Digital Product Innovation in Manufacturing Industries-Towards a Taxonomy for Feedback-Driven Product Development Scenarios
Abstract
In the light of pervasive digitalization, traditional physical products get augmented with digital components that create the potential of making the whole product lifecycle visible for product developers. Despite numerous opportunities that sketch out how feedback such as sensor data might be leveraged for future products, a comprehensive model to describe feedback-driven product development does not exist. Hence, this paper pursues a scenario-based approach and proposes a taxonomy for feedback-driven product development scenarios in manufacturing industries. Grounded on (1) empirical data from case studies and focus groups and (2) a systematic literature review, we follow an established taxonomy development method employing the general systems theory as metacharacteristic. The developed taxonomy nominates the following dimensions: (1a) Approach to data collection, (1b) product data source (level of abstraction), (1c) product data source (format of appearance), (2a) complexity of feedback processing, (2b) degree of feedback processing autonomy, (3a) degree of product novelty, (3b) addressed product development stage, (3c) enabled business benefit, and (3d) enabled increase in value. With the limitation of a (1) qualitative, interpretive empirical research design and a (2) representative literature review, we contribute to the body of knowledge by shedding light on feedback-driven product development from a classification perspective which may act as structuring and creativity fostering tool.