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Articles

Competence combination for digital transformation: a study of manufacturing companies in Finland

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Pages 1355-1368 | Received 14 Jun 2021, Accepted 04 Nov 2021, Published online: 15 Nov 2021
 

ABSTRACT

Digital transformation brings significant challenges for managing competences. Exploiting digital technologies requires new competences, which need to be combined with existing competences to increase business efficiency and introduce digital innovations. However, competence combination for digital transformation is particularly challenging due to the scale of needed organisational change, conflicts between new and existing operating logics, and employee stress and resistance. Nonetheless, earlier research has neglected the question of how companies approach competence combination for digital transformation. Therefore, we investigated the views of top managers from ten companies in the Finnish machinery and metal products industry for this purpose. Based on an inductive analysis, we identified triggers for digital transformation and developed a managerial framework as a response. We argue that companies can create new transformative competence combinations by engaging in three activities: developing new competencies, promoting competence combination, and enhancing transformational leadership.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Matti Pihlajamaa

Matti Pihlajamaa, D.Sc. (Tech.), Senior Scientist at VTT Technical Research Centre of Finland within the research area of Foresight and Data Economy. His research focuses on innovation management and innovation policy.

Nando Malmelin

Nando Malmelin, PhD, works at VTT Technical Research Centre of Finland as a Professor of Practice focusing on disruptive business. He is also an Adjunct Professor of media and communication studies at the University of Helsinki.

Arto Wallin

Arto Wallin is a Senior Scientist and Project Manager at VTT Technical Research Centre of Finland within the research area of Foresight and Data Economy.

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