A Comparative study between Multinational and … This is to certify that the thesis titled “A Comparative study between Multinational and Private IT Industries: To understand the

A Comparative study between Multinational and Private IT

Industries: To understand the effect of Talent Management and

Managerial Competencies on Employee Engagement

Thesis Submitted to the Padmashree Dr. D. Y. Patil University,

Department of Business Management

in partial fulfillment of the requirements

for the award of the Degree of

DOCTOR OF PHILOSOPHY

In BUSINESS MANAGEMENT

Submitted by

Ms. Seema Panicker

(Enrollment No. DYP- PHD - 086100009)

Research Guide Dr. G. Vijayaragavan

PADMASHREE DR. D.Y. PATIL UNIVERSITY, DEPARTMENT OF BUSINESS MANAGEMENT,

Sector 4, Plot No. 10, CBD Belapur, Navi Mumbai – 400 614

NOVEMBER 2011

A Comparative study between Multinational and

Private IT Industries: To understand the effect of

Talent Management and Managerial

Competencies on Employee Engagement

DECLARATION

I hereby declare that the thesis titled “A Comparative study between

Multinational and Private IT Industries: To understand the effect of Talent

Management and Managerial Competencies on Employee Engagement”

submitted for the Award of Doctor of Philosophy in Business Management at the

Padmashree Dr. D.Y. Patil University Department of Business Management is

my original work and the thesis has not formed the basis for the award of any

degree, associate ship, fellowship or any other similar titles.

Place: Navi Mumbai.

Date:

Signature of the Signature of the Signature of the

Head of the dept. Guide student

CERTIFICATE

This is to certify that the thesis titled “A Comparative study between

Multinational and Private IT Industries: To understand the effect of Talent

Management and Managerial Competencies on Employee Engagement ”

and submitted by Ms. Seema Panicker is a bonafide research work for the

award of the Doctor of Philosophy in Business Management at the Padmashree

Dr. D. Y. Patil University Department of Business Management in partial

fulfillment of the requirements for the award of the Degree of Doctor of

Philosophy in Business Management and that the thesis has not formed the

basis for the award previously of any degree, diploma, associate ship, fellowship

or any other similar title of any University or Institution.

Also certified that the thesis represents an independent work on the part of the

candidate.

Place:

Date:

Signature of the Signature of the Guide

Head of the Department

ACKNOWLEDGEMENT

I am greatly indebted to the Padmashree Dr. D.Y. Patil University, Department

of Business Management which has accepted me for the Doctoral Program and

provided me with an excellent opportunity to carry out the present research work.

I am grateful to my guide, mentor, philosopher Dr. G. Vijayaragavan for having

guided me throughout the research span of time. I would also like to thank sir for

being there at any point of time without considering his own precious personal

time.

I would also like to thank Dr. Gopal and for providing his constructive criticism

and support which made me bring my best.

Special thanks to Prof. Praveen Gupta for having supported me throughout the

study.

I sincerely thank my Parents, Husband and my son Amrit for providing me the

necessary motivation and support for completing this research.

Above all, I wish to place on record my sincere thanks to my Guru and my deity

Mata Amritanandamayi Amma who provided me with the strength and ability to

carry this research out of the best of my ability.

Lastly I also wish to thank all my near and dear ones who have been directly

and indirectly instrumental in the completion of my dissertation.

Place:

Date:

Signature of the student

My Thesis work

Dedicated To the Lotus Feet of AMMA

MATA AMRITANANADAMAYI

CONTENTS

CHAPTER

NO

TITLE

PAGE

NO.

List Of Tables

List Of Figures

List of Abbreviations

EXECUTIVE SUMMARY

1. Introduction 1 - 7

1.1 Newer Approaches in managing HR’s to face competition

1

1.2 Growing Realization with changing business context

1

1.3 Framework of employee engagement 3

1.4 Importance of Talent Management 4

1.5 Impact of managerial competencies on employee engagement

6

2. Literature Review 8 - 37

2.1. Shift of HRM practices of talent management 8

2.2. Specific HRD interventions 13

2.3. Key components of a highly effective talent management process

14

2.4 Talented people and their characteristics 15

2.5. Trends of talent management and its impact 17

2.6. Focus on talent engagement 18

2.7. Changing business context 19

2.8 Glance on IT sector 20

2.9. Employee engagement for maximizing performance

24

2.10. Sustainability of business through Managerial Competencies

27

2.11 Role of the managers to enhance employee engagement and performance

29

2.12 Research gap 35

3. Statement of the problem 38

3.1. Objectives 40

3.2. Hypotheses 41

4 Research Methodology 44 - 57

4.1. Understanding the issue 44

4.2. Pre study 44

4.3. The study concentrated on both primary and secondary data

45

4.4. Research design 46

4.4.1. Secondary data collection 46

4.4.2. Primary data collection

47

4.4.3. Population and sample 47

4.4.4. Sampling technique 47

4.4.5. Sample frame 48

4.4.6. Tools used 49

4.4.7. Instrument used 49

4.4.8. List of Variables 54

4.4.9. The survey process 56

4.4.10 Limitation of the study 56

5 Conceptual framework 59 - 63

5.1. Conceptual frame work on talent management 59

5.2 Integrated Talent Management 59

5.3. Managerial abilities to lead talent engagement

for sustainable growth 60

5.4. Conceptual framework of employee engagement

62

6 Changing business context 64 - 100

6.1 A perspective on global scenario 65

6.2 The importance of sustainability in the phase of new era

67

6.3 Reshaping the business landscape 68

6.4. Emergence of talent management 69

6.5. The tipping point of talent management 70

6.6. Business Leaders :The changing Business context

72

6.7 A current application of talent management for optimizing the performance

74

6.8. Critical areas and importance of talent management

76

6.9. The magic formula to increase the productivity and capability

79

6.10 Impact of talent management 81

6.11 Components of engagement‘ 82

6.12 Engagement and related terminology 90

6.13 Competency for effective performance 93

6.14 Importance in identifying the competency gaps 94

6.15 Measurement issues with the competency approach

95

7 Information Technology

101- 146

7.1 Technological capacity and growth 103

7.2. Government initiatives : a key catalyst for increased it adoption

105

7.3. Road ahead : a sunshine sectors of the Indian economy

106

7.4 Sustainable growth of IT sector in India 106

7.5. Indian IT sector’s performance: Clues from

Accenture Results 108

7.6 A study of the performance of the INDIAN IT sector

110

7.7. Background of the IT industry in terms of its evolution, structure, growth: significance to the Indian economy.

113

7.8 Trends in the Indian software industry 124

7.9. Market for the Indian software industry 127

7.10 The future of the Indian software industry 129

7.11 Policy initiatives for the growth of the it industry 130

7.12 Intellectual property and “brain drain” 131

8 Data collection procedure and data preparation

147

9 Pilot testing 148-163

10 Data Preparation 164 -169

10.1 Sample preparation and characteristics 164

10.2. Data preparation using statistical package for social sciences

164

11 Quick view on the process of analysis 170-173

12 Prerequisite for dimension reduction 174- 183

12.1 Steps involved in factor analysis: independent variable: independent variable Managerial Competencies

174

12.2. Steps involved in factor analysis: independent variable: talent management

179

13 Factor analysis 184-200

14 Data Analysis and findings 201-256

14.1.b Summary of the findings 256

15 Bold Innovators in Talent Management 263 -276

16 Conclusion 277 -281

17 Suggestions and Recommendation 282-289

Reference section 290

ANNEXURE I - Bibliography

ANNEXURE II - Questionnaire

ANNEXURE III - First letter to participants

ANNEXURE IV - Follow up note

ANNEXURE V - Histogram: regression standardized residual: Talent management and managerial competencies on Employee engagement in MNC IT companies

ANNEXURE VI - Normal p-p plot of regression standardized residual: Talent management and managerial competencies on Employee engagement in MNC IT companies

ANNEXURE VII - Meaning and definition of Multinational companies and Private companies

ANNEXURE VIII - Details of the companies

LIST OF TABLES

CHAPTER

NO

TITLE

PAGE NO.

1 Sample sizes 48

2 Alpha Coefficients for Physical, Emotional, and Cognitive Engagement

51

3 List of variables 55

4 Flow chart of research methodology 58

5 Cronbach's alpha internal consistency 159

6 Results for the engagement levels Indicator Instrument Dimensions : Cronbach’s Alpha Split Half Test , Spearman-Brown Coefficient

160

7 Reliability Test Results for the talent management Indicator Instrument Dimensions : Cronbach’s Alpha Split Half Test , Spearman-Brown Coefficient

161

8 Reliability Test Results for the managerial competencies Indicator Instrument Dimensions : Cronbach’s Alpha Split Half Test ,Spearman-Brown Coefficient

163

9 Sample Sizes and Response Rates 164

10 Correlation: Independent variable Managerial Competencies vs. Employee engagement

175

11 correlation matrix : Independent variable: managerial Competencies

178

12 Correlation: Independent variable: Talent Management vs. Employee engagement

180

13 Correlation: Independent variable: Talent Management

183

14

KMO and Barletts test kaiser-meyer olkin measure of sampling adequacy: managerial competencies

186

15 Communalities: Independent Variable: Managerial Competencies, Extraction Method: Principal Component Analysis

188

16 Eigen values and Proportion of Variances: Managerial competencies:Extraction Method:

190

Principal Component Analysis.

17 Extraction of managerial competencies variables 192

18. component matrix: managerial competencies 191

19

KMO and Barletts test : measure of sampling adequacy: talent management

194

20 Communalities: Independent Variable: Talent Management

195

21

Eigen values and Proportion of Variances: talent Management Extraction Method: Principal Component Analysis

198

22 component matrix: managerial competencies 200

23 Test of homogeneity of variances for employee engagement

203

24 Descriptive Statistics of Employee engagement

204

25 ANOVA test on employee engagement MNC and Private IT sector

204

26 Test of homogeneity of variances for talent management

208

27 Descriptive Statistics of talent management 209

28 ANOVA test: talent management, MNC Private IT sector

209

29 Test of homogeneity of variances :managerial competencies

212

30 Descriptive Statistics of managerial competencies

213

31 ANOVA test: managerial competencies, MNC Private IT sector

214

32 Descriptive statistics: talent management, managerial competencies and employee engagement for MNC

217

33 Pearson correlation :Talent management ,managerial competencies on employee engagement in MNC IT

218

34 Model summary: talent management, managerial Competencies on Employee engagement in the multinational IT industries

220

35 ANOVA TEST: talent management, managerial competencies on Employee engagement in the multinational IT industries

221

36 Pearson Correlation: talent management, managerial Competencies on employee engagement in the Private IT industries

224

37 Chi-square independent variable talent management and employee engagement

227

38 correlations: talent management on the engagement levels

228

39 chi-square on managerial competencies on engagement levels

232

40 correlations: managerial competencies on the engagement levels

233

41 linear regression of key factors: talent management, managerial competencies and employee engagement

239

42 Stepwise regression of the factors : A model summary

240

43 ANOVA TEST: talent management, Managerial competencies and employee engagement in MNC

241

44 linear regression of key factors: managerial competencies and employee engagement in MNC

250

45 stepwise regression of the factors: linear regression of key factors: managerial competencies and employee engagement in MNC

251

46 ANOVA TEST: managerial competencies and employee engagement

252

LIST OF FIGURES

TITLE

PAGE

NO.

1 Scree plot: managerial competencies 191

2 Scree Plot: Independent variable:Talent

management 200

3 Graph of mean of employee engagement 205

4 Graph of mean of talent management 209

5 Graph of mean of managerial competencies 210

6 Histogram on regression standardized residual: talent management, Managerial competencies and employee engagement in MNC

243

7 Normal P-P plot Normal P-P plot of regression standardized residual: talent management, Managerial competencies and employee engagement in MNC

244

8 Histogram on regression standardized

residual: Managerial competencies and

employee engagement in MNC

254

9 Normal P-P plot Normal P-P plot of regression standardized residual: Managerial competencies and employee engagement in MNC

255

10 TALENT ENGAGEMENT MODEL 262

LIST OF ABBREVIATIONS

JES Job Engagement survey

NeGP National e Governance Programmes

UIDA Unique Identification Development

Authority of India

SIGITE Special Interest Group for IT Education

ACM Association for Computing Machinery

FDI foreign direct investment

TAGUP Technical Advisory Group for Unique

Projects

NPS New Pension System

GST Goods and Services Tax

STPIs Software Technology Parks of India

ITIR Information Technology Investment

Region

NASSCOM National Association of Software and

Service Companies

IIIT Indian Institute of Information Technology

NCERT National Council for Education, Research

and Training

MNC Multinational corporation

Pvt Cos. Private companies

L&D Learning and development

DDI Development Dimension International

CIPD Chartered Institute of Personnel and

development

VIF Variance Inflation factor

EXECUTIVE SUMMARY

The competent and motivated people can make things happen and enable an

organization to achieve its goal. When employees are engaged with their

company’s sustainability strategy, they proactively identify, communicate and

pursue opportunities to execute the strategy. Engaged employees within an

organization provide a competitive advantage to organizations, and hence there

is a need to continuously engage employees. A strongly disengaged employee

will have no interest in their work and may even sabotage the potential success

of a project. A talent management system must be worked into the business

strategy and implemented in daily processes throughout the company as a

whole. Talent management is a key to engagement. Talent has become a

strategic issue as companies make decisions based on the availability of a labor

and skills. In order to win the war of talent, organizations have invested heavily

to implement human resources systems and processes, and talent issues have

become the agenda for any business forum. Although these moves are laudable

and necessary too many organizations still dismiss talent management are short

term, tactical problem rather than an integral part of a long term business

strategy, requiring the attention of top level management and substantial

resources. Since investments in talent management are intangibles are

expensed rather than capitalized, managers may prefer to raise short term

earnings by cutting expenditures on people development. This tendency may fail

to embed a talent strategy in the overall strategy of the business and turn in to

vicious circle. A lack of talent blocks the corporate growth, creating additional

performance besides these challenges, Paese (2006), argued that organizations

may face two major impediments without overarching strategic plan, resulting in

frequent and unpredictable objectives and disruptions. Secondly, senior leaders

don’t have a personal connection to talent management through personal

involvement and accountability.

RESEARCH GAP

A study about the impact of HR practices and organizational commitment on the

profitability of business units found a close relationship between HR practices,

operating expenses and firm performance. In addition, employees were found to

be more committed to the organization when managed with progressive HR

practices. There were following gaps in study which did not focus mainly on

comparative studies between MNC and Private IT companies. The differences’ of

engagement levels in the MNC and Private sector of IT industries shows a gap

with the talent management tools and managerial competencies. But replicating

a high-quality, highly engaged workforce is nearly impossible. The studies have

not touched how talent management tools with managerial competencies can

affect the engagement levels in different sectors of IT companies. The

companies may have talent management tools but the extensive use of

managerial competencies also may affect engagement levels. There are no

studies which can help to identify the predictive model on talent engagement for

better performance. The study can be based on the managerial competencies to

enhance the engagement levels by developing the managerial competencies

model.

PURPOSE OF THE STUDY

Some of the organizations are forefront in having the best talent in order to

succeed in the hypercompetitive and increasingly complex global economy. So

the purpose of the study was to identify the effect of talent management tools

with managerial competencies on the engagement levels in different sectors of IT

companies that is between Multinational and Private IT sectors.

OBJECTIVES

1. To find the differences of employee engagement levels, talent

management and managerial competencies between Private and

Multinational IT companies

2. To study the relation and effect of talent management and managerial

competencies on the levels of employees engagement in the Multinational

IT companies

3. To study the relation of talent management and managerial competencies

on the levels of employees engagement in the Private IT companies

4. To understand the association and relation of workforce planning, talent

acquisition, talent measurement, talent development, talent retention

scores and levels of employee engagement in the Private IT sector

5. To understand the association and relation of managerial competencies

scores i.e. thinking strategically, initiative and innovation, planning &

organizing, coaching, decision making and result orientation that best

predicts employee engagement in the Private IT sector

6. To develop a predictive talent engagement model

7. To develop a managerial competencies model to enhance

employee engagement.

RESEARCH DESIGN

The study was primarily designed to find out from a cross section of employees

from MNC and Private ltd companies of an IT sector of Mumbai, Hyderabad,

Pune, Cochin and Bangalore, to find the effect of talent management,

managerial Competencies and employee’s engagement between Multinational

and Private IT companies.

POPULATION AND SAMPLE

The population defined for this study consisted of IT professionals in Private and

MNC IT sector. Total Size of the Population were 5500 from the area of Mumbai,

Hyderabad, Pune, Cochin and Mangalore considering the Multinational and

Private IT Company’s .The population size for Multinational was 2500 and for

Private IT sector of 3000. The 20 organizations were included in the study and

were selected on the basis of convenience and accessibility as well as the size of

the organization, organizational growth and turnover. The ten companies from

MNC sector and 10 from Private sector were included in the study .The samples

selected for the study included all professionals of IT background. The sample

sizes for MNC were 650 and private sector of 700. The sample frames from

where samples were drawn from the population were senior level managers and

junior level managers mainly from MNC and Private IT companies. Senior level

managers holding the positions of leader, Program Managers, project managers,

production managers, HR Managers, Senior Business Development managers

were considered. From the junior level positions assistant programmers,

Business developers, Software Programmers’, Associate Consultants,

Developers, and executives were also included in the sample frame. The

samples were divided in to 2 strata’s of Multinational and Private IT industries

with respect to companies using stratified random sampling method.

FINDINGS

1. The results showed that there was a significant differences in

engagement levels between Multinational and Private IT sector .It was

observed that multinational employees were more physically, emotionally

and cognitively engaged than Private IT sector. There were also

differences in talent management and managerial competencies between

MNC and Private IT sector. The Mean scores of engagement level, talent

management and Managerial competencies in Multinational Company

were more than Private IT companies.

2. It was observed that there was a direct link between Talent Management

and Managerial competencies on the Employee engagement in the

Multinational IT Companies. Regression results indicated an overall

model of two predictors, talent management and managerial

competencies that significantly predicts employee engagement in

Multinational IT sector.

3. The result showed correlation between high scores of Talent

Management and high scores of Managerial competencies on Employee

disengagement but low scores of Talent Management and low scores of

Managerial competencies showed significant relation on Employee

disengagement in the Private IT sector.

4. The Talent Management and Managerial competencies on Employee

engagement levels in Private sector showed a significant relation and

there were also differences in talent management tools, managerial tools

and employee engagement between Private and MNC, the tools of talent

management were further tested. It was observed that the low scores of

talent management tools i.e. workforce planning, talent acquisition, talent

measurement, talent development, talent retention showed significant

association between disengaged employees and high scores of workforce

planning, talent acquisition, Talent development, talent deployment ,talent

retention showed significant association between engaged employees

5. It was observed that the Managerial competencies scores showed

significant association between engaged and disengaged employees

Thus low scores of managerial competencies that were initiative and

innovation, thinking strategically, result orientation, planning and

organizing, decision making and coaching showed a significant

association and direct link with disengaged employees. The high scores

of managerial competencies scores that were planning and organizing,

initiative and innovation, thinking strategically, result orientation, decision

making and coaching showed a significant association and significant

relation with the engaged employees.

6. Step wise regression statistical tool was applied to develop the talent

engagement model thus identified the talent management factors that

determine the employee engagement in Multinational IT Companies

7. Step wise regression statistical tool was applied to develop the managerial

competencies model and to identify the managerial competencies factors ,

thinking strategically, initiative and innovative approach, planning and

organizing, coaching strategically , decision making and result orientation

that determine the employee engagement in Multinational IT Companies.

SUGGESTIONS

1. The research has highlighted the need for private sector organisations to

improve the way in which they develop an active talent management tools

and develop leadership capability for the employees so they are engaged

physically, emotionally and cognitively. This should be the main HR strategy

which should be discussed how engagement can help organisations

outperform. Talent management strategies and policies need to be aligned

with those of the wider business.

2. The talent management strategy can be supported by technology such as

HRIS (HR Information Systems). Modern techniques also use Competency-

based management methodologies to capture and utilize competencies

appropriate to strategically drive an organization's long term plans.

3. The combination of talent management tools i.e. recruitment and selection,

job fit, Performance appraisal, training & coaching, individual development

Plan, monitoring, competency mapping, succession planning Predicts

employee engagement and should be applied across companies. The

employee engagement survey should be regularly carried out to identify the

engagement factors.

4. The major setback is due to ineffective talent management tools which reflect

on ineffective managerial competencies that hamper engagement levels. The

manager can mould a strong team for better performance. The combination of

managerial competencies i.e. thinking strategically, initiative and innovation,

planning & organizing, coaching, decision making and result orientation can

lead to high employee engagement. Thus managers need to be moulded and

developed accordingly with the above managerial competencies for improving

the employee engagement

CHAPTER 1: INTRODUCTION

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CHAPTER 1

INTRODUCTION

1.1. NEWER APPROACHES IN MANAGING HR’S TO FACE

COMPETITION.

Over the years, organizations across globe over have increasingly become

aware of the importance of human resources. In today‘s globalized world, it is

relatively easy to gain access to the competition‘s technology and product

differentiation. The ―real life‖ experiences substantiate the assumption that no

matter how sophisticated and modern the business activities of the

organization are, it will be extremely difficult to sustain its growth and

effectiveness of human resources as complementary to its operations. This

realization has propelled human resource management as a major field of

study in the recent years. This renewed interest has further facilitated the

development of newer approaches in managing human resource in respective

organization of open competition. It is being continuously influenced by the

ever changing sub-systems in the environment. Human Resource

Management could thus be viewed as a dynamic process which needs to be

aligned with the changing realities in the environment which largely mean to

suit the increasing competitive productivity and efficiency.

1.2. GROWING REALIZATION WITH CHANGING BUSINESS CONTEXT

The popular notion among business scholars and experts is that competent

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and motivated people can make things happen and enable an organization to

achieve its goal. It is about providing employees with the tools that will help

them to improve their job skills and manage their career paths. Employees

spend most of their valuable time, energy skill at their workplace. In the

changing socio economic scenario the face of work culture has also

undergone a change. Employees now seek appropriate working conditions,

which will enhance their contributions. In order to retain skilled manpower the

management of several companies has started implementing human

resource policies with family orientation and flexibility. It‘s not just training –

it‘s about coaching and mentoring the employees from the heart. Human

Resources Services Company achieved this status because its key focus was

training its talent. Aditya Birla Group was named the best employer in India

for 2007 by Hewitt in their best employer‘s survey 2007. The group constantly

focuses on personal and professional growth of its people, providing them

with challenging opportunities, and improving their quality of their life. TCS

keeps its employees constantly engaged through rotation in terms of

technology, customer and industry domain. It implements several innovative

leadership development programs, uses the performance management

system for employee‘s career planning, and ensures work life balance by

ensuring people in leisure time interests and hobbies in addition to personal

development.

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1.3. FRAMEWORK OF EMPLOYEE ENGAGEMENT

When employees are engaged with their company‘s sustainability strategy,

they proactively identify, communicate and pursue opportunities to execute

the strategy. Companies can engage employees through numerous means,

ranging from inviting them to share ideas with senior management to giving

them opportunities to volunteer for local community-outreach programs

Engaged employees within an organization provide a competitive advantage

to organizations, as explained by the resource-based view (RBV) of the firm

([62] Joo and Mclean, 2006), and hence there is a need to continuously

engage employees. The resource-based view points that human and

organizational resources, more than physical, technical or financial resources,

can provide a firm with sustained competitive advantage because they are

particularly difficult to emulate ([66] Lado and Wilson, 1994; [118] Wright and

McMahan, 1992). The RBV points out that firms can develop sustained

competitive advantage only by creating value in a way that is rare and difficult

for competitors to imitate (e.g. [5] Barney, 1991, 1995; [51] Grant, 1991; [86]

Peteraf, 1993; [83] Paauwe, 1994; [113] Teece et al. , 1997; [44] Foss, 1997).

Engaged employees are more likely to act as organizational advocates than

disengaged employees and can play a powerful role in promoting their

organization as an employer of choice (CIPD REPORT). Many different

engagement studies from Gallup organization, Towers Perrin, Hewitt,

Blessing White, the corporate Leadership Council and the Conference Board

have used different definitions of engagement that managers must take in to

4 | P a g e

considerations when supervising employees. Those drivers include doing

exciting and challenging work, having career growth and learning and

development opportunities: working with great people, receiving fair pay,

having supporting management and being valued recognized and respected.

As per the above study the top drivers of engagement come down to the

employee‘s connection between their work and organization success. The

second driver is an employee‘s belief that his work matters to the

organization. According to Jonathan Austin, chief executive officer of Best

Companies Ltd, "there is nothing more important to a company than engaged

employees". Employee engagement is the term that defines the quality and

strength of the relationship between an employee and their organization.

Research by Best Companies shows that levels of engagement can seriously

affect a company. A strongly disengaged employee will have no interest in

their work and may even sabotage the potential success of a project.

(Whitehall & Westminster World on 14 March 2005)

The most common factors influencing job satisfaction are:

■ More opportunities to use talent

■ Career development and training.

1.4. IMPORTANCE OF TALENT MANAGEMENT

At a time when companies are increasingly relying on employees to

demonstrate the knowledge, skills and attitudes needed to execute

sustainability initiatives, the quality of company leaders are more important

5 | P a g e

than ever. Some companies are fortunate to have leaders who are passionate

and knowledgeable about sustainability, who can drive the changes needed

to support it in their organizations and who can inspire employees to achieve

new levels of performance. The issue with many companies today is that their

organizations put tremendous effort into attracting employees to their

company, but spend little time into retaining and developing talent. A talent

management system must be worked into the business strategy and

implemented in daily processes throughout the company as a whole. It cannot

be left solely to the human resources department to attract and retain

employees, but rather must be practiced at all levels of the organization. The

business strategy must include responsibilities for line managers to develop

the skills of their immediate subordinates. Divisions within the company

should be openly sharing information with other departments in order for

employees to gain knowledge of the overall organizational objectives.

Companies that focus on developing their talent integrate plans and

processes to track and manage their employee talent, including the following:

Sourcing, attracting, recruiting and on boarding qualified candidates with

competitive backgrounds, managing and defining competitive salaries,

Training and development opportunities, Performance management

processes, Retention programs, Promotion and transitioning. Talent

management is a key to engagement. Companies that engage in talent

management (Human Capital Management) are strategic and deliberate in

how they source, attract, select, train, develop, retain, promote, and move

6 | P a g e

employees through the organization. Research done on the value of such

systems implemented within companies consistently uncovers benefits in

these critical economic areas: revenue, customer satisfaction, quality,

productivity, cost, cycle time, and market capitalization. The mindset of this

more personal human resources approach seeks not only to hire the most

qualified and valuable employees but also to put a strong emphasis on

retention.

1.5. IMPACT OF MANAGERIAL COMPETENCIES ON EMPLOYEE

ENGAGEMENT

This term "talent management" is usually associated with competency based

management. Talent management decisions are often driven by a set of

organizational core competencies as well as position specific competencies.

The competency set may include knowledge, skills, experience, and personal

traits. Older competency models might also contain attributes that rarely

predict success e.g. education, tenure, and diversity factors that are illegal to

consider in relation to job performance in many countries, and unethical within

organizations. New techniques involve creating a competency for the

organization that includes a Competency dictionary to hold the competencies

in order to build job descriptions. The managers should use their

competencies to perform a variety of behavior and tasks that result in

products and services or in other words output that is being catered to

different stakeholders. The quality of the inputs in the form of behavior and

tasks has an influence on the people who receive them which results positive

7 | P a g e

and negative outcomes of an organization. The sustainability of an

organization depends on the effectiveness of their management team, their

ability to foresee the future, leadership capabilities and the skill and

knowledge of its workforce. This means that the success of an organization is

primarily indebted to the competencies of their managers. The core idea of

this research is to carry out an empirical investigation on the relationship

between Talent management and Managerial competencies and their role

and effectiveness on employee engagement in Private and MNC IT sector.

CHAPTER 2: LITERATURE REVIEW

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CHAPTER 2

LITERATURE REVIEW

2.1. SHIFT OF HRM PRACTICES OF TALENT MANAGEMENT

The current market is witnessing a wave of the shift from traditional practices

of Human Resources Management, to the strategic practices. This shift

requires organizations to reflect on how to attract, recruit, employ, and retain

talented employees. Organizations know that they must have the best talent

in order to succeed in the hypercompetitive and increasingly complex global

economy. Along with the understanding of the need to hire, develop, and

retain talented people, Organizations are aware that they must manage talent

as a critical resource to achieve the best possible results. The results of many

studies and researches indicated that; talent management has become one of

the priorities of the management. The main reason for this importance is the

similarity of dynamic global demographical, economical, social, cultural, and

business trends where scope and speed are creating a significant talent gap

(White, 2009, p. 4), as the gap widened, it is difficult for organizations to

acquire and retain talent to achieve success through the traditional practices

of Human Resources Management. Few, if any, organizations today have an

adequate a totally different approach because the ―talent pool‖ identified is

coming from within a managed diverse workforce where everyone is

managed and developed ―differently‖ according to their backgrounds, beliefs,

religions, etc. To identify talent from a diverse workforce and take that talent

forward will require a separate HRD intervention, particularly if the need for

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talent was identified as a consequence of an organizational business need.

Organizational success is the most effective evaluation of Talent

Management (Tansley et al., 2007) and thus the outcomes will reflect the

inputs in the form of HRD interventions that identified and subsequently

trained the talent. Following a year long research project undertaken by

Nottingham Business School on Talent Management for the Chartered

Institute of Personnel and Development (CIPD), they have developed a

definition of Talent Management (Tansley et al., 2007).

Talent consists of those individuals who can make a difference to

organizational Performance, either through their immediate contribution or in

the longer term by demonstrating the highest levels of potential. However, the

same work also argues that specifications of talent are: organizationally

specific; highly influenced by the type of industry and the nature of its work;

and dynamic, so likely to change over time according to organizational

priorities. It seems therefore that conceptual and practical difficulties will

remain a feature of Talent Management. The project defined what is to be

addressed by talent management, e.g. retention of best performers, lack of

successors to senior or key positions, development of potential of

staff/development of future leaders (Internal document). There seemed to be

a fairly a common view about Talent management, ―A company‘s traditional

department-oriented staffing and recruiting process needs to be converted to

an enterprise wide human talent attraction and retention effort.‖ While many

advocates of this perspective view Talent Management quite broadly within

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the organization, there is a tendency for practitioners who focus primarily on

sub-disciplines or specialist areas within HR to narrow the definition of Talent

Management. For instance, recruiters have a tendency to discuss Talent

Management in terms of sourcing the best candidates possible (HR Focus,

2004; Sullivan, 2005), training and development professionals advocate and

encourage ―growing talent‖ through the use of training/leader development

programs (Cohn et al., 2005, p. 64), compensation experts tend to emphasize

the use of compensation and performance management processes (Garger,

1999), while leadership-focused writers stress succession planning and

leader development (Conger and Fulmer, 2003). Regardless of the breadth of

their point of view, or lack thereof, these authors replace the traditional term

―human resources‖ with ―Talent Management‖ (Lewis and Heckerman, 2006).

A second perspective on Talent Management focuses primarily on the

concept of talent pools. Talent Management, to these authors, is a set of

processes designed to ensure an adequate flow of employees into jobs

throughout the organization (Kesler, 2002; Pascal, 2004; HR Focus, 2003).

Approaches such as these can be said to be typically succession

planning/management or human resource planning ( Jackson and Schuler,

1990; Rothwell, 1994) and may also include typical HR practices and

processes such as recruitment and selection (Lermusiaux, 2005). Central to

these approaches is forecasting employee/staffing needs and managing the

progression of employees through positions and tends to be more internal

than external. Schweyer (2004a, p. 20) offers a perspective typical of this

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approach, ―The first step in Talent management is to gain a solid

understanding of the internal workforce.‖

Lewis and Heckerman suggest a third perspective on Talent management

focuses on talent generically; that is, ―without regard for organizational

boundaries or specific positions.‖ It is within this perspective that two general

views on talent materialize. The first views talent, typically high performing

and high potential talent, as an unqualified good and a resource to be

managed primarily according to performance levels. That is, highly competent

performers are to be sought, hired, and differentially rewarded regardless of

their specific role or, in some cases, the organization‘s specific needs. This is

in contrast to the second perspective outlined above that organizations are

encouraged to manage pools of talent based on performance generally rather

than succession pools developed for specific jobs. The second view of

generic talent regards it as an undifferentiated good and emerges from the

both the humanistic and demographic perspectives (Lewis and Heckerman,

2006). It follows that talent is critical because HR functions‘ role is to manage

all individuals to high performance (Buckingham and Vosburgh, 2001; Walker

and Larocco, 2002) and because changes in demographic and business

trends make talent in general more valuable (Gandossy and Kao, 2004;

Romans and Lardner, 2005; Tucker et al., 2005).These three perspectives

take us only part of the way to understanding the role of Talent management

in organizations and in general organizations do adopt their ―own style‖ of

policy and approach (Tansley et al., 2007). These postulations though from

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Lewis and Heckerman endorse the concept that Talent management in an

organization is in essence about the strategic attraction, retention and

development of individuals of high potential for organizational performance.

Will HRD interventions to ―manage diversity‖ be capable of being extended to

deal strategically with the management of talent? It is also clear from that

document and from interviews that there are currently different views on what

constitutes Talent Management. One interview responded that Talent

Management means ―loads and loads of things‖; perhaps a colloquial

expression of the ―cradle to grave‖ view of Talent Management; while another

actually used the ―cradle to grave‖ description of Talent Management. Others

focused on the items suggested in the project document and highlighted

succession planning and/or developing future leaders. A number of

respondents expressed the view that the approach adopted in the council is

likely to be narrow, and therefore exclusive, rather than all encompassing and

inclusive. This in part was based on the observation that while a Talent

management policy and strategy is yet to be formulated there are isolated

pockets of Talent Management currently being practiced in some directorates,

and on the related observations that these tend to be focused only on

selected individuals. This situation is also acknowledged to exist in the project

plan. It is not uncommon in organization for activities which would be

recognized as Talent management to be happening without a formal and

planned strategy but where this is the case those activities are likely to have

significant impact on eventual formalized strategies (Tansley et al., 2007).

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2.2. SPECIFIC HRD INTERVENTIONS

For examples of specific HRD interventions on either or both of Talent

Management or managing diversity under the broad headings of

management training and development (MTD), career management and

development (CMD), and professional development (CPD). These as fairly

standard and well-established categories of HRD practice which would be

recognized, if not necessarily used on a daily basis, by our respondents. The

council is in the process of introducing management standards and will be

using those for all three categories with associated use of 360 degree

appraisals and new performance management processes. Qualification

based programmes are also utilized within all three categories, as are

development centre‘s and short courses, both internal and external. However,

it seems from what were told by most respondents that only some of these

might form part of eventual Talent Management programmes. There seemed

to be a fairly Talent management that ensures organizations have the

quantity and quality of people in place to meet their current and future

business priorities. The process covers all key aspects of an employee‘s ―life

cycle:‖ selection, development, succession and performance management.

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2.3. KEY COMPONENTS OF A HIGHLY EFFECTIVE TALENT

MANAGEMENT PROCESS

The key components of a highly effective Talent Management Process

include the following:

2.3.1. A clear understanding of the organization‘s current and future

business strategies.

2.3.2. Identification of the key gaps between the talent in place and the

Talent required driving business success.

2.3.3. A sound talent management plan designed to close the talent gaps.

It should also be integrated with strategic and business plans.

2.3.4. Accurate hiring and promotion decisions.

2.3.5.Connection of individual and team goals to corporate goals, and

providing clear expectations and feedback to manage performance.

2.3.6. Development of talent to enhance performance in current positions

as well as readiness for transition to the next level.

2.3.7. A focus not just on the talent strategy itself, but the elements

required for successful execution.

2.3.8. Business impact and workforce effectiveness measurement during

and after Implementation.

This above underline points shows the importance of recognizing that it is not

enough to just attract individuals with high potential. Developing, managing

and retaining those individuals as part of a planned strategy for talent is

equally important, as is adopting systems to measure the return on this

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investment. More organizations are also now broadening their definitions,

looking at the ‗talents‘ of all their staff and working on ways to develop their

strengths. Many practitioners and authors have recognized the insufficient

role of HR practices in the new era which characterized by rapid globalization

and high competitive environment (Budhwar and Debtah, 2008). The new

business's environment needs to be changed from HR traditional practices to

strategic Human Resources Management (SHRM) that defined as: "the

pattern of planned Human Resources deployment and activities intended to

enable an organization to achieve its goals (Yuengo and Minglau and Foley,

2008). According to this definition, one can recognize that SHRM is a strategy

that aims to accomplish the organizational goals, through the work-force, and

this strategy is closely consisting with the supply of talent. Gaps exist at the

top of the organization, in the first- to midlevel leadership ranks, and at the

front lines. Talent is an increasingly scarce resource, so it must be managed

to the fullest effect.

