Using Statistics To Improve Satisfaction

Article

Goldstein, Sheldon D.   (ASQ)   Indiana Institute of Technology

Quality Progress    Vol. 40    No. 3
QICID: 20908    March 2007    pp. 28-33
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Article Abstract

Choosing which attributes to improve from customer survey data maximizes the use of resources and increases the chances of positive returns on your efforts. The Kruskal-Wallis one-way analysis of variance by ranks helps focus attention on what needs most improvement. In satisfaction data, distribution data is rarely normal. The Kruskal-Wallis test provides a way to evaluate ordinal data in more depth and draw statistical interpretations from the results. The process can be used with any quality improvement program. It provides a statistical basis to discriminate between attributes that need attention and those that will not result in measurable increases in customer satisfaction even if they are improved.

Keywords

Customer surveys, Customer satisfaction (CS), Statistical tests, Analysis of variance (ANOVA), Quality Improvement System (QIS), Organizational improvement initiatives


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