue is 0.82.
Here it is clear that there is a high correlation between the revenue and net profit.
That is as revenue increase the net profit also increases.
Intercept
218.5
5
Slope
0.049
7
Regression equation
y=218.55+.9497
SPEARMAN’S RANK CORRELATION COEFFICIENT
This method is applied to measure the association between two variables when only
ordinal or rank data are available. Mathematically, spearman’s rank correlation coefficient
is defined (SRCC) as
R= 1- (6εd^2/n (n^2-1)) = 0.88
R=0.87 shows that the net profit is strongly associated with revenue.
The coefficient of correlation varies between 0.7 and 1, shows that there is high positive
correlation.
e) PROBABILITY DISTRIBUTION
Services/
Employee
BPO
ITO
BOTH
Total
0-25000
8
4
3
15
25000-50000
2
1
1
4
50000-75000
1
1
3
5
75000-100000
0
1
0
1
100000-125000
0
0
2
2
125000-150000
0
1
0
1
Total
11
8
9
28
From these various probabilities can be calculated of which some of them are given below:
Probability that a company being both (BPO&ITO) and having 550000 employees is 0.33
Probability that a given company is BPO 0.39
Probability that a given company is an ITO and has 20000 employees is 0.14
THANK YOU