More emphasis is placed on people issues when adopting digital HRM practices across the HR value chain (Bondarouk et al., 2017). This is because of every aspect of the business operation involving human beings and people being the end users of HRM service delivery. Hence, if people issues are ignored, the success rate and intended purpose of adopting digital HRM practices within organisations could be derailed. In this respect, Thite and Bhatta (2019) observe that the failure rate of digital technology projects is often caused by paying more attention to technology than to people and process issues. This failure correlates with a lack of executive support, emotional maturity, user involvement and the availability of skilled staff as four of the top five factors affecting the adoption of technology (Hastie & Wojewoda, 2015). These factors are all people factors, placing technology as a secondary issue. In managing the human aspect in the adoption of digital HRM, pertinent factors that require attention include user reaction, involvement, satisfaction and acceptance, communication or collaboration with stakeholders, buy-in from top management and HRM skills and leadership (Burbach, 2019). This suggest that HRM practitioners must consider the needs of employees and line managers when planning, designing and adopting digital HRM technology solutions across the HR value chain. The approach of designing processes and practices with the user experience in mind is called ‘design thinking’ (Thite & Bhatta, 2019).

Top management support is viewed as the most influential factor. Top management provides finance, support and emotional backing for the adoption of digital HRM (Bondarouk et al., 2017; Muhammad, 2018). Top management should not regard the adoption of digital HRM as a less important and costly investment (Bondarouk et al., 2017). It is therefore important that HRM practitioners gain the support and commitment of top management and provide regular feedback to them. In addition, HRM practitioners should build a strong business case for their digital HRM agenda to gain support and funding from top management, by illustrating the link between the digital HRM agenda and the overall business digital agenda (Ulrich, 2019). Ulrich (2019, p. xvi) underlines that ‘HR is not about HR, but about delivering value to employees, organisations, customers, investors and communities’. Therefore, HRM practitioners should get clarity on their current digital HRM position in relation to where they want to be (audit and vision) and craft strategies to get there (Thite, 2019).

Users of digital HRM such as HRM practitioners, line managers and employees expect HRM solutions and service delivery that are easy to use, efficient and that add value (Burbach, 2019). Conversely, digital HRM solutions that do not empower end users will have a low adoption rate. It is expected that HRM practitioners themselves may not have all the skills required and therefore have to collaborate with essential other people, such as experts from information and technology (IT), in articulating the digital HRM agenda (Bondarouk et al., 2017). Line managers and general employees must be trained in the use of digital HRM practices (Hosain, 2019) to increase their motivation and a positive attitude towards the adoption of digital HRM.

It is a concern that HRM practitioners may not have the required expertise to articulate a digital HRM strategy (Dhanpat et al., 2020). Crummenerl et al. (2018) emphasise that, in the context of 4IR, HRM practitioners need digital skills to be agile enablers, innovation architects, data analysts and act as digital consultants in the adoption of digital HRM practices. To act as strategic partners in the new world of work, entry-level HRM practitioners also need to be competent in digital HRM processes, data processing and identifying trends (Joseph et al., 2021). However, it is a concern that HRM practitioners are believed to be mostly experts in the entry, editing and retrieval of data, tasks that demand less analytical and technical skills (Hannon et al., 2020). The upskilling or reskilling of these practitioners is essential for the successful adoption of digital HRM.

Data integrity is also indicated as challenge in digital HRM, with Subramaniyan et al. (2019) observing that transformation in technology in the new world of work has compounded issues related to the loss and leakage of data because of the vague ownership of data. As such, HRM practitioners, managers and employees are rendered vulnerable. In South Africa, laws such as the Protection of Personal Information (Act 4 of 2013) (POPIA) requires organisations to develop effective organisational policies, guidelines and practices, to ensure information security and privacy.

Organisational factors such as size, capabilities, structure and culture could influence the rate at which digital technology is adopted. Organisations with large amounts of capital that trade on large scale find the adoption of digital HRM easier than those without such capital as the digitalisation of HRM requires a large financial investment (Hosain, 2019). As such, small businesses struggle to invest in digital HRM (Muhammad, 2018). Financial resources are required for technology, combat the risk of hackers and train HRM practitioners and employees (Brahma, 2020; Zavyalova et al., 2022). Similarly, bureaucratic structures as opposed to centralised organisational structures discourage the adoption of digital HRM. Thite (2019) stresses the importance of reducing red tape in the switch to technology and recommends the adoption of a centralised structure, which aids quick decision making and fosters agility.