2.4. TALENTED PEOPLE AND THEIR CHARACTERISTICS

Highly talented people have very different values and motivation from the

majority of people. More is expected from them, and they expect more in

return, often have a significant impact, and high cost. Their thinking is

different and faster. They become bored easily. And they prefer different

types of challenges. They can deal with more complexity, but are more

complex in themselves (Robertson and Abbey, 2003).relationship or the

manager-employee relationship in this perspective is clarified by Steve Jobs,

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Founder of Apple Computer: "it doesn't make sense to hire smart people and

then tell them what to do; we hire smart people, so they can tell us what to

do" (Baker, 2006). The term talent management refers to the strategic

management of the flow of talent through an organization. The purpose of

talent management is to ensure availability of adequate supply of talent to

align the right people with the right jobs at the right time based on strategic

business objectives (Duttagupta, 2007). There fore, the talent management is

not just an HR activity, but it is a mindset that goes towards a holistic and

integrated approach to maximize the competitive advantage through people.

Talent management is a complex collection of connected HR processes that

delivers a simple fundamental benefit for any organization. It is the systematic

attraction, identification, development, engagement/ retention and deployment

of those individuals who are of particular value to an organization, either in

view of their ‗high potential‘ for the future or because they are fulfilling

business/operation-critical roles. There is no shortage of definitions for this

term, used by corporate leadership the world over. With a nod to other points

of view, DDI defines talent management as a mission critical process

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2.5. TRENDS OF TALENT MANAGEMENT AND ITS IMPACT

Talent management is fast gaining a top priority for organizations across the

world. Trends for talent management, talent wars, talent raids and talent

shortage, talent metrics retention and concerns for talent strategy are

expressed in the literature, across various countries like the USA, the UK,

Australia, Japan, China, India, and across Asia (see [119] Yeung, 2006; [98]

Ruppe, 2006; [36] Dunn, 2006; [30] Chugh and Bhatnagar, 2006; [69] Lewis

and Heckman, 2006; Lewis, 2005; [17] Branham, 2005; [10] Bennett and Bell,

2004). Talent management was initially designed to improve the process for

recruiting and developing people with the required skills and aptitude to meet

current organizational needs. The various aspects of talent management are

recruitment, selection, on-boarding, mentoring, performance management,

career development, leadership development, replacement planning, career

planning, recognition and reward (Romans and Lardner, 2006; [55] Heinen

and O'Neill, 2004; [108] Scheweyer, 2004). Competition and the lack of

availability of highly talented and skilled employees make finding and

retaining talented employees major priorities for organizations ([42] Fegley,

2006). In order to attract and retain the best talent anywhere in the world, an

organization must have a strong and positive employer brand ([18] Brewster

et al., 2005) which looks at performance results as an opportunity for an

"assessment" of ability, leads to lower performance and unhappy staff who do

not fulfill their potential and thus would reflect low talent engagement.

Employer brand interventions in recent research indicates talent management

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as a key driver for this strategy, and is on the agenda for HR executives in

2007 and beyond ([58] HR Focus, 2006, [59] Focus, 2007). Talent has

become the key differentiator for human capital management and for

leveraging competitive advantage. Grounded within strategic HRM ([52]

Gratton, 2000; [9] Becker et al. 2001), the management of talent seems to be

one of the key functions that HRM is playing strategically in organizations

([12] Bhatnagar, 2004). Recent research indicates that the war for talent is

intense due to labour market shortages ([17] Branham, 2005; [18] Brewster et

al., 2005; [67] Lawler, 2005; [19] Boudreau and Ramstad, 2005; [26] Cappelli,

2000; [82] Nybo, 2004; [109] Sparrow, 2004), yet very little research attention

has been aimed at competitive talent management strategies. Further, [87]

Pfeffer and Sutton (2006) reflect that the typical HRM/talent mindset, which

looks at performance results as an opportunity for an "assessment" of ability,

leads to lower performance and unhappy staff who do not fulfill their potential

and thus would reflect low talent engagement.

2.6. FOCUS ON TALENT ENGAGEMENT

In fact, talent engagement (Fombrum, 2006) is an area which needs a special

research focus. It raises questions such as:

What is the engagement score?

At what level are various talent segments and departments engaged?

Are engagement levels increasing over time due to talent management?

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These questions need to be addressed through research. Companies with

highly engaged employees articulate their values and attributes through

"signature experiences" - visible, distinctive elements of the work environment

that send powerful messages about the organization's aspirations and about

the skills, stamina, and commitment employees will need in order to succeed

in these organizations Brown, A., Roddan, M. And Jordan, S. 2007, p.

1).Employee engagement as a key to the retention of talent (one-of-a-kind

hire in 100 employees; [50] Glen, 2006) is an area in which the lead has been

taken by practitioners ([85] Parsley, 2006; [7] Baumruk et al. , 2006; [117]

Woodruffe, 2005; [48] Gallup Management Journal , 2006; [10] Bennett and

Bell, 2004; Hay Group, 2002). It is an area where rigorous academic research

is required ([25] Cartwright and Holmes, 2006; [62] Joo and Mclean, 2006;

[71] Luthans and Peterson, 2002). Employee engagement ([96] Rothbard,

2001; [25] Cartwright and Holmes, 2006; [62] Joo and Mclean, 2006), is an

important outcome variable which research studies in India have not

investigated. In fact, [42] Fegley (2006) indicated trends in the Western world

that the Indian HR community needs to look into. Given the relevance of the

dynamic work environment post-liberalization, this study becomes important.

2.7. CHANGING BUSINESS CONTEXT

After liberalization of the Indian economy, the impact of restructuring,

economic transition to an open market, and increased competition from

internal and external sources has put pressure on all functions of

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organizations ([13] Bhatnagar, 2007; [23] Budhwar et al. , 2006). There has

been evidence of a general need among the managerial cadre to build

capabilities, resources, competencies, strategies, and macro as well as micro

HRM activities ([23] Budhwar et al., 2006; [14] Bhatnagar and Sharma, 2005).

Some leading Indian organizations have brought out newer issues in the

strategic management of their HR function. An attempt has been made in this

research to fill this gap, and to investigate the emerging talent management,

managerial competencies and employee engagement issues in the IT

industries.

2.8. GLANCE ON IT SECTOR

The Indian BPO/ITES sector has been the focus of some research studies in

the West recently (for a detailed analysis of this sector, see [75] McMillan

(2006); [23] Budhwar et al., 2006; [76] Mehta et al., 2006; [104] Singh and

Pandey, 2005; [116] Venkatraman, 2004).India's competitive advantage as

compared to other countries has made it a target destination of multinationals

for their back-end operations. To begin with, the abundant skilled manpower

gives the country an edge. India has the largest English-speaking talent pool

in the world with 4.40 lakh (1 lakh=100,000) engineering diploma holders,

about 23 lakh graduates in other disciplines and 3 lakh post graduates.

Three-fifths of the Indian technical workforce has more than four years of

experience ([84] Pandeya and Bali, 2006, p. 20). Global Services Location

Index (2007) cited in an [2] A.T. Kerney Report (2007) claims that in the

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overall ranking of BPOs, dominated by developing countries from Asia, India

is followed by China, Malaysia, Thailand and Brazil. To arrive at the final

ranking, A.T. Kearney surveyed over 50 countries for different aspects related

to off shoring services, like people skills, financial attractiveness and business

environment. India maintains a wide, albeit slightly shrinking, lead over China,

confirming what industry surveys and visiting executives have found. While

compensation costs in India have increased because of recent high economic

growth, "these cost escalations have been matched by corresponding

increases in skill supply and quality indicators", the global consultancy said.

Although India ranks high overall, mainly because of its skilled and technically

superior pool of manpower, it suffers on the other two parameters - financial

attractiveness and business environment rankings. In terms of people skills

India ranks second, behind the US (tier II cities) but ahead of China and

Germany. As for business environment rankings, India is placed a distant

34th. When it comes to the question of cost effectiveness, Vietnam, with one

of the lowest telecom costs in the world, comes out on top while India is

ranked sixth. Meanwhile [75] McMillan (2006, p. 240) reported that the US

accounts for 59 per cent of total global investment in the Indian ITES-BPO

industry, targeting legal, logistics and customer care segments. Europe is the

second largest market at 22 per cent, targeting HR, purchasing, finance, and

accounting. Finally, the Asia/Pacific region follows at 15 per cent, with the

fastest growing areas including HR, engineering, finance, accounting, and

purchasing. While the NASSCOM ([80] National Association of Software and

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Services Companies, 2006) Report states that the IT-ITES sector contributed

4.8 per cent of GDP in 2006 and is to achieve the targeted $60 billion in

exports by 2010. On the other hand, it was reported by ICRA, an associate of

Moody's Investors Service, reported that the Indian BPO/ITES industry is

benefiting from the continued trend of outsourcing by global corporations of

their business processes service to developing countries, and the domestic

ITES sector is set to reach the $10 billion mark by 2006-2007 from $7.2 billion

in 2005-2006, a growth of almost 39 per cent ([88] PTI, 2006). The report also

pointed out that in line with the growth of the sector, manpower demand is

also expected to surge to around 1.4 million by 2012. Sustaining this high

growth in the ITES sector would require the industry to attract an additional

0.5 million employees over the estimated figures, it said. Dispelling the fears

of outsourcing backlash from developed countries, the study stated that over

the long term, outsourcing by developed nations may lead to the creation of

new jobs in occupations that require higher levels of skill, increase real

wages, and yield significant economic gain. According to the NASSCOM

strategic review ([80] National Association of Software and Services

Companies, 2006), for India to fully capitalize on the opportunity and sustain a

disproportionate lead in the global IT-ITES space, it needs to focus on

enhancing the talent pool advantage - focus on skill development to better

leverage the world's largest working population, among others. According to

[23] Budhwar et al. (2006), with India expected to achieve revenues of $148

billion by 2014; the industry requires direct recruitment of over 3.7 million

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personnel. With recruitment becoming a source of concern, attrition within the

sector is creating problems of employee engagement within this sector. While

India does have a large talent pool, not all are "industry-ready" or equipped

with the necessary skill sets to become useful to companies. This means that

while there is plenty of supply at the entry level (voice processes), there are

huge gaps in the middle management and senior management levels. This

has resulted in increased levels of poaching and attrition cases. Presently, the

average attrition rate faced by this industry is somewhere around 30-35 per

cent ([90] Phukan, 2007). Attrition has actually stabilized in the IT and ITES

sector, if one takes the three-to-four year time frame. For BPOs/ITES

centered around Bangalore (Southern India), it could be around 35-40 per

cent ([101] Sen, 2007).Over the last few years, a number of studies related to

the management of human resources in outsourcing centre‘s have been

conducted. The literature highlights that most of these studies have been

conducted in the developed countries (see for example, special issues of

HRMJ , 2002, European Journal of Work and Organizational Psychology ,

2003; [57] Holtgreve et al. , 2002; [20] Butler, 2004; [34] Deery and Kinnie,

2004). They provide the theoretical basis for analyzing employee engagement

studies in the HR practices context. A framework for employee engagement

in the BPO sector can provide interesting leading points for practitioners and

academicians to plan training interventions to arrest disengagement and

hence quitting behavior in the workforce and leverage the quality of the

engagement index as a competitive advantage. Hence there is an immense

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need to study employee engagement in this sector. The next section focuses

on the conceptual framework of employee engagement and the literature

review in this area. This fulfils the first aim of the current study.

2.9. EMPLOYEE ENGAGEMENT FOR MAXIMIZING PERFORMANCE

The literature on employee engagement has a practitioner influence, and

research studies (barring a few like [96] Rothbard, 2001; [74] May et al.,

2004; [107] Schaufeli and Bakker, 2004) are sparse in this area. This paper

examines both the aspects in the literature. It first deal with practitioner-

oriented definitions and then move to academic research. According to CEO

Speak in the Hewitt Best Employers Survey (2004), among the many key

people challenges one is to build a fierce employer brand equity ([43] Fitz-

enz, 2003), and one way to do that is to retain employees. This would be

possible if organizations provide them with a passion to work, and an

engrossing environment which maximizes their performance and gives a

continuous work experience that is difficult for competitors to replicate.

Managers are an important key in this equation ([7] Baumruk et al. , 2006;

[72] Lockwood, 2006). Further, an employer of choice recruits and engages

talent through practices that address both tangibles and intangibles, with a

focus on the long-term as well as the short term, and are tailored to the

organization ([17] Branham, 2005). A recent survey of HR professionals in

Western countries reflects that the most important issue anticipated in 2006

involved retaining and developing key employees (75 percent of responses);

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the next issue was of employee engagement and enhanced productivity (60.7

percent of responses cited this issue), followed by leadership training and

development (59.8 percent respondents cited this issue; [58] HR Focus,

2006). Effective talent management policies and practices demonstrate

commitment to human capital, resulting in more engaged employees and

lower turnover. Consequently, employee engagement has a substantial

impact on employee productivity and talent retention. Employee engagement,

in fact, can make or break the bottom line ([72] Lockwood, 2006). [73] Martel

(2003, pp. 30, 42) is of the opinion that, "in order to obtain high performance

in post industrial, intangible work that demands innovation, flexibility, and

speed, employers need to engage their employees. Engaging employees -

especially by giving them participation, freedom, and trust - is the most

comprehensive response to the ascendant postindustrial values of self-

realization and self-actualization". The performance data of the best

companies in the USA show that in all the practice areas discussed

previously, objectives are more easily met when employees are engaged and

more likely to fall short when they are not. In order to maintain an employer

brand, an emergence of a series of studies on employer of choice, which also

measure engagement index and financial performance ([32] Coleman, 2005).

A recent [100] SHRM Conference (2006) reported the result of a new global

employee engagement study showing a dramatic difference in bottom-line

results in organizations with highly engaged employees when compared to

organizations whose employees had low engagement scores. The study,

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gathered from surveys of over 664,000 employees from around the world,

analyzed three traditional financial performance measures over a 12-month

period, including operating income, net income and earnings per share (EPS).

Most dramatic among its findings was the almost 52 percent gap in the one-

year performance improvement in operating income between organizations

with highly engaged employees versus organizations whose employees have

low engagement scores. Employee engagement surveys are designed to

gauge the employee engagement based on employees' perceptions of the

work environment, which is part of the above surveys. Furthermore, when

done well, practices that support talent management also support employee

engagement (e.g. work-life balance programs - flexi time, telecommuting,

compressed workweeks, reward programs, performance management

systems) according to the Corporate Leadership Council (2004) and [73]

Martel (2003). Employee engagement begins with an on-boarding program

and is essentially a part of the human capital pipeline or talent pipeline, as

some researchers have determined (e.g. Romans and Lardner, 2005). In

India, although many multinational organizations have carried out the

engagement index survey, but the private IT companies has not made an

attempt has been made to study the same and link it to talent management

strategy. The current study attempts to map the engagement levels and

performance across the MNC and Private sector of IT companies with Talent

management strategy.

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2.10. SUSTAINABILITY OF BUSINESS THROUGH MANAGERIAL

COMPETENCIES

In the current climate of change, it's critical to hold onto the key people. These

are the people who will lead the organization to future success, and the

organization can't afford to lose them. The cost of replacing a valued

employee is enormous. Organizations need to promote diversity and design

strategies to retain people, reward high performance and provide

opportunities for development.

Every organization needs talented persons in different levels to enhance the

efficiency of the company. In this globalize era talented personals are having

demand and are offered good remuneration. For discharging specific tasks

talented and work ethic specialists are needed. In every field the case is

same. It is not easy to find the right talent needed for the organization, it takes

a wholesome effort involving lot of human resource to find the talents and

recruit them.

For any successful organization team of talented dynamic executioners,

passionate leaders in right roles will make sure effective execution of

strategies and correction if needed as per the situation. In the work

environment and the competitive world demands that the managers should

use their competencies to perform a variety of behavior and Tasks that result

in products and services or in other words output that is being catered to

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different stakeholders. The quality of the inputs in the form of behavior and

tasks has an influence on the people who receive them which results positive

and negative outcomes of an organization. Effective organizations anticipate

the leadership and talent requirement to succeed in the future. Leaders

understand that it's critical to strengthen their talent pool through succession

planning, professional development, job rotation and workforce planning. The

sustainability of an organization depends on the effectiveness of their

management team, their ability to foresee the future, leadership capabilities

and the skill and knowledge of its workforce. This means that the success of

an organization is primarily indebted to the competencies of their managers.

The core idea of this research is to carry out an empirical investigation on the

relationship between managerial competencies and their role effectiveness on

employee engagement. The resource based view (Barney 2000) suggests

that a firms competency and competencies arise out of its internal resources,

(people, knowledge, skill), and the strategic advantage of a firm lies in the

efficient utilization of its internal resources. Thus the managerial

competencies arising out of the managerial talent pool of an organization has

a very strong influence on its effectiveness.

Prior research has proved that the leader‘s role is crucial in setting the goals

of an organization and ensuring its long term and sustainable execution. It will

keep supplying value to the organization. In turn, Management needs to

realize its worth, extract it, polish it and utilize it.

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2.11. ROLE OF THE MANAGERS TO ENHANCE EMPLOYEE

ENGAGEMENT AND PERFORMANCE

The manager uses their competencies to perform a variety of behavior and

tasks those results in products and services or in other words output that is

being catered to different stakeholders. The quality of the inputs in the form of

behavior and tasks has an influence on the people who receive them which

results positive and negative outcomes of an organization. The sustainability

of an organization depends on the effectiveness of their management team,

their ability to foresee the future, leadership capabilities and the skill and

knowledge of its workforce. This means that the success of an organization is

primarily indebted to the competencies of their managers. The core idea of

this research is to carry out an empirical investigation on the relationship

between managerial competencies and their role effectiveness on employee

engagement. Boyatzis (1982) defined competency as ―A capacity that exists

in a person that leads to behavior that meets the job demands within

parameters of organizational environment, and that, in turn brings about

desired results.‖ SCMS Journal of Indian Management, January - March,

2011. 39 A Quarterly Journal Competencies can be otherwise defined as

behavior (i.e. communication, leadership) rather than a skill or ability. The

competency management systems are extensively used for appraising,

rewarding and promoting people in most of the organizations. However there

are not many studies in the recent past which have highlighted the fact that

30 | P a g e

the managerial competency can enhance managerial effectiveness and thus

leads to a superior organizational performance.

The resource based view (Barney 2000) suggests that a firms competency

and competencies arise out of its internal resources, (people, knowledge,

skill), and the strategic advantage of a firm lies in the efficient utilization of its

internal resources. Thus the managerial competencies arising out of the

managerial talent pool of an organization has a very strong influence on its

effectiveness. Prior research has proved that the leader‘s role is crucial in

setting the goals of an organization and ensuring its long term and

sustainable execution. Although there are many possible ways in which

leaders can drive innovation and change so as to have a sustainable growth

in their organizations, the best Indian leaders used an unusually consistent

and logical pattern is reflected in the driving change competency. Leaders

must also nurture and grow their teams, supporting their team‘s success

(Team Leadership). Finally, leaders must simultaneously empower their

people and hold them accountable, fostering their development and their

ability to take on greater responsibilities (Empowerment with Accountability).

People, and particularly leaders, lie at the heart of economic growth. No

strategy or policy can achieve the transformation of the Indian economy

without the right people, the right technical know-how, and the right mindset

and behavior. The leader should act as facilitator of change in any

organization by engaging his energy and empowering all the employees to

work together toward the same end.

31 | P a g e

The following section throws light into the study conducted in the pioneering

stages.

The Management concept in its nascent stage advocated that organizations

comprise certain specialized functions such as of setting goals and to develop

planning and control strategies for achieving them (Fayol 1916). These

included the coordination of interdependent activities, design and

management of the organizational architecture and taking measures for

motivating the work force. It was later summarized that senior managers have

several distinguishing roles of figurehead, leader, monitor, disseminator,

disturbance handler, resource allocator, and negotiator and of an

entrepreneur (Mintzberg, 1973; Mintzberg, 2001). Some of the roles are

pinned into almost all managerial positions and some others may be more

specific to certain industry, function or level in the organization (Kickul and

Gundry, 2001). On a macro-perspective, a manager ‘s job is broader than

managing their subordinates as he has to operate in an environment

constrained with organizations nature of business, the life cycle stage of

organization its vision and mission authority and resources available and so

for this the complexity that lays in a manager ‘s job. This demands a higher

degree of navigational and communicational skills, flexibility, creativity,

toughness, perseverance etc which leads to a question that which proves

these traits and competencies as aids in superiority in the performance of

managerial roles.

32 | P a g e

In the recent days organizations are more focusing on teams and workgroups

which can reduce the workload of a manager by sharing some of the

managerial tasks but both the success and failure of at the team depends on

a manager of that team (Antonioni, 1994). Sir Alex Ferguson is a classical

example of a manager who enacted as a consultant. Visionary coach and

educator which in turn produced the most valued football club Manchester

United of England. In a business scenario a manager as an inside consultant

should be able to identify problems and as a visionary who leads the team in

congruence with business SCMS Journal of Indian Management, January -

March, 2011.

A Quarterly Journal plan and top management goals. In the role of a coach

the manager trains and observes a team‘s performance, providing

constructive feedback and rewarding them at times for their performance

driven behaviors and which in turn nurture a team spirit. A good manager is a

good educator who facilitates the discussion and implementation of lessons

which can mould a strong team for the future. Management‘s success relies

upon the extent and quality of a managers contribution in achieving the goals

of his unit and that of the organization as whole (A .Shirazi, S.Mortazavi

2009). Cockerill (1989) is of the view that this more apt to manager as an

individual rather than their hierarchical authority within an organization. The

performance of a manager depends on the competency that he possesses or

that he develops. These are of cognitive (knowledge and skills affective

(values, beliefs), behavioral (personality types) and motivational in nature.

33 | P a g e

These competencies help him to demonstrate a set of behavior in a particular

situation (Ley, 2006; Boyatzis, 1982). Scholars like Finn (1993) argue

attributes such as task-related knowledge and experience (input

competencies), and personality characteristics (process competencies) can

have an impact on a manager‘s effectiveness. A study carried out by

Srivastava (2003) on successful Indian Business transformational leaders

helped in identifying those competencies in the form of useful motives,

attitudes, and personality traits have been contributing for managerial

success.

In his research McClelland‘s (1975) has proved that power motive and activity

inhibition or self-control of managers are two significant success factors. But

the other researchers such as Campbell (1970) were of the view that

intelligence, verbal skills, good judgment, organizing skill, effective

interpersonal relations, risk taking, hard work, pro-activity, confidence,

straight-forwardness, dominance, low anxiety, good health, ambition, active

participation, sense of autonomy in extra-curricular and community activities,

etc., result in a higher degree of managerial effectiveness. Boyatiz (1982) has

defined a set of competencies and traits that distinguish the elite group of

managers who are high performers from that of average and poor performers.

Kanungo and Misra (1992) in their paper presented the competencies that

constitute managers resourcefulness.( SCMS Journal of Indian Management,

January - March, 2011. 41 A Quarterly Journal) They classified them as

specific such as of greeting all customers with a smile, and generic that is,

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skills that are useable with some customization matching wide range of task

situations. The latter competency is an essential requirement in a non-routine

task that managers typically perform. It is a well known fact that companies

change business models for their survival, to face competition and for

attaining their organizational vision. In these situations the managers have to

act as an innovator or that of a change agent and hence the may have to

possess a number of competencies that may be associated with that of a

change agent. Kanter (1982) in her study of 165 middle level managers in

which she considered 99 of them as innovators and change agents and this

study underlines the fact innovators and change agents. The study suggests

that effective innovators and change agents are comfortable with change,

have foresight, mark opportunities well possess a clear sense of direction,

and have resilience, that is, they do not easily get dejected. They are tactful

but unrelenting and organize themselves thoroughly for meetings and

presentations. They liberally include colleagues and subordinates in decision-

making, and generously share rewards with their team members, and can

motivate team members to perform at their best. They are also good at

organizational politics and have a knack for identifying and cultivating

powerful supporters. The studies which identify the competencies of

successful managers are many in the realm of behavioral and competency

research and it should be considered that Managerial performance can be

broken down into a set of Key roles (Khandwalla, 2004) that can improve his

or her performance. The roles were identified from the study conducted by

35 | P a g e

Khandawalla (2004) among senior executives on his study in which he had

interviewed 25 managers on the role played by them in their respective

organizations. By a careful review of literature and content analysis and by

combining similar roles he streamlined it into twenty seven roles. These 27

roles can be broadly categorized into strategic operations-related, and

leadership/‗people management‘ roles (Khandwalla, 1995). These dimensions

comprise strategic roles operation, related roles and leadership or people

management roles.

The competencies and role effectiveness of the managers are measured

using an instrument developed by Khandwalla (1988) for his studies on senior

manager‘s competencies. The various dimensions considered for the study

are contextual sensitivity-related competencies, innovation sponsoring

capabilities, initiative managing competencies, resilience and problem solving

capabilities, task accomplishment-related competencies, and interpersonal

competencies.

2.12. RESEARCH GAP

The Indian economy, the impact of restructuring, economic transition to an

open market, and increased competition from internal and external sources

has put pressure on all functions of organizations ([13] Bhatnagar, 2007; [23]

Budhwar et al. , 2006). There has been evidence of a general need among

the managerial cadre to build capabilities, resources, competencies,

strategies, and macro as well as micro HRM activities ([23] Budhwar et al. ,

36 | P a g e

2006; [14] Bhatnagar and Sharma, 2005). Repeated research has shown that

there is a direct correlation between the level of employee engagement in a

company and the company‘s overall financial and operational performance.

The Instititute for Employment Studies in its publication: The Drivers of

Employee Engagement (Robinson D, Perryman S, Hayday S, April 2004)

cites that based on research it undertook ―the strongest driver of all is a sense

of feeling valued and involved.‖ The 2006 Conference Board publication

which summarized twelve major studies on employee engagement over the

past four years by top research firms such as Gallup, Towers Perrin, Blessing

White, the Corporate Leadership Council and others and came up with 26 key

drivers of engagement defined the direct relationship with one‘s manager as

the strongest of all drivers. A study about the impact of HR practices and

organizational commitment on the profitability of business units found a close

relationship between HR practices, operating expenses and firm

performance. In addition, employees were found to be more committed to the

organization when managed with progressive HR practices. The kind of

performance the company might see as a result of developing and

implementing proven HR practices. Going one step further, to assist

business-unit leaders whose groups were not meeting performance goals, the

company developed a portal to help identify key performance deficiencies and

now offers information on HR practices to help increase performance. As this

study demonstrates, HR's role in promoting employee commitment including

coaching managers to be effective people managers is a significant factor for

37 | P a g e

employee. In addition, HR practices can make the difference between

effective engagement and valuable human capital joining the competition.

There were following gaps in study which did not focus mainly on comparative

studies between MNC and private IT companies. The differences‘ of

engagement levels in the Multinational and Private sector of IT industries

showed a gap with the talent management tools and managerial

competencies. There was a gap in the studies where the effect of talent

management tools and managerial competencies can show significant

relation on the employee engagement. The talent management tools with the

managerial competencies can predict or enhance the employee engagement.

.

CHAPTER 3: STATEMENT OF THE PROBLEM

OBJECTIVES

HYPOTHESES

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CHAPTER 3

STATEMENT OF THE PROBLEM

The moot aim of any competitive organization becomes now to keep a pace

with the technological change and which continues to challenge all

organizational strategies and measures, thus impacting the human resource

development of any organization. Talent has become a strategic issue as

companies make decisions based on the availability of a labor and skills.

Many organizations speak about the importance of retaining their talent, but

workplace analysts point out that few organizations with a mature plan have

implement talent management which addresses the entire cycle from hire to

retire. Today‘s, HR is expected to identify potential talent and also

comprehend conceptualize and implement relevant strategies to contribute

effectively to achieve organizational objectives. Hence a serious concern of

every manager in order to survive this ―war for talent‖ is to fight against a

limited and diminishing pool of qualified available candidates to replace

valuable employees when they leave, dramatically underscoring the difficulty

to attract, motivate and retain the best employees in an organization. All the

organizations are finding loads of business opportunities and consequently

their revenues are growing rapidly .The increasing business opportunities

have necessitated that these organizations go for massive recruitment. But to

find the best talents those fit the job description and adjust organizations

39 | P a g e

values and norms. In order to win the war of talent, organizations have

invested heavily to implement human resources systems and processes, and

talent issues have become the agenda for any business forum. Although

these moves are laudable and necessary too many organizations still dismiss

talent management are short term, tactical problem rather than an integral

part of a long term business strategy, requiring the attention of top level

management and substantial resource. Due to the short term mind sets of the

leaders and managers. Since investments in talent management are

intangibles are expensed rather than capitalized, managers may prefer to

raise short term earnings by cutting expenditures on people development.

This tendency may fail to embed a talent strategy in the overall strategy of the

business and turn in to vicious circle: A lack of talent blocks corporate growth,

creating additional performance besides these challenges, Paese (2006),

argued that organizations may face two major impediments without

overarching strategic plan, resulting in frequent and unpredictable objectives

and disruptions. Secondly, senior leaders don‘t have a personal connection to

talent management through personal involvement and accountability.

Statement of the problem studies suggests that under such circumstances it

is very essential to study that certain organizations are forefront in having the

best talent in order to succeed in the hypercompetitive and increasingly

complex global economy. So it is important to identify the companies having

high engaged employees thus a comparative studies between MNC and

private sector IT companies are considered that understand the need to hire,

40 | P a g e

develop, and retain talented people, are the critical resource to achieve the

best possible results through engaged employees. But replicating a high-

quality, highly engaged workforce is nearly impossible. The studies have not

touched how talent management tools with managerial competencies can

affect the engagement levels in different sectors of IT companies. The

companies may have talent management tools but the extensive use of

managerial competencies also may affect engagement levels. There are no

studies which can help to identify the predictive model on talent engagement

for better performance. The study can be based on the managerial

competencies and the best managerial competencies that can enhance the

engagement levels by developing the managerial competencies model.

3.1. OBJECTIVES:

1. To find the differences of employee engagement levels, talent

management and managerial competencies between Private and

Multinational IT companies

2. To study the relation and effect of talent management and managerial

competencies on the levels of employees engagement in the Private

and Multinational IT companies

3. To understand the association and relation of talent management tools

that is workforce planning, talent acquisition, Talent measurement, talent

development, talent retention scores and levels of employee

engagement in the Private IT sector

41 | P a g e

4. To understand the association and relation of managerial competencies

scores i.e. thinking strategically, initiative and innovation, planning &

organizing, coaching, decision making and result orientation and levels

of employee engagement in the Private IT sector

5. To develop a predictive talent engagement model

6. To develop a managerial competencies model to enhance employee

engagement

3.3. HYPOTHESES

H01: There are no significant differences between employees

engagement in the Private and Multinational IT industries

H11: There are significant differences between employees

engagement in the Private and Multinational IT industries

H02: There are no significant differences between Talent management

tools in the Private and Multinational IT industries

H12: There are significant differences between Talent management

tools in the Private and Multinational IT industries

H03: There are no significant differences between Managerial

Competencies in the Private and Multinational IT industries.

H13: There are significant differences between Managerial

competencies in the Private and Multinational IT industries

H04: There are no significant relations between the Talent Management,

42 | P a g e

Managerial competencies and employee engagement in the

Multinational IT industries

H14: There are significant relations between the Talent management

Managerial Competencies and employee engagement in the

Multinational IT industries

H05: There are no significant effects between Talent Management

Managerial Competencies on the employee engagement in the

Multinational IT industries

H15: There are significant effects between talent management,

managerial competencies on the employee engagement in the

Multinational IT industries

H06: The Talent management and Managerial Competencies have no

significant relations on the levels of employee engagement in the

Private IT industries

H16: The Talent management and Managerial Competencies have

significant relations on the levels of employee engagement in

the Private IT industries

H07: There are no significant associations and relations of talent work

force planning, talent acquisition, talent measurement, talent

development, talent retention scores and the levels of employee

engagement in the Private IT industries.

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H17: There are significant association and relation of talent work

force planning, talent acquisition, talent measurement, talent

development, talent retention scores and the levels of

employee engagement in the Private IT industries.

H08: There are no significant associations and relations of Managerial

Competencies scores that best predicts employee engagement in

the Private IT industries

H18: There are significant associations and relations of Managerial

Competencies scores and levels of employee engagement in

the Private IT industries

H09: Predictive talent engagement management model cannot enhance

employee engagement

H19: Predictive talent engagement management model can enhance

employee engagement

H10: Predictive managerial competencies model cannot enhance

Employee engagement

H10: Predictive managerial competencies model can enhance

Employee Engagement

CHAPTER 4: RESEARCH METHODOLOGY

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CHAPTER 4

RESEARCH METHODOLOGY

Chapter 4 describes the research design and procedures followed to collect

and analyze the data needed to address the objectives. Information is

provided on the study design, population and sampling, research

instrumentation, data collection, and data analysis.

Research methodology is a blue print of the study conducted which includes

steps of data collection, sample selection, type of questionnaire, process of

data and finally interpretation of data.

4.1. UNDERSTANDING THE ISSUE

The research had to be started by understanding the concepts of talent

management, managerial competencies that can drive the engagement

levels. To study the IT sector considering the Multinational and Private

companies the secondary data‘s been essential.

4.2. PRESTUDY

This was done by open conversation with the HR department of the MNC and

Private sector of IT companies. The companies have been selected on the

basis of the turnover, organizational growth and size of the organization.

(Refer ANNEXURE VIII).

45 | P a g e

4.3. THE STUDY CONCENTRATED ON BOTH PRIMARY AND

SECONDARY DATA

4.3.1. The secondary data would give information on talent management,

managerial competencies and engagement levels. The information on

Private and MNC sector of IT companies were considered from

secondary sources.

4.3.2. The primary survey was critical component of the study and as it gives

the idea of impact of talent management, managerial competencies on

employee engagement levels in private and MNC sector of IT

companies

The survey would give an idea on:

1. The differences of talent management, managerial competencies on

employee engagement levels in private and MNC sector of IT companies

2. The effect of talent management and managerial competencies on the

levels of employees engagement in the Private and MNC of IT

companies

3. The association and relation of workforce planning, talent acquisition,

talent measurement, talent development, talent deployment, talent

retention scores and levels of employee engagement in the Private IT

sector

4. The association and relation of Managerial competencies scores i.e.

thinking strategically, initiative and innovation, planning & organizing,

coaching, decision making and result orientation that best predicts

employee engagement in the Private sector

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4.4. RESEARCH DESIGN

The study was primarily designed to find out from a cross section of

employees from MNC and Private Ltd companies of an IT sector from the

following cities such as Mumbai, Hyderabad, Bangalore, Cochin and Pune.

To find the differences of talent management, managerial competencies and

employee‘s engagement between MNC and Private IT companies. Size of the

Population comprised of 5500, considering the MNC and Private companies.

The companies were selected on the basis of organizational growth, size of

the organization. As it was impossible for the research, within the constraints

of time and money, to collect information from all, it was proposed to select

sample with stratified random sampling method. The samples drawn were the

executives, middle level with minimum one year of experience. The

questionnaire were provided to the respondents in order to fill their responses

and focused group interview was followed for in depth questions

4.4.1. SECONDARY DATA COLLECTION

Data‘s have been collected from the books and the journals. The details are

mentioned in the ANNEXURE I.

4.4.2. PRIMARY DATA COLLECTION

Questionnaire with open ended and closed ended questions were used as a

tool for collecting the data‘s. (Refer ANNEXURE II)

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4.4.3. POPULATION AND SAMPLE

The population defined for this study consisted of IT professionals in Private

and Multinational IT companies. Professionals were defined as individuals

with at least a graduate degree in a field related to IT background. The 20

organizations were included in the study and were selected on the basis of

convenience and accessibility. The ten companies from Multinational sectors

with the population of 2500 and sample size of 650 at 0.01 significance level

and ten from Private sectors with the population of 3000 and sample size of

700 at 0.01 significance level was calculated by using a sample size

calculator. The samples selected for the study included all professionals of IT

background. Table No 1 explains the population and the Sample size to study

the effects of talent management and Managerial competencies on the levels

of employee engagement in Multinational and Private IT industries.

4.4.4. SAMPLING TECHNIQUE

Since the population was heterogeneous with respect to Industries ie.MNC

and Private IT industries, to understand the effect of talent management and

managerial competencies on the levels of employee engagement and the

performance that is trying to ascertain .So to try the heterogeneity in the

population to be reduced by some means for a given sample size and to

achieve greater accuracy in the estimate, stratified random sampling was

logical. The sample was divided in to 2 strata‘s with respect to companies.

