Strategies to Retain Employees in the IT Industry in India

ABSTRACT

Although the Information Technology (IT) sector accounts for the highest contribution to Gross Development Product in India, it has high employee turnover. This turnover is a waste of investment and detracts from organizations’ knowledge and experience pools. Person organization (PO) fit theories posit that when people are hired by and for organizations (not just individual jobs), they are less likely to quit. This study examines the benefits provided by IT firms to retain their employees and how these benefits’ effectiveness vary by designation and firm. It does so by employing the ‘work environment congruence’ approach to PO fit. Moreover, it proposes how to build a strategic model of the mix of benefits for retaining staff at different position levels (designations) in the firm. Findings show that preferred benefits differ by designation. For all factors except location, organization does not play an important role in retention, but designation impacts it in all the factors.

Keywords: Retention strategies, Retaining employees, Information technology, Indian IT industry.

INTRODUCTION 

The Information Technology (IT) sector is important to India’s economic and social development and provides the highest relative market share of the nation’s Gross Development Product. However, employee turnover has emerged as a major challenge to the IT sector. The rate of attrition increases with the skill levels of employees (Cho & Lewis, 2012) and is also impacted by experience, with the highest level of turnover occurring in the first four years of employment (Elkjaer & Filmer, 2015; Malhotra, 2004; Yiu & Saner, 2008). One prominent reason for staff turnover in the IT sector is demand for higher pay packages (Ganco et.al., 2015). Turnover has many repercussions for firms, such as waste of financial investments (Perez, 2008) and a reduction in the combined knowledge and experience of a firm’s workforce (Hancock et al., 2013).

Firms need to retain their human resources as these are their highest source of competitive advantage in what is known as the resource-based view (RBV) (Holland et al., 2007; Ostroff & Bowen, 2016). Employers aim to be the “employer of choice” (Bellou et al., 2015) and strategically attract, retain, and motivate its employees. However, retention varies significantly among industries and organizations due to different cultures, policies and procedures, and management (Sheridan, 1992). Research suggests that Person Organization (PO) fit can play a significant role in retaining employees in high turnover jobs (McCulloch & Turban, 2007) by enhancing the environmental and value congruence of employees with the firm (Amos & Weathington, 2008; Steers & Mowday, 1981). When people are hired into an organization and not just for ‘jobs,’ their satisfaction with organizational factors (salary and career advancement) increases, and they display significantly better work attitudes, lower turnover intention, and higher work performance (Elkjaer & Filmer, 2015; Kristof, 1996).

Given all of this, this study aims to examine how to retain employees in IT firms by employing the ‘work environment congruence’ and ‘value congruence’ approaches to PO fit in two Indian technology firms: Tata IT Consultancy Services (TCS) and Infosys (Arthur, 2001). It aims to identify the organizational factors that aid in enhancing this approach to PO fit, leading to employee retention. The study also shows how the preferences for the retention mix of benefits varies by designation in IT firms, with the term designation in this article referring to the kind of work that an employee conducts in their job position at a firm. Organizations can build a retention policy based on this bundle of benefits to attract and retain individuals (Morrow & Wirth, 1989). This research primarily focuses on the first three designations of software engineers working in India’s leading tier 1 IT firms.

LITERATURE REVIEW

India is the most sought-after destination for firms outsourcing their IT services (Presbitero et al., 2016) and the IT industry needs a shift in focus from recruitment to retention (Kumar & Arora, 2012). Many studies acknowledge that Human Resource Management (HRM) practices that fit the value systems of employees, like competitive remuneration, training and development, opportunities for career development, financial participation like profit sharing (Richter & Schrader, 2016), employee ownership plans (Carberry, 2012), and work-life balance policies, increase employees’ PO fit, thereby increasing the firm’s retention rate, and enhancing employer branding (Cascio, 2014). Thite (2010) explains that organizational factors are behind the turnover in the Indian IT sector, and PO fit assessment is vital for employee retention. The strategies to enhance PO fit and thereby increase staff retention used by firms include offering voice mechanisms (Spencer, 1986), adopting ‘commitment’ HRM policies (Arthur, 1994), like meaningful work, fair hiring, training, performance appraisal (Cho & Lewis, 2012) and providing intrinsic motivation through career advancement and relationship building (Bertelli, 2007; Kim, 2005; Astakhova,2016; Garg & Rastogi,2006; Moynihan & Landuyt, 2008). The majority of research on this topic propounds that PO fit is an important predictor of employee retention, however, to the best of our knowledge, no work has explored how PO fit can be used to develop a retention mix of benefits differing by designation in IT organizations. This research gap is what this article seeks to address: how differences in employee designations in the IT sector affect their PO fit and their preferred mix of offered retention benefits (Backhaus, 2016; Pasewark & Viator, 2006).

