Public research has reached an inflection point. Nowhere is this clearer than in Europe, where concerns mount about the growing innovation gap with the US and China. This gap exists despite more spending per GDP on public research, a high world share of scientific publications and a strong position in patenting according to the European Commission’s 2024 Draghi Report. Researchers are producing world-class knowledge, but much of it stays within academic circles, never progressing toward application or impact.

"Much of the knowledge generated in research institutions remains commercially unexploited. According to the European Patent Office (EPO), only about one-third of the patented inventions registered by European universities or RTOs are commercially exploited."

- The Future of European Competitiveness (Draghi Report)

The challenge facing Europe today is strikingly similar to what once plagued manufacturing, startups, and software development: slow progress, underused talent, and fragmented systems. In each case, the solution was a shift from maximizing output to maximizing learning and value, driven by feedback, iteration, and real-world responsiveness.

This transformation was guided by Lean Thinking.

Lean Thinking

Lean Thinking began in post-WWII Japan, when Toyota pioneered methods for eliminating waste, improving flow, and empowering workers to improve quality and efficiency. These principles went on to revolutionize manufacturing, shape Agile and DevOps in software, guide startups through Lean Startup methodology, and inspire mission-driven organizations through Lean Impact.

While not every Lean domain shares all the same constraints, each faced persistent friction caused by complexity, uncertainty, or institutional inertia, making traditional, linear approaches inefficient. That’s where Lean made the difference: by creating systems that could learn and adapt quickly. The application of Lean Thinking to social change is a testament to its applicability to mission- and knowledge-driven domains.

Lean Thinking is structured around five principles (illustrated below).

The next section will explore what these principles mean for research teams and institutions aiming to improve efficiency, relevance, and real-world impact with a particular focus on early-stage translational work that has the potential to reach patients, markets, or public services in the years ahead.

Lean Principles in Research

Lean Thinking can play a role in publically funded research, which often diverges from eventual utility, not for a lack of quality, but because of misalignment between what is being developed and what the world actually needs or is able to use. Lean can help teams make better strategic decisions earlier, shaping work that maintains academic rigor but is more likely to become useful, fundable, and scalable.

The core ideas behind the Lean Principles can bring much-needed agility, focus, and stakeholder alignment to the research-to-impact journey. Each of the principles is described in the public research context.

Define Value

Creating value from research is called valorization. It takes many forms, including commercialization, citizen participation, policy influence, open science, cultural and educational outreach, and practice-based integration.

It is crucial to clarify which forms of value the work could realistically support, and which stakeholders might care. Many projects stall because they pursue technically elegant work that lacks a clear beneficiary who is willing and motivated to integrate the innovation into their workflow.

Map the Value Stream

The term value stream describes the steps that turn an idea into a meaningful outcome, such as improving patient care, enabling policy, or creating a viable product. In innovation ecosystems, one of the most common tools for describing technological maturity is the Technology Readiness Level (TRL) scale , which ranks maturity from 1 (basic principles observed) to 9 (proven in operational environment).

But real-world innovation is rarely linear. Many promising technologies stall in the so-called “valley of death”, where funding dries up, barriers to innovation abound, regulations overwhelm research teams, and key assumptions go untested.

It is thus essential to move beyond TRL and map the actual value stream by asking:

• What conditions must hold true for this to work in practice?
• Who would benefit—and under what constraints?
• What bridges are missing between our current work and future use?

Create flow

Flow is the continuous and efficient progression of value through a process, minimizing delays, waste, and interruptions. In research, this means reducing delays between insight, feedback, and decision-making and working across silos, which ultimately translates to higher quality, greater relevance, and genuine morale.

To improve flow, research teams can:

• Shorten feedback loops with potential users or clinical stakeholders
• Integrate ethical and regulatory perspectives early, avoiding rework down the road
• Break big questions into testable components to maintain direction and flexibility
• Design projects to surface uncertainty early, not hide it until late stages
• Write agility into grant proposals, ensuring projects are adaptive and iterative

Establish Pull

Pull means responding to real demand rather than pushing ideas forward based solely on internal priorities. In Lean Thinking, establishing pull ensures that effort is directed toward outcomes that are actually needed and likely to be adopted.

In academic research, "pull" is often interpreted through proxies like scientific curiosity, citation potential, or available grant calls. While valid within the academic system, these signals don’t always reflect unmet needs in practice, policy, or industry.

To establish true pull, researchers should explore:

• Who would actively want or use this innovation, and why?
• What barriers do potential adopters face in integrating new solutions?
• Are there stakeholders signaling urgency or readiness, beyond academic circles?

Working toward pull doesn’t mean abandoning fundamental research. It means spotting opportunities for real-world relevance and measuring early traction as a signal that the work aligns with genuine demand.

Seek Perfection

Seeking perfection in Lean doesn’t mean flawless outputs. It means continuously improving the process by identifying friction, learning faster, and aligning efforts with purpose.

In research, this mindset shifts focus from polishing individual results to improving the system of inquiry:

• Are we working on the right problems?
• Are we learning fast enough to make informed decisions?
• Are we spending time on questions unlikely to lead to meaningful outcomes?

Perfection is pursued not through control, but through reflection, feedback, and refinement.

Ready to Make Your Research Go Further?

Whether you're a researcher or in a support role, you're likely already doing valuable, rigorous work. If you're aiming to boost real-world relevance, speed up progress, or strengthen your team's impact, then get in touch with Eunovus.