48 | P a g e

Table no 1: Sample sizes

MNC Popul

ation

Sample

size

Private

companies

Popul

ation

Sample

size

1. Cape

Gemini

300 65 Bluestar

InfoTech

200 70

2 Accenture 200 65 Zenith

computer

300 60

3 Infosys 350 65 Arteria 350 60

4 Cognizant 200 75 Philips

software

350 74

5 SAP 150 65 Covansys

India Pvt Ltd

300 75

6 WIPRO 300 67 Syntel

Telecom

300 70

7 L & T 300 74 CMS InfoTech 300 70

8 Apple 200 55 Tata InfoTech 300 75

9 Dell

computers

300 55 3i InfoTech 300 74

10 Oracle 200 64 Softcell

Technologies

Ltd

300 72

TOTAL 2500 650 3000 700

4.4.5. SAMPLE FRAME

The sample frames from where samples were drawn from the population

were mainly from MNC and Private IT companies and were senior level

managers and junior level managers. Senior level managers holding the

positions of leader, program managers, project managers, production

49 | P a g e

managers, HR Managers, Senior Business Development managers were

considered. From the junior level positions assistant programmers, Business

developers, Software Programmers‘, Associate Consultants, Developers, and

executives were also included in the sample frame.

4.4.6. TOOLS

The questionnaire was an open ended as well as close ended questionnaire

using 5 point Likert scale. The questionnaire was prepared taken in to

consideration of the following parameters such as tools on talent

management, combination of managerial competencies and employee

engagement aspects considering the emotional, cognitive and physical

components.

4.4. 7. INSTRUMENT USED

Descriptive information on the Job Engagement Survey was included. The

Job Engagement survey or JES (Rich, 2006) was developed by Bruce Rich

as part of his dissertation at the University of Florida. Rich‘s tool was based

on William Kahn‘s (Kahn, 1990) three-dimensional model of engagement

including cognitive, physical, and emotional components. The JES includes

18 items grouped under three factors: ―cognitive engagement‖ (examples:

at work my mind is focused on the job, at work I focus a great deal of

attention on my job), ―physical engagement‖ (examples: I work with intensity

on my job, I exert full effort on my job), and ―emotional engagement‖

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(examples: I am excited about my job, I am proud of my job). A copy of the

JES questions is included in Annexure II.

One key objective of Rich‘s dissertation was the construct validation of the

JES. The construct validity of a scale is established indirectly, by

accumulating evidence that the scale measurements ―result in a close

correspondence between the construct of interest and the scores provided by

the measure‖ (Schwab, 2005, p. 26). Three criteria for construct validity are

content validity, instrument reliability, and convergent validity. Content validity

is the correspondence between the measurement items and the construct the

instrument is built to measure (Schwab, 2005). Schwab suggested that

content validity should be supported by the testimony of experts in the field.

The JES items were designed to closely match Kahn‘s engagement model

and were examined by faculty members at the University of Florida. Schwab

(2005) defined instrument reliability as the ―degree to which measurement

scores are free of random errors‖ (p. 32) and the instrument is consistent both

internally (internal consistency) and over time (stability reliability). Because

the JES is a new scale no stability information is yet available. Rich (2006)

reported, however, strong internal consistency indexes (alpha coefficients) for

all three engagement factors, as reported in Table 2. Finally, convergent

validity means the correspondence between the scores of two measures of

the same construct (Schwab, 2005). In order to test convergent validity, Rich

(2006) contrasted the scores of the JES with those of the UWES (Schaufeli &

51 | P a g e

Bakker, 2003) with a sample of 245 fire fighters. Results supported a strong

correlation between the two measures (r =.64, p < 0.001).

Table no 2: Alpha Coefficients for Physical, Emotional, and Cognitive

Engagement

Factor Alpha

Physical engagement 0.93

Emotional engagement 0.94

Cognitive engagement 0.89

Overall engagement 0.93

Note. N = 180.

Source: by B. L. Rich, 2006.

Adapted from ―Job Engagement: Construct Validation and Relationships with

Job Satisfaction, Job Involvement, and Intrinsic Motivation,‖ by B. L. Rich,

2006.

The independent variables of talent Management (Romans and Lardner,

2006; [55] Heinen and O'Neill, 2004; [108] Scheweyer, 2004) were:

1.) Workforce planning (the supply and demand for talent over a two-

year or longer period of time for key jobs within the enterprise). Key issues

are retirements, planned and unplanned attrition, varying staffing options,

competencies for superior performers and bench strength for key talent. The

factors considered for workforce planning were critical role analysis,

52 | P a g e

critical role vulnerability analysis, and critical people analysis; identify

talent pool in to new roles.

2.) Talent acquisition (the ability of a company to attract and hire key talent)

Key issues are compelling employment brand and value propositions, referral

recruiting, and keeping a gold standard for new talent entering the

organization. The factors involved in talent acquisition were recruitment and

selection methods, assessment methods and tools

3.) Talent appraisal & assessment represents the extent to which the

workforce evaluation of their performance with the assessment tools the

employees by the way of individual development plan and competency

mapping which help in employee development.

4. Talent development: Informal learning is more powerful than formal

learning through such activities as stretch assignments; cross-functional

teams; international assignments and flexible job design and designed

as per the job description and developed understanding the individual

development plans. These factors were included in the talent management

5. Talent deployment can be summarized as the right people are doing the

right job at the right time. Top talent is assigned to the most vital projects or

roles. Alignment is a key aspect of talent deployment, and it is most often

achieved through performance management systems and competency

databases matching project needs to employee capabilities. The factors

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included were centralized information about employees with succession

planning, employee deployment

6. Talent retention: The variables considered were development

opportunities, career opportunities, mentoring, guidance, and support for the

development of the employee and organization.

Three criteria for construct validity were content validity, instrument reliability

and have been used to validate the data‘s. With the expert‘s opinion, using

reliability statistical tool like split half, Cronbochs alpha and Correlation test

were used which is detailed in the Pilot study chapter no 9

In the study managerial competencies were considered as independent

variable. The ability to lead talent was also the key factor. Great managers

were like chess players who understand that different employees have unique

strengths (Buckingham, 2004), and these managers work hard to put

employees in positions where they can shine. Great managers also

understand that their value to the organization was through the contributions

of others, and it was their responsibility to develop, guide and enhance the

performance of the people that report to them. The variables included in the

managerial competencies are

1. Managing & Developing

2. Problem Solving and participative management

3. Initiative/Innovation

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4. Results Oriented

5. Communication and building trust

6. Change Management

7. Coaching

8. Continual Learning

9. Continual Improvement

10. Developing others

11. Decision Making

12. Emotional Intelligence

13. Empowering others

14. Establishing focus/setting direction

15. Results orientation

These variables were considered from the competency dictionary and

included to construct the validation and reliability test.

4.4.8. LIST OF VARIABLES

The variables for talent management, managerial competencies which

are independent variables are listed in the table no 3 and employee

engagement is treated as dependent variable is also indicated in the

table no. 3.

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Table no 3 : List of variables

Independent

variable:

Talent

management

Independent variable:

managerial competencies

Dependent

variable:

Employee

engagement

1. Recruitment &

Selection

2. Job fit

3. Assessment

tool

4. Training

5. Performance

appraisal

6. Personal

development

plan

7. Mentoring and

coaching

8. Potential

measurement.

9. Developing

talent pool

10. Career

management

11. Ensuring

critical

retention

12. General

deployment

13.Succession

planning

1. Managing &

Developing

2. Problem Solving and

participative mgt

3. Initiative/Innovation

4. Results Oriented

5. Communication and

building trust

6. Change Management

7. Coaching

8. Continual Learning

9. Continual

Improvement

10. Developing others

11. Decision Making

12. Emotional

Intelligence

13. Empowering others

14. Establishing

focus/setting direction

15. Getting Results

1. Physical

engagement

2. Cognitive

engagement

3. Emotional

engagement

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4.4.9. THE SURVEY PROCESS

The survey was done on pilot scale at two MNC and two Private companies

by which the questionnaire was revised.

4.4.10. LIMITATION OF THE STUDY

The population was heterogeneous so proposed sampling design was

stratified sampling, the measurement in taking the sample may have some

errors since as per the convenience some of the questionnaire was sent

through mail. There can be chance of not understanding of questions or not

filling it appropriately by the sample so there can be an error in this situation.

The error can be reduced by calling up and or through sending emails.

A second limitation of this study was the potential impact of social desirability

bias. Social desirability bias could have lead participants to answer questions

about ―socially desirable attitudes, states and behaviors‖ (Bowling, 2005, p.

204) in the direction perceived as ―better. Thus, social desirability bias might

have artificially increased engagement scores. In particular, social desirability

may have reduced the variability .The participants were assured that the

surveys would be kept anonymous and may have reduced but not completely

eliminated this threat. Understanding this threat before hand, it was important

to understand the main variables related to engagement and managerial

competencies. Thus in order to reduce the diameter of the threat, this main

questions related to engagement and managerial competencies needed to be

focused upon .The variables that were the key factors for engagement and

managerial practices were identified and were framed in such a way that the

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respondents focus of attention is on the changes needed in managerial

practices and talent management activities for engagement. The indirect

questions actually helped in the research that gave the crux or material

needed to carry out the further research.

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FLOW CHART OF RESEARCH METHODOLOGY

Table no 4: Flow chart of research methodology

Design of the Study

• Cross-sectional designs

• MNC & PRIVATE IT Sector

Method of Data

Collection

• Primary data: Survey

• Tools: questionnaire(open ended & close ended)5pt likert scale

• secondary data: books, journal

Population & Sampling

•

• MNC PRIVATE

• Population 2500 3000

• Sample size 650 700

• Sampling method: stratified sampling

Instrumentation

• Dependent variable: employee engagement: job engagement survey or

• jes (rich, 2006)

• Independent variable: talent management: romans and lardner, 2006;

• [55] heinen and o'neill, 2004; [108] scheweyer, 2004

• Independent variable: managerial competencies: competency dictionary

Analysis

Of

Data

• Coorelation, multiple coorelation, multiple regression, factor analysis,

• cronbosch alpha, anova, chi-square

CHAPTER 5: CONCEPTUAL FRAMEWORK

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CHAPTER 5

CONCEPTUAL FRAMEWORK

5.1 CONCEPTUAL FRAME WORK ON TALENT MANAGEMENT

Talent is now a global game. It requires a much broader horizon than just a

specific company, city, region or country. And it requires a much broader

vision even within a company. The Talent Wheel highlights the key talent

functions that need to be coordinated and integrated within organizations.

5.2. INTEGRATED TALENT MANAGEMENT WHEEL

5.2.1. Workforce planning: It looks at the supply and demand for talent over

a two-year or longer period of time for key jobs within the enterprise.

Key issues are retirements, planned and unplanned attrition, varying

staffing options, competencies for superior performers and bench

strength for key talent.

5.2.2. Talent acquisition: Talent acquisition is the ability of a company to

attract and hire key talent. This is one of the two most pressing needs

according to Accenture‘s 2005 survey of global executives.

5.2.3 Talent development: It used to be synonymous with training, but no

longer. Informal learning is more powerful than formal learning through

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such activities as stretch assignments, cross-functional teams,

international assignments and flexible job design.

5.2.4. Talent deployment: It can be summarized as the right people are

doing the right job at the right time. Top talent is assigned to the most

vital projects or roles. Alignment is a key aspect of talent deployment,

and it is most often achieved through performance management

systems and competency databases matching project needs to

employee capabilities.

5.2.5. Talent retention: It is the number one issue on the minds of global

executives according to the Accenture study (2005). Many CEOs doubt

their company‘s ability to retain top talent. The employee turnover can

damage a business. These talent functions must work together and be

part of a seamless system. Being excellent in one or two areas is a

start, but the whole system must be working effectively. It does little

good, for example, for a company to attract and hire great talent but

then have few challenging development opportunities.

5.3. MANAGERIAL ABILITIES TO LEAD TALENT ENGAGEMENT FOR

SUSTAINABLE GROWTH

The ability to lead talent is also key factor. Great managers are like chess

players who understand that different employees have unique strengths

(Buckingham, 2004), and these managers work hard to put employees in

positions where they can shine. Great managers also understand that their

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value to the organization is through the contributions of others, and it is their

responsibility to develop, guide and enhance the performance of the people

that report to them. The resource based view (Barney 2000) suggests that a

firms competency and competencies arise out of its internal resources,

(people, knowledge, skill), and the strategic advantage of a firm lies in the

efficient utilization of its internal resources.

Thus the managerial competencies arising out of the managerial talent pool of

an organization has a very strong influence on its effectiveness. Although

there are many possible ways in which leaders can drive innovation and

change so as to have a sustainable growth in their organizations, the best

Indian leaders used an unusually consistent and logical pattern is reflected in

the driving change competency. Leaders must also nurture and grow their

teams, supporting their team‘s success (Team Leadership). Finally, leaders

must simultaneously empower their people and hold them accountable,

fostering their development and their ability to take on greater responsibilities

(Empowerment with Accountability). People, and particularly leaders, lie at

the heart of economic growth. No strategy or policy can achieve the

transformation of the Indian economy without the right people, the right

technical know-how, and the right mindset and behavior. The leader should

act as facilitator of change in any organization by engaging his energy and

empowering all the employees to work together toward the same end.

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5.4. CONCEPTUAL FRAMEWORK OF EMPLOYEE ENGAGEMENT

The engaged employees are strong organizational assets for sustained

competitive advantage and a strategic asset. Donahue (2001) emphasized in

a talent management strategy the credo of "heads, hands and hearts". It is

hearts (passion - a person's intrinsic motivation) that are the essence of

employee engagement. Further, there is confusion in the literature about

employee engagement. We see overlapping constructs of organizational

commitment, intrinsic motivation, and employee involvement, passion and

dedication to work. According to [63] Kahn (1990) employee engagement is

different from other role constructs such as job involvement ([68] Lawler and

Hall, 1970; [70] Lodahl and Kejner, 1965), commitment to organizations ([78]

Mowday et al , 1982) or intrinsic motivation (Deci, 1975). Employee

engagement is a multidimensional construct. Employees can be emotionally,

cognitively or physically engaged. [71] Luthans and Peterson (2002)

proposed [63], [64] Kahn's (1990, 1992) work on personal engagement, which

provides a convergent theory for Gallup's empirically derived employee

engagement. To be emotionally engaged is to form meaningful connections to

others (peers, co-workers) and to experience empathy and concern for others'

feelings. In contrast, being cognitively engaged refers to those who are

acutely aware of their mission and role in their work environment. According

to [63] Kahn (1990) employees can be engaged on one dimension and not

the other. However, the more engaged the employee is on each dimension,

the higher his or her overall personal engagement. On the other hand, [96]

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Rothbard (2001, p. 655) states that engagement may look at depletion or

enrichment in multiple roles. The theory behind role conflict is visited to prove

the point. This study also draws on the basic study of [63], [64] Kahn (1990,

1992), as does the research study by [74] May et al. (2004, p. 13), which

bases its work on meaningfulness in [63], [64] Kahn's (1990, 1992) basic

work. The study quotes the research study of [15] Britt et al. (2001), which

found that engagement in meaningful work, can lead to perceived benefits

from the work. Kahn (1990) suggests that employees experience dimensions

of personal engagement or disengagement during daily task performance.

Kahn (1990) noted that disengagement is dependant on social and cognitive

withdrawal and reflects incomplete role performance.

CHAPTER 6: CHANGING BUSINESS CONTEXT

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CHAPTER 6

THE CHANGING BUSINESS CONTEXT

The current economic environment sets the foundation for the reason that

talent management practices have arisen in the first place. Bossidy and

Charan (2004) have identified five different economic stages that have

existed during the past century. Others have talked more generally about the

movement from agrarian to industrial to the knowledge economy. Pink (2005)

describes the next step as moving from the knowledge age to the conceptual

age, while Friedman (2005) discusses many of these same shifts in terms of

‗Globalization 3.0‘. While neither of these terms has resonated with wider

audiences, there is no doubt that we are entering a post-knowledge worker

economic stage. The management models and systems from past stages

tend to be the first ones applied in new stages. These, after all, have been

what executives know, understand and have experienced. Past success

becomes a blinder for future achievements, because it is natural to think that

what worked once, should work again. It takes years and even decades for

new models and practices to emerge.

Most of our current management practices are mired in the past and based

on a set of assumptions that no longer exist. The sidebar opposite highlights

many of these differences. Consider this list and assess your own company‘s

position.

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Many companies are at a spot along this continuum with one foot in the past

and another in the future. Some of these factors may not be as important as

others, but it is becoming increasingly clear that old practices will not be

effective in a future that requires innovation, fast responses, horizontal

relationships, high engagement levels and optimum performance from assets

that are not ―owned‖ by the company. Perhaps this is why in this transition

period, 75 percent of change managements fail, less than 10 percent of

companies do a good job of implementing their own strategy, and the vast

majority of mergers and acquisitions fail to meet their objectives. New

mindsets and practices are needed for new times.

6.1. A PERSPECTIVE ON GLOBAL SCENARIO

―Today, the most profound thing is that a 14 year old in Romania or

Bangalore or Vietnam has all the information, all the tools, all the software

easily available to apply knowledge however they want.‖

Perhaps the biggest contributor to the talent management tipping point is the

new global marketplace. More than any single factor it has caused us to

consider how fast change can take place, and how firmly held beliefs are

wavering or are no longer valid. The world is a very different place than it was

even at the start of the century, barely six years ago.

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Consider the following examples:

Billions of people are new entrants into the world economy and entire nations

have skipped stages of economic growth to get there faster than anyone

could have anticipated.

The talented minds of foreign born nationals are returning to their home

country rather than contributing to the human capital of Western Europe and

the United States.

China is revamping its educational system to focus less on rote memorization

and more on creativity and innovation.

Ireland is the world‘s largest exporter of software.

The business incentives and infrastructure offered by many ‗developing

countries‘ are equal to or better than the environment in the so-called ‗richer

nations‘.

Three countries that excel in new scientific and technical talent are India,

China and Russia.

Talent pools, just like markets, exist all over the world and are no longer the

exclusive province of Western countries.

Microsoft‘s R&D center in Beijing is the best performing software research

unit in the corporation.

Outsourcing and off shoring are not just about cheaper wages and low cost

services, but also about access to talent. The companies that will win in this

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post-knowledge economy may not be those that were the most successful in

past stages.

6.2. THE IMPORTANCE OF SUSTANABILITY IN THE PHASE OF NEW

ERA

Several studies have concluded that many employees care deeply about

environmental and social responsibility and want to play a role in their

company‘s sustainability efforts. Companies can tap into this energy through

several means – including providing employees with sustainability-related

learning opportunities.

6.2.1. PERFORMANCE MANAGEMENT

How companies manage workforce performance matters when it comes to

carrying out Sustainability initiatives. Leaders must clearly communicate

expected behaviors to enable employees to spearhead such efforts. And they

must clarify what actions they will be measuring to evaluate employee

performance. Making sustainability a regular component in performance

management can help. For example, Novo Nordisk, the Denmark-based

healthcare company focused on combating diabetes, has integrated

sustainability-related metrics into a company wide balanced scorecard

(Morsing and Oswald, 2004)[1].Organizations can also link reward systems to

sustainability performance.

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6.2.2. EMPLOYEE ENGAGEMENT

When employees are engaged with their company‘s sustainability strategy,

they proactively identify, communicate and pursue opportunities to execute

the strategy. Companies can engage employees through numerous means,

ranging from inviting them to share ideas with senior management to giving

them opportunities to volunteer for local community-outreach programs.

6.3. RESHAPING THE BUSINESS LANDSCAPE

The sustainability imperative is reshaping the business landscape – and will

continue to do so. To become high performers in this landscape, companies

must constantly come up with new ways to demonstrate environmental and

social responsibility – driving innovation in business processes, management

practices and products and services. But even the best ideas for supporting

sustainability will fall flat unless a company‘s workforce can put them into

action. That calls for focused investments in talent. Firms must invest in

helping employees acquire and build the knowledge, skills and attitudes

required to carry out Sustainability-related initiatives and generate additional

fresh ideas. And they must tap into employees‘ desire to make a positive

difference in their organizations, communities and the world. The five levers –

organizational change, leadership development, employee learning,

Performance management and employee engagement can help. Today,

when companies are finding it increasingly difficult to grow, investing in talent

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to meet the sustainability imperative may be the most potent way to achieve

high performance.

6.4. EMERGENCE OF TALENT MANAGEMENT

Talent management is a term that emerged in the 1990's to incorporate

developments in Human Resources Management which placed more of an

emphasis on the management of human resources or talent. The term was

coined by David Watkins of Softscape[2] published in an article in 1998 [3];

however the connection between human resource development and

organizational effectiveness has been established since the 1970's [4]. Talent

management is part of the Evolution of Talent Measurement Technologies.

The issue with many companies today is that their organizations put

tremendous effort into attracting employees to their company, but spend little

time into retaining and developing talent. A talent management system must

be worked into the business strategy and implemented in daily processes

throughout the company as a whole. It cannot be left solely to the human

resources department to attract and retain employees, but rather must be

practiced at all levels of the organization. The business strategy must include

responsibilities for line managers to develop the skills of their immediate

subordinates. Divisions within the company should be openly sharing

information with other departments in order for employees to gain knowledge

of the overall organizational objectives.[5] Companies that focus on

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developing their talent integrate plans and processes to track and manage

their employee talent, including the following:

Sourcing, attracting, recruiting and on boarding qualified candidates with

competitive backgrounds

Managing and defining competitive salaries

Training and development opportunities

Performance management processes

Retention programs

Promotion and transitioning

The talent management strategy may be supported by technology such as

HRIS (HR Information Systems) or HRMS (HR Management Systems).

Modern techniques also use Competency-based management methodologies

to capture and utilize competencies appropriate to strategically drive an

organization's long term plans.

6.5. THE TIPPING POINT OF TALENT MANAGEMENT

Talent management is ready to be tipped. First, there is the growing amount

of empirical evidence that shows a clear relationship between excellent talent

practices and improved shareholder returns. Among the providers of this

research are McKinsey, Gallup, Collins, Bassi, Watson & Wyatt, Becker and

Huselid, and the Fortune Best Places to Work surveys.

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Second, there are the best practices from companies that truly believe that

talent is the essence of their success. Among these companies are GE, Dell,

P&G, HSBC, FedEx, Starbucks, Microsoft and Capital One, to name just a

few.Third there is the growing realization that talent issues are board level

issues. More investment analysts and company directors are demanding to

know about engagement levels, segmented turnover data, and the types of

developmental opportunities for top talent. CEOs are starting to spend 30

percent or more of their time on talent issues, and are being held accountable

for the strength of their talent pools. For instance, all companies registered in

Denmark will be required to include in their annual reports information about

customers, processes and human capital. A minimum of five measures for

each is required and comparisons with the previous two years must be

shown. Information for investors about intellectual capital both current and

future should occupy at least one-third of the report.

The confluence of both internal and external factors is causing a new science

of talent management to emerge and tip. This is very different from traditional

human resources concerns. While HR is more concerned with consistency,

compliance and treating everyone in the same fashion, talent management

recognizes that different people make different contributions to the enterprise,

and that top talent is the key to competitive differentiation. The seamless and

integrated functioning of the talent management wheel is what will drive

companies into a leadership position in the new, post-knowledge economy.

But not every company has a leader that is knowledgeable and passionate

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about sustainability. In such firms, these qualities must be developed. To that

end, in 2008 the European Association of Business in Society (EABIS) and

Ashridge Business School conducted research into the competencies that

leaders must develop to support their companies‘ sustainability efforts and

inspire employees to do so (Ashridge Business School, 2008). Analysis of the

survey and interview results led Ashridge and the EABIS to identify three

essential competencies that they term ‗‗context,‘‘ ‗‗complexity,‘‘ and

‗‗connectedness‘‘:

6.6. BUSINESS LEADERS MUST UNDERSTAND THE CHANGING

BUSINESS CONTEXT.

Senior executives need to grasp the business risks and opportunities

presented by environmental and social trends. Senior executives also require

specific skills to respond to this information including being able to factor

social and environmental trends into strategic decision making, capital-

expenditure decision making, brand development, horizon scanning, scenario

building and risk management (Ashridge Business School, 2008).

6.6.1. Complexity

To lead in the face of such complexity, senior executives need to be flexible,

to find fresh ways of solving problems, to learn quickly from mistakes and to

balance short- and long-term considerations. They must also understand the

interdependency of different players‘ actions (including local decisions‘ impact

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on seemingly distant players) and the ethical considerations informing

business decisions (Ashridge Business School, 2008).

6.6.2. Connectedness.

Effective leaders must understand the actors operating in the wider political

landscape and know how to build productive relationships with new kinds of

external partners who may include regulators, NGOs, leaders of local

communities and even competitors. Yet many leaders today are not trained to

engage with stakeholders outside their organization. They might receive

plenty of training in negotiation skills, for example, but not in effective

dialogue and partnership-building. To correct this situation, leaders must learn

to identify all stakeholders who can exert an influence on their organization, to

assess how the organization‘s decisions and actions in turn affect these

stakeholders (positively and negatively), to engage in effective dialogue and

to build partnerships with both internal and external stakeholders ( Ashridge

Business School, 2008).

6.6.3. Competencies and talent management

This term "talent management" is usually associated with competency-based

management. Talent management decisions are often driven by a set of

organizational core competencies as well as position-specific competencies.

The competency set may include knowledge, skills, experience, and personal

traits (demonstrated through defined behaviors). Older competency models

might also contain attributes that rarely predict success (e.g. education,

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tenure, and diversity factors that are illegal to consider in relation to job

performance in many countries, and unethical within organizations). New

techniques involve creating a competency for the organization that includes a

Competency dictionary to hold the competencies in order to build job

descriptions.

6.7. A CURRENT APPLICATION OF TALENT MANAGEMENT FOR

OPTIMIZING THE PERFORMANCE

A talent marketplace is an employee training and development strategy that is

set in place within an organization. It is found to be most beneficial for

companies where the most productive employees can pick and choose the

projects and assignments that are most ideal for the specific employee. An

ideal setting is where productivity is employee centric and tasks are described

as ―judgment-based work,‖ for example, in a law firm. The point of activating a

talent marketplace within a department is to harness and link individuals‘

particular skills (project management or extensive knowledge in a particular

field) with the task at hand. Examples of companies that implement the talent

marketplace strategy are American Express and IBM.

In current economic conditions, many companies have felt the need to cut

expenses. This should be the ideal environment to execute a talent

management system as a means of optimizing the performance of each

employee and the organization. However, within many companies the

concept of human capital management has just begun to develop. ―In fact,

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only 5 percent of organizations say they have a clear talent management

strategy and operational programs in place today.‖

6.7.1. Talent review

To develop a clear talent management strategy and to increase awareness of

available talent and successors, all organizations should conduct regular

Talent Review meetings to be prepared for a variety of business changes,

such as mergers, company growth, or a decrease in talent needs. In the

same way that all companies have regular meetings and reports regarding

their financial status and budgetary needs, the Talent Review meeting is

designed to review the current talent status and future successor needs in the

organization.

The Talent Review meeting is an important part of the overall talent

management process; it is designed to review the performance and career

potential of employees, to discuss possible vacancy risks of current

employees, to identify successors and top talent in the organization, and to

create development action plans to prepare employees for future roles in the

organization. "This is what talent management is all about — gathering

information about talent, analyzing their career interests and organizational

business needs, identifying top talent and successes, and developing these

individuals to reduce the risk of losing the best people and experiencing

extensive leadership gaps when turnover occurs."

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6.7.2. Employee performance management (EPM)

It encompasses a variety of HR processes (e.g., goal management,

performance appraisals, multi-rater/360 feedback, compensation

management, workforce & succession planning, development planning and

training.) When harnessed correctly in an enterprise they are used to help

employees understand their roles, strategic business objectives, expectations

in their day-to-day activities based on the business objectives and

performance success as viewed by the management, peers, customers, etc.

Assessment proves more valuable when it serves as a guide for

benchmarking alignment and performance against strategic business

objectives and employee developmental and training.

6.8. CRITICAL AREAS AND IMPORTANCE OF TALENT MANAGEMENT

The prime focus of talent management is enabling and developing people,

since the quality of an organization is determined by the people it employs

and has onboard. After hiring and deploying we may say that retaining and

nurturing talent is quintessential.

Talent management also known as human capital management is evolving as

a discipline that encompasses process right from hiring people to retaining

and developing the same. So it includes recruitment, selection, learning,

training and development, competency management, succession planning

etc. These are all critical processes that enable an organization to compete

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and stand out in the market place when managed well

Talent management is now looked upon as a critical HR activity

6.8.1. Talent War

Finding and retaining the best talent is the most difficult aspect of HR

management. HR survey consultancies are one in their view that

organizations globally are facing a dearth of talented employees and it‘s often

more difficult to retain them. Further research has also shown that there is

clear link between talent issues and overall productivity.

6.8.2. Technology and Talent Management

Technology is increasingly getting introduced into people development.

Online employee portals have become common place in organizations to

offer easy access to employees to various benefits and schemes. In addition

employees can also manage their careers through these portals and it also

helps organizations understand their employees better.

6.8.3. Promoting Talent internally

When there is a fit between hired employees abilities or skills and the

requirements of the organization. The next step is enabling learning and

development of the same so that he/she stays with the organization. This is

employee retention. An enabled or empowered means an empowered

organization. It is also of interest to organizations to know their skills

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inventories and then develop the right individual for succession planning

internally.

6.8.4. Population Worries Globally

World populations are either young or aging. For example, stats have it that

by 2050. 60% of Europe‘s working population will be over 60. On the other

hand a country like India can boast of a young population in the coming and

present times. Population demographics are thus a disturbing factor for

people managers. Researchers have predicted that demographic changes in

United States will lead to shortage of 10 million workers in the near future.

6.8.5. Talent Management to rescue HR

HR has been compelled to focus on qualitative aspects equally and even

more than quantitative aspects like the head count etc. Through talent

management more effort is now being laid on designing and maintaining

employee scorecards and employee surveys for ensuring that talent is

nurtured and grown perpetually.

6.8.6. Increase in Employer of Choice Initiatives

An organization‘s perceived value as an employer as helps improve its brand

value in the eyes of its consumer. Most importantly it helps it attract the right

talent.

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6.9. THE MAGIC FORMULA TO INCREASE THE PRODUCTIVITY AND

CAPABILITY

Talent Management is beneficial to both the organization and the employees.

The organization benefits from: Increased productivity and capability; a better

linkage between individuals' efforts and business goals; commitment of

valued employees; reduced turnover; increased bench strength and a better

fit between people's jobs and skills. Employees benefit from: Higher

motivation and commitment; career development; increased knowledge about

and contribution to company goals; sustained motivation and job satisfaction.

6.9.1. EFFECTIVE WAYS OF TALENT MANAGEMENT

1. Recognize talent

It is important to note employees what they do in their free time and find out

their interests. Try to discover their strengths and interests. Also, encourage

them to discover their own latent talents.

2. Attracting Talent

Good companies create a strong brand identity with their customers and then

deliver on that promise. Great employment brands do the same, with

quantifiable and qualitative results. As a result, the right people choose to join

the organization.

3. Selecting Talent

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Management should implement proven talent selection systems and tools to

create profiles of the right people based on the competencies of high

performers. It's not simply a matter of finding the "best and the brightest," it's

about creating the right fit - both for today and tomorrow.

4. Retaining Talent

In the current climate of change, it's critical to hold onto the key people. These

are the people who will lead the organization to future success, and y ou can't

afford to lose them. The cost of replacing a valued employee is enormous.

Organizations need to promote diversity and design strategies to retain

people, reward high performance and provide opportunities for development.

5. Managing Succession

Effective organizations anticipate the leadership and talent requirement to

succeed in the future. Leaders understand that it's critical to strengthen their

talent pool through succession planning, professional development, job

rotation and workforce planning. They need to identify potential talent and

groom it.

6. Change Organization Culture

"Why would a talented person choose to work in the current organization?" If

the organization wishes to substantially strengthen its talent pool, it should be

prepared to change things as fundamental as the business strategy, the

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organization structure, the culture and even the caliber of leaders in the

organization. A rightly managed talent turns out to be a Gold Mine. It will keep

supplying value to the organization. In turn, Management needs to realize its

worth, extract it, polish it and utilize it.

6.10. IMPACT OF TALENT MANAGEMENT

Talent is something, which is highly on demand. Eventually the term Talent

management has become very much popular, especially in today's

commercial world. Talent management is simply a process of recruitment of

talents, developing the skills of existing workforce, promoting and retaining

the employees, attracting highly talented and rated employees from other

companies etc. Human resources department of each and every company

practices talent management. Every organization needs talented persons in

different levels to enhance the efficiency of the company. In this globalize era

talented personals are having demand and are offered good remuneration.

For discharging specific tasks talented and work ethic specialists are needed.

In every field the case is same. It is not easy to find the right talent needed for

the organization, it takes a wholesome effort involving lot of human resource

to find the talents and recruit them.

For a successful organization team of talented dynamic executioners,

passionate leaders in right roles will make sure effective execution of

strategies and correction if needed as per the situation. That means talent

should be there in executive, middle and lower level of the Organization. But

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setting up and maintaining this kind of persons for longer periods is not an

easy task. Performance management is directly linked with talent

management. In every organization the challenges as well as strategies are

entirely different. Hence the focus is mainly on getting and connecting the

talent with the organizational set up as well as making sure that the person

can cope up with the organizational challenges and deliver the might. Senior

human resource executives are dealing with the talent management and it is

very important for companies, as there is practice of rival companies luring

away the talents. So motivation and retention of talents in an organization is a

real challenge for HR officials. With companies becoming global with

overseas acquisitions, keeping the upward growth will depend on cost

effectiveness, internal execution of strategies precisely with existing

workforce as well as integrating new talents. Talent management best

practices are competency based and some of the competencies are skills,

personal traits, experience as well as knowledge. Talent management is for

the optimization of the resources in the organization, henceforth achieving

good business results. Always there is chemistry between better talent in

workforce and better business outcome. Leaders are developed through the

talent management system. Top-level management including CEO and senior

leadership should support the efforts of human resource department for

developing talent pool. Line managers have a proactive role in talent

management. They are the ones who can spot talents within organization for

higher levels. Developing the talent within the organization is cost effective

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than really recruiting new ones in some cases and it can be termed as one of

the talent management practices

6.11. COMPONENTS OF ENGAGEMENT

In a traditional work environment, workers do as they are told and tailor their

work according to clear job descriptions (Frese, 2008). Current work

conditions, however, no longer follow that model. Instead, Frese suggested

that the modern-day organizational environment –characterized by global

pressures, intense customer demands, lower supervision, more technology,

and greater need for teamwork and communications – led to a ―shift in job

concept‖ (p. 68). Predictably, the image of an engaged and enthusiastic

worker who is willing to ―devote extra effort to innovation, cooperate with each

other, and effectively adapt to change‖ (Griffin, Parker, & Neal, 2008, p. 48)

has lately gained considerable popularity. Part of the recent enthusiasm with

employee engagement may have resulted from recent research findings

connecting the phenomenon to positive employee behaviors and

organizational outcomes. For instance, a 16-country survey conducted by the

consulting firm Towers Perrin (2008) reported positive connections between

engagement and the employee‘s intention to stay in the organization. Also, a

meta-analysis on engagement conducted by Harter, Schmidt, and Hayes

(2002) found significant correlations between engagement and customer

satisfaction, productivity, profit margins, employee turnover, and safety

records. In spite of the interest generated by engagement, however,

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academic research on the phenomenon is still relatively new, with much of

the current research still being provided by consulting firms such as the

Gallup Organization (Rich, 2006). The field still offers, therefore, significant

opportunities for academic research.

This section of the study will review relevant studies on engagement and

address

a) History, definitions, and components of engagement,

b) 35 differences between ―trait,‖ ―state,‖ and ―behavioral‖ engagement,

c) Differences between engagement and related terms such as involvement,

satisfaction, commitment, empowerment, and Csikszentmihalyi‘s ―flow‖

concept (Csikszentmihalyi, 1990), and

d) Organizational, job, and personal antecedents of engagement.

This will lead to a final discussion on personality, engagement, and the level

of ―fit‖ between the person and the environment. History, Definitions, and

Components of Engagement William Kahn (1990) tied the origins of

engagement to Goffman‘s (1961) role behavior theory. Role theory examines

individual behaviors as shaped by the ―demands and rules of others‖ (Biddle

& Thomas, 1966b, p. 4). Thus, role theorists believe that individuals must

conform to certain societal expectations and that these expectations relate to

the roles these individuals occupy. In this sense, people‘s behaviors can be

predicted from the analysis of their roles (Biddle & Thomas, 1966a). The term

―role‖ and other related terminology from role theory were borrowed from the

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theatrical world (Biddle & Thomas, 1966a). Indeed, role theorists used

dramatic ―scripts‖ as metaphors to understand social behavior. Later, William

Kahn (1990) suggested that individuals could follow their roles more or less

closely, attaching themselves to their roles or defending their own personal

identities from such roles. Kahn‘s definition of engagement was the

―harnessing of organization members‘ selves to their work roles‖ (Kahn, 1990,

p. 694). Kahn‘s ethnographic studies on camp counselors and architects

found that engagement was a changeable phenomenon, resulting from

―calibrations of self-in-role‖ (p. 694) which occurred at the physical,

cognitive, and emotional levels.

