Digital transformation skills

Industry 4.0 is characterized by the adoption of different interdependent digital technologies across diverse sectors, to enhance processes, decision-making, and services, changing the ways organizations operate and interact with customers, and fundamentally changing the nature of work [13]. The speed and scale of ongoing advancements of digital technologies lead to a digital disruption regarding work, because jobs or tasks are being displaced by digital innovations, and at the same time new jobs and tasks arise due to the emergence of new digital technologies [3, 14]. This makes skill disruption inevitable. For example, as digital technologies replace employees in performing certain tasks, the skills needed to perform those tasks become obsolete, and new digital technologies will create new tasks for which new skills are needed [5]. This disruption is not unexpected as industrial revolutions have historically displaced jobs and industries, necessitating new and often more complex skillsets [14].

The transformative shift of Industry 4.0 is generally viewed as a DT, which, in turn, is regarded as a socio-technical process of exploiting the potentials of digital technologies for strategic organizational purposes, often as a response to (possible) marginalization or displacement of an organization due to the digital advancements of other organizations in its sector [15]. Compared to digitization (converting from analogue to digital processes), and digitalization (using the potentials of digital technologies for mainly operational purposes), DT involves development towards direct integration of digital technologies in digital business strategies [15].

For digital strategies to be successfully implemented, organizations must undergo significant changes in structures and processes. It is often argued that an agile approach [16], or adoption of a malleable organizational design [17], is needed to respond to and leverage emerging digital technologies, as these increase the likelihood of maintaining competitiveness, exploiting new opportunities, and adeptly navigating unpredictable situations [17]. This need for agile approaches and malleable organizational designs underscores how DT differs from other organizational change processes which are often episodic and infrequent, whereas DT is ongoing, evolving, and cumulative [17]. Gong and Ribiere [1] therefore describe DT as a transformative shift, driven by innovative use of digital technology and strategic resource optimization, aiming to radically enhance and redefine value propositions for stakeholders within organizations, or even business networks, industries, or society.

Employees are regarded as one of the strategic pillars for DT [9], as their ability to adapt to DT is a critical determinant of its success [1]. When some tasks become obsolete and other tasks emerge, it is crucial that employees adopt essential skillsets for DT [18]. This will be challenging for employees for several reasons. First, digital technologies are advancing at a rapid and exponential rate, whereas employees can currently only adapt at a much slower rate, and this growing skills gap will overpower some employees if they are not acutely aware of their potential skills obsolescence [12]. Second, employees in DT contexts not only need job-specific and ever-changing technological skills, but also relevant soft skills such as collaboration skills [12], problem solving skills, and project management skills [2]. This is affirmed by the World Economic Forum [6] which, alongside technological skills, identifies soft skills related to collaboration, communication, entrepreneurship, and self-efficacy as increasingly vital. Foerster-Paster and Golowko [19] and Ivaldi et al. [2] even argue that soft skills are more valuable for employees than digital technological skills, as they contribute to one’s adaptability and flexibility, which are essential to adaptive learning in the dynamic context of DT.

Organizations bear responsibility for preparing employees for DT, by developing upskilling activities through which employees can learn new skills needed to perform new tasks, and reskilling activities through which employees learn new skills needed to perform new jobs [2, 20]. Responsibility for re- and upskilling for DT typically lies with human resource management (HRM) [7, 20–28]. However, although there is consensus that expectations towards employees are changing and that organizations need to implement re- and upskilling activities, there is hardly agreement on which specific characteristics of employees are missing specific to DT [29]. In other words, there is no consensus on which specific skills are increasingly important. Therefore, identifying these essential skills is key for re- and upskilling activities to be successful [2].

Despite the increasing number of scientific articles on the subject, there is no unequivocal answer as to which DT skills are essential. The primary reason for this is the conceptual ambiguity surrounding essential skills in increasingly digitalized workplaces. This ambiguity is the result of ongoing advancements in digital technology, which require concepts of digital technology-related skills to rapidly evolve as well [30]. Consequently, various and often overlapping skills frameworks, such as digital literacy, information literacy, and digital competence, have emerged to describe essential digital technology-related skills. Apart from this conceptual ambiguity, most of these existing skills frameworks do not fully capture the complex and multifaceted nature of DT. For instance, many skills frameworks focus exclusively on technological or digital skills, failing to explain the essential soft skills necessary to exploit the full potential of DT [9]. As DT is a fundamental organizational change process [1], a comprehensive framework of essential skills for DT should go beyond digital technology-oriented skills and include soft, transformation-oriented skills as well.

