Juxt Consult India Employee Speak 2007 Current Hr Trends

India Employee Speak 2007

Current HR Trends


Current HR Trends


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Current HR Trends


Table of contents India Employee Speak 2007 ............................................. 1 India Employee Speak 2007 Reports ................................... 2 Methodology............................................................... 3 Executive Summary ...................................................... 5 Key Findings ............................................................... 7 Detailed Findings- Current Terms of Employment ........................................21 Age at First Job ..........................................................23 Total Work Experience .................................................26 Number of Jobs Held....................................................29 Proportion Who Moved Jobs with a Promotion .....................32 Total Work Experience .................................................35 Average Tenure per Job ................................................37 Tenure with Current Company ........................................38 Demographic Profile ....................................................43 Socio-Economic Profile .................................................62 Segment Wise Detailed Tables ........................................64

Current HR Trends


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India Employee Speak 2007 India Employee Speak 2007 is one of the largest survey based annual HR studies on the latest ‘white collar’ HR trends and corporate perceptions in India. The study attempts to uncover the HR trends in all types of industry segments and companies. It not only profiles the work experience details and current job satisfaction levels of those currently employed but also uncovers job aspirations and expectations of those who aspire to be employed soon. The study also delves into the job search behavior and preferences of both the currently employed as well as the prospective ‘white collar’ employees. The India Employee Speak 2007 reports are designed to provide you with:

Insightful understanding of key current HR trends and issues in the white collar world - employment terms, average tenures, salary levels and benefits, employee expectations, satisfaction levels, improvements desired, etc.

Comparative trends - by industry segments, sectors, size of

companies, job functions, hierarchy levels, etc.

Expected future trends - based on current aspirations and intentions of employees and prospective employees.

Employee expectations and aspirations – employee speak on good

job content, HR policies, corporate reputations, etc.

Job search dynamics – active versus passive search, preferred search methods, preferred job search intermediaries (both offline and online) and their perceptions.

Corporate brand perceptions - attractiveness of companies on key

corporate image parameters and key HR parameters (both at the overall level as well as at the industry level).

Demographic and socio-economic statistics on current and potential

while collar employees.

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India Employee Speak 2007 Reports Main Reports

Current white collar employment trends and practices

Current job search behavior and preferences

Current employee expectations, motivations, satisfaction and desired improvements

Current company perceptions on key corporate and HR parameters

Possible Supplementary Reports

Category Reports∗ (examples)-

Industry specific (IT/ITES, Consumer Goods, Consumer Services, industrial Goods, Banking/Finance)

Function specific (Marketing, Finance/Accounts, Admin & General

Management, IT) Segment Reports∗ (examples)-

Women (vis-à-vis men)

Qualified professionals (vis-à-vis general qualification ones)

Corporate employees on the net

Fresher (vis-à-vis the working ones)

∗ depending on the sufficiency of sample size of relevant respondents


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Methodology The India Employee Speak 2007 study findings are based on a very large sample base of over 16,500 current and prospective employees surveyed online in April-May 2007. The online surveys were conducted through an e-mailer campaign undertaken by a leading generic portal in India among their opted-in and active email users, as well as banner and text ads using Google Ad Sense (contextual search ads). The online survey was conducted using an e-questionnaire segmented into three sections. In the online questionnaire, a response format of ‘clicking’ a single or multiple options among the various given options was used for most questions. For each of these questions it was also possible for a respondent to answer ‘none’ or ‘any other’. However, all perceptions, associations and recall based answers were collected ‘unprompted’ and respondents were asked to type in the name of the company in a ‘text box’ provided for the purpose. To enlist complete and sincere responses, an incentive of a significant cash prize was also announced to be given to one randomly selected respondent at the end of the survey. The questionnaire was pre-tested and timed to take approximately 20 minutes (± 5 minutes) for a respondent to complete depending on the speed of comprehension and answering of the questions. The questionnaire was structured and designed to reduce the level of ‘respondent fatigue’ to an extent that was practically possible. Over 16,500 unduplicated and clean responses were collected from the online survey campaign in about 4 weeks time. The responses covered employees of over 4,765 companies of various sizes from all types of industry segments, sectors, job functions and hierarchy levels. These respondents came from over 2, 975 unique universities and educational institute alumni. Table 1: Sample sizes achieved in the online survey

Employment Profile Sample Size %

Salaried employees 9,000 55%

Completed studies but unemployed 1,315 8%

Students 3,232 20%

Others (self-employed, business owners, retired) 2,772 17%

Total Sample 16,319 100%

The collected data was then made representative of the urban Indian population by using appropriate 'demographic multipliers’ using highly authentic Govt. of India population statistics. The weights were derived using 4 highly employment relevant demographic parameters – age, socio-economic classification (SEC), town class and region.

The end result is that the findings possibly represent the 'white collar' employment and HR trends of over 160 million urban Indians (almost

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half of the total urban Indian population of around 336 million in 20071). Further, the findings represent and effectively cover urban Indians from all SEC groups, all age groups above 18 years, all income groups and all types of town classes (right down to 20,000 population size level towns). Table 2: Urban population representation of the survey sample data

Demographic Attributes Study Respondent Profile Actual Urban Population2

Below 18 years Not included in study NA

18-24 years 38% 33%

25-35 years 25% 27%

36-45 years 19% 18%

Age Distribution

Above 45 years 18% 22%

SEC - A 17% 9%

SEC – B 31% 18%

SEC - C 52% 25%

Socio Economic Classification

SEC – D & E Not included in study 48%

Up to 1 Lakh 25% 31%

1-5 Lakhs 9% 27%

5-30 Lakhs 40% 25% City Type by Population Size

Above 30 Lakhs 26% 17%

North 23% 24%

East 13% 15%

South 32% 29%

Region-wise Distribution

West 32% 32%

The occupational break up of over 160 million urban Indians as represented in this study is as follows:

Salaried employees - 52% - 83 million Completed studies but unemployed - 5% - 8 million Students - 27% - 43 million Self-employed - 8% - 13 million Business owners - 4% - 6.5 million Retired - 4% - 6.5 million

Total - 100% - 160 million The study broadly represents employment profiles, status, preferences, and job search behavior and company perceptions of 83 million white collar salaried employees. It further covers employment preferences, job search behavior and corporate perceptions of 51 million ‘prospective’ white collar employees. Lastly it includes corporate perceptions of additional 26 million important ‘influencers’ in the employment market (retired employees, self-employed individuals and business owners).

1 Estimate by Indicus Analytics, a leading economic research firm in India. The estimates have been derived using Census 2001 population data extrapolated to year 2007 using decadal population growth numbers.

2 Same as 1


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Executive Summary Full time employment is the norm among urban white-collar employees – only 2% hold part-time positions. Interestingly, the incidence of part-time jobs is slightly higher among those working in NGOs, IT, Consumer Services and Banking/Finance jobs and also in Emerging Towns. Females constitute about one-tenth of the urban white-collar workforce. The gender ratio improves in the IT, Consumer Services and Consumer Good industries as well as in the Private sector and in NGOs. Female employees are also relatively more common in HRs, Office Administration and Accounts /Finance roles and in Metros. The typical employee is middle-aged at 36.3 years. While less than one-fifth of the employee base is below 25 years, over a third is 25-35 years old and the majority viz. nearly half the workforce is above 35 years of age. Those employed in the Private sector, working in IT, Consumer Goods and Healthcare industries are relatively younger. About 2-in-5 are from relatively smaller towns. If Metros and Urban Uptowns account for 58% of the urban white-collar workforce, the Emerging Towns and Other Towns account for a sizeable 42%. In fact while Public Sector employees largely originate from the smaller towns (73%), employees of NGOs are primarily from Metros (76%) and the Private Sector has a sizeable contribution from Metros and Urban Uptowns (59%). Only 1-in-5 holds a ‘professional’ educational degree. In fact ‘professional’ stream post-graduates number even fewer at 1-in-10. The clear majority, 66%, has either not pursued an under-graduate degree or has done so in a general stream. The incidence of ‘professional’ employees is higher in IT, Healthcare, Core Industries and in the HR function. The socio-economic profile is largely commonplace - only 1-in-5 belongs to the ‘premium’ stratum. A minority, 21%, belongs to SEC A and a similar proportion claims monthly household income levels of Rs.30,000 or more. This also gets reiterated by the low ownership of cars (23%) and credit cards (41%). The average age for entering the white-collar workforce is 23 years. While nearly a third starts working when they turn 20 years old or even earlier, the majority does so only later. This offers an explanation for the fairly ‘old’ age profile of the average employee. The initiation age is slightly lower (22 years)among those who belong to Metros /Urban Uptowns, those who have not pursued higher education post schooling and for those engaged in Office Administration functions or in the Government sector. Experience runs high with the average work experience adding up to 13 years. This ties up with the aforementioned age profile and is also

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not surprising since over half (51%) the employees have work experience of 10 years or more and about a fourth (26%)have been in the workforce for at least 2 decades! The work experience is higher among those engaged in Marketing/Communication Services or Core Industries and those in the Office Administration function. Among the town classes, the work experience of those in smaller towns is relatively higher (13.3 years compared to 10.8 years among Metro employees). On the other hand, those working in the Private sector especially in the IT sector have lower work experience. The average number of jobs held is 2.7 although 1-in-4 has held 4 or more jobs. While half the workforce has held 1 or 2 jobs, the balance has held at least 3 jobs. The number of jobs held is relatively higher among Private sector employees, among those engaged in Consumer Goods, Consumer Services, Core Industries, Healthcare and those in the HR function. Employees in larger towns have held more jobs on an average than their counterparts in smaller towns. While the typical tenure with the current company is 7.7 years, the average tenure per job is significantly lower at 4.7 years. The length of the tenure varies interestingly across the various segments. Those employed in Marketing/ Communication Service, Banking/ Finance, Core Industries or engaged in Accounts/ Finance or Administrative functions tend to stick on longer in their jobs while those the Private sector especially in IT industries and those engaged in Marketing, Design/ Creative functions change relatively jobs faster. Employees in small towns also show a relatively higher average tenure per job. Over half the workforce earns up to Rs.2 lacs annually and the average annual package is roughly Rs.2.6 lacs. Packages are relatively better among Private Sector companies, among Core Industries and in the IT, HRs and Accounts/Finance functions. Surprisingly, employees in Urban Uptowns and Other towns have higher salary and benefits packages on an average than their counterparts in Metros. Most aspire for jobs in the Private Sector especially in Core Industries and IT companies. This could be partly on account of the higher salary packages drawn by employees in the Private Sector and in these industries. The Private Sector is specially sought after by those in Government jobs. The majority would move out of Healthcare, Marketing and Consumer Services industries if given a choice. IT and Core Industries not only top the list of aspired industries overall but also have the highest ‘loyalty’ in terms of proportion of employees voting for their current industry. Bonus, HRA and Medical Reimbursement are the most sought after company benefits. Nearly 3-in-4 employees aspire for these benefits. Employer’s contribution to Provident Fund and LTA are lower in the list. Driver allowance, Company leased car and Stock Options – which are currently fairly rare benefits- are also desired by a sizeable proportion of employees.


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97.6%

2.0% 0.4%

Full-time Part time Apprenticeship / Internship

11%

89%

0%

30%

60%

90%

All white collar

Male Female

Key Findings Full time employment is the norm among white collar employees – only 2% hold part-time positions

Interestingly, the incidence of part-time jobs is slightly higher among those working in NGOs (11%), IT (5%), Consumer Services (4%) and Banking/Finance (4%) jobs and also in Emerging Towns (3%). Part-time jobs are also somewhat more common among the latest entrants to the workforce – About 6% of those with experience of less than a year, have a part-time/apprenticeship arrangement with their employer.

Females constitute about one-tenth of the urban white-collar workforce

Males dominate the white-collar ‘employee-scape’ with a whopping 89% share.

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14%

26%22%

3%

35%

0%

10%

20%

30%

40%

All white collar

Below 21 years 21-25 years 25-35 years35-45 years Above 45 years

The gender ratio improves in the IT, Consumer Services and Consumer Good industries as well as in the Private sector and in NGOs. Table 3: Distribution of employees by gender, by industry verticals

Female employees are also relatively more common in HRs, Office Administration and Accounts /Finance roles and in Metros. An interesting observation is that while the share of Female employees among Trainees/ Freshers is 22%, this alarmingly reduces to 6% among Senior Mgt. This could either be indicative of a growth in female employees at the entry level and/or of a disposition of female employees to exit the workforce over time.

The typical employee is middle-aged at 36.3 years

While less than one-fifth of the employee base is below 25 years, over a third is 25-35 years old and the majority viz. Nearly half the workforce is above 35 years of age. This is also evident from the fact that 58% are married and have children.

Gender Marketing / Comm. Services

Consumer Services

Core Ind. / Ind. Goods & Services

Banking & Finance IT Consumer

Goods Healthcare

Projected Base 2,482,231 8,297,777 11,498,625 5,446,781 5,922,796 5,076,814 3,502,774

Male 91% 87% 95% 89% 81% 87% 89%

Female 10% 14% 6% 11% 19% 13% 11%


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Those employed in the Private sector, working in IT, Consumer Goods and Healthcare industries are relatively younger.

Age Marketing / Comm. Services

Consumer Services



Goods Healthcare

Projected Base 2,482,231 8,297,777 11,498,625 5,446,781 5,922,796 5,076,814 3,502,774

Bellow 21 years 1% 4% 4% 7% 7% 3% 1%

21-25 years 11% 9% 10% 15% 32% 17% 16%

25-35 years 37% 37% 27% 26% 49% 45% 50%

35-45 years 18% 31% 30% 23% 8% 24% 25%

Above 45 years 34% 19% 29% 30% 5% 12% 10% Average age of employees 39 37 38 37 28 34 33

As may have been expected, the age profile of employee by and large increases with seniority – while the average Trainee is aged 26 years, Senior Managers at the other end of the spectrum average 40 years. Interestingly, Junior Managers (average 38 years) do not appear to follow this trend since they are actually older than Middle Managers (average 36 years). This could be related to their education level and will be examined subsequently.

Only 1-in-5 holds a 'professional' educational degree

In fact 'professional' stream post-graduates number even fewer at 1-in-10. The clear majority, 66%, has either not pursued an under-graduate degree or has done so in a 'general' stream. The incidence of 'professional' employees is higher in IT, Healthcare, Core Industries and in the HR function.

Educational Qualification

All white collar

Marketing / Comm. Services

Consumer Services



Goods Healthcare

Projected Base 56,614,875 2,482,231 8,297,777 11,498,625 5,446,781 5,922,796 5,076,814 3,502,774

HSC/SSC 32% 53% 34% 36% 18% 23% 23% 21% Graduate General Stream 35% 23% 33% 30% 50% 34% 42% 42%

Graduate Professional Stream 8% 3% 4% 11% 5% 15% 6% 5%

Post-Graduate General Stream 9% 6% 11% 5% 13% 8% 11% 9%

Post-Graduate Professional Stream 10% 8% 10% 9% 13% 10% 8% 20%

Others 7% 7% 7% 10% 2% 9% 9% 3%

Professional stream 15% 10% 14% 20% 18% 25% 14% 25%

Interestingly, the proportion of ‘professional’ stream employees is significantly higher among Middle and Senior levels. This could explain the relatively lower age profile of Middle Managers compared to Junior Managers – since holding a ‘professional’ degree seems to increase the upward mobility on the corporate ladder and age does not appear to be the leading determinant of the same.

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All white collar

Trainee/ Fresher

Executive/ Operation level

Junior Management

Middle Management

Senior Management

Advisory Staff / Consultant

Projected Base 56,614,875 4,129,904 13,433,566 9,669,740 13,469,914 7,006,215 2,660,007

HSC/SSC 32% 36% 33% 30% 21% 33% 39% Graduate General Stream 35% 35% 41% 38% 32% 28% 39%

Graduate Professional Stream 8% 13% 7% 6% 9% 13% 2%

Post-Graduate General Stream 9% 7% 6% 12% 11% 8% 14%

Post-Graduate Professional Stream 10% 5% 6% 7% 16% 15% 4%

Others 7% 4% 8% 6% 11% 3% 1%

Professional Stream 18% 18% 13% 13% 25% 27% 6%

About 2-in-5 are from relatively smaller towns

If Metros and Urban Uptowns account for 58% of the urban white-collar workforce, the Emerging Towns and Other Towns account for a sizeable 42%.

26%22%

32%

21%

0%

10%

20%

30%

40%

All white collar

Metros Urban uptowns Emerging Towns Others

In fact while Public Sector employees largely originate from the smaller towns (73%), employees of NGOs are primarily from Metros (76%) and the Private Sector has a sizeable contribution from Metros and Urban Uptowns (59%). Also, the Marketing/Communication services industry and Core Industries (to a lesser extent) have a higher proportion of employees belonging to Other towns whereas IT industries are skewed on Metro residents and Banking and Healthcare companies have a higher share of employees from Emerging Towns.


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Table 4: Distribution of employees by city type, by industry verticals

City Type Marketing / Comm.Services

Consumer Services



Goods Healthcare Others

Projected Base 2,482,231 8,297,777 11,498,625 5,446,781 5,922,796 5,076,814 3,502,774 7,610,865

Metros 29% 33% 22% 27% 53% 32% 30% 33%

Urban uptowns 13% 22% 29% 24% 29% 31% 21% 23% Emerging Towns 13% 24% 22% 29% 12% 17% 28% 19%

Others 45% 22% 27% 20% 7% 19% 22% 26%

The socio-economic profile is largely commonplace - only 1-in-5 belongs to the 'premium' stratum

A minority, 21%, belongs to SEC A and a similar proportion claims monthly household income levels of Rs.30,000 or more. This also gets reiterated by the low ownership of cars (23%) and credit cards (41%). On the other hand, mobile phones are very common with 87% ownership.

22%21%

43%

0%

10%

20%

30%

40%

50%

All white collar

SEC A SEC B SEC C

Distribution of employees by MHI All white collar

Projected Base 56,614,875

Sample Base 9,000

Up to Rs.10,000 34.10%

Rs.10,000 to Rs.20,000 27.70%

Rs.20,000 to Rs.30,000 14.50%

Rs.30,000 to Rs.50,000 8.40%

Rs.50,000 to Rs.75,000 3.40%

Rs.75,000 to Rs.100,000 3.00%

More than Rs.100,000 6.60%

70% of the salaried employees are the chief wage earner of the household. This also means that at least 30% are from multiple income households.

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Chief Wage Earner (CWE)

30%

70%

Not the CWE CWE

Marketing/Communication Services and Consumer Services have a significantly higher share of SEC C employees whereas Healthcare, Consumer Goods and Core Industries have a relatively higher proportion of SEC A employees. Banking/ Finance industry has the highest share of SEC B employees.

Distribution of employees by SEC


Consumer Services



Goods Healthcare

Projected Base 2,482,231 8,297,777 11,498,625 5,446,781 5,922,796 5,076,814 3,502,774

SEC A 17% 15% 24% 23% 20% 25% 28%

SEC B 22% 31% 39% 44% 33% 36% 37%

SEC C 61% 54% 38% 33% 47% 38% 35%

Other highlights related to the socio-economic profile are:

The Public Sector boasts of the highest proportion of SEC A employees (26.4%), the Government Sector has a relatively higher share of SEC B employees (43%) while the NGOs are dominated by SEC C (69%).

The above sectoral SEC distribution is also reflected in the income

level - 28% of Public sector employees belong to households with monthly incomes Rs.30,000 or more whereas this proportion drops to 23% and 13% respectively among Private sector employees and NGOs.

HR function has a visibly higher share of SEC A employees (44%)

Designing / Creative function largely comprises SEC C employees

(75%)

Credit card ownership is most common among employees belonging to Metros (34%)

Middle/Senior Mgt have larger shares of SEC A employees (31%, 37%

respectively)

Car ownership is as expected more common among Middle/ Senior Mgt


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11%9% 9%

15%

10%

26%

10% 10%

0%

10%

20%

30%

All white collar

Up to 1 year 1-3 years 3-5 years5-7 years 7-10 years 10-15 years15-20 years Above 20 years

Ownership of credit cards as well mobile phones is less prevalent

among employees working in the Consumer Services industry - this could be related to the higher share of SEC C employees in this sector as mentioned earlier

The average age for entering the white-collar workforce is 23 years.

While nearly a third (30%) start working when they turn 20 years old or earlier, the majority does so only later - the most common age of entry being 21-22 years. This offers an explanation for the fairly 'old' age profile of the average employee seen earlier.

19% 20% 19%

4%

11%

28%

0%

10%

20%

30%

40%

All white collar

Up to 18 years Age 19-20 years Age 21-22 years

Age 23-24 years Age 25-30 years Above Age 30 years

The initiation age is slightly lower (22 years) among those who belong to Metros /Urban Uptowns. Not surprisingly, those who do not pursue higher education post-schooling enter the workforce relatively earlier. Employees engaged in Office Administration functions or in the Government sector also start working earlier than others.

