The Influence of Job Characteristics on Attrition in the IT Industry

M Showry
Associate Professor, Department of HR, IBS Hyderabad (Under IFHE - A Deemed to be University u/s 3 of the UGC Act, 1956), Hyderabad, Telangana, India; and is the corresponding author. E-mail: mshowry@ibsindia.org

Ravi Dasari
Vice-President, Group Head HR, Jasper Industries, Hyderabad, Telangana, India. E-mail: ravi.dasari@jasperindustries.com

The attrition of employees has emerged as one of the unyielding human resource challenges confronting the IT industry. Brutal cost-efficiency, intense competition, relentless innovation, and persisting rate of attrition of employees would threaten the organization's ability to accomplish strategic goals. Hence, organizations in the IT sector have made substantial efforts to reduce the rate of attrition by implementing diverse HRM practices. Despite the implementation of innovative human resource practices, the attrition among IT professionals remains unabated and threatening the competitive advantage of the organization. Hence, the managers have shifted their attention to examining the influence of the job characteristics on employee attrition. The current study examines whether or not an employee's subjective evaluation of job characteristics influences attrition by using Hackman and Oldham's job characteristics model. The findings of the study conclude that skill variety, task identity, task significance, and autonomy influence attrition.

Introduction

Studies show that employee attrition in the IT industry is significantly higher than in all the other industries. According to the research firm Gartner, the attrition rate has seen a steep rise from sluggish 10% in 2020 to alarming 20% in 2021, and some are even battling with higher rates of up to 30%. According to Business Standard, the attrition rate at top tech majors like Infosys, Wipro and HCL Tech touched a new high of 20.1%, 20.5% and 15.7%, respectively. The research studies indicated poorly designed tasks, lack of appreciation in the job and task ambiguities that triggered an intention to leave the organization. Employees are the most indispensable resource of any organization, especially the IT industry, as they are responsible for delivering the projects on time and fulfilling the specifications of the clients which are the key to accomplishing the objectives of an organization. To achieve this, an organization should design a job environment that stirs up efforts to acquire and utilize skills, and importantly allocate specific tasks according to the skills that they deliver on the job. However, many organizations in the IT industry fail to understand the importance of job characteristics derailing employee motivation and effectiveness. The job environment as the primary cause of attrition in IT industry is poorly understood and has not been adequately examined.

Meyer and Allen (1984) defined turnover as an employee's intention to quit his or her present job or organization (Lingard, 2003). Generally, turnover of employees is the term extensively used in research to explain the quitting of employees from an organization, while the term attrition has been specially referred to the decrease in the number of employees caused by the voluntary resignations but cannot be easily replaced. David (2016) distinguished attrition as the phenomenon where the vacancy remains unfilled due to scarcity of finding a suitable replacement. An instance is when an employee leaves their position at their workplace but the vacancy needs to be filled. Carmeli and Weisberg (2006) stated that employee who starts thinking about leaving an organization to find another alternative will have a turnover intent. If such alternatives do not exist, employees may involuntarily stay in their job, leading to the problem of poor attitude and reduced effort resulting in declined performance. Abii et al. (2013) concluded that attrition causes the companies to experience a drop off in the quality of products and services rendered especially if a talented professional departs. Holtom et al. (2008) revealed that attrition affects customer service and satisfaction. Employee attrition thus yields both undesirable tangible and intangible organizational costs (Hillmer et al., 2004).

Several employers are not clearly aware of why some employees leave and the remaining employees stay with the organization (Iqbal, 2010). Organizations with high attrition tend to record lower than average customer satisfaction and loyalty.

The Job Characteristics Models
The studies conducted on the influence of job characteristics have been scarce and systematic analysis of job characteristics of IT professionals may broaden the understanding of attrition in IT industry in particular. The objective of this paper is to investigate the influence of job characteristics using Hackman and Oldham's (1974) Job Characteristic model on attrition. Specifically, this study may answer an array of questions pertaining to employee attrition triggered by job-related factors in the IT industry.

The job characteristics model emerged when the American sector failed to come to grips with rampant job dissatisfaction and felt that the traditional design of the job was not well suited to meet the demands of the competitive marketplace. Buchanan and Huczynski (1997) stated that Taylor's scientific management signaled the beginning of designing of stress-free and well-controlled work environment by the simplification and the standardization of jobs resulting in the specialization of skills. This has further enhanced the workers' efficiency, productivity, and eventually skills as well as optimum performance. However, the inescapable ill-effects of the scientific management like boredom due to routine and unexciting tasks along with the Herzberg's Two factor theories of motivation finally gave rise to Hackman and Oldham's Job characteristics model which is extremely relevant to the IT sector.