THEORETICAL FRAMEWORK & HYPOTHESIS DEVELOPMENT

The concept of PO is derived from Person-Environment fit (Shin, 2004) and based on the theory of work adjustment (Bretz & Judge, 1994). This theory posits that individuals who fit well within organizations have positive work-related outcomes (Spurk et al., 2019; Menezes, 2015), such as intent to remain with their firm (Ostroff & Bowen, 2016) which can be explained by the ‘work environment congruence’ and ‘value congruence’ approaches (Westerman & Cyr, 2004) of PO fit. Additionally, PO fit is an important predictor of job satisfaction and organizational commitment (Van Vianen et al., 2007; Grima et al., 2021), and higher physical and mental wellbeing (Carless, 2005), contributing to reduced staff turnover. PO fit has been extensively used to recruit for high-turnover jobs (McCulloch & Turban, 2007; Williams & Dreher, 1992). Weathington & Tetrick (2000) posit that organizational factors affect the PO fit of the employees, thereby affecting their intent to stay, and therefore the firm’s employee retention (Black & Lynch, 1996). In this study, we carry out an investigation of the perception of organizational factors using two-way ANOVA analysis to understand its variation in different designations and organizations. Figure 1 depicts the research framework

Figure 1. The research framework.

The organizational factors (mix of benefits) offered to employees currently employed by tier 1 Indian IT firms were identified through an extensive literature review, interviews with employees working in the IT firms and brainstorming with subject experts, displayed in table 1. A total of six categories were created by academic experts performing semantic analysis independently (Poba-Nzaou et al., 2016; Vorhauser-Smith, 2012) and then comparing and labeling. Intercoder reliability was determined using the Cohen Kappa statistic.

Table 1. Categories of retention mix of benefits.

DEVELOPMENT OF HYPOTHESIS

A core premise of this article is that although organizations offer similar benefits to all their designations, a different mix should be offered to each based on the differences in their level of experience and opportunities (Nishii et al., 2008). The RBV supports this proposition, customizing retention strategies for a particular designation (Jones et al., 2009; Presbitero et al., 2016; Watson et al., 2004). Intent to remain with a firm varies by organization (Fletcher et al., 2016; Yamamoto, 2008) and designation, which defines the type of job the person conducts (Ishiyama, 2011; Yamamoto, 2013). Therefore, the intent to stay with a firm varies by designation and organization. This article tests eight hypotheses, laid out below.

Firms adopt strategic HRM practices like remuneration to retain valuable employees (Chadee & Raman, 2012; Scullion et al., 2010). Firms offer attractive remuneration packages in the specialty jobs market where there is a dearth of skilled professionals, adding incentives and perks to retain employees (Ferguson & Brohaugh, 2009). Satisfaction with remuneration is significant in managing employee’s decision to quit (Motowidlo, 1983; Hoffman & Woehr 2006). Therefore, we can hypothesize that an employee’s satisfaction with their remuneration is a retention factor that varies by designation and organization, also referred to as H1.

IT sector employees face the challenge of obsolescence of their skill set in relatively shorter periods than other industries (Presbitero et al., 2016). Training and development are essential to upgrading the skills of IT employees and have been seen to improve employee retention (Armstrong-Stassen & Ursel, 2009), specifically in job learning practices in the IT sector (Egan et al., 2004). Organizations which invest in Human Resource Development (HRD) initiatives to develop employee potential (Cascio, 2014) and provide a continuous learning environment through innovative tools improve employee retention (O’Leonard, 2013; Schmidt & Bjork; 1992). Therefore, we can hypothesize that an employee’s satisfaction with training and development opportunities is a retention factor that varies by designation and organization, also referred to as H2 (Astakhova & Porter, 2015).