On the other hand, those in the IT and Designing / Creative functions are comparatively older when they embark upon their careers. To illustrate this point, 64% of employees engaged in IT and 66% of those engaged in Designing/ Creative functions began working at the age of 21-24 years compared to only 48% among all white-collar employees.

Experience runs high with the average work experience adding up to 13 years

This is not surprising since over half (51%) the employees have work experience of 10 years or more and about a fourth (26%)have been in the workforce for at least 2 decades!

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The work experience is higher among those engaged in Marketing/Communication Services or Core Industries and those in the Office Administration function. Among the town classes, the work experience of those in smaller towns is relatively higher (13 years compared to 11 years among Metro employees). On the other hand, those working in the Private sector especially in the IT sector have lower work experience.

Total work experience

Marketing / Comm Services

Consumer Services

Core Industries



Projected Base 2,482,231 8,297,777 11,498,625 5,446,781 5,922,796 5,076,814 3,502,774 7,610,865

Up to 1 year 5% 6% 7% 4% 15% 6% 8% 4%

1-3 years 8% 11% 7% 17% 33% 12% 10% 4%

3-5 years 12% 5% 8% 11% 15% 13% 20% 7%

5-7 years 5% 14% 5% 8% 14% 13% 9% 7%

7-10 years 15% 7% 8% 8% 9% 14% 14% 8%

10-15 years 11% 20% 16% 9% 8% 15% 18% 18%

15-20 years 9% 8% 12% 7% 3% 16% 8% 13%

Above 20 years 35% 28% 37% 37% 4% 13% 13% 39%

Average Years 17 13 16 14 5 10 9 17

The average number of jobs held is 2.7 although 1-in-4 has held 4 or more jobs

While half the workforce has held 1 or 2 jobs including the current job, the balance has held at least 3 jobs.

21%

12%

7%3%

1% 1% 1% 0%

29%25%

0%

10%

20%

30%

All white collar

1 2 3 4 5 6 7 8 9 10

The number of jobs held is relatively higher among Private sector employees, among those engaged in Consumer Goods, Consumer Services, Core Industries, Healthcare and those in the HR function. Employees in larger towns have held more jobs on an average than their counterparts in smaller towns. Not surprisingly, the average number of jobs held increases with the work experience of the employee. For instance, while the average number of jobs among those who have been working for a year is 1.3 (22% have moved on within a year of their first job!) This increases to


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3.3 among those with 7-10 years of experience. Interestingly, the white collar veterans with work experience of more than 10 years actually display lower mobility (average number of jobs 3.0) than those with 7-10 years of work experience.

While the typical tenure with the current company is 7.7 years, the average tenure per job is significantly lower at 4.7 years

The tenure with the current company is significantly higher than the average tenure across all jobs held. This indicates that by and large, the disposition to change jobs is higher during the earlier period of an employee’s career graph. Chart 1: Tenure with current company

21%

5% 5%

10%6%

15%

30%

9%

0%

10%

20%

30%

40%

All white collar

Up to 1 year 1-3 years 3-5 years 5-7 years7-10 years 10-15 years 15-20 years Above 20 years

The length of the tenure varies interestingly across various segments. Those employed in Marketing/ Communication Service, Banking/ Finance, Core Industries or engaged in Accounts/ Finance or Administrative functions tend to stick on longer in their jobs while those the Private sector especially in IT industries and those engaged in Marketing, Design/ Creative functions change relatively jobs faster. Employees in small towns also claim a relatively higher average tenure per job.

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Average Tenure

per Job (years)

Average Tenure with Current Company

(years)

All Employees 4.7 7.7

Marketing/ Communication Services 6.2 13.4

Core Industries 5.6 8.5

Banking / Finance 5.6 10.4

Consumer Services 4.6 8.9

Healthcare 3.4 4.1

Consumer Goods 3.3 5.2

IT 1.9 1.6

Government sector 8.8 17.6

NGO 8.6 15.6

Public Sector 7.5 15.7

Private Sector 3.9 6.0

Office Administration 6.6 12.0

Accounts and Finance 5.2 9.2

Human Resources 4.5 7.5

Project Management 4.4 6.6

Marketing 3.7 5.3

Design / Creative 3.3 6.0

IT 3.1 5.1

Larger size companies show more efficient use of employees (better productivity)

Only 1 in 5 (21%) white collar employees come from a small company of less than 50 employees. Almost half (47%) are working in relatively larger size companies with over 500 employees. However in terms of turnover, a significantly higher 40% of the white collar employees work in smaller companies with less than 50 crores in turnover. This indicates a disproportionately less efficient use of people (or lower turnover per employee) in the smaller companies as compared to the relatively larger companies. The efficiency equation increases with size and large companies show the best efficiency ratio (probably a result of economies of scale).


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Distribution by company size

40% 39%

21%

47%

21%

33%

0%

10%

20%

30%

40%

50%

Small (upto 50) Medium (51- 500) Large (501 plus)

Size by no. of employees Size by turnover in crore rupees

Over half the workforce earns upto Rs.2 lacs annually and the average annual package drawn is roughly Rs.2.6 lacs

Packages are relatively better among Private Sector companies, among Core Industries and in the IT, HRs and Accounts/Finance functions. Surprisingly, employees in Urban Uptowns and Other towns have higher salary and benefits packages on an average than their counterparts in Metros.

27%

10%

3% 2% 2%0%

15%

26%

15%

0%

10%

20%

30%

All white collar

Up to Rs 1 lac Rs 1-2 lacs Rs 2-3 LacsRs 3-5 lacs Rs 5-7 lacs Rs 7-10 lacsRs 10-20 lacs Above Rs 20 lacs Not Specified

Current Salary Levels and Benefits Packages

Marketing / Comm Services

Consumer Services



Goods Healthcare

Projected Base 2,482,231 8,297,777 11,498,625 5,446,781 5,922,796 5,076,814 3,502,774

Up to Rs.1 lac 18% 34% 22% 23% 27% 34% 26%

Rs.1-2 lacs 41% 26% 24% 28% 35% 20% 31%

Rs.2-3 Lacs 15% 19% 16% 21% 14% 14% 9%

Rs.3-5 lacs 4% 6% 13% 15% 9% 10% 16%

Above Rs.5 lacs 6% 5% 15% 6% 5% 8% 12%

Rs.7-10 lacs 2% 1% 4% 2% 1% 3% 1%

Rs.10-20 lacs 1% 1% 5% 1% 1% 1% 2%

Above Rs.20 lacs 0% 0% 0% 1% 1% 1% 0% Average annual salary (Rs.) 218731 183977 332324 251621 238612 252728 249540

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Other highlights related to salary and benefits are:

Not surprisingly, the average packages increase with hierarchy – ranging from Rs.1 lac for Trainees to Rs.4 lacs for Senior Managers.

Those with a ‘professional’ degree, especially a post-graduate

degree, earn more than those possessing a ‘general’ degree

Salary levels are relatively higher in IT, HRs and Accounts/ Finance functions

Most aspire for jobs in the private sector and in core industries and IT companies

This could be partly on account of the higher salary packages drawn by employees in the Private Sector and in these industries as seen above. The Private Sector is specially sought after by those in Government jobs - 4-in-5 aspire for a Private Sector job. Further, 95% of the employees currently with the Private Sector want to continue with the sector.

Aspired Sectors

All White Collar

Currently in Government sector

Currently in Public sector

Currently in Private sector

Projected Base 24,497,230 2,886,979 1,188,199 18,542,505

Public Sector 6.20% 11.90% 41.50% 3.60%

Private Sector 91.60% 80.30% 58.20% 95.10%

Others 2.20% 7.80% 0.40% 1.30%

The majority would move out of Healthcare, Marketing and Consumer Services industries if given a choice. IT and Core Industries not only top the list of aspired industries overall but also have the highest ‘loyalty’ in terms of proportion of employees voting for their current industry.

Aspired Industry Verticals All White Collar

Marketing / Comm

Services

Consumer Services

Core Ind. / Ind. Goods &

Services

Banking &

Finance IT Consumer

Goods Healthcare

Projected Base 24,497,230 635,881 3,356,202 5,674,216 2,976,054 3,257,304 2,257,245 1,384,939

Marketing / Comm. Services 2% 14% 4% 0.0% 0.1% 4% 0.3% 2%

Consumer Services 14% 14% 29% 9% 4% 5% 18% 8% Core Ind. / Ind. Goods & Services 32% 17% 19% 54% 28% 13% 21% 17%

Banking & Finance 11% 17% 2% 6% 42% 7% 7% 8%

IT 29% 33% 31% 20% 22% 69% 22% 25%

Consumer Goods 11% 6% 12% 11% 4% 2% 32% 27%

Healthcare 0.9% 0.2% 0.3% 0.4% 0.0% 0.0% 0.0% 11%

Consultancy 2% 0.6% 2% 0.4% 0.6% 0.3% 0.7% 1%


19

Other points related to aspirations of employees are:

As may have been expected, most employees aspire for the next hierarchical level

Project Mgt, Marketing and Office Administration functions are

overall more sought after while HRs and IT functions show the highest growth in movement from current function to aspired function

Employees in Accounts / Finance and IT functions display the

highest ‘satisfaction’ in terms of proportion voting for their current function

Bonus, HRA and medical reimbursement are the most sought after company benefits.

Nearly 3-in-4 employees aspire for these benefits. Employer’s contribution to Provident Fund and LTA are lower in the list. Driver allowance, Company leased car and Stock Options – which are currently fairly rare benefits and relatively more common among the middle/senior Mgt cadre - are also desired by a sizeable proportion of employees.

Current Benefits Aspired Benefits

Bonus 50% 76%

House Rent Allowance (HRA) 58% 74%

Medical bill reimbursement 52% 71%

Medical insurance and Hospitalization 44% 65%

Employers Contribution to Provident fund 58% 64%

Leave Travel Allowance 50% 63%

Performance Incentive 33% 61%

Petrol Expense Reimbursement 32% 56%

Gratuity 47% 53%

Transport (pick and drop) 24% 47%

Company leased accommodation 17% 36%

Company leased car 7% 31%

Ex-Gratia 20% 28%

Stock options 3% 25%

Driver Allowance 4% 19%

Restricted stock unit 1% 9%

Current HR Trends

20

Detailed Findings- Current HR Trends


21

98%

2% 0.4%Full-time Part time Apprenticeship / Internship

Current Terms of Employment Chart 2: Current terms of employment

Base: 9,000

Current HR Trends

22

Table 5: Current terms of employment by industry verticals

Current Terms Of Employment

Marketing / Comm.

Services Consumer

Services Core Ind. / Ind.

Goods & Services



Projected Base 2,482,231 8,297,777 11,498,625 5,446,781 5,922,796 5,076,814 3,502,774 7,610,865

Full-time 98% 96% 99% 96% 95% 100% 98% 99%

Part time 2% 4% 0.8% 4% 5% 0.5% 2% 1%

Apprenticeship / Internship

0.1% 0.5% 0.7% 0.1% 0.2% 0.0% 0.7% 0.2%

Base: 9,000

Table 6: Current terms of employment by job function

Base: 9,000

Table 7: Current terms of employment by hierarchy level


Trainee/Fresher Executive /Operation

Junior Mgt Middle Mgt Senior Mgt Advisory Staff / Consultant

Projected Base 4,129,904 13,433,566 9,669,740 13,469,914 7,006,215 2,660,007

Full-time 92% 98% 99% 97% 99% 98%

Part time 4% 2% 1% 3% 1% 2%

Apprenticeship / Internship 4% 0.3% 0.0% 0.0% 0.4% 0.0%

Base: 9,000

Table 8: Current terms of employment by educational qualification

Current Terms Of Employment HSC/SSC Graduate

General Stream Graduate

Professional Stream Post-Graduate

General Stream Post-Graduate

Professional Stream

Others

Projected Base 17,843,583 19,640,344 4,422,478 5,276,626 5,559,933 3,871,911

Full-time 97% 98% 97% 99% 98% 99%

Part time 3% 2% 0.9% 1% 1% 1%

Apprenticeship / Internship 0.4% 0.2% 2% 0.2% 0.5% 0.0%

Base: 9,000

Table 9: Current terms of employment by years of experience

Current Terms Of Employment Less than 1 year 1 - 3 years 4 - 6 years 7 - 10 years More than 10 yearsProjected Base 5,777,915 6,405,850 7,635,364 8,042,904 28,752,843Full-time 94% 96% 99% 97% 98%Part time 3% 3% 0.8% 3% 2%Apprenticeship / Internship 3% 0.2% 0.4% 0.1% 0.1%

Base: 9,000


Accounts & Finance

Office Admin & General Mgt Marketing IT HR Project Mgt &

Operations Designing /

Creative Services

Projected Base 6,146,271 12,504,097 12,221,536 4,172,091 1,397,504 9,691,283 2,651,668

Full-time 99% 97% 97% 98% 98% 97% 98%

Part time 1% 2% 3% 1% 2% 2% 2%

Apprenticeship / Internship

0.1% 0.3% 0.5% 0.1% 0.0% 0.8% 0.0%


23

19% 20% 19%

4%

11%

28%

0%

10%

20%

30%

40%

All white collar

Up to 18 years Age 19-20 years Age 21-22 years

Age 23-24 years Age 25-30 years Above Age 30 years

Age at First Job Chart 3: Age at first job

Base: 9,000

Current HR Trends

24

Table 10: Age at first job, by industry verticals

Age At First Job Marketing /

Comm. Services

Consumer Services




Projected Base 2,482,231 8,297,777 11,498,625 5,446,781 5,922,796 5,076,814 3,502,774 7,610,865

Up to 18 years 6% 21% 12% 10% 8% 10% 7% 11%

Age 19-20 years 42% 15% 20% 19% 20% 21% 14% 18%

Age 21-22 years 16% 25% 29% 26% 30% 32% 34% 32%

Age 23-24 years 18% 16% 19% 32% 26% 18% 24% 21%

Age 25-30 years 17% 21% 19% 13% 14% 17% 21% 17%

Above Age 30 years 0% 3% 1% 1% 1% 2% 1% 1%

Average age in 1st Job 21.50 22.10 22.10 22.10 22.10 22.30 22.70 22.30

Base: 9,000

Table 11: Age at first job, by job function

Age At First Job Accounts & Finance



Creative Services

Projected Base 6,146,271 12,504,097 12,221,536 4,172,091 1,397,504 9,691,283 2,651,668

Up to 18 years 7% 21% 10% 7% 13% 9% 2%

Age 19-20 years 21% 25% 18% 13% 9% 21% 19%

Age 21-22 years 25% 21% 31% 33% 31% 31% 45%

Age 23-24 years 27% 13% 21% 30% 22% 17% 21%

Age 25-30 years 19% 17% 18% 16% 23% 20% 13%

Above Age 30 years 2% 2% 3% 0% 1% 2% 0%

Average age in 1st Job 22.40 21.60 22.60 22.40 22.80 22.40 22.10

Base: 9,000

Table 12: Age at first job, by hierarchy level

Age At First Job Trainee/Fresher Executive/ Operation level

Junior Mgt Middle Mgt Senior Mgt Advisory Staff / Consultant

Projected Base 4,129,904 13,433,566 9,669,740 13,469,914 7,006,215 2,660,007

Up to 18 years 15% 9% 15% 11% 7% 9%

Age 19-20 years 25% 16% 18% 18% 29% 24%

Age 21-22 years 37% 31% 26% 29% 30% 21%

Age 23-24 years 12% 20% 22% 25% 17% 18%

Age 25-30 years 11% 23% 18% 16% 12% 24%

Above Age 30 years 1% 1% 1% 2% 5% 4%

Average age in 1st Job 21.30 22.50 22.10 22.20 22.60 22.90

Base: 9,000


25

Table 13: Age at first job, by educational qualification

Age At First Job HSC/SSC Graduate General Stream

Graduate Professional Stream

Post-Graduate General Stream

Post-Graduate Professional Stream

Others

Projected Base 17,843,583 19,640,344 4,422,478 5,276,626 5,559,933 3,871,911

Up to 18 years 29% 11% 9% 7% 2% 6%

Age 19-20 years 23% 21% 14% 7% 12% 28%

Age 21-22 years 18% 29% 38% 29% 23% 34%

Age 23-24 years 8% 22% 27% 26% 34% 21%

Age 25-30 years 15% 15% 13% 28% 27% 9%

Above Age 30 years 6% 2% 1% 3% 2% 2%

Average age in 1st Job 21.90 22.20 22.20 23.50 23.70 21.90

Base: 9,000

Table 14: Age at first job, by years of experience

Age At First Job Less than 1 year 1 - 3 years 4 - 6 years 7 - 10 years More than 10 years

Projected Base 5,777,915 6,405,850 7,635,364 8,042,904 28,752,843

Up to 18 years 29% 18% 14% 8% 13%

Age 19-20 years 16% 23% 19% 21% 19%

Age 21-22 years 18% 24% 27% 37% 25%

Age 23-24 years 12% 23% 24% 16% 20%

Age 25-30 years 12% 12% 15% 17% 21%

Above Age 30 years 14% 1% 1% 2% 3%

Average age in 1st Job 23.30 21.40 21.80 22.20 22.60

Base: 9,000

Current HR Trends

26

11%9% 9%

15%

10%

26%

10% 10%

0%

10%

20%

30%

All white collar

Up to 1 year 1-3 years 3-5 years5-7 years 7-10 years 10-15 years15-20 years Above 20 years

Total Work Experience Chart 4: Total work experience

Base: 9,000


27

Table 15: Total work experience by industry verticals

Total Work Experience

Marketing / Comm.

Services Consumer

Services Core Ind. / Ind.

Goods & Services



Projected Base 2,482,231 8,297,777 11,498,625 5,446,781 5,922,796 5,076,814 3,502,774 7,610,865

Up to 1 year 5% 6% 7% 4% 15% 6% 8% 4%

1-3 years 8% 11% 7% 17% 33% 12% 10% 4%

3-5 years 12% 5% 8% 11% 15% 13% 20% 7%

5-7 years 5% 14% 5% 8% 14% 13% 9% 7%

7-10 years 15% 7% 8% 8% 9% 14% 14% 8%

10-15 years 11% 20% 16% 9% 8% 15% 18% 18%

15-20 years 9% 8% 12% 7% 3% 16% 8% 13%

Above 20 years 35% 28% 37% 37% 4% 13% 13% 39%

Average Years 16.80 13.30 15.80 13.90 5.00 10.30 9.40 16.50

Base: 9,000

Table 16: Total work experience by job function

Total Work Experience Accounts & Finance Office Admin &

General Mgt Marketing IT HR Project Mgt & Operations

Designing / Creative Services

Projected Base 6,146,271 12,504,097 12,221,536 4,172,091 1,397,504 9,691,283 2,651,668

Up to 1 year 6% 6% 11% 10% 7% 7% 6%

1-3 years 12% 8% 11% 25% 6% 11% 11%

3-5 years 14% 5% 15% 15% 9% 6% 8%

5-7 years 9% 9% 11% 10% 10% 6% 13%

7-10 years 9% 9% 9% 9% 8% 11% 20%

10-15 years 14% 12% 14% 14% 17% 19% 14%

15-20 years 8% 11% 7% 8% 10% 10% 12%

Above 20 years 27% 40% 22% 10% 33% 30% 17%

Average Years 13.00 17.20 10.70 8.10 14.90 13.60 10.60

Base: 9,000

Table 17: Total work experience by hierarchy level

Total Work Experience Trainee/Fresher Executive/Operation level Junior Mgt Middle Mgt Senior Mgt Advisory Staff / Consultant

Projected Base 4,129,904 13,433,566 9,669,740 13,469,914 7,006,215 2,660,007

Up to 1 year 67% 5% 1% 1% 6% 0%

1-3 years 33% 13% 13% 7% 5% 8%

3-5 years 0% 14% 11% 11% 7% 10%

5-7 years 0% 11% 10% 13% 6% 5%

7-10 years 0% 11% 9% 12% 12% 4%

10-15 years 0% 13% 12% 18% 18% 27%

15-20 years 0% 8% 13% 14% 11% 7%

Above 20 years 0% 26% 32% 25% 37% 41%

Average Years 1.10 12.10 14.50 13.50 16.70 15.50

Base: 9,000

Current HR Trends

28

Table 18: Total work experience by educational qualification

Total Work Experience HSC/SSC Graduate General Stream

Graduate Professional



Others

Projected Base 17,843,583 19,640,344 4,422,478 5,276,626 5,559,933 3,871,911

Up to 1 year 20% 11% 19% 9% 12% 10%

1-3 years 14% 15% 25% 15% 20% 16%

3-5 years 7% 13% 9% 7% 11% 13%

5-7 years 5% 9% 6% 10% 9% 16%

7-10 years 6% 9% 9% 12% 13% 14%

10-15 years 14% 13% 8% 16% 11% 10%

15-20 years 5% 10% 7% 13% 11% 7%

Above 20 years 31% 20% 17% 20% 13% 15%

Average Years 12.20 10.90 9.20 11.30 9.10 9.30

Base: 9,000


29

21%

12%

7%3%

1% 1% 1% 0%

29%25%

0%

10%

20%

30%

All white collar

1 2 3 4 5 6 7 8 9 10

Number of Jobs Held Chart 5: Number of jobs held

Base: 9,000

Current HR Trends

30

Table 19: Number of jobs held, by industry verticals

Number Of Jobs Held


Consumer Services




Projected Base 2,482,231 8,297,777 11,498,625 5,446,781 5,922,796 5,076,814 3,502,774 7,610,865

