This article is based on the findings in the report, Understanding the Impacts of Industry 4.0 on Manufacturing Organizations and Workers, prepared for the Smart Factory Institute and written by Chris Cunningham, PhD, UC Foundation Professor of Psychology, and Scott Meyers, Graduate Assistant, Psychology Department & Smart Factory Institute, from the Industrial and Organizational Psychology Department at the University of Tennessee at Chattanooga.
Although the technical aspects of machine integration into the industry with smart manufacturing has been in the center spotlight, there is a need to increase the focus and attention given to what constitutes the “smart worker” required for successful operations within the smart factories promised by Industry 4.0. The need for a more generally skilled manufacturing workforce has become apparent (Brutto, 2012). Employers are beginning to see the increased value of lowering unit labor cost by investing in more skilled workers in comparison to lowering wages. A clear example of this comes from Germany which provides an hourly compensation that is 66% higher than what is common in America and is experiencing a booming industry despite this higher labor cost (Brutto, 2012). Within the automobile manufacturing sector especially, labor is one of the main operating costs and is dependent on hourly wages, the skill and productivity levels of workers, their flexibility to learn new production techniques, and presence or absence of a strong labor union (Nelson et al., 2021). The presence and integration of new technologies and ways of working under Industry 4.0 requires manufacturing workers to develop new and different KSAO (Fig. 1) and competencies to effectively respond to the demands of technology-driven manufacturing. This trend can be expected to increase as the manufacturing industry becomes more fully digitalized and technology-driven (Statista, 2021).
Worker KSAO’s can also be referred to as the human capital workers possess that enable them to meet the demands and address the responsibilities of a specified job (Shet & Pereira, 2021). Another and often complementary form of individual difference that also can explain and predict worker performance is a workers’ underlying competencies, which can generally be understood as the behavioral intentions and behaviors necessary for effective performance in a more general sense (e.g., Bartram, 2005). Competencies are often understood as broader constellations and combinations of a variety of general KSAO elements workers possess and which collectively contribute to meaningful behaviors and desired performance in a work setting (e.g., Boyatzis, 1982; Rothwell & Lindholm, 1999). Competency models are developed when a set or combination of competencies is used to describe what is generally required and necessary for effective performance in a broadly defined work domain (Pickett, 1988; Martone, 2003).
There is probably no more accurate way to describe the current and future manufacturing reality in terms of what it will require of workers. For this reason, a competency-based approach to explaining critical worker requirements for success under Industry 4.0 is appropriate. Although there is no clear consensus yet on specific workforce requirements to best operate and advance in Industry 4.0, various research and reports have indicated specific relevant KSAO’s and competencies that are likely to be of high importance (Hernandez-de-Menendez, 2020). Many of these competency requirements are related to workers’ generalizable abilities to use and interact with Industry 4.0 technologies while also demonstrating competence in technical and soft skills (Rangraz & Pareto, 2021). In an analysis by the McKinsey Global Institute (Figure 2), demand for physical/manual skills for repeatable and predictable tasks was projected to decrease 27% by 2030. Basic cognitive skills such as literacy and numeracy skills were also expected to decrease by 17%. Increased demand was projected for higher and more complex cognitive skill (by 24%) and for social/emotional skills such as initiative taking, leadership, and entrepreneurship (projected increase of 33%) (Ellingrud et al., 2020). These projects jointly indicate that despite the increasing presence of machines and automation under Industry 4.0, less technical, more “human” skills will still be valuable. The greatest projected demand increase, with an impressive 58%, was the need for technological skills such as coding and interacting with technology (Ellingrud et al., 2020).
Along a similar line of inquiry, Hecklau et al. (2016) conducted a literature review and identified competencies required for the workforce to implement Industry 4.0. These competencies can be organized into four main groups as summarized in Figure 3. We use this competency framework to organize and showcase the salient KSAO/competency requirements that the “smart worker” must possess in Industry 4.0.
These core competency domains are expected to be essential to worker success and general organization functioning in manufacturing under Industry 4.0. These forms of personal critical worker requirements will evolve and shift as new technologies and organizational changes are implemented. The worker KSAO’s and competencies identified in this section are not entirely stable and will likely need to adapt as organizations more fully adopt Industry 4.0 technologies and practices. An implication of this is that continuous upskilling and reskilling of the workforce will be needed to ensure continued competence in these critical areas (Strack et al., 2021). Related to this is the need for manufacturing organizations and workers to adhere to practices of lifelong learning and a continuous learning or growth mindset (Dweck, 2009; Hernandez-de-Menendez et al., 2020; Strack et al., 2021). It is also important to note that these competencies are valuable not so much in isolation of each other, but rather in complex combinations and adaptive blends of technical, digital, and personal competencies (IBSA, 2018; Hernandez-de-Menendez et al., 2020). Related to this is the concept of transversal or intersecting competencies that can be applied in many different work domains, such as problem-solving skills, interpersonal competencies, systems thinking, business thinking, and technological literacy (Universities of the Future, 2019). Within these competencies there is great emphasis on problem solving competencies and thinking processes. There is also a clear emphasis on general technology literacy, which refers to the knowledge of essential engineering tools regarding how they function and is necessary to understand and solve Industry 4.0 problems (Universities of the Future, 2019). People, teams, and factories will need these core competencies to fully benefit from Industry 4.0 advancements.
