Workforce Diversity: A Springboard for Employee Productivity and Customer Experience

Abstract

Purpose: The purpose of this study was to examine the differential effect of workforce diversity on employee productivity and its subsequent impact on customer experience. Research design, data and methodology: A once-off cross-sectional research design was used in this study where the Zimbabwean civil service was targeted. Randomization was used to collect 324 validated responses. The study focused on both primary (age and gender) and secondary (education and political affiliation) dimensions of workforce diversity. Results: The results were confirmatory that workforce diversity is a significant predictor of employee productivity (β = 0.668, P < 0.05), at the same time employee productivity holds explanation to customer experience by 37%. Results also revealed that gender diversity, educational diversity and political diversity were significant determinants of workforce diversity (P < 0.05). However, the study established that age diversity was not a significant factor in enhancing employee productivity (P > 0.05). Conclusions: The study concluded that workforce diversity is a powerful tool in enhancing both customer experience and employee productivity. As such, the latter can be augmented through shrewd workforce diversity practices as championed by management. To that end, the study recommends the development of a workforce diversity framework which promotes inclusivity.

1. Introduction

This article examines the effect of workforce diversity on employee productivity and customer experience. With increased globalization and interrelatedness comes a blend of different individuals who meet at the same workplace to work towards achieving the same objectives. The modern workplace is made up of employees of different backgrounds in terms of ethnicity, social values, economic status, race and physiology. In some cases, especially in the early phases of team building, this has led to serious clashes, hatred and production dysfunctionality at the work place (Zhuwao, 2017). This has given rise to the need to foster an efficient, united, harmonious, homogenous workforce regardless of the inevitable heterogeneity. A unified workforce, regardless of its multi - prolonged diversity is bound to be convergent towards the development of a more productive labour force and a translation into superior customer experience.

Employee diversity has been perceptible in Zimbabwe and Africa at large. The development of a diversified labour force is deeply rooted in the county’s legislation which calls for equality and cooperation among various stakeholders. The Zimbabwean Constitution (2013) mandates full participation of women in socio-economic activities (Section 17), Section 22 of the Zimbabwean Constitution acknowledges full participation of the disabled in all aspects of life. In support of the constitution, the Labour Act Chapter 28:01 also cogently promotes congruence at work place and protects the rights of both men and women, including minority stakes (Madhuku, 2017). It goes without prejudice that the laws of the land have made it indispensable for people from different backgrounds to work together at the same workplace.

Regardless of the undisputable diversity of the labour force, employees have been treated homogenously irrespective of age, gender, disability, culture or educational background; which in turn affects their productivity and ultimately the failure to surpass customer experience and satisfaction. Women have broken the glass ceiling and took jobs that the traditional patriarchal society had formally reserved for men (such as engineering and executive positions). Undoubtedly, such women have not been easily oriented as equally competent job takers by both their male counterparts and superiors or subordinates. Non-availability of inclusive infrastructures such as wheelchair ramps to allow easy access by disabled employees or clients is also a challenge. Generally, an egoistic culture of greediness promotes non tolerance to political diversity which in turn shadows staff morale. It shuts doors to innovation, thereby importing shoddy work and ultimately low employee productivity. The generational gap among different employees is also a problem, as conflicts escalate and continued weakening of work teams often result in poor job performance.

This paper therefore examines workforce diversity as an instrument to enhancing employee productivity and ensuring customer experience. The paper also presents a new orientation to labour management through linking employee productivity and performance to the service that they offer to customers. Another unique contribution of this study is that the paper examines workforce diversity from both primary and secondary dimensions of diversity thereby offering validated research-based recommendations to the management of a heterogenous work group.

2. Literature Review

2.1. Workforce Diversity

After three decades of talking about diversity in the workplace, there is still considerable debate and confusion over what actually constitutes workforce diversity (Gitonga, Kamaara & Orwa, 2016). There has been much debate whether diversity is physiological (age, gender, race) or should include any aspects of human resource heterogeneity. In terms of employee diversity, some scholars and authorities argue that diversity is broader whilst others coin that it should be viewed from a narrow perspective (Ehimare & Ogaga-Oghen, 2018).