The model emphasizes that the characteristics of a job can have an effect on employee involvement, motivation, and satisfaction. Hackman and Oldham (1980) proposed that positive job characteristics will provide employees with positive feelings and experiences and these in turn influence work outcomes such as intrinsic work motivation. The primary focus of the model is to measure the objective characteristics of a task that lead to high internal work motivation, performance, meaning, and job satisfaction.

The job characteristics model has effortlessly been adapted to employees across diverse organizations and implies that the absence of job characteristics could decisively decrease motivation and fuel attrition. The Human capital theory and the Exit-voice theory foretell that workers in high involvement work systems are less likely to quit their companies. The high involvement work systems tap into each employee's initiative, imagination and resourcefulness by informing them of happenings at their workplace, giving the autonomy to voice their views and empowering them to take decisions as well as impart ample training. An individual's disposition towards the job determines success or failure and also may influence their motivation and intention to leave. Herzberg examined what employee desires from the job and concluded that intrinsically rewarding feelings of achievement, recognition, work, responsibility, growth, etc., contribute immensely to employee motivation. Hence, talented employees who have better alternatives are expected to leave the job if the job content is uninspiring. Hence, enhancing intrinsic rewards by making the job more fulfilling and energizing might decrease the intention to leave.

The job characteristics would help the employees experience critical psychological state like meaningfulness of work and responsibility for outcomes of the work, and knowledge of the actual results of work activities would lead to internal motivation, performance and satisfaction. Sledge et al. (2011) stated that the five job characteristic of the Job characteristics model produces three critical psychological state among employees which include experienced meaningfulness, experienced responsibility, and knowledge of results.

Meaningfulness of the Work
It is the ability of a given job to evoke a sense of meaning and value while performing the job that results in meaningfulness and contributes towards the organizational effectiveness.

Felt Responsibility
It explains whether an employee experiences responsibility for the work and feels individually accountable for the outcomes.

Knowledge of Results
This describes whether an employee receives the inputs about the final results and outcomes of the jobs they do. Hackman and Oldham's job characteristics model determines the three psychological states of the employees as explained further.

High Internal Work Motivation
It refers to the degree to which an employee is willing to work and consider the organizational objectives as a part of his/her goals.

High Growth Satisfaction and General Satisfaction
The growth refers to the achievement an employee experiences in overcoming challenges and becoming successful while the general satisfaction is derived from overall satisfaction with the work itself.

High Effectiveness and High Commitment
The quality and quantity aspects of work performance give rise to commitment and effectiveness.

The job characteristics motivate individuals by producing experiences of meaningfulness, responsibility, and knowledge of results (Hackman and Oldham, 1975). Thus, autonomy, skill variety and feedback would be negatively related to attrition since employees who possess resources to promote job tasks are more expected to invest energy and personal resources in their work roles (Christian, 2011). Several empirical studies have verified that these five core job characteristics have an influence on employee work outcomes like attrition.

The studies indicated poorly designed tasks, lack of appreciation in the job, and task ambiguities push the employees on the brink of attrition. The way organizations design the jobs and the employee's evaluation of the key dimensions of the job can substantially determine the motivation, commitment, and eventually employee attrition. Trevor (2001) revealed that a job or organization becomes unattractive and obsolete if it fails to offer the desired exposure, learning, and achievement, ultimately resulting in attrition. Contrarily, when IT employees gain the necessary skills to become productive, it translates into more job alternatives, and subsequently a higher probability of attrition. Griffeth's (1985) field experiments of job redesign interventions reported that employees are more likely to stay in their job when their job is enriched by giving more autonomy or more skill variety. This means that changes in job characteristics would influence an employee's level of job attachment. Fried and Ferris' (1987) study found that the favorable job characteristics resulted in low intention to quit the job. Spector and Jex (1991) reported that the previous research across several industries found a direct and negative relationship between job characteristics and employee intention to quit. Kanfer (1991) found that the job characteristics enhance employees' acquisition of task-related knowledge and skills. The knowledge and skills attained by the employees would help to perform up to the demands of the organization. This results in better fit, higher task accomplishment, and greater intention to stay. The companies which are proactive in creating flexible working conditions and an environment that fosters innovation, challenge, and fun have mitigated attrition.