1 41% 17% 23% 30% 27% 21% 26% 43%

2 15% 21% 22% 23% 27% 23% 22% 16%

3 20% 37% 28% 26% 21% 23% 22% 21%

4 7% 13% 11% 12% 11% 15% 17% 9%

5 4% 6% 9% 8% 8% 10% 6% 6%

6 10% 3% 2% 1% 3% 4% 6% 4%

7 4% 1% 2% 1% 1% 1% 1% 0%

8 0% 1% 1% 0% 1% 2% 0% 0%

9 0% 0% 0% 0% 1% 1% 0% 0%

10 0% 1% 0% 0% 0% 1% 0% 0%

Average Number of Jobs

2.70 2.90 2.80 2.50 2.70 3.10 2.80 2.40

Base: 9,000

Table 20: Number of jobs held, by job function

Number Of Jobs Held Accounts & Finance Office Admin &



Projected Base 6,146,271 12,504,097 12,221,536 4,172,091 1,397,504 9,691,283 2,651,668

1 30% 30% 23% 34% 18% 21% 18%

2 25% 23% 19% 19% 19% 22% 14%

3 28% 25% 29% 20% 22% 23% 37%

4 11% 8% 15% 14% 14% 18% 11%

5 3% 9% 7% 7% 18% 7% 7%

6 2% 2% 4% 2% 4% 5% 12%

7 1% 1% 2% 1% 1% 2% 1%

8 1% 1% 1% 3% 1% 1% 0%

9 0% 1% 1% 0% 2% 1% 0%

10 0% 0% 0% 0% 0% 0% 0%

Average Number of Jobs

2.50 2.60 2.90 2.60 3.30 3.10 3.20

Base: 9,000


31

Table 21: Number of jobs held, by hierarchy level

Number Of Jobs Held Trainee/Fresher Executive/Operation level Junior Mgt Middle Mgt Senior Mgt Advisory Staff / ConsultantProjected Base 4,129,904 13,433,566 9,669,740 13,469,914 7,006,215 2,660,0071 49% 21% 28% 18% 28% 30%2 36% 24% 21% 18% 20% 18%3 15% 29% 30% 29% 14% 39%4 0% 12% 11% 20% 13% 9%5 0% 8% 6% 8% 11% 2%6 0% 4% 2% 4% 8% 2%7 0% 0% 1% 2% 2% 1%8 0% 1% 1% 1% 2% 0%9 0% 0% 1% 0% 1% 1%10 0% 0% 0% 0% 1% 0%Average Number of Jobs 1.70 2.80 2.60 3.10 3.10 2.50

Base: 9,000

Table 22: Number of jobs held, by educational qualification

Number Of Jobs Held HSC/SSC Graduate

General Stream Graduate

Professional Stream Post-Graduate General

Stream Post-Graduate

Professional Stream Others

Projected Base 17,843,583 19,640,344 4,422,478 5,276,626 5,559,933 3,871,911

1 38% 30% 42% 32% 27% 23%

2 19% 19% 25% 26% 20% 22%

3 23% 23% 16% 20% 24% 40%

4 12% 13% 7% 11% 12% 7%

5 5% 9% 6% 6% 11% 6%

6 3% 3% 1% 3% 3% 1%

7 0% 1% 1% 1% 2% 1%

8 0% 1% 1% 1% 1% 0%

9 1% 1% 0% 1% 0% 0%

10 0% 0% 0% 0% 0% 0%

Average Number of Jobs 2.40 2.80 2.30 2.60 2.90 2.60

Base: 9,000

Table 23: Number of jobs held, by years of experience

Number Of Jobs Held Less than 1 year 1 - 3 years 4 - 6 years 7 - 10 years More than 10 years Projected Base 5,777,915 6,405,850 7,635,364 8,042,904 28,752,843 1 78% 38% 24% 10% 26% 2 15% 34% 27% 19% 15% 3 6% 21% 28% 29% 27% 4 1% 4% 13% 23% 14% 5 1% 3% 6% 13% 9% 6 0% 0% 1% 4% 5% 7 0% 0% 0% 1% 2% 8 0% 0% 1% 0% 1% 9 0% 0% 0% 0% 1% 10 0% 0% 0% 0% 0% Average Number of Jobs 1.30 2.00 2.60 3.30 3.00

Base: 9,000

Current HR Trends

32

26%

18%

12%

2%5%

20%18%

0%

10%

20%

30%

All white collar

Trainee /Fresher Executive / Operation levelJunior Management Middle ManagementSenior Management Top Management (CEO / Owner)Advisory Staff / Consultant

Proportion Who Moved Jobs with a Promotion Chart 6: Proportion who moved jobs with a promotion

Base: 7,355


33

Table 24: Proportion who moved jobs with a promotion, by industry verticals

Hierarchy Level Marketing /

Comm. Services

Consumer Services




Projected Base 2,336,733 7,186,001 9,976,239 4,401,476 5,100,792 4,485,602 3,018,665 5,945,488

Trainee /Fresher 10% 20% 17% 30% 17% 22% 20% 24%

Executive / Operation level 32% 22% 26% 29% 27% 27% 31% 16%

Junior Mgt 11% 18% 20% 18% 18% 20% 16% 27%

Middle Mgt 9% 16% 18% 15% 22% 19% 19% 14%

Senior Mgt 37% 11% 14% 6% 11% 8% 11% 9%

Top Mgt (CEO / Owner) 0.7% 1% 1% 0.6% 1% 2% 0.3% 3%

Advisory Staff / Consultant 1% 12% 3% 0.8% 5% 2% 3% 8%

Base: 7,355

Table 25: Proportion who moved jobs with a promotion, by job function

Hierarchy Level Accounts & Finance


Operations Designing / Creative

Services

Projected Base 5,351,303 11,088,536 10,526,789 3,022,596 1,184,946 8,632,875 2,423,984

Trainee /Fresher 23% 18% 19% 18% 15% 21% 24%

Executive / Operation level 21% 22% 31% 28% 17% 31% 18%

Junior Mgt 23% 18% 18% 18% 17% 14% 26%

Middle Mgt 11% 14% 18% 29% 31% 19% 10%

Senior Mgt 17% 13% 9% 4% 17% 11% 22%

Top Mgt (CEO / Owner) 0.4% 4% 2% 1% 1% 0.7% 0.1%

Advisory Staff / Consultant 5% 12% 3% 1% 2% 3% 0.4%

Base: 7,355

Current HR Trends

34

Table 26: Proportion who moved jobs with a promotion, by educational qualification

Hierarchy Level HSC/SSC Graduate General Stream




Professional Stream

Others

Projected Base 15,263,271 16,275,882 3,404,291 4,131,360 4,391,974 3,349,019

Trainee /Fresher 31% 21% 31% 18% 17% 26%

Executive / Operation level 25% 28% 19% 25% 22% 18%

Junior Mgt 12% 20% 15% 22% 18% 21%

Middle Mgt 13% 16% 14% 18% 26% 21%

Senior Mgt 10% 11% 7% 9% 12% 12%

Top Mgt (CEO / Owner) 0.3% 2% 7% 2% 1% 1%

Advisory Staff / Consultant 9% 3% 8% 6% 4% 0.4%

Base: 7,355

Table 27: Proportion who moved jobs with a promotion, by years of experience

Hierarchy Level Less than 1 year 1 - 3 years 4 - 6 years 7 - 10 years More than 10 years

Projected Base 3,146,288 5,373,899 6,415,544 7,147,589 24,732,477

Trainee /Fresher 67% 34% 20% 10% 17%

Executive / Operation level 15% 29% 33% 31% 21%

Junior Mgt 8% 14% 20% 22% 18%

Middle Mgt 8% 12% 14% 21% 19%

Senior Mgt 1% 6% 6% 11% 16%

Top Mgt (CEO / Owner) 0.5% 0.9% 1% 4% 2%

Advisory Staff / Consultant 1% 5% 6% 2% 8%

Base: 7,355


35

Total Work Experience Table 28: Total work experience, by industry verticals

Total Work Experience

All white collar


Consumer Services


Services



Projected Base 56,614,875 2,482,231 8,297,777 11,498,625 5,446,781 5,922,79 5,076,814 3,502,774 7,610,865

Less than 1 year 10% 5% 6% 7% 4% 15% 6% 8% 4%

1-3 years 11% 8% 11% 7% 17% 33% 12% 10% 4%

4-6 years 14% 14% 8% 11% 15% 22% 19% 26% 11%

7-10 years 14% 19% 18% 10% 12% 16% 20% 18% 11%

More than 10 years 51% 55% 57% 65% 53% 14% 43% 38% 70%

Average Years 12.64 16.77 13.29 15.76 13.91 5.02 10.31 9.36 16.50

Base: 9,000

Table 29: Total work experience, by job function

Total Work Experience All white collar Accounts

& Finance Office Admin &



Projected Base 56,614,875 6,146,271 12,504,097 12,221,536 4,172,091 1,397,504 9,691,283 2,651,668

Less than 1 year 10% 6% 6% 11% 10% 7% 7% 6%

1-3 years 11% 12% 8% 11% 25% 6% 11% 11%

4-6 years 14% 18% 10% 19% 20% 13% 9% 12%

7-10 years 14% 15% 13% 15% 14% 14% 14% 30%

More than 10 years 51% 50% 63% 43% 31% 60% 59% 43%

Average Years 12.64 12.99 17.16 10.70 8.08 14.89 13.65 10.59

Base: 9,000

Table 30: Total work experience, by hierarchy level

Total Work Experience All white collar Trainee/Fresher Executive/

Operation level Junior Mgt Middle Mgt Senior Mgt Advisory Staff / Consultant

Projected Base 56,614,875 4,129,904 13,433,566 9,669,740 13,469,914 7,006,215 2,660,007

Less than 1 year 10% 67% 5% 1% 1% 6% 0%

1-3 years 11% 33% 13% 13% 7% 5% 8%

4-6 years 14% 0% 19% 16% 15% 10% 11%

7-10 years 14% 0% 16% 14% 20% 14% 7%

More than 10 years 51% 0% 46% 56% 57% 65% 74%

Average Years 12.64 1.07 12.07 14.50 13.54 16.72 15.51

Base: 9,000

Current HR Trends

36

Table 31: Total work experience, by educational qualification

Total Work Experience All white collar HSC/SSC Graduate

General Stream


Stream


Post-Graduate Professional

Stream Others

Projected Base 56,614,875 17,843,583 19,640,344 4,422,478 5,276,626 5,559,933 3,871,911

Less than 1 year 10% 20% 11% 19% 9% 12% 10%

1-3 years 11% 14% 15% 25% 15% 20% 16%

4-6 years 14% 9% 18% 12% 11% 17% 15%

7-10 years 14% 8% 14% 12% 18% 16% 27%

More than 10 years 51% 49% 43% 32% 48% 35% 32%

Average Years 12.64 12.24 10.90 9.17 11.29 9.12 9.28

Base: 9,000


37

Average Tenure per Job Table 32: Average tenure per job

Average Tenure Per Job Less than 1 year 1 - 3 years 4 - 6 years 7 - 10 years More than 10 years

Projected Base 5,777,915 6,405,850 7,635,364 8,042,904 28,752,843

1 Job 100% 45% 12% 1% 0%

1-2 Jobs 0% 38% 50% 34% 3%

2-4 Jobs 0% 17% 27% 46% 20%

More than 4 Jobs 0% 0% 12% 19% 77%

Average Tenure of Jobs 1.00 1.72 2.39 2.83 3.75

Median Tenure of Jobs 1.00 2.00 2.00 3.00 4.00

Mode Tenure of Jobs 1.00 1.00 2.00 3.00 4.00

Base: 9,000

Current HR Trends

38

21%

5% 5%

10%6%

15%

30%

9%

0%

10%

20%

30%

40%

All white collar

Up to 1 year 1-3 years 3-5 years 5-7 years7-10 years 10-15 years 15-20 years Above 20 years

Tenure with Current Company Chart 7: Tenure with current company

Base: 9,000


39

Table 33: Tenure with current company, by industry verticals

Tenure With Current Company

Marketing / Comm.

Services

Consumer Services




Projected Base 2,482,231 8,297,777 11,498,625 5,446,781 5,922,796 5,076,814 3,502,774 7,610,865

Up to 1 year 25% 24% 24% 25% 52% 28% 27% 15%

1-3 years 17% 18% 22% 24% 30% 26% 30% 11%

3-5 years 3% 10% 11% 6% 10% 13% 18% 8%

5-7 years 2% 6% 4% 3% 6% 5% 4% 8%

7-10 years 11% 4% 5% 3% 1% 8% 7% 4%

10-15 years 9% 19% 10% 4% 2% 13% 10% 10%

15-20 years 1% 5% 11% 4% 1% 3% 3% 12%

Above 20 years 30% 15% 14% 31% 0% 6% 2% 31%

Average Years 13.40 8.90 8.50 10.40 1.60 5.20 4.10 13.00

Base: 9,000

Table 34: Tenure with current company, by job function

Tenure With Current Company

Accounts & Finance

Office Admin &

General Mgt Marketing IT HR

Project Mgt &

Operations


Projected Base 6,146,271 12,504,097 12,221,536 4,172,091 1,397,504 9,691,283 2,651,668

Up to 1 year 24% 21% 34% 39% 34% 32% 19%

1-3 years 25% 13% 25% 24% 19% 26% 26%

3-5 years 8% 10% 11% 11% 4% 6% 12%

5-7 years 6% 6% 6% 3% 8% 4% 6%

7-10 years 5% 7% 2% 4% 5% 5% 15%

10-15 years 8% 11% 10% 7% 8% 12% 6%

15-20 years 4% 7% 5% 5% 8% 4% 16%

Above 20 years 22% 26% 7% 8% 13% 12% 1%

Average Years 9.20 12.00 5.30 5.10 7.50 6.60 6.00

Base: 9,000

Table 35: Tenure with current company, by hierarchy level

Tenure With Current Company Trainee/Fresher Executive/

Operation level Junior Mgt Middle Mgt Senior Mgt Advisory Staff / Consultant

Projected Base 4,129,904 13,433,566 9,669,740 13,469,914 7,006,215 2,660,007

Up to 1 year 80% 28% 19% 25% 24% 24%

1-3 years 20% 25% 17% 22% 25% 12%

3-5 years 0% 8% 8% 12% 10% 4%

5-7 years 0% 5% 7% 6% 6% 8%

7-10 years 0% 5% 6% 5% 7% 1%

10-15 years 0% 12% 7% 13% 8% 19%

15-20 years 0% 4% 12% 6% 3% 9%

Above 20 years 0% 15% 24% 10% 17% 24%

Average Years 0.60 7.60 11.10 7.00 8.90 10.10

Base: 9,000

Current HR Trends

40

Table 36: Tenure with current company, by educational qualification

Tenure With Current Company HSC/SSC Graduate General

Stream Graduate Professional



Professional Stream Others

Projected Base 17,843,583 19,640,344 4,422,478 5,276,626 5,559,933 3,871,911

Up to 1 year 29% 30% 35% 28% 35% 28%

1-3 years 17% 22% 25% 17% 25% 24%

3-5 years 8% 10% 5% 10% 10% 13%

5-7 years 4% 5% 4% 6% 5% 9%

7-10 years 4% 4% 8% 6% 5% 3%

10-15 years 13% 9% 7% 10% 9% 7%

15-20 years 5% 6% 4% 8% 5% 9%

Above 20 years 19% 15% 13% 16% 5% 8%

Average Years 9.40 7.40 6.80 8.20 4.90 6.30

Base: 9,000

Table 37: Tenure with current company, by years of experience

Tenure With Current Company Less than 1 year 1 - 3 years 4 - 6 years 7 - 10 years More than 10 yearsProjected Base 5,777,915 6,405,850 7,635,364 8,042,904 28,752,843Up to 1 year 93% 56% 34% 23% 14%1-3 years 6% 41% 35% 31% 12%3-5 years 0% 3% 23% 14% 7%5-7 years 0% 0% 7% 16% 4%7-10 years 0% 0% 1% 15% 5%10-15 years 0% 0% 0% 1% 19%15-20 years 0% 0% 0% 0% 11%Above 20 years 0% 0% 0% 0% 29%Average Years 0.60 0.90 2.00 3.40 13.40

Base: 9,000

Table 38: Current and aspired industry verticals

Industry Verticals All white collar

Marketing / Comm.

Services

Consumer

Services




Projected Base 56,614,87 415,551 3,450,68 7,697,818 2,619,416 6,987,308 2,649,093 219,385 457,972

Marketing / Comm. Services 5% 21% 3% 2% 4% 3% 1% 0.6% 0.8%

Consumer Services 17% 34% 32% 9% 3% 16% 15% 5% 20%

Core Ind. / Ind. Goods & Services 23% 0.2% 17% 44% 12% 17% 24% 12% 7%

Banking & Finance 11% 0.8% 4% 12% 48% 10% 5% 0.3% 5%

IT 12% 33% 5% 6% 9% 34% 3% 0.2% 3%

Consumer Goods 10% 1% 13% 7% 6% 7% 29% 0.5% 4%

Healthcare 7% 8% 4% 3% 5% 5% 15% 77% 4%

Consultancy 15% 1% 22% 17% 13% 9% 7% 4% 57%

Base: 9,000


41

Table 39: Current and aspired sectors

Current And Aspired Sectors All white collar Government Public Private

Projected Base 56,614,875 549,974 1,515,787 22,431,468

Public Sector 5% 0.9% 33% 3%

Private Sector 79% 52% 44% 85%

Others 16% 47% 23% 12%

Base: 9,000

Table 40: Current and aspired functions

Current And Aspired Functions All white collar

Accounts & Finance

Office Admin & General

Mgt Marketing IT HR

Project Mgt &

Operations


Projected Base 56,614,875 3,667,887 10,726,084 9,418,725 4,251,350 1,785,888 8,678,870 2,697,098

Accounts & Finance 11% 75% 10% 2% 1% 3% 0.5% 2%

Office Admin & General Mgt 22% 8% 51% 13% 18% 27% 6% 5%

Marketing 22% 5% 12% 70% 7% 16% 14% 2%

IT 7% 5% 2% 2% 56% 0.5% 4% 0.9%

HR 3% 0.1% 2% 0.4% 1% 42% 0.6% 2%

Project Mgt & Operations 17% 0.2% 10% 8% 5% 6% 66% 15%

Designing / Creative Services 5% 0.1% 0.3% 0.7% 6% 0.3% 4% 63%

Others 8% 5% 8% 4% 5% 4% 5% 10%

Not specify 6% 0.3% 4% 1% 0.2% 2% 1% 0.3%

Base: 9,000

Table 41: Current hierarchy level and aspired hierarchy level

Current And Aspired Hierarchy Level

All white collar Trainee/Fresher

Executive/Operation

level Junior

Mgt Middle Mgt Senior Mgt Top Mgt Advisory

Staff / Consultant

Projected Base 56,614,875 2,747,503 8,583,061 5,837,582 11,289,887 9,973,742 1,274,115 2,325,545

Trainee /Fresher 7% 28% 14% 11% 2% 2% 2% 3%


Junior Mgt 17% 10% 8% 32% 28% 10% 8% 10%

Middle Mgt 24% 17% 8% 4% 45% 42% 27% 21%

Senior Mgt 12% 2% 2% 1% 3% 32% 47% 24%

Advisory Staff / Consultant 5% 4% 10% 1% 1% 4% 0.8% 18%

Others 5% 7% 12% 6% 0.6% 2% 0.8% 8%

Not specify 6% 2% 0.9% 2% 4% 2% 5% 2%

Base: 9,000

Current HR Trends

42

Table 42: Current hierarchy level and aspired hierarchy level

Compared To Previous As Well All white collar

Trainee/Fresher

Executive/Operation

level Junior Mgt Middle

Mgt Senior

Mgt Top Mgt Advisory

Staff / Consultant

Projected Base 56,614,875 8,428,57 10,969,81 7,812,071 7,406,105 5,011,085 720,932 2,083,148