Scholars favourably disposed to a narrow definition (Ehimare & Ogaga-Oghen, 2018; Lee & Gilbert, 2014) argue that the concept of diversity should be restricted to specific natural categories such as age and gender. Following the narrow understanding, employee diversity is understood as the degree of heterogeneity among employees that is precisely limited to specific natural attributes such as age, gender and ethnicity (Zhuwao, 2017).

The danger in narrowly defining diversity, however, is that only one dimension of natural diversity (race, age, ethnicity, or gender) is the subject of research at a time. Since a natural diversity dimension interacts with other dimensions of diversity, a narrow concept of diversity would be deficient by failing to recognize these interactions (Ehimare & Ogaga-Oghen, 2018).

Scholarly advocates of a broader understanding of employee diversity included Barak (2016) and Foma (2014). Using a broader understanding, Zhuwao (2017) defines workforce diversity as acknowledging, understanding, accepting, valuing and celebrating differences amongst people with respect to a whole continuum of differences including age, class, ethnicity, gender, physical and mental ability, race, economic status, sexual orientation, spiritual practice and public assistance status.

Therefore, from a broader view, all employees are unique in their own making. Ehimare and Ogaga-Oghen (2017) argue that if diversity is to be by any nature broader, the simple conclusion that ‘everyone is different’ would be accepted. In essence, Ehimare and Ogaga-Oghen (2017) note that a broader concept of diversity would therefore be meaningless, as anything can be different at any point using any measure.

Away from the broader or narrower debate of employee diversity, Alghazo and Shaiban (2016) define employee diversity as the heterogeneous composition of employees of the same organization in terms of gender, age, race and education background. Though the understanding of Alghazo and Shaiban (2016) brings out the idea of ‘diversity’, Barak (2016) critique that view by indicating that diversity relates to employee differences that extend to the values, organizational roles, occupation and behavioral styles. The middle of the park and rationalized understanding of workforce diversity was suggested by Ogbo and Ukpere (2014) who define it as the multitude of the individual differences and similarities that exist among the people working in an organization. Therefore, workforce diversity entails acceptance, respect and appreciation of each employee’s uniqueness.

Today’s workforce is getting more and more heterogeneous due to the effects of globalization (Chulanova, 2019; Gitonga, Kamaara & Orwa, 2016). Gupta (2017) seconded the views of Gitonga, et al. (2016) on the role of globalization, and adds that competition and the need for skilled labour force have also contributed to growth in diversity. Alghazo and Shaiban (2016) also posit that workplace diversity has been contributed by improvements in modern technology and the neatness of the global economy which has attracted different people from different ends of the globe.

2.2. Employee Productivity

Employee productivity is a multi-dimensional concept which refers to an employee’s proficiency with which a worker undertakes activities that contribute or add value to the organizational technical core, and contextual performance (Zhuwao, 2017). Employee productivity is largely a function of individual contribution (Makhdoomi & Nika, 2018). This understanding diverges from group thinking of considering the productivity of the organization as a whole, otherwise known as organizational performance. Thus, through employee productivity, the role that each individual employee plays is considered.

Other scholars such as Weiliang et al. (2011) broaden the discussion on employee productivity by considering the aspect of requisite duties. Employee productivity is the effective discharge of duty for which one is hired to do (Weiliang et al., 2011). This follows that employees may do several activities at the work place, however, what is mainly used to measure an employee’s performance is the extent to which the employee has accomplished his tasks as prescribed by the job description.

Zhuwao (2017) posits that employee productivity standards are set by various stakeholders. The main principal standard setter is the employer through the human capital management unit. However, other measures of performance are set within various functional aspects of the organization. For instance, a functional manager may set specific targets for his department. These targets must not conflict with the overall organizational goals. Thus, productivity standards may be set by a supervisor or organization, or some predefined acceptable standards. High performing employees are an asset to an organisation. In essence, if an organisation has more performing employees that acts as a predictor of the overall performance of the organisation (Maqpfara, 2020).

2.3. Dimensions of Workforce Diversity

Several theories have been proposed to address the aspect of workforce diversity. This paper reviews the heterogeneity theory, the social categorization theory and the dimensional theory. The main argument of the heterogeneity theory is that employees from a diverse background can produce different results depending on the nature in which their heterogeneity is handled by the organization (Blau, 1985). The heterogeneity theory posits that the dimensions of workforce diversity are two namely, heterogeneous and homogenous labor force. Heterogenous employees are diversified on the basis of race, gender and age; among other indicators, whilst a homogenous labor force is rare to find.