However, it should be noticed that centralised structures are inflexible and susceptible to discouraging creativity and innovation within organisations (Büschgens et al., 2013). Zavyalova et al. (2022) boldly state that a lack of digital orientation within the organisational culture is a main barrier to the adoption of digital HRM. This view is supported by Kokt (2019) who states that, in the new world of work, openness and flexibility are a prerequisite for change.

Other challenges cited are an unclear vision and ambiguous goals and competition in the allocation of resources (Burbach, 2019). In this regard, because of a lack of knowledge of digital HRM technologies, inadequate research and a lack of digital skills, HRM practitioners may adopt too ambitious digital HRM agendas that are likely to fail (Ghosh & Tripathi, 2018). Ghosh and Tripathi (2018) suggest a step-by-step approach to the implementation of digital HRM to meet the resource capacity of the organisation and reduce the risk of failure.

Larger organisations are more likely to deploy state-of-the-art technologies (Thite, 2019). Technological factors to consider include IT infrastructure, technological compatibility, technology complexity and the relative advantage of technology (Alam et al., 2016; Muhammad, 2018). Alam et al. (2016) argue that IT infrastructure is most significant in the adoption of digital HRM and refers to the availability of computers, software, hardware, data, networks, computing resources, applications and devices. This view is supported by Al-Mobaideen et al. (2013) who found a positive correlation between rich technological infrastructure and the successful adoption of digital HRM.

In addition, complex technology, which is difficult to understand and implement, is likely to face resistance from HRM practitioners and other users (Al-Mobaideen et al., 2013). This strengthens the assertion that the adoption of technology positively correlates with ease of use, benefit to the user and provision of support to the user (Andersson et al., 2016). Pillai and Sivathanu (2020) underscore that digital HRM technology solutions should enable users (HRM practitioners, line managers, employees) to easily execute their tasks.

For sufficient support in the implementation of digital HRM, in addition to having technological skills (Joseph et al., 2021; Schultz, 2021), the HRM team should collaborate with IT professionals who deal with technology in their daily operational tasks (Andersson et al., 2016). On the other hand, Muhammad (2018) posits that digital HRM technology should be compatible with the culture, values, overall strategy, practices and the organisation’s other digital technology solutions. This challenges HRM practitioners to be both business partners and digital technology proponents to be successful in the implementation of digital HRM (Andersson et al., 2016).

The degree of digital technology adoption varies across the world and continents and within countries. This is because of unevenness in the intensity and penetration of technology across the world (Thite, 2019). As such, organisations operating in different countries may do so at different levels to accommodate different technology adoption policies and practices in the different countries (Thite, 2019). Other environmental factors that impact the adoption of technology include legislation, social cultures, different levels of competitive pressure and political freedom, extent of support offered by government and the support offered by HRM technology vendors to their clients (Alam et al., 2016). In countries with restrictive laws for the adoption of technology and where the freedom of citizens is limited, organisations struggle to adopt digital HRM even if they are able to source global and digital talent (Ahmadi et al., 2015; Thite, 2020). This is despite the pressure exerted by the 4IR and subsequently the COVID-19, which forced many organisations to adopt digital HRM (Komm et al., 2021). In South Africa, for example, labour laws and the POPIA should be adhered to at all times and considered in the implementation of digital HRM.

Particularly small organisations without internal IT expertise and IT infrastructure may have to use external consultants or vendors to digitalise their HRM functions (Baykal, 2019). According to Bersin (2021) successful vendors of digital HRM technology are those supplying quality technological solutions that improve both the productivity and overall experience of employees. As such, HRM practitioners also require digital competencies to negotiate viable digital HRM technology to deal with vendors (Joseph et al., 2021; Schultz, 2021).

Table 1 presents a summary of challenges that organisations typically face in the adoption of digital HRM, as gleaned from the literature review.