Trainee /Fresher 7% 22% 8% 3% 0.5% 0.9% 0.0% 2%


Junior Mgt 17% 16% 12% 41% 8% 6% 4% 43%

Middle Mgt 24% 14% 16% 34% 59% 16% 28% 15%

Senior Mgt 12% 3% 4% 8% 20% 51% 41% 12%

Advisory Staff / Consultant 5% 8% 4% 2% 2% 8% 4% 21%

Others 5% 6% 2% 0.4% 0.1% 1% 2% 3%

Not specify 6% 1% 1% 3% 6% 2% 1% 1%

Base: 9,000


43

11%

89%

0%

30%

60%

90%

All white collar

Male Female

Demographic Profile Chart 8: Distribution of employees by gender

Base: 9,000

Current HR Trends

44

Table 43: Distribution of employees by gender, by industry verticals

Gender Marketing /

Comm. Services

Consumer Services




Projected Base 2,482,231 8,297,777 11,498,625 5,446,781 5,922,796 5,076,814 3,502,774 7,610,865

Male 91% 87% 95% 89% 81% 87% 89% 93%

Female 10% 14% 6% 11% 19% 13% 11% 7%

Base: 9,000

Table 44: Distribution of employees by gender, by job function

Gender Accounts & Finance



Creative Services

Projected Base 6,146,271 12,504,097 12,221,536 4,172,091 1,397,504 9,691,283 2,651,668

Male 87% 85% 92% 90% 83% 96% 92%

Female 14% 15% 8% 10% 17% 4% 8%

Base: 9,000

Table 45: Distribution of employees by gender, by hierarchy level

Gender Trainee/Fresher Executive/Operation level Junior Mgt Middle Mgt Senior Mgt Advisory Staff / Consultant

Projected Base 4,129,904 13,433,566 9,669,740 13,469,914 7,006,215 2,660,007

Male 78% 89% 89% 91% 94% 90%

Female 22% 11% 11% 9% 6% 10%

Base: 9,000

Table 46: Distribution of employees by gender, by educational qualification

Gender HSC/SSC Graduate General Stream



Post-Graduate Professional Stream Others

Projected Base 17,843,583 19,640,344 4,422,478 5,276,626 5,559,933 3,871,911

Male 89% 85% 91% 71% 85% 92%

Female 11% 15% 9% 29% 15% 8%

Base: 9,000

Table 47: Distribution of employees by gender, by years of experience

Gender Less than 1 year 1 - 3 years 4 - 6 years 7 - 10 years More than 10 years

Projected Base 5,777,915 6,405,850 7,635,364 8,042,904 28,752,843

Male 87% 79% 86% 87% 93%

Female 13% 21% 14% 13% 7%

Base: 9,000


45

14%

26%22%

3%

35%

0%

10%

20%

30%

40%

All white collar

Below 21 years 21-25 years 25-35 years35-45 years Above 45 years

Chart 9: Distribution of employees by age

Base: 9,000

Current HR Trends

46

Table 48: Distribution of employees by age, by industry verticals

Age Marketing

/ Comm. Services

Consumer Services


Banking &

Finance IT Consumer


Projected Base 2,482,231 8,297,777 11,498,625 5,446,781 5,922,796 5,076,814 3,502,774 7,610,865

Below 21 years 1% 4% 4% 7% 7% 3% 1% 0%

21-25 years 11% 9% 10% 15% 32% 17% 16% 7%

25-35 years 37% 37% 27% 26% 49% 45% 50% 33%

35-45 years 18% 31% 30% 23% 8% 24% 25% 27%

Above 45 years 34% 19% 29% 30% 5% 12% 10% 32%

Average age of employees

39.30 36.70 38.40 36.70 28.40 33.50 32.80 39.70

Base: 9,000

Table 49: Distribution of employees by age, by job function

Age Accounts & Finance



Creative Services

Projected Base 6,146,271 12,504,097 12,221,536 4,172,091 1,397,504 9,691,283 2,651,668

Below 21 years 7% 3% 5% 5% 1% 2% 2%

21-25 years 11% 10% 18% 22% 8% 13% 15%

25-35 years 36% 23% 38% 49% 30% 33% 59%

35-45 years 21% 28% 25% 14% 30% 29% 16%

Above 45 years 25% 37% 14% 10% 31% 23% 9%

Average age of employees

36.20 40.20 34.20 31.20 39.00 36.50 32.90

Base: 9,000

Table 50: Distribution of employees by age, by hierarchy level

Age Trainee/ Fresher Executive/ Operation level Junior Mgt Middle Mgt Senior Mgt Advisory Staff /

Consultant

Projected Base 4,129,904 13,433,566 9,669,740 13,469,914 7,006,215 2,660,007

Below 21 years 16% 3% 2% 3% 2% 5%

21-25 years 47% 16% 11% 7% 10% 9%

25-35 years 27% 41% 34% 43% 28% 14%

35-45 years 7% 19% 27% 26% 28% 51%

Above 45 years 3% 21% 26% 21% 33% 21%

Average age of employees 26.20 35.30 37.80 36.20 40.20 38.30

Base: 9,000


47

Table 51: Distribution of employees by age, by educational qualification

Age HSC/SSC Graduate

General Stream


Stream



Stream Others

Projected Base 17,843,58 19,640,344 4,422,478 5,276,626 5,559,933 3,871,911

Below 21 years 38% 11% 37% 1% 2% 21%

21-25 years 9% 19% 26% 12% 22% 15%

25-35 years 17% 31% 17% 34% 37% 39%

35-45 years 19% 19% 10% 26% 21% 14%

Above 45 years 17% 21% 10% 28% 17% 12%

Average age of employees 30.80 34.40 28.10 37.80 34.40 30.30

Base: 9,000

Table 52: Distribution of employees by age, by years of experience

Age Less than 1 year 1 - 3 years 4 - 6 years 7 - 10 years More than 10 years

Projected Base 5,777,915 6,405,850 7,635,364 8,042,904 28,752,843

Below 21 years 37% 27% 8% 1% 0%

21-25 years 27% 45% 30% 2% 1%

25-35 years 18% 28% 60% 86% 15%

35-45 years 13% 1% 3% 10% 42%

Above 45 years 4% 0% 0% 0% 43%

Average age of employees 25.60 23.90 26.60 30.60 44.10

Base: 9,000

Current HR Trends

48

26%22%

32%

21%

0%

10%

20%

30%

40%

All white collar

Metros Urban uptowns Emerging Towns Others

Chart 10: Distribution of employees by city type

Base: 9,000


49

Table 53: Distribution of employees by city type, by industry verticals

City Type Marketing /

Comm. Services

Consumer Services




Projected Base 2,482,231 8,297,777 11,498,625 5,446,781 5,922,796 5,076,814 3,502,774 7,610,865

Metros 29% 33% 22% 27% 53% 32% 30% 33%

Urban uptowns 13% 22% 29% 24% 29% 31% 21% 23%

Emerging Towns 13% 24% 22% 29% 12% 17% 28% 19%

Others 45% 22% 27% 20% 7% 19% 22% 26%

Base: 9,000

Table 54: Distribution of employees by city type, by job function

City Type Accounts & Finance



Creative Services

Projected Base 6,146,271 12,504,097 12,221,536 4,172,091 1,397,504 9,691,283 2,651,668

Metros 29% 37% 33% 35% 39% 28% 38%

Urban uptowns 24% 21% 28% 34% 21% 27% 27%

Emerging Towns 30% 16% 16% 20% 21% 20% 21%

Others 17% 27% 24% 10% 19% 26% 15%

Base: 9,000

Table 55: Distribution of employees by city type, by hierarchy level

City Type Trainee/Fresher Executive/Operation level Junior Mgt Middle Mgt Senior Mgt Advisory Staff /

Consultant

Projected Base 4,129,904 13,433,566 9,669,740 13,469,914 7,006,215 2,660,007

Metros 37% 36% 34% 29% 33% 27%

Urban uptowns 24% 19% 26% 34% 22% 18%

Emerging Towns 27% 20% 15% 20% 18% 33%

Others 13% 25% 25% 18% 28% 22%

Base: 9,000

Current HR Trends

50

Table 56: Distribution of employees by city type, by educational qualification

City Type HSC/SSC Graduate General Stream


Stream



StreamOthers

Projected Base 17,843,583 19,640,344 4,422,478 5,276,626 5,559,933 3,871,911

Metros 30% 31% 22% 20% 24% 37%

Urban uptowns 30% 23% 27% 29% 29% 21%

Emerging Towns 15% 24% 19% 22% 23% 20%

Others 26% 23% 32% 29% 24% 22%

Base: 9,000

Table 57: Distribution of employees by city type, by years of experience

City Type Less than 1 year 1 - 3 years 4 - 6 years 7 - 10 years More than 10 years

Projected Base 5,777,915 6,405,850 7,635,364 8,042,904 28,752,843

Metros 36% 30% 30% 30% 31%

Urban uptowns 30% 32% 26% 24% 25%

Emerging Towns 18% 23% 27% 22% 19%

Others 16% 15% 17% 25% 26%

Base: 9,000


51

15%

36%

21%

14%

0%

10%

20%

30%

40%

All white collar

North South East West

Chart 11: Distribution of employees by region

Base: 9,000

Current HR Trends

52

Table 58: Distribution of employees by region, by industry verticals

Region Marketing /

Comm. Services

Consumer Services




Projected Base 2,482,231 8,297,777 11,498,625 5,446,781 5,922,796 5,076,814 3,502,774 7,610,865

North 16% 17% 17% 23% 20% 22% 25% 36%

South 15% 31% 25% 31% 39% 25% 23% 29%

East 7% 14% 19% 13% 7% 18% 17% 12%

West 61% 37% 38% 33% 34% 34% 35% 23%

Base: 9,000

Table 59: Distribution of employees by region, by job function

Region Accounts & Finance



Creative Services

Projected Base 6,146,271 12,504,097 12,221,536 4,172,091 1,397,504 9,691,283 2,651,668

North 16% 23% 18% 25% 21% 20% 23%

South 30% 24% 33% 41% 36% 27% 32%

East 24% 12% 15% 9% 13% 17% 4%

West 30% 41% 34% 25% 30% 37% 41%

Base: 9,000

Table 60: Distribution of employees by region, by hierarchy level

Region Trainee/Fresher Executive/Operation level Junior Mgt Middle Mgt Senior Mgt Advisory Staff / Consultant

Projected Base 4,129,904 13,433,566 9,669,740 13,469,914 7,006,215 2,660,007

North 16% 19% 25% 23% 18% 21%

South 32% 31% 25% 29% 30% 24%

East 12% 18% 16% 13% 8% 11%

West 40% 32% 34% 35% 44% 44%

Base: 9,000


53

Table 61: Distribution of employees by region, by educational qualification

Region HSC/SSC Graduate General Stream


Stream



Stream Others

Projected Base 17,843,583 19,640,344 4,422,478 5,276,626 5,559,933 3,871,911

North 22% 23% 32% 24% 25% 12%

South 32% 28% 32% 39% 33% 33%

East 10% 18% 13% 17% 15% 10%

West 36% 33% 22% 20% 27% 45%

Base: 9,000

Table 62: Distribution of employees by region, by years of experience

Region Less than 1 year 1 - 3 years 4 - 6 years 7 - 10 years More than 10 years

Projected Base 5,777,915 6,405,850 7,635,364 8,042,904 28,752,843

North 16% 27% 20% 20% 21%

South 42% 25% 32% 28% 29%

East 8% 12% 15% 14% 15%

West 34% 37% 34% 38% 35%

Base: 9,000

Current HR Trends

54

11%

0% 1%

31%

58%

0%

20%

40%

60%

All white collar

Unmarried Married without childrenMarried with children Divorced/widow without childrenDivorced/widow with children

Chart 12: Distribution of employees by marital status

Base: 9,000


55

Table 63: Distribution of employees by marital status, by industry verticals

Marital Status Marketing /

Comm. Services

Consumer Services


Banking &

Finance IT Consumer


Projected Base 2,482,231 8,297,777 11,498,625 5,446,781 5,922,796 5,076,814 3,502,774 7,610,865

Unmarried 26% 22% 26% 33% 61% 29% 44% 21%

Married without children 6% 11% 11% 7% 12% 20% 9% 11%

Married with children 68% 67% 62% 59% 27% 50% 46% 68%

Divorced/widow without children

0.0% 0.1% 0.3% 0.1% 0.4% 0.2% 0.1% 0.1%

Divorced/widow with children 0.0% 0.5% 0.3% 0.8% 0.4% 0.0% 0.5% 0.6%

Base: 9,000

Table 64: Distribution of employees by marital status, by job function

Marital Status Accounts & Finance


Operations


Projected Base 6,146,271 12,504,097 12,221,536 4,172,091 1,397,504 9,691,283 2,651,668

Unmarried 29% 23% 38% 40% 21% 29% 35%

Married without children 10% 7% 14% 14% 9% 10% 12%

Married with children 61% 70% 48% 45% 63% 60% 54%

Divorced/widow without children 0.0% 0.2% 0.1% 0.1% 0.4% 0.1% 0.0%

Divorced/widow with children 0.4% 0.2% 0.3% 0.3% 7% 0.3% 0.0%

Base: 9,000

Table 65: Distribution of employees by marital status, by hierarchy level

Marital Status Trainee/Fresher Executive/ Operation level Junior Mgt Middle Mgt Senior Mgt Advisory Staff /

Consultant

Projected Base 4,129,904 13,433,566 9,669,740 13,469,914 7,006,215 2,660,007

Unmarried 78% 37% 24% 23% 22% 23%

Married without children 7% 11% 14% 11% 8% 8%

Married with children 14% 52% 62% 65% 70% 69%

Divorced/widow without children 0.1% 0.1% 0.2% 0.3% 0.3% 0.0%

Divorced/widow with children 0.2% 0.1% 0.1% 0.6% 0.8% 0.2%

Base: 9,000

Current HR Trends

56

Table 66: Distribution of employees by marital status, by educational qualification

Marital Status HSC/SSC Graduate

General Stream


Stream



Stream Others

Projected Base 17,843,583 19,640,344 4,422,478 5,276,626 5,559,933 3,871,911

Unmarried 54% 41% 69% 30% 45% 49%

Married without children 6% 11% 7% 9% 10% 13%

Married with children 38% 47% 23% 50% 44% 37%

Divorced/widow without children 0.3% 0.3% 0.1% 0.2% 0.4% 0.1%

Divorced/widow with children 1% 0.4% 1% 11% 0.6% 0.4%

Base: 9,000

Table 67: Distribution of employees by marital status, by years of experience

Marital Status Less than 1 year 1 - 3 years 4 - 6 years 7 - 10 years More than 10 years

Projected Base 5,777,915 6,405,850 7,635,364 8,042,904 28,752,843

Unmarried 77% 83% 65% 33% 6%

Married without children 4% 9% 15% 20% 8%

Married with children 19% 8% 19% 46% 85%

Divorced/widow without children 0.0% 0.1% 0.3% 0.1% 0.2%

Divorced/widow with children 0.1% 0.0% 0.1% 0.8% 0.6%

Base: 9,000

Table 68: Distribution of employees by educational qualification

Educational Qualification All white collar


HSC/SSC 32%

Graduate General Stream 35%

Graduate Professional Stream 8%

Post-Graduate General Stream 9%

Post-Graduate Professional Stream 10%

Others 7%

Base: 9,000


57

Table 69: Distribution of employees by educational qualification, by industry verticals

Base: 9,000

Table 70: Distribution of employees by educational qualification, by job function


All white collar

Accounts & Finance

Office Admin & General Mgt Marketing IT HR

Project Mgt &

Operations


Projected Base 56,614,875 6,146,271 12,504,097 12,221,536 4,172,091 1,397,504 9,691,283 2,651,668

HSC/SSC 32% 23% 33% 33% 12% 4% 39% 48%

Graduate General Stream 35% 50% 40% 40% 28% 34% 24% 19%



9% 15% 11% 5% 19% 25% 6% 2%


Others 7% 2% 5% 5% 8% 4% 9% 22%

Base: 9,000


All white collar

Marketing / Comm.

Services

Consumer Services


Services


Goods Healthcare

Projected Base 56,614,875 2,482,231 8,297,777 11,498,625 5,446,781 5,922,796 5,076,814 3,502,774

HSC/SSC 32% 53% 34% 36% 18% 23% 23% 21%



8% 3% 4% 11% 5% 15% 6% 5%



Others 7% 7% 7% 10% 2% 9% 9% 3%

Current HR Trends

58

Table 71: Distribution of employees by educational qualification, by hierarchy level


Trainee/ Fresher

Executive/ Operation

level Junior Mgt Middle Mgt Senior Mgt

Advisory Staff /

Consultant Projected Base 56,614,875 4,129,904 13,433,566 9,669,740 13,469,914 7,006,215 2,660,007

HSC/SSC 32% 36% 33% 30% 21% 33% 39%

Graduate General Stream 35% 35% 41% 38% 32% 28% 39%




Others 7% 4% 8% 6% 11% 3% 1%

Base: 9,000

Table 72: Distribution of employees by educational qualification, by educational qualification


Trainee/ Fresher


level Junior Mgt Middle Mgt Senior Mgt Advisory Staff

/ Consultant

Projected Base 56,614,875 17,843,583 19,640,344 4,422,478 5,276,626 5,559,933 3,871,911

HSC/SSC 32% 100% 0.0% 0.0% 0.0% 0.0% 0.0%

Graduate General Stream 35% 0.0% 100% 0.0% 0.0% 0.0% 0.0%

Graduate Professional Stream 8% 0.0% 0.0% 100% 0.0% 0.0% 4%

Post-Graduate General Stream 9% 0.0% 0.0% 0.0% 100% 0.0% 0.0%

Post-Graduate Professional Stream 10% 0.0% 0.0% 0.0% 0.0% 100% 2%

Others 7% 0.0% 0.0% 0.0% 0.0% 0.0% 94%

Base: 9,000

Table 73: Distribution of employees by educational qualification, by years of experience

Educational Qualification All white collar Less than 1 year 1 - 3 years 4 - 6 years 7 - 10 years More than 10 years

Projected Base 56,614,875 5,777,915 6,405,850 7,635,364 8,042,904 28,752,843

HSC/SSC 32% 47% 29% 23% 21% 39%

Graduate General Stream 35% 25% 31% 44% 35% 33%

Graduate Professional Stream 8% 11% 13% 7% 7% 6%

Post-Graduate General Stream 9% 5% 8% 6% 11% 9%

Post-Graduate Professional Stream 10% 8% 13% 12% 12% 8%

Others 7% 4% 7% 7% 13% 5%

Base: 9,000


59

Table 74: Distribution of employees by area of educational specialization

Area Of Educational Specialization All white collar


Engineering / Technical 27%

Mgt Studies 15%

Commerce 13%

Arts 6%

Gen. Science 6%

Other Specialized Courses 4%

No Spl 3%

Medical 2%

Economics 1%

Maths & Stats 1%

Others 3%

Not specify 19%

Base: 9,000

Table 75: Distribution of employees by area of educational specialization, by industry verticals

Area Of Educational Specialization

All white collar

Marketing / Comm.

