1,720,971 research outputs found
Digitalization and middle-skill gaps: The moderating role of lean production
No full textDigitization technologies such as the Internet of Things, material tracking and machine vision are transforming manufacturing plants’ operations enabling, for example, predictive maintenance and data-driven decision making. While automation had an unprecedented impact on production workers, the interconnected technologies that make huge amounts of operational data available in real time – the so-called Industry 4.0 – is affecting middle-skill jobs as production supervisors, team leaders, or maintenance and quality specialists. In order to base their daily decisions on such data, they need knowledge in statistics, IT and analytical skills, and relational skills to foster increasingly frequent interactions with production workers, who know better than anyone what such data mean. Firms adopting lean production, where production workers are already involved and data is already used for continuous improvement, might hold an advantage in having middle-skill workers prepared for this digitalization wave. Through a survey issued to 101 manufacturing plants of the Italian automotive supply chain, we showed that the presence of formal lean production programs negatively moderates the impact of digitization technologies on the presence of skill gaps in middle-skill workers. What emerges is the need, when digitalizing operations, of a holistic management innovation considering technology, inclusive organizational structures, and data-driven managerial practices
Una nuova istruzione per preparare l’Italia alla rivoluzione 4.0
Full text linkIl report pubblicato su Agenda Digitale descrive l'impatto della trasformazione digitale sui cosiddetti "middle-skill worker", tecnici e operai specializzati a contatto con la linea operativa che vedranno maggiormente trasformato il loro modo di lavorare con l'avvento della digitalizzazione, e delinea brevemente i relativi bisogni di investimenti in formazione continua e integrazione tra università, istituti tecnici e ITS per favorire reskilling, upskilling, e una ritrovata attrattività dei percorsi professionalizzanti
Digitalization and operational data-driven decision-making: A socio-technical investigation of the implications for front-line production managers and workers
Full text linkL'abstract è presente nell'allegato / the abstract is in the attachmen
Leveraging IoT in Experiential Learning to develop operational knowledge in the digital era
No full textThe complexity brought by digitalization in operations is disrupting blue-collar and technical jobs, increasing levels of knowledge required to perform them. When workers such as electrical grid operators become “smart grid operators”, the breadth of knowledge required to them increases. The shift from I-shaped to T-shaped profiles has been described by literature (e.g. Demirkan, 2015), and the need for a shift from T-shaped to Pi-shaped profiles, with a second “depth” of knowledge in data science, has been discussed for skilled jobs such as researchers (Faris et al., 2011). In this work we show how, with the advent of digitalization, also operational job profiles will need more depth in a second field of knowledge: not only domain knowledge, but also digital literacy. This study intends to explore the benefits of integrating IoT technologies in a Challenge-Based Learning approach to innovate Education and develop pieces of the new digital knowledge that will be required to operational jobs of the future. By means of an action research, we explored how the operational firm-specific knowledge needs of an electric distribution firm are evolving, and provided an off-the-job Challenge-Based training to two classes of students involved in its dual apprenticeship. Our findings show how such experiential learning activities based on IoT technologies can be fostered by concurrent dual apprenticeships, which act as the “concrete experience” phase of the experiential learning cycle (Kolb, 1984; Morris, 2019). Its two tacit phases, namely “experience” and “experimentation” (Raelin, 1998), were the two that benefited the most from complementing on-the-job and off-the-job training. Last, we disentangle the contributions of firm and the technical high school, and discuss how such structured collaboration can be effective in co-creating effective Challenge-Based activities. Further studies will be needed to explain in detail benefits and rationales of involving a university as off-the-job provider in such educational paradigm
Are Team Leaders’ Skill Gaps Hindering the Diffusion of Data-Driven Decision-Making in Manufacturing? A quantitative micro and meso-level analysis
No full textToward data-driven operational decision-making in digitalized manufacturing plants: a qualitative micro- and meso-level analysis
