Heaps of raw data on inventor collaborations exist within R&D organisations. Similarly, significant amounts of data with regard to the collaborative structures of competitors, clients, suppliers and partners are available. Valuable insights and subsequent actions based on these data are however often missed out on. Kenedict enables clients to fill this gap.
Innovation Network Analysis
Based on a unique data-driven methodology, Kenedict provides insights into the inherent structure of knowledge networks through elaborate analytics and extensive visualisations. Making use of the principles of Social Network Analysis, knowledge networks are constructed to gain insight into network structure and evolution on various levels:
Internal knowledge networks of the own organisation, competitors, clients, suppliers and (potential) partners can be constructed based on various data sources, providing a unique and valuable view on inventor and technology connectivity.
Technologies & Industries
Mapping (the evolution of) networks in specific technologies and industries to identify key players, enhance market intelligence and improve technology forecasting.
To gain insight into inter-company collaboration and innovation clusters, networks can be constructed for geographies (e.g. for Silicon Valley, or the Brainport area in the Netherlands) to gain an objective overview of regional innovative activity.
Networks focusing on a specific individual (e.g. a prolific inventor in a certain industry) can be constructed to gain insight into the inventor’s reach and mobility, thereby providing a basis to predict future collaborative behavior.