Innovation is described by some as ‘connecting the dots’. The iconoclastic chief of the Virgin Group, Sir Richard Branson, uses the mantra “A-B-C-D. (Always Be Connecting the Dots).” The magic in this recipe is seeing the dots in the first place, since most people view a subset of what’s really out there and work within that framework. It is a criticism of much of higher education that students are taught to ‘collect the dots’, rather than connecting them (Seth Grodin, Stop Stealing Dreams) .
Companies have made numerous attempts at building innovation groups within them, usually without success. Some were iconic failures. Others were extraordinarily influential, just not for the company that paid them. Xerox PARC comes to mind. But the most enduring innovation company comes from the least likely of places – the US Government, and specifically the Department of Defense in the Defense Advanced Projects Research Agency – DARPA. It was founded in the shadow of the Russian launch of Sputnik, with a simple mission “to prevent and create strategic surprise.”
The special forces reference pertains to giving the local R&D groups the independence to make decisions ‘on the ground’ as the work they are doing dictates. This includes budget redirection, hiring, shelving unproductive research directions and revising them toward new ones. In short, it’s about giving the people leading these groups the permission to creatively respond to the emerging conditions in real-time. Summarized in list form, the three principle characteristics of DARPA-like organizations on which their success rests are:
- – Ambitious Goals
- – Temporary Project Teams
- – Independence
These are critical observations in the HBR article by
We believe that the past efforts failed because the critical and mutually reinforcing elements of the DARPA model were not understood, and as a result, only some of them were adopted. Our purpose is to demonstrate that DARPA’s approach to breakthrough innovation is a viable and compelling alternative to the traditional models common in large, captive research organizations.
Relevance to Higher Ed
It might be logical to translate this to the university context and to the organizations or units within it that try to address emerging technologies and their application to issues of teaching, learning and entrepreneurship. There is some utility in this, but it’s unfortunately not a simple parallel with mappings of DARPA processes to university practices. Were it ever that easy.
Dugan and Gabriel remind us of Pasteur’s Quadrant, developed in by Donald Stokes back in late 90’s, where he argued convincingly that recognizing the importance of use-inspired basic research a new relationship can be established between science and government. (see Pasteur’s Quadrant: Basic Science and Technological Innovation). The crux of the argument is illustrated by the Cartesian graphic below
The upper right quadrant is the sweet spot in this model, labelled after Luis Pasteur for his work advancing microbiology while coming up with practical advancements such as discovering the principles of inoculation, pasteurization of milk (from whence the term comes), and microbial fermentation. DARPA ‘lives’ in Pasteur’s Quadrant.
In the university context, there are a few laboratories and centers that thrive in this space. Some bridge the boundary between Pasteur and Edison, such as MIT’s Senseable City Lab, led by Carlo Ratti. The majority, however, inhabit the upper left quadrant, Bohr’s Quadrant, characterized by pure or basic research. That has been one of the problems that many accountability minded legislatures find difficult, articulated most succinctly by newly elected Governor Ronald Reagan when he wrote in 1967
taxpayers shouldn’t be “subsidizing intellectual curiosity” at universities.
to which the LA Times replied
If a university is not a place where intellectual curiosity is to be encouraged, and subsidized, then it is nothing.
The challenge is that most higher ed institutions are confronting rapid changes in areas such as big data, analytics, and computational algorithms, but these rarely find their way back into the course teaching and learning practices of the academy.
Informing the T&L space based on advances in data & learning analytics, visualization, and cognitive sciences is tricky. On the one hand most organizations who own this responsibility are in Edison’s quadrant. They are focused on applications of practical value, often articulated by the caution not to ‘experiment on’ the young charges that are in faculty classrooms. Their goal is to move best practices of established value more widely into the realm of the iconic space where learning purportedly takes place – the classroom. Nevermind that there is substantial data to suggest that the classroom is among the last places that substantive learning happens.
I’m reminded of a recent visit to a well known research university where in the company of a computer science colleague we visited a variety of groups as part of an information gathering trip about inter-disciplinary innovation. We spent part of the day in that university’s teaching and learning center and then moved on to another group. On arriving at the next stop of the itinerary I explained to our new host we had just visited the teaching & learning center. The professor looked me in they eyes, and paused for a long minute before saying
some people would say on this side of the campus that if you’re teaching, students aren’t learning…
Getting innovation to ‘happen’ requires stepping outside the square of one’s own design or thinking paradigm. One way to do that is find people who can engage with you but from either the edges of your current domain focus, or outside it altogether. For example Philips had established a significant market share in PET, CAT, and related medical visualization technologies. But incremental improvements weren’t achieving further expansions of their market as competing companies had technology improvements and incremental advances didn’t translate into major expansion of the market or large increases in profits. Just the opposite. Substituting newer technology, developed a significant cost, for older technology couldn’t significantly advance either the competitive value of their scanners nor qualitatively improve the patient experience. Instead they sought to technologies that might enable the creation of products and services that people would find more meaningful than current offerings. They asked , “Will a new approach, not just to the technology but to the entire problem space in which the technology is embedded transcend existing needs and give customers a completely new reason to buy a product?”
