Empirical Investigation of Lean Management and Lean Six Sigma Success in Local Government Organizations

Lean Management and Lean Six Sigma (LM/LSS) are improvement methodologies that have been utilized to achieve better performance outcomes at organizational and operational levels. Although there has been evidence of breakthrough improvement across diverse organizational settings, LM/LSS remains an early-stage improvement methodology in public sector organizations, specifically within local government organizations (LGOs). Some LGOs have benefited from LM/LSS and reported significant improvements, such as reducing process time by up to 90% and increasing financial savings by up to 57%. While the success of LM/LSS can lead to satisfactory outcomes, the risk of failure can also result in a tremendous waste of financial and non-financial resources. Evidence from the literature indicates that the failure to achieve the expected outcomes is likely due to the lack of attention paid to critical success factors (CSFs) that are crucial for LM/LSS success. Furthermore, research in this research area regarding characterizing and statistically examining the CSFs associated with LM/LSS in such organizational settings has been limited. Hence, the aim of this research is to provide a comprehensive investigation of the success factors for LM/LSS in LGOs. The initial stage of this dissertation involved analyzing the scientific literature to identify and characterize the CSFs associated with LM/LSS in LGOs through a systematic literature review (SLR). This effort identified a total of 47 unique factors, which were grouped into 5 categories, including organization, process, workforce knowledge, communications, task design, and team design. The next stage of this investigation focused on identifying a more focused set of CSFs. This involved evaluating the strength of the effect (or importance) of the factors using two integrated approaches: meta-synthesis and expert assessment. This process concluded with a total of 29 factors being selected for the empirical field study. The final stage included designing and implementing an online survey questionnaire to solicit LGOs' experience on the presence of factors during the development and/or implementation of LM/LSS and their impact on social-technical system outcomes. Once the survey was concluded, an exploratory factor analysis (EFA) was conducted to identify the underlying latent variables, followed by using a partial least square-structural equation model (PLS-SEM) to determine the significance of the factors on outcomes. The EFA identified three endogenous and five exogenous latent variables. The results of the PLS-SEM model identified four significant positive relationships. Based on the results from the structural paths, the antecedent Improvement Readiness (IR) and Change Awareness (CA) were significant and had a positive influence on Transformation Success (TS). For the outcome Deployment Success (DS), Sustainable Improvement Infrastructure (SII) was the only significant exogenous variable and had the highest positive impact among all significant predictor constructs. Furthermore, Measurement-Based Improvement (MBI) was significant and positively influenced Improvement Project Success (IPS). Findings from this dissertation could serve as a foundation for researchers looking to further advance the maturity of this research area based on the evidence presented in this work. Additionally, this work could be used as guidelines for practitioners in developing implementation processes by considering the essential factors to maximize the success of LM/LSS implementation. Given the diversity of functional areas and processes within LGO contexts, it is also possible that other public sector organizations could benefit from these findings.