6.11.1. Physically engagement

Physically engaged employees means the channeling of one‘s physical

energies toward the completion of a certain task (Rich, 2006). Rich explained

that physical engagement ranges from 36 lethargy to vigorous involvement.

For instance, one of the participants in Kahn‘s (1990) study – a camp

counselor – reported ―just laying around‖ (p. 702) rather than performing her

actual duties. Another participant, an architect, removed himself physically

from the job by farming work to his colleagues.

6.11.2. Cognitively engagement

Cognitively engaged employees individuals are thoroughly absorbed by their

work (Rothbard,2001). Indeed, Rothbard explained that engaged individuals

are able to ignore competing distracters and intensely focus on the task at

hand. Cognitive disengagement, on the other hand, means a ―lack of attention

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toward one‘s work tasks‖ (Rich, 2006, p. 13). Interview data from Kahn‘s

(1990) study provided interesting examples of the contrast between cognitive

engagement and disengagement. For instance, while a ―cognitively vigilant‖

(Kahn, 1990, p. 700) scuba-diver at a summer camp was keenly aware of the

divers under his responsibility, a disengaged senior designer at an

architectural firm adopted an ―automatic, perfunctory approach marked by not

questioning others‘ decisions‖ (p. 702).

6.11.3. Emotional engagement

Emotionally engaged employees means a strong connection between one‘s

emotions, thoughts, and feelings and the job (Kahn, 1990) leading to feelings

of enthusiasm and pride (Rich, 2006). The opposite of emotional engagement

is ―emotional absence‖ (Kahn, 1990, p. 701), characterized by an emotional

detachment from others. In this sense, emotional engagement is the opposite

to the ―cynicism‖ component of burnout (Maslach, 2003). For instance, an

emotionally disengaged camp counselor reported being ―bland, superficial,

talking in flat, unemotional tones‖ (Kahn, 1990, p. 702).An alternative

conceptualization of engagement was offered by Dutch researcher Wilmar

Schaufeli (2002), who defined engagement as a ―positive, fulfilling, work-

related state of mind‖ 37 (Schaufeli et al., 2002, p. 74). Schaufeli‘s

engagement model included three major factors: vigor, dedication, and

absorption. Vigor, a factor defined as ―high levels of energy and mental

resilience‖ (Gonzalez-Roma et al., 2006, p. 74), relates to Kahn‘s physical

engagement. Vigorous individuals are willing to invest considerable energy in

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their work and strongly persist in the face of obstacles. Dedication is a set of

attitudes encompassing enthusiasm for one‘s work, pride, and inspiration

(Gonzalez-Roma et al., 2006). This definition of dedication ties the construct

to Kahn‘s (1990) emotional engagement. Finally, absorption means ―being

fully concentrated and deeply engrossed in one‘s work‖ (Gonzalez-Roma et

al., 2006, p. 75). A comparison between items designed to measure

absorption in Bakker and Schaufeli‘s Utrecht Work Engagement Scale or

UWES (Schaufeli & Bakker, 2003) and those included in the cognitive

engagement category of Bruce Rich‘s JES (2006) supports connections

between absorption and Kahn‘s cognitive engagement (as measured by

Rich). For instance, while the UWES absorption items include ―When I am

working I forget everything else around me‖ and ―I am immersed in my work‖

(p. 6), the JES cognitive items include ―at work, I focus a great deal of

attention on my job‖ and ―at work, I am absorbed by my job.‖ Because the

academic study of engagement is relatively recent, researchers are still

debating key conceptual issues such as whether engagement is permanent

or momentary, trait or state related, and whether it should reasonably be

differentiated from other related terminology. A summary of this debate will be

offered next.38 Trait, State, and Behavioral Engagement Macey and

Schneider (2008a) argued that engagement is an ―inclusive multidimensional

construct‖ (p. 76), which encompasses three distinct dimensions: trait

engagement, state engagement, and engagement-related behaviors. From a

practical standpoint, the differentiation between traits, states, and behaviors is

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important – practitioners may need to first identify the employees most likely

to become engaged in the first place, and then pinpoint the organizational

conditions that allow these engagement-prone employees to actually feel

engaged and behave in an engaged manner (Vosburgh, 2008). As previously

discussed in this chapter, a ―trait‖ is a ―disposition to behave‖ (Pervin, 1994, p.

108), which is likely to be relatively stable and cut across a variety of

situations. By definition, traits are not constrained by time. Psychological

―states‖ on the other hand, are time bound, including moods (more diffuse

states, without a specific ―causal‖ agent) and emotions (affective states

connected to specific situations or circumstances) (Heiss & Kurek, 2003).

Macey and Schneider (2008b) offered a good analysis of the differences

between engagement-related ―traits‖ and ―states.‖ Trait engagement is the

―inclination or orientation‖ (p.5) to experience the world in a positive

―engaged‖ manner. Macey and Schneider further connected trait engagement

with Csiksentmilalyi‘s ―autotelic personality‖ (Csikszentmihalyi & Nakamura,

2002) – a type of personality characterized by higher than average curiosity

and interest in life, strong persistence, and intrinsic motivation. In addition,

Macey and Schneider proposed that trait engagement is likely related to

positive affect, a ―proactive‖ personality type,and to the FFM ―consolidation‖

personality trait. Further research is needed to support Maceyand Schneider‘s

claims.39 Hirschfeld and Thomas (2008) partially agreed with Macey and

Schneider‘s (2008) trait engagement characterization. Hirschfeld and Thomas

suggested, however, that Macey and Schneider‘s engagement traits –

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autotelic personality, positive affect, proactivity, and consolidation – have in

common the ―propensity to exercise human agency‖ (Hirschfeld & Thomas,

2008, p. 63). Hirschfeld and Thomas then went on to define human agency as

the ―ability of people to exercise control over their own thoughts and

intentions‖ (p. 63) in order to actively shape circumstances and create

optimum conditions for goal achievement. In this sense, the engagement-

prone personality encompasses a combination of traits that leads a person to

set challenging goals, become involved in situations favoring such goals,

continuously hone her competencies, seek feedback, and persist in the face

of obstacles (Hirschfeld & Thomas, 2008).

Possible connections between engagement traits and the FFM will be

addressed in the ―personal antecedents of engagement‖ section of this

chapter. Engagement ―traits‖ may generate a disposition towards

engagement but do not fully account for engaged behaviors. In other words, a

person could have an engagement-prone personality and still not be engaged

or act in an engaged manner. A possible mediator between engaged traits

and behaviors is the ―state‖ of engagement, which is relatively durable and is

supported by both personal traits and organizational conditions (Macey &

Schneider, 2008b). Macey and Schneider further suggested that state

engagement includes attitudes of satisfaction, involvement, and commitment,

ultimately leading to high energy (physical engagement) and full

concentration (cognitive engagement). Finally, behavioral engagement is the

area that most interests organizational development practitioners and leaders

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(Newman & Harrison, 2008). Engaged behaviors are atypical or out of the

ordinary, involving significant initiative, proactivity, adaptability to changing

circumstances, 40 and role expansion (Macey & Schneider, 2008b). Newman

and Harrison (2008) suggested that behavioral engagement is the ―behavioral

provision of personal resources – time and energy into one‘s work role‖ (p.

34). These researchers further suggested that a focus on engagement

behaviors would allow researchers to avoid the confusion between real

engagement and antecedents of engagement such as traits (personality) and

attitudes (state of engagement).Predictably, researchers have not reached a

complete agreement on engagement definitions or even on the usefulness of

the construct. For instance, while Macey and Schneider (2008b) suggested

that engagement is a ―new blend of old wines‖ (p. 10), Newman and Harrison

(2008) argued that the construct is largely redundant and can be best

understood under the general umbrella of job attitudes. A useful differentiation

at this point, therefore, is that between engagement and related terms such

as job involvement, satisfaction, commitment, empowerment, and flow. Such

differentiation will be offered next.

6.12. ENGAGEMENT AND RELATED TERMINOLOGY

Reasonably, researchers wonder whether ―engagement‖ represents truly a

unique construct or simply a repackaged term (Saks, 2006). As a result,

researchers have attempted to differentiate engagement from various related

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concepts such as job involvement, job satisfaction, job commitment, job

empowerment and flow.

Job involvement is ―the degree to which a person is identified psychologically

with his work‖ (Lodahl & Kejner, 1965, p. 24). Lodahl (1965) suggested that

when a person‘s job involvement is high, the resulting work performance

positively impacts both self image and self esteem. Later, Kanungo (1982)

further differentiated work and job involvement – while work involvement

refers to the centrality of work for the person‘s life, job involvement is about a

particular job, and how well this job fulfills the employee‘s particular

needs.41Rich (2006) distinguished job involvement and engagement.

Involvement, Rich argued, precedes the physical expenditure of effort that

characterizes engagement. Later, Macey and Schneider (2008b) suggested

that job involvement is but one facet of the psychological state of

engagement. Other facets include satisfaction, commitment, and

empowerment. Job satisfaction is ―the pleasurable emotional state‖ (Locke,

1969, p. 10) that results from the employee‘s positive evaluation of his or her

job. Satisfied employees feel that their job related expectations have been

met and that the job will help them achieve their goals (Locke, 1969). Various

authors (Blizzard, 2004; Frese, 2008b; Macey & Schneider, 2008b; Rich,

2006) agreed that job satisfaction and engagement are not identical terms.

For instance, Rich (2006) argued that job satisfaction refers to the positive

emotions resulting from a job but does not necessary result in the investment

of positive energies on the job. Concurringly, Macey and Schneider (2008)

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criticized the use of job satisfaction measures to assess engagement, arguing

that such use would require ―an inferential leap‖ (p. 8). Likewise, Frese

(2008a) explained that while engagement requires persistence, energy,

absorption and enthusiasm, none of these components are a necessary

element of job satisfaction.

Job commitment is the degree to which employees are ―absorbed by their job‖

(Bashaw & Grant, 1994, p. 43). Bashaw and Grant (1994) differentiated job

and organizational commitment, explaining that one has to do with one‘s

attachment to a particular job, whereas the other measures the ―relative

strength‖ (p. 43) of an employee‘s identification with his organization. Later,

Macey and Schneider (2008) agreed that commitment is an important

engagement-related attitude, related to feelings of pride and the willingness to

spend energies in favor of the organization. Empowerment was defined by

Conger and Kanungo (1988) as a ―process of enhancing feelings of self-

efficacy‖ (p. 174). As per Conger and Kanungo‘s definition, empowerment is a

set of managerial processes that distribute power amongst organizational

members and thus ―encourage commitment, risk taking, and innovation‖

(Thomas & Velthouse, 1990, p. 667). Other researchers (Mathieu, Gilson, &

Ruddy, 2006), however, defined empowerment from the perspective of the

employee. Indeed, Mathieu et al.‘s four-dimensional model of empowerment

included a) competence and self efficacy, b) self determination or the freedom

to control one‘s job, c) the meaningfulness of the task, and d) the positive

impact of the task for the functioning of the greater organizational system.

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Macey and Schneider (2008) later suggested that when seen under those

four dimensions empowerment is strongly related to the state of engagement.

Finally, flow is a ―state of optimal experience‖ (Schaufeli et al., 2002, p. 75)

featuring total concentration, a loss of sense of time, and the enjoyment of an

activity for its own sake (Csikszentmihalyi & Nakamura, 2002). Flow is clearly

connected to engagement, as both experiences are characterized by intrinsic

motivation, profound satisfaction, and a keen sense of concentration

(Csikszentmihalyi & Nakamura, 2002) ―whereby time passes quickly‖

(Schaufeli & Bakker, 2004, p. 295). Schaufeli and Bakker, however, argued

that while engagement is a longer-term connection to work.

6.13. COMPETENCY FOR EFFECTIVE PERFORMANCE

The term ―competency‖ was first used in the managerial context in the research

conducted by Boyatzis (1982) in the late 1970s in the USA to identify the

characteristics which distinguish superior from average managerial

performance. Boyatzis (1982) adopted the term ―competency‖, plural

―competencies‖, which he described as an underlying characteristic of an

individual that is causally related to effective or superior performance in a job.

The study concluded that there was no single factor but a range of factors that

differentiated superior from average performers. These included personal

characteristics, experience, motives and other attributes. Following the definition

given by Hay Group (2001), for this study a competency is considered as a

measurable characteristic of a person that is related to effective performance in

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a specific job, organization or culture. These characteristics are defined in terms

of behaviors. Because competencies are behavioral, they can be developed.

6.14. IMPORTANCE IN IDENTIFYING THE COMPETENCY GAPS

It is important to identify which particular set of key individual competencies is

required for a business to achieve its strategic goals. Antonacopoulou and

FitzGerald (1996) state that there is a danger if organizations concentrate on

competencies of the past rather than on competencies of tomorrow. Hence,

competency framework should reflect an organization‘s current and future

needs. In this regard, competency management has an important contribution at

the organizational and individual levels as it ensures that individual

competencies are linked to strategies of an organization (Draganidis and

Mentzas, 2006; Homer, 2001). Equally vital is the ability to ―health-check‖ those

competencies on a regular basis (Homer, 2001). Hence, from the Management

development viewpoint, it is important to know whether managers possess the

required competencies to achieve an expert job performance. In this context,

literature suggests that when competency needs are considered in terms of

gaps, it allows for a better understanding of managerial performance (Agut et

al., 2003; Barber and Tietje, 2004; Scholes and Endacott, 2003). A discrepancy

or a gap arises when a competency an individual possesses is lower than what

is required for the expert job performance (Agut and Grau, 2002; Boydell and

Leary, 1996; Goldstein, 1991). Further, there are differences in the importance

of different competencies for performing a job. By taking into account

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individuals‘ perceptions of how important a specific competency is for

performing a particular job could avoid an unbalanced focus on less important

competencies (Hansson, 2001). Although a perceived gap could sometimes be

an expression of preference (Latham, 1988), such information is useful in

decision making. For instance, once competency gaps were identified and, if

necessary, an organization could decide to address those through appropriate

strategies such as training, job enrichment, job content innovation, job redesign,

enhancement of the organizational climate, etc. (Goldstein, 1991; Naquin and

Holton, 2003; Tharenou, 1991; Wright and Geroy, 1992).

6.15. MEASUREMENT ISSUES WITH THE COMPETENCY APPROACH

Although popularity of competency frameworks among practitioners increasing,

scientific community has regarded competency studies with some degree of

skepticism (Lievens et al., 2004). The validity of ―competencies‖ as measurable

constructs appears to be at the core of this controversy (Lawler, 1996;

Schippmann et al., 2000; Tett et al., 2000). Content validity means that the list of

competencies used for the study is a representative sample of the universe of

interest. Face validity means that the competencies are accurate and

appropriate as judged by their users. In this regard, Hayes et al. (2000) argue

that the lists of competencies will always be incomplete. They cite examples of

studies where managers have not been able to describe all the competencies

required for a job. Construct validity emphasizes the importance of operational

competencies so as to observe and measure (Markus et al., 2005). In criterion

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validity, the importance of measuring competencies accurately is emphasized.

However, the way competencies are operational and measure depend on how

those will be used. Competencies are usually assessed using three distinct

methodologies: self-evaluation that allows the assessment of the improvement

and/or decline of competencies over time; third-party evaluation that allows the

monitoring and evaluation of the evolution of individual learning/acquisition of

competencies; peer evaluation that allows the evaluation of the possession of

competencies as perceived by peers (Camuffo and Gerli, 2004; Graham and

Tarbell, 2006). However, the assessment of competencies is likely to suffer from

reliability problems, such as rater bias (Fletcher, 2001). Therefore, an accurate

measurement of competencies is a key issue (Markus et al., 2005).

In a rapidly changing work environment, increased focus on customer and rapid

response to problems and opportunities has made the manager a vital resource

in guiding and directing front-line workers to success (Hay Group, 2001). The

impact of outstanding managers on revenue and profit is well documented.

Therefore, in a continuously changing environment, for a sustained personal

development, an expansion of a person‘s capacity to be effective in managerial

roles becomes vital (Davis et al., 2004; Jackson et al., 2003; Tubbs and Schulz,

2006). In this regard, the competency approach marks a new development and

the importance given to competencies in the organizational context is continually

increasing (Matthewman, 1995). Competency frameworks are commonly used

at the organizational level to guide decision making; Lawler (1994, p. 6)

competency-based organizations are organizational systems in which the

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capabilities of individuals are the primary focus, which cause them to be

managed in a way that provides competitive advantage. Vertically, competency

framework is a tool to delineate individual and organizational competencies from

the mission and strategy of the organization. Horizontally, competency

framework can be used for different purposes in human resource management

(HRM), including selection, management development, career and succession

planning, and performance management (Rothwell and Lindholm, 1999;

Schippmann et al., 2000). Therefore, competencies are the common language,

which enable an organization to match its human resources against the

resources it needs (Antonacopoulou and FitzGerald, 1996; Harvey et al., 2000).

When capturing and capitalizing on individual capabilities, it is important to

understand whether managers working in different work environments require

different sets of competencies in order to satisfy the different job demands that

encounter or whether different job demands connected to different areas of

functional specialization could be satisfied by a common set of management

competencies. Though there is an enormous diversity in the scope of

competency studies, a few empirical research studies have been conducted on

management competency requirements for different functional areas. Findings

of such studies have indicated that the variations in functions and contexts of

managerial roles make a one-size-fits-all competency profile impractical (Barber

and Tietje, 2004; Hayes et al., 2000; McKenna, 2002). The identification of

competencies that match job requirements has become an issue in human

resource development (HRD) in any context.

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In many instances, a vague list of desirable competencies provided by

policymakers or advocated by scholars is used as a guide in making crucial

decisions on HRD programs. Further, some academic literature proposes that

competency needs should be identified in terms of gaps as a gap informs

whether there is a deficiency in a competency while reducing managers‘

subjectivity and preference in identifying managerial competency needs.

However, a few empirical studies have been conducted treating competency

needs as gaps (Agut et al., 2003; Barber and Tietje, 2004; Chen et al., 2005;

Hansson, 2001). Finally, a limited number of competency studies have been

conducted in Asia and in many cases those were confined to identify requisite

competencies for managers from a specific functional area, such as HRD (see-

Chen et al., 2005; Han et al., 2006; Zhu et al., 2000). Therefore, this research

aims to partially fill this lacuna in literature by investigating whether there is a set

of management competencies that should be possessed in IT industries of MNC

and Private sector to which they are attached to using quantitative methodology.

CIPD research over the last decade has repeatedly demonstrated the links

between the way people are managed and business performance, the most

recent being shaping the Future, a longitudinal research programme

investigating the drivers of sustainable organization performance In recent years

government skills policy has also started to focus on the importance of

leadership and management skills as it has become increasingly clear that steps

to improve supply and raise the skills of the workforce are, while extremely

important, not enough to drive productivity improvements on their own. The UK

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Commission for Employment and Skills has conducted significant research

exploring skills utilization and its impact on productivity and performance since

2008. This research has identified high-performance working as one way to

encourage better use of skills in the workplace. High-performance working

practices can be defined as a set of complementary working practices within

three areas:

High employee involvement practices: for example self-directed teams,

quality circles and sharing/access to company information.

HR practices: for example sophisticated recruitment processes, performance

appraisals, work redesign and mentoring.

Reward and commitment practices: For example various financial rewards,

family-friendly policies, job rotation and flexible hours. HPW emphasizes the

importance of the role of the line manager, as well as a range of issues that are

directly affected by line management behavior, including: employee learning and

development; their treatment; autonomy; and the quality of communication and

teamwork. All of these factors influence employee engagement and the extent to

which employees are prepared to the go the extra mile for the organization they

work for. In 2008, the Department for Business, Innovation and Skills (BIS)

commissioned David MacLeod and Nita Clarke to take an in-depth look at

employee engagement (one aspect of HPW) and to explore and report on its

potential benefits for organizations and employees. The review identified four

key enablers of employee engagement:

Leadership provides a strong strategic narrative which has widespread

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ownership and commitment from managers and employees at all levels.

Engaging managers are at the heart of this organizational culture – they

facilitate and empower rather than control or restrict their staff; they treat their

staff with appreciation and respect and show commitment to developing,

increasing and rewarding the capabilities of those they manage.

Voice: An effective and empowered employee voice – employees‘ views are

sought out; they are listened to and see that their opinions count and make a

difference.

Integrity: Behavior throughout the organization is consistent with stated values,

leading to trust and a sense of integrity. MacLeod‘s conclusions again highlight

the importance of line managers in supporting employee engagement; however

there is little research evidence that shines a light on the day-to-day

management behaviors that underpin employee engagement. This Research

Insight is designed to identify the specific management behaviors that line

managers need to show in order to enhance Management competencies for

enhancing employee engagement employee engagement in the workplace. The

research will also lead to the creation of practical guidance to help organizations

develop the core management skills with talent management strategies that

underpin enhanced employee engagement and sustainable organization

performance.

CHAPTER 7: INFORMATION TECHNOLOGY

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CHAPTER 7

INFORMATION TECHNOLOGY

Information technology is the acquisition, processing, storage and dissemination

of vocal, pictorial, textual and numerical information by a microelectronics-based

combination of computing and telecommunications. The term in its modern

sense first appeared in a 1958 article published in the Harward Business

Review in which authors Leavitt and Whistler commented that "the new

technology does not yet have a single established name. Call it information

technology (IT)." Some of the modern and emerging fields of Information

technology are next generation web technologies, bioinformatics, cloud

computing, global information systems, large scale Knowledge bases, etc.

Information technology (IT) is defined as the design, development,

implementation and management of computer-based information systems,

particularly software applications and computer hardware. Today, it has grown

to cover most aspects of computing and technology. The reason why it has

catapulted in importance is due to the improving accessibility, awareness and

utility of technology.

IT is the area of managing technology and spans wide variety of areas that

include but are not limited to things such as processes, Computer

software, information systems, computer hardware, programming languages,

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and data constructs. In short, anything that renders data, information or

perceived knowledge in any visual format whatsoever, via any multimedia

distribution mechanism, is considered part of the IT domain. IT provides

businesses with four sets of core services to help execute the business strategy:

business process automation, providing information, connecting with customers,

and productivity tools. It is a common fact that a country‘s IT potential is

paramount for its march towards global competitiveness, healthy GDP and

defense capabilities. IT professionals perform a variety of functions (IT

Disciplines/Competencies) that ranges from installing applications to designing

complex computer networks and information databases. A few of the duties that

IT professionals perform may include data management, networking,

engineering computer hardware, database and software design, as well as

management and administration of entire systems. Information technology is

starting to spread further than the conventional personal computer and network

technologies, and more into integrations of other technologies such as the use

of cell phones, televisions, automobiles, and more, which is increasing the

demand for such jobs.

IT professionals perform a variety of duties ranging from data management,

networking, engineering computer hardware, database and software design, to

the management and administration of entire systems. With the already high

penetration of conventional personal computer and network technology, coupled

with the growing convergence of information, communication and entertainment,

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the industry is now keenly focused on the integration with other technologies

such as mobile phones, automobiles and televisions etc, thereby increasing the

demand for such jobs. The largest firms globally include IBM, HP, Dell and

Microsoft.

In the recent past, the Accreditation Board for Engineering and Technology and

the Association for Computing Machinery have collaborated to form

accreditation and curriculum standard for degrees in Information Technology as

a distinct field of study as compared to Computer Science and Information

Systems today. SIGITE (Special Interest Group for IT Education) is the ACM

working group for defining these standards. The Worldwide IT services revenue

totaled $763 billion in 2009.[6]

7.1.TECHNOLOGICAL CAPACITY AND GROWTH

Based on a global inventory of the world's IT capacity, Hilbert and Lopez identify

the exponential pace of technological change (a kind of Moore's law): machines‘

application-specific capacity to compute information per capita has roughly

doubled every 14 months between 1986-2007; the per capita capacity of the

world‘s general-purpose computers has doubled every 18 months during the

same two decades; the global telecommunication capacity per capita doubled

every 34 months; the world‘s storage capacity per capita required roughly 40

months to double (every 3 years); and per capita broadcast information has

doubled roughly every 12.3 years. Between April 2000 and February 2011, the

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computer software and hardware sector received cumulative foreign direct

investment (FDI) of US$ 10,705 million, according to the Department of

Industrial Policy and Promotion.

The total investments of EMC Corporation, a leading global player of information

infrastructure solutions in India, will touch US$ 2 billion (over US$ 2.01 billion)

by 2014.Russian IT security software provider, Kaspersky Lab, will be investing

US$ 2 million in its India operations at Hyderabad during 2011.On the back of

40 per cent revenue growth, Cognizant will invest more than US$ 500 million till

2014 to expand its campuses to add over 8 million square feet to house over

55,000 employees. It will create additional software development and training

facilities in regions designated as special economic zones in Chennai, Pune,

Coimbatore and Kolkata. In order to integrate the learning experience for the

students, Globsyn Business School, would launch an online platform, e-

Globsyn, by July 2011 that would work as a virtual classroom environment for its

students, as well as facilitate them with other amenities. Chennai-based Polaris

Software Lab has announced that it is buying an 85 per cent stake in San

Francisco-based digital identity authentication services provider Iden-Trust for

US$ 20 million. The acquisition will mark Polaris' entry into the cloud computing

space for financial technology solutions, the company said in a filing to the

Bombay Stock Exchange.

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7.2. GOVERNMENT INITIATIVES : A KEY CATALYST FOR

INCREASED IT ADOPTION

Government sector is a key catalyst for increased IT adoption- through sectors

reforms that encourage IT acceptance, National e Governance Programmes

(NeGP) , and the Unique Identification Development Authority of India (UIDAI)

programme that creates large scale IT infrastructure and promotes corporate

participation. Certain crucial steps taken by the Indian government to propel the

sector growth are:

Constitution of the Technical Advisory Group for Unique Projects

(TAGUP) under the chairmanship of Nandan Nilekani. The Group would

develop IT infrastructure in five key areas, which includes the New

Pension System (NPS) and the Goods and Services Tax (GST)

Setting up the National Taskforce on Information Technology and

Software Development with the objective of framing a long term National

IT Policy for the country.

Enactment of the Information Technology Act, which provides a legal

framework to facilitate electronic commerce and electronic transactions.

Setting up of Software Technology Parks of India (STPIs) in 1991 for the

promotion of software exports from the country. There are currently 51

STPI centres where apart from exemption from customs duty available

for capital goods, there are also exemptions from service tax, excise duty,

and rebate for payment of Central Sales Tax.

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Plans to formulate Information Technology Investment Regions (ITIRs).

These regions would be endowed with excellent infrastructure and would

reap the benefits of co-siting, networking and greater efficiency through

use of common infrastructure and support services.

7.3. ROAD AHEAD : A SUNSHINE SECTORS OF THE INDIAN ECONOMY

The Indian information technology sector continues to be one of the sunshine

sectors of the Indian economy showing rapid growth and promise. According to

a report prepared by McKinsey for NASSCOM called 'Perspective 2020:

Transform Business, Transform India', the exports component of the Indian

industry is expected to reach US$ 175 billion in revenue by 2020. The domestic

component will contribute US$ 50 billion in revenue by 2020. Together, the

export and domestic markets are likely to bring in US$ 225 billion in revenue, as

new opportunities emerge in areas such as public sector and healthcare and as

geographies including Brazil, Russia, China and Japan opt for greater

outsourcing.

7.4. SUSTAINABLE GROWTH OF IT SECTOR IN INDIA

In India, it is important to make the distinction between IT and ITES (IT

enabled services). The latter refers to services delivered over telecom

networks/ Internet to a range of external business areas (Colloquially referred

to as KPO and BPO) and is treated elsewhere on this website (see ITES

industry overview). Hence, we shall focus on the IT industry here by limiting

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the discussion to electronics hardware manufacturing and software

development and services.

Despite the unprecedented global economic downturn, the Indian IT industry

has weathered the storm well, and will achieve sustainable growth going

forward. India is expected to witness an average 8% salary increase in 2010

and 50% of companies have strong hiring plans, according to a survey by

global HR consultancy Mercer, giving yet another indication of the high

confidence levels among the country‘s corporate houses after the economy

staged a faster-than-expected recovery from the slowdown. While the larger

players continue to lead growth, gradually increasing their share in the

industry aggregate, several high-performing small and medium enterprises

have also stood out. The strong demand for electronic hardware and software

in India has been fuelled by a variety of drivers including the high growth rate

of the economy, emergence of a vast domestic market catering to the new

generation of young consumers, a thriving middleclass populace with

increasing disposable incomes and a relatively low-cost work force having

advanced technical skills. Indeed, the Government has also identified growth

of this sector as a thrust area as there remains great expectation for

significant growth given the fairly low levels of penetration of technology

among the 1.1 billion population; There were only 60 million Internet users in

2009, 7 million DVD players and personal computers were sold in 2008-09,

and 11 million new mobile subscribers were added every month in the same

period. In this scenario there is now a big opportunity to step up the

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production to gain higher global share besides meeting the domestic

demands. The Indian IT sector has also built a strong reputation for its high

standards of software development ability, service quality and information

security in the foreign market- which has been acknowledged globally and

has helped enhance buyer confidence. The industry continues its drive to set

global benchmarks in quality and information security through a combination

of provider and industry-level initiatives and strengthening the overall

frameworks, creating greater awareness and facilitating wider adoption of

standards and best practices.

7.5. INDIAN IT SECTOR’S PERFORMANCE: CLUES FROM

ACCENTURE RESULTS

Indian information technology (IT) service companies will report results for

the April-June period in around two weeks‘ time. How are they likely to

perform? Accenture Plc, which reported results for its third quarter ended May

last week, provides some clues. Accenture is a management consulting,

technology services and outsourcing company, and competes with large

Indian IT firms for outsourcing projects. The company reported a strong

recovery with revenue growing by 8% in dollar terms both on a year-on-year

and a quarter-on-quarter basis. Revenue was boosted by the appreciation in

the dollar. But even adjusted for this, i.e. in local currency terms, growth stood

at 4%. According to a report by Morningstar Research Inc., this is after five

successive quarters of year -on-year revenue declines. The markets were

enthused by the results—especially the fact that the company grew across

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geographies and industries. Accenture‘s shares rose by 8% after the results

were announced. Does this mean that Indian IT companies, too, would report

strong results? The company gets around 42% of its revenue from

outsourcing and part of its consulting revenue is from technology consulting.

The outsourcing business grew by 3% in local currency terms y-o-y, lower

than the company average. There‘s little doubt that demand for outsourcing

has picked up and revenue of Indian IT firms are likely to get boosted by pent-

up demand. Growth in the near-term, therefore, will be strong. Even so,

Accenture‘s comments don‘t suggest an extremely positive environment as

far as IT outsourcing goes, and it remains to be seen if the strong growth in

the next couple of quarters will sustain. On the positive side, demand for

technology consulting is robust, with record order bookings for the second

consecutive quarter.

According to a report by IIFL Capital, the strong growth in the firm‘s consulting

practice points to an improvement in discretionary spending. Accenture‘s

growth was led by the Americas region, which grew by 8% y-o-y in local

currency. The EMEA (Europe, Middle East, or West Asia, and Africa) region,

which has traditionally contributed a larger proportion of revenue compared

with the Americas, reported flat revenue y-o-y. Among industries, financial

services led growth with a 7% increase in local currency terms. These points

to strong growth for Indian IT firms in the June quarter, since they get a

majority of their revenue from the Americas region and from the financial

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services sector. Unfortunately, all this and more is priced into the shares of

Indian IT firms, which trade at around 24 times trail.

7.6. A STUDY OF THE PERFORMANCE OF THE INDIAN IT SECTOR

The Electronics industry in India is poised at a stage ―which taken at the

flood‖ could ―lead on to fortune.‖ For this the growth of the sector has to be

sustainable – which means that the resource capital (natural resources,

human, and finance) required has to be nurtured and maintained. The

Electronics Industry has emerged as the fastest growing segment of Indian

industry both in terms of production and exports. During the Eighth Plan

(1992-97), the electronics industry achieved a cumulative annual growth of

20% in production and over 40% in exports. The targeted growth in

production and exports at the end of the Ninth Plan (1997-2002) is 37% and

52% respectively. The overall production base of the Indian electronics

industry is widely distributed across various segments. There are more than

3500 units engaged in electronics production which include about 600 large /

medium units in the organized private sector and about 2900 units in the

small-scale sector. The total direct manpower employed in the Indian

electronics industry is about 5,00,000. Traditionally considered and

categorized as a clean, non-polluting sector, it is increasingly becoming clear

that this rapidly expanding sector is polluting and has significant environment,

health and safety issues. The electronics industry is very vast and diverse

and comprises the supply side i.e. hardware such as consumer electronics,

industrial electronics, computers, communication and broadcast equipment,

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strategic (defense) electronics, components and the demand. The

Government of India's planning exercise is carried out through development

and implementation of a Plan every five years called the Five-Year Plan.

Since the origin of this planning exercise nine plans have been developed.

The country in the Ninth Five Year Plan (also called Ninth Plan) developed in

1997 for the period 1997-2002. A National Level Planning Commission at the

Centre carries out the planning exercise.

Informatics applications in all economic sectors, information service

industries, electronic publishing, broadcasting, and management information

systems. The Consumer Electronics sector has been a leading catalyst for

Indian electronics industry, contributing about 37% of the total electronics

hardware production. India also has a well - developed electronic components

industry catering to the requirements of consumer electronics, telecom, and

defense and information technology. The production of Electronic

Components in the year 1998-99 represented a growth of 14% over 1997-98.

In the last decade the ―visible‖ part of the electronics industry has been the

Information Technology (IT) industry. The IT industry is constituted by the

hardware ―backbone‖ from the electronics industry and a very meteorically

rising segment - the software industry. In the last 5-6 years the sector has

seen a tremendous growth and is increasingly occupying a niche position in

the global IT marketplace. Some interesting insights into the IT industry

indicate the significant impact the industry has and is likely to have on the

economic and social structure of the country.

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The IT industry clocked a turnover of US $ 9.6 Billion in 1999-2000 a growth

of over 30% over 1998-99.

The sales of personal computers in 1999-2000 were 1.5 Million Units and the

market showed the growth at 50% per annum.

The Indian computer industry has been recording an impressive annual

growth rate of over 30% during the past few years. This trend showed a

continuous progress for the next three to five years.

The IT industry has the potential to become an engine of growth for all

sectors of the economy. In order to ensure that this economic growth is

consistent, its sustainability must be ensured. The present report proposes to

examine the various issues – environmental, health, safety, labor and

community related – that need to be considered to ensure this sustainability.

The IT industry is very diverse in its operations and the associated

environmental and social issues are heterogeneous. To lend focus to the

present study, the central theme selected for this report is the computer

industry, given the phenomenal and far-reaching economic and social impact

that it has had and is likely to continue to have in India. For the purpose of

this report therefore the generic term ―IT industry‖ will be used while

discussing the computer industry. Where it is felt necessary, for the sake of

completeness, relevant sub-sectors of the IT industry will be included in the

discussion. The IT industry is a very rapidly expanding sector of the

electronics industry. The environmental, health, safety and social issues

associated with the IT industry in India, including the relevant existing and

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emerging policies and regulatory framework. Based on this understanding,

recommendations were derived for policy and governance to ensure

accountability and environmental and social responsibility of the sector thus

enabling sustainable growth of this industry.

7.7. BACKGROUND OF THE IT INDUSTRY IN TERMS OF ITS

EVOLUTION, STRUCTURE, GROWTH: SIGNIFICANCE TO THE

INDIAN ECONOMY.

Given the spectacular growth of the industry presents a situation analysis of

the environmental, health, and labor issues associated with the industry and

how they are managed today.

7.7.1. Evolution of the IT industry

The global perception of the IT industry in India has typically been ―software.‖

Interestingly, a review of the industry statistics show that in 1990-91,

hardware accounted for nearly 50% of total IT revenues while software's

share was 22%. The scenario changed by 1994-95, with hardware share

falling to 38% and software's share rising to 41%. This shift in the IT industry

began with liberalization, and the opening up of Indian markets together with

which there was a change in India‘s import policies vis-à-vis hardware leading

to substitution of domestically produced hardware by imports. Since the early

1990s, the software industry has been growing at a compound annual growth

rate of over 46%. Taking cognizance of the growth of the IT industry (with a

presence of over 1,000 Indian and Multinational players)1 and the increasing

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dependency on imports for supportive hardware, the Government of India has

set forth policy initiatives to provide an impetus to the growth of the hardware

sector (both domestic and export), in its recent Annual Budget (2000-2001).

7.7.2. From Nehru to the 1980s

To understand the evolution of the IT industry it would be interesting to trace

its development from Nehru‘s times. In the post independence era, India was

geared towards a program of self-reliance and internalization of production.

