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Systematic comparison of digital maturity assessment models

Article dans une revue avec comité de lecture
Author
COGNET, Bruno
136804 Ecole de Technologie Supérieure [Montréal] [ETS]
ccPERNOT, Jean-Philippe
543315 Laboratoire d’Ingénierie des Systèmes Physiques et Numériques [LISPEN]
RIVEST, Louis
136804 Ecole de Technologie Supérieure [Montréal] [ETS]
DANJOU, Christophe
57241 École Polytechnique de Montréal [EPM]

URI
http://hdl.handle.net/10985/26192
DOI
10.1080/21681015.2023.2242340
Date
2023-08
Journal
Journal of Industrial and Production Engineering

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.

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