A Use of Subjective Clustering to Support Affinity Diagram Results in Customer Needs Analysis
A Use of Subjective Clustering to Support Affinity Diagram Results in Customer Needs Analysis
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DOI：
10.1177/1063293x10372792
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发表时间：
2010-06-01
影响因子：
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通讯作者：
Ishii, Kosuke
中科院分区：
文献类型：
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作者：
Takai, Shun;Ishii, Kosuke
分析客户需求是成功开发产品的关键第一步。客户需求分析通常包括采访潜在客户以了解他们的需求，对相似需求进行分组以确定代表性需求，并要求客户评估代表性需求的相对重要性。使用重要性数据，客户可以根据他们对代表性需求的优先顺序进行分组。本文比较了识别代表性需求的两种方法-亲和力图(AD)和主观聚类法(SC)，并提出了一种使用主观聚类法来支持从AD获得的分组结果。通过对下一代粒子加速器的客户需求分析，展示了AD和SC在确定代表性需求方面的应用。
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.