11/13/2015Cory R. Schaffhausen and Timothy M. Kowalewski
J. Mech. Des 137(12), 121102 (2015); doi: 10.1115/1.4031655​

Collecting data on user needs can result in overwhelming amounts of data, especially if user groups are large and diverse. Additional analysis is necessary to prioritize a small subset of needs for further consideration. This study presents a simplified quality metric and online interface appropriate to initially screen and prioritize lists exceeding 500 statements for a single topic or product area. Over 20,000 ratings for 1697 need statements across three common product areas were collected in 6 days.  A series of analyses tested whether particular characteristics of users and groups affect the number of high-quality needs that can be generated.  The evaluated characteristics were user group size, needs submitted per person, and expertise and experience levels of users.  The results provided important quantitative evidence of fundamental relationships between the quantity and quality of need statements. Increased quantities of high-quality need statements resulted both due to increasing user group size and due to increasing counts per person using novel content-rich methods to help users articulate needs. However, a user’s topic-specific expertise (self-rated) and experience level (self-rated hours per week) were not significantly associated with increasing need quality.

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