However, this may be too short-sighted, because those companies don’t necessarily invest in long-term value creation, but instead focus on short-term product development. There’s still a critical place for long-term corporate research – but the form of that research needs to change. There needs to be a reason to look three to five years into the future, outside of existing product roadmaps and to take bigger risks on novel ideas. But the research can’t be arbitrarily open-ended. As lovely as it was for researchers to feel like they were working on blue-sky ideas in a university with no students and big budgets, the time for that kind of research is likely over, everywhere except for a very few exceptions. Even universities, which used to predominantly focus on basic research, increasingly do applied research with the intention of licensing their own patent portfolios.
As linear waterfall methods of doing research disintegrate, there is also significant competitive pressure to work across disciplines. Manufacturing companies need to understand AI. Cosmetics companies need to understand both computer vision and the social use of images. Raw material companies need to understand machine learning, distributed sensor networks. A mouthguard developed at PARC with UCSD, University of California San Diego, required the knowledge of biology, chemistry, electronics, manufacturing and AI to put together something that can identify different kinds of things in saliva and then make sense of it.
Today, basic research needs to be market tested much more quickly to justify continued investment and research agendas must adapt much more quickly. Researchers no longer have the luxury of assuming that someone else will figure out how to apply and commercialise their work. Now it’s everyone’s job. Traditional research looked for return on investment seven, 10 years into the future, which given today’s shifting markets and technologies, might as well be forever.
Start-ups, on the other hand, are highly incentivised, especially in the highly instrumented lean market of today, to demonstrate market traction as quickly as possible. They tend to focus on incremental change mashups based on mature technology stacks. There’s a big gap between the near-term traction-driven incremental development and long-term open-ended investment. Both are necessary for a balanced portfolio, but they’re the extremes.
Design practice is what enables that middle zone, the three to five year out disruptive transformation based on bleeding edge scientific knowledge. It’s how you create novel experiences and connect the discoveries of today with near-term business transformation. Design practice creates a mechanism to justify the necessary sustained investment to bring risky, disruptive, transformative technologies that are not based on existing tech stacks to market, and then have the patience to wait until their impact can be understood.
At PARC we believe that design practice delivers this middle ground and define it as a combination of product strategy, service design, user experience design, social science-based customer research and iterative prototype-driven concept exploration. When people ask what the Innovation Services Group does at PARC, I reply that our researchers find deep answers about the way the world works and then we have to find out what the question is.
Author profile:
Mike Kuniavsky is head of design at PARC (Palo Alto Research Centre)