Turner (1987) in the social categorization theory suggests that individuals classify themselves on the basis of their social identities. Groups are more responsive to activities and information that is related to their social identities and which they purport to be strengthening their cohorts. The model also indicates that within a group of similar social identities, cooperation is high and they tend to be more productive as a group. Gitonga et al. (2016) also notes that using the social categorization theory, dissimilar individuals are less likely to collaborate with one another compared to similar individuals.

The dimensional theory of workforce diversity was largely populated by Rijamampianina and Carmichael (2005). The theory indicates that there are three dimensions of workforce diversity, namely: primary, secondary and tertiary. The primary dimension includes age, disability, ethnicity, race and gender. The secondary dimensions consist of culture, sexual orientation, thinking style, religion, lifestyle, economic status, education, nationality, geographic origin, political orientation, language, family status and work experience. The tertiary dimensions include assumptions, beliefs, feelings, values, group norms, attitudes, and perceptions which are the nucleus of an individual’s identity.

This paper was therefore informed by the above discussed theories, especially Rijamampianina and Carmichael (2005), towards the development of workforce diversity variables. Two primary dimensions and two secondary dimensions of workforce diversity were considered in this study

2.3.1. Age Diversity

Age diversity is characterized by differences on the basis of stages in life (Lee, 2019). Some employees are older than others and the age diversity theory posits that age presents significant organizational output variations among employee groups (Azam & Waheed, 2018). Age is prodigious in the family, at schools or any institution. It is also crucial at work place as most workplace activities are characterized by people of different age groups and categories (Gitonga et al., 2016). In line with Azam and Waheed (2018), there is no institution with employees of the same group, age varies across all aspects of the organization. An even farfetched example was given by Nyamubarwa (2013) who indicated that even in academic institutions where we would expect pupils of the same age, we would still see significant age variances and diversity.

The relationship of age and employee productivity has been previously theorized and reviewed empirically. It is essentially believed that employees between the ages of 30 and 40 years are more productive and fuller of energy and vigor (Gitonga et al., 2016). They can accomplish most tasks quickly and effectively. This category of employees is mainly self-reliant and they believe that they can change the world. Most of their activities are radical and innovation is usually the outcome of their performance. Zhuwao (2017) also states that these employees are generally referred to as young adults because of their medium level of maturity.

In terms of employee productivity, employees below the age of 30 are considered as keen knowledge acquirers. They are open minded and are willing to learn new things and new ways of increasing productivity. They are usually high performers and are mainly characterized of school leavers and fresh graduates. They look to cumbersome tasks with zeal and optimism. However, the major drawback of this age category on employee productivity included absence of organizational and life experience. Their decisions are usually based on intuition and not necessarily on practice. Productivity across groups with this age group is usually affected especially when this age group is working with those above 50 years, who usually use their experience to make decisions (Azam & Waheed, 2018; Busolo, 2017; Gitonga et al., 2016; Zhuwao, 2017).

Employees aged between 40 and 50 years are considered as the rational beings of the organizations. They usually make balanced decisions and their thinking and employee performance are balanced by work experience and need for excellence (Busolo, 2017). This age category consists of employees who have worked for a significant number of years. The majority of them have switched organizations in the past and so they have vast years of experience. Their experience makes them resourceful. Ekot (2017) suggests that this age group is mainly referred to when new recruits are oriented to the organizational culture.

Employees above the age of 50 years are essentially approaching the retirement age. Their priorities are usually focused on life after employment. Some of the employees in this category have rage and regrets over how they have failed to plan well for their retirement. Lee (2019) indicates that Korea is experiencing a rapid population aging as the older members of the community retire. When employees get to this age, they worry more about who will cater for them and worry less about how to enhance employee productivity (Ekot, 2017). This is the most unproductive group of all employees especially when an employee holds a non-managerial position. However, Azam and Waheed (2018) also indicates that this is the most resourceful age group. Most managers are in this age category as well as most company directors and executives. They have significant experience which they can use to further the performance of the organization, and of individuals. However, employee productivity maybe dysfunctional because individuals tend to favor members of their own age group at the expense of the other age groups, against which they may discriminate (Weiliang, et al, 2011).

