Statistical techniques for continuous improvement: a citizen's satisfaction survey
Lucio Cappelli, Roberta Guglielmetti Mugion, Giovanni Mattia, Roberto Merli, Maria Francesca Renzi · The TQM Journal · 2010
Purpose The purpose of this paper is to propose a path analysis of data coming from a citizen's satisfaction survey to support decision makers in quality service improvement. In detail, the survey aims to measure citizen's satisfaction of an Italian local Public Administration regarding the “infant school (0‐6 years) enrollment service”. Design/methodology/approach The survey represents an experimentation of an original model measuring customers' satisfaction toward on‐line services. Some statistical methods to analyse a given dataset from different points of view are selected. Findings Outcomes of descriptive statistics as well as of multivariate data analysis to summarize information variables are presented. A new multivariate statistical technique, Probabilistic Expert Systems (PES) (Cowellet al.), is proposed to simulate corrective actions (scenarios) and to suggest the best one for the service quality improvement. Originality/value The paper shows that statistical methods are able to support the decisional process because they allow the development of information (gathered from survey) into know‐how. However, managers need to join together both statistical information and experience by means of a systematic method, in order to take effective decisions.