Comparative analysis of manpower planning in India: an experimental approach

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The top management needs to follow an organized and systematic process to operate, monitor and control Manpower planning measures in the Organizations. It is obvious that the development and success of an organization are never possible without competent, trained and satisfied people in the organization.

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International Journal of Management (IJM) Volume 9, Issue 2, March–April 2018, pp. 56–63, Article ID: IJM_09_02_006 Available online at http://www.iaeme.com/ijm/issues.asp?JType=IJM&VType=9&IType=2 Journal Impact Factor (2016): 8.1920 (Calculated by GISI) www.jifactor.com ISSN Print: 0976-6502 and ISSN Online: 0976-6510 © IAEME Publication COMPARATIVE ANALYSIS OF MANPOWER PLANNING IN INDIA: AN EXPERIMENTAL APPROACH Arindam Chatterjee Ph.D Scholar, School of Management, West Bengal University of Technology, India Dr. S. Guha Assistant Professor, School of Management Studies, Narula Institute of Technology, India ABSTRACT The top management needs to follow an organized and systematic process to operate, monitor and control Manpower planning measures in the Organizations. It is obvious that the development and success of an organization are never possible without competent, trained and satisfied people in the organization. Proactive preparation in this matter is highly desired from the management that should be based on the future targets of the management, as also anticipate changes in the external factors. The parameters discussed or comparison hereinafter is closely interlinked to carry a significant portion of outcome and end results. It becomes essential to foster a holistic analytical view of the underlying factors in Indian scenario with a particular comparative reference to the Information Technology and Manufacturing sectors in order to derive a relevant and balanced recommendation on the research findings. Key words: Manpower Planning, Information Technology, Manufacturing, Comparative. Cite this Article: Arindam Chatterjee and Dr. S. Guha, Comparative Analysis of Manpower Planning in India: An Experimental Approach. International Journal of Management, 9 (2), 2018, pp. 56–63. http://www.iaeme.com/IJM/issues.asp?JType=IJM&VType=9&IType=2 1. INTRODUCTION According to Youdi and Hinchliffe (1985) in their work titled “Forecasting skilled manpower needs”, corporate manpower planning is extremely crucial today for every type of business firm or public services organization. Corporate manpower planning is the department of any company which manages the personnel’s working in that specific company. The process of manpower planning basically involves understanding the availability and requirement of the manpower pool for the company and then coming up with ideas that will help in bridging this http://www.iaeme.com/IJM/index.asp 56 editor@iaeme.com
Comparative Analysis of Manpower Planning in India: An Experimental Approach gap to a large extent. An approximate forecast is required for understanding this demand and supply and there are various mathematical tools which can be used for the same. The discrepancies are also analyzed with these tools. 1.1. Problem Statement Manpower planning differs according to different sectors and hence manpower practices of one sector cannot be effectively applied to other sector. Thus this study will aim to study and provide solution to the issues by evaluating and understanding the differences in the reward and promotion, and other manpower planning and practices by comparing IT and manufacturing sector. To achieve this research work will examine the difference amongst the manpower planning and practices in IT and manufacturing sector. 2. RESEARCH OBJECTIVES  To evaluate and understand the difference in the reward and promotion, and other manpower planning and practices in IT and manufacturing sector.  To examine the difference amongst the manpower planning and practices in IT and manufacturing sector.  To correlate the impact of different variables on Manpower Planning of mostly in IT and Manufacturing Sector .  To prepare a compare and contrast study on the data gathered through sampling techniques and find out possible recommendations on the study. 2.1. Research Hypotheses H01: There is no significant difference in manpower practices on Productivity/ Efficiency IT and manufacturing sector. H02: There is no significant difference in the level of productivity/ efficiency with Manpower Forecasting of mostly in IT and Manufacturing sector. 