Beyond Product Families: Building a Product Population?

Design of Personalized Devices—The Tradeoff between Individual Value and Personalization Workload

Applied Sciences ◽

10.3390/app11010241 ◽

2020 ◽

Vol 11 (1) ◽

pp. 241

Author(s):

Juliane Kuhl ◽

Andreas Ding ◽

Ngoc Tuan Ngo ◽

Andres Braschkat ◽

Jens Fiehler ◽

...

Keyword(s):

Customer Value ◽

Early Stage ◽

Treatment Success ◽

Product Family ◽

Flow Diverter ◽

New Method ◽

Product Families ◽

Wide Range ◽

The Individual ◽

Individual Value

Personalized medical devices adapted to the anatomy of the individual promise greater treatment success for patients, thus increasing the individual value of the product. In order to cater to individual adaptations, however, medical device companies need to be able to handle a wide range of internal processes and components. These are here referred to collectively as the personalization workload. Consequently, support is required in order to evaluate how best to target product personalization. Since the approaches presented in the literature are not able to sufficiently meet this demand, this paper introduces a new method that can be used to define an appropriate variety level for a product family taking into account standardized, variant, and personalized attributes. The new method enables the identification and evaluation of personalizable attributes within an existing product family. The method is based on established steps and tools from the field of variant-oriented product design, and is applied using a flow diverter—an implant for the treatment of aneurysm diseases—as an example product. The personalization relevance and adaptation workload for the product characteristics that constitute the differentiating product properties were analyzed and compared in order to determine a tradeoff between customer value and personalization workload. This will consequently help companies to employ targeted, deliberate personalization when designing their product families by enabling them to factor variety-induced complexity and customer value into their thinking at an early stage, thus allowing them to critically evaluate a personalization project.

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