Developing a maintenance maturity model for prioritising water infrastructure maintenance in South Africa

Abstract

South Africa's water infrastructure is grappling with severe challenges, characterised by frequent breakdowns and systemic decline. National assessments such as the South African Institution of Civil Engineering's fourth infrastructure report and the Department of Water and Sanitation's drop reports highlight that much of this deterioration stems from inadequately structured and overly rigid maintenance strategies that fail to ensure sustainable asset performance. A key issue emerging from these evaluations is the lack of structured, progressive mechanisms for assessing and enhancing institutional maintenance capabilities. This gap significantly limits the ability of water authorities and utilities to move beyond short-term, reactive interventions and develop resilient, future-oriented maintenance regimes.

To respond to this critical deficiency, this study proposes the adoption of a maintenance maturity model (MMM). Maturity models are established tools across various sectors, providing structured frameworks for evaluating organisational capabilities across defined developmental stages. When applied to maintenance, an MMM enables systematic assessment of current practices, identification of process and system deficiencies, and guidance for strategic improvements. By supporting the evolution from reactive maintenance toward more proactive approaches, the MMM acts as a catalyst for building resilient, cost-effective, and sustainable infrastructure management systems. In doing so, this study offers both a practical and strategic solution to the persistent maintenance challenges confronting South Africa's water sector.

To ensure the model addressed the identified challenges, this research was situated within the design science research (DSR) approach, utilising the elaborated action design research (eADR) method. The study was limited to the diagnosis and design stages. It commenced with problem diagnosis, underpinned by a comprehensive literature review, which revealed a significant misalignment between existing maintenance policies and actual practices; largely characterised by reactive approaches. Additionally, a review of maintenance prioritisation approaches revealed limited adoption, particularly in developing regions such as South Africa, where significant infrastructure deficits persist. Among the key barriers identified, a lack of technical capacity emerged as a dominant concern; contributing to the widespread inadequacies in maintenance practices.

Following problem diagnosis, the design phase focused on establishing model requirements and ensuring contextual fit. Design requirements were defined, and a gap analysis of existing maturity models was conducted to ensure the model's relevance and applicability. The development process was further guided by Maier and Beckers' model development guidelines to ensure methodological rigour and practical utility.

To assess the model's robustness and relevance, validation was conducted through a Delphi study, which reached expert consensus by the second round. The resulting MMM is a validated decision-support tool that enables water utilities to effectively prioritise maintenance activities. By guiding organisations toward more proactive maintenance strategies, the model enhances infrastructure reliability and ensures the sustainable delivery of services.

The MMM also serves as a tool for raising awareness of the critical role of maintenance in sustaining infrastructure reliability. Furthermore, it can be used as a structured guide for training and developing maintenance teams, equipping them with the necessary capacity and competencies to support the organisation's transition to more mature maintenance practices.

While the model presents a validated framework, its real-world application was beyond the scope of this study. Future research should explore piloting the model within operational water utilities to evaluate its practical applicability, effectiveness, and impact on maintenance outcomes.