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Talent management model for business schools: factor analysis.

Three Pillars

The three pillars of any higher education institution are: quality of faculty, infrastructure facilities and learning environment. With the increasing demand-supply gap, organizations are facing immense war for talent. Like business and industry, education field too is discovering the need for talent so as to meet the new quality standards demanded by the society and is also facing leadership crisis. While most higher education institutions, especially professional institutes and colleges are able to develop the needed skills in students for success in the working world, experience shows that the management of upcoming technical and management institutions has failed to be just and fair in the treatment of their faculties. This paper has used the survey method based on which faculty members of the various management and technical schools were being interviewed. The objective of the paper is to investigate the issues and factors related to talent management in business and technical schools which can contribute to the growth and development of these institutions. For the study faculty are being considered as talent. The finding of this study may be helpful for the management of these institutions and the policy makers for developing a more effective and better education system.

Research on the development of higher education reveals that India's position is 76 out of the 94 developing countries (World Conference on Higher Education, UNESCO, Paris 5-9 October, 1998). At present India is striving to compete in a globalized economy in areas that require highly trained professionals, and thus the quality of higher education has become increasingly important. Experience which the students will derive from higher education is, to a large extent, dependent on the performance of faculty, both as teachers and researchers. The faculty has a major role in student learning and thus in the present research, the attempt has been to formulate an approach to prioritize the initiatives that institutions need to take for faculty satisfaction and to attain leadership in higher education through talent management. The present study has used seventeen parameters to explain the expectation of faculties in a business school.

Expansion of Higher Education

Higher Education in India has expanded many folds since Independence. The number of universities has increased from 20 in 1947 to 378 in 2005, colleges from 500 to 18064, teaching staff from a meagre 1500 to nearly 4.80 lakhs and student population in higher education from 1 lakh in 1950 to over 112 lakhs. Many fold expansion in institutional capacity in higher education has enhanced enrolment ratio from less than 1% in 1950 to about 10% in 2007 (Jyotsnarani 2007). Since Independence, the system has grown around 22 fold in terms of universities and 33 folds in terms of number of colleges suggesting a transition from an elitist system of education of the British India to a mass based one characterizing a democratic republic. In this era of cut throat business competition there is a burning need of world class business managers and executives. Further the phenomenal growth of Indian industry over last two decades has also resulted in increasing demand for efficient business mangers from business schools. While the top B-schools of India are increasingly getting recognized internationally, the many thousands of remaining management institutes in the country have felt the need for improving in all the basic parameters. It also can not be denied that it is Indian higher education system that, to a significant extent, has contributed to India rising to become the World's second fastest growing economy, the World's third largest economy, fastest growing mobile phone market, owner of the largest bandwidth capacity and the second largest pool of scientists and engineers in the world.

Theoretical Framework

Talent management is a process that emerged in the 1990s and continues to be adopted as more companies come to realize that their employees' talents and skills drive their business success. The term was coined by Mckinsey & Company following a 1997 study. There is the process perspective which proposes that talent management includes all processes needed to optimize people within an organization (Farley 2005). This perspective believes that the future success of the company is based on having the right talent, so managing and nurturing talent is part of the every day process of organizational life. There is the cultural perspective according to which talent management is a mindset (Creelman 2004), and that you must believe that talent is needed for success (Michaels Handfield-Jones & Axelrod 2001). This can be seen where every individual is dependent on their talent for success due to the nature of the market in which they operate, and is typical of organizations where there is a free internal labour market, with assignments being allocated according to how well they performed on their last assignment. Alternatively, this can be an organization where the development of every individual's talent is paramount and appreciated, and allowing people to explore and develop their talent becomes part of the work routine. There is the competitive perspective underpinned by the belief that talent management is about identifying talented people, finding out what they want, and giving it to them. This tends to be the default perspective if no other perspective is taken, if only as a retention strategy. It is also seen in the professional services firms where they generally adopt the competitive approach because their business proposition is based on the talents of their people. There is the developmental perspective that proposes talent management as about accelerated development paths for the highest potential employees, applying the same personal development process to everyone in the organization, but accelerating the process for high potentials. Hence the focus is on developing high potentials or talents more quickly than others.

Extant literature underpins the importance of faculty for quality in higher education (Ewell 1991, Cornesky 1991, Chen et al 2006). Research on academic quality in higher education is by and large focused on students as customers, their satisfaction or dissatisfaction with various programs. Faculty satisfaction has been given only a cursory importance. Chen et al (2006) have adapted Importance--Satisfaction model (I-S model) in higher education illustrating quality improvement in terms of satisfaction. Tribus (1995) developed an early model of customer-supplier for higher education (cited in Raouf 2004). It has been argued that if the quality of the service is to be determined then the beneficiaries have to be clearly defined in terms of their needs and expectations (Raouf 2004). The model conceptualizes faculty as customer in the education industry, and states that, similar to the concept of internal and external customers in business, there are also internal and external customers in education.