Leaders like Nehru envisaged a move from labor intensive industrialization to

more capital- intensive and mechanized systems of production. Associated

with this was the development of the public sector as the predominant

provider of utilities and basic infrastructure. Industrial research in hardware

and software R&D did not receive government support. Rather, fundamental

research was almost exclusively restricted to state run laboratories and

defense establishments, with limited diffusion of results into the market. The

electronics industry, till the mid-60s was monopolized by select multinational

companies such as IBM and ICL and until the mid-1970s they were the

largest providers of hardware in India.The Department of Electronics,

implemented policies to foster the hardware industry. High import duties,

quotas and licensing requirements were used to protect it from foreign

competition. Greater restrictions were imposed on the hardware industry in

the late 1970s and early 1980s to protect the domestic hardware industry

further from sale of second hand hardware bought for training professionals in

India. This did not strengthen the industry. It however led to significant

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benefits for the public sector organization Electronics Corporation of India

Limited (ECIL), which was the first electronics manufacturing and R&D

establishment in India. The objective of establishing ECIL was for it to be the

sole supplier of indigenously manufactured mini computers, a monopoly

strengthened by Government policies that resisted the entry of private or

transnational entry into this market. The result was a poor market, with low

supply and highly priced products (with a cost differential of at least five times

vis-à-vis contemporary imported products!). A ―panel on minicomputers‖

instituted in 1972 asserted that minicomputer manufacture could indeed be

achieved without foreign collaboration. This seems to have resulted in

―curtailing the ability of Indian firms to join technology or marketing ventures

with foreign collaborators in order to disperse high R&D costs or high

investments in overseas marketing.‖ Technology development remained

stunted, to the extent that, by the mid 70s, ―.India‘s technology gap was

estimated at least eight years‖, though this was subsequently narrowed by

renewed thrust toward technology development. Legislation ―proved

inadequate to establish technological capabilities in entrant firms till 1977.

While a restrictive industrial policy curbed access to technology, slowed

market penetration and virtually eliminated competition. Indian products

managed to achieve compatibility with global component standardization in

the 1980s. In fact until the mid-1980s, India‘s development strategy was

characterized by import substitution policies aimed at nurturing the domestic

industry, including computer hardware and software. These included

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―quantitative restrictions and high tariffs on imports, elaborate import licensing

procedures, export subsidies, controls on foreign direct investment and an

overvalued exchange rate‖ In fact in 1984 there were only a few strong

domestic computer companies including HCL and Wipro. It was also during

the mid to late 1980s that computer firms shifted focus from mainframe

computers (the mainstay of multinational corporations) to personal

computers.

In the 1990s, the market thrived through import and local assembly, of

components manufactured offshore. The old anthem of self-reliance through

internalization of production has now been replaced by a focus on the

―Technological development of strategic industry‖ The much criticized

industrial policies are today credited with the development of the human

resources necessary for the growth of the IT sector. An interesting point to

note here are that the protectionist policies towards the domestic hardware

industry forced computer firms to shift focus from mainframes towards

producing and using personal computers (PCs), as discussed above. This led

to a generation of software engineers who gained experience in programming

for PCs. The high skill levels however have focused primarily on the software

sector of the IT industry.

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7.7.3. Locational preferences of the IT industry

Although Bangalore is today considered India‘s ―Silicon City‖ the industry

originated in Mumbai as described in a study by Heeks4. The business district

of Nariman Point Mumbai was the site of origin of the Indian software industry

in the late 1970s. Rise in prices and commute times led to the industry

moving to the Santa Cruz Electronics Export Processing Zone (SEEPZ) in the

city‘s western suburbs. Till the mid-1980s Mumbai continued to be the centre

of the software industry. The Indian software industry, started in Mumbai, is

thus more than twenty years old, but it was only in the mid-1980s that India‘s

presence in the global software services market became visible.

During this period, the industry migrated to Bangalore due to a decline in

availability of technically skilled labor (the vital element in this sector). This

was triggered by high prices, poor quality of life and the overseas brain drain

from Mumbai. Bangalore provided the industry (both local firms and foreign

investors) abundant technically skilled labor drawn from its research

laboratories and technical educational institutions such as Indian Institute of

Science, Indian Institute of Management and the various engineering

colleges. Electronics industry (particularly defense electronics) has had, since

Nehru‘s times, a strong presence in Bangalore for strategic reasons. Public

sector firms such as Bharat Electricals Limited became key sources of both IT

industry employees and entrepreneurs.

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The superior quality of life in terms of weather, dust free environment, better

infrastructure in the mid 1980s (water and power) the social fabric, combined

with a comparative absence of communal and labor relations strife (that

troubled Mumbai) led to movement of IT companies and workers to

Bangalore.

Probably the turning point in the history of the IT industry‘s locational decision

in India was the establishment of the US company Texas Instruments' (TI)

design centre in Bangalore. TI established its subsidiary in Bangalore in 1986

and was the first offshore software facility using high-speed satellite links for

communication. This event led to what Heeks4 describes as a ―snowball

effect‖ and Bangalore became an IT software hub with Indian and

International companies clustering in and around Bangalore. Today, most of

the top international computer and software companies (HP, Digital, Compaq,

IBM, Intel etc.) have wholly owned subsidiaries or joint ventures with Indian

companies based in Bangalore. The large Indian companies such as Infosys,

Wipro, etc. are also headquartered in Bangalore.

An emerging IT centre and a strong contender to Bangalore‘s premier

position is the city of Hyderabad.

7.7.4 Indian IT industry in the 1990s

The IT industry with a turnover of US $ 9.6 Billion [Hardware Domestic: US $

4 Billion; Software Exports: US $ 3.9 Billion (Over 10% of Total Indian

Exports) and Software Domestic: US $ 1.7 Billion] had a tremendous impact

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on every facet of India‘s development - the Indian economy, commerce, the

education system, and the direction of growth of technical skills. India crossed

the one million mark in computer installations with a new computer being

installed every two minutes in 1998. At this growth rate, India, which had only

100 computers before 1970 (many of them being mainframe computers), was

predicted to have five million computers (a large number of them likely to be

personal computers) before 20005. A more recent survey by the National

Association of Software and Service Companies (NASSCOM)6 estimates that

the installed base of personal computers in India would zoom from 4.3 million

as on March 31st 2000 to 20 million by 20087 while the number of Internet

users would expand to 100 million by 2008 from the current base of 4 million.

The turnover of the Indian software industry rose from US$ 10 million in 1985,

to approximately $835 million in 1995, according to estimates made by

NASSCOM. Although these figures are low by global standards, the industry's

average annual rate of growth between 1992 and 1997 has been 46 %, with

exports growing much faster than domestic sales.

In 1998-99, the software industry in India was worth US$ 3.9 billion, and if the

value of in-house development that takes place at many large commercial /

corporate end-users is added in, then the total software industry is close to

US $ 4.6 billion. Ten years ago, the software industry in India was not more

than US $ 150 million8.

In 1998-99, more than 203 out of the Fortune 1000, that‘s nearly one in five,

outsourced their software requirements to India. US customers bought almost

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61% of the software that Indian companies exported to 91 countries around

the world. A recent World Bank Survey ranked India as number one in the

preference list of US vendors for offshore software development. The

Government has identified this as a thrust sector, both for export as well as

for the domestic market, with such proactive measures as the Amendment of

Indian Copyright Act, reduction of import duty on hardware in subsequent

budgets, incentive schemes like software parks, etc. Despite these high

growth rates, India‘s share in the world software product market is still very

low, but India still enjoys an advantage over many other nations in software

development, services and exports. This is due to the fact that India

possesses the world‘s second largest pool of scientific manpower which is

also English speaking. Coupled with the fact that the quality of Indian

software is extremely good with relatively low cost, it provides India a very

good opportunity in the world market.

The Indian computer hardware industry grew from USD 1370 million in 1995-

96 to an estimated USD 1912 million during 1996-97 reflecting an annual

growth of 40%. This industry is targeted to reach USD 7,830 million by 2001.

This meteoric rise and growth of the IT industry has spawned ―Silicon‖ metros

such as Bangalore, Hyderabad, Mumbai, Pune, Chennai, and

Thiruvananthapuram. This has had significant socio-economic impacts. In

addition, smaller cities like Bhubaneshwar in the East, Pondicherry in the

South and Girgaun and Perwanoo in the North .Government of India has

identified the IT industry (specifically software) as its thrust area; has created

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a new ministry at the Centre – the Ministry of Information and Technology

with a Cabinet Minister and, has released the IT Policy which provides

tremendous incentives to develop the industry. IT policies are also being

drafted at the State level by Andhra Pradesh, Karnataka, Goa, Orissa,

Maharashtra, Gujarat, Tamil Nadu, West Bengal, Kerala, Uttar Pradesh,

Punjab, Delhi, Rajasthan and Himachal Pradesh. Some States viz.,

Karnataka and Andhra Pradesh in Southern India, Maharashtra and

Rajasthan in Western India have also established independent Department of

Information Technology.

7.7.5. Structure, Focus and Growth of the IT industry

An overview of the Indian IT Industry by Manufacturers' Association of

Information Technology (MAIT) presented the following structure:

A schematic presentation of the structure of the IT industry For the purpose of

this report, the Indian IT industry is broadly categorized into software and

hardware, While software encompasses products for a whole host of

applications, hardware as described above cannot be compartmentalized to

include only computing hardware. Related sectors such as telecom hardware,

manufacture of Printed Circuit Boards, Semi-conductors, and other electronic

components are also encompassed in structure of the IT hardware industry.

In this report while greater focus is on the computer hardware and software

sectors of the IT industry, it is proposed to briefly touch upon, where relevant,

related sectors such as the manufacture of printed circuit boards, and

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accessories such as power systems, and power cords, given the

environmental, health and safety issues associated with their manufacturing

operations. The focus areas of the Indian IT industry as described by the

Manufacturers‘ Association for Information Technology (MAIT) include: (I)

software - exports and domestic (II) hardware - domestic and (III)

maintenance services of hardware and software and other associated

services. Hardware: Computers (PCs and notebooks), servers,

motherboards, power supplies, monitors, keyboards, printers, networking

products and add-on cards. Software: Offshore development, products and

technical support. Training: Training material, multimedia computer based

tools (CBTs).Service: Maintenance, IT enabled Services

7.7.6. Structure of the Indian IT Industry

The IT industry‘s contribution to the Indian economy has been phenomenal in

the last few years. Exports of the IT industry grew at the rate of 36% (in rupee

terms) in 1999-2000. The sector thus contributed 15% to the country‘s export

earnings during the last (1999-2000) fiscal year vis-à-vis 12.4% in 1998-99.

100% growth was seen in computer hardware exports in 1999-2000. India

exported software and services worth INR 173.00 billion thereby registering a

growth of over 38% in rupee terms. The software industry also constitutes

around 35% of the Indian exports and 7.5% of the GDP. The growth of the

Indian IT industry over the last five years has grown by over 300%. The

production of the software industry is above US$ 5.6 Billion and that of the

hardware industry and related services industry is approx. US$ 3.5 Billion in

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1999-2000. Major portion of the software production (US$ 3.5 Billion) was

exported in 1999-2000. Hardware exports are not significant15.In India, IT

spending as a percentage to GDP is currently less than 1% compared to the

USA, where the figure is more than 3.5%. However, with Government of

India‘s resolve to increase IT spending - it is predicted that by 2003, India‘s IT

spending could be 2.5% of its GDP15. Government has conventionally been

recognized a key driver of domestic IT demand in India and even around the

world. For example, in USA, about 23% of total domestic IT spending is

derived from government and public sector units. However, in the year1998-

99, in India, Government spending constituted more than 28% of total IT

spending.

7.7.7. Growth of the Indian IT industry from 1994-95 to 1999-2000

The fiscal year 1998-99 was characterized by the Indian economy going

through its worst phase (% growth of GDP was 5.8% in 1998-99 vis-à-vis

7.8% in 1996-97); industrial growth reached a low (index of industrial

production was 4% in 1998-99 dropping from 6.6% in 1997-98); exports

growth declined considerably over the previous year registering –1.1% in

1998-99 from 1.6% in 1997-98. The IT industry however showed only a

marginal fall in the annual growth rate from 18% in 1997-98 to 17.8% in 1998-

99 indicating the sustaining power of the industry. Till almost 1995, the bulk of

Indian software exports have been in the form of professional services with

majority of software exports being classified as ‗‗projects‘‘ or ‗‗professional

services‘‘. Studies showed that in 1997-98, 95% of the exports from India

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were in the form of software services5. Even today the Indian software

industry is very much a provider of professional software services, where

custom services are the primary function. India‘s competitive advantage in the

software business has been its cost-effectiveness, world-class quality, high

reliability, and rapid delivery. Of the top 300 software companies 145 have

ISO 9001 and 70 are in the pipeline; 41 companies are SEI-CMM certified

and of the 21 companies world-wide with Level 5, thirteen are in India.

7.8. TRENDS IN THE INDIAN SOFTWARE INDUSTRY

This competitive advantage was responsible for India being one of the earliest

players in the global software market. The software outsourcing

arrangements in the early 70‘s required import of programmers to work on the

client site in the US on a regularly billed basis since the American firms did

not want to risk outsourcing higher in the value chain activities like design3.

This was also triggered by the severe shortage in the supply of programmers

and software developers in the American software industry. This practice

called ―body shopping‖ though still prevalent, is slowing down. In 1988, the

percentage of on-site software development was almost as high as 90%.

Body-shopping or on-site services have declined significantly but they still

account for over 60% of industry revenues. Around the late 1980s global

markets (primarily the US) began to recognize that there were possibilities

available for offshore14 software development in India. Leading multinational

IT companies like Texas Instruments set up offshore software development

centers and R&D laboratories. Over the last few years HP, IBM, Intel, Apple,

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SUN, Oracle, Microsoft and many other US companies have set up offshore

software development centers where software teams in India and their US

counterparts work in close conjunction on various aspects of software

development. Not only cost but also productivity, quality and technology

governed these decisions. Recently however, the shift towards off shore

project development has been more marked. This has also begun to include

offshore package development. The offshore component is expected to

increase further with the improvement in infrastructure, communications

services, liberalization in economic policy and because of visa restrictions in

the United States and Europe. During 1999-2000, the offshore component

was expected to increase to about 45% of total software exports.

An examination of the type of activities in the software industry shows a

distinct difference between the domestic and export market. A segment-wise

break-up of the activities in the domestic and export market for the year 1998-

9915. 45% of software exports are in the category professional services and

35% in the area of projects (consultancy). Products and packages form a very

small segment of the export market. As the PC revolution spreads there

would be a greater demand for packages and products that can be bought off

the shelf. It is therefore important for the sustainability of the Indian software

industry to focus on products and packages for the export market as well. A

survey of the software industry in 1997-98, by NASSCOM, indicated that in

general the developed Nations have lower rates of piracy vis-à-vis the

developing nations. However, in absolute terms the level of piracy in software

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in the developed countries will be higher because of the larger size of the

computer market.

In the Asia-Pacific region revenue losses from software piracy were estimated

at US$ 3.7 billion in 1996 out of which Japan's contributions was US$1.2

billion. Vietnam and Indonesia had the highest piracy rate at 99% and 97%

respectively followed by China at 96% and Korea at 70%. India was in a

better position with a piracy rate at 60%. Piracy rate is defined as the amount

of software pirated as a percentage of total software installed in each country.

The piracy estimate is arrived at by taking the difference between software

application installed (demand) and software applications legally shipped

(supply).

According to a recent analysis15 of the sector by the management consulting

company McKinsey & Co., India is best positioned to offer competitive cross-

border IT services and enterprise IT solutions scoring high on multiple

parameters of vendor sophistication as well as people sophistication.

A potentially high growth area for the Indian IT industry is IT enabled services.

IT enabled services do not include remote production or manufacturing units;

the local branches of global businesses; or businesses on the Internet.

Companies, such as Bechtel, GE Capital, British Airways and many others

are already benefiting from IT-enabled services provided from India. Bechtel

has set up its own engineering design subsidiary in New Delhi. Over 500

employees in this subsidiary provide engineering design services to Bechtel

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customers over telecom and data networks. The benefits for Bechtel are

twofold: (I) the company‘s transaction and salary costs are greatly reduced;

and (II) it can now cover customers in different time zones. Other

organizations obtaining IT-enabled services are US Hospitals, which obtain

medical transcriptions services from Bangalore, the software technology park

in Thiruvananthapuram etc.

Government of India is providing extensive support to facilitate supportive

infrastructure for proliferation of IT Enabled Services throughout the country.

In fact, stress is being laid on developing suitable infrastructure in ‗non-

software‘ cities. Industry observers have noted that hi-tech industries flourish

essentially in the rural hinterland adjacent to the cities with modern telecom

and communication infrastructure and top class hi-tech educational/research

institute. The state of Andhra Pradesh was one of the first States to announce

a special policy for IT Enabled Services industries. Among other incentives,

the State Government has provided land at concessional rates. The States of

Karnataka, Tamil Nadu, Maharashtra, Rajasthan, Goa, Gujarat and Orissa

also have announced special fiscal and policy incentives to promote IT

enabled services.

7.9. MARKET FOR THE INDIAN SOFTWARE INDUSTRY

Export of Indian software, until the mid-1970s was mainly to Eastern Europe.

In the early 1980s the scenario changed with the United States taking over as

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the main export market with 75% of the Indian exports geared to that market.

This was because of

(i) the sheer size of the United States market for software, which is

much larger than any other market, as well as

(ii) the long history of Indian engineers and computer personnel

working in the United States. Some of them came back to India to

set up their own companies but maintained their contacts in the

United States and were able to use these to penetrate the market.

Indians who worked for large American IT multinationals also

played a role in attracting attention to the software development

work that was being done in India and to the level of skill and

expertise. Furthermore, India enjoys an advantage in English, the

main language used in the development of software. The United

States continues to be the main export market with 60% total

software exports from India. Market opportunities in Japan, South

Africa, Canada, France and Middle East were discovered. Efforts

were made in 1996-97 to penetrate the Japanese and European

market. This was through (i) formation of a consortium of software

companies to Japan and (ii) a Software Services Support &

Education Centre (3SE), in Bangalore by the European

Commission and the Indian Government to promote software

ventures and projects between European and Indian companies.

NASSCOM states that the six OECD countries (U.S.A, Japan, U.K.,

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Germany, France and Italy) together have almost 71% of the

market share of the worldwide software market and India‘s exports

to these countries is also almost 79% of its total software exports.

7.10. THE FUTURE OF THE INDIAN SOFTWARE INDUSTRY

As on 31 March 1999, the software industry in India employed more than

250,000 people and continues to be amongst the fastest growing sectors in

the Indian economy. NASSCOM‘s study, of the software industry does not

indicate any slowdown in the industry. The industry was estimated to grow by

more than 50% during 1999-2000. The study indicates that due to increased

government spending towards IT in the domestic market, as well as increase

in sale of PCs, the domestic software market will fetch revenue in 2000-2001

which would be almost a record 50% increase in the domestic market.

Predictions and projections for the future of the software industry are very

optimistic. It is projected that during the year 2001-02, software industry in

India would be close to Rs 55,500 crore. At current level of dollar-rupee

parity, this would translate to almost US$ 13 billion industry in that year. On

the other hand, it is predicted that exports will continue to grow in 2000-2001

with focus on E-Commerce, IT Enabled Service, Euro and ERP. Exports

during 2000-2001 are expected to continue to grow by almost 50%.

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7.11. POLICY INITIATIVES FOR THE GROWTH OF THE IT INDUSTRY

Policy has played a very important role in the development of the IT industry.

The early protectionist policies gave way to liberalization policies, which

opened markets and led to growth, both domestic and international, of the

Indian IT industry. A turning point in the policy framework has now emerged

with India signing the WTO IT agreement (ITA). According to India‘s

commitment on the ITA, by 2003 no duty will be charged on imports i.e., a

zero duty regime. Given this scenario, some of the significant policy initiatives

made by the Government of India, to achieve this Commitment and to ensure

sustainability of the Indian IT industry, are discussed below.

7.11.1. Creation of a Ministry of Information Technology

The newly formed Ministry of Information Technology, Government of India

will provide direction to the growth of the IT industry as it is responsible for the

national development of Electronics and Information Technology (IT) industry

and promoting applications of Electronics and Information Technology in the

country. Its mandate is to develop the Indian Electronics and Information

Technology Industry as a major global player and to bring the benefits of

Initiatives underway by Ministry of Information Technology (MIT)

Aside from the IT Action Plan which is yet to be implemented, some policy

initiatives made by the Ministry of Information Technology (MIT) are already

underway to promote growth of the IT industry. These include: Industrial

licensing and clearance procedures: Industrial licensing has been virtually

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abolished in the electronics sector except for manufacturing electronic

aerospace and defense equipment. There is no reservation for public sector

enterprises in the electronics industry and private sector investment is

welcome in every area.

7.12. INTELLECTUAL PROPERTY AND “BRAIN DRAIN”

Intellectual property in the form of technically skilled, highly qualified and

competent manpower is India's competitive advantage in the IT industry. In

1999 the IT industry as a whole had 300,000 technical and managerial

personnel. Figures for the software industry alone in 1998 were about

200,000 people16 up from 140,000 in 1997 and between 2500 and 6800 in

198517.

7.12.1. Type of workforce and status of skills

Studies on the software industry by Heeks in 1996 and Lateef in 1997

indicated that this sector per se is not a very large employer. By the mid-

1990s, the software industry employed about 8% of the total electronics

industry workforce and about 0.5% of total employment in the manufacturing

sector in India. The studies also indicate that the export side of the Indian

software industry is extremely skill intensive. The number of software

Professionals working for the export sector are approx. 20% of the total

software industry workforce and generating an export revenue figures of

about 58% of total revenues. Hence with the targets of increasing export

revenues, the demand for highly skilled personnel will continue to increase.

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This demand for technically skilled personnel will have to be drawn from the

very large English speaking, skilled labor force in the country. It is interesting

to note at this point that India has been emphasizing the development of a

strong technical workforce both in its industrial policy as well as in the field of

education since the post-Independence period. In addition to establishing the

Indian Institutes of Technology, which were educational institutions located in

various cities around India aimed at creating a large pool of technical skills,

the Government of India (GOI) has had a computer policy since the creation

of the Department of Electronics (DOE) in 1970. It was the first developing

country to do so and to explicitly target software as a "thrust area", for its high

skill requirements, its labor intensity, and its foreign exchange earnings

potential. According to NASSCOM, with over 4 million people with technical

backgrounds, 1,670 educational institutions and over 55,000 graduates in

engineering and the sciences every year, there is a rather large "trainable"

technical workforce. Management institutes produce 40,000 management

graduates annually. All these are potential entrepreneurs. India also has a

vast pool of existing and on-going scientific and technical research carried out

by a large number of research laboratories, including defense laboratories as

well as universities and technical institutes. These skills however need to be

constantly upgraded since technologies change very fast. Further, to meet

global needs, India needs to continuously add to its manpower pool. The

global advancement and worldwide opportunities are so huge that India

needs to train more skilled manpower in this field, so as to fulfill demand, not

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only in India, but across the globe. In fact studies in 1997 showed that

demand far outstripped the supply of professionals. In the United States the

demand for programmers had risen to 190,000 and world-wide there were

over 900,000 programming jobs waiting to be filled. There are, therefore, a

large number of projects that need to be completed or that have not been

initiated because of the lack of manpower. Both manufacturing (particularly

assembling) and the software industry require a skilled, Technical labor force.

However the profile of the skilled Indian labor force has always been

discussed with respect to the software industry due to the significant impact

that its growth has had on the Indian economy, education, employment

situation, and the socioeconomic structure. Some skews or unevenness has

been observed by many researchers in this area which, will be briefly

discussed here in the context of labor.

7.12.3. Working conditions including health and safety

An examination of the issues pertaining to working conditions here includes

workplace health and safety (including ergonomics) in manufacturing and

software facilities. Manufacturing facilities for components necessarily require

clean, enclosed, controlled temperature areas due to the strict product quality

standards demanded by the industry. However, during component

manufacture workers are exposed to soldering fluxes, One notable feature of

all the IT companies visited was the stress and focus on fire safety. At

computer manufacturing units in the country, no chemicals are used and the

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process is largely automated in clean rooms with controlled environments.

Ergonomic issues however are relevant from the point of health and safety.

In India the working conditions (including health and safety) at a

manufacturing facility are regulated by the Factories Act, 1948 (amended

1987). Conditions and standards for workplace cleanliness, disposal of

wastes and effluents, ventilation and temperature, exposure limits to dust and

fume, definition of overcrowding (in terms of area / volume required per

worker) and lighting are specified by this Act. In terms of space available per

person there typically is overcrowding in smaller operations where the space

available per person is anywhere between 40-60 sq.ft. In the larger more

established IT companies however it ranges from 80-100 sq.ft. Providing

very comfortable working conditions. Apart from working conditions within a

formal workplace, the software industry also raises the issue of working

conditions in the case of working from home offices. To elaborate on this, the

above discussion on trends in the use of intellectual property in India needs to

be revisited. As discussed above, improved telecommunications has led to an

increasing trend towards offshore work and this has led to a delocalization of

information processing work…..‖ described as ―teleworking.‖ This includes

using telecommunications to work within (telecommuting) and across national

borders (teletrade). While teletrade has been in practice in India for a while

and is largely the mode of operation of the IT industry today, telecommuting in

India is still in its infancy.

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Increasingly however with modification of Labor laws in the country both at

the level of Government of India and the State levels on the anvil, working

conditions will undergo significant changes. Some of the main drivers for

telecommuting to become a viable proposition in India are: working practices

becoming flexible; commuting in cities like Mumbai and Bangalore is

becoming increasingly resource intensive due to congestion; a high

concentration of women in the IT sector (with family responsibilities);

opportunities for self-employment and the mushrooming of 'SOHO' ('small

office; home office') businesses; telemediated services such as telebanking

and teleshopping are on the increase, telephone help lines are providing

access to customer service departments or government information. Working

conditions and health and safety conditions will therefore vary between

operations in an office and in the case of telecommuting.

7.12.4. Health hazards due to working with computers

Literature has established five types of health hazards attributed to working

with computers23. This needs to be examined in the context of both office-

based operations and telecommuting. The health hazards include:

Musculoskeletal: This includes a range of disorders of the neck,

upper limbs, shoulders and back (well known among these being

tendinitis and carpal tunnel syndrome). A category of injuries of

musculoskeletal origin termed Repetitive Strain Injury (RSI) describes

injuries to hands, wrists and neck.

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Visual capacity: Deterioration of visual capacity, eyestrain and

tiredness, loss of focus and mobility, reduction in capacity to dilate

pupils, cataracts and a range of discomfitures due to eyestrain such as

blurred and double vision, migraine, nausea etc.

Stress and fatigue: In the short-term it could include irritability,

depression, headaches, insomnia etc. while in the long-term it could

lead to heart disease, high blood pressure, anxiety, dermatitis, fertility

problems among other problems.

Reproductive Hazards: Due to exposure to ionizing and non ionizing

radiation from the Visual Display Units it is reported that reproductive

hazards such as miscarriages are likely. However this is issue has

been extensively contested. Discussions with the various companies

visited as part of the present study indicated that among the MNCs and

large domestic companies‘ workplace ergonomics was considered to

be a significant issue. Employees were provided with instructions on

optimal distance from the monitor, keyboard positioning, correct

working posture, optimal lighting etc. Fire safety was accorded high

priority at most of these companies. In the case of Infineon Techno for

e.g., corporate codes of conduct on ergonomics, health and safety are

mandated in the policy by Infineon Techno in Munich. This is

applicable across all facilities. Performance is assessed by an annual

corporate security audit conducted by a team from Munich. The focus

of this is to codify practices to ensure security of information as well as

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health and safety. At TI‘s R&D Centre, ergonomic experts from TI Inc.

were brought in to provide advice on seating, correct working posture

for more effective productivity. Agilent24 and HP, Corporate EHS

codes are applicable for software development as well. These include

non-usage of Lead, Asbestos etc. in construction and ensuring

ergonomically sound workplace conditions. Increasingly, employee

welfare in the form of good working conditions is becoming critical for

the software industry to retain the skilled workforce. A number of (both

MNCs and domestic) are setting up offices in well equipped, state-of-

art infrastructure like the ITPL at Whitefield in Bangalore, Software

Technology Parks or specialized areas like Electronic City in

Bangalore. Complexes like the ITPL (a private sector, Government of

Karnataka collaboration) which offer modular offices with

uninterrupted, clean power supply, domestic wastewater treatment

facilities, well designed, illuminated and well ventilated working area,

common recreation facilities such as gymnasium, restaurants,

bookshops, landscaped open areas, banking facilities etc. provide

working environments equivalent to any facility overseas. However, the

need to adhere to project deadlines, and ensure just-in-time delivery

does create stressful work conditions. The duration of this study was

not long enough to make a more categorical comment on the working

conditions in some of the smaller operations.

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7.12.5. Working hours

The working hours at the manufacturing facilities, like in the case of all other

industrial sectors, are regulated by the Factories Act 1948, (amended 1987)

which stipulates 48 hour week for adult workers and 9 hour days. In Offices

however a work-week is generally considered to be 35 to 40 hours.

Increasingly, flexi times are being permitted for the electronics sector. In

Mumbai where software processing is done for foreign airlines at the Santa

Cruz Electronics Export Processing Zone (SEEPZ), many software

companies have been operating under flexi time conditions since 1996-97.

The working shifts are also as applicable for other industries i.e., three shift

system. Women, according to the Factories Act however are not allowed to

work more than one shift. They can work only between 06.00 h and 21.00 h.

Flexibility under this provision is also being practiced by many companies. In

fact the State Government of Karnataka proposes to modify the labor law to

permit women to work in three shifts with a caveat placing the onus of

employee safety on the employer. Smaller software companies are regulating

by the Shops and Establishments Act and not under the Factories Act.

Typically official working hours for many of these software Increasing

competition from countries like Taiwan, Singapore, Korea and Philippines,

has led the Government of India to consider simplification of labor laws limited

to the IT industry to remain on par with the labor laws in these countries.

Some of the major changes suggested by the IT Action Plan II for the

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manufacturing sector include flexi times, increase in working hours, and night

shift for women.

7.12.6. Wages

India not only has a skilled labor force but also inexpensive vis-à-vis

international standards. Studies17 suggest that in the mid-1990s, salaries for

programmers and systems analysts were 4-5 times lower in India than in the

UK and 6-8 times lower than in the United States. More recent data however

indicates that wages in the Indian software industry have been rising

consistently at over 20% a year since the early 1990s. NASSCOM estimates

that the average basic salary rose by over 23% in 1995. These rates are not

very different to the software industry in other countries. Studies by Lateef17

and Heeks18 attribute much of the rise in wages to the tight labor market in

this industry and the very high turnover rate of 16%. A three year long study

(1997-1999) by the UNU INTECH22 showed that even with rising wages,

wages in India were 16% of those in the US in 1999. Apart from the wage

increases the overall monetary compensation has increased significantly with

schemes like the ESOP (Employee Stock Option Scheme) being announced

by a number of the larger IT companies with Infosys being one of the leaders.

These wage increases however, are primarily in the large Silicon metros like

Mumbai and Bangalore. This may present a problem for India in the future as

lower cost locations begin to enter the market and to compete for similar

projects. Today the IT industry is one of the highest payers in the Indian

market. This also has been responsible to some extent for retention of some

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of the talented workforce and marginally deterring the ―brain drain.‖This rising

rate in wages will very soon have to be reflected in corresponding rise in

productivity if the process is to be sustainable. Moreover charges, such as

overheads, transportation costs, telecommunications costs, office space,

travel allowances etc. are not that much lower than in other countries. This

according to Lateef17 weakens India's advantage, although it still figures as a

low cost location. Wages are not uniformly high across the IT sector

7.12.7. Gender issues

Manufacture of electronics, has traditionally employed women particularly for

the assembly operations due to their greater dexterity. Discussions with

Compaq also indicated that there was a greater preference for women due to

their dexterous skills. At Compaq women also head and manage shifts.

Similar preference shown by many IT companies to recruit women. This was

reportedly also due to the attrition rate among women being lower than that

among men. A gender division of labor was however observed due to the

―body shopping‖ phenomenon in studies by Heeks19. This study reported that

only about 10% of Indian software developers are female. When onsite work

was the predominant export earner for the software industry, many women

faced difficulties at having to work overseas.Lateef17 reports that the

software industry in India, like in other countries, is highly male dominated,

with about 86% of the labor force being men. In terms of remuneration,

women are paid at an equal pay-scale. Surveys carried out during the UNU

INTECH study25 indicated that in software women enjoy preferences on a

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scale that they never experienced in any other field of engineering and

science. In the metro cities like Calcutta and Bangalore, the percentage of

women is higher than 19% - the average figure for India. In both of these

cities women typically occupy 20- 25% of professional jobs. Neither in

Bangalore nor in Kolkata did the researchers find any evidence of

discrimination, either at the point of recruitment or in career progression.

Women receive a very large proportion of remote processing jobs. In Mumbai,

in large subsidiaries of multinational airline companies, for example, 60% or

more of the employees are women. The salaries, at Rs 5000 (US$ 100

approximately) per month for a trainee, are good by Indian standards. At

Infosys, for e.g., women employees who have children can take advantage of

a company run crèche. Some firms, such as Novell Software and WIPRO for

instance, are experimenting with telecommuting in order to maintain the skill-

levels of female workers with young children. Companies such as Datamatics

receive assignments from their international clients. In turn, they pass these

to women teleworkers who work from their homes, mostly on-line, and with

their own computers. These home-based teleworkers comprise a wide range

of women: housewives, doctors, lawyers, chartered accountants. The IT

industry thus appears to be bringing some attitudinal changes in gender

issues. Another important gender issue is that of exposure of pregnant

women to monitors at the workplace. There do not appear to be any studies

done in India on this aspect and even internationally, the cause - effect

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relationship between exposure to monitors and reproductive disorders has not

really been established.

7.12.8. IT industry and the Community

The interaction and impact of the IT industry on the community has been at

two levels: local and national. At the local level it has meant: changes in the

local infrastructure, pressures on utilities due to growth of the city, growth of

the local economy and the employment opportunities, sociological changes

due to changes in the socio-economic structures, changes in land use, rising

real estate prices, and focus of the educational system becoming strongly ―IT

centric.‖At the National level the IT industry has brought about, growth of the

economy and a pre-eminent position in the global market, very rapid growth

of the large and small metros, employment opportunities and increasingly

greater retention of intellectual talent in the country and access to latest

technology. Communication will improve with the increased access to Internet

while e-governance hopes to enable greater transparency and accountability

in governance. Civil society‘s participation in governance will be enhanced. E-

commerce will have great implications for trade and business. The various

impacts of the IT industry will be considered in greater detail in the following

sections of the Chapter under various headings. Here the categorization is in

terms of the impact of the IT industry and the local and national level

manifestations will be discussed as and when appropriate and relevant.

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7.12.9. Contribution to growth of the economy

The IT industry‘s contribution to the Indian economy has been significant in

the last few years. The sector contributed 15% to the country‘s export

earnings during the last fiscal year 1999-2000 vis-à-vis 12.4% in 1998-99. At

the State levels also this economic growth has been reflected in terms of local

economic growth. What is essential now is to put policy and governance in

place to sustain this growth. A strongly export oriented industry can also have

repercussions on local economic growth particularly since tax holidays are

being provided as incentives for establishment of export oriented units,

software and hardware parks etc. This would lead to a reduction in tax

revenues, thereby affecting the State‘s ability to provide supportive

infrastructure for the growth of the industry. In tandem with such tax

incentives, alternatives such as an increasing need to privatize infrastructure

development and services are being explored.

7.12.10. Creation of employment opportunities

The IT industry has tremendous potential to create employment opportunities.

Some industry observers argue that the jobs created can be accessible only

to the fairly well off and educated sections of society and that even However,

given the projected growth of IT enabled services: NASSCOM reports that in

1998-99 IT-enabled services employed 23,000 people. Projections for

employment in this sector for 2008 are 1,100,000. This will therefore create

greater employment per unit of capital and the requirement is not for a highly

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skilled technical workforce. The employment opportunities in the IT sector

particularly software and IT enabled services could quite easily be realized by

the physically disadvantaged and disabled section of the community as well.

A pioneering effort by IBM has been the donation of computers and providing

training expertise to the Victoria School for the Blind, while developing and

promoting use of software and hardware for the blind. In essence therefore,

with the right thrust to formal and vocational education in IT, the employment

opportunities thrown up by the sector can be effectively used.

7.12.11. Changes in educational system

The meteoric growth of the IT industry has led to introduction of IT based

courses and programs in schools, colleges and universities. Apart from

premier institutions like IITs and IIMs and the various engineering and science

colleges and institutions, which were and are the main sources of technical

skills in the country, specialized IT institutes i.e., the Indian Institute of

Information Technology (IIIT) are being set up across the country. Large IT

companies both MNCs and domestic players are setting up laboratories in

these institutes. Computer training institutes are mushrooming all over the

country, offering skills ranging from basic computer literacy through

programming to web design.

