BYANITHA .C

ASHA VDEEPTHI .J

SHALINI

OBJECTIVE:

The main objective of our project is collection, classification, analysis and interpretation of data formaking 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.

NAME OF COMPANIESNAME OF COMPANIES Revenue (M)Revenue (M)Net Profit Net Profit

MarginMarginNet Profit Net Profit

(M)(M) EmployeesEmployees ServicesServices LocationLocation

CognizantCognizant 886886 18.3418.34 162.49162.49 2500025000 BothBoth FOREIGNFOREIGN

Perot SystemsPerot Systems 20002000 5.205.20 104.00104.00 1800018000 ITOITO FOREIGNFOREIGN

InfosysInfosys 22002200 26.0226.02 572.44572.44 5800058000 BothBoth INDIAINDIA

TATA Consulting ServicesTATA Consulting Services 29002900 21.9721.97 637.13637.13 5400054000 ITOITO INDIAINDIA

HCLHCL 757757 2.572.57 19.4519.45 1300013000 ITOITO INDIAINDIA

GenpactGenpact 10001000 12.2512.25 122.50122.50 3000030000 BPOBPO INDIAINDIA

MellonMellon 43004300 18.8818.88 811.84811.84 1700017000 BPOBPO FOREIGNFOREIGN

Hewlett PackardHewlett Packard 8670086700 4.074.07 3528.693528.69 150000150000 ITOITO FOREIGNFOREIGN

ConvergysConvergys 26002600 4.894.89 127.14127.14 6600066000 BPOBPO FOREIGNFOREIGN

CapgeminiCapgemini 69006900 2.032.03 140.07140.07 6000060000 BothBoth FOREIGNFOREIGN

i-Flex Solutionsi-Flex Solutions 323323 16.6516.65 53.7853.78 60006000 ITOITO INDIAINDIA

Larsen & Toubro Larsen & Toubro InfoTechInfoTech 21002100 8.328.32 174.72174.72 2400024000 ITOITO INDIAINDIA

FiservFiserv 40604060 11.6611.66 473.40473.40 2300023000 BPOBPO FOREIGNFOREIGN

AccentureAccenture 1710017100 7.187.18 1227.781227.78 123000123000 BothBoth FOREIGNFOREIGN

CeridianCeridian 14601460 9.579.57 139.65139.65 90009000 BPOBPO FOREIGNFOREIGN

ICICI One SourceICICI One Source 123123 8.998.99 11.0611.06 85008500 BPOBPO FOREIGNFOREIGN

SatyamSatyam 11001100 22.8122.81 250.91250.91 2900029000 BothBoth INDIAINDIA

IBM Global ServicesIBM Global Services 4620046200 9.339.33 4310.464310.46 2000020000 BothBoth FOREIGNFOREIGN

OracleOracle 1180011800 23.5123.51 2774.182774.18 5000050000 ITOITO FOREIGNFOREIGN

DatamaticsDatamatics 3030 14.8414.84 4.504.50 20002000 BPOBPO FOREIGNFOREIGN

EDSEDS 1970019700 1.521.52 299.44299.44 117000117000 BothBoth FOREIGNFOREIGN

WiproWipro 23002300 18.9518.95 435.85435.85 5500055000 BothBoth INDIAINDIA

ADPADP 85008500 12.3812.38 1052.301052.30 4400044000 BPOBPO FOREIGNFOREIGN

Computer Sciences CorpComputer Sciences Corp 1460014600 3.953.95 576.70576.70 7900079000 ITOITO FOREIGNFOREIGN

XansaXansa 376376 3.673.67 13.8013.80 60006000 BPOBPO FOREIGNFOREIGN

MphasiSMphasiS 205205 15.9415.94 32.6832.68 1200012000 BothBoth FOREIGNFOREIGN

PeoplesupportPeoplesupport 6262 32.2732.27 20.0420.04 40004000 BPOBPO FOREIGNFOREIGN

