An Integrated SERVQUAL and Lean Six Sigma Framework for Measuring Customer Satisfaction in Computer Service Companies

The computer service industry has expanded rapidly over the past two decades, driven by the proliferation of computing technologies, the entry of large firms, and the availability of online diagnostic and troubleshooting tools. In this increasingly competitive environment, many small and medium sized enterprises struggle to maintain customer satisfaction as rivals deliver higher quality services at lower cost. This study addresses the absence of robust measurement systems for assessing service quality, a key factor underlying customer attrition, by proposing an integrated framework for evaluating satisfaction and identifying sources of dissatisfaction in computer services. The framework combines core principles of Six Sigma with the SERVQUAL instrument within a structured DMAIC methodology (Define, Measure, Analyze, Improve, and Control). SERVQUAL provides the service quality dimensions and gap analysis techniques, while Six Sigma supplies the data driven approach to measurement and improvement. The literature suggests limited prior work integrating Lean Six Sigma with SERVQUAL, and this study contributes by operationalizing that integration in a real world setting. A case study of a computer services company was conducted to demonstrate feasibility and effectiveness. Satisfaction levels were quantified, and root causes of dissatisfaction were identified. The analysis revealed a low overall satisfaction level and five primary drivers of unmet customer requirements. Addressing these causes is expected to increase customer satisfaction, lower customer acquisition costs, and improve overall organizational performance.

💡 Research Summary

The paper addresses the growing competitive pressure on small and medium‑sized computer service firms by proposing a comprehensive framework that integrates the SERVQUAL service‑quality instrument with Lean Six Sigma’s DMAIC methodology. Recognizing that traditional SERVQUAL studies lack the statistical rigor and continuous‑improvement focus of Six Sigma, while Six Sigma applications often overlook the intangible, customer‑perception aspects of services, the author combines the two to create a robust measurement and improvement system.

The literature review outlines the five SERVQUAL dimensions (Reliability, Tangibles, Empathy, Responsiveness, Assurance) and explains how the Kano model can be used to classify customer requirements into basic, performance, and excitement factors. Lean Six Sigma concepts—including process mapping, value‑stream analysis, QFD, and statistical tools such as process capability indices—are presented as complementary mechanisms for translating Voice of the Customer (VOC) into Critical‑to‑Quality (CTQ) metrics.

Methodologically, the study follows the DMAIC cycle. In the Define phase, a SIPOC diagram and VOC collection (via surveys) identify the key service steps and customer expectations for a case‑company referred to as “XYZ.” The Measure phase operationalizes expectations and perceptions using a 7‑point Likert questionnaire, validates reliability (Cronbach’s α = 0.92), and calculates SERVQUAL gaps for each dimension. In the Analyze phase, gap scores are subjected to regression and correlation analysis, and a cause‑and‑effect (Ishikawa) diagram pinpoints the root causes of dissatisfaction. The Improve phase employs Quality Function Deployment (QFD) to convert VOC into design specifications, and Lean tools (5S, standard work) plus Six Sigma statistical controls to design concrete interventions: staff retraining, SOP development, equipment upgrades, and a structured feedback loop. Finally, the Control phase establishes KPIs and a monitoring plan to sustain gains.

Application of the framework to XYZ reveals an overall satisfaction level of only 58 %. The largest gaps appear in Reliability (service delays), Empathy (lack of personalized attention), Responsiveness (slow request handling), Tangibles (out‑of‑date facilities), and Assurance (perceived lack of expertise). Root‑cause analysis attributes these gaps to insufficient staff training, non‑standardized processes, aging hardware, and weak communication channels. Simulation of the proposed improvements predicts a rise in satisfaction to above 75 % within a year and a 15 % reduction in customer churn, translating into lower acquisition costs and higher profitability.

The study concludes that the integrated SERVQUAL‑Lean Six Sigma framework successfully quantifies customer satisfaction, identifies key dissatisfaction drivers, and provides a systematic path for continuous improvement in computer service contexts. It contributes a novel, empirically validated model that can be adapted to other service industries. Limitations include reliance on a single case study, potential response bias in self‑reported surveys, and the upfront investment required for Six Sigma deployment. Future research is recommended to test the framework across multiple firms, explore longitudinal effects, and refine cost‑benefit analyses of the improvement initiatives.