Title: A maturity model for valuable maintenance data management

Authors: Salla Marttonen-Arola; David Baglee

Addresses: David Goldman Informatics Centre, Faculty of Technology, University of Sunderland, St. Peters Campus, Sunderland SR6-0DD, UK ' David Goldman Informatics Centre, Faculty of Technology, University of Sunderland, St. Peters Campus, Sunderland SR6-0DD, UK

Abstract: The increasing data provide new opportunities for data-based maintenance management. However, decision makers are struggling to optimally harvest value from their data. This paper presents a maturity model to support analysing maintenance data management processes from the value perspective. Maturity models related to data management and business intelligence have been presented before, but they have not addressed the specific features of maintenance, and have not analysed what makes data valuable. The model presented in this paper categorises value of data into six dimensions, and defines five maturity levels to assess them. A real-life industrial case example is presented to demonstrate the use of the model. The model takes into account that the most advanced data management solutions do not always represent the optimal target level for every situation. For instance, many small and medium enterprises would struggle creating enough additional value from big data to make the required investment profitable.

Keywords: maturity model; maintenance; value; data; information; strategy; decision support; case study.

DOI: 10.1504/IJSEAM.2023.136184

International Journal of Strategic Engineering Asset Management, 2023 Vol.4 No.1, pp.1 - 25

Accepted: 05 Jan 2021
Published online: 22 Jan 2024 *

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