Therefore, we consider essential DT skills to be a combination of digital technology-oriented skills (hard skills) that enable the optimal use of new digital technologies in work, and transformation-oriented skills (soft skills) that enable adaptability and flexibility in the wake of changing work conditions. This is the starting point for developing a new comprehensive framework of essential skills for DT.

Search strategy and selection process

Our search strategy consisted of two steps: an advanced search action in Web of Science, followed by a forward citation search in Google Scholar for the selection of articles found in Web of Science. Searches were conducted in November–December 2021 and in November-December 2023.

Step one: Selection of articles via web of science.

For the search action in Web of Science, we combined multiple search terms into one Boolean search operator. Fig 2 presents the search terms by abstract and keywords (see S1 Fig for the detailed Boolean search operator). This resulted in the identification of 240 articles. After identification, we screened the articles in two stages. In stage one, we screened the titles and abstracts of all 240 articles for the following eligibility criteria:

• Includes conceptualizations, definitions and/or measurements of DT skills or a related term.
• Includes DT skills or related terms that are not too domain-specific for one profession or sector.
• Published in a peer-reviewed journal.
• Written in English.

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Fig 2. Boolean search action.

https://doi.org/10.1371/journal.pone.0304127.g002

Three co-authors independently conducted this round of screening and discussed differences in judgment to reach absolute interrater agreement. After the stage one screening, we excluded 175 articles based on the eligibility criteria, and two articles could not be retrieved. The main reasons for exclusion were (a) the articles had no specific focus on skills for DT, (b) the articles contained only domain-specific skills for DT (e.g., for healthcare or educational professionals only), or (c) the articles focused on skills for organizations instead of employees. We followed the same process for stage two, this time reviewing the full texts of the remaining 63 articles. Reasons for exclusion of articles in this stage are included in Fig 1. This procedure resulted in the final inclusion of 33 articles from the Web of Science database.

Analysis and framework development

We applied template analysis to analyze the concepts used in the articles and to develop a framework of DT skills. Template analysis is a particular style of thematic analysis, in which an initial coding template is developed based on a subset of the data, which is then applied to further data and is revised and refined based on additional data, leading to a final template [35]. The concepts of the most cited article included in this SLR [9] provided our starting point for our initial coding template. We then revised and refined this initial template by comparing and adding concepts from the other included articles. To increase the reliability of our analysis, three co-authors discussed the framework and differences in judgements to reach absolute interrater agreement. This resulted in a framework containing six skillsets, of which three skillsets are further delineated into subgroups of skills, and a total of 44 different skills.

In the next step, we developed definitions for each skillset, subgroup, and skill, based on definitions, descriptions, and indicators provided in the 36 articles. Again, to increase reliability and the clarity of definitions, the three co-authors discussed the definitions to reach absolute interrater agreement.

Digital working skills

The first skillset, digital working skills, refers to all digital technology-oriented skills needed to utilize both established and emerging digital technologies and media platforms to achieve optimal productivity and effectiveness within an increasingly digitalized work environment. The skills derived from literature are divided into two subgroups: fundamental digital working skills and advanced digital working skills.

The first subgroup contains skills needed for everyday tasks common in many professions, such as handling hardware, handling software such as mail and text software, and handling social media channels and the internet for a given task. This subgroup also includes sharing information and data with others in the cloud or shared drives for synchronous online work, and a basic level of digital problem solving when devices or systems do not work as intended.

The second subgroup, advanced digital working skills, includes skills that are relevant for a broad array of professions, although the level of required skill mastery may very per profession. For instance, programming is a very relevant skill for IT professionals but is also increasingly relevant for other employees working with big data and AI technologies in data-driven decision-making processes. Similarly, dealing with law, copyrights, and licenses, which requires employees not only to understand them but also to be able to act in compliance with them, becomes increasingly important for a broad array of professions, yet it belongs more to core tasks of certain professions such as digital ethics officers. The same applies to the other two skills of this subgroup: digital content creation such as creating or editing videos, images or audio, and digital safety skills, which entails adequately protecting one’s devices, systems, and data from disclosure.