3. DIFFERENT ASPECTS OF MANPOWER PLANNING According to Youdi and Hinchliffe (1985) in their research work “Forecasting skilled manpower needs” corporate manpower planning is extremely crucial today for every type of business firm or public services organization. Corporate manpower planning is the department of any company which manages the personnel’s working in that specific company. The process of manpower planning basically involves understanding the availability and requirement of the manpower pool for the company and then coming up with ideas that will help in bridging this gap to a large extent. An approximate forecast is required for understanding this demand and supply and there are various mathematical tools which can be used for the same. The discrepancies are also analyzed with these tools (Ruud, 1970). Vajda (1970) has expressed their view on corporate manpower planning as the following: “manpower planning is concerned with arranging for the necessary number of suitable people to be allocated to various jobs, usually in a hierarchical structure,” Geisler (1967) gives an even more analogous approach to corporate manpower planning. It says that corporate manpower planning is all about having the right number of people and the right kind for a given task. The timing of these people and the place where they are present also matters. The entire purpose of having people is to enhance the economy of the company. In order to achieve all this, it becomes paramount to have the right kind of instruments for forecasting and controlling the development of the people who are hired and http://www.iaeme.com/IJM/index.asp 57 editor@iaeme.com
Arindam Chatterjee and Dr. S. Guha assigned a specific task. Thus, it becomes necessary to manage the people with the tools that are present with the company. 3.1. Training Policies Training is the most vital part of the advancement of HR and expanding up their productivity. Training comes about into the advancement of innovation constantly at a quicker rate. Due to the revealing of new advances, framework and techniques get obsolete soon. These comprise of specialized, administrative and behavioral strands. It is very difficult for an employee to perform well at the job place without any pre- training (Thomas N. Garavan, 1997). Trained employees perform well as compared to untrained employees (Partlow, 1996; Tihanyi et al., 2000; Boudreau et al., 2001). It is absolutely necessary for any sector to give its employees training to get overall goals of the organization in a better way (Flynn et al., 1995; Kaynak, 2003; Heras, 2006). Training and development increase the overall performance of the organization (Shepard, Jon et al., 2003). Training is always a worthy ploy in the long run (Flynn et al., 1995; Kaynak, 2003; Heras, 2006). It enhanced the overall skills and efficiency level leading to sectional and overall organizational success both in quantitative and qualitative aspects. Moreover, in order to get competitive advantage and continuous dominance over the business sector through effective understanding and execution of new Technology and knowledge, training in mandatory for all such skill reforms and technological advancement (Carlos A. Primo Braga,1995). 3.2. Job Analysis Clifford, 1994, vide his research established and on the efficacy and importance of job analysis in different levels of human resource and manpower planning practices in related and non-related category of organizations which also depicts corrective analysis and arrangements with recourse in order to specify strengths and limitations along with necessary analysis on skills and job requirements. Gatewood & Feild, (1994) illustrated in a different way where assignments/jobs, human factors and employee attributes for a particular task, sub-task and proportion of jobs as job analysis as a part of employee’s knowledge, skills and abilities (KSAs) characteristics. McCormick, vide his study in 1976 stated that the accumulation and formulation of job related information and related evaluations and specifications through job analysis can be considered as a pre-requisite for Manpower planning both in short and long run. Sanchez and Levine published in 2000 that many faulty propositions of the job analysis may affect certain HR activities related to job design and job analysis and inter-related areas. Earlier research in 1988 by by Mullins & Kimbrough; Schmitt & Cohen, 1989, Avolio & Waldman, 1989 and Landy & Vasey, 1991 on direct and indirect variables of demographics in job analysis analytics and ratings. Cascio, (1998) and later on Bowin & Harvey (2001) reflected on the strategic significance of job analysis as a regulating factor of Manpower Planning in overall performance of the Organization. Brannick and Levine (2002) defined this as a process by which nature, purpose, methodology of the job is established and Job, task and sub-tasks are fragmented into smaller parts and units for better execution and compilation. 3.3. Job Satisfaction Job Satisfaction in late 90’s was termed as one of the most crucial and vulnerable factor of manpower retention, planning, augmenting, monitoring, controlling and even development in service, Manufacturing, Education and NGOs and the same was systematically described by Locke (1976) and other Management scientists who defined job satisfaction as a pleasing or http://www.iaeme.com/IJM/index.asp 58 editor@iaeme.com