Services

Consumer Services


Banking &

Finance IT Consumer


Projected Base 56,614,875 2,482,231 8,297,777 11,498,625 5,446,781 5,922,796 5,076,814 3,502,774 7,610,865

No Spl 3% 2% 9% 2% 3% 1% 0.9% 2% 3%

Commerce 13% 5% 10% 9% 38% 11% 14% 10% 11%

Mgt Studies 15% 13% 10% 16% 16% 11% 27% 19% 14%

Gen. Science 6% 6% 5% 6% 6% 6% 3% 11% 8%

Engineering / Technical 27% 15% 28% 40% 8% 45% 21% 14% 25%

Medical 2% 0.1% 0.7% 0.3% 0.7% 0.4% 1% 9% 1%

Arts 6% 5% 7% 5% 3% 6% 9% 7% 10%

Maths & Stats 1% 0.2% 0.7% 0.8% 3% 2% 0.5% 2% 0.9%

Economics 1% 0.7% 0.7% 0.3% 2% 0.9% 4% 2% 1%

Other Specialized Courses

4% 6% 9% 0.6% 0.6% 2% 0.6% 7% 5%

Others 3% 0.3% 3% 5% 5% 2% 1% 0.6% 7%

Not specify 19% 48% 18% 16% 16% 13% 18% 17% 15%

Base: 9,000

Current HR Trends

60

Table 76: Distribution of employees by area of educational specialization, by job function


All white collar

Accounts & Finance

Office Admin &

General Mgt Marketing IT HR

Project Mgt &

Operations


Projected Base 56,614,875 6,146,271 12,504,097 12,221,536 4,172,091 1,397,504 9,691,283 2,651,668

No Spl 3% 2% 7% 2% 1% 0.1% 0.5% 2%

Commerce 13% 53% 10% 15% 3% 8% 3% 0.7%

Mgt Studies 15% 7% 17% 22% 5% 39% 15% 7%

Gen. Science 6% 4% 4% 8% 5% 4% 10% 0.4%

Engineering / Technical 27% 8% 19% 22% 68% 6% 35% 47%

Medical 2% 0.5% 0.7% 1% 0.1% 3% 2% 0.0%

Arts 6% 2% 9% 5% 3% 22% 3% 12%

Maths & Stats 1% 0.1% 0.8% 1% 2% 9% 1% 0.0%

Economics 1% 0.2% 4% 0.6% 2% 0.4% 0.6% 0.0%

Other Specialized Courses 4% 0.7% 4% 3% 0.6% 1% 10% 3%

Others 3% 0.9% 5% 3% 2% 2% 3% 6%

Not specify 19% 22% 20% 17% 10% 4% 16% 22%

Base: 9,000

Table 77: Distribution of employees by area of educational specialization, by hierarchy level


All white collar

Trainee/ Fresher


levelJunior Mgt Middle Mgt Senior Mgt

Advisory Staff /

ConsultantProjected Base 56,614,87 4,129,904 13,433,566 9,669,740 13,469,914 7,006,215 2,660,007

No Spl 3% 2% 2% 10% 0.8% 0.8% 0.3%

Commerce 13% 9% 17% 17% 14% 10% 9%

Mgt Studies 15% 7% 14% 14% 19% 21% 16%

Gen. Science 6% 4% 7% 6% 6% 4% 6%

Engineering / Technical 27% 28% 28% 27% 31% 21% 13%

Medical 2% 0.4% 0.7% 3% 2% 2% 2%

Arts 6% 4% 6% 5% 7% 5% 8%

Maths & Stats 1% 1% 1% 2% 0.8% 1% 0.0%

Economics 1% 0.9% 2% 2% 1% 1% 0.3%

Other Specialized Courses 4% 4% 3% 1% 7% 3% 11%

Others 3% 6% 4% 0.8% 0.8% 2% 22%

Not specify 19% 33% 17% 13% 12% 30% 14%

Base: 9,000


61

Table 78: Distribution of employees by area of educational specialization, by educational qualification


All white collar HSC/SSC

Graduate General Stream




Professional Stream

Others

Projected Base 56,614,875 17,843,583 19,640,344 4,422,478 5,276,626 5,559,933 3,871,911

No Spl 3% 5% 3% 0.7% 0.3% 0.2% 1%

Commerce 13% 6% 20% 4% 16% 16% 1%

Mgt Studies 15% 4% 13% 11% 10% 39% 11%

Gen. Science 6% 4% 8% 2% 16% 6% 1%

Engineering / Technical 27% 25% 15% 68% 11% 19% 52%

Medical 2% 4% 1% 0.3% 0.5% 9% 6%

Arts 6% 4% 9% 0.6% 28% 4% 6%

Maths & Stats 1% 0.3% 3% 0.0% 2% 0.5% 0.0%

Economics 1% 0.0% 2% 0.0% 4% 0.4% 0.0%

Other Specialized Courses 4% 3% 4% 3% 3% 5% 3%

Others 3% 3% 2% 0.9% 1% 0.6% 2%

Not specify 19% 43% 22% 9% 8% 2% 17%

Base: 9,000

Table 79: Distribution of employees by area of educational specialization, by years of experience

Area Of Educational Specialization All white collar Less than 1 year 1 - 3 years 4 - 6 years 7 - 10 years More than 10 years

Projected Base 56,614,875 5,777,915 6,405,850 7,635,364 8,042,904 28,752,843

No Spl 3% 2% 0.9% 3% 2% 4%

Commerce 13% 9% 14% 13% 16% 13%

Mgt Studies 15% 10% 13% 13% 18% 16%

Gen. Science 6% 7% 6% 5% 6% 6%

Engineering / Technical 27% 23% 34% 25% 30% 24%

Medical 2% 0.6% 2% 2% 1% 2%

Arts 6% 3% 5% 10% 6% 6%

Maths & Stats 1% 0.7% 0.9% 0.9% 0.9% 1%

Economics 1% 1% 0.9% 2% 1% 0.9%

Other Specialized Courses 4% 2% 1% 1% 4% 5%

Others 3% 3% 0.4% 1% 0.5% 5%

Not specify 19% 41% 21% 25% 14% 18%

Base: 9,000

Current HR Trends

62

22%21%

43%

0%

10%

20%

30%

40%

50%

All white collar

SEC A SEC B SEC C

Socio-Economic Profile Chart 13: Distribution of employees by socio-economic classification

(SEC)

Base: 9,000


63

Table 80: Distribution of employees by SEC, by industry verticals

SEC Marketing / Comm. Services

Consumer Services




Projected Base 2,482,231 8,297,777 11,498,625 5,446,781 5,922,796 5,076,814 3,502,774 7,610,865

SEC A 17% 15% 24% 23% 20% 25% 28% 19%

SEC B 22% 31% 39% 44% 33% 36% 37% 42%

SEC C 61% 54% 38% 33% 47% 38% 35% 39%

Base: 9,000

Table 81: Distribution of employees by SEC, by job function

SEC Accounts & Finance

Office Admin & General Mgt Marketing IT HR Project Mgt & Operations Designing /

Creative Services

Projected Base 6,146,271 12,504,097 12,221,536 4,172,091 1,397,504 9,691,283 2,651,668

SEC A 20% 19% 23% 21% 44% 23% 8%

SEC B 42% 37% 35% 43% 46% 38% 17%

SEC C 39% 44% 42% 36% 10% 39% 75%

Base: 9,000

Table 82: Distribution of employees by SEC, by educational qualification

SEC HSC/SSC Graduate

General Stream


Stream



Stream Others

Projected Base 17,843,583 19,640,344 4,422,478 5,276,626 5,559,933 3,871,911

SEC A 5% 20% 29% 30% 47% 13%

SEC B 23% 46% 25% 35% 26% 36%

SEC C 72% 34% 46% 35% 26% 51%

Base: 9,000

Table 83: Distribution of employees by SEC, by years of experience

SEC Less than 1 year 1 - 3 years 4 - 6 years 7 - 10 years More than 10 years

Projected Base 5,777,915 6,405,850 7,635,364 8,042,904 28,752,843

SEC A 11% 13% 19% 23% 22%

SEC B 31% 29% 34% 33% 40%

SEC C 58% 58% 47% 44% 39%

Base: 9,000

64

Segment Wise Detailed Tables

65

Table 1: Current terms of employment

Gender All white collar Full-time Part time Apprenticeship / Internship

Sample Base 9,000 8,843 117 40

Male 89% 90% 76% 92%

Female 11% 10% 24% 8%


Age Group All white collar Full-time Part time Apprenticeship / Internship

Sample Base 9,000 8,843 117 40

Bellow 25 years 13% 12% 21% 60%

25-35 years 40% 40% 27% 32%

36-45 years 26% 25% 32% 4%

Above 45 years 22% 22% 21% 5%


Education All white collar Full-time Part time Apprenticeship / Internship

Sample Base 9,000 8,843 117 40

HSC/SSC 32% 31% 48% 30%

Graduate General Stream 35% 35% 33% 19%

Graduate Professional Stream 8% 8% 4% 34%

Post-Graduate General Stream 9% 9% 5% 4%

Post-Graduate Professional Stream 10% 10% 7% 12%

Others 7% 7% 4% 0.3%


Job Function All white collar Full-time Part time Apprenticeship / Internship

Sample Base 9,000 8,843 117 40

Accounts & Finance 13% 13% 6% 4%

Office Admin & General Mgt 26% 26% 27% 21%

Marketing 25% 25% 33% 30%

IT 9% 9% 6% 3%

HR 3% 3% 3% 0.0%

Project Mgt & Operations 20% 20% 21% 43%

Designing / Creative Services 5% 6% 5% 0.0%

66


Industry Category All white collar Full-time Part time Apprenticeship / Internship

Sample Base 9,000 8,843 117 40

Marketing / Comm. Services 5% 5% 4% 2%

Consumer Services 17% 16% 27% 22%

Core Ind. / Ind. Goods & Services 23% 23% 9% 45%

Banking & Finance 11% 11% 18% 5%

IT 12% 12% 26% 6%

Consumer Goods 10% 10% 2% 0.0%

Healthcare 7% 7% 6% 13%

Others 15% 16% 8% 7%


Hierarchy Level All white collar Full-time Part time Apprenticeship / Internship

Sample Base 9,000 8,843 117 40

Trainee/Fresher 8% 8% 17% 68%

Executive/Operation level 27% 27% 27% 17%

Junior Mgt 19% 20% 11% 0.0%

Middle Mgt 27% 27% 33% 1%

Senior Mgt 14% 14% 7% 14%

Advisory Staff / Consultant 5% 5% 6% 0.0%

67

Table 7: Age at first job

Gender All white collar Bellow 18 years 19-21 years 22-25 years 26-30 years 30 years or more

Sample Base 9,000 655 2,866 4,476 823 180

Male 89% 90% 85% 88% 92% 95%

Female 11% 10% 15% 12% 8% 5%


Age Group All white collar Bellow 18 years 19-21 years 22-25 years 26-30 years 30 years or more

Sample Base 9,000 655 2,866 4,476 823 180

Bellow 25 years 13% 54% 30% 12% 0.0% 0.0%

25-35 years 40% 17% 36% 47% 46% 8%

36-45 years 26% 11% 18% 22% 31% 63%

Above 45 years 22% 19% 17% 19% 23% 30%


Education All white collar Bellow 18 years 19-21 years 22-25 years 26-30 years 30 years or more

Sample Base 9,000 655 2,866 4,476 823 180

HSC/SSC 32% 64% 35% 19% 35% 59%





Others 7% 3% 8% 8% 2% 4%


Job Function All white collar Bellow 18 years 19-21 years 22-25 years 26-30 years 30 years or more

Sample Base 9,000 655 2,866 4,476 823 180

Accounts & Finance 13% 8% 12% 13% 16% 11%

Office Admin & General Mgt 26% 47% 28% 18% 24% 25%

Marketing 25% 21% 24% 28% 18% 40%

IT 9% 5% 7% 12% 6% 0.2%

HR 3% 3% 2% 3% 4% 2%

Project Mgt & Operations 20% 16% 19% 20% 29% 22%

Designing / Creative Services 5% 0.9% 8% 6% 5% 0.1%

68


Industry Category All white collar Bellow 18 years 19-21 years 22-25 years 26-30 years 30 years or more

Sample Base 9,000 655 2,866 4,476 823 180

Marketing / Comm. Services 5% 3% 7% 4% 6% 1%

Consumer Services 17% 29% 13% 14% 22% 33%

Core Ind. / Ind. Goods & Services 23% 24% 24% 21% 27% 17%

Banking & Finance 11% 9% 11% 13% 8% 6%

IT 12% 8% 13% 14% 7% 8%

Consumer Goods 10% 9% 11% 10% 10% 17%

Healthcare 7% 4% 6% 9% 8% 4%

Others 15% 14% 16% 15% 14% 15%


Hierarchy Level All white collar Bellow 18 years 19-21 years 22-25 years 26-30 years 30 years or more

Sample Base 9,000 655 2,866 4,476 823 180

Trainee/Fresher 8% 11% 9% 8% 4% 3%

Executive/Operation level 27% 22% 25% 29% 30% 18%

Junior Mgt 19% 27% 19% 17% 22% 7%

Middle Mgt 27% 27% 25% 29% 27% 25%

Senior Mgt 14% 9% 18% 12% 10% 36%

Advisory Staff / Consultant 5% 4% 5% 5% 8% 11%

69

Table 13: Total work experience

Gender All white collar Less than 1 year 1-3 years 4-6 years 7-10 years More than 10 years

Sample Base 9,000 972 1,354 1,719 1,686 3,269

Male 89% 87% 79% 86% 87% 93%

Female 11% 13% 21% 14% 13% 7%


Age Group All white collar Less than 1 year 1-3 years 4-6 years 7-10 years More than 10 years

Sample Base 9,000 972 1,354 1,719 1,686 3,269

Bellow 25 years 13% 60% 57% 30% 2% 0.5%

25-35 years 40% 23% 42% 68% 88% 15%

36-45 years 26% 13% 0.6% 3% 10% 42%

Above 45 years 22% 4% 0.0% 0.3% 0.3% 43%


Education All white collar Less than 1 year 1-3 years 4-6 years 7-10 years More than 10 years

HSC/SSC 32% 47% 29% 23% 21% 39%





Others 7% 4% 7% 7% 13% 5%


Job Function All white collar Less than 1 year 1-3 years 4-6 years 7-10 years More than 10 years

Sample Base 9,000 972 1,354 1,719 1,686 3,269



Marketing 25% 36% 24% 35% 25% 21%

IT 9% 11% 19% 12% 8% 5%

HR 3% 2% 2% 3% 3% 3%


Designing / Creative Services 5% 4% 5% 5% 11% 5%

70


Industry Category All white collar Less than 1 year 1-3 years 4-6 years 7-10 years More than 10 years

Sample Base 9,000 972 1,354 1,719 1,686 3,269




Banking & Finance 11% 6% 15% 11% 9% 11%

IT 12% 25% 32% 19% 14% 3%

Consumer Goods 10% 9% 10% 14% 14% 8%

Healthcare 7% 8% 6% 13% 9% 5%

Others 15% 8% 6% 12% 11% 21%


Hierarchy Level All white collar Less than 1 year 1-3 years 4-6 years 7-10 years More than 10 years

Trainee/Fresher 8% 68% 23% 0.0% 0.0% 0.0%


Junior Mgt 19% 3% 21% 21% 18% 21%

Middle Mgt 27% 2% 17% 29% 37% 30%

Senior Mgt 14% 10% 6% 10% 14% 18%

Advisory Staff / Consultant 5% 0.2% 4% 4% 3% 8%

71

Table 19: Number of jobs held

Gender All white collar 1st Job 2-3 Jobs 4-6 Jobs 7-10 Jobs

Sample Base 9,000 2,115 4,143 2,436 306

Male 89% 90% 86% 91% 91%

Female 11% 10% 14% 9% 9%


Age Group All white collar 1st Job 2-3 Jobs 4-6 Jobs 7-10 Jobs

Sample Base 9,000 2,115 4,143 2,436 306

Bellow 25 years 13% 36% 21% 6% 4%

25-35 years 40% 27% 41% 49% 18%

36-45 years 26% 19% 22% 24% 38%

Above 45 years 22% 19% 17% 21% 40%


Education All white collar 1st Job 2-3 Jobs 4-6 Jobs 7-10 Jobs

Sample Base 9,000 2,115 4,143 2,436 306

HSC/SSC 32% 39% 33% 32% 17%

Graduate General Stream 35% 30% 32% 39% 45%

Graduate Professional Stream 8% 10% 8% 6% 9%

Post-Graduate General Stream 9% 8% 9% 8% 10%

Post-Graduate Professional Stream 10% 8% 10% 12% 16%

Others 7% 4% 9% 4% 3%


Job Function All white collar 1st Job 2-3 Jobs 4-6 Jobs 7-10 Jobs

Sample Base 9,000 2,115 4,143 2,436 306

Accounts & Finance 13% 15% 14% 8% 8%

Office Admin & General Mgt 26% 30% 26% 21% 23%

Marketing 25% 22% 26% 27% 24%

IT 9% 11% 7% 8% 10%

HR 3% 2% 3% 4% 4%

Project Mgt & Operations 20% 16% 19% 25% 29%

Designing / Creative Services 5% 4% 6% 7% 3%

72


Industry Category All white collar 1st Job 2-3 Jobs 4-6 Jobs 7-10 Jobs

Sample Base 9,000 2,115 4,143 2,436 306

Marketing / Comm. Services 5% 8% 4% 5% 8%

Consumer Services 17% 10% 20% 16% 19%

Core Ind. / Ind. Goods & Services 23% 20% 25% 23% 27%

Banking & Finance 11% 12% 11% 10% 4%

IT 12% 12% 12% 12% 10%

Consumer Goods 10% 8% 10% 13% 20%

Healthcare 7% 7% 7% 9% 4%

Others 15% 24% 12% 13% 7%


Hierarchy Level All white collar 1st Job 2-3 Jobs 4-6 Jobs 7-10 Jobs

Sample Base 9,000 2,115 4,143 2,436 306

Trainee/Fresher 8% 16% 9% 0.0% 0.0%

Executive/Operation level 27% 22% 29% 28% 14%

Junior Mgt 19% 21% 20% 15% 18%

Middle Mgt 27% 19% 26% 36% 32%

Senior Mgt 14% 16% 10% 18% 32%


73

Table 25: Tenure with current company

Gender All white collar Less than 1 year 1-3 years 4-6 years 7-10 years More than 10 years

Sample Base 9,000 3,441 2,538 1,090 674 1,257

Male 89% 85% 88% 91% 89% 94%

Female 11% 15% 12% 9% 11% 6%


Age Group All white collar Less than 1 year 1-3 years 4-6 years 7-10 years More than 10 years

Sample Base 9,000 3,441 2,538 1,090 674 1,257

Bellow 25 years 13% 24% 23% 6% 0.4% 0.2%

25-35 years 40% 50% 54% 62% 57% 6%

36-45 years 26% 16% 17% 16% 33% 43%

Above 45 years 22% 10% 6% 17% 10% 51%


Education All white collar Less than 1 year 1-3 years 4-6 years 7-10 years More than 10 years

Sample Base 9,000 3,441 2,538 1,090 674 1,257

HSC/SSC 32% 31% 27% 29% 24% 39%





Others 7% 6% 8% 11% 6% 5%


Job Function All white collar Less than 1 year 1-3 years 4-6 years 7-10 years More than 10 years

Sample Base 9,000 3,441 2,538 1,090 674 1,257



Marketing 25% 30% 29% 29% 17% 18%

IT 9% 12% 10% 9% 6% 6%

HR 3% 3% 3% 2% 3% 3%



74


Industry Category All white collar

Less than 1 year

1-3 years

4-6 years

7-10 years

More than 10 years

Sample Base 9,000 3,441 2,538 1,090 674 1,257




Banking & Finance 11% 10% 12% 6% 8% 13%

IT 12% 23% 17% 13% 3% 0.9%

Consumer Goods 10% 11% 12% 12% 14% 7%

Healthcare 7% 7% 10% 11% 10% 3%

Others 15% 9% 8% 16% 15% 25%


Hierarchy Level All white collar Less than 1 year 1-3 years 4-6 years 7-10 years More than 10 years