MNCs such as Intel and IBM are investing in intellectual skill development

through various community based programs. Intel has a program called

Teach for the Future through which it is cooperating with the National Council

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for Education, Research and Training (NCERT) and a number of schools to

promote computer literacy. Intel also sponsors an educational initiative for

kids encouraging scientific thinking and creativity with incentives like visits to

Intel‘s laboratories in the US and state-of-art PCs as awards for the winners.

Hardware and software has been donated by IBM to the Bharatiya Vidya

Bhavan‘s school in Mumbai to enable free computer education to the

economically disadvantaged. Also, a commitment to underwrite the operation

and maintenance cost for the school for three years has been made by IBM.

A Memorandum of Understanding has been signed by IBM with the State

Government of Maharashtra to offer free copies (not requiring licensing) of

Lotus Notes, etc. to all government schools and colleges in the State. There

is thus a multi-pronged approach both by Government and the private sector

at eventually ensuring that a large pool of technically skilled workforce is

available for the IT sector. The flip side of this is of course the mushrooming

of a number of mediocre ―training‖ institutions that offer attractive ―training

packages‖ to students eager to be part of the IT boom. Mere computer

literacy or familiarity with standard word processing software does not

guarantee a slice of the pie.

7.12.12. Sociological changes

The impact of the IT industry has been on every aspect of Indian society

ranging from education to life-style. Greater access to information and

technology has increased awareness. With the onset of SOHO and

telecommuting (although slowly) working styles become flexible, women‘s

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employment opportunities are undergoing a change and entrepreneurship

has increased. It is beginning to influence people‘s perceptions of what it can

do for their businesses, in terms of efficiency and in terms of linking them up

with the global economy. Work culture of the global software industry is

starting to permeate to other sectors, either through the movement of people

between sectors or through the use of computers. Till date however this

influence is largely on part of this industry. The pressure could range from

affordability of housing to lifestyles. The growing difference between incomes

in this sector and other sectors of the Indian economy will thus have a

significant impact on Indian polity and society. In smaller cities and rural areas

what will create sociological changes will be the intended plan of the

government to provide Internet for All and the policy of e-governance already

underway in some states in the country. Access to information in the local

language will cut across barriers to education and awareness and will

contribute to elevation of literacy. The benefits of which will be reflected in

health, agriculture, business and the local economy.

CHAPTER 8: DATA COLLECTION PROCEDURE AND

DATA PREPARATION

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CHAPTER 8

DATA COLLECTION PROCEDURES AND DATA

PREPARATION

In order to facilitate data collection, the data collection followed the steps

described below.

Step1: Introductory letter

The surveys and an introductory letter (included in Appendix III) were

forwarded to participants of different organizations. The introductory letter

explained:

a) The voluntary nature of participation,

b) The benefits of participation, and

c) How participants‘ confidential information would be protected.

In addition, informed participants that the survey was anonymous and only

aggregate data on engagement, Managerial competencies and Talent

Management would be reported. The email id was taken to do the follow up.

Step 2: Follow up Letter through email

A week after the first letter were sent to participants, a follow up letter

encouraging participation was sent to all who had not yet responded. A copy

of this letter is included in Appendix IV

CHAPTER 9: PILOT TESTING

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CHAPTER 9

PILOT TESTING

A pilot study should be performed to develop, adapt, or check the feasibility of

techniques, to determine the reliability of measures, and/or to calculate how

big the final sample needs to be. In the latter case, the pilot should have the

same sampling procedure and techniques as in the larger study.

The pilot testing was done at MNC and Private IT companies. The two

companies from MNC and Private sector were selected by which the

questionnaire was revised. After the data was collected, the data was

exported into SPSS for Windows software version 18 for a series of data

analysis tests, as follows. All tests were run at an alpha level of 0.05, 0.01.

9.1. Validity

Conclusions drawn from analyzing survey data were only acceptable to the

degree to which they were determined valid. Validity was used to determine

whether research measures what it intended to measure and to approximate

the truthfulness of the results. In quantitative research testing for validity and

reliability is given. To disregard validity was to put the trustworthiness of the

work in question and to call into question others confidence in its

results. Validity and reliability make the difference between ―good‖ and ―bad‖

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research reports. Quality research depends on a commitment to testing and

increasing the validity as well as the reliability of the research results.

Any research worth its weight was concerned with whether what is being

measured is what is intended to be measured and considers the ways in

which observations were influenced by the circumstances in which they were

made. The basis of how the conclusions were made play an important role

in addressing the broader substantive issues of any given study. Various

validity types have been formulated as a part of legitimate research

methodology.

9.1.1. Face Validity

This is the least scientific method of validity as it is not quantified using

statistical methods. This is not validity in a technical sense of the

term. Valid is a measure appears on the surface and make subjective

judgments based on that. In research it‘s never sufficient to rely on face

judgments alone and more quantifiable methods of validity are necessary in

order to draw acceptable conclusions. There are many instruments of

measurement to consider so face validity is useful in cases where the study

need to distinguish one approach over another. Face validity should never be

trusted on its own merits.

9.1.2. Content Validity

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This was also a subjective measure but unlike face validity it was important to

identify whether the content of a measure covers the full domain of the

content. This was considered a subjective form of measurement because it

still relies on people‘s perception for measuring constructs that would

otherwise be difficult to measure. Where it distinguishes itself is through its

use of experts in the field or individuals belonging to a target population. This

study was made more objective through the use of rigorous statistical

tests. The study have a content validity study informs how items used in a

survey represent their content domain, how clear they are, and the extent to

which they maintain the theoretical factor structure assessed by the factor

analysis.

9.1.3. Construct Validity

A construct represents a collection of behaviors that were associated in a

meaningful way to create an image or an idea invented for a research

purpose. The existence of a construct is manifest by observing the collection

of related indicators. Any one sign may be associated with several

constructs. Construct validity is the degree to which inferences can be made

from operationalizations (connecting concepts to observations) in the study to

the constructs on which those operationalizations are based. To establish

construct validity first provide evidence that the data supports the theoretical

structure. The study controls the operationalization of the construct; in other

words, show that the theory has some correspondence with reality.

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9.1.4. Convergent Validity

The degree to which an operation is similar to other operations it should

theoretically be similar to.

9.1.5. Discriminative Validity

If a scale adequately differentiates itself or does not differentiate between

groups that should differ or not differ based on theoretical reasons or previous

research.

9.1.6. Nomological Network

The representation of the constructs must be of interest in a study, their

observable manifestations, and the interrelationships among and between

these. According to Cronbach and Meehl, a nomological network have been

developed for a measure in order for it to have construct validity

9.1.7. Multitrait - Multimethod Matrix

Six major considerations when examining construct Validity according to

Campbell and Fiske. This includes evaluations of the convergent validity and

discriminative validity. The others are trait method unit, multi-method/trait,

truly different methodology, and trait characteristics.

9.1.8. Internal Validity

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This refers to the extent to which the independent variable can accurately be

stated to produce the observed effect. If the effect of the dependent variable

is only due to the independent variable(s) then internal validity is achieved.

This is the degree to which a result can be manipulated.

9.1.9. Statistical Conclusion Validity

A determination of whether a relationship or co-variation exists between

cause and effect variables. It requires ensuring adequate sampling

procedures, appropriate statistical tests, and reliable measurement

procedures. This is the degree to which a conclusion is credible or believable.

9.1.10. External Validity

This refers to the extent to which the results of a study can be generalized

beyond the sample.

9.1.11. Criterion-Related Validity

It can alternately be referred to as Instrumental Validity. The accuracy of a

measure was demonstrated by comparing it with a measure that have been

demonstrated to be valid. i.e. Correlations with other measures that have

known validity. It was checking the performance of the operationalization

against criteria.

9.1.12. Predictive Validity

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Operationalization‘s ability was to predict what it was theoretically able to

predict. The extent to which a measure predicts expected outcomes.

9.1.13. Concurrent Validity

Operationalization‘s ability to distinguish between groups it theoretically

should be able to. This is where a test correlates well with measures that

have been previously validated.

9.2. VALIDITY IN SURVEY DATA

The research depends on the respondent‘s mind set and attitude in order to

give the valid data. In other words depend on the respondents to answer all

questions honestly and conscientiously. It depends on whether they were

able to answer the questions in the questionnaire. When questions were

asked that the respondent cannot comprehend or understand then the data

does not tell what were needed in the research. So the questionnaire was

given for validity to the few HR consultants to understand and approve the

link between the objectives and the results intended to measure which helped

to go for further reliability test.

The research questions fulfilled the Validity test in which the research were

measured what it was intended to. It helped to check the Content validation

how well the content of the research were related to the variables to be

studied. The research questions representatives of the variables were being

researched. It is an expression that the items of a test were drawn from the

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domain being measured. Criterion validation checks how meaningful the

research criteria were relative to other possible criteria. When the criterion

was collected later the goal was to establish predictive validity. Construct

validation checks what underlying construct was being measured. One key

objective of Rich‘s dissertation was the construct validation of the JES. The

construct validity of a scale is established indirectly, by accumulating

evidence that the scale measurements ―result in a close correspondence

between the construct of interest and the scores provided by the measure‖

(Schwab, 2005, p. 26). Three criteria for construct validity were content

validity, instrument reliability, and convergent validity for employee

engagement, talent management and managerial competencies were fulfilled.

9.3. RELIABILITY TEST

Reliability refers to the consistency of a measure. A test is considered reliable

if it gets the same result repeatedly. It can be estimated in a number of

different ways are as follows

9.3.1. Test-Retest Reliability

To gauge test-retest reliability, the test was administered twice at two different

points in time. This kind of reliability was used to assess the consistency of a

test across time. This type of reliability assumes that there were no changes

in the quality or construct being measured. Test-retest reliability was best

used for things that are stable over time, such as intelligence. Generally,

reliability will be higher when little time has passed between tests.

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9.3.2. Inter-rater Reliability

This type of reliability was assessed by having two or more independent

judges score the test. The scores were then compared to determine the

consistency of the rater‘s estimates. One way to test inter-rater reliability is to

have each rater assign each test item a score. For example, each rater might

score items on a scale from 1 to 10. The next step involves calculating the

correlation between the two ratings to determine the level of inter-rater

reliability. Another means of testing was inter-rater reliability to have raters

determine which category each observations falls into and then calculate the

percentage of agreement between the raters. So, the raters agreed 8 out of

10 times, the test had an 80% inter-rater reliability rate.

9.3.3. Parallel-Forms Reliability

Parellel-forms reliability was gauged by comparing two different tests that

were created using the same content. This is accomplished by creating a

large pool of test items that measure the same quality and then randomly

dividing the items into two separate tests. The two tests should then be

administered to the same subjects at the same time.

9.3.4. Internal Consistency Reliability

This form of reliability was used to judge the consistency of results across

items on the same test. Essentially, comparing test items that measure the

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same construct to determine the tests internal consistency. A question that

seems were very similar to another test question, it indicated that the two

questions were being used to gauge reliability. Because the two questions

were similar and designed to measure the same thing, and should answer

both questions the same, which would indicate that the test had internal

consistency.

9.3.5. Split-half reliability

In split –half reliability test, all items were randomly divided that purport to

measure the same construct into two sets. The entire instruments were

administered to a sample of people and calculate the total score for each

randomly divided half. The split-half reliability estimate, as shown in the

figure, is simply the correlation between these two total scores. In the

example it is .87

.

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Compute one split-half reliability and then randomly divide the items into

another set of split halves and recomputed, and was repeated until computed

all possible split half estimates of reliability.

9.3.6. Cronbach's Alpha

Cronbach‘s alpha is a statistic. It was generally used as a measure of internal

consistency or reliability of a psychometric instrument. Cronbach's Alpha is

mathematically equivalent to the average of all possible split-half estimates.

The figure shows several of the split-half estimates for our six item example

and lists them as SH with a subscript. Although Cronbach's Alpha is

equivalent to the average of all possible split half correlations actually help to

calculate it quickly.

Cronbach's alpha increases as the intercorrelations among test items

increase, and is thus known as an internal consistency estimate of reliability

of test scores. Because intercorrelations among test items were maximized

when all items measure the same construct, Cronbach's alpha is widely

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believed to indirectly indicate the degree to which a set of items measures a

single one-dimensional latent construct. However, the averages inter

correlation among test items is affected by skew just like any other average.

Thus, whereas the modal inter correlation among test items equal zero when

the set of items measures several unrelated latent constructs, the average

inter correlation among test items were greater than zero in this case. Indeed,

several investigators have shown that alpha can take on quite high values

even when the set of items measures several unrelated latent constructs

(e.g., Cortina, 1993; Cronbach, 1951; Green, Lissitz & Mulaik, 1977; Revelle,

1979; Schmitt, 1996; Zinbarg, Yovel, Revelle & McDonald, 2006). As a result,

alpha is most appropriately used when the items measure different

substantive areas within a single construct. When the set of items measured

more than one construct, coefficient omega hierarchical was more

appropriate (McDonald, 1999; Zinbarg, Revelle, Yovel & Li, 2005). Alpha

treats any covariance among items as true-score variance, even if items co

vary for spurious reasons. Alpha can be artificially inflated by making scales

which consist of superficial changes to the wording within a set of items or by

analyzing speeded tests. A commonly accepted rule of thumb for describing

internal consistency using Cronbach's alpha is as follows:

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Table no 5: Cronbach's alpha internal consistency

Cronbach's alpha Internal consistency

α ≥ .9 Excellent

.9 > α ≥ .8 Good

.8 > α ≥ .7 Acceptable

.7 > α ≥ .6 Questionable

.6 > α ≥ .5 Poor

.5 > α Unacceptable

9.4.1. RELIABILITY TEST FOR EMPLOYEE ENGAGEMENT

There are lots of items, so Cronbach‘s Alpha tends to be the most frequently

used estimate of internal consistency. Table number 6 shows reliability test

for engagement level. The Spilt Half test was estimated as the Pearson

product-moment correlation coefficient between two halves of the instrument,

treated as alternate forms of the measure (Allen and Yen, 2002). Again, the

statistic ranges from 0 to 1 and the higher the statistic, the higher the

reliability of the instrument. Cronbach’s Alpha range was 0.716 to 0.916,

strong findings, across the 12 dimensions. The split half reliability range

was 0.621 to 0.922, strong findings, across the 12 dimensions. The

Spearman-Brown Coefficient ranged from 0.706 to 0.902, strong findings,

across the 12 dimensions. Reliability is not the same thing as validity.

Reliability means that an instrument is measuring something and measuring it

consistently.

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Table no 6: Reliability Test : Results for the engagement levels

Indicator Instrument Dimensions : Cronbach’s Alpha

Split Half Test , Spearman-Brown Coefficient

Instrument

Dimensions

Cronbach’s

Alpha

Split Half Test Spearman-

Brown

Coefficient

Emotional1 0.841 0.866 0.836

Emotional2 0.742 0.748 0.756

Emotional3 0.761 0.819 0.829

Emotional4 0.621 0.716 0.706

Physical1 0.751 0.866 0.846

Physical2 0.891 0.828 0.833

Physical3 0.922 0.829 0.835

Physical4 0.911 0.916 0.902

Cognitive1 0.899 0.866 0.846

Cognitive2 0.741 0.828 0.821

Cognitive3 0.741 0.819 0.810

Cognitive4 0.696 0.726 0.775

9.4.2. RELIABILITY TEST FOR TALENT MANAGEMENT

Table no 7 shows reliability test for talent management. The Spilt Half test

was estimated as the Pearson product-moment correlation coefficient

between two halves of the instrument, treated as alternate forms of the

measure (Allen and Yen, 2002). Again, the statistic ranges from 0 to 1 and

the higher the statistic, the higher the reliability of the instrument. Cronbach’s

Alpha range was 0.621 to 0.922, strong findings, across the 14 dimensions.

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The split half reliability range was 0.666 to 0.916, strong findings, across

the 14 dimensions. The Spearman-Brown Coefficient ranged from 0.612

to 0.902, strong findings, across the 14 dimensions. Reliability is not the same

thing as validity. Reliability means that an instrument is measuring something

and measuring it consistently.

Table no 7: Reliability Test Results for the talent management

Indicator Instrument Dimensions : Cronbach’s Alpha

Split Half Test , Spearman-Brown Coefficient

Instrument Dimensions

Cronbach’s Alpha

Split Half Test Spearman-Brown Coefficient

Recruitment & Selection

0.741 0.866 0.836

Assessment tools

0.621 0.677 0.612

Job fit 0.745 0.733 0.766

Performance appraisal

0.841 0.866 0.836

Individual development plan

0.742 0.748 0.756

Training, guidance

0.761 0.819 0.829

Implementation

0.678 0.716 0.706

Monitoring 0.781 0.886 0.836

Potential measurement

0.871 0.821 0.813

Mentoring and coaching

0.922 0.829 0.835

Developing talent pool

0.923 0.916 0.902

Career management

0.699 0.666 0.646

Ensuring critical retention

0.748 0.823 0.871

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General deployment

0.744 0.814 0.813

Succession planning

0.696 0.736 0.745

9.3. RELIABILITY TEST FOR MANAGERIAL COMPETENCIES

Table no 8 shows reliability test for managerial competencies. The Spilt Half

test was estimated as the Pearson product-moment correlation coefficient

between two halves of the instrument, treated as alternate forms of the

measure (Allen and Yen, 2002). Again, the statistic ranges from 0 to 1, and

the higher the statistic, the higher the reliability of the instrument.

Cronbach’s Alpha range was 0.652 to 0.881, strong findings, across the 15

dimensions. The split half reliability range was 0.677 to 0.894, strong

findings, across the 15 dimensions. The Spearman-Brown Coefficient

ranged from 0.612 to 0.871, strong findings, across the 14 dimensions.

Reliability is not the same thing as validity. Reliability means that an

instrument is measuring something and measuring it consistently.

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Table no 8: Reliability Test Results for the managerial competencies

Indicator Instrument Dimensions : Cronbach’s Alpha Split

Half Test ,Spearman-Brown Coefficient

Instrument Dimensions Cronbach’s Alpha

Split Half Test

Spearman-Brown Coefficient

Managing & Developing 0.641 0.766 0.736

Problem Solving and participative mgt

0.652 0.677 0.612

Initiative/Innovation 0.659 0.745 0.766

Results Oriented 0.741 0.766 0.736

Communication and building trust

0.642 0.749 0.726

Change Management 0.861 0.819 0.829

Coaching 0.728 0.716 0.756

Continual Learning

0.781 0.886 0.836

Developing others

0.881 0.892 0.813

Decision Making

0.822 0.829 0.835

Emotional Intelligence

0.823 0.816 0.802

Empowering others

0.699 0.776 0.746

Getting Results

0.728 0.863 0.871

CHAPTER 10: DATA PREPARATION

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CHAPTER 10

DATA PREPARATION

10.1. SAMPLE PREPARATION AND CHARACTERISTICS

The data for the study were collected from Private and Multinational IT

companies. Table 9 lists the total number of surveys sent, surveys received,

and the response rates for each sample. The questionnaire was sent to 650

respondents to 10 different multinational IT companies and the 600

respondents responded with the completed forms. The 700 questionnaire

were sent to Private sector with 650 respondents responding to it.

TABLE 9: Sample Sizes and Response Rates

IT COMPANIES

SENT

RESPONDED

PERCENTAGE RESPONDED

MNC 650 600 92 %

PRIVATE

700

650

92%

10.2. DATA PREPARATION USING STATISTICAL PACKAGE FOR

SOCIAL SCIENCES

The data collected were analyzed using the Statistical Package for Social

Sciences (SPSS) version 18. Data Preparation involves checking or logging

the data in; checking the data for accuracy; entering the data into the

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computer; transforming the data; and developing and documenting a

database structure that integrates the various measures.

10.2.1. Logging the Data

The procedure used for logging the information and keeping track of it until it

was ready to do a comprehensive data analysis. To set up a database that

enables to assess at any time what data was already in and what was still

outstanding was accomplished using standard statistical programs (e.g.,

SPSS, SAS, Minitab, Data desk) and running simple descriptive analyses to

get reports on data status. It was also critical to retain the original data

records for a reasonable period of time -- returned surveys, field notes, test

protocols, and so on, to trace a result from a data analysis back to the original

forms on which the data was collected. As database for logging incoming data

is a critical component in good research record-keeping.

10.2.2. Checking the Data for Accuracy

As soon as data was received it was screened for accuracy. Thus in some

circumstances doing this right away will allow to go back to the sample to

clarify any problems or errors. There were several questions asked as a part

of this initial data screening:

Are the responses legible / readable?

Are all important questions answered?

Are the responses complete?

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Is all relevant contextual information included

The quality of measurement was a major issue and thus assuring that the

data collection process does not contribute inaccuracies would help assure

the overall quality of subsequent analyses.

10.2.3. Developing a Database Structure

The database structure was the manner in which it was intended to store the

data for the study so that it can be accessed in subsequent data analyses.

There were generally two options for storing data on computer database

programs and statistical programs. A printed codebook was prepared which

helps to describe the data and indicates where and how it can be accessed.

Minimally the codebook should include the following items for each variable:

variable name

variable description

variable format (number, data, text)

instrument/method of collection

data collected

respondent or group

variable location (in database)

notes

Thus the codebook helped as an indispensable tool for the analysis.

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10.2.4. Entering the Data into the Computer

There were a wide variety of ways to enter the data into the computer for

analysis. The data‘s were typed directly. The data‘s once were entered and

set up a procedure for checking the data for accuracy by spotting check

records on a random basis. Once the data was entered, used various

programs to summarize the data that allowed to check that all the data were

within acceptable limits and boundaries.

10.2.5. Data Transformations

The data have been entered to transform the raw data into variables that

were usable in the analyses. There were wide varieties of transformations

finding and using missing values

10.2.6. Missing values

The missing values were designated with specific values to represent missing

values. A value of 99 was used to indicate that the item was missing. The

data were prepared for analysis which can be carefully screened for missing

data, outliers and normality following the recommendations of Mertler and

Vannatta (2005). To investigate and to find the differences of engagement

level, talent management and managerial competencies in private and

multinational IT sector. An analysis of variance (ANOVA) was run to

investigate separately. Finally, various statistical tests Pearson correlations,

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factorial analysis of variance, multiple regressions, analysis of variances, was

run to address each of the study questions.

The following steps were taken to prepare the raw data for analysis:

a) Screening participants to ensure that all were members of the

intended Population,

b) Screening for missing data

c) Recoding nominal data: On scales and surveys, used a reversal items

to help reduce the possibility of a response set. To analyse the data, all

scores for scale items to be in the same direction where high scores mean

the same thing and low scores mean the same thing. In these cases the

ratings for some of the scale items were reversed. To compare the two

items, the scores of one of the item were reversed so that high values will

always indicate higher score. The transformation were made where if the

original value was 1 it's changed to 5, 2 is changed to 4, 3 remains the

same, 4 is changed to 2 and 5 is changed to 1. These changes were

programmed as separate statements; it was easier to do this with a simple

formula:

New Value = (High Value + 1) - Original Value

The High Value for the scale is 5, so to get the new (transformed) scale

value; it was subtracted from each Original Value 6 (i.e., 5 + 1).

Scale totals

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Individual scale items were transformed often wants to add or average

across individual items to get a total score for the scale.

Categories

Many variables were grouped into categories. Calculating engagement

scores, talent management scores and managerial competencies scores

d) Eliminating outliers: Outliers were data values that deviate from the

mean by more than three standard deviations. When estimating

parameters from data containing outliers, the results may not be accurate.

Outliers were removed replaces the data samples containing outliers with

99, which represent missing data.

e) Verifying the normality of the dependent and independent variables that

were talent management, managerial competencies and employee

engagement

CHAPTER 11: QUICK VIEW ON THE PROCESS OF

ANALYSIS

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CHAPTER 11

QUICK VIEW ON THE PROCESS OF ANALYSIS

This chapter gives a quick view on the process of analysis , how the

analysis is being carried out with the objectives assigned and with

the application of different analytical tools .With the set of objectives as

the point of reference the different analytical tools are applied which are

as follows:

11.1. To analyse and compare the variables in MNC and Private sector,

that is for establishing results of Employee Engagement levels, talent

management and managerial competencies among Private and

Multinational IT companies, statistical tool ANOVA was used. The results

might show that there were significant differences in engagement levels,

talent management and managerial competencies among Private and

Multinational IT companies. MNC shows more Engagement level than

Private sector. Since there were differences in Target variables it was

important to find which Predictor variables that affect the values of the

target. So to identify the Relation and the effect of Talent Management

and Managerial competencies on Employee engagement levels in Private

sector and Multinational Company. The correlation and regression

analytical tools were used to understand the relation and the effect for the

above variables.

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11.2. First the MNC‘s data were used to study the relation and effect.

Multiple correlations and Regression Analysis were used on MNC data‘s in

order to identify the effect of talent management and managerial

competencies on employee engagement levels.

11.3. In the case of Private IT sector, multiple correlations were used to find

the relation of talent management and managerial competencies on

engagement level.

11.4. The variables related to talent management i.e. .recruitment and

selection, job fit, performance appraisal, training & coaching, individual

development plan, monitoring, competency mapping, succession planning

were considered for finding the association between talent management

variables with the engagement levels. The scores were created ―high‖ and

―low‖ categories for each variable. The cut off points for each category were

taken from talent management (Romans and Lardner, 2006; [55] Heinen and

O'Neill, 2004; [108] Scheweyer, 2004) and the scores for engagement levels

are taken as engaged and disengaged level from the Job Engagement

survey or JES (Rich, 2006) .

11.5. Similarly scores for managerial competencies were created as ―high‖

and ―low‖ categories for each variables of managerial competencies: initiative

& innovation, planning and organizing, result orientation, coaching, decision

making, thinking strategically. To test the association between managerial

competencies and levels of employee engagement chi-square and

correlation were used.

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11.6. The data‘s of MNC were further considered for testing the variables of

talent management and computed variables of managerial competencies on

the engagement level using step wise regression thus developing the talent

engagement model to enhance employee engagement

11.7. Similarly the data‘s of MNC were further considered for testing the

variables of managerial competencies and engagement level using step wise

regression thus developing the managerial competency model to enhance

employee engagement.

The data analysis conducted for this study included

Factor Analysis: The number of variables for managerial competencies

and talent management were reduced through correlation and the factor

analysis used for dimension reduction.

ANOVAS: ANOVAS was used to explore differences or compare

engagement, Talent Management and managerial competencies between

MNC and private sector.

Correlation analyses and multiple regressions: Pearson product

moment correlation coefficient and multiple regressions are used to explore

relationships and the effect between the Talent management, managerial

competencies on the employee engagement levels for MNC.

The same procedures was used to explore relationships of the above

variables in Private sector

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Chi square and correlation: Chi square and correlation were used to

explore differences or compare scores of factors of talent management

between levels of engagement in Private sector.

Chi square and correlation: Chi square and correlation was used to

explore differences or compare scores of factors of managerial

competencies between levels of engagement in Private sector.

Stepwise Multiple regressions: Multiple regressions were used to predict

talent engagement model and managerial competency model using

various variable combinations of talent management and managerial

competencies.

CHAPTER 12: PREREQUISITE FOR DIMENSION

REDUCTION

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CHAPTER 12

PREREQUISITE FOR DIMENSION REDUCTION

Dimension Reductions for the independent variables: Managerial

Competencies and Talent Management.

Factor analysis is based on correlation, linearity is important and it is

satisfying to go further with factor analysis .The data‘s are prepared for factor

reduction with the two Independent variables i.e. managerial competencies,

talent management separately. Dimension Reduction methods have the goal

of using the correlation structure among the predictor variables to accomplish

the following:

To reduce the number of predictor components

To help ensure that these components are independent

To provide a framework for interpretability of the results.

12.1. DIMENSION REDUCTION: STEPS FOLLOWED FOR THE

INDEPENDENT VARIABLE MANAGERIAL COMPETENCIES

Step1. The correlation between dependent variable and independent

variable was determined to reduce the number of variables. The

correlations between independent variables and dependent

variables have to be analyzed i.e. managerial competencies with

the employee engagement. Correlation coefficient measure was

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used to quantify the linear relationship between two quantitative

variables is the correlation coefficient. Investigation of variable-by-

variable association between the predictors and the target variables

need to be ascertained. The higher correlation values were

considered for dimension reduction and the values with low

correlation were eliminated. The following variables having high

correlation with values more than 0.5 to 1 were considered. Table

no 10 showed the values with in the range of 0.5 to 0.7 showed

higher correlation. The variables of managerial competencies which

showed values between 0.5 to 0.7 were Initiative and innovation,

Planning and organizing, Result orientation, Coaching, conflict,

Decision making, Development, Thinking Strategically eliminating

two sub variables problem solving and listening which were lesser

than 0.4

Table no 10: Correlation: Independent variable: Managerial Competencies vs. Employee engagement

Symmetric Measures

Independent variable

vs engagement Value

Asymp. Std. Errora Approx. Tb Approx. Sig.

Problem solving

.263

.082

5.465

.000c

Initiative and innovation

.672

.116

3.297

002c

Result orientation

.510

.105

3.622

.001c

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Decision making

.651 .133 3.117 .001c

Development

.663 .082 5.465 .000c

Empowerment

.572 .116 3.297 .002c

Listening

.247 .113 4.024 .000c

Thinking strategically

.551 .133 3.117 .001c

Planning and organizing

.663 .082 5.465 .000c

Conflict

.451 .133 3.117 001c

Result orientation

.547 .113 4.024 .000c

Step 2. The variables with higher values were again tested with the Bivariate

correlation with only independent variables separately excluding the

target variable to guard against multicollinearity. Multicollinearity

leads to instability in the solution space, leading to possible

incoherent results. The predictors if correlated the response surface

is unstable, providing highly variable coefficient estimates with

inflated values. To avoid multicollinearity, it was important to

investigate the correlation structure among the predictor variables

ignoring the target variable for the moment. The variables of

managerial competencies were tested using Bivariate correlation. To

investigate the variable-by-variable association between the

predictors, the pair wise correlation coefficients among the

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predictors were applied and noted that those correlations that were

strongest. Table no 11 contains a listing of the pair wise correlations

that are the strongest in absolute value among the predictors. The

variables having low correlation values and high correlation values

were further considered for dimension reduction process thus

determining the appropriateness of the factor analytic model. It

showed that the relation between the independent variables i.e.

predictor variables should be. It had no strong correlation between

the independent variables which further considered for factor

reduction. This step has to be followed with the independent

variables that were factors of managerial competencies.

The following variables have been considered for factor

analysis:

1. Initiative & Innovation

2. Coaching

3. Result Orientation

4. Decision Making

5. Thinking Strategically

6. Development

7. Planning and organizing

8. Conflict

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Table no 11: Correlation matrix: Independent variable: Managerial

Competencies

I&I CON CO RO DM DEV P&O TS

Initiative & innovation

1

Conflict

.601** 1

Coaching

.370** .266** 1

Result

orientation

.291** .386** .322** 1

Decision making

.393** .219** .376** .365** 1

Development

.386** .368** .289** .490** .339** 1

Planning and

organizing

.486** .368** .489** .390** .339** .280** 1

Thinking strategic

.393** .319** .476** .265** .300** .339** .239** 1

**. Correlation is significant at the 0.01 level (2-tailed).

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12.2. DIMENSION REDUCTION: STEPS INVOLVED IN FACTOR

ANALYSIS FOR INDEPENDENT VARIABLE: TALENT

MANAGEMENT

The following steps are to be followed for the independent variable for talent

management variables.

Step1. The correlation between dependent variable and independent variable

was determined to reduce the number of variables. Correlation

coefficient measure were used to quantify the linear relationship

between two quantitative variables is the correlation coefficient, thus

to investigate the variable-by-variable association between the

predictors and the target variables. The multiple regressions with

higher correlation value have been considered shown on the table no

12. The higher correlation values were considered for dimension

reduction and the values with low correlation were eliminated. The

following variables having high correlation with values more than 0.5

to 1 were considered Table no 12 shows the values between 0 .5 to

0.7 with higher correlation were considered for step 2. The variables

of talent management are as follows Recruitment and selection,

assessment tools, job fit, performance appraisal, individual

development plan, mentoring, implementation, monitoring,

competency mapping, succession planning are these variables show

correlation values more than 0.5 are treated in the step two processes

are shown in the table no 13.

180 | P a g e

The correlation between dependent variable and independent variable

was determined to reduce the number of variables. The higher

correlation value was considered. These variables are again tested

with the Bivariate correlation with only independent variable to reduce

the number of variables. The variables having low correlation values

were not further considered for factor analysis. The following variables

have been considered for factor analysis: Recruitment and selection,

assessment tools, job fit, performance appraisal, individual

development plan, mentoring, implementation, monitoring,

competency mapping, succession planning are these variables show

correlation values more than 0.3 were treated in the step two

processes are shown in the table no 13. Potential measurement,

ensuring critical retention, general deployment shows low correlation

values were eliminated.

Table no 12: Correlation: Independent variable: Talent Management vs.

Employee engagement:

Value

Asymp. Std. Errora Approx. Tb

Approx. Sig.

R& S

0.463

0.082

3.465

.000c

Assessment tools

0.402

116

3.297

002c

Job fit

0.410

0.105

3.622

.001c

Perf.App 0.430 0.092 3.6529 .001c

idp 0.451 0.133 3.117 .001c

Training 0.563 0.082 4.465 .000c

Implementation 0.362 0.116 2.297 .002c

181 | P a g e

Monitoring

0.547 0.113 4.024 .000c

Potential measurement

0.251 0.133 3.117 .001c

Mentoring and coaching

0.663 0.082 5.465 .000c

Career management

0.247 0.113 4.024 .000c

Ensuring critical

retention

0.282 0.113 3.0377 000c

General deployment

0.212 0.082 1.024 .000c

Succession planning

0.496 0.113 2.0377 000c

The following talent management variables have been considered for

dimension reduction

1. Recruitment & Selection

2. Assessment tools

3. Job fit

4. Training

5. Performance appraisal

6. Personal development plan

7. Mentoring and coaching

8. Implementation

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9. Succession planning

Step 2. These variables were again tested with the Bivariate correlation with

only independent variable to reduce the number of variables. The

variables having low and high correlation values were further

considered for factor analysis thus determining the appropriateness

of the factor analytic model. Similarly Factor analyses have been

used for dimension reduction of Talent management. Variables with

higher values are again tested with the Bivariate correlation with only

independent variables separately excluding the target variable to

guard against multicollinearity. Multicollinearity leads to instability in

the solution space, leading to possible incoherent results. The

predictors if correlated the response surface is unstable, providing

highly variable coefficient estimates with inflated values .To avoid

multicollinearity, it was investigated with the correlation structure

among the predictor variables ignoring the target variable for the

moment. The variables of talent management tools were tested using

Bivariate correlation, to investigate the variable-by-variable

association between the predictors. The pair wise correlation

coefficients among the predictors were applied and noted that those

correlations that were strongest. Table no 13 contains a listing of

the pair wise correlations that are the strongest in absolute value

among the predictors. The variables having low correlation values

and high correlation values were further considered for dimension

183 | P a g e

reduction process thus determining the appropriateness of the factor

analytical model. It showed that the relation between the independent

variables i.e. predictor variables should be. The correlation between

the independent variables values which can be further considered for

dimension reduction. This step has to be followed with the

independent variable with respect to talent management

TABLE NO 13: Correlation: Independent variable: Talent Management

r&s as jf pa idp T mon M Co im sp

R&S 1

Assessment tools 0.263 1

Job fit 0.268 0.32 1

Perf.app .299 .312 .370 1

idp .290 .512 .391 .286 1

Training

.239 .344 .393 .219 .376 1

Monitoring .230 .344 .316 .318 .289 .390 1

Mentoring .236 .234 .281 .268 .289 .290 .239 1

Competency mapping .339 .322 .393 .319 .476 .265 .300 .291 1

implementati

on

.435

.433

.465

.391

.361

.312

.395

.451

0.44

1

Succession planning .230 .344 .316 .338 .289 .300 .322 .306 .302 .312 1

**. Correlation is significant at the 0.01 level (2-tailed).

CHAPTER 13: FACTOR ANALYSIS

184 | P a g e

CHAPTER 13

FACTOR ANALYSIS

13.1. FACTOR ANALYSIS: TESTING OF THE INDEPENDENT

VARIABLES: MANAGERIAL COMPETENCIES

Factor analysis is a data reduction techniques needed to determine the

number of factors that need to extract i.e. used to reduce a large number of

variables to a smaller set of underlying factors that summarize the essential

information contained in the variables.