The study therefore posits the following hypothesis:

H1: Age diversity positively affects employee productivity.

2.3.2. Gender Diversity

Gender diversity relates to the extent to which both male and female employees work together (Ehimare & Ogagaoghene, 2011). Gender diversity studies follow that differences between males and females are significant enough to lead to organizational dysfunctional or organizational performance (Gellner & Veen, 2019; Makhdoomi & Nika, 2018; Ogbo & Ukpere, 2014). This follows that males and females respond differently to certain organizational stimuli.

In poorly managed and yet diversified organizations, gender diversity is more likely to lead towards stereotypes and discrimination (Ogbo & Ukpere, 2014; Olga, et al., 2020). Females are usually the main victims as they are at times denied the social support to rise to some organizational positions which are regarded as masculine. However, Gellner and Veen (2019) indicate that most female employees have broken the glass ceiling and accepted and performed well in senior positions. This disconfirms the trait theory which indicates that females are meant to take orders and not to issue orders. In such cases employee productivity is enhanced as female employees self-actualize.

There are numerous employee performance related benefits that are associated with gender diversity. Weiliang, et al. (2011) support this notion as they posit that women are naturally enthusiastic, cheerful and sympathetic social animals. This accords well with the liaison skill much desired to lure customers. The same notion is upheld especially when the work task involves boundary spanning. Female employees are more characterized of deep emotional labour acting as compared to males who are more of surface acting (Makudza, 2020). That helps female employees to perform better without negative effects of emotional burn out.

Even in situations where males and females work together, productivity per employee may increase as well as output of groups. A study by Mandiq and Nolisal (2020) indicates that mixed groups of both males and females performed better than gender-based groups of males only or females only (P = 0.02). Though their study could not offer factual reasons for that development, results from the work of Hur et al. (2010) indicate that with employees of the same gender, non-value adding activities do affect the productivity levels per employee.

In light of the foregoing discussion, the following hypothesis was stated:

H2: Gender diversity positively affects employee productivity.

2.3.3. Educational Diversity

Educational diversity emanates from training at school or college or career development through experience and apprenticeship. It has been a long-standing hypothesis that the most educated ones are the most productive employees. It has been a hypothesis because it is not always true, in fact that notion has created a stereotype and workforce division between the so called learned and the unlettered. The division has been dysfunctional because it affects employee productivity when working within a group (Alghazo & Shaiban, 2016; Daniel et al., 2016).

Daniel et al. (2016) discovered that different levels of education expect different mobility rates. For instance, there are various occupations that are available for different sets of people. The type of occupation that is available for someone who has gained some years of work experience but does not have a university degree in a course of study is different from the one who has the required certificate from the university. Based on Daniel et al. (2016)’s findings, an employee’s productivity depends on the level of education he/ she has acquired.

The Daniel et al. (2016)’s result brought about a controversial aspect of what really constitute education. Whether education should be regarded as university or tertiary qualification or should be considered on job learning. Alghazo and Shaiban (2016) indicate that in some organizations, conflict emanates from this variance. At work place there are clans or groups on the basis of the employees’ former universities or colleges. The same notion was also uncovered by Akinnusi et al. (2017), who even note that the effect even affects the human capital management aspects whereby students from a certain educational institution are favored for employment by the human resource department.

Based on the discussed literature, the study states the following hypothesis:

H3: Educational diversity positively affects employee productivity.

2.3.4. Political Affiliation Diversity

Very few studies have focused on political affiliation diversity (Daniel et al., 2016; Andrews et al., 2016). Maqpfara (2020) postulated that maybe it was because most studies on diversity were done in the developed nations were politics is fairly viewed. However, Maqpfara (2020) found out that political affiliation can be a serious source of conflict and heterogeneity which heavily affect work performance notably in Africa. In fact, a study by Daniel et al. (2016) notes that some employees would hate and hurt each other on the basis of differences in political affiliations. In this study, political affiliation matters in view of the sample population in consideration which involved the civil service. Civil service’s nature of the job requires active participation in national policy formulation and execution. This makes political affiliation diversity a more fundamental aspect in this study.