‘Family friendliness’ refers to firms adopting measures to help employees with their family responsibilities (Yamamoto, 2011; Lambert & Lambert,2012). It includes work-life balance and family-friendly practices. Work-life balance practices include supervisor support (Paul & Anantharaman, 2003) through mentoring (Cascio & Aguinis, 2011) and are seen to lower withdrawal cognition by positively affecting employee attitudes (Batt & Valcour, 2003). When individuals believe that supervisors and management are protective of and generous towards their workers, they experience value congruence with the firm (Presbitero et al., 2016). Mentoring, another work-life balance practice (Lawrence, 2011), has proven to be a useful tool to retain young employees in IT industries (Long et al., 2012; Tsuda, 1993). Peer support is essential in a continuous learning environment such as the IT sector (Cascio, 2014). Therefore, we can hypothesize that the perception of work-life balance practices is a retention factor that varies by designation and organization, also referred to as H3.

To promote employees’ work-life balance, organizations indulge in ‘family-friendly practices,’ such as flexibility of place of work (Rau & Hyland, 2002), as it positively impacts employees’ job satisfaction, morale and engagement (Atkinson & Hall, 2011). Other practices involve the flexi-timings option, working part-time, long breaks for major life events, sabbatical, work from home option, etc. Such options have been seen to highly reduce attrition (TNN, 2016). Therefore, we can hypothesize that satisfaction with family-friendly practices is a retention factor that varies by designation and organization, also referred to as H4.

In the Indian IT industry, more than 80 percent of workers are continually seeking better job opportunities (Guchait & Cho, 2010; Griffin & Moorhead, 1981), as it raises their morale, self-esteem and trust in the firm. Therefore, one needs to understand the triggers of turnover to ensure the retention of employees (Presbitero et al., 2016). When a job becomes monotonous, especially in the IT industry, employee absenteeism and dissatisfaction increase (Batt et al., 2005; Roy, 2010), making retention a challenging task. Firms attempt to enlighten employees through allocating tasks that match their knowledge, skills, abilities, and interests (Samuel & Chipunza, 2009). Therefore, we can hypothesize that ‘self-enlightenment’ is a retention factor that varies by designation and organization, also referred to as H5.

Firms implement various recognition and reward measures which act as a positive reinforcement (Presbitero et al., 2016) that reduces employees’ intent to quit (Long et al., 2012). On the other hand, multiple periodic appraisals generate a sense of insecurity among employees in the Indian IT sector (Ferguson & Brohaugh, 2009) and affect the retention of employees (Van Vianen, et al., 2007). Based on this, we can hypothesize that employees’ perception of recognition by the firm and job security are retention factors that vary by designation and organization, also referred to as H6.

Fringe benefits provide instrumental value, serving as end benefits to employees (Van Vianen, et al., 2007). These include family health insurance coverage, retirement savings, employee stock ownership plans, paying dividends, and allowances (Yamamoto, 2011), besides offering sabbaticals and recreational facilities (Akhtar et al., 2015; Kossivi et al., 2016). By engendering improved job attitudes and organizational attachment, employee benefits increase employees to stay, serving as a major retention factor for firms (Fairris, 2004; Wagar & Rondeau, 2006). Based on this, we can hypothesize that employees’ satisfaction with ‘employee benefits’ is a retention factor that varies by designation and organization, also referred to as H7.

Employer branding influences employees’ choice of firms (Bellou et al., 2013) while also boosting their work attitudes through image identification (Gberevbie, 2010; Karatepe, 2013; Silbert, 2005). Additionally, influential industry leaders in any given economic environment belong to firms with positive employer brands (Cascio, 2014). Firms, therefore, enhance their image by adopting favorable HRM policies such as the provision of effective communication channels (Guchait & Cho, 2010), especially among millennials (Cascio, 2014), who value informal and continuous feedback. Additionally, open-door policies, addressing grievances (Baltes et al., 1999; Dibble, 1999), bulletins on the Intranet and blogs also build the company image (De Vos & Meganck, 2009; Heeks, 2015). Employee empowerment and autonomy are two major techniques essential for company identification and raising employees’ self-esteem (Laura, 2013; Whiting & Williams, 2013). Based on this, we can hypothesize that the employees’ perception of their ‘company identification’ is a retention factor that varies by designation and organization, also referred to as H8.

