I was reading Peter Amer’s “Pre-competitive collaboration” in which he discusses the interaction between private and public sectors in research and innovation, as someone coming from the private sector. Nice commentary.
I work for a public university, so I come from a slightly different position.
In my quantitative genetics work, most of the methodologies are publicly available. Most software is also freely available (databases, R, Python) or it is affordable (asreml-R).
Most breeding programmes can access all those “components”. What often varies between programmes, setting aside biological differences, is the quality of the execution: how do we put together the components? This also relates to the ability of the people involved in the programme and their “vision”.
From that point of view, collaboration between competing actors—contributing to a common pool of knowledge and tools—helps everyone to deliver more effective programmes.
In my mind, there is room for a mix of breeding programmes and service providers. This mix will vary with location and time. In some places/countries, private providers will be the best choice, while in others public programmes or mixed partnerships could be best.
