Categorizing product attributes efficiently in QFD-Kano: a case analysis in telecommunication

Abstract

Purpose

The purpose of this paper is to propose a methodology to use complaints, claims and company innovation as an internal data source of customer needs for product development using the quality function deployment (QFD)-Kano approach instead of an ordinary customer survey.

Design/methodology/approach

This paper confirms that the customer complaints and claims and company innovations from the internal data source are equivalent to the Kano model’s product attributes. Data were selected from the company’s documents. To investigate the data category, a Kano questionnaire was designed and tested with 100 random respondents. Based on their answers, categories for the quality characteristics were determined and compared with the initial data categories. A second survey using professional customer respondents was conducted to increase the results’ reliability.

Findings

The approach was shown to be effective in employing complaints, claims and innovations as an alternative source of customer needs in the QFD-Kano approach.

Research limitations/implications

It is assumed that companies document their customer complaints and claims, as well as their strategic innovation plans. The complaint and claim data need to be extracted to reveal their quality characteristics. For future research, data extraction using text or data mining may be useful to bridge this gap.

Practical implications

The product development team may ascertain customer needs as duly classified. This voice of the customer is more accurate and requires less time.

Originality/value

The paper may be of value to researchers and practitioners involved in product design and development, since it offers a new source of customer need data obtained internally as an alternative to customer surveys.

Citation

Suef, M., Suparno, S. and Singgih, M.L. (2017), "Categorizing product attributes efficiently in QFD-Kano: a case analysis in telecommunication", The TQM Journal, Vol. 29 No. 3, pp. 512-527. https://doi.org/10.1108/TQM-03-2015-0036