Technical Competencies
The ability to understand, use, and interact with various Industry 4.0 technologies is essential. Therefore, technical competencies and “hard” skills will be extremely relevant in Industry 4.0 manufacturing environments, especially within the AI and robotics fields (Hecklau et al., 2016; Hernandez-de-Menendez, 2020). Having technical knowledge and being trained to develop technical skills, abilities, and broader competencies pertaining to emerging technologies of Industry 4.0 will be essential for existing and emerging workers’ success as manufacturing work evolves. Being able to apply such technical knowledge with new information and continuously reskill in this technical domain is also necessary (Hernandez-de-Menendez, 2020).
Increased connectivity associated with the IoT, cloud computing, and real-time feedback technologies under Industry 4.0 is creating a big data situation that requires new and advanced data management and data analysis skills among workers and leaders within manufacturing organization who need to understand and leverage this data to develop insights and inform decisions (Hernandez-de-Menendez, 2020). Abilities to analyze big data with help of data mining software, algorithms, and resource planning interfaces is required to work within the industrial IoT (Nagy et al., 2018). Data analytics will also help with predictive and remote system maintenance. Sometimes referred to as digital competencies, new and more advanced knowledge and skills within digital analysis, additive manufacturing, programming, and coding will also be more important as production processes become more digitized (Hecklau et al., 2016; Hernandez-de-Menendez et al., 2020; Innovation and Business Skills Australia (IBSA), 2018). Several broader competencies generally associated with the IT domain will also be more essential than ever in manufacturing environments, including programming language skills, code-writing, software development, and computer networks (Hernandez-de-Menendez et al., 2020).
Although pinpointing future work requirements is difficult, the anticipated technical competencies just outlined align very well with those in several existing and established fields of study. For example, fields such as engineering already include education requirements that are technology intensive and emphasize digital interconnectedness of systems. More generalizable and impactful competencies related to these abilities are decision making, cultural skills, lifelong learning, interdisciplinary thinking, problem-solving, and using Industry 4.0 technologies (Hernandez-de-Menendez, 2020). Additional engineering competencies relevant to Industry 4.0 are seen in the findings of a survey of industry representatives and include: data science and advanced analytics, human-machine interfaces, digital to physical transfer technology, advanced simulation/virtual modeling, data communication, real time inventory/logistic organization, AI, robotics, automation, programming, information technologies, mechatronics, cybersecurity, AR/VR, and knowledge of IoT, interfaces, communication protocols, systems understanding, cloud computing, sensors, and lean manufacturing (Universities of the Future, 2019). The field of design is also relevant here. Within this discipline, knowledge of technology impacts, human-robot interaction, user interface, tech-enabled product/service design, and tech-enabled user experiences were noted (Universities of the Future, 2019). These lists of technical KSAO and competency requirements for future success as a manufacturing worker are long and serve to highlight just how advanced manufacturing is poised to become under Industry 4.0.
Methodological Competencies
Success as an Industry 4.0 manufacturing worker will require more than just technical competence. Industry 4.0 is likely to lead to work (re)design that creates more strategic tasks, greater responsibility, and more decision-making power for many workers. This, in turn, creates a need for more advanced methodological competencies within this population (Hecklau et al., 2016). One main competency along these lines is systems thinking, which challenges manufacturing workers to develop a broad and comprehensive understanding of the overall production process, its sub-elements, and how all its pieces fit together as an overall system (Hernandez-de-Menendez et al., 2020). This shift develops as fewer competencies associated with traditional manual or physical labor become essential for manufacturing work.
The focus on manual tasks requiring physical and cognitive abilities (e.g., finger dexterity) can be expected to reduce as these types of tasks become more automated. Instead, competence pertaining to overall processes, systems, information displays, analytical skills, and problem-solving skills will be increasingly essential for worker success (Rangraz & Pareto, 2021).
