Skills and employment under automation: Active adaptation at the local level

Abstract

Context: The article contributes to a discussion of how patterns of employment and qualifications are modified by the ongoing industrial transformation, called Industry 4.0. Although this transformation is said to be a global phenomenon, scholars increasingly discuss the national differences in the wake of Industry 4.0. Our article aims to intervene in this debate by analysing the industrial transformation of a small island situated at the West coast of Norway. We notably investigate the technological renewal by means of Computerised Numeric Control (CNC) and robotics in a network of mechanical firms. Approach: Nine small mechanical engineering firms are analysed by drawing on theories on business networks and clustering of firms. This allows for a discussion of how automation, employment, staff training and profitability are interconnected. The main research question is how the firms are locally embedded in a way that sheds light on the social dimension of vocational training, which is considered a form of Corporate Social Responsibility. Findings: It is informative to use the heuristic concept ‘pre-cluster agglomeration’ to characterise how the nine firms under scrutiny are interacting, while being assisted by a forward-looking industrial association and supported by an active local community. The municipality and the county to which this agglomeration belongs, provide training services and other infrastructures that support the firms when they recruit new employees and upskill their staff, - notably by setting up a CNC training centre attached to an upper secondary school. Conclusion: Our case does not support off-the-shelf narratives of robotisation implies job cuts. In the same way as previous technological transformations were not solely driven by their inherent technical opportunities, the ongoing robotisation is nuanced by the social shaping of technology. There is room for strategic choices when new technology is integrated in work organisations. The extent to which the workforce should be (re-)trained is subject to decisions and negotiations.