There is a dearth of empirical literature investigating the relationship between job characteristics and employee attrition among IT employees in India. Not many studies have analyzed how job attributes influence the employees' probability of quitting the job. Kochanski and Ledford (2001) revealed that IT employees often do not quit a company, but they quit a job. An improvement in the job design is one of the most effective but least used tools in reducing attrition in the long run. Outsourcing mundane and less significant jobs to free the IT professionals to work more on the creative projects they deeply crave can mitigate attrition (McEachern, 2001). McEachern (2001) reported that IT professionals in large IT firms grieve at the feeling of frustration with the jobs involving maintaining the systems rather than working on new projects. Poor utilization of the skills in IT job due to poor management at IT companies lead to attrition. The life cycle of a project is a sequence of activities that the project passes through from the inception to the end. There are some marked stages in the life of the project, namely, inception, integration and coordination, implementation, and the finish of the project as a whole. Programmers and developers need to understand the context, what system they have to build, and how it would be used by a client. Employees need to keep the whole task in their mind and check how their task is embedded with the whole job. Fisher and Rouse (2001) found that despite high rewards, programmers and software employees are likely to be dissatisfied in a work environment that stifles creativity and fails to respect their professional expertise. Much of the motivation and perception of value for the job comes from the striking impact the project will have on the organization.

Objective
The primary objective of the paper is to examine the impact of five job characteristics proposed by Hackman and Oldham, viz., skill variety, task identity, task significance, autonomy, and feedback on attrition to know which of the five factors have a stronger influence on the attrition.

The hypothesizes formulated are:

H₁: Job characteristics have no influence on attrition intention among IT professionals in select firms.

H₂:: Skill variety has no significant influence on attrition intention among IT professionals in select firms.

H₃:: Task identity has a negative influence on attrition intention among IT professionals in select firms.

H₄:: Task significance has a negative influence on attrition intention among IT professionals in select firms.

H₅:: Autonomy has a negative influence on attrition intention among IT professionals in select firms.

H₆:: Feedback has a negative influence on attrition intention among IT professionals in select firms.

Data and Methodology
The study is descriptive in nature based on primary data. A standardized questionnaire comprising job characteristics and turnover intention has been administered to the employees from the selected IT companies. The population comprises the technical employees working in the three IT companies at Hyderabad. A random sampling technique is followed to administer the questionnaire. A total of 497 sets of questionnaires were received from the employees from the selected companies. Table 1 provides the profile of the respondents.

An analysis of Table 3 shows that the attrition among the employees in higher designation is greater than the employees in the lower designations.

An analysis of Table 4 shows that the mean satisfaction with job characteristics across various designations is low.

An analysis of Table 5 shows that the mean satisfaction with job characteristics is 2.34. It shows that the satisfaction with the job characteristics is merely average. The mean satisfaction with job characteristics in TCS at 2.39 is higher than Infosys at 2.32 and Wipro 2.31 respectively.

An analysis of Table 6 shows that F = 2.053 and p > 0.10, i.e., insignificant. Hence, there are no significant differences between the mean satisfaction of the job characteristics of the IT employees across the three companies.

An analysis of Table 7 shows that F = 0.984 and p > 0.000, i.e., insignificant. Hence, there are no significant differences between the mean satisfaction with the job characteristics of the IT employees across the different designations of the IT employees.

Linear Regression Between Job Characteristics and Attrition
Table 8 presents the correlation between job characteristics and attrition.
An analysis of Table 8 shows that correlation between job characteristics and attrition is -0.724 moderately negative and significant as indicated by p < 0.05. Hence, an increase in job characteristics will result in decrease in attrition.

Table 9 explains the regression model's ability to account for the variation in attrition. The adjusted R² of the model is 0.523. It implies that the linear regression model consisting of five job characteristics, namely, skill variety, task significance, task identity, autonomy, and feedback, together explains 52.3% of the total variance in attrition.

Table 10 presents the coefficient between job characteristics and attrition.The height of regression is equal to 6.098. The B coefficient of job characteristics is -1.060 and p < 0.05 thus significant. It may be concluded that job characteristics have a negative influence on attrition as the Beta coefficient is negative. Hence, if the satisfaction with job characteristics increases, the attrition comes down.

