Encouraging Entrepreneurial Thinking in Academic Training

If you care about research actually changing the world, not just filling journal pages, then encouraging entrepreneurial thinking in academic training should be on your short list. Yes, that specific phrase, encouraging entrepreneurial thinking in academic training, is the point. Say it out loud, write it on a whiteboard, tattoo it somewhere sensible, because the status quo is not serving either students or society very well.

The problem is obvious, and we all pretend it is not. Academia runs on the charming anthem of “publish or perish”, which often translates to publish frequently, chase impact factors, and optimize for metrics instead of usefulness. That produces lots of papers, sure, but not necessarily research that is robust, scalable, or actually used. Meanwhile industry complains that graduates lack practical skills, and PhD students end up surprised that no one outside their bubble knows what “neuroimaging preprocessing” means. The gap widens.

Encouraging entrepreneurial thinking in academic training is not about forcing every lab to spawn a startup. It is about cultivating mindsets and practices that help researchers turn good ideas into usable things, while retaining rigorous science. Here is what that looks like in practice.

 

Start with mindset, not just modules

Entrepreneurial thinking is a mindset, not a business minor. That mindset includes:

  • Thinking about who benefits from the research, and how
  • Validating ideas early with users or stakeholders
  • Iterating rapidly based on feedback
  • Communicating value clearly to non-academic audiences

We don’t need to turn every PhD into a CEO, but we should teach PhD students to ask, “Who will benefit from this?” and “How could this be used outside the lab?” That one shift in questions changes the trajectory of research from inward hobby to outward impact.

 

Teach core, practical skills

Soft skills are not fluff. Time management, project planning, pitching, stakeholder communication, and basic financial literacy are all directly relevant. These are the skills industry expects, and they make academic work more efficient too. Instead of assuming everyone will pick them up by osmosis, add structured opportunities during the PhD to learn them. Not in a token one-day workshop, but integrated options students can pick depending on their goals.

A simple, effective change is to encourage every PhD candidate to build a living portfolio, focused on “non-academic” skills. Document grant writing, project roadmaps, public communications, collaborations, tools developed, and management experience. This makes transferability visible, and helps during job transitions.

 

Build bridges, not barriers

Universities already have incubators and tech transfer offices, but they are often siloed and focused on IP and commercialization as a trophy. If the goal is encouraging entrepreneurial thinking in academic training, these units should help researchers explore options, not just patent and shelve. That means:

  • Funding and advising for prototype validation, user testing, and pilots
  • Program managers who help coordinate multi-disciplinary teams
  • Pathways for researchers to join industry partnerships, while retaining academic independence

Grants can nudge this. When funding agencies require a plan for societal impact, they should also support the people and infrastructure that make impact feasible, not just demand a paragraph in the application.

 

Rethink IP, with pragmatism

There is a constant argument about patents versus openness. Yes, taxpayer-funded research should ideally benefit everyone. But free code that nobody maintains is still useless. Patenting has its place when it enables investment and product development. Open source has its place when communities will maintain and improve tools.

A pragmatic approach is to plan sustainability, not ideology. If an open tool is likely to be maintained, support it. If a patent is the only way to get industry traction and bring a product to patients, then pursue that. And always ask, who will maintain this framework in five years? Plan for the answer.

 

Train PIs in management, not just mentorship

A familiar piece of advice I heard is simple and blunt, “Do you get along with your supervisor?” three times over. That micro truth speaks to a bigger point. Supervisors need management skills. Being a brilliant scientist does not automatically make you a good lab leader. Encouraging entrepreneurial thinking in academic training includes upskilling PIs in team management, communication, and strategic planning.

If your lab functions like a small company, then treat people like contributors who need clarity, feedback, and alignment. The best labs are the ones where leaders can attract talent because people want to work there, not because of coercion or hierarchical pressure.

 

Fund differently, with diversity

Traditional grant cycles and the publish-for-evaluation culture create perverse incentives. Alternative funding routes, like collaborative industry grants, SME partnerships, and yes, even crowdfunding for specific applied projects, offer diversity. These models can support projects that are user-focused and iterative, and they reduce the risk of burying negative results.

Importantly, grant calls should allow budgets for project managers, engineers, and maintenance. If you want usable outputs, don’t pretend a PhD stipend will cover product development and ongoing upkeep.

 

Pilot, iterate, and pre-register

Entrepreneurial teams iterate fast, test assumptions early, and pivot when needed. Applied academic projects should do the same, while keeping methodological rigor. Pre-registration and transparent workflows help here, because they make iterations visible and reduce the replication crisis incentives. Pilot, fail fast in an honest way, learn, and keep a record of what changed and why.

Encouraging entrepreneurial thinking in academic training is not a replacement of curiosity-driven science. It is a complement. It gives researchers tools to make their work durable and useful. It fixes the chronic blind spot where excellent people invent brilliant things and then nobody uses them.

If you are a PhD student, start documenting your non-academic skills and talking about impact. If you are a PI, learn to manage a team and experiment with structures that focus on outcomes, not metrics. If you run a university or funder, fund project management and maintenance, and reward useful transparency as much as flashy headlines.

This is not a revolution that needs permission, it is an approach that requires small, deliberate changes. Encouraging entrepreneurial thinking in academic training will make research more relevant, graduates more employable, and ultimately, science less likely to hide behind the convenient excuse of “publish or perish.” Start asking the practical questions today, and the work we do tomorrow will be a lot less theoretical and a lot more useful.

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