Improving asset management maturity in production system: a novel DSS to maturity assessment and evidence on business performance

Abstract

Asset management (AM) has emerged as an interdisciplinary approach that enables the improvement of the financial and non-financial value delivery of assets in asset-intensive organizations. However, many organizations have conveyed challenges in the AM implementations and decision-making processes, which may come from the absence of tools and managerial capabilities. In order to support the improvement of AM processes, asset management maturity models (AMMMs) have been developed in academia and practice, which face some difficulties. Specifically, the AM literature reports that these AMMMs have not developed an assessment procedure and have not provided evidence to the validation process, provoking challenges in the application that may reduce the effectiveness of the assessment. Therefore, although there are AMMMs available, a novel AMMM needs to be developed to overcome these challenges. Then, by applying design science research, a reference model and the Asset Management Maturity Assessment Procedure (AMAP) were developed, which are implemented in a decision support system (DSS) to guarantee replicability and a self- assessment approach. On the other hand, another interesting challenge has stood out in the AM literature: the relationship between AM maturity and business performance. Considering this, data from AMAP applications were modeled using Partial least squares structural equation modeling in order to reveal the role of AM maturity on business performance, which demonstrates a positive association. Therefore, the thesis proposes a tool for asset-intensive organizations to assess their AM maturity, enabling the development of roadmaps for improvement, as well as bringing empirical evidence of the impact of AM maturity on business performance.