The population for this study comprised 160 automotive manufacturing companies in the Eastern Cape Province of South Africa (NAACAM or NAAMSA, 2018). The participants for this study, namely representatives of these organisations, included HRM professionals and line managers who were recruited via purposive and snowball sampling methods. A total of 425 questionnaires were distributed to the targeted respondents.

For this study, an online questionnaire administered on the platform QuestionPro was used to collect data. The questionnaire comprised three sections. The first section elicited demographic information and the second section measured challenges experienced in the adoption of digital HRM practices. This second section contained 22 items on a five-point Likert rating scale with answer options ranging from not at all (1), small extent (2), moderate extent (3) great extent (4) to very great extent (5). Examples of items in this section included ‘difficulties in customising to digital HRM’, ‘a lack of awareness or knowledge of HRM digitalisation’, ‘a lack of buy-in from senior or top management’, ‘data security concerns’ and ‘lack of conducting an audit for HRM technology suitability’, as also depicted in Figure 2. As there was no existing validated questionnaire found, the items included in this section were derived from the literature review conducted on challenges that influenced the adoption of digital HRM. A Cronbach’s alpha coefficient of 0.97 confirmed reliability of this scale.

The third section measured the extent to which digital HRM practices were adopted in the organisations of the respondents. This section included 34 items. Items for this section were based on the seven functional areas contained in the SABPP HRM System Standards Model, as well as 30 HR professional practice standards (SABPP, 2014), which are considered the architecture of HRM in South Africa. Examples of items included in this section were ‘digital recruitment’, ‘digital selection’, ‘digital management of grievance procedure’, ‘digital management of remuneration practices’ and ‘digital instilling of a culture of adaptability and flexibility’. These items were also measured on a five-point Likert rating scale, ranging from not at all (1), small extent (2), moderate extent (3) great extent (4) to very great extent (5). This third section was included to ascertain, through regression analysis, the extent to which the identified challenges influenced the adoption of digital HRM practices. Cronbach’s alpha coefficients for factors that emerged from this section ranged above 0.8, indicating reliability of the scale.

Ethical approval to conduct the study was obtained from the university from where the study was conducted. Ethical considerations included being transparent about the purpose of the study, voluntary participation of the respondents and the right to withdraw at any given time. Anonymity was ensured through using a web-administered survey instrument, which was accompanied by a cover letter and guidelines on how to complete the questionnaire. Consent was indicated and withdrawal was enabled through an exit button.

Descriptive and inferential statistics were used to analyse the collected data. Utilising the Statistical Package for Social Sciences (SPSS) version 27, exploratory factor analysis (EFA) was conducted to establish structures and latent factors underlying the item variables. The results of Kaiser–Meyer–Olkin (KMO) and Bartlett’s Test of Sphericity (BTS) showed sampling adequacy and data suitability for EFA (Hair et al., 2018). The KMOs for the sections ‘challenges’ and ‘digital HRM practices’ were 0.959 and 0.929, respectively, and sphericity on the BTS was indicated at 0.000. The factor extraction method used was principal axis factoring (PAF) (Williams et al., 2012). Descriptive statistics were used to describe and explain the factors, while Pearson product-moment correlation and regression analysis were used to establish and explain relationships between the factors measured.

Ethical clearance to conduct this study was obtained from Nelson Mandela University Research Ethics Committee (H20-BES-HRM-016. 14 April 2020).

The pattern matrix and related loadings produced one factor for the variables measuring challenges experienced in the adoption of digital HRM practices, and this factor was labelled ‘Challenges’. These challenges were discussed in the literature review and are listed in Figure 2, with the mean scores obtained for each item. For sample sizes of 300, a factor loading of 0.30 is considered significant (Hair et al., 2018). In this study, all the items for ‘Challenges’ were valid as they revealed loadings higher than the acceptable 0.3, with the highest loading being 0.883 and the lowest 0.584 (Hair et al., 2018).