RESEARCH METHODOLOGY

This study employed a survey method based on the Person-Environment fit by Shin (2004) and the theory of work adjustment by Bretz & Judge (1994). The survey was used to gauge the preferred mix of benefits held by respondents working at the first three level designations (starting from the entry point into the engineering cadre of the firm) in tier 1 Indian IT firms. The three levels of designations are widely termed to be System Engineer/Software Engineer, Senior System Engineer/IT Analyst and Project Lead/Assistant Consultant. Answers were given on a Yes/No dichotomous scale (Creswell & Poth, 2015; McElroy, 2014). Using Google Forms and deploying non-probability purposive and snowballing sampling, 581 valid responses were received during three months of data collection from December, 2021 to March, 2022. Using a sample size calculator (Creative Research Systems, 2012; Ostroff et al., 2005) we determined that the 581 responses is above the required sample of 384 to ensure a 95 percent confidence level and five percent confidence interval. After collecting the data and inputting it into software (Statistical Package for the Social Sciences, version 23), the two-way ANOVA was applied to carry out our analysis.

Since the questionnaire was administered electronically and was not targeted to a specific location, it cannot be said with confidence that the survey covered all the locations of the two firms researched in India. The firms also have offices outside India, creating cross-cultural factors that affect retention and work outcomes. These factors were not incorporated into this study. There may have been a self-reporting bias for respondents due to employee’s reluctance to spare time and express their opinions in the survey (Roberts & Illardi, 2003; Knippenberg, 2000; Grima et al., 2020).

RESULTS

H1 was split into the three parts below to apply the two-way ANOVA.

Designation

H10: Perception of Remuneration for each designation is the same.

H11: Perception of Remuneration for each designation is different.

Organization

H10: Perception of Remuneration for each organization is the same.

H11: Perception of Remuneration for each organization is different.

Interaction

H10: Perception of Remuneration for all interactions is the same.

H11: Perception of Remuneration for all interactions is different.

Table 2. Results of two-way ANOVA for Remuneration as a retention factor.

Table 3. Descriptive statistics for designation and perception of remuneration.

Observing the significance values, all null hypotheses except for ‘designation’ can be accepted, implying that the Perception of Remuneration for each designation is not the same. When comparing the mean values of different designations, Remuneration is the most attractive as a retention factor for level 2 and level 3 engineers and the least attractive for level 1 engineers in both firms (tables 1, 2 and 3). A summary of the results for all other factors is presented below (and in tables 4 to 40 in the appendix):

•      For t training, all null hypotheses except for designation are accepted. This implies that the perception of training as a retention factor differs significantly from the designation. Comparing mean scores, training is the most attractive retention factor for designation level two.

•      Perception of supervision as a retention factor differs significantly from the designation, as all null hypotheses except for designation can be accepted. Comparing mean scores, supervision is most attractive as a retention factor for designation levels one and two.

•      Perception of relationship with colleagues has a significant impact on retention for different designations. Here again, the null hypotheses for organization and interaction effect are accepted, while for designation, it is rejected. After comparing the mean scores across designations, we find that this is most influential at designation level two.

•      Similarly, the perception of career advancement as a retention factor differs significantly among designations. Career advancement is the most attractive for designation level three as a retention factor.

•      The designation seems to significantly impact the perception of engineers towards the type of work irrespective of organization. When comparing the mean scores, the most important factor is for level three engineers.

•      Perception of recognition varies with the designation. It is most attractive for level one workers and highly attractive for level three workers.

•      Job security perception varies by designation, and mean scores suggest that it is most attractive for level one engineers.

•      Fringe benefits are significant for different designations, thereby rejecting the null hypothesis for designation. It is most attractive for level one engineers.

