Developing a lean six sigma–based sustainable facility management framework for a South African university of technology

Abstract

Established in 2004 through the merger of three institutions, Tshwane University of Technology (TUT) has grown into South Africa’s largest residential higher education institution, accommodating over 65,000 students across five provinces and providing more than 40,000 residence beds. Despite its scale, TUT continues to experience persistent facility management (FM) challenges, including overcrowded and ageing student housing, deferred maintenance, and declining state funding. These challenges mirror global higher education FM concerns characterised by customer dissatisfaction, resource constraints, and limited adoption of integrated, data-driven management systems. The primary objective of this study was to develop and validate a Lean Six Sigma (LSS)-based framework for Sustainable Facility Management Systems (SFMS) within a university of technology context. Secondary objectives included identifying and empirically examining Critical Facility Defaults (CFD), Facility Contributing Factors to Management failure (FCFM), Root Causes of Facility Management challenges (RCFM), Sustainable Facility Management strategies (SFM), and the role of Lean Six Sigma (LSS) practices in enhancing sustainability outcomes. A convergent mixed-methods research design was adopted. The target population comprised facility management stakeholders at TUT, including academics, engineers, project managers, residence managers, and Lean Six Sigma practitioners. A total of 353 questionnaires were distributed and 333 returned giving a total response of 95.1%. Out of a total of 333 questionnaires returned 326 were found valid for the analysis, yielding a valid response rate of 97.9% whereas the rest of the questionnaires were not used due to missing information. The participants for the interview were 21. Quantitative data were analysed using exploratory factor analysis, reliability and validity testing, Pearson product–moment correlation analysis, multiple regression analysis, and Structural Equation Modelling (SEM). The results confirmed six reliable and distinct constructs (Sustainable Facility Management Scheme based on five predictor variables: Lean Six Sigma, Factors Contributing to Poor Facility Management, Classes of Facility Defaults, Strategies Used in Facility Management and Root Causes to Poor Facility Management), with strong factor loadings (0.5310.860), high internal consistency (Cronbach’s α = 0.807–0.896), and acceptable convergent and discriminant validity. Pearson correlation analysis revealed that sustainable facility management systems were negatively associated with facility defaults, contributing factors, and root causes, while showing positive associations with sustainable strategies and Lean Six Sigma practices. Both SEM and multiple regression analysis validated these relationships, explaining approximately one-third of the variance in sustainability outcomes (SEM R² = 0.35; regression R² = 0.316). The regression model confirmed all predictors as statistically significant and produced a robust predictive equation: SFMS = 3.935 + 0.200(SFM) + 0.096(LSS) − 0.113(CFD) − 0.204(FCFM) −0.214(RCFM). Framework validation by the respondent group demonstrated high reliability and practical relevance, particularly in addressing financial efficiency, social sustainability, and digital readiness within FM systems. This study contributes to facility management scholarship by presenting one of the first empirically validated, context-specific Lean Six Sigma frameworks for sustainable facility management in South African universities of technology, offering both methodological advancement and a practical roadmap for FM leadership.