Sample Base 9,000 3,441 2,538 1,090 674 1,257

Trainee/Fresher 8% 23% 8% 0.0% 0.0% 0.0%


Junior Mgt 19% 13% 15% 19% 24% 27%

Middle Mgt 27% 23% 28% 36% 30% 25%

Senior Mgt 14% 11% 16% 16% 19% 13%

Advisory Staff / Consultant 5% 4% 3% 5% 0.9% 9%

75

Table 31: Current salary levels and benefits packages

Gender All white collar

Up to Rs.1 lac

Rs.1-2 lacs

Rs.2-3 Lacs

Rs.3-5 lacs

Rs.5-7 lacs

Rs.7-10 lacs

Rs.10-20 lacs

Above 20 lacs

Not Specify

Sample Base 9,000 1,645 2,250 1,460 1,292 454 317 227 67 1,288

Male 89% 82% 90% 92% 94% 95% 95% 97% 96% 93%

Female 11% 18% 10% 8% 6% 5% 5% 3% 4% 7%


Age Group All white collar

Up to Rs.1 lac

Rs.1-2 lacs

Rs.2-3 Lacs

Rs.3-5 lacs

Rs.5-7 lacs

Rs.7-10 lacs

Rs.10-20 lacs

Above 20 lacs

Not Specify

Sample Base 9,000 1,645 2,250 1,460 1,292 454 317 227 67 1,288

Bellow 25 13% 24% 13% 7% 2% 2% 3% 2% 7% 10%

25-35 years 40% 48% 38% 33% 39% 36% 26% 21% 24% 41%

36-45 years 26% 18% 26% 27% 28% 38% 37% 20% 27% 31%

Above 45 22% 10% 23% 34% 31% 24% 34% 57% 43% 19%


Education All white collar

Up to Rs.1 lac

Rs.1-2 lacs

Rs.2-3 Lacs

Rs.3-5 lacs

Rs.5-7 lacs

Rs.7-10 lacs

Rs.10-20 lacs

Above 20 lacs

Not Specify

Sample Base 9,000 1,645 2,250 1,460 1,292 454 317 227 67 1,288

HSC/SSC 32% 32% 39% 31% 12% 17% 26% 13% 0.0% 38%


35% 40% 34% 35% 28% 25% 18% 42% 23% 35%

Graduate Professional Stream 8% 5% 5% 8% 17% 17% 13% 19% 19% 6%

Post-Graduate General Stream 9% 11% 9% 8% 13% 6% 7% 4% 11% 8%

Post-Graduate Professional Stream 10% 4% 7% 9% 25% 27% 33% 21% 40% 8%

Others 7% 8% 7% 9% 5% 8% 3% 2% 7% 5%

76


Job Function All white collar

Up to Rs.1 lac

Rs.1-2 lacs

Rs.2-3 Lacs

Rs.3-5 lacs

Rs.5-7 lacs

Rs.7-10 lacs

Rs.10-20 lacs

Above 20 lacs

Not Specify

Sample Base 9,000 1,645 2,250 1,460 1,292 454 317 227 67 1,288

Accounts & Finance 13% 16% 12% 11% 10% 6% 19% 32% 10% 9%

Office Admin & General Mgt

26% 29% 28% 27% 20% 12% 18% 10% 36% 24%

Marketing 25% 21% 29% 22% 23% 46% 19% 13% 12% 29%

IT 9% 8% 8% 7% 13% 8% 11% 19% 10% 8%

HR 3% 2% 3% 3% 4% 4% 4% 6% 4% 3%

Project Mgt & Operations 20% 18% 16% 25% 25% 23% 28% 19% 28% 21%

Designing / Creative Services 5% 6% 6% 6% 6% 1% 2% 0.7% 0.0% 6%



Up to Rs.1 lac

Rs.1-2 lacs

Rs.2-3 Lacs

Rs.3-5 lacs

Rs.5-7 lacs

Rs.7-10 lacs

Rs.10-20 lacs

Above 20 lacs

Not Specify

Sample Base 9,000 1,645 2,250 1,460 1,292 454 317 227 67 1,288


5% 4% 7% 5% 2% 3% 5% 1% 5% 7%

Consumer Services 17% 21% 16% 20% 9% 11% 4% 6% 10% 17%


23% 19% 20% 22% 30% 25% 36% 57% 20% 24%

Banking & Finance 11% 10% 11% 15% 16% 9% 7% 5% 14% 7%

IT 12% 12% 15% 10% 10% 9% 6% 6% 27% 9%

Consumer Goods 10% 13% 7% 9% 10% 12% 13% 3% 13% 12%

Healthcare 7% 7% 8% 4% 11% 21% 4% 8% 3% 4%

Others 15% 14% 15% 16% 12% 9% 26% 15% 9% 20%


Hierarchy Level All white collar

Up to Rs.1 lac

Rs.1-2 lacs

Rs.2-3 Lacs

Rs.3-5 lacs

Rs.5-7 lacs

Rs.7-10 lacs

Rs.10-20 lacs

Above 20 lacs

Not Specify

Sample Base 9,000 1,645 2,250 1,460 1,292 454 317 227 67 1,288

Trainee/Fresher 8% 20% 4% 5% 0.6% 0.6% 0.7% 0.4% 0.0% 8%

Executive/Operation level

27% 24% 34% 24% 13% 18% 5% 33% 13% 36%

Junior Mgt 19% 15% 21% 30% 17% 13% 9% 7% 2% 21%

Middle Mgt 27% 22% 22% 26% 52% 36% 41% 29% 36% 23%

Senior Mgt 14% 10% 16% 9% 16% 32% 30% 25% 49% 11%


5% 9% 4% 6% 1% 0.5% 15% 6% 0.2% 2%

77

Table 37: Distribution of employees by gender

Gender All white collar Male Female

Sample Base 9,000 7,581 1,419

Male 89% 100% 0.0%

Female 11% 0.0% 100%


Age Group All white collar Male Female

Sample Base 9,000 7,581 1,419

Bellow 25 years 13% 33% 43%

25-35 years 40% 30% 29%

36-45 years 26% 19% 15%

Above 45 years 22% 19% 13%


Education All white collar Male Female

Sample Base 9,000 7,581 1,419

HSC/SSC 32% 42% 34%

Graduate General Stream 35% 27% 31%

Graduate Professional Stream 8% 12% 8%

Post-Graduate General Stream 9% 6% 15%

Post-Graduate Professional Stream 10% 8% 9%

Others 7% 6% 3%


Job Function All white collar Male Female

Sample Base 9,000 7,581 1,419

Accounts & Finance 13% 12% 17%

Office Admin & General Mgt 26% 24% 39%

Marketing 25% 26% 21%

IT 9% 9% 8%

HR 3% 3% 5%

Project Mgt & Operations 20% 21% 7%

Designing / Creative Services 5% 6% 4%

78


Industry Category All white collar Male Female

Sample Base 9,000 7,581 1,419

Marketing / Comm. Services 5% 5% 5%

Consumer Services 17% 16% 21%

Core Ind. / Ind. Goods & Services 23% 24% 12%

Banking & Finance 11% 11% 11%

IT 12% 11% 21%

Consumer Goods 10% 10% 13%

Healthcare 7% 7% 7%

Others 15% 16% 10%


Hierarchy Level All white collar Male Female

Sample Base 9,000 7,581 1,419

Trainee/Fresher 8% 7% 17%

Executive/Operation level 27% 27% 27%

Junior Mgt 19% 19% 20%

Middle Mgt 27% 27% 22%

Senior Mgt 14% 15% 8%

Advisory Staff / Consultant 5% 5% 5%

79

Table 43: Distribution of employees by age

Gender All white collar Bellow 21 years 21-25 years 25-35 years 35-45 years Above 45 years

Sample Base 9,000 205 1,850 4,215 1,826 904

Male 89% 82% 86% 87% 89% 90%

Female 11% 18% 14% 14% 11% 10%


Age Group All white collar Bellow 21 years 21-25 years 25-35 years 35-45 years Above 45 years

Sample Base 9,000 205 1,850 4,215 1,826 904

Bellow 25 years 13% 100% 69% 0.0% 0.0% 0.0%

25-35 years 40% 0.0% 31% 100% 0.0% 0.0%

36-45 years 26% 0.0% 0.0% 0.0% 100% 0.0%

Above 45 years 22% 0.0% 0.0% 0.0% 0.0% 100%


Education All white collar Bellow 21 years 21-25 years 25-35 years 35-45 years Above 45 years

Sample Base 9,000 205 1,850 4,215 1,826 904

HSC/SSC 32% 65% 25% 28% 43% 40%



Post-Graduate General Stream 9% 0.2% 6% 10% 10% 11%

Post-Graduate Professional Stream 10% 0.8% 12% 12% 9% 8%

Others 7% 5% 5% 8% 4% 4%


Job Function All white collar Bellow 21 years 21-25 years 25-35 years 35-45 years Above 45 years

Sample Base 9,000 205 1,850 4,215 1,826 904



Marketing 25% 34% 32% 28% 25% 15%

IT 9% 11% 14% 12% 5% 4%

HR 3% 0.7% 2% 3% 4% 4%



80


Industry Category All white collar Bellow 21 years 21-25 years 25-35 years 35-45 years Above 45 years

Sample Base 9,000 205 1,850 4,215 1,826 904




Banking & Finance 11% 20% 12% 8% 10% 15%

IT 12% 21% 28% 16% 4% 2%

Consumer Goods 10% 9% 12% 13% 10% 5%

Healthcare 7% 1% 8% 10% 7% 3%

Others 15% 2% 8% 14% 17% 22%


Hierarchy Level All white collar Bellow 21 years 21-25 years 25-35 years 35-45 years Above 45 years

Sample Base 9,000 205 1,850 4,215 1,826 904



Junior Mgt 19% 10% 16% 18% 21% 23%

Middle Mgt 27% 19% 14% 32% 29% 25%

Senior Mgt 14% 6% 10% 11% 16% 21%

Advisory Staff / Consultant 5% 8% 4% 2% 11% 5%

81

Table 49: Distribution of employees by city

Gender All white collar Agra Ahmadabad Allahabad Amritsar Asansol Aurangabad

Sample Base 9,000 35 157 22 20 17 36

Male 89% 95% 80% 96% 93% 79% 86%

Female 11% 5% 20% 4% 7% 21% 14%


Gender Bangalore Bhopal Bhubaneswar Chandigargh Chennai Coimbatore Cuttack Dehradun Delhi Dhanbad Sample Base 1,022 45 109 100 616 104 28 32 982 8 Male 81% 78% 92% 93% 92% 66% 95% 94% 86% 97%

Female 19% 23% 8% 7% 8% 34% 5% 6% 14% 3%


Gender Faridabad Ghaziabad Goa Gurgaon Guwahati Hyderabad Indore Jabalpur

Sample Base 63 85 64 130 47 783 61 32

Male 86% 90% 93% 88% 87% 90% 82% 98%

Female 14% 10% 7% 12% 13% 10% 18% 2%


Gender Jaipur Jodhpur kanpur Kochi kolkata Lucknow Ludhiana

Sample Base 90 20 43 128 517 117 45

Male 95% 79% 94% 81% 93% 85% 77%

Female 6% 21% 7% 19% 7% 15% 23%


Gender Madurai Mangalore Meerut Mumbai Nagpur Nashik Noida

Sample Base 31 35 12 1,380 91 66 115

Male 88% 93% 99% 79% 91% 97% 83%

Female 12% 7% 1% 21% 9% 3% 17%


Gender Patna Pune Raipur Rajkot Ranchi Solapur Surat Thiruvananthapuram Tiruchirapalli

Sample Base 43 416 34 30 29 8 57 63 38

Male 96% 83% 88% 98% 92% 97% 95% 93% 86%

Female 4% 17% 12% 2% 8% 3% 5% 7% 14%


Gender Vadodara Varanasi Vijayavada Visakhapatanam Others from North India

Others from South India

Others from East India

Others from West India

Sample Base 91 11 48 98 197 263 148 138

Male 89% 95% 92% 90% 96% 74% 96% 85%

Female 11% 5% 9% 10% 4% 26% 4% 15%

82


Age Group All white collar Agra Ahmadabad Allahabad Amritsar Asansol Aurangabad

Sample Base 9,000 35 157 22 20 17 36

Bellow 25 years 13% 53% 36% 17% 48% 32% 28%

25-35 years 40% 20% 19% 12% 36% 39% 49%

36-45 years 26% 21% 26% 70% 9% 21% 18%

Above 45 years 22% 6% 19% 1% 6% 8% 5%


Age Group Bangalore Bhopal Bhubaneswar Chandigargh Chennai Coimbatore Cuttack Dehradun Delhi Dhanbad

Sample Base 1,022 45 109 100 616 104 28 32 982 8

Bellow 25 years 37% 32% 22% 23% 42% 47% 20% 37% 34% 44%

25-35 years 37% 48% 43% 42% 16% 27% 31% 23% 26% 29%

36-45 years 17% 6% 26% 6% 11% 12% 18% 32% 25% 20%

Above 45 years 9% 14% 9% 29% 32% 14% 31% 8% 15% 7%


Age Group Faridabad Ghaziabad Goa Gurgaon Guwahati Hyderabad Indore Jabalpur

Sample Base 63 85 64 130 47 783 61 32

Bellow 25 years 62% 49% 24% 27% 20% 37% 44% 22%

25-35 years 26% 15% 38% 26% 50% 32% 37% 46%

36-45 years 5% 7% 29% 41% 17% 16% 13% 29%

Above 45 years 8% 29% 9% 6% 14% 16% 6% 4%


Age Group Jaipur Jodhpur kanpur Kochi kolkata Lucknow Ludhiana

Sample Base 90 20 43 128 517 117 45

Bellow 25 years 56% 57% 24% 39% 25% 19% 35%

25-35 years 26% 35% 20% 31% 27% 19% 39%

36-45 years 12% 5% 33% 16% 20% 16% 22%

Above 45 years 6% 4% 23% 13% 28% 47% 4%

83


Age Group Madurai Mangalore Meerut Mumbai Nagpur Nashik Noida

Sample Base 31 35 12 1,380 91 66 115

Bellow 25 years 28% 32% 67% 26% 47% 55% 26%

25-35 years 39% 15% 21% 30% 36% 8% 40%

36-45 years 11% 8% 7% 20% 11% 9% 17%

Above 45 years 22% 44% 5% 24% 6% 29% 17%


Age Group Patna Pune Raipur Rajkot Ranchi Solapur Surat Thiruvananthapuram Tiruchirapalli

Sample Base 43 416 34 30 29 8 57 63 38

Bellow 25 years 59% 43% 29% 87% 48% 45% 36% 18% 36%

25-35 years 20% 32% 49% 7% 22% 27% 19% 31% 20%

36-45 years 9% 14% 9% 5% 13% 27% 30% 30% 28%

Above 45 years 12% 11% 14% 1% 17% 1% 16% 21% 16%


Age Group Vadodara Varanasi Vijayavada Visakhapatanam Others from North India




Sample Base 91 11 48 98 197 263 148 138

Bellow 25 years 27% 21% 53% 30% 40% 30% 21% 31%

25-35 years 30% 35% 28% 44% 30% 26% 26% 28%

36-45 years 18% 32% 10% 8% 16% 22% 25% 21%

Above 45 years 26% 12% 9% 18% 15% 22% 28% 21%

84


Education All white collar Agra Ahmadabad Allahabad Amritsar Asansol Aurangabad

Sample Base 9,000 35 157 22 20 17 36

HSC/SSC 32% 34% 37% 67% 41% 17% 28%


Graduate Professional Stream 8% 17% 12% 8% 4% 22% 10% Post-Graduate General Stream 9% 6% 4% 3% 9% 25% 14%


Others 7% 1% 4% 9% 0% 1% 5%


Education Bangalore Bhopal Bhubaneswar Chandigargh Chennai Coimbatore Cuttack Dehradun Delhi Dhanbad

Sample Base 1,022 45 109 100 616 104 28 32 982 8

HSC/SSC 42% 19% 21% 36% 47% 47% 8% 36% 45% 9% Graduate General Stream 21% 31% 28% 28% 19% 11% 60% 38% 33% 64%

Graduate Professional Stream 16% 19% 16% 10% 11% 18% 11% 9% 6% 9%

Post-Graduate General Stream 5% 7% 16% 13% 6% 8% 16% 8% 7% 5%

Post-Graduate Professional Stream 7% 12% 12% 8% 6% 8% 4% 8% 7% 7%

Others 10% 12% 7% 4% 11% 9% 1% 1% 2% 6%


Education Faridabad Ghaziabad Goa Gurgaon Guwahati Hyderabad Indore Jabalpur

Sample Base 63 85 64 130 47 783 61 32

HSC/SSC 30% 51% 55% 42% 37% 30% 22% 29%



Post-Graduate General Stream 3% 7% 8% 5% 16% 10% 9% 11% Post-Graduate Professional Stream 11% 6% 8% 13% 5% 11% 17% 7%

Others 1% 2% 2% 6% 1% 2% 8% 2%


Education Jaipur Jodhpur kanpur Kochi kolkata Lucknow Ludhiana

Sample Base 90 20 43 128 517 117 45

HSC/SSC 49% 32% 10% 54% 28% 17% 33%



Post-Graduate General Stream 9% 4% 14% 9% 5% 33% 7% Post-Graduate Professional Stream 8% 5% 29% 7% 10% 18% 10%

Others 1% 12% 0% 1% 8% 1% 0%

85


Education Madurai Mangalore Meerut Mumbai Nagpur Nashik Noida

Sample Base 31 35 12 1,380 91 66 115

HSC/SSC 15% 50% 20% 53% 27% 42% 33%





Others 7% 4% 1% 8% 5% 5% 2%


Education Patna Pune Raipur Rajkot Ranchi Solapur Surat Thiruvananthapuram Tiruchirapalli

Sample Base 43 416 34 30 29 8 57 63 38

HSC/SSC 34% 41% 22% 59% 34% 61% 35% 57% 22%

Graduate General Stream 34% 29% 21% 17% 39% 31% 13% 23% 34%

Graduate Professional Stream 24% 12% 10% 18% 14% 2% 7% 8% 19%

Post-Graduate General Stream 3% 4% 2% 1% 5% 3% 4% 7% 2% Post-Graduate Professional Stream 4% 8% 21% 4% 8% 2% 28% 4% 20%

Others 1% 7% 24% 2% 0% 1% 14% 2% 3%


Education Vadodara Varanasi Vijayavada Visakhapatanam Others from North India




Sample Base 91 11 48 98 197 263 148 138

HSC/SSC 54% 27% 44% 28% 36% 42% 44% 45%

Graduate General Stream 25% 47% 24% 41% 22% 23% 32% 26% Graduate Professional Stream 4% 4% 8% 11% 26% 9% 9% 8%



Others 3% 1% 12% 6% 2% 4% 1% 12%

86


Job Function All white collar Agra Ahmadabad Allahabad Amritsar Asansol Aurangabad

Sample Base 9,000 35 157 22 20 17 36

Accounts & Finance 13% 2% 6% 27% 9% 53% 18% Office Admin & General Management 26% 16% 45% 38% 31% 12% 31%

Marketing 25% 40% 16% 18% 36% 13% 27%

IT 9% 11% 3% 2% 0% 1% 8%

Human Resource 3% 0% 21% 4% 3% 0% 1%

Project Management & Operations 20% 32% 10% 11% 7% 6% 15%

Designing / Creative Services 5% 0% 1% 0% 14% 15% 0%


Job Function Bangalore Bhopal Bhubaneswar Chandigargh Chennai Coimbatore Cuttack Dehradun Delhi Dhanbad

Sample Base 1,022 45 109 100 616 104 28 32 982

8

Accounts & Finance 12% 10% 25% 9% 6% 5% 2% 23% 9% 17% Office Admin & General Management 19% 11% 8% 28% 15% 8% 42% 21% 44% 0%

Marketing 28% 32% 34% 17% 16% 24% 25% 9% 22% 69%

IT 19% 10% 3% 7% 14% 17% 24% 28% 10% 14%

Human Resource 2% 0% 1% 2% 6% 2% 0% 2% 3% 0% Project Management & Operations 18% 37% 28% 21% 16% 34% 6% 10% 8% 0%

Designing / Creative Services 4% 0% 1% 16% 28% 11% 0% 6% 4% 0%


Job Function Faridabad Ghaziabad Goa Gurgaon Guwahati Hyderabad Indore Jabalpur

Sample Base 63 85 64 130 47 783 61 32

Accounts & Finance 23% 7% 24% 14% 19% 17% 27% 17% Office Admin & General Management 32% 24% 7% 23% 21% 16% 9% 48%

Marketing 12% 28% 29% 30% 28% 39% 36% 6%

IT 4% 12% 6% 12% 1% 10% 9% 8%

Human Resource 0% 5% 2% 2% 10% 3% 1% 3% Project Management & Operations 12% 22% 27% 18% 19% 13% 15% 7%

Designing / Creative Services 18% 3% 8% 1% 2% 3% 3% 11%

87


Job Function Jaipur Jodhpur kanpur Kochi kolkata Lucknow Ludhiana

Sample Base 90 20 43 128 517 117 45

Accounts & Finance 20% 0% 5% 26% 16% 4% 53% Office Admin & General Management 36% 26% 6% 17% 20% 18% 3%

Marketing 19% 62% 21% 30% 35% 11% 36%

IT 4% 4% 19% 9% 6% 51% 6%

Human Resource 2% 0% 3% 6% 3% 4% 0% Project Management & Operations 11% 8% 46% 10% 19% 11% 3%



Job Function Madurai Mangalore Meerut Mumbai Nagpur Nashik Noida

Sample Base 31 35 12 1,380 91 66 115

Accounts & Finance 28% 78% 4% 12% 12% 52% 3%

Office Admin & General Management 9% 8% 25% 36% 17% 12% 16%

Marketing 13% 4% 49% 17% 30% 14% 21%

IT 28% 8% 0% 6% 5% 7% 11%

Human Resource 15% 2% 0% 3% 1% 1% 5%

Project Management & Operations 7% 1% 22% 19% 35% 12% 22%



Job Function Patna Pune Raipur Rajkot Ranchi Solapur Surat Thiruvananthapuram Tiruchirapalli

Sample Base 43 416 34 30 29 8 57 63 38

Accounts & Finance 31% 4% 1% 7% 28% 0% 6% 2% 4% Office Admin & General Management 13% 13% 27% 17% 22% 16% 46% 39% 16%

Marketing 21% 47% 20% 41% 10% 16% 18% 33% 8%

IT 24% 10% 1% 6% 2% 3% 0% 9% 4%

Human Resource 0% 2% 1% 3% 0% 0% 3% 1% 2% Project Management & Operations 12% 22% 15% 23% 38% 65% 25% 16% 53%

Designing / Creative Services 0% 2% 36% 4% 0% 0% 2% 1% 14%


Job Function Vadodara Varanasi Vijayavada Visakhapatanam Others from North India




Sample Base 91

11

48 98 197 263 148 138

Accounts & Finance 4% 1% 3% 10% 6% 8% 20% 7% Office Admin & General Management 23% 65% 30% 37% 29% 22% 28% 43%

Marketing 33% 3% 12% 14% 22% 43% 19% 19%

IT 13% 0% 31% 11% 7% 5% 3% 2%

Human Resource 1% 4% 8% 4% 4% 3% 3% 1% Project Management & Operations 26% 28% 16% 23% 33% 14% 26% 23%


88


Industry Category All white collar Agra Ahmadabad Allahabad Amritsar Asansol Aurangabad Sample Base 9,000 35 157 22 20 17 36 Marketing / Comm. Services 5% 1% 2% 0% 0% 1% 1% Consumer Services 17% 10% 10% 11% 22% 4% 18% Core Ind. / Ind. Goods & Services 23% 12% 12% 23% 15% 25% 14% Banking & Finance 11% 22% 39% 15% 3% 0% 13% IT 12% 6% 8% 5% 30% 1% 18% Consumer Goods 10% 15% 17% 8% 0% 58% 24% Healthcare 7% 6% 6% 20% 7% 0% 10% Others 15% 29% 7% 19% 23% 11% 3%


