The Golden Rules of Successful University-Industry Collaboration
I have worked collaboratively with industry in a variety of roles and using almost every funding modality available. I have been responsible for some considerable successes and, without doubt, a few miserable failures. I think I know what works, for sure I know what does not. Here are the 'golden rules', garnered from experience and offered with humility. A few caveats. These rules are principally addressed to larger organisations that sustain a range of relationships with universities. They are based on my experience in engineering and technology and I lack confidence in their generality beyond this.
Focus on problems. My experience is that the best collaborations have arisen from a clear focus on a practical problem. This does not imply a purely instrumental or short-term approach but instead using a problem to inspire and give shape to new and fundamental science. A good problem provides a clear meeting point and a way of establishing the success (or otherwise) of a collaboration, a benchmark if you like. The problem obviously needs to be meaningful, that is a solution must matter, and it must be concrete, with all the contextual richness that comes with real problems.
Share strategy and timelines. This may seem bizarre but many collaborations are attempted without the parties feeling the need to share, or worse, actually withholding, their strategy and timelines. Industry partners do not share their commercial strategy, for competitive reasons, and do not have a research strategy. University partners do not have a translational strategy and do not share their research strategy, for fear that it is at odds with the interests of the potential industry partner. These approaches bake-in the risk of failure.
No secrets. There is very little point in engaging in collaborative research if you are unwilling to share potentially commercially sensitive data. You cannot expect industrially relevant research to proceed in the absence of data drawn from the 'operational' frontline. Experience suggests that it would be sensible to ensure the availability of the data prior to kicking off a project that will likely depend upon it.
Reject the project. I realise that I risk being something of the 'pub bore' on this issue but forgive me, I feel passionately about it. The 'project' has become a fixed notion in research: a carefully scoped and delimited research question worked on extensively over a two or three year period against a predetermined work plan, culminating in academic papers and, ideally, follow-on funding. This model, inherited from research funders, operating under their own constraints, is, largely ill-suited to university-industry collaborative research. Simply shortening the timeline does not really help. There are many other models: intensive workshops, long-term programmatic engagements, 'residencies', and so on. It is important to think openly here.
Research is a relationship business. And relationships take time and patience, obviously. The university needs to devote resources to manage the relationship. The industry partner needs to assign the right person - that is somebody from the sharp business end of their activity. Somebody with contacts and currency. Both need to avoid churning people at the university-industry interface. Personal chemistry matters and needs care and attention, it is built from consistent efforts at mutual understanding.
Teach each other. Both parties will come to a research collaboration with a good deal of background, prior research and experience. This needs to be shared and the best way is to devote the time to teaching each other. This process of establishing a common platform of concepts and techniques, and often a shared language, can be incredibly productive and should not be skimped on.
Exploit existing work. Do not start from scratch on a whim. If either party has already made progress, exploit it. There is a peculiar version of 'not invented here' that often tempts collaborators to start from a blank sheet of paper. Use the resources that are available to the partnership to the full.
Eschew the 'big name'. In every area of science and engineering there are 'big name' individuals and institutions. They have the reputation and an obvious track record. They are the brand, the safe collaborator. They are also, chances are, busy and overcommitted. They will undoubtedly be pleased to work with you but buying their full attention will be expensive. Your money will buy a lot more commitment as well as time from an early career academic. Use the big name to talent-spot, provide thought leadership and scope out the larger field; an advisory role, suitably remunerated will get you this.
Sometimes you get an A student and sometimes an F student. Students can be an incredibly valuable resource bringing dedication and talent to a project. They are particularly good if the aim is to gain exposure to, and map out, a new field. Remember however, the student is learning and will take time to get up to speed and they have their own goals perhaps to get a doctorate that take priority and may not be wholly compatible with the aims of the collaboration. With masters and undergraduate students it is critical to understand that sometimes you get a strong student and sometimes a struggling or uncommitted student, the university has the obligation to educate and support both, which you get is essentially random.
Use smart money. Universities are complex organisations and they have a wide range of ways in which they can engage and secure funding. The same amount of funding, applied in different ways, can secure very different results. Thus, consultancy, funded-research, studentships, corporate donations, matched funding, and so on, are each treated differently, both internally and in the ways that university performance is assessed externally. Working together to ensure that money is used smartly, perhaps in 'patchwork' can significantly improve the effectiveness of the funding and the success of the collaboration.
Stop quibbling. I have seen many collaborations, too many, founder over arguments relating to IP that neither party are in a position, or are intending, to exploit. Indeed, these arguments often relate to IP that it is, realistically, unlikely to arise from the collaboration or where the route to exploitation is not available. Often, the commercial and legal departments of both industry and university are blamed, and to be sure they can have their faults. Ultimately however, they are working to technical appraisals, risk assessments and directions given to them by the principals in the collaboration. These need to be sensible and commercially informed. The keywords here are partnership and risk-sharing based on a reasonable understanding of the risks and potential returns.
Reveal win conditions. Quite often what constitutes success to the individuals engaged in a collaboration is not clear. Perhaps flashy presentations for senior management are more important than scientific papers. Perhaps patents are highly valued or possibly keynotes at industry conferences. Insofar as possible this needs to be clarified early in the collaborative process and respected. My experience suggests that, in most cases, prototypes are particularly important to industry collaborators, they may pay lip service to scientific papers but demos buy credibility.
External funding is not 'free cash'. It is very tempting to leverage a collaboration using funding from a government research funder. It may or may not be the right thing to do. The funders have their own goals and expectations that may not necessarily align with what either university or industry want to achieve. They have frameworks that significantly restrict the way the work is conducted as well as adding more or less complex processes for application and obligations in respect of reporting. Understand the implications of a decision to look for external funding, more of the wrong sort of money may mean less of the right sort of science.
These golden rules are, as they say, 'necessary but not sufficient'. Have fun, the best reason to do collaborative research and the most reliable guarantor of success.