The main applications of factor analytic techniques are:

1.) To reduce the number of variables and

2.) To detect structure in the relationships between variables

To classify the variables, therefore, factor analysis was applied as a data

reduction or structure detection method (Thurstone, 1931). Already factor

analysis is based on correlation, linearity is important and it is satisfying to go

further with factor analysis which is satisfied with the predictor variables as

shown in the in the chapter no 12. Factor analysis is sensitive to outlying

cases as it was already carried out in the steps of preparing the data for

analysis (refer chapter no 12). Factorability of the correlation matrix was

important. Factor analysis is based on the correlation matrix of the variables

involved, and correlations usually need a large sample size before they

stabilize. Tabachnick and Fidell (2001, page 588) cite Comrey and Lee's

185 | P a g e

(1992) advise regarding sample size: 50 cases is very poor, 100 is poor, 200

is fair, 300 is good, 500 is very good, and 1000 or more is excellent. As a rule

of thumb, a bare minimum of 10 observations per variable is necessary to

avoid computational difficulties. The measures of sampling adequacy with a

measure more than acceptance level of 0.5 should be included in the

analysis. In order to determine sampling adequacy Kaiser –Meyer- Olkin

and Barletts test of spherecity are used to determine the factorability of the

matrix as a whole. Including the original and reproduced correlation matrix,

the scree plot and the plot of the rotated factors are used.

13.1.2. KAISER –MEYER- OLKIN TEST AND BARLETTS TEST:

Kaiser –Meyer- Olkin test was conducted to measure the sampling

adequacy. This measure varies between 0 and 1, and values closer to

1 are better. A value of 0.6 is a suggested minimum. Values of the

KMO statistic was more than 0.60 indicated that factor analysis is

appropriate indicated in the table no 14.

Bartlett's Test of Sphericity: This tests the null hypothesis that the

correlation matrix is an identity matrix that is variables are really

uncorrelated. An identity matrix is matrix in which all of the diagonal

elements are 1 and all off diagonal elements are 0 to reject this null

hypothesis. The statistics reported is the p-value, so that small values

would indicate evidence against the null hypothesis that is variables

are correlated. For p values much smaller than 0.10, there is sufficient

186 | P a g e

evidence that variables are not correlated so factor analysis is suitable.

A minimum standard have been attained taken together, these tests of

Kaiser –Meyer- Olkin test and Bartlett‘s Test of Sphericity. Taken

together, these tests provide a minimum standard which should be

passed before a factor analysis or a principal components analysis.

Table no 14. KMO AND Barletts test provides the results the statistical

tests .The KMO statistic had a value of 0.714 which was not less than

0.5 ,this means that this test does not find the level of correlation to be

too low for factor analysis. The p-value for Barletts test of spherecity

rounds to zero, so that the null hypothesis that no correlation exists

among the variable was rejected .Thus allows to proceed with factor

analysis

Table no 14: KMO AND BARLETTS TEST

Kaiser-Meyer Olkin measure of sampling adequacy:

Managerial Competencies

KMO and Barletts test

Kaiser-Meyer Olkin measure of sampling adequacy

0.714

Barletts test of spherecity

Approx Chi-Square

df

sig

2491.010

1250

.000

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13.1.3. PRINCIPAL COMPONENT ANALYSIS

The table no 15 display the commonality of the items and all the variables

have high commonality. This is the proportion of each variable's variance that

can be explained by the factors. It is also noted as h2and can be defined as

the sum of squared factor loadings for the variables. Principal component

analysis seeks to explain the correlation structure of a set of predictor

variables using a smaller set of linear combination of these variables. These

linear combinations called components. The principal components analysis

will use this correlation structure of the standardized variables to identify a

certain number of independent components. The values in this column

indicate the proportion of each variable's variance that can be explained by

the retained factors. Variables with high values are well represented in the

common factor space, while variables with low values are not well

represented. They are the reproduced variances from the factors that have

been extracted thus extracting the variables were as follows initiative and

innovation, planning and organizing, result orientation, coaching, decision

making, thinking strategically development, and conflict. These values on the

diagonal of the reproduced correlation matrix

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Table No 15: Communalities: Independent Variable: Managerial

Competencies, Extraction Method: Principal Component

Analysis.

Initial extraction

Initiative & innovation 1.000 0.851

Result orientation 1.000 0.835

Coaching 1.000 0.615

Decision making 1.000 0.879

Thinking strategic 1.000 0.879

Development 1.000 0.715

Planning and organizing

1.000 0.755

Conflict 1.000 0.322

1.) Factor

The initial number of factors is the same as the number of variables used in

the factor analysis. However, it showed that not all 8 factors were retained.

2.) Initial Eigen values

Eigen values are the variances of the factors. Factor analysis was conducted

on the correlation matrix, the variables were standardized, which means that

the each variable had a variance of 1, and the total variance was equal to the

number of variables used in the analysis.

3.) Total

This column contains the eigen values. The first factors is accounting for the

most variance and hence have the highest eigen value, and the next factor

will account for as much of the left over variance as it can, and so on. Hence,

each successive factor will account for less and less variance.

4.) % of Variance

189 | P a g e

This column contains the percent of total variance accounted for by each

factor.

5.) Cumulative %

This column contains the cumulative percentage of variance accounted for by

the current and all preceding factors. For example, the third row shows a

value of 81. This means that the first three factors together account for 81 of

the total variance.

Table no16 displays the total variances explained at two stages. At the initial

stages, it shows the factors and their associated eigen values, the percentage

of variances explained with cumulative percentages. In reference to eigen

values, one factor was extracted because they have eigen values greater

than 1. Table no 16 shows the eigen values for each component along with

the percentage variance explained and the cumulative percentages. In

reference to the eigen values, one factor was extracted because they have

eigen values greater than 1. 81.202 percent of the variances have been

explained. The following scree plot graphically displayed the eigen values for

each factor and suggested that there were two predominant factors. Table no

16 shows the eigen values for each component along with the percentage

variance explained and the cumulative percentages. In reference to the eigen

values, one factor was extracted because they have eigen values greater

than 1. 81.202 percent of the variances have been explained.

190 | P a g e

Table no 16: Eigen values and Proportion of Variances:

Managerial Competencies

Extraction Method: Principal Component Analysis.

Compone

nt Initial Eigen values Extraction Sums of Squared

Loadings

Total

% of Variance

Cumulative % Total

% of Variance

Cumulative %

1

4.060 81.202 81.202 4.060 81.202 81.202

2

0.573 7.466 88.667

3 0.207 4.243 92.810

4 0.160 3.142 95.952

5 0.126. 2.100 97.052

6 0.122 1.099 98.151

7 0.111 1.012 99.163

8 0.091 0.937 100.000

13.1.4. Scree plot:

The following scree plot graphically displays the eigen values for each factor

and suggests that there is one predominant factor. It determines and used for

finding an upper bound for the number of components that should be

retained. The scree plot graphs the eigen value against the factor

number. The value in the first columns of the table no 17 shown immediately

above and from the first factor on, can be seen that the line is almost flat,

meaning the each successive factor is accounting for smaller and smaller

191 | P a g e

amounts of the total variance. This is because the first component usually

explains much of the variability, the next shows the moderate amount of

variability. Thus extracting one component showed in table no 17. Factor

analysis of the original -item longitudinal survey revealed strong loadings of 8

variables that are as follows:

Figure No 1: Scree Plot: independent variable: Managerial

Competencies variables

192 | P a g e

Table no17: component matrix: managerial competencies

Component

1

Initiative & Innovation 0.923

Result Orientation 0.914

Coaching 0.784

Decision making 0.938

Thinking strategically 0.938

Development 0.833

Planning and organizing

0.733

Conflict

Extraction Method: Principal Component Analysis. a.) components 1 extracted.

Table No18: extraction of managerial competencies variables

Initiative & Innovation

Result Orientation

Planning and organizing

Coaching

Decision making

Thinking strategically

Development strategically

Factor like conflict was eliminated for further analysis.

193 | P a g e

13.2. FACTOR ANALYSIS STEPS FOLLOWED FOR THE TESTING OF

THE INDEPENDENT VARIABLE: TALENT MANAGEMENT

Factor analysis is a data reduction techniques used to reduce a large number

of variables to a smaller set of underlying factors that summarize the essential

information contained in the variables. Already factor analysis is based on

correlation, linearity is important and it is satisfying to go further with factor

analysis. Factor analysis is sensitive to outlying cases as it has been already

carried out in the steps of preparing the data for analysis. Factorability of the

correlation matrix is important. The measures of sampling adequacy with a

measure more than acceptance level of 0.5 should be included in the

analysis. In order to determine sampling adequacy kaiser –meyer- olkin and

Barletts test of spherecity are used to determine the factorability of the matrix

as a whole.

13.2.1. KAISER MEYER OLKIN AND BARLETTS TEST OFSPHERECITY:

Kaiser Meyer Olkin test: was conducted to measure the sampling

adequacy. Values of the KMO statistic was more than 0.60 indicated

that factor analysis is appropriate indicated in the table no 19

Bartlett's Test of Sphericity: This tests the null hypothesis that the

correlation matrix is an identity matrix that is variables are really

uncorrelated. An identity matrix is matrix in which all of the diagonal

elements are 1 and all off diagonal elements are 0 to reject this null

hypothesis. The statistics reported is the p-value, so that small values

194 | P a g e

would indicate evidence against the null hypothesis that is variables

are correlated. For p values much smaller than 0.10, there was

sufficient evidence that variables were not correlated so factor analysis

was suitable. A minimum standard have been attained considering

these tests of Kaiser –Meyer- Olkin test and Bartlett‘s Test of

Sphericity. Taken together, these tests provide a minimum standard

which was passed before a factor analysis.

Table no 19 Kaiser-Meyer-Olkin and Barletts provides the results of the

statistical tests .The KMO statistic has a value of 0.695 which is more than

0.5 ,this means that this test does not find the level of correlation to be too low

for factor analysis. The p-value for Barletts test of spherecity rounds to zero,

so that the null hypothesis that no correlation exists among the variable was

rejected .Thus allowed to proceed with factor analysis

Table no 19: Kaiser-Meyer-Olkin and Barletts measure of sampling

adequacy: Talent management

Kaiser-meyer-olkin measure of sampling adequacy.

.695

194.032 Bartlett's test of sphericity Approx. Chi-Square

df 1250 Sig. 0.000

195 | P a g e

13.2.2. PRINCIPAL COMPONENT ANALYSIS

The table no 20 displays the commonality of the items and all the variables

have high commonality. This is the proportion of each variable's variance that

can be explained by the factors. It is also noted as h2and can be defined as

the sum of squared factor loadings for the variables. Principal component

analysis seeks to explain the correlation structure of a set of predictor

variables using a smaller set of linear combination of these variables. These

linear combinations called components. The principal components analysis

will use this correlation structure of the standardized variables to identify a

certain number of independent components. The values in this column

indicate the proportion of each variable's variance that can be explained by

the retained factors. Variables with high values are well represented in the

common factor space, while variables with low values are not well

represented. They are the reproduced variances from the factors that have

been extracted thus extracting the variables. The table no 20 displays the

commonality of the items and all the variables have high values but show

lower values that are assessment tool, implementation.

Table No 20: Communalities: Independent Variable: Talent management

Communalities

Initial extraction

R&S 1.000

0.962

Assessment tool 1.000 0.322

Jobfit 1.000 0.885

Pefapp 1.000 0.679

idp 1.000 0.801

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Training and guidance

1.000 0.653

Implementation 1.000

0.333

Monitoring 1.000 0.632

Comp Mapping 1.000 0.477

Succession planning 1.000 0.730

Extraction Method: Principal Component Analysis. 1.) Factor

The initial number of factors is the same as the number of variables used in

the factor analysis. However, it showed that not all 10 factors were retained.

2.) Initial Eigen values

Eigen values are the variances of the factors. Factor analysis was

conducted on the correlation matrix, the variables are standardized, which

means that the each variable had a variance of 1, and the total variance is

equal to the number of variables used in the analysis.

3.) Total

This column contains the eigen values. The first factor will always account for

the most variance and hence have the highest eigen value, and the next

factor will account for as much of the left over variance as it can, and so

on. Hence, each successive factor will account for less and less variance.

4.) % of Variance

This column contains the percent of total variance accounted for by each

factor.

5.) Cumulative %

197 | P a g e

This column contains the cumulative percentage of variance accounted for by

the current and all preceding factors. For example, the third row shows a

value of 66. This means that the first three factors together account for 66 of

the total variance.

Table no 21 displays the total variances explained at two stages. At the initial

stages, it shows the factors and their associated eigen values, the percentage

of variances explained with cumulative percentages. In reference to eigen

values, two factors were extracted because they have eigen values greater

than 1. Table no 21 which shows the eigen values for each component along

with the percentage variance and the cumulative percentages. In reference to

the eigen values, two factors have been extracted because they have eigen

values greater than 1. 66 percent of the variances have been explained. The

following scree plot graphically displays the eigen values for each factor and

suggests that there were two predominant factors. Table no 21 which shows

the eigenvalues for each component along with the percentage variance

explained and the cumulative percentages. In reference to the eigen values,

one factor has been extracted because they have eigen values greater than

1. 66 percent of the variances have been explained. Table no 21 displays the

total variances explained at two stages. At the initial stages, it shows the

factors and their associated eigen values, the percentage of variances

explained with cumulative percentages. In reference to eigen values, two

factors were extracted because they have eigen values greater than 1. Table

no 21 which shows the eigen values for each component along with the

198 | P a g e

percentage variances and the cumulative percentages. In reference to the

eigen values, two factors have been extracted because they have eigen

values greater than 1. 66 percent of the variances have been explained. The

following scree plot graphically displays the eigen values for each factor and

suggests that there were two predominant factors. Table no 22 shows

component matrix .The factors were extracted with those variables which

gives values more than 0.4. Thus after factor reduction of managerial

competencies and talent management, further analysis have been carried out

to determine the objectives.

Table no 21: Eigen values and Proportion of Variances: Talent

Management: Extraction Method: Principal Component

Analysis

Component

Initial Eigen values Extraction Sums of Squared Loadings

Total

% of Variance

Cumulative % Total

% of Variance

Cumulative %

1 4.225 52.809 52.809 4.225 52.809 52.809

2 1.075 13.442 66.251 1.075 13.442 66.251

3 .961 12.012 78.263

4 .720 9.001 87.264

5 .597 7.467 94.731

6 .205 2.560 97.291

7 .136 1.695 98.986

8 .081 1.014 100.000

.

13.2.3. Scree plot:

The following scree plot graphically displays the eigen values for each factor

and suggests that there is one predominant factor. It determines and used for

finding an upper bound for the number of components that should be

199 | P a g e

retained. The scree plot graphs the eigen value against the factor

number. The value in the two columns of the table no 21 shown immediately

above and from the first factor on, can be seen that the line is almost flat,

meaning the each successive factor is accounting for smaller and smaller

amounts of the total variance. This is because the two components usually

explains much of the variability, the next shows the moderate amount of

variability. Thus extracting two components shown in table no 22.Factor

analysis of the original 10-item longitudinal survey revealed strong loadings of

8 variables that are as follows:

1. Recruitment & selection

2. Job fit

3. Performance appraisal

4. Individual development plan

5. Training & guidance

6. Monitoring

7. Competency mapping

8. Succession planning

Factors like assessment tools and implementation were eliminated for

further analysis.

200 | P a g e

Figure no 2: Scree Plot: Independent variable :Talent management

Table no 22: component matrix: managerial competencies

Component Matrixa

Component 1 Component 2

R & S .403

Assessment tool

Job fit .939

Performance appraisal .823

IDP .885

Training & Guidance .797

Monitoring

.761

Implementation

Competency mapping .686

Succession planning .854

Extraction Method: Principal Component A

a) 2 Components extracted.

CHAPTER 14: DATA ANALYSIS AND FINDINGS

201 | P a g e

CHAPTER 14

DATA ANALYSIS AND FINDINGS

14. a. Differences of employee engagement levels, talent management

and managerial competencies between private and multinational

IT companies.

To find the differences of employee engagement levels, talent management

and managerial competencies between Private and Multinational IT

companies. In order to find the above objective, it was fragmented in to three

different objectives

14.1. To find the differences of employee engagement between Private and

Multinational IT companies

14.2. To find the differences of talent management between Private and

Multinational IT companies

14.3. To find the differences of managerial competencies between Private

and Multinational IT companies.

The performance of the multinational and private companies of the IT sector

depends on the employee engagement. So it was important to identify the

differences between employee engagement in Private and Multinational IT

companies. To find out the differences of employee engagement between

202 | P a g e

Private and Multinational IT sector. The data‘s of employee engagement for

the private and multinational IT sectors have been computed separately and

run on statistical tool ANOVA in order to find the differences. The hypothesis

was formulated as follows.

14.1.1. HYPOTHESIS

H0: There are no significant differences between employee

engagement in the Private and Multinational companies of IT

sector

H1: There are significant differences between employee

engagement in the Private and Multinational companies of

IT sector

The data analysis conducted for this study included an analysis of variance

(ANOVA) to compare employee engagement in Private and MNC IT sector.

The dependent variable was the employee engagement. The independent

variables were the two samples Private company and Multinational IT

companies.

In order to determine the analysis of an independent group and to detect the

difference in group means. Therefore the above differences was determined

by using ANOVA but there were preconditions to be fulfilled where the

samples were independently and randomly selected from the population with

normal distribution. The data analysis conducted for this study included an

analysis of variance (ANOVA) to compare engagement levels in the two

203 | P a g e

samples. In order to verify the assumption of homogeneity of variance

central to ANOVA (Mertler & Vannatta, 2005) the Levene‘s test of equality of

error variances were run. Levene‘s results showed whether it is significant or

not significant.

Table no 23 shows homogeneity assumption has not been violated. Levens

test for homogeneity of variance is not significant (p>.01) and therefore

population variances for each group are approximately equal.

Table no 23 : Test of homogeneity of variances for employee

engagement

Levens Statistic

df1 df2 Sig.

0.125 1 1249 0.01

Table no 24 reviews means, standard deviations, minimum and maximum

levels for each sample for the variable employee engagement. This table

provides the mean and standard deviation for the groups that have been split

by both independent variables. In addition, the table also provides "Total"

rows, which allows means and standard deviations for groups only split by

one independent variable. The mean of the variable that was employee

engagement in Private and MNC were 35.55 and 44.60 respectively with

standard deviation 5.236 and 6.261 .The mean of the dependent variable

differs significantly which was statistically significantly different in Private and

Multinational IT sector.

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Table no 24 : Descriptive Statistics of Employee engagement

sector

N

Mean

Std. Dev

Std. Error

95% Confidence Interval for Mean

Min

Max

Lower Bound

Upper bound

private 600 33.5 5.23 1.171 31.10 36.00 25 45

MNC 650 40.6 6.26 1.400 37.67 43.53 29 47

Total 1250 37.0 6.72 1.063 34.92 39.23 25 47

Table no 25 shows to determine whether F-ratio is significant, with a degree

of freedom (dfs) (1, 1249) FOBS = 14. 922 is greater than FCRIT = 6.851.

F (1, 1249) =14.922, P< 0.01, given that p < 0.01, null hypothesis was

rejected. This shows that there were significant differences between

employee engagement in MNC and private IT industries.

Table no 25: ANOVA test on employee engagement MNC and

Private IT sector

Sum of

Squares df

Mean Square

F

SIG

Between Groups 497.025 1 497.025 14.922 0.01

Within Groups 1265.750 1249 33.309

Total 1762.775 1250

14.1.3. PLOTS

A schematic view of the data makes it much easier to decipher where the

significant main effects and interactions may lie. Even if the results are not

205 | P a g e

statistically significant, a plot will show the pattern of results, which can be just

as informative as the statistical findings reporting of exact significance levels.

By examining the absolute differences, there was a difference where the

mean score of MNC for the variable employee engagement was 41 which

were more than the mean of private sector with the mean value of 34.

Figure no 1: Graph of mean of Employee engagement & private,

MNC

F (1, 1249) =14.922, P< 0.01, given that p < 0.01, null hypothesis was

rejected This shows that there were significant differences between

employee engagement in MNC and private sector of IT industries The result

showed that there was a significant difference in engagement levels between

multinational IT sectors than private sector .It was observed that multinational

206 | P a g e

employees were more physically, emotionally and cognitively engaged than

private sector. Thus it was observed that there were differences in

engagement level between MNC and Private IT Company that is MNC shows

more Engagement level than Private sector. It shows that there were

significant differences between employee engagement in the Private and

Multinational IT sector. The alternate hypothesis was accepted. Since there

were differences in Target variable it was important to identify which

Predictor variables affect the values of the target that is, talent management

or managerial competencies among Private and Multinational IT companies

14.2. The difference of talent management between Private and

Multinational IT companies

It was been observed that there were differences in the employee

engagement between the Private and multinational IT sectors so it is

important to derive and find out the reasons for the differences considering

talent management as the variable. It was necessary to identify the

differences of talent management between Private and Multinational IT

sector. The data‘s of talent management for the private and multinational IT

sectors have been computed separately and were run on statistical tool

ANOVA in order to find the differences. The hypothesis framed as follows.

14.2.1. HYPOTHESIS

H02: There are no significant differences between talent management in

private and Multinational IT industries

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H12: There are significant differences between talent management

in Private and Multinational IT industries

The hypothesis have been tested using statistical tool analysis of variance

(ANOVA) to compare talent management between multinational and private

IT sectors. The dependent variable was talent management. The independent

variables were the two samples Private and Multinational IT companies. In

order to determine the analysis of an independent groups to detect the

difference in group means. Therefore the above differences were determined

by using ANOVA but there were preconditions to be fulfilled where the

samples were independently and randomly selected from the population with

normal distribution. The data analysis conducted for this study included an

analysis of variance (ANOVA) to compare the talent management in the MNC

and Private IT sector. In order to verify the assumption of homogeneity of

variance central to ANOVA (Mertler & Vannatta, 2005) the Levene‘s test of

equality of error variances was run. Levene‘s results showed either

significance or non significance. Table no 26 shows homogeneity assumption

and indicated it was not violated. Levens test for homogeneity of variance is

not significant (p>.01) and therefore population variances for each group are

approximately equal.

Table no 26: Test of homogeneity of variances for talent management

Levens Statistic

df1 df2 Sig.

0.125 1 1249 0.01

208 | P a g e

Table no 27 reviews mean, standard deviations, minimum and maximum

levels for each sample for the Variable talent management. This table is very

useful as it provides the mean and standard deviation for the groups that

have been split by both independent variables. In addition, the table also

provides "Total" rows, which allows means and standard deviations for

groups only split by one independent variable. The mean of the variable that

was talent management in private and MNC were 54.25 and 61.65

respectively with standard deviation 4.643 and 5.982 .The mean of the

dependent variable differs significantly which was statistically significantly

different in Private and MNC sector

Table no 27 : Descriptive Statistics of talent management

sector

N

Mean

Std. Dev

Std. Error

95% Confidence Interval for Mean

Min

Max

Lower Bound

Upper bound

private 600

54.25 4.643 1.038 52.07 56.4 41.00 60.00

MNC 650

61.65 4.804 1.0742 59.40 63.89 50.00 67.00

Total 1250

57.95 5.982 0.945 56.0367 59.8633 41.00 67.00

Table no 28 shows to determine whether F-ratio is significant, with a degree

of freedom (df) (1, 1249) FOBS = 24. 530 is greater than FCRIT = 6.851.

209 | P a g e

F (1, 1249) = 24.530, P< 0.01, given that p < 0.01, null hypothesis was

rejected. This showed that there were significant differences between talent

management in MNC and Private sector of IT industries.

Table no 28: ANOVA test: talent management, MNC Private IT sector

Sum of

Squares df

Mean Square

F

SIG

Between Groups 547.600

1 547.600 24.530 .000

Within Groups 848.300

1249 22.324

Total 1395.900 1250

14.2.2. PLOTS

A schematic view of the data makes it much easier to decipher where the

significant main effects and interactions may lie. Even if the results are not

statistically significant, a plot will show the pattern of results, which can be just

as informative as the statistical findings reporting of exact significance levels.

By examining the absolute differences, there was a difference where the

mean of MNC for the variable talent management showed the mean value of

61 which indicated that it was more than the mean of private sector with a

mean value of 54.25.

210 | P a g e

Figure no 3: Graph of mean of talent management

The further result showed that there were differences in the talent

management between MNC and Private IT sector. It showed the talent

management was more prominent in Multinational Company than private

sector. F (1, 1249) = 24.530, P< 0.01, given that p < 0.01, null hypothesis

was rejected .This shows that there were significant differences between

talent management in MNC and private sector of IT industries .The findings

denotes that alternate hypothesis was accepted. It shows there were

significant differences between talent management in the Private and

Multinational IT companies.

211 | P a g e

14.3.1. The differences of managerial competencies between Private

and Multinational IT companies

The result showed there were differences in the employee engagement level

in the Private and MNC of IT sector. From the above set objective also

showed differences in talent management also. So it is important to derive

and find out the differences in the other dependent variable considering

managerial competencies as the variable. Hence it is important to find out the

differences of managerial competencies between Private and Multinational IT

sector. The data‘s of managerial competencies for the private and

multinational of IT sectors were computed separately and was run on

statistical tool ANOVA to find the differences

14.3.2. HYPOTHESIS

H03: There are no significant differences between managerial

competencies in private and Multinational IT industries

H13: There are significant differences between managerial

competencies in private and Multinational IT industries

The data analysis conducted for this study included an analysis of variance

(ANOVA) to compare managerial competencies in MNC and private IT

Companies. The dependent variable was managerial competencies and the

independent variables were the two samples Private and multinational IT

companies. In order to determine the analysis of an independent groups to

212 | P a g e

detect the difference in group means. Therefore the above differences can be

determined by using ANOVA but there were preconditions to be fulfilled

where the samples were independently and randomly selected from the

population with normal distribution. The data analysis conducted for this study

included an analysis of variance (ANOVA) compare managerial competencies

in the two samples. In order to verify the assumption of homogeneity of

variance central to ANOVA (Mertler & Vannatta, 2005) the Levene‘s test of

equality of error variances helps to identify the significance and non

significance. Table no 29 shows homogeneity assumption has not been

violated. Levens test for homogeneity of variance is not significant (p > 0.01)

and therefore population variances for each group are approximately equal.

Table no 29: Test of homogeneity of variances for managerial

competencies

Levens Statistic

df1 df2 Sig.

2.852 1 1249 0.01

Table no 30 reviews mean, standard deviations, minimum and maximum

levels for each sample for the Variable managerial competencies. This table

is very useful as it provides the mean and standard deviation for the groups

that have been split by both independent variables. In addition, the table also

provides "Total" rows, which allows means and standard deviations for

groups only split by one independent variable. The mean of the variable that

was managerial competencies in private and MNC were 35.05 and 47.75

213 | P a g e

respectively with standard deviation 11.49 and 13.36. The mean of the

dependent variable differs significantly which was statistically significantly

different in Private and Multinational IT Industries

Table no 30 : Descriptive Statistics of managerial competencies

sector

N

Mean

Std. Dev

Std.

Error

95% Confidence Interval for Mean

Min

Max

Lower Bound

Upper bound

private 600

35.05 11.49 2.5705 29.6698 40.4302 21.00 56.00

MNC 650

47.75 13.36 2.9884 41.4951 54.0049 29.00 67.00

Total 1250

Table no 31 shows to determine whether F-ratio is significant, with a degree

of freedom (dfs) (1, 1249) FOBS = 10.380 is greater than FCRIT = 6.851.

F (1, 1249) =10.380, P< 0.01, given that p < 0.01, null hypothesis was

rejected. This shows that there were significant differences between talent

management in MNC and private IT industries.

214 | P a g e

Table no 31: ANOVA test: managerial competencies, MNC, Private IT Company

Sum of

Squares df

Mean Square

F

SIG

Between Groups 1612.900

1 1612.900 10.380 0.01

Within Groups 5904.700

1249 155.387

Total 7517.600 1250

14.2.3. PLOTS

A schematic view of the data makes it much easier to decipher where the

significant main effects and interactions may lie. Even if the results are not

statistically significant, a plot will show the pattern of results, which can be just

as informative as the statistical findings reporting of exact significance levels.

By examining the absolute differences there was a difference where the mean

score of MNC for the variable managerial competencies showed 47.75 which

was more than the mean of private sector with the mean score of 35.05

215 | P a g e

Figure No 5 : Graph of mean of managerial competencies, pvt, MNC

The study helped to analyse the differences of managerial competencies

among Private and Multinational IT companies. There were significant

differences between managerial competencies in private and multinational

companies. The mean scores of managerial competencies were more in

MNC than Private IT sector. Table no 31 shows to determine whether F-ratio

is significant, with a degree of freedom (dfs) (1, 1249) FOBS = 10.380 is

greater than FCRIT = 6.851. F (1, 1249) =10.380, P< 0.01, given that p < 0.01,

null hypothesis was rejected .This shows that there were significant

differences between managerial competencies in MNC and private IT

industries.

216 | P a g e

The alternate hypothesis was accepted. There were significant differences

between managerial competencies in Private and Multinational IT industries.

14.4. The relationship between talent management and managerial

competencies on the levels of employee’s engagement in the

multinational IT companies

The result showed that there were differences in the employee engagement,

talent management tools and managerial competencies between private and

multinational IT industries by using statistical tool ANOVA hence the further

research was carried out to identify the relation between talent management

and managerial competencies on the levels of employees engagement in the

Multinational IT companies .The hypothesis formulated as follows:

14.4.1. HYPOTHESIS

H04: There are no significant relations between the Talent management

Managerial competencies and employee engagement in the

Multinational IT industries

H14: The Talent management and managerial competencies have

significant relations on the levels of employee engagement in

the Multinational IT industries

In order to find the above hypothesis, Pearson Correlation analysis was run to

identify the relationship between talent management, managerial

competencies on employee engagement in the multinational IT industries.

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The Means, standard deviations, for each talent management, managerial

competencies and for engagement are listed on Table 32. The mean score

for Talent management was 62 for employee engagement showed 41 and

managerial competencies indicated 48.

Table no 32: Descriptive statistics: talent management, Managerial

Competencies and engagement for MNC

Mean Std. Deviation N

Talent management

62 8.587 600

engagement level

41 6.697 600

managerial competencies

48 7.411 600

Table no 33 shows the relationship between talent management, managerial

competencies on employee engagement in the Multinational IT industries.

Table no 33 summarizes Pearson Correlation results. The result helps to

indicate the relationship between talent management, managerial

competencies on employee engagement in the Multinational IT industries

218 | P a g e

Table no 33: Pearson Correlation talent management, managerial

competencies on employee engagement in the

multinational IT industries

Talent managem

ent

eng Managerial

Competencies

Talent management Pearson Correlation

Sig. (2-tailed)

N

1

0.813*

0.709**

.000 0.000

600 600 600

employee engagement Pearson Correlation

Sig. (2-tailed)

N

0.813*

1

0.788**

.000 .000

600 600 600

managerial competencies Pearson Correlation Sig. (2-tailed) N

0.709** 0.788** 1

.000 .000

600 600 600

From the results showed that there were differences in engagement level,

talent management and managerial competencies between MNC and Private

sector which showed mean scores of engagement level, talent management

and managerial competencies more than Private sector. Since there were

differences in Target variable it was important to find which Predictor

variables affect the values of the target. Table no 33 summarizes Pearson

Correlation results. The result indicated the positive relationship between

talent management, managerial competencies on employee engagement in

the multinational IT industries. The alternate Hypothesis was accepted that it

was observed that there were direct link between Talent Management and

219 | P a g e

Managerial competencies on the Employee engagement in the Multinational

IT Company.

14.5. Effect of talent management, managerial competencies on

employee engagement in the Multinational IT industries.

The results of table no 33 showed a positive relationship so the further

analysis of data‘s helps to identify the effect of talent management,

managerial competencies on employee engagement in the multinational IT

industries. The data‘s were run on Multiple regression considering the talent

management, managerial competencies and employee engagement data‘s

and were computed separately in the software SPSS 18 .The hypothesis was

framed as:

14.5.1. HYPOTHESIS

H05: There are no significant effect between the Talent management,

Managerial competencies and employee engagement in the

multinational IT industries

H15: The Talent management and managerial competencies have

significant effect on the levels of employee engagement in

the multinational IT industries

The hypothesis was tested using multiple regressions as the statistical tool.

Employee Engagement was the dependent variable and the talent

management and managerial competencies were the independent variables.

220 | P a g e

Mertler and Vannatta (2005) recommended that multivariate normality and

linearity were tested prior to running and interpreting a multiple regression

analysis. In order to assess normality, used SPSS chart generation feature to

test the samples for linearity in Appendix V (Figure A-1), a scatter plot of

standardized predicted values by standardized residuals was generated. The

resulting image was rectangular in shape with scores concentrated in the

middle. The scatter plot is included in Appendix VI (see Figure A-2). The

image supports a linear relationship between the variables (Mertler &

Vannatta, 2005). Since the basic assumptions of normality and linearity were

met, multiple regression using the ―forward‖ method. A summary of the

regression model is presented in Table 34. Regression results indicated an

overall model of two predictors talent management and managerial

competencies that significantly predicts engagement, R2 = 0.737, R2adj =

0.727, F (1, 650) =0.515, p < 0.05. Both the independent variables together

explain the 73% of the variance (R square) in talent management and

managerial competencies which is highly significant, as indicated by the F-

value of 0.515 in the table no 35

Table no 34: Model summary: talent management, managerial

competencies on Employee engagement in the

multinational IT industries

Model

R R Square

Adjusted R

Square

Std. Error of

the Estimate

1 0.815a 0.737 0.727 6.727

221 | P a g e

Table no 35: ANOVA TEST: talent management, managerial

competencies on Employee engagement in the

multinational IT industries

Model Sum of

Squares df

Mean

Square F Sig.

Regression 307.301 649 30.730 .515 .005

Total 367.000 650

a. Predictors: (Constant), talent management, managerial competencies

b. Dependent Variable: engagement

Table no 34. showed Regression results indicated an overall model of two

predictors talent management and managerial competencies that significantly

predicted employee engagement, R2 = 0.737, R2adj = 0.727, F (1, 600) =0.515,

p < 0.05.Both the independent variables together explained the 73% of the

variance (R square) in talent management and managerial competencies

which was highly significant, as indicated by the F-value of 0.515 in the table

no 35

Regression results indicated an overall model of two predictors, talent

management and managerial competencies that significantly predicted

employee engagement in MNC IT sector. This shows that in MNC, the talent

management tools are effectively applied with the managerial competencies

which lead to employee engagement. The alternate hypothesis was accepted

222 | P a g e

14.6. Relationship of talent management, managerial competencies on

employee engagement in the Private IT industries

The results of table no 39 showed a positive relationship of talent

management, managerial competencies on employee engagement in the

MNC IT industries. The further analysis need to identify the relationship of

talent management, managerial competencies on employee engagement in

the Private IT industries. In order identify the relationship in the private sector

the hypothesis was formulated as follows:

14.6.1. HYPOTHESIS

H06: The Talent management and managerial competencies have no

significant relation on the levels of employee engagement in the

private IT companies

H16: The Talent management and managerial competencies have

significant relation on the levels of employee engagement in

the private IT companies

The data‘s were run on Pearson correlation considering the talent

management, managerial competencies and employee engagement and

were computed separately in the software SPSS 18. The computed scores of

talent management, managerial competencies and employee engagement

were further categorized in to high scores and low scores. The score values

with less than 25 was low Talent management and the score values with

more than 26 were considered as high talent management. Table no 36

223 | P a g e

shows Pearson correlation and was conducted to find the above objective.

Employee Engagement was the dependent variable and the talent

management and managerial competencies were the independent variables.

Table no 36 tried to show the relationship between talent management,

managerial competencies on employee engagement in the private IT

industries. Table no 36 summarizes Pearson Correlation results. The result

indicated the negative relationship between low scores of talent management

with the employee engagement in the private IT industries but showed

positive relation with the disengaged employees. The high scores of talent

management showed a significant positive relation with engaged employees

but negative correlation with the disengaged employees. Similarly the result

indicated negative relationship between low scores of managerial

competencies with the employee engagement in the private IT industries but

showed positive relation with the disengaged employees. The high scores of

managerial competencies showed a significant positive relation with engaged

employees but negative correlation with the disengaged employees. There

was significant relationship between Talent management and employee

engagement. There was significant relationship between managerial

competencies and Employee engagement. The alternate hypothesis was

accepted. The Talent management and managerial competencies have a

significant relation on the levels of employee engagement in the Private

sector IT companies.

224 | P a g e

Table no 36: Pearson Correlation talent management, managerial

Competencies on employee engagement in the Private

IT industries

enga

ged

diseng

aged

High

Talent

mgt

Low

Talen

t mgt

High

Managerial

competencie

s

Low

Manag

erial

compe

tencie

s

Engaged

1.000 -0.816 0.896 -0.818 0.885 -0.744

Disengaged

-.816 1.000 -0.690 0.994 -0.690 0.702

High talent

management 0.896 -.690 1.000 -0.681 0.990 -0.845

Low talent

management -.818 0.994 -0.681 1.000 -0.681 0.675

High

managerial

competencies

0.885 -.690 0.990 .681* 1.000 -0.845

Low managerial

competencies -.744 0.702 -0.845 0.675* -0.845 1.000

Sig. (2-tailed) =0.000 , N=600

14.7. Associations and relations of talent work force planning, talent

acquisition, talent measurement ,talent development, talent

retention scores and the levels of employee engagement in the

Private sector IT industries.