Industry Category Bangalore Bhopal Bhubaneswar Chandigargh Chennai Coimbatore Cuttack Dehradun Delhi Dhanbad Sample Base 1,022 45 109 100 616 104 28 32 982 8 Marketing / Comm. Services 2% 6% 3% 4% 3% 1% 0% 21% 8% 0%

Consumer Services 15% 12% 28% 19% 11% 10% 39% 10% 11% 31%

Core Ind. / Ind. Goods & Services 14% 18% 27% 24% 25% 31% 10% 14% 12% 0%

Banking & Finance 6% 14% 8% 9% 4% 5% 4% 11% 8% 17% IT 33% 18% 5% 15% 22% 13% 0% 27% 10% 14% Consumer Goods 10% 11% 11% 22% 6% 19% 34% 3% 10% 0% Healthcare 13% 7% 15% 2% 2% 4% 2% 5% 10% 31% Others 7% 14% 3% 6% 27% 16% 10% 9% 31% 7%



Industry Category Jaipur Jodhpur kanpur Kochi kolkata Lucknow Ludhiana Sample Base 90 20 43 128 517 117 45 Marketing / Comm. Services 7% 0% 7% 1% 2% 8% 0%

Consumer Services 11% 6% 28% 35% 13% 6% 5% Core Ind. / Ind. Goods & Services 12% 2% 17% 10% 18% 7% 17%

Banking & Finance 27% 68% 5% 14% 17% 54% 46% IT 7% 4% 1% 12% 18% 2% 13% Consumer Goods 7% 4% 7% 14% 10% 4% 9% Healthcare 19% 10% 12% 5% 10% 3% 5% Others 11% 6% 23% 10% 12% 16% 5%

Industry Category Faridabad Ghaziabad Goa Gurgaon Guwahati Hyderabad Indore Jabalpur Sample Base 63 85 64 130 47 783 61 32 Marketing / Comm. Services 2% 4% 1% 2% 4% 5% 2% 0%


Banking & Finance 24% 19% 6% 7% 5% 18% 5% 10% IT 7% 7% 2% 27% 1% 25% 22% 2% Consumer Goods 5% 8% 5% 20% 8% 4% 13% 14% Healthcare 16% 2% 21% 4% 8% 8% 25% 1% Others 26% 36% 2% 11% 54% 11% 5% 9%

89


Industry Category Madurai Mangalore Meerut Mumbai Nagpur Nashik Noida

Sample Base 31 35 12 1,380 91 66 115

Marketing / Comm. Services 0% 0% 0% 6% 7% 3% 3%

Consumer Services 17% 9% 28% 27% 15% 6% 14% Core Ind. / Ind. Goods & Services 8% 7% 10% 16% 42% 30% 35%

Banking & Finance 22% 67% 49% 7% 4% 4% 3%

IT 6% 4% 0% 14% 2% 2% 18%

Consumer Goods 13% 0% 14% 10% 7% 9% 6%

Healthcare 5% 1% 0% 4% 7% 3% 5%

Others 30% 11% 0% 16% 18% 44% 17%


Industry Category Patna Pune Raipur Rajkot Ranchi Solapur Surat Thiruvananthapuram Tiruchirapalli

Sample Base 43 416 34 30 29 8 57 63 38

Marketing / Comm. Services 1% 1% 4% 2% 0% 0% 0% 3% 2%

Consumer Services 26% 6% 7% 16% 22% 0% 1% 27% 55% Core Ind. / Ind. Goods & Services 4% 14% 71% 24% 33% 22% 83% 33% 16%

Banking & Finance 11% 6% 10% 30% 32% 3% 3% 5% 2%

IT 2% 46% 0% 2% 2% 0% 2% 13% 20%

Consumer Goods 14% 21% 4% 16% 4% 73% 9% 2% 2%

Healthcare 10% 2% 0% 5% 4% 3% 1% 2% 2%

Others 32% 5% 4% 5% 4% 0% 2% 16% 2%


Industry Category Vadodara Varanasi Vijayavada Visakhapatanam Others from North India




Sample Base 91 11 48 98 197 263 148 138 Marketing / Comm. Services 3% 0% 2% 16% 1% 1% 3% 33%


Banking & Finance 13% 4% 9% 11% 7% 12% 5% 13%

IT 17% 0% 21% 9% 2% 6% 3% 2%

Consumer Goods 4% 0% 19% 1% 8% 11% 11% 6%

Healthcare 7% 3% 7% 5% 12% 6% 6% 4%

Others 5% 63% 26% 34% 35% 17% 10% 8%

90


Hierarchy Level All white collar Agra Ahmadabad Allahabad Amritsar Asansol Aurangabad

Sample Base 9,000 35 157 22 20 17 36

Trainee/Fresher 8% 6% 28% 2% 0% 3% 1%

Executive/Operation level 27% 16% 15% 47% 31% 7% 44%

Junior Management 19% 24% 28% 4% 19% 70% 14%

Middle Management 27% 16% 16% 27% 26% 3% 22%

Senior Management 14% 39% 13% 21% 17% 14% 7% Advisory Staff / Consultant 5% 0% 1% 0% 7% 3% 13%


Hierarchy Level Bangalore Bhopal Bhubaneswar Chandigargh Chennai Coimbatore Cuttack Dehradun Delhi Dhanbad

Sample Base 1,022 45 109 100 616 104 28 32 982 8

Trainee/Fresher 12% 10% 11% 14% 6% 8% 5% 4% 3% 7%

Executive/Operation level 27% 25% 31% 11% 25% 11% 29% 14% 35% 71%

Junior Management 17% 6% 20% 19% 13% 16% 15% 6% 16% 0%

Middle Management 23% 44% 30% 38% 44% 46% 12% 62% 27% 16%

Senior Management 20% 15% 9% 7% 11% 19% 6% 13% 12% 0%

Advisory Staff / Consultant 1% 0% 0% 12% 2% 0% 34% 0% 7% 7%


Hierarchy Level Faridabad Ghaziabad Goa Gurgaon Guwahati Hyderabad Indore Jabalpur

Sample Base 63 85 64 130 47 783 61 32

Trainee/Fresher 22% 1% 20% 4% 14% 11% 2% 5%

Executive/Operation level 38% 13% 8% 20% 33% 35% 16% 22%

Junior Management 5% 29% 17% 38% 23% 10% 16% 15%

Middle Management 17% 49% 31% 28% 24% 27% 37% 18%

Senior Management 19% 5% 20% 8% 4% 14% 28% 39%



Hierarchy Level Jaipur Jodhpur kanpur Kochi kolkata Lucknow Ludhiana

Sample Base 90 20 43 128 517 117 45

Trainee/Fresher 1% 4% 3% 4% 7% 1% 1%

Executive/Operation level 33% 14% 7% 24% 33% 7% 41%



Senior Management 12% 0% 44% 13% 16% 7% 22%

Advisory Staff / Consultant 11% 54% 6% 0% 1% 2% 4%

91


Hierarchy Level Madurai Mangalore Meerut Mumbai Nagpur Nashik Noida

Sample Base 31 35 12 1,380 91 66 115

Trainee/Fresher 0% 2% 0% 9% 1% 4% 6% Executive/Operation level 33% 82% 37% 22% 30% 19% 9%



Senior Management 13% 3% 9% 14% 11% 7% 15% Advisory Staff / Consultant 0% 2% 0% 7% 2% 50% 3%


Hierarchy Level Patna Pune Raipur Rajkot Ranchi Solapur Surat Thiruvananthapuram Tiruchirapalli

Sample Base 43 416 34 30 29 8 57 63 38

Trainee/Fresher 2% 9% 0% 8% 8% 75% 16% 6% 1%

Executive/Operation level 21% 50% 23% 25% 31% 13% 10% 52% 7%

Junior Management 11% 15% 8% 0% 28% 8% 8% 11% 15%

Middle Management 64% 16% 53% 42% 18% 0% 63% 18% 13%

Senior Management 2% 8% 13% 17% 8% 0% 2% 13% 15%

Advisory Staff / Consultant 0% 2% 3% 8% 8% 4% 1% 0% 49%


Hierarchy Level Vadodara Varanasi Vijayavada Visakhapatanam Others from North India




Sample Base 91

11

48 98 197 263 148 138

Trainee/Fresher 12% 0% 3% 29% 4% 10% 4% 1%

Executive/Operation level 32% 0% 18% 27% 34% 26% 42% 23%

Junior Management 17% 79% 4% 20% 27% 26% 25% 10%

Middle Management 30% 8% 52% 14% 15% 18% 21% 29%

Senior Management 8% 13% 12% 4% 14% 16% 5% 29%


92

Table 91: Distribution of employees by city type

Gender All white collar Metros Urban uptowns Emerging Towns Others

Sample Base 9,000 5,873 1,561 820 746

Male 89% 84% 87% 90% 86%

Female 11% 16% 13% 10% 14%


Age Group All white collar Metros Urban uptowns Emerging Towns Others

Sample Base 9,000 5,873 1,561 820 746

Bellow 25 years 13% 33% 39% 34% 32%

25-35 years 40% 29% 28% 35% 28%

36-45 years 26% 19% 18% 17% 21%

Above 45 years 22% 20% 16% 14% 21%


Education All white collar Metros Urban uptowns Emerging Towns Others

Sample Base 9,000 5,873 1,561 820 746

HSC/SSC 32% 43% 46% 32% 41%





Others 7% 7% 4% 6% 5%


Job Function All white collar Metros Urban uptowns Emerging Towns Others

Sample Base 9,000 5,873 1,561 820 746



Marketing 25% 25% 27% 21% 27%

IT 9% 9% 11% 9% 4%

HR 3% 3% 2% 3% 3%



93


Industry Category All white collar Metros Urban uptowns Emerging Towns Others

Sample Base 9,000 5,873 1,561 820 746




Banking & Finance 11% 9% 11% 15% 10%

IT 12% 20% 14% 7% 4%

Consumer Goods 10% 10% 13% 8% 9%

Healthcare 7% 7% 6% 10% 7%

Others 15% 16% 14% 14% 17%


Hierarchy Level All white collar Metros Urban uptowns Emerging Towns Others

Sample Base 9,000 5,873 1,561 820 746

Trainee/Fresher 8% 9% 8% 11% 5%


Junior Mgt 19% 20% 20% 15% 21%

Middle Mgt 27% 24% 36% 26% 21%

Senior Mgt 14% 14% 12% 12% 18%


94

Table 97: Distribution of employees by region

Gender All white collar North South East West

Sample Base 9,000 2,009 3,265 946 2,780

Male 89% 91% 82% 93% 85%

Female 11% 9% 18% 7% 15%


Age Group All white collar North South East West

Sample Base 9,000 2,009 3,265 946 2,780

Bellow 25 years 13% 36% 36% 26% 35%

25-35 years 40% 29% 29% 31% 30%

36-45 years 26% 19% 17% 21% 19%

Above 45 years 22% 16% 19% 22% 17%


Education All white collar North South East West

Sample Base 9,000 2,009 3,265 946 2,780

HSC/SSC 32% 39% 42% 31% 46%





Others 7% 3% 6% 4% 7%


Job Function All white collar North South East West

Sample Base 9,000 2,009 3,265 946 2,780



Marketing 25% 22% 28% 26% 24%

IT 9% 11% 12% 5% 6%

HR 3% 3% 4% 3% 2%



95


Industry Category All white collar North South East West

Sample Base 9,000 2,009 3,265 946 2,780




Banking & Finance 11% 12% 12% 10% 10%

IT 12% 11% 16% 6% 12%

Consumer Goods 10% 10% 9% 13% 10%

Healthcare 7% 8% 6% 9% 7%

Others 15% 25% 16% 13% 10%


Hierarchy Level All white collar North South East West

Sample Base 9,000 2,009 3,265 946 2,780



Junior Mgt 19% 23% 17% 22% 18%

Middle Mgt 27% 30% 27% 24% 26%

Senior Mgt 14% 12% 14% 8% 17%


96

Table 103: Distribution of employees by marital status

Gender All white collar Unmarried Married without

children Married with

children Divorced/widow without

children Divorced/widow with

children

Sample Base 9,000 3,455 1,335 4,129 32 49

Male 89% 86% 87% 90% 36% 46%

Female 11% 14% 13% 10% 64% 54%



Unmarried Married without children

Married with children


Divorced/widow with children

Sample Base 9,000 3,455 1,335 4,129 32 49

Bellow 25 years 13% 67% 10% 0.5% 0.6% 0.0%

25-35 years 40% 28% 66% 24% 34% 12%

36-45 years 26% 3% 12% 38% 21% 39%

Above 45 years 22% 1% 12% 38% 44% 49%


Education All white collar





Sample Base 9,000 3,455 1,335 4,129 32 49

HSC/SSC 32% 45% 30% 39% 46% 35%


35% 23% 36% 32% 29% 7%


8% 16% 9% 7% 6% 8%



10% 7% 9% 9% 12% 3%

Others 7% 5% 8% 5% 2% 1%

97


Job Function All white collar Unmarried Married without


children Divorced/widow without

children Divorced/widow with

children

Sample Base 9,000 3,455 1,335 4,129 32 49



26% 19% 17% 31% 37% 9%

Marketing 25% 31% 33% 21% 25% 17%

IT 9% 11% 11% 7% 5% 5%

HR 3% 2% 2% 3% 9% 44%


Designing / Creative Services 5% 6% 6% 5% 0.0% 0.0%


Industry Category All white collar Unmarried Married without


children Divorced/widow without children


Sample Base 9,000 3,455 1,335 4,129 32 49


5% 4% 3% 6% 0.0% 0.0%



23% 19% 23% 25% 35% 19%

Banking & Finance 11% 12% 7% 11% 7% 20%

IT 12% 23% 13% 6% 27% 11%

Consumer Goods 10% 10% 19% 9% 11% 0.0%

Healthcare 7% 10% 6% 6% 3% 8%

Others 15% 10% 15% 18% 7% 23%







Sample Base 9,000 3,455 1,335 4,129 32 49



27% 32% 28% 24% 8% 9%

Junior Mgt 19% 15% 25% 21% 24% 4%

Middle Mgt 27% 20% 28% 30% 42% 47%

Senior Mgt 14% 10% 10% 17% 22% 32%


5% 4% 4% 6% 0.9% 3%

98

Table 109: Distribution of employees by socio-economic classification (SEC)

Gender All white collar SEC-A SEC-B SEC-C

Sample Base 9,000 5,196 1,642 302

Male 89% 86% 89% 86%

Female 11% 15% 11% 14%


Age Group All white collar SEC-A SEC-B SEC-C

Sample Base 9,000 5,196 1,642 302

Bellow 25 years 13% 22% 30% 40%

25-35 years 40% 32% 27% 30%

36-45 years 26% 23% 18% 18%

Above 45 years 22% 24% 25% 12%


Education All white collar SEC-A SEC-B SEC-C

Sample Base 9,000 5,196 1,642 302

HSC/SSC 32% 13% 32% 59%





Others 7% 4% 6% 5%


Job Function All white collar SEC-A SEC-B SEC-C

Sample Base 9,000 5,196 1,642 302


Office Admin & General Mgt 26% 23% 26% 27%

Marketing 25% 27% 24% 25%

IT 9% 8% 10% 7%

HR 3% 6% 3% 0.7%

Project Mgt & Operations 20% 22% 21% 18%

Designing / Creative Services 5% 2% 3% 10%

99


Industry Category All white collar SEC-A SEC-B SEC-C

Sample Base 9,000 5,196 1,642 302





IT 12% 11% 11% 13%

Consumer Goods 10% 12% 10% 9%


Others 15% 14% 18% 14%


Hierarchy Level All white collar SEC-A SEC-B SEC-C

Sample Base 9,000 5,196 1,642 302



Junior Mgt 19% 14% 23% 19%

Middle Mgt 27% 38% 25% 22%

Senior Mgt 14% 23% 8% 14%

Advisory Staff / Consultant 5% 2% 5% 8%

100

Table 115: Distribution of employees by monthly household income (MHI)


Up to Rs.10,000

Rs.10,000 to

Rs.20,000

Rs.20,000 to

Rs.30,000

Rs.30,000 to

Rs.50,000

Rs.50,000 to

Rs.75,000

Rs.75,000 to Rs.100,000

More than Rs.100,000

Not specify

Sample Base 9,000 1,794 2,397 1,649 1,327 602 351 666 214

Male 89% 85% 89% 88% 88% 89% 90% 81% 90%

Female 11% 15% 11% 12% 12% 11% 10% 20% 10%


Age Group

All white collar

Up to Rs.10,000

Rs.10,000 to Rs.20,000

Rs.20,000 to Rs.30,000

Rs.30,000 to Rs.50,000

Rs.50,000 to Rs.75,000

Rs.75,000 to Rs.100,000


Not specify

Sample Base 9,000 1,794 2,397 1,649 1,327 602 351 666 214

Bellow 25 years 13% 44% 28% 22% 20% 25% 28% 30% 45%

25-35 years 40% 30% 29% 31% 28% 32% 36% 25% 25%

36-45 years 26% 15% 24% 20% 23% 14% 22% 15% 23%

Above 45 years 22% 12% 19% 27% 29% 29% 15% 31% 7%


Education All

white collar

Up to Rs.10,000

Rs.10,000 to

Rs.20,000

Rs.20,000 to

Rs.30,000

Rs.30,000 to

Rs.50,000

Rs.50,000 to

Rs.75,000

Rs.75,000 to Rs.100,000


Not specify

Sample Base 9,000 1,794 2,397 1,649 1,327 602 351 666 214

HSC/SSC 32% 51% 37% 24% 23% 29% 32% 46% 50%


35% 25% 31% 36% 27% 27% 30% 21% 19%


8% 9% 12% 14% 15% 10% 17% 9% 12%


9% 6% 8% 7% 11% 8% 5% 7% 5%


10% 3% 7% 13% 20% 20% 13% 13% 6%

Others 7% 6% 5% 5% 5% 6% 3% 5% 8%

101


Job Function

All white collar

Up to Rs.10,000

Rs.10,000 to

Rs.20,000

Rs.20,000 to

Rs.30,000

Rs.30,000 to

Rs.50,000

Rs.50,000 to

Rs.75,000

Rs.75,000 to Rs.100,000


Not specify

Sample Base 9,000 1,794 2,397 1,649 1,327 602 351 666 214

Accounts & Finance

13% 15% 11% 14% 9% 12% 16% 12% 8%


26% 31% 27% 17% 21% 25% 15% 25% 19%

Marketing 25% 19% 24% 34% 27% 28% 31% 33% 22%

IT 9% 7% 10% 7% 15% 7% 7% 8% 7%

HR 3% 1% 4% 3% 3% 6% 2% 2% 5%

Project Mgt & Operations

20% 20% 19% 21% 23% 22% 28% 15% 16%


5% 8% 4% 4% 2% 0.8% 2% 6% 24%



Up to Rs.10,000

Rs.10,000 to

Rs.20,000

Rs.20,000 to

Rs.30,000

Rs.30,000 to

Rs.50,000

Rs.50,000 to

Rs.75,000

Rs.75,000 to

Rs.100,000

More than

Rs.00,000

Not specify

Sample Base 9,000 1,794 2,397 1,649 1,327 602 351 666 214


5% 8% 2% 4% 2% 6% 3% 3% 25%

Consumer Services 17% 17% 19% 11% 15% 11% 34% 12% 20%

Core Ind. / Ind. Goods & Services 23% 23% 19% 31% 26% 33% 21% 19% 15%

Banking & Finance 11% 7% 12% 16% 18% 10% 8% 15% 9%

IT 12% 15% 11% 11% 10% 10% 10% 10% 12%

Consumer Goods 10% 12% 10% 8% 8% 7% 9% 11% 8%

Healthcare 7% 7% 5% 6% 9% 10% 11% 13% 4%

Others 15% 12% 22% 14% 13% 12% 5% 17% 8%



Up to Rs.10,000

Rs.10,000 to

Rs.20,000

Rs.20,000 to

Rs.30,000

Rs.30,000 to

Rs.50,000

Rs.50,000 to

Rs.75,000

Rs.75,000 to

Rs.100,000


Not specify

Sample Base 9,000 1,794 2,397 1,649 1,327 602 351 666 214

Trainee/Fresher 8% 15% 4% 4% 3% 13% 4% 7% 20%


27% 26% 29% 30% 17% 15% 27% 28% 35%

Junior Mgt 19% 14% 30% 22% 12% 9% 11% 16% 13%

Middle Mgt 27% 23% 22% 29% 49% 30% 39% 30% 15%

Senior Mgt 14% 16% 10% 11% 19% 28% 18% 14% 14%

Advisory Staff / Consultant 5% 7% 6% 5% 2% 4% 1% 5% 3%

102

Table 121: Distribution of employees by most expensive vehicle owned

Gender All white collar Scooter Motorcycle Small Car Mid Size Car Premium Car Luxury Car Do not own any vehicle