Entrepreneurial skills

The second skillset, entrepreneurial skills, includes transformation-oriented skills needed to fully leverage the potential of DT. The present study identifies three interconnected subgroups of entrepreneurial skills: fundamental entrepreneurial skills, openness to novelty, and value creation skills. Most articles included in this SLR include one or more skills that are part of the larger entrepreneurial skillset, such as creativity and problem solving. However, these articles often do not explicitly link these skills to entrepreneurship and neglect to describe links between these individual skills in the context of DT.

The first subgroup, fundamental entrepreneurial skills, contains skills that are essential throughout the whole value creation process. This group consists of creativity and innovation, needed for generating new ideas or treating familiar ideas in new ways, and problem solving, which not only entails recognizing and defining problems and generation solutions, but also developing, testing, and refining prototypes that generate value.

The second subgroup, openness to novelty, contains skills needed to interpret developments and events in an organizational environment, and to identify new opportunities that arise from these developments. Spotting opportunities to generate value by establishing new ways of connecting and combining digital technology developments and events, and sensemaking, or the ability to determine the deeper meaning of digital transformation and create unique insights, make up this subgroup.

The third subgroup, value creation skills, consists of seven skills needed for turning opportunities and unique insights into value: (1) taking initiative by immediately applying ideas until a better solution is found; (2) strategic planning by developing, adapting, and evaluating action plans for achieving goals; (3) informed decision making to determine the best strategy for problem solving and value creation; (4) anticipation of the short- and long-term consequences and potential impact of actions; (5) risk taking by making mistakes and defending unconventional or unpopular opinions to tackle problems in the value creation process; (6) risk management via minimizing and overcoming harmful effects and adversities while searching for solutions; and (7) the leadership skills to guide teams in creating original and valuable solutions.

Evidence-based working skills

The third skillset contains evidence-based working skills that are needed in a digitalized work environment with increased information and data flows. Evidence-based working skills are a combination of digital technology-oriented and transformation-oriented skills. This skillset, which consists of three subgroups, enables employees to extract beneficial insights for their organization.

The first subgroup, fundamental evidence-based working skills, is a crucial basis for the other subgroups within this skillset. The first fundamental skill is formulating research questions, which is the ability to identify key areas of inquiry, understand the organization’s goals and objectives, and formulate research questions that align with these strategic priorities. The other fundamental skill is critical thinking, which is the proficiency to evaluate information and ideas critically, resisting premature conclusions, exploring multiple solutions, and supporting claims with sufficient evidence.

The second subgroup, information processing skills, is widely emphasized in the reviewed literature. This subgroup encompasses searching and selecting information from vast digital sources, which involves articulating information needs, developing search strategies, and filtering results. Another skill is interpreting and evaluating information based on relevance and quality in a discerning and critical manner; for instance, through rigorous fact-checking and other verification techniques to ensure accuracy, and through evaluation of the quality, appropriateness, reliability, and credibility of information sources. The last skill of this subgroup is information management, which involves organizing, storing, and retrieving digital information in a structured and meaningful manner; for example, using data editing methods or adding metadata.

The third subgroup, data fluency skills, involves the ability to comprehend large quantitative datasets and convert them into relevant insights, such as actionable reports for decision-making. The first skill in this subgroup, data collection, involves identifying the appropriate sources and methods to gather data, ensuring its relevance and applicability to the desired objectives. The second skill, data analysis, involves the application of basic descriptive, explorative, and inferential statistical methods, coupled with the ability to employ suitable presentation or visualization methods. The skill data interpretation builds upon previous skills, as it involves being able to make sense of data by identifying patterns and trends, recognizing relationships and dependencies, and also understanding the inherent properties of the data, such as measurement errors and discrepancies. The next skill, data application, involves the ability to construct clear, concise, and coherent reports or presentations on key findings, insights, and recommendations derived from the data. The skill of data management is very similar to information management and involves the systematic handling of quantitative data throughout its lifecycle, including organization, storage, retrieval, and maintenance. Lastly, data ethics and security involves conscientious consideration and responsible decision-making regarding the handling, storage, and analysis of data, with a focus on protecting individual privacy, ensuring ethical data collection practices, and minimizing potential harm.

