Business process improvements using SERVQUAL, FMEA and text-mining methods for processing the voice of customer

PurposeThis study proposes a new framework for business process improvement (BPI) by identifying areas of improvement based on customer complaints.Design/methodology/approachThe proposed framework comprises several stages. The first stage captures the voice of customer (VoC) in the form of customer complaints. The complaints are processed using text mining and sentiment analysis. Negative sentiments indicate areas for improvement by matching words with SERVQUAL dimensions. The FMEA method is used to identify business processes that need to be improved.FindingsThe opposing quality dimensions of SERVQUAL can be incorporated into a database for later identifying consumer complaints. FMEA can be used to identify potential failures in aspects that correspond to consumer complaints; therefore, improvement areas can be identified. The proposed framework, applied to a garment manufacturer, shows that the SERVQUAL dimensions, which were originally intended for service companies, can be adapted to manage customer complaints to support BPI in manufacturing companies.Practical implicationsThe framework can be used by either the manufacturing or service industries to handle customer complaints and use the complaint analysis results to identify improvement areas to avoid the same complaints occurring in the future.Originality/valueIn this study, the construction of a database based on the SERVQUAL dimension to match sentiment results, where negative sentiment indicates improvement, and the use of FMEA to indicate specific business processes that should be improved is novel and has not yet been proposed by previous studies.