It is therefore important to highlight faculty satisfaction from the point of view of job satisfaction also. Managing faculty satisfaction as talent remains relatively under researched as compared to managing employee satisfaction as talent in business. Faculty as the main resource is central to appropriate educational activity. Therefore, faculty satisfaction is an essential pre-requisite for excellence in faculty performance with reference to quality in education (Shagbemi 1997b). Research on the quality of higher education has now also started to look at the job satisfaction of faculty members (Korey 1995). Faculty satisfaction is a key to quality output in terms of professional commitment of faculty members (Ewell 1991) and how well that is aligned with the over all goals of universities for quality enhancement. Schonberger's (1990) emphasis on internal customer relationship supports the idea that the faculty may be seen as the customer of the educational manager; it is the manager's task to minimize problems that hinder faculty from performing at their highest levels of ability (Rowley 1996). So far there has not been research in the area to look for faculty as talent and institutionalize talent management process for academic institutions.

Talent management refers to the process of developing and integrating new workers, developing and keeping current workers and attracting highly skilled workers to work for a company. Conceptual framework established in this paper considers faculty as talent and suggests derive talent management strategies on the basis of influencing factors, focusing on relative importance and level of satisfaction among the faculties.

Faculty as Talent in Business Schools

Talent management is being considered today by corporate as a key business process and like any business process it also takes inputs to generates output. In educational institutions faculty are the major inputs in the process of generating learning as a major output among others. A structured talent management process will systematically close the gap between the faculties an institution currently has and the competent faculties it will eventually need to respond to challenges and create right set of skills in students. This will help faculties achieve their best individual potential; it helps institutions respond to challenges with right set of talent available. An institution with talented faculties can develop a reputation for being great place to work, with great learning environment where quality in education is expected. An institution in higher education therefore needs to be able to develop and deploy faculty who can articulate the passion and vision of institution and satisfaction of students. Faculty members as internal customers satisfy the working environment of universities (Chen et al 2006). This implies that in order to enhance faculty performance certain aspects and functions of their job have to be prioritized. The issues related to faculty are sufficiently significant for an analysis to be appropriate, to understand the 'whole picture' and suggest possibilities to sustain quality and leadership in institution of higher education. The conceptual talent management model has been shown in the fig. 1. The first important aspect to consider in structured talent management process for institutions is to align the complete process with the institutes' vision, mission, and strategy as this will define the talent of faculties for that institution, it may vary from research focused or teachings focused institutions. With the idea of competencies required for faculties to define them as talent, institutions can draw the talent management initiatives and model for that institution. This will enable knowledge creation and tapping the full potential of talent available, ultimately results in effective learning.


Methodological Framework

The present study is exploratory in nature. The findings of this study are based on a survey conducted with majority of the responses from Delhi-NCR. The objective was to understand the factors important for faculty and their satisfaction so as to suggest factors to be considered in designing talent management process and in attracting, developing and retaining star faculties. A structured questionnaire was used in the survey. Faculties and directors of management institutions were asked to fill the responses. The questionnaire contained about the expectations of faculties and their satisfaction with the actual. Twenty two parameters were used in the questionnaire to analyze the expectations of faculties at different business schools.

Pilot Study

After designing the questionnaire, opinions from 5 experts (academicians) were gathered and necessary corrections were carried out. Then the pilot study was done with 24 respondents. During the pilot study, problems faced by the respondents in filling up the questionnaires were identified and necessary corrections were incorporated.

Data Collection

A questionnaire was developed to gather information from the faculty members of management & technical institutions, keeping in view the nature of their work and environment. The questionnaire was divided into A & B. A consist of demographic aspects whereas B consists of variables selected after review of literature. The questionnaire was administered with faculties having minimum three years of experience and two research publications with business schools having student feedback system in practice as mentioned in their websites. Faculties have been asked to rate seventeen variables in a 5 point scale on their importance level. Questionnaires were distributed to 130 faculty members of the business institutes. 82 completed questionnaires were received out of which 16 were disqualified to satisfy conditions of experience and publications.

Findings & Discussion

Faculty members of the business schools were selected through convenient sampling. Demographically, these faculty members were asked to indicate their, designation, length of service and gender. The analysis of open ended questions were also added in the questionnaire to find out any additional information related to important factors for faculty and their satisfaction. These factors were analyzed by taking seventeen variables. The respondents were asked to rank the variables on a five point scale. Then data reduction is done by doing factoring.

