An Integrated PMBOK ISO 9001 DMAIC Framework for Lean Six Sigma Driven Project Quality Management

Abstract

This quantitative study examined an integrated PMBOK–ISO 9001–DMAIC framework for Lean Six Sigma–driven project quality management to explain variations in project quality performance. Data were collected from 214 completed and near-completion projects across construction, manufacturing, engineering services, and information systems sectors. Descriptive analysis showed that project quality governance capability recorded a mean score of 3.87 (SD = 0.61), while quality management system maturity demonstrated the highest mean of 3.92 (SD = 0.58), indicating well-established governance and system controls across the sampled projects. Data-driven quality improvement capability achieved a mean of 3.78 (SD = 0.65), and process efficiency orientation recorded a mean of 3.69 (SD = 0.63), reflecting moderate to strong application of DMAIC and Lean practices. Project quality performance outcomes indicated high acceptance compliance with a mean of 3.96 (SD = 0.57), while defect density and rework frequency exhibited lower means of 3.34 (SD = 0.72) and 3.29 (SD = 0.75), respectively, suggesting observable variability in execution quality. Reliability analysis confirmed strong internal consistency, with Cronbach’s alpha values ranging from 0.87 for process efficiency orientation to 0.93 for data-driven quality improvement capability. Multiple regression analysis revealed that project quality governance capability (β = 0.31, p < 0.001) and quality management system maturity (β = 0.34, p < 0.001) significantly influenced project quality performance, jointly explaining 47% of the variance. Mediation analysis demonstrated that data-driven quality improvement capability exerted a strong positive effect on project quality performance (β = 0.39, p < 0.001), while moderation analysis showed that process efficiency orientation significantly strengthened this relationship (interaction β = 0.17, p < 0.001), increasing explanatory power to 58%. These findings empirically confirmed that project quality performance, reflected through defects, rework, acceptance compliance, process stability, and cost of quality indicators, was most effectively explained through an integrated governance, system control, analytical improvement, and efficiency-oriented framework.