Comparative Analysis of Manpower Planning in India: An Experimental Approach positive emotional state resulting from the evaluation of a person’s job (Haque and Taher, 2008). Job satisfaction is defined by Robbins, 1999 as a one’s general attitude towards a job mostly in terms of individual and group experiences generate out of it. Mullins (1993) stressed on the difference of motivation and job satisfaction as both of them are inter-linked, closely related significantly different from each other. There are many factors such as employee needs , social status, relationships, quality of work life, empowerment issues, style and involvement of management, job rotation & design, compensation and benefits, working conditions, career opportunities, and sense of belongingness are considered to be the determinants of job satisfaction (Byars and Rue, 1997; According to Robbins (1999), a workforce with positive approach towards job can increase individual, departmental and organizational productivity through lesser absenteeism, more intense and quality involvement, proactive-ness, learning and implementation of knowledge with utmost accountability. Moorhead and Griffin, 1999). According to Robbins (1999), also mentioned about few incidences of destructive behavior, and low medical costs. 4. DATA ANALYSIS 4.1. Demographics of the Collected Data Table: 4.2 Demographics of the collected data Varianc Standard Parameters Sector N Min Max Mean e Deviation IT 40 1 5 2.41 1.59 1.26 Job Analysis Manufacturing 40 1 5 2.19 1.38 1.18 IT 40 1 5 2.20 1.59 1.26 Training Policies Manufacturing 40 1 5 2.24 1.42 1.19 IT 40 1 5 2.55 1.78 1.33 Job Satisfaction Manufacturing 40 1 5 1.62 1.17 1.08 4.2. Feedback Received Table: 4.3 Satisfaction Percentages Feedback Percentage Strongly Strongly Agree Slightly Agree Disagree Parameters Sector Agree Disagree 1 2 3 4 5 IT 27% 35% 17% 12% 9% Job Analysis Manufacturin g 32% 40% 12% 8% 8% IT 38% 29% 17% 9% 8% Training Manufacturin Policies g 32% 37% 15% 10% 7% IT 27% 26% 23% 11% 12% Job Manufacturin Satisfaction g 69% 13% 9% 6% 3% 4.3. Hypothesis Analysis through T- Test This section talks about the outcome of the hypotheses in the study, which aimed at assessing significant difference between manpower practices and Job Satisfaction in IT sector and Manufacturing sector. H01: There is no noteworthy differentiation in Training planning and job satisfaction between IT and manufacturing sector companies in India. http://www.iaeme.com/IJM/index.asp 59 editor@iaeme.com
Arindam Chatterjee and Dr. S. Guha Table: 4.4 Hypothesis Test A Independent Samples Test Std. Std. Error Sector N Mean t Sig. Deviation Mean Training IT Sector 40 2.200 .3850 0.0609 -.435 .065 Policies Manufacturing Sector 40 2.235 .3332 0.0527 ANOVA Sum of Squares df Mean Square F Sig. .025 1 .025 .189 .665 Between Groups Within Groups 10.111 78 .130 Total 10.136 79 Independent Samples Test Std. Std. Sector N Mean Error t Sig. Deviation Mean IT Sector 40 2.546 .5741 0.091 Job Satisfaction 8.691 .061 Manufacturing Sector 40 1.618 .3564 0.056 ANOVA Job Satisfaction Sum of Squares df Mean Square F Sig. 17.245 1 17.245 75.537 .061 Between Groups Within Groups 17.807 78 .228 Total 35.052 79 Inference: Above table shows results of the study of the main hypotheses (H01). There is no significant difference in training policies and job satisfaction between IT sector and manufacturing sector. Results indicated that there is a slight difference in the Job Satisfaction in the IT sector and manufacturing sector with significant level of .061, which results into the acceptance zone of the null hypothesis. Hence it can be concluded that job satisfaction policies in IT sector is slightly better than the manufacturing sector. Whereas, training policies manufacturing sector is better than the IT sector (Sig. = 0.065). Source: Primary Data http://www.iaeme.com/IJM/index.asp 60 editor@iaeme.com
Comparative Analysis of Manpower Planning in India: An Experimental Approach H02: There is no remarkable contrast in relationship of Job Satisfaction with job analysis among IT and manufacturing sectors in India. Table 4.6 Hypothesis Test B Independent Samples Test Std. Std. Sector N Mean Error t Sig. Deviation Mean IT Sector 40 2.546 .5741 0.091 Job Satisfaction 8.691 .061 Manufacturing Sector 40 1.618 .3564 0.056 ANOVA Job Satisfaction Sum of Squares df Mean Square F Sig. 17.245 1 17.245 75.537 .061 Between Groups Within Groups 17.807 78 .228 Total 35.052 79 Independent Samples Test Std. Std. Error Sector N Mean t Sig. Deviation Mean IT Sector 40 2.413 .4950 0.0783 Job Analysis 2.11 .058 Manufacturing Sector 40 2.192 .4394 0.0695 ANOVA Job Analysis and Competency Mapping Sum of Squares df Mean Square F Sig. Between Groups .975 1 .975 4.453 .058 Within Groups 17.085 78 .219 Total 18.061 79 Inferences: Above table shows results of the study of the third hypotheses (H02). There is no significant difference in the level of Job Satisfaction with Job Analysis of IT and Manufacturing sector. Results indicated that there is a slight difference in the Job Satisfaction in the IT sector and manufacturing sector with significant level of .061, which results into the acceptance zone of the null hypothesis. Hence it can be concluded that Job Satisfaction due to Job Analysis in IT sector is slightly better than the manufacturing sector. Whereas, Job Analysis and Competency Mapping in IT sector is better than the manufacturing sector (Sig. = 0.058). Source: Primary Data 5. CONCLUSIONS  The present research work evaluated and contrasted the differences in the reward and promotion, and other manpower planning and practices in IT and manufacturing sector in India.  The research work has found that manufacturing sector manpower policies are slightly better than the IT sector manpower policies. However, overall no significant difference has been found in manpower policies and productivity between IT and Manufacturing sector. http://www.iaeme.com/IJM/index.asp 61 editor@iaeme.com