Figure 2 shows that the variable ‘competing organisational priorities’ accounted for the highest perceived obstacle in the adoption of digital HRM practices with a mean of 4.28, followed by ‘a lack of conducting an audit for digital HRM technology suitability’ (M = 4.20), ‘difficulties in customising to digital HRM’ (M = 4.17), ‘bureaucratic structure’ (M = 4.16), ‘a lack of awareness or knowledge of HRM digitalisation’ (M = 4.16), ‘data security concerns’ (M = 4.15), ‘unclear goals or vision for HRM digitalisation’ (M = 4.08), ‘resistance to change’ (M = 4.08), ‘lack of involving diverse people groups’ (M = 4.07), ‘HRM digitalisation seen as an issue for HRM management only’ (M = 4.07), ‘passive organisational culture’ (M = 4.04), ‘inadequate training in using digital HRM processes’ (M = 4.03) and ‘lack of buy-in from senior or top management’ (M = 4.01). Overall, all the variables obtained mean scores of above 3.00, with the factor ‘restrictive labour laws’ accounting for the least perceived obstacle in the adoption of digital HRM (M = 3.38). This shows that the respondents perceived these identified challenges as obstacles in the adoption of digital HRM practices across the HR value chain within their organisations.

Concerning the EFA, four factors were extracted from the variables measuring adoption of digital HRM practices. In examining the items that clustered together within each factor for ‘Digital HRM Practices’, the four factors were labelled as follows:

All the items were valid as they loaded onto each factor, revealing loadings higher than 0.30, with the highest loading being 1.02 and the lowest 0.374 (Hair et al., 2018). Digital HRM practices clustered together on Factor 1 (Digital Talent Management Practices) relate to the digital acquisition, onboarding, remuneration, development, management of performance, succession planning and retention of talented people within the organisation, as well as digital leadership development and predictive HR analytics. Items that clustered together on Factor 2 (Digital Organisational Design and Culture Practices) relate to the digital management of organisational culture and design, including the use of HR dashboards and scorecards, development of programmes to coordinate human and machine interaction, use of chatbots to resolve employees’ HR-related queries, digital ethics and risk management and digitally enabling adaptability and flexibility. Factor 3 (Digital Employment Relations Management Practices) items relate to the digital management of the employment relationship, including digital management of employment relation processes, digital diversity management and digital management of grievance, disciplinary and collective bargaining processes, as well as the digital monitoring of employee wellness, and digital coaching and mentoring. Factor 4 (Digital Media Practices) items relate to everyday digital HRM practices, applications and platforms that keep employees connected, including the use of mobile applications to transact HR work, digital absenteeism management and the use of social media platforms such as Whatsapp, Facebook, Twitter and Linkedin, to advertise jobs and connect staff.

Descriptive statistics and Cronbach’s alpha coefficients obtained for the factors Digital HRM Practices and Challenges are depicted in Table 2.

The Cronbach’s alpha coefficients obtained for Challenges is 0.978 and for the Digital HRM practices range from 0.807 to 0.944. These coefficients indicate that both the questionnaire and data collected are reliable and valid. Challenges obtained the highest mean and standard deviation scores (M = 4.00; SD = 0.91), indicating that the respondents experienced to a ‘great extent’ the challenges as obstacles in the adoption of digital HRM practices, with consistency in the way they responded to the items loading onto this factor. Digital Media Practices obtained the highest mean score (M = 3.69; SD = 0.88), followed by Digital Talent Management Practices (M = 3.52; SD = 0.74), Digital Organisational Design and Culture Practices (M = 3.11; SD = 0.84) and lastly Digital Employment Relations Management Practices (M = 2.88; SD = 0.87). These mean scores with accompanying standard deviations (SDs) showed that the respondents to a ‘great extent’ experienced the adoption of Digital Media Practices and Digital Talent Management Practices, while they experienced to a ‘moderate extent’ the adoption of Digital Organisational Design and Culture Practices and Digital Employment Relations Management Practices in their organisations.