Sample Base 9,000 965 3,103 1,883 864 105 33 2,047

Male 89% 87% 93% 82% 73% 85% 95% 85%

Female 11% 13% 8% 18% 27% 15% 6% 16%



Scooter Motorcycle Small Car

Mid Size Car

Premium Car

Luxury Car

Do not own any vehicle

Sample Base 9,000 965 3,103 1,883 864 105 33 2,047

Bellow 25 13% 32% 34% 30% 33% 45% 37% 38%

25-35 years 40% 23% 37% 25% 23% 25% 12% 28%

36-45 years 26% 22% 19% 20% 19% 8% 31% 15%

Above 45 years 22% 23% 10% 26% 25% 21% 21% 19%


Education All white collar Scooter Motorcycle Small

Car Mid Size

Car Premium

Car Luxury

Car Do not own any

vehicle

Sample Base 9,000 965 3,103 1,883 864 105 33 2,047

HSC/SSC 32% 49% 36% 30% 31% 45% 52% 51%



8% 10% 13% 13% 17% 10% 12% 7%



Others 7% 3% 7% 4% 4% 2% 2% 6%

103


Job Function All white collar Scooter Motorcycle Small

Car Mid Size

Car Premium

Car Luxury

Car Do not own any

vehicle

Sample Base 9,000 965 3,103 1,883 864 105 33 2,047

Accounts & Finance 13% 14% 10% 16% 7% 5% 2% 15%


26% 34% 24% 20% 18% 38% 8% 28%

Marketing 25% 22% 28% 29% 31% 22% 76% 18%

IT 9% 7% 9% 9% 14% 9% 0.0% 7%

HR 3% 3% 2% 4% 5% 3% 0.2% 3%

Project Mgt & Operations 20% 20% 20% 19% 23% 21% 3% 21%




Scooter Motorcycle Small Car

Mid Size Car

Premium Car

Luxury Car

Do not own any vehicle

Sample Base 9,000 965 3,103 1,883 864 105 33 2,047


5% 10% 3% 3% 6% 6% 1% 6%

Consumer Services 17% 14% 19% 8% 10% 22% 81% 21%


23% 29% 19% 34% 20% 25% 0.8% 19%

Banking & Finance 11% 10% 11% 15% 18% 16% 7% 6%

IT 12% 7% 15% 7% 13% 14% 4% 15%

Consumer Goods 10% 10% 10% 8% 9% 10% 0.5% 13%

Healthcare 7% 4% 9% 8% 5% 3% 0.6% 7%

Others 15% 17% 15% 16% 20% 4% 5% 13%


Hierarchy Level All white collar Scooter Motorcycle Small

Car Mid Size

Car Premium

Car Luxury

Car Do not own any

vehicle

Sample Base 9,000 965 3,103 1,883 864 105 33 2,047

Trainee/Fresher 8% 7% 9% 3% 2% 11% 1% 13%


27% 31% 29% 24% 14% 15% 50% 24%

Junior Mgt 19% 17% 17% 22% 8% 6% 31% 24%

Middle Mgt 27% 19% 29% 35% 37% 34% 14% 22%

Senior Mgt 14% 23% 10% 15% 27% 34% 3% 11%

Advisory Staff / Consultant 5% 4% 7% 2% 11% 0.0% 0.0% 5%

104

Table 127: Distribution of employees by credit card ownership

Gender All white collar Single Card Multiple Cards No Credit Card

Sample Base 9,000 2,371 2,201 4,428

Male 89% 89% 92% 85%

Female 11% 11% 8% 15%


Age Group All white collar Single Card Multiple Cards No Credit Card

Sample Base 9,000 2,371 2,201 4,428

Bellow 25 years 13% 18% 5% 42%

25-35 years 40% 29% 30% 29%

36-45 years 26% 24% 33% 15%

Above 45 years 22% 28% 32% 14%


Education All white collar Single Card Multiple Cards No Credit Card

Sample Base 9,000 2,371 2,201 4,428

HSC/SSC 32% 32% 20% 46%





Others 7% 6% 5% 5%


Job Function All white collar Single Card Multiple Cards No Credit Card

Sample Base 9,000 2,371 2,201 4,428


Office Admin & General Management 26% 26% 16% 28%

Marketing 25% 26% 30% 24%

IT 9% 9% 8% 8%

Human Resource 3% 3% 3% 3%

Project Management & Operations 20% 19% 24% 19%

Designing / Creative Services 5% 6% 5% 5%

105


Industry Category All white collar Single Card Multiple Cards No Credit Card

Sample Base 9,000 2,371 2,201 4,428





IT 12% 12% 11% 12%

Consumer Goods 10% 8% 13% 10%


Others 15% 16% 10% 17%


Hierarchy Level All white collar Single Card Multiple Cards No Credit Card

Sample Base 9,000 2,371 2,201 4,428



Junior Management 19% 15% 20% 21%

Middle Management 27% 27% 37% 24%

Senior Management 14% 17% 17% 11%

Advisory Staff / Consultant 5% 3% 6% 6%

106

Table 133: Distribution of employees by mobile phone ownership


Personally own mobile phone

Company provided mobile phone

Both personal and company provided separately

No mobile phone

Sample Base 9,000 6,478 803 1,002 717

Male 89% 89% 89% 91% 80%

Female 11% 11% 11% 9% 21%






No mobile phone

Sample Base 9,000 6,478 803 1,002 717

Bellow 25 13% 30% 16% 12% 54%

25-35 years 40% 31% 36% 29% 23%

36-45 years 26% 20% 33% 24% 10%

Above 45 22% 19% 15% 35% 13%


Education All white collar Personally own mobile phone



No mobile phone

Sample Base 9,000 6,478 803 1,002 717

HSC/SSC 32% 38% 33% 26% 54%


35% 29% 35% 29% 22%




Others 7% 5% 4% 5% 6%

107


Job Function All white collar




No mobile phone

Sample Base 9,000 6,478 803 1,002 717


Office Admin & General Management

26% 24% 19% 20% 41%

Marketing 25% 26% 40% 27% 9%

IT 9% 8% 5% 12% 10%

Human Resource 3% 3% 2% 6% 3%

Project Management & Operations 20% 19% 21% 27% 18%







No mobile phone

Sample Base 9,000 6,478 803 1,002 717


5% 5% 5% 5% 3%



23% 21% 34% 30% 24%

Banking & Finance 11% 12% 9% 19% 3%

IT 12% 13% 10% 6% 13%

Consumer Goods 10% 9% 18% 12% 11%

Healthcare 7% 7% 6% 10% 4%

Others 15% 17% 11% 11% 7%






No mobile phone

Sample Base 9,000 6,478 803 1,002 717



27% 29% 21% 18% 20%

Junior Management 19% 19% 16% 10% 29%

Middle Management 27% 25% 32% 40% 27%

Senior Management 14% 13% 23% 25% 11%


108

Index: Charts

Chart 1: Tenure with current company ............................................... 15 Chart 2: Current terms of employment ............................................... 21 Chart 3: Age at first job ................................................................. 23 Chart 4: Total work experience ........................................................ 26 Chart 5: Number of jobs held........................................................... 29 Chart 6: Proportion who moved jobs with a promotion ............................ 32 Chart 7: Tenure with current company ............................................... 38 Chart 8: Distribution of employees by gender ....................................... 43 Chart 9: Distribution of employees by age ........................................... 45 Chart 10: Distribution of employees by city type ................................... 48 Chart 11: Distribution of employees by region....................................... 51 Chart 12: Distribution of employees by marital status ............................. 54 Chart 13: Distribution of employees by socio-economic classification (SEC) ... 62

109

Index: Tables

Table 1: Sample sizes achieved in the online survey .................................3 Table 2: Urban population representation of the survey sample data.............4 Table 3: Distribution of employees by gender, by industry verticals ..............8 Table 4: Distribution of employees by city type, by industry verticals .......... 11 Table 5: Current terms of employment by industry verticals ..................... 22 Table 6: Current terms of employment by job function ........................... 22 Table 7: Current terms of employment by hierarchy level ........................ 22 Table 8: Current terms of employment by educational qualification............ 22 Table 9: Current terms of employment by years of experience .................. 22 Table 10: Age at first job, by industry verticals ..................................... 24 Table 11: Age at first job, by job function ........................................... 24 Table 12: Age at first job, by hierarchy level........................................ 24 Table 13: Age at first job, by educational qualification ........................... 25 Table 14: Age at first job, by years of experience .................................. 25 Table 15: Total work experience by industry verticals ............................. 27 Table 16: Total work experience by job function ................................... 27 Table 17: Total work experience by hierarchy level................................ 27 Table 18: Total work experience by educational qualification ................... 28 Table 19: Number of jobs held, by industry verticals .............................. 30 Table 20: Number of jobs held, by job function..................................... 30 Table 21: Number of jobs held, by hierarchy level ................................. 31 Table 22: Number of jobs held, by educational qualification ..................... 31 Table 23: Number of jobs held, by years of experience............................ 31 Table 24: Proportion who moved jobs with a promotion, by industry verticals 33 Table 25: Proportion who moved jobs with a promotion, by job function ...... 33 Table 26: Proportion who moved jobs with a promotion, by educational qualification ............................................................................... 34 Table 27: Proportion who moved jobs with a promotion, by years of experience.............................................................................................. 34

Table 28: Total work experience, by industry verticals ............................ 35 Table 29: Total work experience, by job function .................................. 35 Table 30: Total work experience, by hierarchy level............................... 35 Table 31: Total work experience, by educational qualification .................. 36 Table 32: Average tenure per job...................................................... 37 Table 33: Tenure with current company, by industry verticals ................... 39 Table 34: Tenure with current company, by job function ......................... 39 Table 35: Tenure with current company, by hierarchy level ...................... 39 Table 36: Tenure with current company, by educational qualification.......... 40 Table 37: Tenure with current company, by years of experience ................ 40 Table 38: Current and aspired industry verticals.................................... 40 Table 39: Current and aspired sectors ................................................ 41 Table 40: Current and aspired functions.............................................. 41 Table 41: Current hierarchy level and aspired hierarchy level.................... 41 Table 42: Current hierarchy level and aspired hierarchy level.................... 42 Table 43: Distribution of employees by gender, by industry verticals ........... 44 Table 44: Distribution of employees by gender, by job function ................. 44 Table 45: Distribution of employees by gender, by hierarchy level .............. 44 Table 46: Distribution of employees by gender, by educational qualification.. 44 Table 47: Distribution of employees by gender, by years of experience ........ 44 Table 48: Distribution of employees by age, by industry verticals ............... 46 Table 49: Distribution of employees by age, by job function ..................... 46 Table 50: Distribution of employees by age, by hierarchy level .................. 46 Table 51: Distribution of employees by age, by educational qualification...... 47 Table 52: Distribution of employees by age, by years of experience ............ 47 Table 53: Distribution of employees by city type, by industry verticals......... 49 Table 54: Distribution of employees by city type, by job function............... 49 Table 55: Distribution of employees by city type, by hierarchy level ........... 49 Table 56: Distribution of employees by city type, by educational qualification 50 Table 57: Distribution of employees by city type, by years of experience...... 50

110

Table 58: Distribution of employees by region, by industry verticals............ 52 Table 59: Distribution of employees by region, by job function .................. 52 Table 60: Distribution of employees by region, by hierarchy level............... 52 Table 61: Distribution of employees by region, by educational qualification .. 53 Table 62: Distribution of employees by region, by years of experience......... 53 Table 63: Distribution of employees by marital status, by industry verticals .. 55 Table 64: Distribution of employees by marital status, by job function......... 55 Table 65: Distribution of employees by marital status, by hierarchy level ..... 55 Table 66: Distribution of employees by marital status, by educational qualification ............................................................................... 56 Table 67: Distribution of employees by marital status, by years of experience 56 Table 68: Distribution of employees by educational qualification ............... 56 Table 69: Distribution of employees by educational qualification, by industry verticals .................................................................................... 57 Table 70: Distribution of employees by educational qualification, by job function .................................................................................... 57 Table 71: Distribution of employees by educational qualification, by hierarchy level ........................................................................................ 58 Table 72: Distribution of employees by educational qualification, by educational qualification................................................................ 58 Table 73: Distribution of employees by educational qualification, by years of experience................................................................................. 58 Table 74: Distribution of employees by area of educational specialization..... 59 Table 75: Distribution of employees by area of educational specialization, by industry verticals ......................................................................... 59 Table 76: Distribution of employees by area of educational specialization, by job function ............................................................................... 60 Table 77: Distribution of employees by area of educational specialization, by hierarchy level ............................................................................ 60 Table 78: Distribution of employees by area of educational specialization, by educational qualification................................................................ 61 Table 79: Distribution of employees by area of educational specialization, by years of experience ...................................................................... 61 Table 80: Distribution of employees by SEC, by industry verticals ............... 63 Table 81: Distribution of employees by SEC, by job function ..................... 63 Table 82: Distribution of employees by SEC, by educational qualification...... 63 Table 83: Distribution of employees by SEC, by years of experience ............ 63

111

Index: Segment wise Detailed Tables

Table 1: Current terms of employment ............................................... 65 Table 2: Current terms of employment ............................................... 65 Table 3: Current terms of employment ............................................... 65 Table 4: Current terms of employment ............................................... 65 Table 5: Current terms of employment ............................................... 66 Table 6: Current terms of employment ............................................... 66 Table 7: Age at first job ................................................................. 67 Table 8: Age at first job ................................................................. 67 Table 9: Age at first job ................................................................. 67 Table 10: Age at first job................................................................ 67 Table 11: Age at first job................................................................ 68 Table 12: Age at first job................................................................ 68 Table 13: Total work experience....................................................... 69 Table 14: Total work experience....................................................... 69 Table 15: Total work experience....................................................... 69 Table 16: Total work experience....................................................... 69 Table 17: Total work experience....................................................... 70 Table 18: Total work experience....................................................... 70 Table 19: Number of jobs held ......................................................... 71 Table 20: Number of jobs held ......................................................... 71 Table 21: Number of jobs held ......................................................... 71 Table 22: Number of jobs held ......................................................... 71 Table 23: Number of jobs held ......................................................... 72 Table 24: Number of jobs held ......................................................... 72 Table 25: Tenure with current company.............................................. 73 Table 26: Tenure with current company.............................................. 73 Table 27: Tenure with current company.............................................. 73 Table 28: Tenure with current company.............................................. 73 Table 29: Tenure with current company.............................................. 74 Table 30: Tenure with current company.............................................. 74 Table 31: Current salary levels and benefits packages ............................. 75 Table 32: Current salary levels and benefits packages ............................. 75 Table 33: Current salary levels and benefits packages ............................. 75 Table 34: Current salary levels and benefits packages ............................. 76 Table 35: Current salary levels and benefits packages ............................. 76 Table 36: Current salary levels and benefits packages ............................. 76 Table 37: Distribution of employees by gender...................................... 77 Table 38: Distribution of employees by gender...................................... 77 Table 39: Distribution of employees by gender...................................... 77 Table 40: Distribution of employees by gender...................................... 77 Table 41: Distribution of employees by gender...................................... 78 Table 42: Distribution of employees by gender...................................... 78 Table 43: Distribution of employees by age.......................................... 79 Table 44: Distribution of employees by age.......................................... 79 Table 45: Distribution of employees by age.......................................... 79 Table 46: Distribution of employees by age.......................................... 79 Table 47: Distribution of employees by age.......................................... 80 Table 48: Distribution of employees by age.......................................... 80 Table 49: Distribution of employees by city.......................................... 81 Table 50: Distribution of employees by city.......................................... 81 Table 51: Distribution of employees by city.......................................... 81 Table 52: Distribution of employees by city.......................................... 81 Table 53: Distribution of employees by city.......................................... 81 Table 54: Distribution of employees by city.......................................... 81 Table 55: Distribution of employees by city.......................................... 81 Table 56: Distribution of employees by city.......................................... 82

112

Table 57: Distribution of employees by city.......................................... 82 Table 58: Distribution of employees by city.......................................... 82 Table 59: Distribution of employees by city.......................................... 82 Table 60: Distribution of employees by city.......................................... 83 Table 61: Distribution of employees by city.......................................... 83 Table 62: Distribution of employees by city.......................................... 83 Table 63: Distribution of employees by city.......................................... 84 Table 64: Distribution of employees by city.......................................... 84 Table 65: Distribution of employees by city.......................................... 84 Table 66: Distribution of employees by city.......................................... 84 Table 67: Distribution of employees by city.......................................... 85 Table 68: Distribution of employees by city.......................................... 85 Table 69: Distribution of employees by city.......................................... 85 Table 70: Distribution of employees by city.......................................... 86 Table 71: Distribution of employees by city.......................................... 86 Table 72: Distribution of employees by city.......................................... 86 Table 73: Distribution of employees by city.......................................... 87 Table 74: Distribution of employees by city.......................................... 87 Table 75: Distribution of employees by city.......................................... 87 Table 76: Distribution of employees by city.......................................... 87 Table 77: Distribution of employees by city.......................................... 88 Table 78: Distribution of employees by city.......................................... 88 Table 79: Distribution of employees by city.......................................... 88 Table 80: Distribution of employees by city.......................................... 88 Table 81: Distribution of employees by city.......................................... 89 Table 82: Distribution of employees by city.......................................... 89 Table 83: Distribution of employees by city.......................................... 89 Table 84: Distribution of employees by city.......................................... 90 Table 85: Distribution of employees by city.......................................... 90 Table 86: Distribution of employees by city.......................................... 90 Table 87: Distribution of employees by city.......................................... 90 Table 88: Distribution of employees by city.......................................... 91 Table 89: Distribution of employees by city.......................................... 91 Table 90: Distribution of employees by city.......................................... 91 Table 91: Distribution of employees by city type ................................... 92 Table 92: Distribution of employees by city type ................................... 92 Table 93: Distribution of employees by city type ................................... 92 Table 94: Distribution of employees by city type ................................... 92 Table 95: Distribution of employees by city type ................................... 93 Table 96: Distribution of employees by city type ................................... 93 Table 97: Distribution of employees by region ...................................... 94 Table 98: Distribution of employees by region ...................................... 94 Table 99: Distribution of employees by region ...................................... 94 Table 100: Distribution of employees by region ..................................... 94 Table 101: Distribution of employees by region ..................................... 95 Table 102: Distribution of employees by region ..................................... 95 Table 103: Distribution of employees by marital status............................ 96 Table 104: Distribution of employees by marital status............................ 96 Table 105: Distribution of employees by marital status............................ 96 Table 106: Distribution of employees by marital status............................ 97 Table 107: Distribution of employees by marital status............................ 97 Table 108: Distribution of employees by marital status............................ 97 Table 109: Distribution of employees by socio-economic classification (SEC).. 98 Table 110: Distribution of employees by socio-economic classification (SEC).. 98 Table 111: Distribution of employees by socio-economic classification (SEC).. 98 Table 112: Distribution of employees by socio-economic classification (SEC).. 98 Table 113: Distribution of employees by socio-economic classification (SEC).. 99 Table 114: Distribution of employees by socio-economic classification (SEC).. 99 Table 115: Distribution of employees by monthly household income (MHI).... 100 Table 116: Distribution of employees by monthly household income (MHI).... 100 Table 117: Distribution of employees by monthly household income (MHI).... 100 Table 118: Distribution of employees by monthly household income (MHI).... 101 Table 119: Distribution of employees by monthly household income (MHI).... 101

113

Table 120: Distribution of employees by monthly household income (MHI).... 101 Table 121: Distribution of employees by most expensive vehicle owned ...... 102 Table 122: Distribution of employees by most expensive vehicle owned ...... 102 Table 123: Distribution of employees by most expensive vehicle owned ...... 102 Table 124: Distribution of employees by most expensive vehicle owned ...... 103 Table 125: Distribution of employees by most expensive vehicle owned ...... 103 Table 126: Distribution of employees by most expensive vehicle owned ...... 103 Table 127: Distribution of employees by credit card ownership ................. 104 Table 128: Distribution of employees by credit card ownership ................. 104 Table 129: Distribution of employees by credit card ownership ................. 104 Table 130: Distribution of employees by credit card ownership ................. 104 Table 131: Distribution of employees by credit card ownership ................. 105 Table 132: Distribution of employees by credit card ownership ................. 105 Table 133: Distribution of employees by mobile phone ownership.............. 106 Table 134: Distribution of employees by mobile phone ownership.............. 106 Table 135: Distribution of employees by mobile phone ownership.............. 106 Table 136: Distribution of employees by mobile phone ownership.............. 107 Table 137: Distribution of employees by mobile phone ownership.............. 107 Table 138: Distribution of employees by mobile phone ownership.............. 107

114

115