Arindam Chatterjee and Dr. S. Guha  The research has indicated that in both the sectors training and development plays a significant role. Hence a significantly strong relation has been found in between training and development and job satisfaction with significantly high correlation.  Further, it has been concluded that there is no significant difference between the Incentives and rewards policy in IT and manufacturing sectors. Moreover, in all the parameters like Manpower forecasting, Training and development policies, Incentives and rewards policies, Promotion Policies, Productivity policies and Performance Appraisal null hypothesis is accepted which means that there is no significant difference between the policies in the IT and manufacturing sector. 6. RESEARCH LIMITATIONS  The first limitation is in reference with the research sample as 40 companies each of IT and other service and Manufacturing sectors had decided to participate in this study as it very specifically examines three very sensitive dimensions of company’s operations – Job Satisfaction, Job Analysis and the Training policies. Hence, it was difficult to attract a larger number of companies to this research.  The next limitation refers to the analysis of organizational performance and comparison between the companies in terms of the feedback measures received in Likart Scale ranging from 1-5 and hence only quantitative feedbacks are analyzed without much hint of influence with qualitative and Audit based information and observation inputs.  and finally, the parameters were analyzed for in the context of India where the participation MNCs play crucial role in determining the overall correlation and trend of relationship and comparison between two variables and sectors respectively. It should, however, be made broader in nature where the study will be made on a much larger areas and with a longer framework of time. REFERENCES [1] Ahamad, B. and Blaug, M. (1973) the practice of manpower forecasting; Elsevier, Amsterdam pp. 635-644. [2] Bowey, A.M. (1974). A guide to manpower planning. MacMillan, London. [3] Clifford, J. (1994). Job Analysis: Why Do It and How Should It Be Done? Public Personnel Management, 23, 321–40. [4] Dessler, G. (2003). Human Resource Management, 9th Ed. Englewood Cliffs, NJ: Prentice Hall [5] Grinold, R. C. and Marshall, K. T. (1977). Manpower planning models. Elsevier North- Holland, New York pp. 315-330. [6] Harbison, F. and Myers, C. A. (1964) education, manpower, and economic growth; McGraw-Hill Book Company, New York, Toronto, London pp.658-667. [7] Hollister, R. (1983) "A perspective on the role of manpower analysis and planning in developing countries". In Psacharopoulos, G. et.al. Manpower issues in educational investment: A consideration of planning processes and techniques; the World Bank, Washington, D.C, USA pp. 575-588. [8] Irfan, M. (1974) manpower and employment in Pakistan: in proceeding of the first R.C.D. manpower planning seminar, Islamabad 20-23 May, 1974; manpower division, Ministry of Labour and Works, Govt. of Pakistan pp. 436-442 . [9] Jolly, R. and Colclough, C. (1972) African manpower plans: An evaluation, international labour review, and vol. 106, Nos. 23. August-September 1972; International Labour Office, Geneva. http://www.iaeme.com/IJM/index.asp 62 editor@iaeme.com
Comparative Analysis of Manpower Planning in India: An Experimental Approach [10] Mace, J. Taylor, S. M. (1975) The demand for engineers in British Industry: Some implications for manpower forecasting, British Journal Of Industrial Relations, volume xiii number 2, July 1975; London School of Economics and Political Sciences. [11] Purkiss, C. (1981). Corporate Manpower Planning: a Review of Models. European Journal of Operational Research, Vol. 8, pp. 315–323. [12] Rajan, A. and Pearson, R. (1986) UK occupational and employment trends to 1990; institute of manpower studies, UK pp. 525-535. [13] Ruud, K. (1970) manpower and educational requirements of Pakistan (1961-90); Planning Commission, Govt. of Pakistan pp. 615-625. [14] Youdi, R. V. and Hinchliffe, K. (1985) forecasting skilled manpower needs: Unesco: IIEP. Paris pp. 457-465. [15] Ziderman, A. (1978) Manpower Training: Theory and Policy; the Macmillan Press Limited London and Basingstoke, Melbourne, New Delhi, New York, Singapore, Tokyo pp. 569-609.Ziderman http://www.iaeme.com/IJM/index.asp 63 editor@iaeme.com