Collaboration skills

The collaboration skillset is regarded as a crucial transformation-oriented skillset in the context of DT by many authors (see Table 2). Employees must master skills that enable them to (digitally) collaborate with different types of employees in agile or cross-functional teams to create value or solve problems, or to collaborate in networks to achieve common goals regarding digital transformation. In the specific context of DT, five collaboration skills are considered important. The first is negotiation with the aim of reaching agreements and making decisions that align with a common goal while maintaining mutual respect for all parties involved. The second skill, multidisciplinary teamwork, involves the proficiency to collaborate with individuals from diverse disciplines to collectively contribute to the development of a common, integrated, and shared mental model by actively engaging in collaborative discussions, exchanging ideas, and leveraging the diverse perspectives and expertise of team members. The third and fourth skills, social intelligence and cultural awareness, both entail adapting oneself to a socially and/or culturally diverse team while considering differences in the team on emotional and cultural levels; for instance, by actively challenging and addressing issues of prejudice and stereotypes, or by effectively interpreting and responding to social signals. Networking is the last skill that makes up the collaboration skillset, and involves employees’ ability to establish networks, form alliances, and engage relevant stakeholders inside and outside one’s organization to achieve shared objectives.

Adaptation skills

Mastering the fifth skillset, adaptation skills, is essential for employees’ flexibility and agility, which is key in response to rapidly changing work conditions due to DT. Adaptation skills necessitate continuously modifying one’s thinking, attitudes, and behaviors to effectively navigate current and future (digital) environments, unpredictable technology consequences, and disruptive changes. As such, it is a transformation-oriented skillset in which four distinct skills are identified. Firstly, self-directed learning involves taking charge of one’s professional development, ands proactive re- and upskilling to meet evolving organizational and environmental demands. Self-directed learners manage their own progression towards self-defined learning goals, take appropriate actions to re- and upskill, reflect upon these actions, and as such prevent skill obsolescence. Secondly, experiential learning encompasses the proficiency to acquire knowledge and skills through hands-on experience in the workplace. This skill is crucial for successfully engaging in more agile project work and adapting to dynamic environments, and involves experimenting with different approaches and methods, engaging in self-reflection as well as collective reflection, and extracting valuable lessons and identifying areas for improvement. The third skill, training others, involves transferring knowledge and expertise to others, empowering them to enhance their DT skills. The last skill, resilience, is the proficiency to successfully adapt and bounce back from disturbances and challenges that threaten an employee’s ability to function. This skill involves not only the capacity to prevent or minimize the harmful effects of adversity but also the ability to overcome obstacles and remain mentally, emotionally, and physically healthy amid adverse conditions.

Communication skills

The sixth and final skillset addresses communication skills. Communication skills are deemed important transformation-oriented skills in the context of DT, as noted by most articles included in this SLR (see Table 2). In an increasingly digitalized workplace, it is important that employees master communication skills that enable them to transmit information and interact with others via appropriate and innovative communication channels. Proficiency in communication skills involves not only the ability to convey information accurately but also to ensure that the intended meaning is effectively understood by the intended recipients. Within this skillset, four skills are distinguished. The first, using appropriate ways to communicate, articulates that employees can effectively convey messages through various digital platforms, and develop communication strategies and formats for specific audiences. The second skill, storytelling, denotes that employees are proficient in crafting compelling narratives that captivate audiences and provide a coherent narrative thread using digital tools, attractive visualizations, models, or simulations, with the goal to persuade or inspire others. The remaining two skills focus on appropriate behavior in the digital environment: netiquette, which emphasizes socially responsible online behavior, respecting privacy, using appropriate language, and preventing misinterpretation, and digital identity management, which involves effectively managing multiple digital identities and communicating in alignment with each identity.

Practical relevance and implications

The DTSF serves as a solid basis for raising awareness on skillsets that are vital across various professions and sectors and provides a starting point for sector-wide re- and upskilling initiatives. The present study therefore calls upon organizations, particularly HRM professionals, to adapt their strategic talent management practices to the digital era and assume responsibility for re- and upskilling the workforce in essential DT skills. In the development of re- and upskilling strategies informed by the DTSF, several considerations should be taken into account.