Factor analysis is a method of reducing data complexity by containing the number of variables. With regard to the factors that are important to faculties and influence them, a total of seventeen variables were subject to factor analysis. KMO Measure of sampling is 0.626 which is in the acceptable range, being more than 0.5; hence factor analysis could be administered further. The result of factor analysis was obtained by Principal Component Analysis and specifying the rotation. Data were analyzed on Eignvale 1 and varimax rotation. The total variables that can be explained with the above factors are more than 80% (Table 3). Outcome of factor analyses are evident in Table 4 which shows extraction of five factors which are considered important by faculties.

Factor 1

Many factors are considered important by faculties. The first factor includes research funding, opportunity for learning, self study and research hours, role clarity of faculties and also support from administration as these items have highest loading as shown in the table. Respective loadings of items are .911, .829, .741, .684, and .609. Because of common nature of these items, the researcher has identified these factors as 'learning opportunities'.

Factor 2

Items which have high loading on second factor are teaching load, work life balance infrastructure facilities, behaviour of colleagues and behaviour of management. The researcher interprets this factor as 'working environment'. Among the working environment group teaching load has the highest loading, closely followed by work life balance and infrastructure facilities. Behaviour of colleagues and behaviour of management came the next. Faculties expect to have high quality of work life as physical environment and ambience affects learning environment also.

Factor 3

Incentive for loyalty, incentive for hard work, attrition rate of faculties, and behaviour of management constitute the third factor. The researcher characterizes these items as incentives. Incentive for loyalty and long term stay with the institution are important constituents which faculties look in business schools. Incentives are extrinsic motivators for loyalty and hard work which also affects attrition of faculties.

Factor 4

Recognition of good work, opportunity for growth and performance appraisal comprises the fourth factor. They are termed as 'recognition'. Even though faculties are more specific about learning opportunities and working environment, they consider 'recognition' also an important factor.

Factor 5

It represents salary and is the only variable which has loading more than 0.5, hence termed as salary only. It is important to find that salary has appeared as a distinguishing factor with no other variable; its variance (8.63) is the least among all the factors.

The most important of all factors is learning opportunity since its Eigen value and percentage of variation explained by this factor are 5.442 and 21.85 percent respectively followed by working environment with 3.524 and 21.84 respectively. It was evident that opportunities for learning and working environment have items with the highest loading and are important factors. In this study seventeen variables are established and factor analysis has illustrated five factors which are important in recruitment, development and retaining of talent and hence for formulating talent management strategies and processes. Talent management includes early identification of potential and competency success profile analysis, talent management process design, assessing readiness for promotion and performance management. Business schools need to understand faculty as talent and construct talent management strategies considering relative importance of various factors similar to the practices in corporate. Performance management focus is mainly on facilitating environment which requires conducive environment for performance. Therefore it's inevitable to understand and create environment across factors important to faculties. In summary, talent management should focus on variables important in performing key jobs and key individuals. These are faculties and teachings that are critical in ensuring long term success of the institution. Succession planning and readiness for promotion depends upon identifying the key talent and providing development initiatives. In a learning institution potential talents are the faculties and providing opportunities for learning is the way to increasing readiness among them.

Limitations & Directions

While generalizing the finding of the study for different academic institutions, caution should be made, considering sample size and area of study and that study was conducted in private business schools with similar vision and purpose. Since the study focused only on faculty as talent, other contributors in educational institutions also need to be identified. The study can not be implanted in its present form in other academic institutions with different structure and purpose. Future research is needed in establishing a model which can guide academicians and bureaucrats in understanding and establishing effective learning and research environment.


Faculties as talent for business schools require their competencies as per the vision and objectives of business schools. As evident in the conceptual framework, specific competencies required in faculties, which will decide attracting; selecting and developing strategies need to be according to the vision and objective of institution. This study shows that opportunities for learning and working environment are important factors. Therefore effective talent management strategies should be made in line with the learning and development of faculties aligned with institution vision. A research focused institution will need different competencies in faculties as compared to those in a teaching focused and student centred institute. Present study shows that faculties in business schools consider learning opportunities, working environment, incentives, and recognition as important factors for them. Considering faculty as talent and establishing effective talent management practices with focus on development, learning opportunities and performance based rewards would reduce attrition. A facilitating working environment may positively result in internal growth of faculties, which is also ranked an important factor by them. With effective practices of learning and growth opportunities, quality faculties can be built within the business schools which would help in building leadership position of the institution while also achieving internal career growth aligned with the vision and strategies of the institution.


Abdul Rauof Quraishi, U. & Kalim R. (2007), "Development of a Faculty Satisfaction Model for Higher Education", CIE Conference, Alexandria, Egypt available at:, retrieved on 14/6/ 2008.

Chen, S. H., Yang, C. C., Shiau, J.Y. & Wang H. H. (2006), "The Development of an Employee Satisfaction Model for Higher Education", The TQM Magazine, 18(5): 484-500.