No full textThe digitalization of manufacturing is disrupting several industries, promising positive impact at the macro-, meso-, and micro-level of organizations. This article aims to investigate how different adoption levels of digital technologies imply different changes in work practices, organizational structures and decision-making approaches (meso-level), and in turn work design and competency needs of production employees (micro-level). Distinct points of view have been collected through a phenomenological research design incorporating 20 qualitative interviews with plant managers, production managers, supervisors and team leaders, and other informants experiencing the digitalization in manufacturing plants of the Italian and Spanish automotive sectors. Grounded theory analysis revealed that the three key factors that could define an effective digital transformation of manufacturing plants are: data-driven decision-making approaches embraced by middle managers; upskilling of first-line managers, especially team leaders, for whom more analytical skills and IT literacy are needed; and the need for high-involvement management practices to truly motivate and engage production workers in consistent data input activities. These factors – whereby both digitization and connection technologies (i.e. a full-digitalized plant) are present – can enable the vision of a “data-driven operational decision-making” that follows a “bottom-up knowledge creation” based on an increasingly decentralized sense-making of operational data. Concerning organizational structures, changes in first-line management power balances emerge, with team leaders acquiring a central role in digitalized manufacturing plants, even more prominent than (theoretically) higher-level supervisors. Recommendations are also offered to practitioners and policymakers in the fields of HR management and education, concerning the direction to be taken in the post-secondary education and training of lower-level managerial professions such as production team leaders, to prevent the generation of middle-skills gaps already faced by other technical professions with the advent of digitalization
Can challenge-based learning be effective online? A case study using experiential learning theory
Full text linkThe COVID-19 outbreak had a major effect on moving online learning activities, also traditionally experiential ones such as those designed upon Challenge-Based Learning (CBL) principles. This article explores the impacts produced on a Challenge-Based Innovation project work carried out in the context of a program developed by Politecnico di Milano and Politecnico di Torino. A survey of 92 students and interviews were carried out to assess the impact on learning outcomes and processes, and four main success factors were identified: informal interaction, time for exploration, asynchronous lecturing, relevant challenges. Suggestions for an effective design of online CBI-like programs are offered
The impact of digitalization on production management practices: A multiple case study
No full textWith the diffusion of Industry 4.0, manufacturing firms can decentralize their operational decisions and enable real-time data-driven decision-making. Using a socio-technical approach and the manufacturing shop-floor as a unit of analysis, this article studies the changes induced by digitalization on operational decision-making, organizational structures, and individual competencies. A cross-country multiple case study conducted in the automotive sector suggests three main areas on which firms have to focus: decentralized data-driven decision-making, front-line managers’ upskilling, and production workers’ involvement. The successful implementation of digitalization and the actual decentralization of decision-making depend on individual factors related to the competencies of front-line managers, who acquire a central role in this skill-biased technological and organizational change
Digital Transformation of the Italian and US Automotive Supply Chains: Evidence from Survey Data
Full text linkWe provide results from a detailed survey of automation and digitization in firms in the automotive sectors in the United States and Italy. In both countries, we find evidence of heterogeneity of organizational architectures—some firms organize around a “Taylorist” approach and others around a pragmatic approach. We find some notable differences in the adoption and use of new technologies, particularly robots. In the US, robots are considered an effective tool to address skill shortage, but not as much in Italy. This is partly explained by the fact that in the US finding workers who possess the desired skills is seen as a major challenge. Italian firms attribute to robots a higher impact on improving safety conditions in the shop floor. This might explain why Italian firms have adopted more technologies for parts tracking, given they are frequently used to trace all the production processes to guarantee product safety. Overall, firms in both countries appear more likely to adopt robots to increase quality rather than to reduce unit and labor costs. Despite technology adoption is underway (though more in the US), we found that companies in both countries (especially in US) are not automating data collection suggesting that firms are not utilizing the new automation and digitization technologies to their fullest extent but in the “old” way
Organizational Architecture and the Adoption and Use of New Technologies: Evidence from Italian and US Survey Data
No full textWe provide results from a detailed survey of automation of firms in the automotive sectors in the United States and Italy. In both countries, we find evidence of heterogeneity of organizational architectures—some firms organize around a “Taylorist” approach and others around a “Pragmatist” approach. We find some notable differences in the adoption and use of new technologies, particularly robots. In the US, robots are considered an effective tool to address skill shortage, but not as much in Italy. This is partly explained by the fact that finding workers who possess the desired skills is seen as a major challenge in the US. Overall, Pragmatist firms in both countries appear more likely to adopt robots to increase quality rather than to reduce unit and labor costs
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