Fast innovation: lessons from scientific research

Feb 16, 2015

In this digital age, where technologies, customers and competitors are ever-changing, speed and innovation are essential. What can companies learn from scientific research, with its centuries-long experience in driving innovation?

The easiest way for companies to address the need for innovation is to start a dual mode of operation, where the traditional or industrial part of the organization functions in parallel with a more agile one focused on innovation.

Launching such an agile mode is, however, not that straightforward. Whether in terms of governance, operations, talent, or technology management, the path is strewn with pitfalls.

This is where insights from scientific research take their full value. The best way to organize this agile mode is to establish a series of project-based cells organized similarly to how research labs are operating. Based on my experience as a scientist, I will describe how the most successful laboratories operate in order to reveal some best practices.

Science is a harsh mistress

The goal of scientific research is simple: to come up with a concept (a theory, an insight, an application) that nobody has ever done or thought of before. Scientific research is pure innovation.

Most people picture researchers as lonely, eccentric people lost in their arcane world without any connection to reality.[1] In reality, these days scientific research is one of the most competitive industries out there. Researchers are competing for (very limited) funding. Science obeys a winner-takes-all dynamics: if you’re not the one to publish the result, all your (months, years of) efforts will be lost. And because science is becoming so complex, no lab has all the knowledge in-house. Competitive partnerships with rival labs are thus necessary to move forward.

Moreover, new scientific concepts must be compatible with the body of knowledge accumulated throughout the centuries (“Standing on the shoulders of giants”, as Newton famously said). In this sense, science is a highly-constrained form of innovation, similar to the way innovation within businesses is constrained by existing activities, culture or processes. Of course, once in a while a totally new breakthrough that departs from prevailing theories occurs, similar to how industries are occasionally disrupted with the arrival of a new technology or business model.

Research labs have thus adapted their way of working to survive in this hyper-competitive environment.[2] So what drives research productivity?

The way of research

Science, like innovation, is not chaotic creativity. On the contrary, it requires a very disciplined approach, both from individuals and from the supporting organization. As American author Zora Neale Hurston aptly puts it:


“Research is formalized curiosity. It is poking and prying with a purpose.”


Formalization is indeed a key aspect. Science cannot progress solely (or even mainly) from the contributions of once-a-century geniuses or looney individuals. At the same time, highly organized research is guaranteed to produce nothing new. So, how to strike the right balance?

A first insight is found in Z. N. Hurston’s quote: purpose. Successful labs have a very clear and focused strategic vision. Researchers are not asked to innovate, but to innovate to contribute to a well-identified objective. Clear strategies enable effective decision-making on allocation of resources and building new capabilities.

Project portfolios are designed to be interlinked, so that they are both additive and synergistic. In this way, each project contributes to the overall purpose, and each project might uncover insights that prove valuable to another. The constant search for ways to create competitive advantage through technologies is another recurring feature.

Laboratory heads are keen to give teams autonomy and not over-define the specific approaches they should use, as doing so risks demotivating researchers and squelching potentially innovative ideas. Instead of micro-managing, they work with the broad group to outline the general approach. In other words, the goal is clearly communicated, but the details of the how to reach it are not (after all, how can you plan or make a business case on something that has never been done before?)

Project teams are assembled to incorporate the mix of skills needed to address particular problems, and it is these, rather than functional groups, that are the focus of the organization. As an example, when I was working in a neuroscience lab in the US, only one out of the 10 lab members was from the US. Similarly, only two were actual neuroscientists, while the other had background in fields like biology, physics or engineering.  

Now, what kind of person is best suited to thrive in research? Specific technical capabilities and creativity are not the most important attributes. Rather, curiosity, general problem-solving skills and adaptability are rated higher. The ability to work within a rigorous framework and in a fast changing environment is also key characteristic.  Interestingly, achievements are rewarded more by peer recognition (e.g., access to top conferences) rather than financial rewards.

Fast innovation: lessons from scientific research 

An open, sharing culture is important for productivity. Physical proximity also plays a key role in promoting collaboration. It is beneficial to organize departments so that different teams and disciplines work closely together and even sit in the same areas.

Laboratory heads also encourage their researchers to spend time on projects driven by their own personal interest. This freedom helps researchers maintain their passion for work, but can also ensure innovative ideas are not overlooked. Some laboratories (and companies) have seen these side projects develop into major initiatives (that’s how Gmail and sticky notes were invented).

But if all does not go according to plan, top labs do not shy away from tough decisions. Although a project might sometimes warrant modification, they are willing to terminate sooner rather than later if a project is not showing results. Pouring more resources into a project that is unlikely to add value, or allowing it to continue at a lower level robs other projects that have greater potential.

Going agile

Innovation, like science, is not the result of single individuals anymore, but a collective (company) effort and responsibility.

As mentioned earlier, the best way to kickstart this evolution toward innovation is to launch a dual mode of operation, in which an agile mode works alongside the core, traditional part of the business.

Scientific research operations provide valuable insights on how to set up this agile mode and how to maximize its effectiveness and chances of success. Set clear goals, but don’t control too tightly. Select low-impact, high learning potential projects at first. Focus on adding business and customer value with a synergetic and additive project portfolio. Create collaborative environments. Mix IT, business, and customers, and look for people with the ability to learn and to adapt.

Using these best practices, these initiatives will likely grow and, before long, you will have moved toward the next step, i.e. synchronizing the two modes of operation to establish a true ‘innovation factory’.

David Andrieux
, PhD

[1] Admittedly, some researchers do fit this stereotype.

[2] This competitive environment has gradually emerged over the last decades due to a series of factors, including decreasing budgets, globalization and faster access to information.