Analysing workforce development challenges in the Industry 4.0

Abstract

PurposeThe aim of this paper is to identify and analyse workforce development challenges in the digital age by first, presenting these challenges and relationship between them, and then proposing a structural model that categorizes these challenges and proposes suggestions for managers to improve human resources practices and firm performance.Design/methodology/approachFuzzy total interpretive structural modelling (TISM) is used as the methodology, which gives an interpretive structural model by presenting direct and transitive relationship between workforce development challenges and categorizes them under autonomous, dependent, independent and linkage groups.FindingsIn total, 13 different workforce development challenges are presented in this study. Results showed that lack of IT/digital skills has a critical role in workforce development in terms of affecting other challenges. Dependent group includes requirements for longer learning time and specialized training, lack of analytical thinking and dealing with complexity, and lack of interdisciplinary thinking and acting. On the other hand, lack of ability in decentralized decision-making and shortage of workforce with adequate skillset within the labour market have more macro-impacts on others. Most of the challenges located in the linkage group, which means that most of the challenges are interrelated with each other.Originality/valueOriginality of this paper is presenting a systematic structure for workforce development in Industry 4.0 that considers challenges systematically.

A systematic review on digital literacy

“…Information and Communication Technology as a support for thinking is a learning objective in any school curriculum. In the same vein, analytical thinking and interdisciplinary thinking, which help solve problems, are yet other concerns of educators in the Industry 4.0 (Ozkan-Ozen & Kazancoglu, 2021 ).…”

The emotional and social side of analytics professionals: an exploratory study of the behavioral profile of data scientists and data analysts

“…Behavioral competencies play a vital role in supporting these workers in understanding the business environment, finding creative solutions, promoting collaboration among their team members and also becoming aware of internal and external stakeholders' needs (Costa and Santos, 2017;De Mauro et al, 2019;Mitchell et al, 2021;Shirani, 2016;Verma et al, 2019). Indeed, research (Beck and Libert, 2017;Capgemini, 2019;Ozkan-Ozen and Kazancoglu, 2021;Singh et al, 2021) has claimed that behavioral/emotional intelligence competencies are expected to grow in importance over the next few years and become a differentiator in the digital era in which artificial intelligence and machine learning will progressively automate routine tasks. However, in the past decade, the literature has highlighted the relevance of behavioral competencies for enabling data analysts and scientists to achieve an outstanding performance, and these studies are primarily based on anecdotal evidence or analyses of Web-based job postings and LinkedIn profiles (De Mauro et al, 2019;Ecleo and Galido, 2017;Verma et al, 2019).…”

“…, 2019). Indeed, research (Beck and Libert, 2017; Capgemini, 2019; Ozkan-Ozen and Kazancoglu, 2021; Singh et al. , 2021) has claimed that behavioral/emotional intelligence competencies are expected to grow in importance over the next few years and become a differentiator in the digital era in which artificial intelligence and machine learning will progressively automate routine tasks.…”

The Role of Integral Model of Critical Infrastructure Safety in Industry 4.0

“…As a result of the research, and organization-level maturity model was developed to optimize overall sociotechnical work system performance in the context of rapid technological development in manufacturing industries (Reiman et al, 2021). Study results showed that lack of IT/digital skills has a critical role in workforce development for Industry 4.0 (Ozen and Kazancoglu, 2021).…”