When employees of the same organization have different political views and orientations, this affects their performance. Every effort to enhance the working environment or innovation is stifled as it is considered a political move. The contributions of individual employees are overshadowed by political overstatements which contribute to the success of certain political affiliations (Andrews et al., 2016).

However, Daniel et al. (2016) argue that diversity on the basis of politics enhances productivity through the provision of checks and balances. The reasoning follows that there is an oversight political role in what employees do, so employee productivity would increase as employees would work towards innovating for their aligned political affiliations.

The following hypothesis was thus stated in this study:

H4: Political affiliation diversity positively affects employee productivity.

2.4. Customer Experience

Customer experience is the perceptual view of how customers perceive the way that they are treated by their brands (Makudza, 2020). Buttle (2009) defines customer experience as the cognitive and affective outcome of the customer’s exposure to, or interaction with, a company’s people, processes, technologies, products, services and other outputs. Customer experience is managed at customer touch points. Customer touch points relate to all encounters that the customer interacts with the company, brand or offering. A good customer experience management strategy not only leads to customer satisfaction, but leads to brand loyalty and high patronage (Buttle, 2009; Makudza, 2020).

According to Usman, Sobari and AlHasan (2020), customer experience is the result of a set of interactions between the customer and the service. When customers interact with brands, they measure their expectations of the product/ service against the actual performance of the product/ service. If the performance of the service surpasses the customer’s expectation, the brand has offered an exquisite customer experience. However, if the customers’ expectations are outweighed by the customers’ perception, the brand has offered poor customer experience (Makudza, 2020; Rooney, Krolikowska & Bruce, 2020).

Modern customers are not after the core product or the core service, they aspire to have a unique experience with their brands (Zhong & Moon, 2020). Instead of just buying, well to do companies offer a buying experience. In that regards, banks should not just offer banking services but they should offer a banking experience, retailers should not just offer an assortment of products, but they should offer a shopping experience (Makudza, 2020).

To enhance customer experience, employees of service organizations train boundary spanners to serve customers with exquisite delight (Becker & Jaakkola, 2020). Some companies engage in emotional labour practices so as to foster the desired emotional experience to their customers (Aksar, Kayani & Ali, 2019; Noh & Cha, 2020). This notion is based on the psychological orientation of emotional contagion, which shares the belief that if an employee presents a jovial mood, customers are more likely to experience the same feeling and emotions. This does not merely lead to satisfaction, but enhances the customer’s experience with the brand (Becker & Jaakkola, 2020; Makudza, 2020).

The study therefore posits that there is a direct association between employee productivity and customer experience. The following hypothesis was thus stated:

H5: Employee productivity directly impacts on customer experience.

2.5. Conceptual Framework

The study investigated the effect of workforce diversity (WD) features β1 – β4 on employee productivity (EP) and customer experience (CX); where workforce diversity (WD) was considered as follows:

WD = ∑[AD+ GD + ED + PAD]       (1)

The following regression equations were thus applied to analyse the effect of workforce diversity on employee productivity and customer experience:

EP= β0 + β1AD+ β2GD + β3ED + β3PAD       (2)

CX= β0 + β1EP       (3)

Where EP is employee productivity, AD is age diversity, GD is gender diversity, ED is educational diversity, PAD is political affiliation diversity, CX is customer experience. Figure 1 below diagrammatically presents the conceptual model.

Figure 1: The Conceptual Framework

3. Methodology

The study followed a causal research design to understand the effect of workforce diversity as a driving tool of employee productivity and customer experience. Data was collected from state employees of the government of Zimbabwe using a structured questionnaire. Randomization was used to collect 324 validated responses. The study targeted the Zimbabwean civil service with the understanding that the government is one major employer to a highly diversified labor force in Zimbabwe; yet the productivity of its employees seems to be dwindling at the same rate as the customer experience.

4. Results and Discussion

The reliability of the questionnaire variables was measured using the Cronbach Alpha test and all study variables were found to be statistically reliable with the Cronbach coefficients above 0.77.

Presence of gender diversity was confirmed in the sample as both males and females were represented. However, the sample was overly dominated by males who constituted 81.5% of the entire respondents, with only 18.5% being females.

