Data-driven innovation: challenges and insights of engineering design

Abstract The value-creation opportunities enabled by the ubiquitous availability of data indisputably lead to the necessity of restructuring innovation processes. Moreover, the variety of stakeholders potentially involved in innovation processes and the apparent heterogeneity of scenarios and contexts imply much less established practices and routines and not yet constituted reference frameworks to lead the transition to data-driven product innovation. In this context, the paper attempts, from the analysis of the data-driven innovation processes of 36 Italian companies, to recognise the emerging innovation opportunities offered by the rich network of the resulting data flows. However, these opportunities also imply new tasks, which in turn raise further concerns. Building on data-driven design literature and on industrial practices in the field of innovation management, the authors discuss the role that research achievements in the field of engineering design can play in addressing such concerns.

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Publication Details

Journal
Design Science
Published
2025-01-01
DOI
https://doi.org/10.1017/dsj.2025.10016
Citations
1
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
2.28
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article

Data-driven innovation: challenges and insights of engineering design

Marco Cantamessa, Francesca Montagna, Gaetano Cascini, Teresa Monti
1 citations
Design Science
Big Data and Business Intelligence
2.28
article

Data-driven innovation: challenges and insights of engineering design

Marco Cantamessa, Francesca Montagna, Gaetano Cascini, Teresa Monti
article en
1 citations

Abstract

Abstract The value-creation opportunities enabled by the ubiquitous availability of data indisputably lead to the necessity of restructuring innovation processes. Moreover, the variety of stakeholders potentially involved in innovation processes and the apparent heterogeneity of scenarios and contexts imply much less established practices and routines and not yet constituted reference frameworks to lead the transition to data-driven product innovation. In this context, the paper attempts, from the analysis of the data-driven innovation processes of 36 Italian companies, to recognise the emerging innovation opportunities offered by the rich network of the resulting data flows. However, these opportunities also imply new tasks, which in turn raise further concerns. Building on data-driven design literature and on industrial practices in the field of innovation management, the authors discuss the role that research achievements in the field of engineering design can play in addressing such concerns.

Design ScienceVol. 11
University of Turin (IT), Politecnico di Milano (IT)
Openalex Percentile: Top 10%
Big Data and Business Intelligence
2.28
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