•      The importance of location as a retention factor varies with both the designation and the organization individually, but the particular combination of the two does not impact its importance to workers. Comparing the mean scores for different designations, it can be seen that location matters the most to level one engineers. At the same time, location is most attractive for engineers working at Infosys.

•      Perception of higher education support varies significantly with the designation. It is the most attractive aspect for level one engineers.

•      Flexible timings are significant for different designations and are more enticing for level two engineers.

•      Perceptions of the ‘work from home option’ vary with the designation, and mean scores suggest that level three engineers are most attracted to it.

•      Designations impact the perception of engineers towards mentoring, and it is the most attractive aspect for level three engineers.

•      Designation plays a significant role in impacting the engineers’ perceptions of communication platforms. It is the most important factor for level one and level two engineers.

•      Since the significance level for organization and interaction effect is greater than 0.05, the null hypothesis is accepted, but rejected for the designation. Comparing the mean scores, acceptance of ideas is an important factor for retention for level three engineers.

•      Designation does impact the perception of extra-curricular activities. The mean score values suggest that level one engineers in IT firms find this factor the most attractive.

•      The designation of an engineer impacts their perception of company size, image, and retention. Comparing mean scores, this factor is most important for level three engineers, followed by level one engineers.

Summarizing the above results, in all the retention factors except location, organization does not play an important role, while designation impacts employee’s perception in all the factors.

DISCUSSION, MANAGERIAL IMPLICATIONS AND CONCLUSION

This study focuses primarily on the theory of work adjustment. It posits that when an organization attempts to enhance the PO fit of an employee, due to the intrinsic motivation, positive attitudes and positive work-related outcomes at play, the employee’s intent to remain with the firm increases. Because of this, the study identified retention mixes of benefits offered by IT firms and how the perception of preference by different designations varies in them. This study follows the ‘Bundle of HRM practices’ approach (Guchait & Cho, 2010; Morita, 2006; Snell & Dean, 1992) for each designation, as the combination of these practices, if applied strategically, is most effective at managing employee performance and turnover (Byle & Holtgraves, 2008). The study findings confirm the proposition of RBV: that retention strategies need to be customized for each designation in the firm, as intent to remain also varies by job level (Jones et al., 2009; Presbitero et al., 2016; Watson et al., 2004; Menezes, 2015).

Findings from this study can help IT organizations to develop retention strategies targeted at different designations. Remuneration, training, supervision, relationships with colleagues, career advancement opportunities, type of work, recognition, job security, fringe benefits, location of posting, higher education support, flexible timings, work from home options, mentoring, communication platforms, acceptance of ideas and company size and image, were used to identify the benefits desired by employees. The findings support the premise that organizational factors affect the PO fit of employees (Weathington & Tetrick, 2000), and that individuals who fit with their organizations have positive work-related outcomes (Spurk et al., 2019) and are content (Ostroff & Bowen, 2016; Sood et al., 2022) which can be explained by the ‘work environment congruence’ and ‘value congruence’ approaches of PO fit (Westerman & Cyr, 2004; McElroy et al., 2014).

Based on the two-way ANOVA applied to the retention mix of benefits for each organization and designation, preferred benefits differ significantly by designation. While the inner circle represents the retention benefits commonly preferred by all designations, the outer circles represent a specific preference for each designation (figure 2). The most attractive factors for retaining level one employees are training and development, recognition and job security, company identification, work-life balance practices, employee benefits, and family-friendly practices (Richter & Schrader, 2016; Tziner & Birati, 1996; Sood, 2022; Yerpudee et al., 2022). The primary reason for this is attraction towards the reputation and size of large organizations. Besides this, at the entry-level, security is of utmost importance, in addition to lucrative compensation and benefits. To move up the career ladder, employees also seek educational and supervisor support to remain motivated (HiringEmployees, 2014). This is consistent with previous literature that HRD initiatives at firms support employee growth through an environment which fosters continuous learning (Bertelli, 2007; Cascio, 2014; Snell & Youndt, 1995).

Figure 2. Model depicting preferred retention mix of benefits.

