NSERC Discovery Grand:
Data Analytics for Open Software Product Innovation
Innovation is the principle of survival in competitive markets and software products are no
exception. Software is no longer developed in a closed but an open environment. Open access to
knowledge, information and resources far beyond the traditional organizational barriers offers new
opportunities to create innovative software products in terms of their innovative functionality, quality
and timely delivery. This proposal is devoted to new concepts, theories, processes and methods to
facilitate Open Software Product Innovation
The long term goal of this proposal is to perform interdisciplinary research to discover new ways
to foster software product innovation. The main idea of the proposal is that product innovation can
be facilitated by (i) the idea to synthesize former experience into pattern-based recommendations
for delivering the right product at the right time to the right groups of users, (ii) incremental
innovation on features and product quality based on continuously analyzed usage and demand, (iii)
the continuous analysis of real-time data in an open environment including users, developers and
customers, and (iv) manageable enlargement of crowd wisdom for incremental innovation and
Following this agenda, we are looking at four areas of discovery to facilitate Open Product
- Hierarchical approach for product innovation combining pattern¬based recommendations (in the
big) and optimization (in the small).
- Analytics for F and NF incremental feature design and development Instead of yes or no
decisions towards features).
- Social media and repository analysis for predictive and prescriptive modeling of feature needs, usage and usefulness.
- Dynamic decision support for crowdsourced open product development.
The research is speculative in the sense that it combines and adjusts methods from different areas of
research in a unique way to make product innovation more systematic and data-driven. In
particular, this includes methods and techniques coming from other areas and disciplines such as
economics, product design, optimization and artificial intelligence.