Author
Listed:
- Diana Chernetska
(University of Bremen, Germany)
- Jörg Freiling
(University of Bremen, Germany)
Abstract
In the era when Big Data and Business Intelligence spark their application in different industries, we strive to illuminate the potential of data usage for enhancing innovation processes for companies operating in B-to-C context. Thus, this article builds a foundation for understanding how Predictive analytics (PA) can promote customer involvement in the fuzzy front end of open innovations. PA as a technology originates from IT industries where its application dominates. Very little is said about its potential for consumer goods industries. Yet, since PA helps to process data in a structured way and provide a specific insight, we assume that consumer goods companies can predict the future behavioural trends, by applying PA to analyse customer behaviour. This could be a significant contributor to envisioning new markets and industrial foresight. Given the increasing role of network interaction, not only customers but also other network participants can contribute and catalyse innovation processes, in this setting known as open innovation. It is predominantly possible due to interaction on online platforms - an architect of such networks. This paper outlines the potential of PA for facilitating customer involvement at the fuzzy front end of open innovation and offers conceptual basis for the subsequent empirical study of this issue by developing specific hypotheses which are to be tested. We infer that PA when properly applied has a tremendous potential in driving innovations in the companies by organising data and providing a meaningful insight into customer behaviour.
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