Cornesky, R.(1991), Implementing Total Quality Management in Higher Education, Magnar Publications and Madison, WI.

Einstein, W. & Bacdayan P. (2001), "Developing Mission-Driven Faculty Performance Standards", Journal of the Academy of Business Education, 2.

Farley, C. (2005). "HR's Role in Talent Management and Driving Business Results", Employment Relations Today, 32(1): 55-61.

Jyotsnarani, K. (2007), "Attainment of Excellence through Higher Education" Orrisa Review, Feburary- March 2007.

Michaels, E., Handfield-Jones, H., & Axelrod, B. (2001), The War for Talent, Harvard Business School Press, Boston.

Shagbemi, T. (1997a), "Job Satisfaction Profiles of University Professors", Journal of Managerial Psychology, 12 (1): 27-39.

Rauof, A. (2004), "Quality in Higher Education", Pakistan Academy of Science (Proceedings), 42(2): 165-74.

Schonberger, R.J. (1990), Building a Chain of Customers, Free Press, New York,

Shagbemi, T. (1997b), "Job Satisfaction Profiles of University Professors", Journal of Managerial Psychology, 12 (1): 27-39.

Swati Agrawal is Associate Professor, Jaipuria Institute of Management, Noida.

Table 1: Raouf Model of Customer-Supplier for Higher Education

Customers        Suppliers                 Service

                 Faculty member            Curriculum design leadership
Students         Administrators            material & equipment
                 Governing body            system development policy
Faculty member   Administrators            material & equipment
                                           knowledge, wisdom, know
Parents          Higher Education System   how, character
Industry         Higher Education System   knowledge, wisdom, know
                                           how, character
Faculty member   Faculty member            knowledge, wisdom, know
                                           how, character

Source: Raouf (2004)

Table 2: Descriptive Statistics (N=75)

                                  Descriptive Statistics

                                  Mean     Std. Deviation

Work life balance                  4.28         1.031
salary structure                 4.4800        .64650
teaching load                      3.74          .694
behaviour of management            3.74         1.275
behaviour of colleagues          4.4200        .85928
opportunity for learning         4.4400        .50143
research funding                 3.3800        .49031
incentive for hard work          4.7400        .44309
incentive for loyalty            4.6000        .49487
opportunity for growth           4.8600        .35051
attrition rate of faculty        3.8200        .59556
infrastructure facilities        4.0000        .69985
role clarity of faculty          4.4200        .53795
self study and research hours    3.6200        .66670
performance appraisal            4.4800        .50467
support from administration      4.6800        .58693
recognition of good work         4.6800        .47121

Table 3: Total Variance Explained

                        KMO & Bartlett's Test

Kaiser-Meyer-Olkin Measure of Sampling Adequacy.        .626
Bartlett's Test of Sphericity Approx. Chi-Square     766.068
                              Df                         136
                              Sig.                      .000

                  Total Variance Explained

Component           Initial Eigen values

            Total    % of Variance   Cumulative %

1           5.442       32.010          32.010
2           3.524       20.732          52.742
3           2.369       13.933          66.675
4           1.440        8.470          75.145
5           1.240        7.296          82.441
6            .612        3.603          86.044
7            .537        3.161          89.205
8            .476        2.798          92.003
9            .358        2.109          94.112
10           .296        1.743          95.855
11           .206        1.213          97.068
12           .165        .968           98.036
13           .134        .786           98.821
14           .101        .592           99.413
15           .058        .341           99.754
16           .026        .151           99.904
17           .016        .096          100.000

                  Total Variance Explained

Component     Rotation Sums of Squared Loadings

            Total    % of Variance   Cumulative %

1           3.715       21.852          21.852
2           3.714       21.849          43.701
3           2.965       17.440          61.141
4           2.154       12.670          73.812
5           1.467        8.630          82.441

Extraction Method: Principal Component Analysis.

Table 4: Rotated Component Matrix (a)


                                   1       2      3      4      5

Research funding                 .911
Opportunity for learning         .829
Self study and research hours    .741
Role clarity of faculty         -.684
Support from Administration      .609
Teaching load                            .939
Work life balance                        .895
Infrastructure facilities                .821
Behaviour of colleagues                  .645
Behaviour of management                  .608   .501
Incentive for loyalty                           .823
Incentive for hard work                         .793
Attrition rate of faculty                       .597
Recognition of good work                               .855
Opportunity for growth                                 .797
Performance appraisal                           .641   .654
Salary                                                        .889
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Title Annotation:Communication
Author:Agrawal, Swati
Publication:Indian Journal of Industrial Relations
Geographic Code:9INDI
Date:Jan 1, 2010
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