Apart from the common preferences at level two in the IT sector, remuneration appears to be a major inducement for retention (Scott et al., 2012; Varma et al., 2022). They are more interested in better-paying jobs than in enhancing their skills and abilities in their present position. This is similar to the characterization of gig economies where employees continually hop between jobs in search of better pay packages and benefits (Ferguson & Brohaugh, 2009), and also makes the employee feel valuable to the firm (Chadee & Raman, 2012; Murray, 1999). In addition, they seek flexible timing and communication platforms for to address grievances and express ideas and emotions. Such practices promote work-life balance, thereby enhancing job outcomes and reducing staff turnover (Presbitero et al., 2016; TNN, 2016). This also allows employees to voice their opinions through effective communication channels and promotes employer branding and identifying with the company (Guchait & Cho, 2010; Laura, 2013).

At level three in the IT sector, remuneration, company identification, self-enlightenment, recognition and job security, family-friendly practices, and work-life balance practices are the most important factors for staff retention (Cappelli, 2000; Hayhurst et al., 2005). Since job roles and responsibilities are often in managerial and leadership areas, employees seek a mentor to attain a work-life balance and empowerment and platforms for expressing their voice and ideas. Mentoring is seen to positively affect work-life balance (Cascio & Aguinis, 2011) and lowers withdrawal cognition through the positive impact on their attitudes (Batt & Valcour, 2013). They also need flexibility in location and recognition of their efforts. At this level, company size and image matter a lot, and that is also why job-hopping increases at higher levels (Hamori, 2010; Kowske et al., 2010). Although the organization does not affect the preferred mix of benefits, ‘Location’ was significant for TCS since it offers choices of location to employees throughout their careers. TNN (2016) also supports the notion that offering work hour and location flexibility to employees helps reduce staff turnover.

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APPENDIX

Table 4. Results of two-way ANOVA for pay as retention factor.

Table 5. Descriptive statistics for designation and perception of pay.

Table 6. Results of two-way ANOVA for training.

Table 7. Descriptive statistics for designation and perception of training.

Table 8. Results of two-way ANOVA for supervision.

Table 9. Descriptive statistics for designation and perception of supervision.

Table 10. Results of two-way ANOVA for relationship with colleagues as retention factor.

Table 11. Descriptive statistics for designation and perception of relationship with colleagues.

Table 12. Results of two-way ANOVA for career advancement opportunity as retention factor.

Table 13. Descriptive statistics for designation and perception of career advancement opportunity.

Table 14. Results of two-way ANOVA for nature and type of work as retention factor.

Table 15. Descriptive statistics for designation and perception of nature and type of work.

Table 16. Results of two-way ANOVA for recognition as retention factor.

Table 17. Descriptive statistics for designation and perception of recognition.

Table 18. Results of two-way ANOVA for job security as retention factor.

Table 19. Descriptive statistics for designation and perception of job security.

Table 20. Results of two-way ANOVA for fringe benefits as retention factor.

Table 21. Descriptive statistics for designation and perception of fringe benefits.

Table 22. Results of two-way ANOVA for location as retention factor.

Table 23.Descriptive statistics for designation and perception of location.

Table 24.Descriptive statistics for organization and perception of location.

Table 25.Results of two-way ANOVA for higher education support as retention factor.

Table 26.Descriptive statistics for designation and perception of higher education support.

Table 27.Results of two-way ANOVA for flexible timings as retention factor.

Table 28.Descriptive statistics for designation and perception of flexible timings.

Table 29.Results of two-way ANOVA for work from home option as retention factor.

Table 30.Descriptive statistics for designation and perception of work from home option.

Table 31.Results of two-way ANOVA for mentoring as retention factor.

Table 32. Descriptive statistics for designation and perception of mentoring.

Table 33. Results of two-way ANOVA for communication problems as retention factor.

Table 34. Descriptive statistics for Designation and perception of communication problems.

Table 35. Results of two-way ANOVA for acceptance of ideas as retention factor.

Table 36. Descriptive statistics for designation and perception of acceptance of ideas.

Table 37. Results of two-way ANOVA for extra-curricular activities as a retention factor.

Table 38. Descriptive statistics for designation and perception of extra-curricular activities.

Table 39. Results of two-way ANOVA for company size and image as retention factor.

Table 40. Descriptive statistics for designation and perception of company size and image.