A Use of Subjective Clustering to Support Affinity Diagram Results in Customer Needs Analysis

Abstract

Analysis of customer needs is a critical first step in successful product development. Customer needs analysis typically consists of interviewing potential customers to understand their needs, grouping similar needs to identify representative needs, and asking customers to evaluate relative importance of the representative needs. Using the importance data, customers may be grouped according to the priorities they place on representative needs. This article compares two approaches for identifying representative needs — affinity diagram (AD) and subjective clustering (SC) — and presents a use of SC to support grouping results obtained from AD. The application of both AD and SC in identifying representative needs is demonstrated using the customer need analysis of the next generation particle accelerator.