HewittHewitt 29002900 4.764.76 138.04138.04 2200022000 BPOBPO FOREIGNFOREIGN

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%

Foreign

71%

INDIAN

Foreign

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

BPO

39%

ITO

29%

Both

32%

BPO

ITO

Both

Out of the 28 outsourcing companies most of the companies are involved in Business process outsourcing.

c) NET PROFIT DISTRIBUTION

BPO

16%

ITO

43%

Both

41% BPO

ITO

Both

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)1) MinimumMinimum 3030

2)2) Lower Quartile QLower Quartile Q11 854854

3)3) MedianMedian 22502250

4)4) upper Quartile Qupper Quartile Q33 73007300

5)5) MaximumMaximum 8670086700

b) REVENUE DISTRIBUTION

REVENUEREVENUENo. of No. of

companiescompanies

Q1Q1 853.75853.75 77

Q2Q2 22502250 77

Q3Q3 73007300 88

Q4Q4 8670086700 66

Pie Chart

Q1, 7, 25%

Q2, 7, 25%Q3, 8, 29%

Q4, 6, 21%

Q1

Q2

Q3

Q4

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

BinBinMid Mid

valuevalueFrequenFrequen

cycy RFRF PFPF CFCF

00 250250 1515 0.540.54 53.5753.57 53.5753.57

500500 750750 77 0.250.25 25.0025.00 78.5778.57

10001000 12501250 33 0.110.11 10.7110.71 89.2989.29

15001500 17501750 00 0.000.00 0.000.00 89.2989.29

20002000 22502250 00 0.000.00 0.000.00 89.2989.29

25002500 27502750 00 0.000.00 0.000.00 89.2989.29

30003000 32503250 11 0.040.04 3.573.57 92.8692.86

35003500 37503750 11 0.040.04 3.573.57 96.4396.43

40004000 42504250 00 0.000.00 0.000.00 96.4396.43

45004500 47504750 11 0.040.04 3.573.57 100.00100.00

50005000 2828 100.00100.00

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

0

2

4

6

8

10

12

14

16

250 750 1250 1750 2250 2750 3250 3750 4250 4750 net profit

freq

uen

cy

Series1

PERCENTAGE FREQUENCY CURVE

Here the Relative frequency is expressed in percentages.

Percentage Frequency Curve

0.00

10.00

20.00

30.00

40.00

50.00

60.00

250 750 1250 1750 2250 2750 3250 3750 4250 4750

Net Profit

Per

cen

tag

e F

req

uen

cy

Series1

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

0.00

20.00

40.00

60.00

80.00

100.00

120.00

250 750 1250 1750 2250 2750 3250 3750 4250 4750

netprofit

cum

ula

tive

Fre

qu

ency

Series1

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

y = 0.31x - 3596

R2 = 0.4222

-10000

0

10000

20000

30000

40000

50000

60000

70000

80000

90000

100000

0 50000 100000 150000 200000

Employee

Re

ve

nu

e

Series1

Linear (Series1)

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.

InterceptIntercept -3596.04-3596.04

SlopeSlope 0.310.31

Regression eqnRegression eqn y=0.31x-3596y=0.31x-3596

CORRELATION BETWEEN REVENUE AND PROFIT

Revenue Vs Net profit

0.00

500.00

1000.00

1500.00

2000.00

2500.00

3000.00

3500.00

4000.00

4500.00

5000.00

0 20000 40000 60000 80000 100000

revenue

Ne

t P

rofi

t

Series1

Linear (Series1)

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.

InterceptIntercept218.5218.5

55  

SlopeSlope0.0490.049

77  

Regression equationRegression equation y=218.55+.9497y=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/Services/EmployeeEmployee BPOBPO ITOITO BOTHBOTH TotalTotal

0-250000-25000 88 44 33 1515

25000-5000025000-50000 22 11 11 44

50000-7500050000-75000 11 11 33 55

75000-10000075000-100000 00 11 00 11

100000-125000100000-125000 00 00 22 22

125000-150000125000-150000 00 11 00 11

TotalTotal 1111 88 99 2828

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 0.33Probability that a given company is BPO 0.39Probability that a given company is an ITO and has 20000 employees is 0.14

THANK YOU