Another set of methodological competencies that is increasingly essential for workers under Industry 4.0 are traditionally associated with success in various business domains (Hecklau et al., 2016) including: creativity, entrepreneurial thinking, problem-solving, conflict-solving, decision-making, analytical skills, research skills, and efficiency. This list can be expanded a bit further by results of an effort to outline business competencies relevant to Industry 4.0 (relevant to both the production and commercial side of manufacturing organizations), which include: technology awareness, change management, talent management, organizational structure, manager-facilitator abilities, technology-enabled processes, business analysis, and digital skills (Universities of the Future, 2019).
Social Competencies
Industry 4.0 also challenges workers and organizations with a variety of changes that can affect the social context of work. As a result, there is a corresponding need for expanding the social competence and “soft skills” generally associated with the more human elements to manufacturing work (Cotet et al., 2017; Hecklau et al., 2016; Hernandez-de-Menendez et al., 2020). In contrast to the preceding competency areas, the requirements here are for development of personality dispositions and attitudes, interpersonal capabilities, assertiveness, intellectual curiosity, creativity, and independence or autonomy that can support a functional workforce that can become competitive industry advantage for a manufacturing organization (Cotet et al., 2017). Related to this is the need, due to increased global connectedness for intercultural and language skills development that can facilitate more effective interactions with diverse stakeholders. Furthermore, good communication skills including listening and presenting to different audiences will become even more important as virtual work increases. With flatter hierarchy and greater individual responsibility involving more strategic tasks, leadership competencies will also be essential in an Industry 4.0 manufacturing workforce (Hecklau et al., 2016).
One primary and complex social competency area under Industry 4.0 pertains to teamwork and collaboration. Social and technological changes resulting from Industry 4.0 will require workers to respond well to different perspectives and forms of working relationships in human-human and human-machine collaborations. This will involve competence in managing cyber-physical systems and problem-solving in cross functional teams (Mourtzis et al., 2018). The previously mentioned soft competencies and skills such as leadership, networking, communication, assertiveness, and the ability to compromise will support effective collaborations (Hecklau et al., 2016; Hernandez-de-Menendez et al., 2020). One competency strongly emphasized was the ability to apply knowledge in interdisciplinary and collaborative contexts or “knowledge transfer” (Hecklau et al., 2016; Hernandez-de-Menendez et al., 2020). Workers in Industry 4.0 must continuously learn from new contexts and people from different disciplines as they constantly acquire new competencies and adapt with Industry 4.0 by learning to work with and complement advanced technologies with their irreplaceable human skills (Hernandez-de-Menendez et al., 2020).
Intrapersonal Competencies
Although related and sometimes overlapping with social competencies, another set of core competencies for Industry 4.0 manufacturing includes characteristics within individual workers that will affect their work-related performance (Hecklau et al., 2016). As new technologies are introduced and integrated into production systems and various changes are made to jobs and processes, the general competency of adaptability or flexibility becomes essential (Hecklau et al., 2016). Also important for individual workers are competencies for creativity, leadership, and critical thinking (Diaz & Flores, 2017; Grzybowska & Łupicka, 2017; Hernandez-de-Menendez et al., 2020). Along with these competencies related to worker adaptability, workers must also be able to work under pressure in a fast-paced environment as Industry 4.0 increases production efficiency (Hecklau et al. 2016). Worker values should also align with Industry 4.0 goals such as sustainability and compliance.
Passow and Passow (2017) emphasized the importance of developing self-knowledge demands such as will, motivation, self-direction, self-regulation, self-judgment, self-awareness which contribute to this lifelong learning process. Workers must be flexible and active listeners as they continuously develop. Continuous learning is also associated with being open to change and interacting with/learning from academic domains (Hernandez-de-Menendez et al., 2020). This indicates a potential shift to a greater connection between academic institutions and the manufacturing industry, which is good because further research is needed to better understand manufacturing subsector worker requirements under Industry 4.0.
This article is based on the findings in the report, Understanding the Impacts of Industry 4.0 on Manufacturing Organizations and Workers, prepared for the Smart Factory Institute. Get access to this full report by clicking here.
Hannover Messe USA 2022 - Solutions Theater - Call For Speakers powered by Smart Factory Institute September 12 - 17, 2022 | Lakeside Center, Chicago IL
The only place to find the innovations and industry connections you're looking for is at HANNOVER MESSE USA. Discover time-saving solutions, learn about which industry trends you need to be following, and connect with your peers in a world-class experience you won't find anywhere else. Free to all attendees, the Solutions Theater will be located on the Hannover Messe USA show floor in the East Building, Level 2. It will feature presentations, case studies, demonstrations, and special events. Topics include Advanced Connectivity, Data Driven Intelligence, Smart Workers & Managers, Human/Machine Integration, & Advanced Manufacturing Methods. Speakers must share their information in an educational, non-commercial and non-self-promotional manner. Sales pitches will not be considered. Application deadline is May 6th, 2022. Submit Your Application
Comments