All age groups were well represented from 18 years to above 55 years. This indicates that the working environment was age diversified. Most employees were in age category 36 to 34 which represented 46% of the entire study, followed by age group 26 to 35; 46 to 55 (25%) and 20.2% respectively.

There was also evidence of educational diversity. This follows the conscious realization that employees had varied levels of academic qualifications. The majority of employees (39.5%) were diploma holders, followed by 22.6% with degrees and 24.2% with certificates. Only 10.5% of respondents had high school qualifications and 3.2% had post graduate degrees.

The majority of respondents also indicated that they do not belong to the same political party, which indicates political affiliation diversity

4.1. The Effect of Employee Diversity on Employee Productivity

To test the study hypotheses, regression and correlation statistical tests were used. Table 1 shows the effect of employee primary and secondary dimensions of workforce diversity on employee productivity, whilst Table 2 further depicts correlation test results.

Table 1: The coefficients of the workforce diversity model

Note: ^a. Dependent Variable: Employee Productivity

Table 2: The correlations of the study variables

Note: ** Correlation is significant at the 0.01 level (2-tailed).

Workforce diversity, through its four dimensions in the study model, explains employee productivity by 66.8% (Adjusted r² = 0.668). This shows a relatively high impact of political diversity, educational diversity, age diversity and gender diversity on employee productivity. This also implies that the model is a good model to predict employee productivity. The model was also statistically significant (P = 0.00).

Gender diversity had a negative beta value of -0.393 (Table 1), with a T value of -7.374 and a p-value of 0.00. This shows that gender diversity significantly and inversely impacts on employee productivity. The correlation between gender diversity and employee productivity was also moderate and inverse (r = -0.507; P = 0.00). The study therefore rejected the null hypothesis and concluded that there is statistical evidence that gender diversity has a negative impact on employee performance (H₁). This means that when gender diversity increases, employee productivity is reduced. In other ways, the study found out that employees perform better when they are working with related gender members. The current results were contrary to most empirical findings in literature (Alghazo & Shaiban, 2016; Ogbo & Ukpere, 2014). A rather supportive result to the current study was observed by Zhuwao (2017) who notes that when there is a weaker diversity plan, majority gender elements tend to manipulate the system for their own benefit and to cause conflict especially on the basis of gender.

Workforce diversity, through its four dimensions in the study model, explains employee productivity by 66.8% (Adjusted r² = 0.668). This shows a relatively high impact of political diversity, educational diversity, age diversity and gender diversity on employee productivity. This also implies that the model is a good model to predict employee productivity. The model was also statistically significant (P = 0.00).

Gender diversity had a negative beta value of -0.393 (Table 1), with a T value of -7.374 and a p-value of 0.00. This shows that gender diversity significantly and inversely impacts on employee productivity. The correlation between gender diversity and employee productivity was also moderate and inverse (r = -0.507; P = 0.00). The study therefore rejected the null hypothesis and concluded that there is statistical evidence that gender diversity has a negative impact on employee performance (H₁). This means that when gender diversity increases, employee productivity is reduced. In other ways, the study found out that employees perform better when they are working with related gender members. The current results were contrary to most empirical findings in literature (Alghazo & Shaiban, 2016; Ogbo & Ukpere, 2014). A rather supportive result to the current study was observed by Zhuwao (2017) who notes that when there is a weaker diversity plan, majority gender elements tend to manipulate the system for their own benefit and to cause conflict especially on the basis of gender.

Age diversity was not statistically significantly related to employee productivity (𝛽= -0.033, T = -0.619, P = 0.537). We therefore accepted the null hypothesis and concluded that there is no statistical evidence that age diversity of employees affects employee productivity (H₂). The interpretation of the results is that age variations of employees do not affect their productivity. Productivity of employees is not predicted by age diversity. In a related study by Gellner and Veen (2019), they found out that when individuals engage in routine repetitive tasks, there are no substantial gains from age heterogeneity that could offset the increasing costs resulting from greater age heterogeneity.