This is closer to the situation of higher education because most technology enabled learning support organizations are not doing novel, discovery oriented research. That’s the province of the faculty or departmental research labs and institutes. Partnerships with these discovery-focused research facilities can be exhilarating and valuable. But they are not the primary work or intellectual space for the application of learning sciences and new practices to the learning mission of the academy.
The trap of applied research learning science groups is the trap of incremental innovation. These are well within the existing frame of reference, representing slight improvements that return immediate pay offs, even if relatively small. The key idea is that the framing of the problem has not been altered, only the exact steps toward getting to a better solution.
In the case of Philips the researchers took a step backward or sideways. The improvements in computed tomography (CT) scanning were steadily advancing. In fact the number of images that a CT scanner could capture with each rotation of the X-ray tube had increased sixteenfold from its introduction in the early 1970’s through early 1980’s and the rotation speed had doubled (improving the machine’s ability to compensate for patients’ movements). It would continue to improve, but so would those of their primary competitors. What else could improve scan results or speed the process overall?
For many getting a CT is a profoundly anxiety provoking experience. You aren’t getting one because things are going well. Further the process is foreign from any normal person’s experience, full of strange machines, injections, and loud noises. The result of all this? Patients don’t lie still when on the scanning bed. No matter how accurate the scanning technology gets, fidgety patients lead to lousy images more time to capture decent ones, and an overall unpleasant experience. For some, especially children, the patient has to be sedated – more time, additional expense, and further negative response to the whole diagnostic experience.
Expand the frame. What is the totality of the experience and how can addressing these other elements enhance the core effectiveness of the incrementally improving technology? The answer was to make the experience leading up to and within the CT scanner more engaging and distract the foreign and fear inducing strangeness it tended to produce. By using LED displays, video animation, RFID (radio-frequency identification) sensors, and sound-control systems, the patients experience was now the focus.
For example, when a child approaches the examination area, she chooses a theme, such as “aquatic” or “nature.” She is then given a puppet containing an RFID sensor, which automatically launches theme-related animation, lighting, and audio when she enters the examination room. The theme can also be used to teach the child to stay still during the exam: In the preparation room, a nurse may show a video of a character on the sea and ask the child to hold her breath when the character dives underwater to seize a treasure. Projecting the same sequence during the exam helps the child hold her breath and lie still at the right moment. (Roberto Vergante, Designing Breakthrough Products, HBR, https://hbr.org/2011/10/designing-breakthrough-products/ar/1)
The result was patients stayed more quiet, fidgeted less and the picture quality improved dramatically. Fewer patients required sedation, making the process overall shorter on average. Change the frame, solve a different but related problem, and make improve a process that includes the one that was the initial focus of attention. But to do this required boundary crossers.
These people have much of the core knowledge base of the primary researchers but who are approaching the problem from a different perspective. In the case of Philips and the CT example, they certainly had their share of doctors, hospital managers, engineers of medical equipment, and marketing experts. What they brought to the table to augment this were architects, psychologists, contemporary interior designers, LED technologists and media specialists, interaction designers, and game oriented interactive hardware and software designers.
To work creatively in Edison’s quadrant within higher education requires reframing the problem space. Yes, the applied researcher typically working in Edison’s Quadrant is looking for practical solutions, and often isn’t looking necessarily to understand why something works in detail, just that it does. In higher ed, because of the nature of our work and our cultural context, we generally do care about why something works – to a point. It has to have credibility because our customers are researchers in their own right, experts in their domains. This is not limited to the STEM disciplines. Faculty in the humanities and performing arts are knowledge creators, using different methodologies, with different criteria by which understanding and meaning are created and assessed. But they are usually looking for logical as well as intuitive consistency that cannot be dismissed with “it just works, but I don’t know why.”
There are critical elements in the “special forces” approach that are critical to groups trying to apply what we know and what we’re learning about cognitive sciences and learning to enhance the undergraduate experience. Indeed, a portfolio of work that includes ambitious goals, temporary project teams or “hot teams”, and independence are necessary ingredients. But so to is the focus on applied innovation, problem solving in the practical world of undergraduate education, and sitting on the boundary of Pasteur’s and Edison’s Quadrants where the work is creative, socially meaningful and pragmatic.
Verne Burkhardt, (2009). “Design Thinking for Innovation: Interview with Tom Kelley, General Manager of IDEO, and Author of The Art of Innovation and The Ten Faces of Innovation“. Design Thinking Blog. http://www.designthinkingblog.com/http:/www.designthinkingblog.com/tom-kelley-on-ideo-and-effective-innovation/
Regina E. Dugan, and Kaigham J. Gabriel, (2013). “Special Forces” Innovation: How DARPA Attacks Problems, HBR, https://hbr.org/2013/10/special-forces-innovation-how-darpa-attacks-problems
Donald E. Stokes, Pasteur’s Quadrant – Basic Science and Technological Innovation, Brookings Institution Press, 1997
Roberto Vergante, (2011). “Designing Breakthrough Products”, HBR, https://hbr.org/2011/10/designing-breakthrough-products