Pearson product-moment correlation statistics are outlined in Table 3 and indicate how the factor challenges relate to Digital HRM Practice factors as identified in the EFA. Interestingly, the results reveal weak correlations between challenges and all the digital HRM practice factors. Notably, while all the correlations are weak, positive correlations are identified between Challenges and Digital Talent Management Practices (0.01) and between Challenges and Digital Media Practices (0.115), with the latter being significant at a 0.05 level. This suggests that an increase, albeit a small one, in the adoption of Digital Talent Management Practices and Digital Media Practices correlates with a small increase in Challenges. On the other hand, negative and significant correlations (−0.166) were identified between Challenges and Digital Organisational Design and Cultural Practices and between Challenges and Digital Employment Relations Practices (−0.167) (see Table 3). This suggests that the adoption of these Digital HRM Practices were decreasing with every increase in Challenges, with significance at a 0.01 level.

To provide further insight into the relationship and connectedness between Challenges and Digital HRM practice factors, regression statistics were computed. As summarised in Table 4, Challenges as a predictor explains 0.00% of the variance in adoption of Digital Talent Management Practices. The F-value (F = 0.034), p-value (p = 0.854), (t = 0.185), unstandardised coefficient (β = 0.008) and standardised coefficient (β = 0.01) indicate that the Challenges insignificantly predict the variance in Digital Talent Management Practices.

As summarised in Table 5, Challenges as a predictor explained 2.7% of the variance in adoption of Digital Organisational Design and Culture Practices. The F-value (F = 8.754), p-value (p = 0.003), (t = −2.959), unstandardised coefficient (β = −0.153) and standardised coefficient (β = −0.166) indicate that Challenges significantly predict the variance in Digital Organisational Design and Culture Practices. In addition, the negative nature of the unstandardised and standardised coefficients indicate that the Challenges is an obstacle to the adoption of Digital Organisational Design and Culture Practices in the organisations although with a small effect.

As summarised in Table 6, Challenges, as a predictor, explain 2.8% of the variance in adoption of Digital Employment Relationship Practices. The F-value (F = 8.853), p-value (p = 0.003), (t = −2.975), unstandardised coefficient (β = −0.158) and standardised coefficient (β = −0.167) indicate that the Challenges significantly predict the variance in Digital Employment Relationship Practices. In addition, the negative nature of the unstandardised and standardised coefficients indicate that the Challenges is an obstacle to the adoption of Digital Employment Relationship Practices in organisations although the effect is small.

As summarised in Table 7, Challenges, as a predictor, explain 1.3% of the variance in the adoption of Digital Media Practices. The F-value (F = 4.119), p-value (p = 0.043), (t = 2.03), unstandardised coefficient (β = 0.11) and standardised coefficient (β = 0.115) indicate that Challenges significantly predict the variance in Digital Media Practices. However, the positive signs of the unstandardised and standardised coefficients indicate that the Challenges are not an obstacle in the adoption of Digital Media Practices in organisations.

This study aimed at identifying challenges that influence the adoption of digital HRM practices across the HR value chain in the South African workplace. The following discussion focuses on the results for Challenges, Adoption of Digital HRM Practices and correlation and regression analyses.

The results for Challenges, as presented in Figure 2, suggest a range of challenges were perceived as obstacles in the adoption of digital HRM practices. These included issues such as a lack of a vision and goals for HRM digitalisation, digitalisation being seen as an HRM issue, not involving diverse people groups, data security concerns, inadequate training, bureaucracy, lack of top management support, competing priorities, a passive organisational culture and resistance to change. Challenges emerged as one factor in the EFA, with an aggregate mean score of 4.00 and SD of 0.91 and being indicative of the ‘great extent’ answer option (Table 2). The scale itself was found reliable with an alpha coefficient of 0.978 obtained option (Table 2).

The results for Digital HRM practices leaned towards the answer option ‘great extent’ for adoption of Digital Talent Management and Digital Media Practices and ‘moderate extent’ for adoption of Digital Organisational Design and Culture and Digital Employment Relations Management Practices. These factors emerged as the focus areas of HRM digitalisation across the HR value chain and could be seen as an emerging Digital HRM value chain. The scales for these factors were found reliable, with alpha coefficients ranging from 0.807 to 0.944 (Table 2). Considering the results, it is observed that even though challenges were experienced in the adoption of digital HRM practices, digital HRM practices were still adopted to a moderate or great extent (Figure 2 and Table 2). It was the intention of this study to determine whether the challenges experienced effected the adoption of digital HRM practices. The outcome could be that the challenges experienced hindered the adoption of digital HRM practices or that the challenges experienced spurred the adoption of digital HRM practices, with HRM digitalisation possibly being seen as a panacea for dealing with the challenges experienced. It was also plausible that no relationship existed between the Challenges and Digital HRM practices. As such, correlation analysis was performed and after that regression analysis.

