Title: Digital maturity models: comparing manual and semi-automatic similarity assessment frameworks

Authors: Bruno Cognet; Jean-Philippe Pernot; Louis Rivest; Chritophe Danjou

Addresses: Systems Engineering Department, ETS, Montreal, Quebec, Canada ' LISPEN, Arts et Métiers Institute of Technology, HESAM Université, Aix-en-Provence, France ' Systems Engineering Department, ETS, Montreal, Quebec, Canada ' Département de Mathématiques et Génie Industriel, Polytechnique Montréal, Montreal, Quebec, Canada

Abstract: The fourth industrial revolution is forcing companies to define their digital strategy, making it imperative that they assess their digital maturity as a basis for improvements. As a result, a variety of maturity models have emerged. However, it can be difficult to identify which one is most appropriate. This paper introduces a new methodology to compare a manual and a semi-automatic framework for assessing the similarity of digital maturity models. It allows identifying the most adequate framework for comparing maturity models. Both frameworks have been designed to identify correspondences between KPIs. The analysis of the matches and the obtained results are then used to tune the semi-automatic framework. The proposed comparison methodology has been validated using two digital maturity models and shows that the semi-automatic framework provides good results in a very efficient manner. Several insights have been derived and will help to develop a new maturity model.

Keywords: Industry 4.0; smart manufacturing; digitalisation; maturity models; comparison framework; semi-automatic comparison; similarity assessment.

DOI: 10.1504/IJPLM.2021.119524

International Journal of Product Lifecycle Management, 2021 Vol.13 No.4, pp.291 - 316

Received: 16 Nov 2020
Accepted: 02 Jul 2021
Published online: 08 Dec 2021 *

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