Digital maturity models: comparing manual and semi-automatic similarity assessment frameworks Online publication date: Wed, 08-Dec-2021
by Bruno Cognet; Jean-Philippe Pernot; Louis Rivest; Chritophe Danjou
International Journal of Product Lifecycle Management (IJPLM), Vol. 13, No. 4, 2021
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.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Product Lifecycle Management (IJPLM):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com