Interestingly, the correlation analysis (Table 3) revealed weak correlations between Challenges and all four Digital HRM practice factors, with the correlation between Challenges and Digital Media Practices (0.115) found positive and significant. Negative, weak but significant correlations were found between Challenges and Digital Organisational Design and Culture Practices (−0.166) and between Challenges and Digital Employment Relations Practices (−0.167). The very weak correlation between Challenges and Digital Talent Management (0.01) was found significant. As such, the correlation analysis could not convincingly illustrate a relation between Challenges and the adoption of Digital HRM practices.

In addition, results from the regression analysis revealed that the Challenges had no effect (R square 0.00) on the adoption of Digital Talent Management Practices and predicted only 2.7% of the variance in Digital Organisational Design and Culture Practices, 2.8% of the variance in Digital Employment Relations Practice and 1.3% of the variance in Digital Media Practices (see Table 4 to Table 7). These results confirmed that, even though challenges were experienced, these did not have a meaningful impact on the adoption of digital HRM practices, either in a positive or a negative manner. As such, the following can be argued: the digitalisation of HRM practices will continue to occur on a moderate, great or even a very great extent, irrespective of challenges that may be associated with this process.

These results are somewhat surprising in the sense that the literature suggests that challenges in adopting digital HRM practices manifest when few stakeholders are involved in HRM digitalisation, when there is stiff competition in the allocation of resources within the organisation, when the HRM team does not have the appropriate expertise to use digital HRM and when there is a lack of top management buy-in, among others (Azhar, 2019; Bondarouk et al., 2017; Burbach, 2019; Masum, 2015).

In addition, Andersson et al. (2016) and Burbach (2019) stated that the challenge of competing organisational priorities results in poor planning and a lack of clear goals and vision for the implementation of digital HRM. Also, setting a clear digital HRM agenda and objectives should involve different stakeholders (Bengtsson & Bloom, 2017; Ghosh & Tripathi, 2018; Mosca, 2020; Thite & Bhatta, 2019). An additional challenge to address is data security in the implementation of digital HRM as was stressed by Hosain (2019) and Subramaniyan et al. (2019), especially in terms of personal information, data loss and leakage. It is apparent in this study that although challenges were experienced in the organisations as reported by the participants (Figure 2), these challenges were not deterrents in the adoption of digital HRM practices. However, although the effect is small, Challenges significantly and negatively predicted the variance in Digital Organisational Design and Culture Practices (2.7%) and Digital Employment Relationship Practices (2.8%) (Table 5 and Table 6). The small and negative effect on the adoption of these digital HRM practices cannot be ignored if organisations want to ingeniously leverage on these digital HRM practices, and the literature somewhat supports this.

Burbach (2019) and Parry and Battista (2019) indicated that it was difficult to digitalise employment relations and management-related practices, as HRM teams and leaders often resisted these practices because of a fear to losing face-to-face contact and making the environment less humane (Burbach, 2019; Parry & Battista, 2019). In this regard, while the use of digital platforms gives employees the option of engaging with HRM and line managers via digital platforms, the demerit is that the boundaries between working life and personal life could be blurred, resulting in time and personal strain, which cause stress (Parry & Battista, 2019). Even though Fenech et al. (2019) advocate for investment in digital HRM in attainment of the strategic goals of the organisation, they actually found that in most organisations digital HRM was less often used to support strategic organisational design, culture and change efforts. Moreover, Bersin (2021) confirmed that digital HRM technology was mostly utilised for HRM administration and payroll. Ulrich (2019) also stated that digital HRM technology was more often adopted to optimise administrative tasks and to modernise HRM practices, while less was performed to forge connections and promote the experience of employees. This suggested that challenges such as resistance to change, lack of knowledge, lack of digital competence and difficulties in customising to digital HRM could be obstacles in the adoption of these digital HRM practices. However, the results of this study showed that the digitalisation of HRM practices was not significantly hampered by the identified challenges, and therefore the results of this study are profound. Having said that it is possible that the organisations surveyed experienced the challenges but then dealt with these challenges sufficiently to enable the digitalisation of HRM practices.

