Methodology for extracting the delighter in Kano model using big data analysis

Abstract

With shortening product lifecycles, product design is more strongly influencing successful business’ competitive advantage. The Kano model has been proposed to define and extract customers’ needs for attractive quality creation in product development. Because product or service differentiation is crucial to business successes, the extraction of the delighter in the Kano model is an important issue. This study proposes a methodology for extracting important factors by using big data outside the organisation; such a factor may not be a megatrend but may be a delighter in the Kano model. Because the delighter in the Kano model is defined as a constant necessity arising from a small number of propounders, the volume concept is used by adding the time axis to the flatland of the data distribution to extract the delighter. To demonstrate the feasibility of the proposed methodology, accumulated data from the iPhoneForum from 2010 are gathered and analysed to extract the delighter for a smartphone’s input device. The result shows that the ‘pen’ and ‘write’ have the highest index of potential delighter during the study period; in particular, before December 2014, ‘pen’ had the highest index of potential delighter.