First, prior to designing or procuring interventions such as training programs focused on specific skillsets, organizations should enrich the DTSF by providing context-specific examples of the relevance of these skills and articulating desired learning outcomes for their workforce. This will enable tailored training offerings. Second, organizations need to establish desired maturity levels for all DT skills of the DTSF. While the DTSF holds relevance for diverse professions, the study emphasizes that desired skill maturity levels may vary across specific professions or organizations. For instance, entrepreneurial skills or evidence-based working skills may not require the same level of maturity in all professions. By establishing these desired maturity levels, organizations can effectively monitor skill development and implement targeted interventions. Third, in the development of re- and upskilling strategies, organizations should consider both horizontal alignment (interconnectedness between different trainings, and connection with other interventions) and vertical alignment (alignment with the overall business strategy) to maximize potential outcomes. Lastly, organizations should periodically reassess their re- and upskilling strategies to ensure that the skills essential to their specific organizational context are given emphasis and are addressed accordingly.

Limitations and directions for future research

The DTSF raises several follow-up research questions, partly based on the limitations of this study. The first limitation prompting future research is the potential incomplete coverage of relevant research due to our search strategy. Although we utilized Web of Science, the most widely used database of scientific publications, in combination with a forward-citation search in Google Scholar, our search methodology may have resulted in key publications being overlooked. Striving for complete coverage, future research could therefore expand the search action by including other scientific databases as well.

The second limitation prompting follow-up research is related to time sensitivity. This SLR reflects the state of knowledge up to a certain point in time, and therefore does not include skills related to very recent developments, such as generative AI. As highlighted in the Introduction, the lack of timely updated frameworks may lead to conceptual ambiguity regarding essential DT skillsets or outdated frameworks. To address this, and to provide ongoing valuable insights for organizations, this study calls upon researchers to continually provide updates to the DTSF.

Furthermore, we have intentionally used the term ‘skills’ over ‘competence’ in this study. This decision is in line with the practical objective of our research, which is to address the re- and up-skilling challenge by pinpointing essential DT skills. We acknowledge that ‘competence’ is a broader concept, encompassing knowledge and attitudes as well as skills. Indeed, certain knowledge and attitudes are intrinsically linked to the essential skills outlined in the DTSF. However, our SLR indicated a degree of interchangeability between these terms, sometimes leading to conceptual ambiguity. By focusing on ‘skills’, we aimed to reduce potential ambiguity in this paper. Nonetheless, we recognize that re- up-skilling initiatives and programs, which aim to develop essential DT skills, inherently involve the acquisition of relevant knowledge and the shaping of appropriate attitudes. Essential DT skills are not standalone entities but are part of a larger competency framework. Consequently, future research should strive to develop this broader framework by incorporating essential DT knowledge and attitudes.

Moreover, the DTSF enables various follow-up studies that are linked to the new insights the framework provides. For instance, follow-up research on the measurement and monitoring of workforce development in DT skillsets is an important next step. The DTSF presents an opportunity to develop instruments for assessing and measuring DT skills in the workplace, and the next research step therefore involves operationalizing the DT skills outlined in this framework and creating validated and reliable measurement instruments.

Additionally, future research should focus on expanding the DTSF to address specific professions. While the strength of the current framework is that it encompasses skills applicable to a wide range of professions, it lacks domain-specific DT skills. Given the complexity of DT, the importance of employees with π-shaped skillsets is becoming increasingly apparent [67], as these skills contribute to better collaboration between people with different expertise and to innovative output [68]. The term ‘π-shaped skillsets’ is a metaphor to describe employees who are generalists and specialists at the same time. The two vertical bars of the π symbol reflect deep expertise, such as domain-specific skills and the evidence-based working skills of the DTSF, and the horizontal bar of the π symbol reflects the generalist skills [67, 68], such as the transformation-oriented skillsets of the DTSF. Developing expansions of the DTSF for specific professions, such as by adding a digital pedagogical skillset for teachers or a digital health skillset for healthcare professionals, therefore further enhances the understanding of profession- or sector-specific essential DT skills.

Lastly, future research should examine the development of effective re- and upskilling strategies, based on the DTSF. This research should also address strategies that consider employees’ digital mindset and self-efficacy in re- and upskilling, as these factors impact their engagement and willingness to participate in such activities [69].