Bersin (2021) pointed out that organisations are forced to adopt easy-to-use digital HRM solutions that interface via digital and mobile platforms despite challenges experiences. In addition, because of an acute shortage of talent in specific sectors and job types, caused by the ‘war for talent’, against all odds, organisations adopt digital HRM solutions that enhance the acquisition, appraisal, development and retention of the right talent (Bersin, 2021). This means that despite the challenges, organisations in general continue with adopting Digital Media Practices and Digital Talent Management Practices. Burbach (2019), and Parry and Battista (2019) observed that digital HRM practices that were mostly adopted within organisations were digital recruitment and selection, digital training and development and digital remuneration management (Burbach, 2019; Parry & Battista, 2019).

The implication of the results for organisations and specifically HRM departments or units is that organisations will increasingly adopt digital HRM practices to increase the effectiveness and efficiency of HRM services to support the organisational vision and goals. While some organisations’ plans for digitalisation may be hampered because of challenges experienced and perceptions of the strength of these challenges, other organisations will simply go ahead and digitalise, giving them a competitive advantage and elevating their HRM function to a level where it is recognised as being very professional and essential to the success of the organisation. The results of the study demonstrated that the identified challenges were not to be used as reasons or excuses for not forging ahead with HRM digitalisation, as it was evident from the results that the organisations surveyed in this study managed to digitalise to some or even a great extent irrespective of challenges observed.

The study also highlighted domains for HRM digitalisation, namely digital talent management, digital media practices, digital organisational design and culture and digital employment relations management practices. Organisations need to adopt suitable digital HRM practices in these focus areas to attract and retain talented employees, foster a flexible organisational design and culture to promote knowledge sharing, innovation and a sense of belonging, and foster constructive and collaborative relationships between management and employees and employees themselves. The adoption of digital HRM practices should promote collaboration, communication and cohesion among managers, in support of excellence and achievement. Organisational culture and design processes and practices related to the management of a productive employment relationship within the workplace should strengthen the strategic role of the HRM towards achieving organisational goals (Bissola & Imperatori, 2013; Ma & Ye, 2015; Thite, 2019). Instead of focusing too much on challenges, the positive outcomes of digital HRM practices should be emphasised.

However, it would be short sighted not to acknowledge the challenges, or perceptions of challenges, that could make the adoption of digital HRM practices challenging. These challenges, as presented in Figure 2, are related to technology, the organisation, people and environment factors (Azhar, 2019; Burbach, 2019; Masum, 2015). The empirical results also brought afore the challenges that were experienced or observed by HRM professionals and managers in automotive manufacturing organisations in South Africa.

It will also be futile to assume that digitalising HRM practices, specifically using Digital Media and Digital Talent Management Practices, will be a panacea for resolving organisational issues, the reason being that social dialogue and problem solving may be experienced as more authentic, interactive and effective, in face-to-face situations rather than in a digitalised space. However, these challenges need to be identified and strategies devised to overcome them as they manifest in organisations.

Attention should be given to the outcome of this study, in which it was proven that these challenges do not necessarily have to have a significant effect on HRM digitalisation. As such, a problem-solving mindset rather than a blame or fault-finding mindset is encouraged so that these identified and observed challenges can be dealt with proactively to smoothen the path to HRM digitalisation.

This study aimed at identifying challenges that influence the adoption of digital HRM practices across the HR value chain in the South African workplace. The prolific advance in digital technologies and the inevitable need for quick solutions by business operations, call for the HRM function to adopt digital technologies across the HR value chain. However, the digitalisation of HRM practices come with challenges, as revealed in the study. These challenges should be monitored in the adoption of digital HRM. Various strategies had been proposed for addressing these challenges. The study also provided empirical evidence that the challenges do not have to be cited as excuses for not forging ahead with the digitalisation of HRM practices, based on the results of the survey performed among HRM professionals and managers in the automotive manufacturing industry in the Eastern Cape Province in South Africa.