Written by Eoin Galligan, Business Development Manager, University of Aarhus
In recent years, Governments have changed university funding in order to expand the outcomes achieved by university research. In addition to publications, research teams need to consider commercial success criteria with industry outcomes and the creation of potential spinout companies. This article discusses how early-career researchers can begin to address such change.
Do humans cope with change? After reading the academic literature, I would argue that managers in both the private and public sector have not coped well! Further, as I work with university partnerships, I observe substantial change that has occurred for academic researchers, just as for the private sector. I note two important issues that affect early-career researchers. First, funding rules have changed and caused a significant increase of university-industry partnerships and spinout companies. Second, many early-career researchers have not received sufficient support to prepare for this change.
Previously, I wrote about how mind-set can affect careers. I suggested that Horizon 2020 and Horizon Europe were examples of research programmes that had changed the goals of academic research. Socio-economic and “business” language entered the research vocabulary. The definition of impact changed. Therefore, in addition to considering mind-set, I suggest we must ask how early-career researcher can plan to adapt to this change. I try to address that question here.
Let us consider a series of variables that created the situation we face. Over the last years, the volume of PhD students has rapidly increased while the number of tenured positions dropped. In the UK, a report in 2010 by Royal Society highlighted that only 3.5% of PhD candidates would proceed to a research position. The aim was to manage PhD students’ career expectations and highlight the range of opportunities. Many industry stakeholders began to question the purpose of doctoral training and ask if it prepared candidates for industry. In parallel, the cost-effectiveness of public sector funding became a focus for government. With public budgets under pressure, the purpose of university research itself (not only PhDs) came under review. Industry stakeholders wanted research outcomes to connect with a country’s ability to innovate.
Globalisation increased across the global economy. Companies had to lower costs by locating operations to cheaper regions and profit margins became tight. Within this context, companies and investor came up with a new approach. Competitive advantage moved towards the “knowledge economy”, where it was more likely that technology (protected by intellectual property) would provide a company with its competitive edge. These investors and companies began to work with a small group of elite universities and created partnerships to access disruptive technology. Governments around the world began to take notice and implement such activity in their own region.
So what can early-career researchers do? I suggest that PhDs and Postdocs master the skills of networking with industry stakeholders. A first step could be to start with a familiar stakeholder – a research-funding organisation. The goal would be to evaluate the organisation’s perspective on impact. Many funding organisations create an impact report, whilst others reference impact directly in their guidance documents. A good example is grant applications that demand an industry partner. This ensures that the implementation of the research project connects with industry standards, and includes a broader set of goals.
A second step would be to form a list of industry contacts i.e. a “target list” by connecting with the innovation offices across a university campus, such as research support offices, knowledge transfer offices and entrepreneurship hubs. The staff in such offices are close to impact activity and can highlight potential funding instruments and industry contacts. In order to begin networking, a researcher needs two additional tools – an approach email and a telephone script. An approach email does not rely on technical research knowledge, but tries to create empathy. It could highlight that a researcher is seeking to learn from the company – yet highlight specific research expertise (or local university infrastructure) that could be a basis for partnership. The email text would also include some understanding that your contact is busy. You would request a 30-minute meeting, a few weeks in advance to enable your contact to plan.
A telephone script provides a structure to any networking meeting. It will contain an icebreaker, some gentle small talk and a list of open questions such as “how do you identify potential academic partners?” – Or – “how could I structure my research projects so that I build a relationship with your organisation?”. I suggest prioritising the list, with the leading contacts at the top and less attractive ones at the end. You will work your way up the target list, where your early mistakes will be part of your training. Developing the skills to create a great meeting with industry takes time – so you expect mistakes to happen, just as with your research activity.
Your final step should be to share your learning within a professional association, such as a PhD or postdoctoral association at your research institution. Could the association work with the innovation offices to create a network of industry contacts for early-stage researchers? What training is available at the innovation hubs for researchers that do not wish to focus on a spinout? Such type of questions could enable professional associations to create a plan for early-stage researchers to understand and manage the consequences of research impact.
I can understand that early-career researchers may find networking somewhat intimidating. I would suggest to allow yourself to be nervous. Allow yourself to fail. In academia, many individuals tend to strive for perfection. In this networking activity, we need to consider a different set of values. We are not seeking a “perfect” data set – but a set of warm, sustainable relationships with individuals that will not only expand our perception, but will be people that we will want to help too. Maya Angelou once said: “I’ve learned that people will forget what you said, people will forget what you did, but people will never forget how you made them feel.”. I wish you well as you find those people. You may find that they were hoping to find you too.