225 | P a g e

The difference in the mean of talent management in Multinational IT

companies was more than the private IT sector. Low scores of talent

management with the employee engagement in the private IT industries

showed negative relation but showed positive relation with the disengaged

employees. The high scores of talent management showed a significant

positive relation with engaged employees but negative correlation with the

disengaged employees. Similarly the result indicated negative relationship

between low scores of managerial competencies with the employee

engagement in the private IT industries but showed close and positive relation

with the disengaged employees. The high scores of managerial competencies

show a significant positive relation with engaged employees but negative

correlation with the disengaged employees. There was a significant

relationship between high scores and low scores of managerial competencies

and Employee engagement and disengagement and similarly there is a

significant relationship between high scores and low scores of Talent

management with Employee engagement and disengagement and also there

were differences in the talent management tools and employee engagement

in MNC and private sector so it was important to identify the factors of talent

management affecting the employee engagement and disengagement in

private IT sector. The further study helped to identify the association between

the talent management tools which were extracted through factor analysis

(refer table no 22) with employee engagement. For the preparation of chi-

square and correlation analysis the data‘s for talent management were binned

226 | P a g e

with the standardized results for the factors of talent management that were

work force planning, talent acquisition, talent measurement, talent

development, talent retention for each factors they were further categorized

as recruitment and selection, job fit, performance appraisal, training and

development, competency mapping, succession planning (refer pg 51). For

employee engagement, levels were created with engaged and disengaged.

The cut off points for each category were taken from the WPB5 Professional

Manual (Howard & Howard, 2001b) and from the Cristina de Mello e Souza

Wildermuth, 2008 for the employee engagement. Table no 37 shows the

association and significant relation of talent management tools with the

engagement levels in the private sector chi-square and correlation were used.

The talent work force planning, talent acquisition, talent measurement, talent

development, talent retention with high and low scores of each factors

categorized as recruitment and selection, job fit, performance appraisal,

training and development, competency mapping, succession planning helped

to identify an association and significant relation between engaged and

disengaged employees. The hypothesis framed as follows:

14.7.1. HYPOTHESIS

H07: There are no significant associations and relations of talent workforce

planning, talent acquisition, talent measurement, talent development,

talent retention scores and the levels of employee engagement in the

Private IT industries.

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H17: There are significant associations and relations of talent

planning, talent acquisition, talent measurement, talent

development, talent retention scores and the levels of employee

engagement in the Private IT industries

Table no 37: Chi square independent variable talent management and

employee engagement

TALENT MGT TOOLS

E DE ENGAGED sig

DISENGAGED sig

1 R&S

HIGH A NA p<0.01=1.1 df1

P >0.50=2.139 df1

LOW NA A P>.20=1.54 df1

P<0.50=1.7866 df3

2 Jobfit

High A NA P<.05=1.20 df1

P>0.I=3.566 df2

Low NA A P>.05=5.118

P<0.5=2.421 df3

3 Perf app

High A NA P<.30=.750 Df1

P>0.10=3.733 df2

Low NA A p>.10=2.40 df1

P<0.10=1.200 df1

4 Idp

High A NA P<.30=0.75 df1

P>.50=2.880 Df4

Low NA A P>.1=2.400 P<.20=9.714 df6

5 T&G

High A NA P<.30=1.15 df1

P>.50=3.880 df4

Low NA A P>.05=2.917

P<.05=6.679 df2

6 Monitoring

High A NA P<.001=1.7 df4

P>.001=2.744 df1

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Low NA A P>.01=2.74 df1

P<.01=12.571 df3

7 Competency

mapping

High A NA P<.01=1.94 df1

P>.01=2.744 df1

Low NA A P>.30=.750 df1

P<.01=5.512 df1

8 S p

High NA NA P<.01=1.744

df1

P>.01=2.944 df1

LOW NA A P<.50=.194 df1

P<.01=13.90 df2

NOTE:

1. CREL:CORELATION 2. R&S:RECRUITMENT AND SELECTION 3. JOBFIT: JOB FIT 4. PERF APP: PERFORMANCE APPRAISAL 5. IDP: INDIVIDUAL DVELOPMENT PLAN 6. T&G: TRAINING AND GUIDANCE 7. MONITERING: MONITERING 8. COMP MAPP:COPETENCY MANPPING 9. S &PLANNING: SUCCESSION PLANNING 10. NA: NO ASSOCIATION 11. A: ASSOCIATION

12. df: degree freedom

Table no 38: correlations: talent management on the engagement levels

TALENT MGT TOOLS

E DE ENG DENG

1 R&S

HIGH R NR 0.810 -0.323

LOW NR R -0.375 0.495

2 JOBFIT

HIGH R NR 0.436 -0.562

LOW NR R -0.553 0.477

229 | P a g e

3 PERF APP

HIGH R NR 0.555 -0.677

LOW NR R -0.632 NR

4 IDP

HIGH R NR 0.500 -0.380

LOW NR R -0.355 0.411

5 TRAINING

HIGH R NR 0.645 -0.539

LOW NR R -0.645 0.539

6 MONITERING

HIGH R NR 0.455 -566

LOW NR R -0.524 0.361

7 COMP MAPP

HIGH R NR 0.677 -0.344

LOW NR R -0.530 0.553

8 S & PLANNING

HIGH NR NR 0.555 -0.66

LOW NR R -0.239

0.385

NOTE:

1. CREL:CORRELATION 2. R&S:RECRUITMENT AND SELECTION 3. JOBFIT: JOB FIT 4. PERF APP: PERFORMANCE APPRAISAL 5. IDP: INDIVIDUAL DVELOPMENT PLAN 6. T&G: TRAINING AND GUIDANCE 7. MONITERING: MONITERING 8. COMP MAPP:COPETENCY MANPPING 9. S &PLANNING: SUCCESSION PLANNING 10. df: degree freedom 11. NR: NEGATIVE RELATION 12. R: RELATION

230 | P a g e

The result showed that talent management tools ie recruitment and selection,

job fit, performance appraisal, training & coaching, individual development

plan, monitoring, competency mapping, succession planning were considered

for finding the associations between talent management variables with the

engagement levels. It was observed that the talent management tools

showed significant association between levels of employee engagement

.Thus low scores of talent management tools like recruitment and selection,

job fit, Performance appraisal, training & coaching, individual development

Plan, monitoring, competency mapping, succession planning showed a

significant association and direct link with the disengaged employees. The

high scores of talent management scores that is talent work force planning,

talent acquisition, talent measurement, talent development, talent retention

scores and the levels of employee engagement in the Private IT industries

with the sub factors as follows were recruitment and selection, job fit,

Performance appraisal, training & coaching, IDP, monitoring, competency

mapping and succession planning showed a significant association and direct

link with the engaged employees. The alternate hypothesis was accepted.

This showed that there were significant association and relation of talent

planning, talent acquisition, talent measurement, talent development, talent

retention scores and the levels of employee engagement in the Private IT

industries

231 | P a g e

14.8. The association between Managerial competencies and levels of

Employee engagement in the Private IT companies.

There was a significant difference in managerial competencies and employee

engagement between MNC and Private IT companies. It was important to

identify the association between factors of managerial competencies which

were extracted through factor analysis (refer table no 17) with employee

engagement. For the preparation of chi-square and correlation analysis the

data‘s of managerial competencies were binned with the standardized results

for the factors of managerial competencies were created with ―high,‖ ―and

―low‖ categories for each factor i.e. Initiative and innovation, Planning and

organizing, Result orientation, Coaching, Decision making, Thinking

strategically with the engagement levels in the private sector. For employee

engagement levels were created with engaged and disengaged employees.

The cut off points for each category were taken from the WPB5 Professional

Manual (Howard & Howard, 2001b) and from the Cristina de Mello e Souza

Wildermuth, 2008 for the employee Table no 39 shows the association and

significant relation of factors or components of managerial competencies

that are Initiative and innovation, planning and organizing, Result orientation,

Coaching, Decision making, Thinking strategically with the engagement levels

in the Private sector.

Chi-square and correlation were used to understand the association of

managerial competencies with the sub factors included were Initiative and

innovation, Planning and organizing, Result orientation, Coaching, Decision

232 | P a g e

making, Thinking strategically with the high and low scores and the levels of

employee engagement

14.8.1. HYPOTHESIS

H08: There are no significant associations and relations between scores

of Managerial competencies and levels of employee engagement in

the Private sector

H18: There are significant associations and relations between scores

of Managerial competencies and levels of employee

engagement in the Private sector

The hypothesis was tested using chi-square to determine the association

between Managerial competencies and levels of employee engagement.

Table no 39: chi-square on managerial competencies on

Employee engagement levels

Managerial competencies

E DE ENGAGED sig

DISENGAGED sig

1 Initiative and innovation

High A NA P<.10=15.412

df1

P>.01=5.412 df1

Low NA A P>.50=6.00 df1

P<0.10=12.07 df6

2 Result orientation

High A NA P<.01=3.412

df1

P>.01=2.412 df1

Low NA A P>0.70=9.17 P<0.70=0.313

233 | P a g e

df2 df2

3 Coaching

High A NA P<0.70=10.17 df2

P>0.50=4.837 df2

Low NA A P>0.80=0.116 df2

P<0.50=5.083 df3

4 Decision making

High A NA P<.01=5.412

df1

P>.01=1.112 df1

Low NA A P>0.60=O.917 df2

P<0.10=13.07 df6

5 Thinking strategy

High A NA P<.01=1.412

df1

P>.01=1.112

df1

Low NA A P>0.60=2.517 df2

P<0.10=14.07 df6

Note: NA: NO ASSOCIATION, A: ASSOCIATION, df: degree freedom

Table no 40: Correlation on managerial competencies on Employee

Engagement levels

Managerial competencies

Engaged Dis Engaged

Engaged DIS ENGAGED

1 Initiative and innovation

High R NR 0.321 -0.213

Low NR R - 0.451 0.851

2 Result orientation

High R NR 0.251

-0.234

Low NR R -0.221 0.333

3 Coaching

High R NR 0.389

-0.300 low

234 | P a g e

Low R R -0.33 low

0.381

4 Decision making

High R NR 0.492 -0.222

Low NR R -0.291 0.345

5 Thinking strategically

High R NR 0.329 -0222

Low NR R -0.212 0.391

CREL: correlation

df: degree freedom

NR: NEGATIVE RELATION

R: RELATION

Managerial competencies with the following sub factors i.e. Initiative and

innovation, thinking strategically, result orientation, decision making and

coaching were considered for finding the associations between the

engagement levels. It was observed that the managerial competencies scores

shows significant association between engaged and disengaged employees.

Thus low scores of managerial competencies that were initiative and

innovation, thinking strategically, result orientation, decision making and

coaching showed a significant strong association and direct link with

disengaged employees. The high scores of managerial competencies scores

that were initiative and innovation, thinking strategically, result orientation,

decision making and coaching showed a significant association and direct

relations with the engaged employees. The alternate hypothesis was

accepted. There are significant associations and relations between scores of

235 | P a g e

Managerial competencies and levels of employee engagement in the Private

sector.

14.9. Predictive talent engagement model to enhance employee

engagement

From the results and findings showed significant negative correlation between

Talent management and employee engagement and the association

between different factors of talent management tools and employee

engagement in the private sector were identified .In order to identify what

makes the multinational companies more efficient with engaged employees

than private sector companies therefore the data‘s of MNC were put on SPSS

18 to develop a predictive talent engagement model that can enhance

engagement. To identify the effect of talent management tools with the

computed score of managerial competencies on employee engagement

helped to develop a predictive talent engagement model that can enhance

engagement. Step wise regression statistical tool was applied to identify the

factors that determine the employee engagement in MNC and to develop the

model.

14.9.1. HYPOTHESIS

H 09: Predictive talent engagement model cannot enhance

Employee Engagement

H19: Predictive talent engagement model can enhance Employee

Engagement

236 | P a g e

A multiple linear was performed on the nine variable items. Table no 41a

shows that all the variables have been entered in to the regression equation.

All the variables are significant at p <.05.

Table no 41a: variables Entered/ Removed

Model Variables Entered

Variables Removed Method

1 R& Sa . Enter

2 Job fit . Enter

3 Performance appraisal . Enter

4 Individual development plan

. Enter

5 Training & guidance . Enter

6 Monitoring . Enter

7 Competency mapping . Enter

8 Succession planning . Enter

9 Managerial competencies

. Enter

Table no 41b shows linear regression of key factors. A multiple linear

regression was performed on the above eight variables. All the items show

the significant variables at p< 0.05.

Multicollinearity is a statistical phenomenon in which two or more predictor

variables in a multiple regression model are highly correlated. In this situation

the coefficient estimates may change erratically in response to small changes

in the model or the data. It may leads to instability in the solution space,

leading to possible incoherent results. Multicollinearity does not reduce the

predictive power or reliability of the model as a whole, at least within the

sample data themselves; it only affects calculations regarding individual

predictors. That is, a multiple regression model with correlated predictors can

237 | P a g e

indicate how well the entire bundle of predictors predicts the outcome

variable, but it may not give valid results about any individual predictor, or

about which predictors are redundant with respect to others.

Identification of multicollinearity present in a model:

1) Large changes in the estimated regression coefficients when a predictor

variable is added or deleted.

2) The formal detection-tolerance or the variance Inflation factor (VIF) for

multicollinearity where is the coefficient of determination of a regression of

explanator j on all the other explanators should be carried out. A tolerance

of less than 0.20 or 0.10 and/or a VIF of 5 or 10 and above indicates a

multicollinearity problem (O'Brien 2007). The tolerance of a variable is

defined as 1 minus the squared multiple correlation of this variable with all

other independent variables in the regression equation . Therefore, the

smaller the tolerance of a variable, the more redundant is its contribution

to the regression i.e., it is redundant with the contribution of other

independent variables. If the tolerance of any of the variables in the

regression equation is equal to zero (or very close to zero), then the

regression equation cannot be evaluated, the matrix is said to be ill-

conditioned, and it cannot be inverted.

Table no 41b shows that the factors recruitment and selection, job fit,

performance Appraisal, Individual development plan, monitoring,

competency mapping, succession planning, managerial competencies

238 | P a g e

showed more than 0.20 of tolerance level and VIF less than 5

indicated all the items are significant variables and do not indicated

multicollinearity. Step wise regression was used to prioritize eight

predictor variables shown in table no 42

Model: SPSS allows specifying multiple models in a single regression

command.

R - R is the square root of R-Squared and is the correlation between the

observed and predicted values of dependent variable which is explained

in the table no 42

R-Square: This is the proportion of variance in the dependent variable

which can be explained by the independent variables. This is an overall

measure of the strength of association and does not reflect the extent to

which any particular independent variable is associated with the

dependent variable.

Adjusted R-square: This is an adjustment of the R-squared that

penalizes the addition of extraneous predictors to the model. Adjusted R-

squared is computed using the formula 1 - ((1 - Rsq) ((N - 1) /( N - k - 1))

where k is the number of predictors.

Std. Error of the Estimate: This is also referred to as the root mean

squared error. It is the standard deviation of the error term and the

square root of the Mean Square for the Residuals in the ANOVA table 43.

239 | P a g e

Table no 41b: linear regression of key factors: talent management,

Managerial competencies and employee engagement in

MNC

Unstandardized Coefficients

Standardized Coefficients

Collinearity Statistics

B

Std.

Error Beta T Sig. Tolerance

VIF

(constant) 20.43 2.719 5.496 .000 .607 1.333

R&S .346 .778 .244 3.445 .660 .502 1.993

jobfit 2.314 .785 .256 2.948 .006 .651 1.535

Perf app 1.035 .876 .153 3.182 .247 .291 1.441

IDP 4.078 1.592 .505 2.561 .016 .226 1.424

Training

guidance 2.154 .744 .416 2.896 .007 .237 1.216

monitoring .907 .971 .113 3.935 .357 .332 1.009

Comp

mapping 2.576 .805 .317 3.200 .003 .500 1.998

Succession

planning .263 .829 .251 2.317 .753 .290 1.263

managerial

competencies .133 .531 .220 2.250 .805 .776 1.289

Dependent variable: employee engagement

240 | P a g e

Table no 42: Stepwise regression of the factors: talent management,

Managerial competencies and employee engagement in

MNC: A model summary

Model

R R Square Adjusted R

Square Std. Error of the Estimate

1 .260a .348 .343 7.759

2 .530b .395 .391 7.352

3 .670c .449 .443 6.127

4 .742d .612 .608 5.214

5 .782e .678 .645 4.004

6 .822f .738 .730 3.062

7 .853g .782 .772 2.367

8 .873h .803 .799 1.415

9 .924i .853 .839 0.468

a. predictors: (constant), R&S, b. predictors: (constant), R&S, job fit,

c. predictors: (constant), R&S, job fit, performance appraisal, d. predictors: (constant), R&S, job fit, performance appraisal, individual development plan, e. predictors: (constant), R&S, job fit, performance appraisal, individual development plan, training guidance, f. predictors: (constant), R&S, job fit, performance appraisal, individual development plan, training guidance, monitoring, g. predictors: (constant), R&S, job fit, performance appraisal, individual development plan, training guidance, monitoring, competency mapping, succession planning, competency

planning h. predictors: (constant), R&S, job fit, performance appraisal, individual development plan, training guidance, monitoring, competency mapping, succession planning, i. predictors: (constant), R&S, job fit, performance appraisal, individual development plan, training guidance, monitoring, competency mapping, succession planning, managerial

competencies. j. dependent variable: employee engagement

241 | P a g e

Table no 43 shows ANOVA, F test. The F test was used to test the

significance of R, Which is the same as testing the significance of R2, which

is the same as testing the significance of the regression model as a whole. If

prob (F) < .05, then the model is considered significantly better and reject

the null hypothesis of no linear relationship of y to the independents. F is a

function of R2, the number of independents, and the number of cases. F is

computed with k and (n - k - 1) degrees of freedom, where k = number of

terms in the equation not counting the constant. F = [R2/k]/[(1 - R2 )/(n - k – 1)].

Alternatively, F is the ratio of mean square for the model (labeled

Regression) divided by mean square for error (labeled residual), where the

mean square are the respective sums of squares divided by the degrees of

freedom. Table no 42 shows the ANOVA test and made sure that Model fit is

checked by using statistics ANOVA, F test. Here the model was significant at

the .001 level.

Table no 43: ANOVA test: talent management, Managerial

competencies and employee engagement in MNC

Model

Sum of Squares df Mean Square F

1 Regression 165.682 1 165.682 6.752

Residual 2287.693 648 60.202

Total 2453.375 649

2 Regression 453.513 2 226.756 4.195

Residual 1999.862 647 54.050

Total 2453.375 649

3 Regression 1101.740 3 367.247 9.781

Residual 1351.635 646 37.545

Total 2453.375 649

4 Regression 1501.842 4 375.460 13.810

242 | P a g e

Residual 951.533 645 27.187

Total 2453.375 649

5 Regression 1908.151 5 381.630 23.798

Residual 545.224 644 16.036

Total 2453.375 649

6 Regression 1908.992 6 318.165 19.287

Residual 544.383 643 16.496

Total 2453.375 649

7 Regression 2090.612 7 298.659 26.345

Residual 362.763 642 11.336

Total 2453.375 649

8 Regression 2091.859 8 261.482 22.422

Residual 361.516 641 11.662

Total 2453.375 649

9 Regression 2092.608 9 232.512 19.335

Residual 360.767 640 12.026

Total 2453.375 649

14.9.2. PLOT

Normally distributed residual error

The error, represented by the residuals, should be normally distributed for

each set of values of the independents. A histogram of standardized residuals

shows a roughly normal curve, the normal probability plot. Figure no 6

supports normality assumption which is important to understand the issue if

any multicoIlinearity which need to be addressed if any. An alternative for the

same purpose is the normal probability plot, with the observed cumulative

probabilities of occurrence of the standardized residuals on the Y axis and of

expected normal probabilities of occurrence on the X axis, such that a 45-

degree line will appear when observed conforms to normally expected. The

P-P plot in the below figure no 7 shows the same moderate departure from

243 | P a g e

normality. But the figure no 7showed the model for talent engagement was fit

and perfect

Figure no 6: Histogram on regression standardized residual: talent

management, Managerial competencies and employee

engagement in MNC

244 | P a g e

Figure no 7: Normal P-P plot of regression standardized residual:

talent management, Managerial competencies and

employee engagement in MNC

Step wise regression statistical tool was applied to develop the model and

identify the talent management factors that determine the employee

engagement in multinational IT companies. The result showed these

variables explain an adjusted R square of 0.853.This analysis showed the

order of the degree of importance as:

1. Company initiated the best method of recruitment, selection and

assessment procedure

2. Company through recruitment and selection procedure develops a job fit

245 | P a g e

3. Company followed scientific performance appraisal system. The

performances were measured and individual development plan were

prepared for each and every employee at all levels.

4. Company believed in individual development plan for the employees

and helped in identifying the proficiency levels of employees in terms of

performances.

5. Company through IDP developed training programme as per the need,

along with guidance, mentoring and support to their employees

6. Company believed in mapping the competencies and planned for further

development

7. Company through mapping of competencies identifies the potential and

talented employees and believes in succession planning for the talent

pool.

8. To develop this need managers have been a key role in developing the

talent pools and hence need the managerial competencies and made

talent management success and thus enhanced employee engagement

and performances

Independent variables together explained 85 percent of the variances. As

shown in table no 42 which is highly significant as indicated by the F-value

shown in the table no 43 .Regression results indicated an overall model of 9

predictors, talent management tools like recruitment and selection, job fit,

Performance appraisal, training & coaching, individual development Plan,

monitoring, competency mapping, succession planning and managerial

246 | P a g e

competencies that significantly predict employee engagement in MNC IT

sector. With the results it indicated that alternate hypothesis was accepted.

Predictive talent engagement model can enhance Employee Engagement.

14.10. Managerial Competencies model enhance employee engagement.

The result showed a significant correlation between high scores of Talent

management tools and employee engagement and significant association

between low scores of talent management tools with the disengaged in

private sector and also showed there was a correlation and association of low

managerial competencies with the disengaged employees. So the data‘s

were put on SPSS 18 , to identify the effect of talent management tools with

the computed score of managerial competencies on the employee

engagement found to develop a predictive talent engagement model that can

enhance engagement in MNC. Step wise regression statistical tool was

applied to develop the model and identified the factors of talent management

tools that determine the employee engagement in MNC. The computed

scores of managerial competencies were considered in the talent

engagement model .But the previous study did not focus on the effect of

different factors of managerial competencies which was obtained by factor

reduction method table no 17 on the employee engagement. The step wise

regression method was used to develop a predictive managerial

competencies model to enhance employee engagement .Therefore the

data‘s of MNC were put on SPSS 18 to develop a predictive managerial

competencies model that can enhance engagement. Step wise regression

247 | P a g e

statistical tool was applied to develop the model and to identify the important

factors that determines the employee engagement by using different sub

factors of managerial competencies derived by factor analysis method in

multinational IT companies.

14.10.1. HYPOTHESIS

H08: Predictive managerial competencies model cannot enhance

Employee Engagement

H18: Predictive managerial competencies model can enhance

Employee Engagement

A multiple linear regression was performed on the eight variable items. Table

no 44a shows that all the variables have been entered in to the regression

equation. All the variables are significant at p<.05.

Table no 44 a: variables entered/ removed

Model Variables Entered

Variables Removed Method

1 Thinking strategically . Enter

2 Initiative & innovation . Enter

3 Plan & organizing . Enter

4 Development . Enter

5 Decision making . Enter

6 Result orientation . Enter

248 | P a g e

Table no 44.b shows Linear regression of key factors .A multiple linear

regression was performed on the above six variables. All the items showed

the significant variables at p< 05.

Multicollinearity is a statistical phenomenon in which two or more predictor

variables in a multiple regression model are highly correlated. In this situation

the coefficient estimates may change erratically in response to small changes

in the model or the data.

It may leads to instability in the solution space, leading to possible incoherent

results. Multicollinearity does not reduce the predictive power or reliability of

the model as a whole, at least within the sample data themselves; it only

affects calculations regarding individual predictors. That is, a multiple

regression model with correlated predictors can indicate how well the entire

bundle of predictors predicts the outcome variable, but it may not give valid

results about any individual predictor, or about which predictors are redundant

with respect to others.

Identification of multicollinearity present in a model:

1) Large changes in the estimated regression coefficients when a predictor

variable is added or deleted

2) A formal detection-tolerance or the variance Inflation factor (VIF) for

multicollinearity: where is the coefficient of determination of a regression of

explanator j on all the other explanators should be carried. A tolerance of

249 | P a g e

less than 0.20 or 0.10 and/or a VIF of 5 or 10 and above indicates a

multicollinearity problem (O'Brien 2007). The tolerance of a variable is

defined as 1 minus the squared multiple correlation of this variable with all

other independent variables in the regression equation. Therefore, the

smaller the tolerance of a variable, the more redundant is its contribution to

the regression i.e., it is redundant with the contribution of other

independent variables. If the tolerance of any of the variables in the

regression equation is equal to zero (or very close to zero), then the

regression equation cannot be evaluated (the matrix is said to be ill-

conditioned, and it cannot be inverted).

Table no 44b shows that the factors Thinking strategically, Initiative &

innovation, Planning & organizing, Development strategically, Decision

making, Result orientation shows more than 0.20 of tolerance level and

VIF less than 5 indicates all the items are significant variables and do not

indicates multicollinearity. If the variables are found to be orthogonal, there is

no multicollinearity; if the variables are not orthogonal, then multicollinearity is

present ( Farrar-Glauber Test). The factors were reduced by factor analysis

method and the variables were orthogonal and so multicollinearity does not

exists. Step wise regression was used to prioritize six predictor variables

shown in table no 45

Model: SPSS allowed specifying multiple models in a single regression

command.

250 | P a g e

R: R is the square root of R-Squared and is the correlation between the

observed and predicted values of dependent variable.

R-Square: This is the proportion of variance in the dependent variable

which can be explained by the independent variables. This is an overall

measure of the strength of association and does not reflect the extent to

which any particular independent variable is associated with the

dependent variable.

Adjusted R-square: This is an adjustment of the R-squared that

penalizes the addition of extraneous predictors to the model. Adjusted R-

squared is computed using the formula 1 - ((1 - Rsq)((N - 1) /( N - k - 1))

where k is the number of predictors.

Std. Error of the Estimate: This is also referred to as the root mean

squared error. It is the standard deviation of the error term and the

square root of the Mean Square for the Residuals in the ANOVA table no

46.

Table no 44.b: linear regression of key factors: managerial

competencies and employee engagement in MNC

Unstandardized Coefficients

Standardized

Coefficients

Collinearity Statistics

B Std.

Error Beta T

Tolerance

VIF

26.939 19.729 1.365 1.000 1.333

Thinking Strategic

.335 2.019 .065 .166 .819 1.993

251 | P a g e

Initiative Innovation

1.444 2.912 .215 .568 1.535

Planning & Organizing

.723 1.814 .164 .399 .972 1.441

Development Strategically

2.438 1.250 -.858 1.951 .859 1.424

Decision Making 1.373 1.648 .477 .833 .319 1.216

Result orientation

1.152 1.569 .236 .734 .722 1.009

Dependent variable: employee engagement

Table no 45: Stepwise regression of the factors: linear regression of

key factors: Managerial competencies and employee

engagement in MNC

Model

R R Square Adjusted R

Square

Std. Error of the

Estimate

1 0.378a 0.374 0.368 5.99444

2 0.480b 0.477 0.475 3.15054

3 0.596c 0.555 0.574 3.29435

4 0.661d 0.679 0.670 2.84465

5 0.724e 0.779 0.771 1.68620

6 0.842f 0.840 0.839 0.79586

a. predictors: (constant), thinking strategically

b. predictors: (constant), thinking strategically, initiative & innovation

c. predictors: (constant), thinking strategically, initiative & innovation, planning & organizing

d. predictors: (constant), thinking strategically, initiative & innovation, planning & organizing,

development

e. predictors: (constant), thinking strategically, initiative & innovation, planning & organizing,

development, decision making

f. predictors: (constant), thinking strategically, initiative & innovation, planning & organizing,

development, decision making, result orientation

g. dependent variable: employee engagement

252 | P a g e

Table no 46 shows ANOVA, F test. The F test was used to test the

significance of R, which is the same as testing the significance of R2, which is

the same as testing the significance of the regression model as a whole. If

prob (F) < .05, then the model is considered significantly better and reject the

null hypothesis of no linear relationship of y to the independents. F is a

function of R2, the number of independents, and the number of cases. F is

computed with k and (n - k - 1) degrees of freedom, where k = number of

terms in the equation not counting the constant. F = [R2/k]/[(1 - R2 )/(n - k - 1)].

Alternatively, F is the ratio of mean Square for the model (labeled

Regression) divided by mean square for error (labeled residual), where the

mean square are the respective sums of squares divided by the degrees of

freedom. Since stepwise regression adds one variable at a time to the

regression model, generating an R2 value each time, subtracting each R2 from

the prior one also gives the R2 increment. R2 increments are tested by the F-

test and are intrinsic to hierarchical regression, discussed below Table no 46.

It shows that Model fit is checked by the F test. Here the model is significant at

the .001 level.

Table no 46: ANOVA Test: Managerial Competencies and Employee Engagement

MODEL Sum of Squares

df Mean

Square F

1. Regression 45.000 1 45.000 5.019

Residual 89.667 648 8.967

Total 134.667 2

2 Regression 45.333 9 22.667 2.284

253 | P a g e

Residual 89.333 11 9.926

Total 134.667 3

3 Regression 47.845 8 15.948 1.470

Residual 86.822 11 10.853

Total 134.667 4

4 Regression 78.023 7 19.506 2.410

Residual 56.644 11 8.092

Total 134.667 5

5 Regression 91.372 6 18.274 2.533

Residual 43.294 11 7.216

Total 134.667 6

6 Regression 95.583 5 15.930 2.038

Residual 39.084 11 7.817

Total 134.667 649

14.10.2. PLOT

Normally distributed residual error

The error, represented by the residuals, should be normally distributed for

each set of values of the independents. A histogram of standardized residuals

should show a roughly normal curve the normal probability plot. Figure no 8

supports normality assumption which is important to understand the issue if

any multicoIlinearity which need to be addressed if any. An alternative for the

same purpose is the normal probability plot, with the observed cumulative

probabilities of occurrence of the standardized residuals on the Y axis and of

expected normal probabilities of occurrence on the X axis, such that a 45-

degree line will appear when observed conforms to normally expect. The P-P

plot in the below figure no 9 shows the same moderate departure from

254 | P a g e

normality. But the figure no 9 showed the model for managerial competencies

was fit and perfect.

Figure No 8: Histogram on regression standardized residual: Managerial

Competencies and employee engagement in MNC

255 | P a g e

Figure No 9: Normal P-P Plot Regression Standardized Residual: Managerial

competencies and employee engagement in MNC

Step wise regression statistical tool was applied to develop the model and

identify the managerial competencies factors , thinking strategically, initiative

and innovative approach, coaching strategically , decision making and result

orientation that determine the employee engagement in multinational IT

companies. And these variables explain an adjusted R square of 0.842.

This analysis showed the order of the degree of importance as:

1) The manager had the competency in terms of thinking strategically as

an independent variable with the employee engagement as a

dependent factor.

2) Thinking strategically needs with innovative and initiative approach

256 | P a g e

3) The manager showed strategic planning and organizing the activities

aligned with the organizational goals.

4) The employees were developed and given the right coaching with the

strategic point view.

5) The MNC managers have been taking competent decisions with the

strategic and analytical approach and exhibited utmost results for a

problem

6) The MNC managers had a result oriented approach to enhance

employee engagement and performances

Independent variables together explained 82 percent of the variances which

is highly significant as indicated by the F-value shown in the table no 46.

Regression results indicated an overall model of 6 predictors, managerial

competencies like thinking strategically, initiative and innovative approach,

planning and organizing, coaching strategically, decision making and result

orientation that determine the employee engagement in the multinational IT

companies. With the results it indicated that the alternate hypothesis was

accepted. Predictive managerial competencies model can enhance

Employee Engagement.

14. 2 .b. Summary of the findings

14.2. b.1.The results show that there was a significant difference in

engagement levels between multinational IT sectors than private

sector. It was observed that multinational employees were more

physically, emotionally and cognitively engaged than private

257 | P a g e

sector. Thus it was observed that there were differences in

engagement level between MNC and Private sector IT Company

that is MNC shows more Engagement level than Private sector.

Since there were difference in Target variable it is important to find

which Predictor variables affect the values of the target that is,

talent management or managerial competencies among Private

and Multinational IT companies.

14.2. b.2.The further result shows that there were differences in the talent

management between MNC and Private IT sector. It shows the

talent management was more prominent in Multinational Company

than private sector.

14.2. b.3.Further study helped to analyze the differences of managerial

competencies among Private and Multinational IT companies.

There were significant differences between managerial

competencies in private and multinational companies. The mean

scores of managerial competencies was more in MNC than Private

IT sector

14.2.b.4.There were differences in engagement level, talent management

and managerial competencies between MNC and Private sector

which shows mean scores of engagement level, talent

management and managerial competencies more than Private

sector. Since there were differences in Target variable it was

important to find which Predictor variables affect the values of the

258 | P a g e

target. Thus it was observed that there was a direct link between

Talent Management and Managerial competencies on the

Employee engagement in the Multinational IT Company.

14.2. b.5.Regression results indicated an overall model of two predictors,

talent management and managerial competencies that significantly

predicts employee engagement in MNC IT sector. This shows that

in MNC, the talent management tools were effectively applied with

the managerial competencies which lead to employee engagement

14.2. b.6.There was a negative correlation between high scores of Talent

Management and Managerial competencies on the Employee

disengagement in the private IT sector but showed positive

correlation between talent management and managerial

competencies on employee engagement. The Relation and the

effect of Talent Management and Managerial competencies on

Employee engagement levels in Private sector showed a negative

effect so the variables or tools related to talent management ie

recruitment and selection, job fit, performance appraisal, training &

coaching, individual development plan, monitoring, competency

mapping, succession planning were considered for finding the

associations between talent management variables with the

engagement levels. It was observed that the talent management

tools showed significant association between levels of employee

engagement. Thus low scores of talent management tools like

259 | P a g e

recruitment and selection, job fit, Performance appraisal, training &

coaching, individual development Plan, monitoring, competency

mapping, succession planning showed a significant association

and showed direct link with disengaged employees. The high

scores of talent management that were recruitment and selection,

job fit, Performance appraisal, training & coaching, IDP,

monitoring, competency mapping and succession planning showed

significant association and direct link with the engaged employees.

14.2. b.7.Managerial competencies i.e. Initiative and innovation, thinking

strategically, result orientation, decision making and coaching were

considered for finding the associations between the engagement

levels. It was observed that the Managerial competencies scores

showed significant association between engaged and disengaged

employees. Thus low scores of managerial competencies that

were initiative and innovation, thinking strategically, result

orientation, decision making and coaching shows a significant

strong association and showed direct link with disengaged

employees. The high scores of managerial competencies that were

initiative and innovation, thinking strategically, result orientation,

decision making and coaching showed a significant association

and direct relation with the engaged employees.

14.2. b.8.Step wise regression statistical tool was applied to develop the

model and identify the talent management factors that determine

260 | P a g e

the employee engagement in multinational IT companies. And

these variables explain an adjusted R square of 0.853.This analysis

showed the order of the degree of importance as:

Company initiated the best method of recruitment, selection and

assessment procedure

Company through recruitment and selection procedure developed a

job fit

Company followed scientific performance appraisal system

Company believed in individual development plan for the

employees

Company through IDP developed the training programme as per

the need, along with guidance, mentoring and support to their

employees

Company believed in mapping the competencies and planned for

further development

Company believed in succession planning for the talent pool

To develop this need managerial competencies to make talent

management success and enhance engagement and performance.

Independent variables together explained 85 percent of the

variances which was highly significant as indicated by the F-value.

Regression results indicated an overall model of 9 predictors, talent

management tools like recruitment and selection, job fit,

Performance appraisal, training & coaching, individual development

261 | P a g e

Plan, monitoring, competency mapping, succession planning and

managerial competencies that significantly predicted employee

engagement in MNC IT sector.

14.2.b.9. Step wise regression statistical tool was applied to develop the

model and identify the managerial competencies sub factors that

were thinking strategically, initiative and innovative approach,

coaching strategically , decision making and result orientation that

determined the employee engagement in multinational IT

companies.

This analysis showed the order of the degree of importance as:

The manager had the competency in terms of thinking strategically

as an independent variable with the employee engagement as a

dependent factor.

Thinking strategically needs with innovative and initiative approach

The manager showed strategic planning and organizing the

activities aligned with the organizational goals.

The employees were developed and given the right coaching with

the strategic point view.