Education diversity enhances employee productivity (𝛽=0.163, T = 3.114, P = 0.002). This indicates that education diversity explains employee performance by a factor of 16%. Conversely, using the Pearson Correlation test results (Table 2), the study found a correlation coefficient of 0.261 (P =0.00). This shows a weak association between educational diversity and employee productivity. We therefore rejected the null hypothesis and concluded that there is statistical evidence that educational diversity has a positive impact on employee productivity (H₃). These results mean that employees perform better when they are of varied educational backgrounds. However, the impact was low, meaning that the effect of educational diversity has a low effect on employee productivity. The current results were also confirmed by other scholars (Ogbo & Ukpere, 2014; Simons & Rowland, 2011).

Political affiliation diversity had a beta coefficient of 0.617, with a T-value of 11.1 and a P-value of 0.00. This shows a high impact of political diversity on employee productivity. The study found a correlation coefficient of 0.703 between political affiliation diversity and employee productivity. This follows that the higher the political diversity the higher the employee productivity. The study therefore rejected the null hypothesis and concludes that there is statistical evidence that political affiliation diversity has a strong positive impact on employee performance (H₄). That means when employees work together with other employees with different political affiliations their productivity is enhanced. Political affiliation diversity calls for checks and balances which promote quality work and productivity (Daniel et al., 2016). When there is no questioning of work done, complacency emanate and productivity goes down (Maqpfara, 2020). This was more pronounced among the sample population given the fact that they are run by politically-elected members who belong to different political parties. Thus, members of the other party would want to scrutinize all done by other members of the other party leading to competitive job performance and employee productivity.

4.2. The Effect of Employee Productivity on Customer Experience

Table 3 shows the association and impact factor of employee productivity on customer experience.

Table 3: The relationship between employee productivity and customer experience

Note: ^a. Predictors: (Constant), Employee productivity

The study found that employee productivity is a moderately-weak predictor of customer experience (r² =0.368, p = 0.00). The association was moderately strong and significant (r = 0.53; P = 0.00). The study thus concluded that there is statistical evidence that employee productivity improves customer experience (H₅). That conclusion means that if employees are more productive, the exquisiteness of the customer-employee interaction is significantly improved. This therefore informs the need to strongly manage a diversified labor force among Zimbabwean state employees so as to enhance both employee productivity and customer experience. Becker and Jaakkola (2020) emphasize that customers enjoy the service interaction as a result of the experience they gain from the service providers at various touch points. Zhong and Moon (2020) also concur and indicate that an exquisite customer experience is directly linked to boundary spanner’s role through a strong dyadic customer- employee engagement.

5. Conclusions

The study validated the role of workforce diversification as a springboard for employee productivity and customer experience. The study thus concludes that when heterogeneous groups of employees work together, they are likely to be more productive. When employees are more productive, they will work hard towards surpassing customer expectations. The study further concludes that both primary (age and gender) and secondary (education and political affiliation) dimensions of workforce diversity were evident in the sample. However, the study concluded that not all dimensions of workforce diversity were statistically significant. Age diversity recorded an insignificant effect on employee productivity, whilst gender recorded a moderate inverse impact. All secondary dimensions of diversity were positively related to productivity. The study further concluded that the association between employee productivity and customer experience is discoverable and positive.

The study invokes human resource and marketing practical implications as well as theoretical implications. Following the statistical evidence of workforce diversity, the human resource function should erect structures and policies that are tolerant of employees’ unique characteristics. A workforce diversity management framework is thus imminent. The marketing unit and the human resource unit should work in unison so as to develop boundary spanners who exceed customer’s expectations. Future studies on diversification will find this study beneficial in understanding and theorizing primary and secondary dimensions of workforce diversity as well as linking the role of employees to customers.

The study thus recommends that different employees be treated differently so as to explore the best out of workforce diversity. This can be done by developing a workforce diversity framework which can be used to manage employee education, political affiliation and gender variations.

The study suffered some limitations. In this study, workforce diversity was understood by considering only four variables of primary and secondary dimensions of workforce diversity. However, there may be many other dimensions and variables of diversity which impact on employee productivity. Another limitation is that this is the first-time workforce diversity, employee productivity and customer experience are modelled together. There is need to further test the model in different situations to guarantee its integrity. Regardless of the said limitations, the study managed to validate the catalytic role of workforce diversity in “breeding” employee productivity and customer experience.