The regression equation is given as
Y = 6.098 - 1.060 * (Job Characteristics)
H01: Job Characteristics have no influence on attrition among the employees of
the select IT companies - Rejected.

Table 11 presents the correlation between job characteristics and attrition. It is evident from the table that the mean satisfaction scores of job characteristics vs skill variety is 2.53, Task identity 2.08, Task significance 2.95, Autonomy 3.13, and feedback 3.21 respectively. It shows that mean satisfaction with feedback is highest and task identity is lowest. Also, the correlation between feedback and attrition is 0.035 and insignificant. Hence, it has no association with attrition. Pearson's coefficient between attrition and skill variety r = -0.141 is negatively low and significant. The Pearson's coefficient between attrition and task identity r = -0.502 is moderately negative and significant. The Pearson's correlation between attrition and task significance r = -0.821 which is strongly negative and significant. The Pearson's correlation between autonomy and attrition is r = -0.703 moderately negative and significant. It can be concluded that the correlation of skill variety, task identity, and task significance with attrition is negative as well as significant. Thus, an increase in skill variety, task identity and task significance results in a decrease in attrition.

Multi Regression - Job Characteristics and Attrition
Table 12 presents the findings of the multi-regression model summary.
An analysis of Table 12 shows that the adjusted R² of the model is 0.744. It implies that the regression model accounts for 74.4% of the total variance in attrition.

A comprehensive analysis of Table 13 reveals that the regression coefficients for skill variety, task identity, and task significance are negative as well as significant. Nevertheless, the regression coefficient for autonomy is positive and significant. The specific analysis of Table 13 reveals that the Beta coefficient for skill variety is -0.050 and significant. Hence, skill variety has a negative influence on attrition. An increase in skill variety results in a corresponding reduction in attrition. Hence, the null hypothesis that skill variety has no influence on attrition among IT employees in select companies is rejected. Further findings reveal that Beta coefficient for task identity attrition is -0.137 and significant and thus has a negative influence on attrition. Hence, the null hypothesis that task identity has no influence on attrition among IT employees in the select companies is rejected. Thus attrition tends to decrease if task identity increases considerably. The B coefficient for task significance is -1.438 negative and significant. Hence, the null hypothesis that task significance has no influence on attrition among IT employees in the select companies is rejected. Further analysis of Table 13 reveals that B coefficient for autonomy is 0.605 and p < 0.05 thus has significant influence. Hence, an increase in autonomy tends to decrease the intention to leave. Hence, the null hypothesis that autonomy has no influence on attrition among IT employees in the select companies is rejected. The multi regression can be expressed by

Attrition = 5.58 - 0.050 (Skill Variety) - 0.137 (Task identity) - 1.438 (Task
Significance) + 0.0605 (Autonomy)

Conclusion
Despite the underlying importance, not many Indian studies have adequately addressed the potential link between employee perceptions about job characteristics and critical work behavior like attrition. This paper has examined the influence of job characteristics on attrition among the IT employees in the select companies at Hyderabad. The study concluded that skill variety, task identity and task significance are the three important predictors of attrition. A significant negative relationship was also found between those three job characteristics and attrition. Interestingly, the study revealed that the influence of job autonomy on attrition is positive while the feedback has no influence on attrition. The characteristics of the jobs are the primary reasons why many organizations in IT industry fail to reduce the rate of attrition among the IT employees. The monetary incentives, however stimulating they may be, cannot replace exciting and challenging work and assignments. The poor job design is one of the root causes of employee de-motivation, employee dissatisfaction and low productivity triggering attrition. The employees will be in general committed to jobs which they perceive contain desirable job characteristics like skill variety, task identity, task significance, autonomy, and feedback. The managers in the IT sector should get into the thick of the matter by making desirable changes in job design and pay increasing attention to designing jobs to enhance skill variety, task significance, and task identity to prevent employees from leaving the organization. The suggestions to enhance job characteristics include providing job rotation to acquire more skills, job enrichment to enhance both task significance and task identity which would reduce attrition. Nevertheless, such changes must be made after considering various cause-and-effect relationships. It is also important for the employees to have realistic expectations about the possible improvements both employees and managers can make to the jobs. The managers can also foster a work environment that promotes autonomy by reducing excessive interference based on different role requirements. However, they need to examine the reasons why autonomy in jobs has a positive influence on attrition. A job embodying good job characteristics inspires, thereby reducing their intention to leave the jobs, while a job that is ill-designed frustrates resulting in attrition.

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