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This paper aims to provide a quantitative decision approach to the service quality management, developed on the basis of Kano's theory of attractive quality. The proposed approach aims at exploiting contacts with service made by “mystery guests” rather than traditional surveys on customer opinions.

A specific probabilistic model of the process of serving quality is the adopted basic tool. Multiple comparison tests aimed at controlling the service quality are the core of the proposed decision approach. In order to collect the needed sampling data, a few mystery guests who experience many customer‐service contacts are employed.

A quantitative decision methodology which both allows one to evaluate the actual service quality level and provides, via comparison tests, a tool to highlight the weak and strong points of the service delivery process.

The proposed quality map is an original graphical tool, which enables one to pin‐point strengths and failings in service quality, prioritize corrective actions and recognize improvements, if any. The operative value of the whole methodology is tested through a real application to the hotel service industry.

In this work, an efficient and easy statistical method to find an equivalent discrete distribution for a continuous random variable (r.v.) is proposed. The proposed method is illustrated by applying it to the treatment of the anthropometrical noise factors in the context of Robust Ergonomic Design (RED; Lanzotti 2006; Barone S. and Lanzotti A., 2007).