Bruno Cognet, Jean-Philippe Pernot, Louis Rivest and Christophe Danjou
Article (2023)
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Abstract
Assessing the digital maturity of companies is essential to prepare for digital transformation in the context of Industry 4.0. Several digital maturity assessment models have emerged in the past few years to support this evaluation. One obstacle for companies is the impossibility of easily comparing themselves to one another quantitatively or qualitatively. This paper introduces a new way to compare digital maturity models through a quantitative framework that is compatible with a wide variety of models. Comparisons are performed in the space of the keywords used to characterize key performance indicators (KPIs) that are reverse engineered from the models. The matches are encoded in a keyword matrix that is used to automatically compute the match level of KPI pairs. The framework has been validated on 13 state-of-the-art maturity models whose analysis resulted in the identification of 451 KPIs characterized using 263 keywords structured according to 12 dimensions and 58 subdimensions.
Uncontrolled Keywords
Digital transformation; maturity models; systematic comparison framework; key performance indicators; matching level; model coverage indicators
Department: | Department of Mathematics and Industrial Engineering |
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PolyPublie URL: | https://publications.polymtl.ca/56331/ |
Journal Title: | Journal of Industrial and Production Engineering (vol. 40, no. 7) |
Publisher: | Taylor and Francis |
DOI: | 10.1080/21681015.2023.2242340 |
Official URL: | https://doi.org/10.1080/21681015.2023.2242340 |
Date Deposited: | 02 Nov 2023 15:35 |
Last Modified: | 30 Sep 2024 17:13 |
Cite in APA 7: | Cognet, B., Pernot, J.-P., Rivest, L., & Danjou, C. (2023). Systematic comparison of digital maturity assessment models. Journal of Industrial and Production Engineering, 40(7), 519-537. https://doi.org/10.1080/21681015.2023.2242340 |
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