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In both science and practice, the assumption is confirmed that collaboration within and between organisations contributes to the innovation of technology and better aligned processes. After all, within a network, forms of knowledge are exchanged, costs and human capital can be shared, and a network can be used to take a (political) position or to legitimise one's own actions. In theory, collaboration and, on a larger scale, networks act as drivers of innovation. This is also recognised in (policy) practice. The Universe Programme (UP) is a concrete example: based on the 'backing winners principle', networking between secondary schools is encouraged to achieve innovations in beta education and the exchange of knowledge about it. Network formation thus plays a significant role in the UP setup. But how does this manifest in practice? Are there relationships between the selected schools? Are there many 'gaps' in the UP school network? Which schools are of fundamental importance and therefore play core or bridging roles within the UP network? And are there schools that lag behind in terms of the knowledge-sharing principle of 'give and take'?
Against this background, Dialogic systematically analyses network formation, embedding of individual UP schools, and the effects on beta performance. In addition to the practical possibilities of a network analysis for UP, this proposal gives extra attention to the added value of network analysis compared to other methods. We also address the critical points to consider when conducting this analysis. This includes confirmed versus unconfirmed relationships, measuring the strength of relationships, the importance of data quality, and data collection.
