Imagine It Forward

by Beth Comstock

  We had an operating system that produced order—that celebrated and enshrined a way of doing things that had enjoyed a stunning run of century-long economic success based on the industrial operating system (OS)—getting bigger and bigger by optimizing, well, everything, and mitigating risk. But we had lost the capacity to create and grow to entrepreneurs, VCs, and the tech-driven agents of New Power. We had misguidedly given up on the new, attempting to buy our way to greatness, by what I call R&D-by-M&A ( research and development by merger and acquisition).

  Could we become more agile, creative, and adaptive while retaining the very hierarchy and bureaucracy that inhibit such capacities? We needed to upgrade our OS. But how? I wasn’t sure. But I knew the first step involved opening GE up and exposing it to more New Power, driven by open, peer-dominated communities.

  It would require GE to understand a radically different mind-set based on informal decision-making and self-organization, open-source collaboration, transparency, do-it-yourself “maker” culture, and tolerance for risk-taking and variability.

  For 120 years, GE had functioned as a medieval castle with high walls, jealously guarding its talent, resources, and knowledge, and treating outsiders (people, companies, ideas) with deep suspicion. The job I’d assigned myself now was to get GE to not only allow these strangers entry into the castle but to invite them to help tear down the walls, pave over the moats, and connect the castle to a diverse flow of goods and people from other villages the world over.

  Party at GE…and Everyone’s Invited

  It started with a simple invitation: “Hello World! We need your help.”

  In the aftermath of the financial crisis, the venture capitalists who had backed the soaring clean-technology industry had gobs of investments in clean tech that were going south. There was a collective realization in Silicon Valley that new models of energy generation, such as solar, battery storage, and biofuels, would require a lot of capital to scale—and that returns would come much farther down the line than past investments.

  While that was true, we knew that clean tech remained essential both for the future of humanity and the future of our business. Those certified products generated $20 billion in annual revenues for us by 2010. In this fervid moment, we created our own high-profile open-innovation event—the GE Ecomagination Challenge.

  Along with VC firms Kleiner Perkins, RockPort Capital, Foundation Capital, Emerald Technology Ventures, and Carbon Trust, we launched a contest for outside inventors to submit clean-energy innovations and committed a combined $200 million to fund those picked by our selection committee.

  As a stab at open innovation, the challenge was a great success. We had expected a few hundred ideas, but we found ourselves swimming in proposals from entrepreneurs around the world—over four thousand ideas from 150 countries. While not all were good, many were. It forced GE to make the humbling admission that it didn’t have all the answers.

  We ended up investing $140 million in twenty-three of the start-ups, and we gave out grants and awards to many more. Some went on to good success—such as Opower, a cloud-based service that tracked residential power usage and created data visualizations for utilities and consumers to save energy; others seemed a bit far out but really captured people’s attention, like a plan to pave roadways with solar generating material.

  And yet, we struggled with what to do with all the good ideas submitted. Take the solar refrigerator for Africa. Now, it didn’t get the temperature very cold, but it really helped reduce food spoilage. It was a lifesaver. But we didn’t know how to gauge need or launch a low-cost consumer product in Africa, so no one was willing to invest.

  There were hundreds of good ideas like this that made me see the limits of how companies and VCs measure start-ups as investments. Venture investors ask one basic question: How will we exit?—meaning, How will we make a return on the company as it gets sold or acquired in a defined period of time? With that guiding them, VCs, like many people, favor models, people, and outcomes with which they are experienced. I think this is one of the reasons it has been so hard to seed diversity in Silicon Valley.

  As the eco challenge went on, it became clear that the real power of the community we were building was not its offerings to us but its ability to collaborate inside itself. Why not connect the solar roadways to a water extraction invention or electric signage? By not focusing our efforts on harnessing that power, however, we failed the community. As soon as the challenge was over, the agglomeration of big organization and start-up entrepreneurs went away.

  Dabbling

  One of the labels I fought at GE was that of “The Dabbler.” Jeff would say, “Yes, but that’s just dabbling,” when we’d talk about one of our open challenges. In other words, “Tell me why this isn’t a waste of time.” But dabbling is an essential part of the innovation process. It is that early pretesting phase that helps you refine what you seek to experiment with, a way of filtering ideas.

  As psychologist Dean Simonton argues, the difference between Bach and his mediocre colleagues is not that he struck out less often, but that he had many more ideas. More ideas, more innovation, and more contact between people lead to more insights, theories, observations, and unplanned connections. To head off the naysayers, however, you have to show that the “dabbles” are part of a broader strategy.

  Still, I saw real promise in these challenges as cultural catalysts and strategic mechanisms to see things earlier, to generate new ideas, to partner for speed and access, and to share the risk and reward of moving fast into new spaces.

  Directed dabbling is what led me to Bre Pettis, a former art teacher from Seattle who started NYC Resistor, a Brooklyn maker space, and also launched the 3-D printing company MakerBot next door. I had been tracking Bre as part of our digital development effort.

  I e-mailed Bre to ask if I could simply hang out and watch what he was doing: “I want to understand the new wave of micro-manufacturing, and especially what you are doing with 3-D printing.”

  Resistor was a higgledy-piggledy series of rooms on the fourth floor of a run-down factory. There Bre introduced me to his “makers” as we walked between workbenches covered with bits of sheet metal and wires and boxes of odds and ends. I saw people making a miniature wind turbine and a portable water purification system. That is, GE kinds of things. One guy was building his own miniature gas turbine, because, well, he could. “Why not?” he said. “People want to live off the grid.”

  “We could use this ingenuity inside GE,” I said out loud.

  After NYC Resistor and MakerBot, I met with Shapeways, in Queens, an advanced contract manufacturer where people submitted designs to be 3-D printed for a fee. As we toured the space and talked about the jewelry they made, I saw printed object parts arrayed in a bed of powder—part of the 3-D printing process. I reached in; the first thing I grabbed was a blue, croissant-shaped sex toy.

  I laughed, but the point is that what’s next always comes from the edge. It’s like streaming video: its first use was for porn, not House of Cards. It’s easy to let yourself think, “This isn’t important.” But the center always gets its innovations from the edge.

  Sensors, 3-D printers, data science, the melding of physical and digital—I didn’t know how it all would work together then, but I knew in my gut that it would lead to a leaner, smarter manufacturing environment.

  Now, how would I translate this for GE? How would I bring makers and their networks back to the organization? That is the critical step for the market innovator. The explorer has to make it real for the people back home.

  Amid a flurry of activity, along with the help of spark Aaron Dignan (who would go on to serve as a spark for GE for nearly a decade), we initiated two threads of activities: First was to offer engineering teams across GE a 3-D printing machine for each workspace to see what they could do with it. The idea was to enable new creation and provoke new inte
ractions by putting the machines in every department, without any threats or instructions. Just play with it. Use it.

  Second, we needed a symbolic maker product as a proof point to capture GE’s collective imagination. To this end, Steve Liguori and I set up one more challenge—one that also challenged the expertise of GE’s engineers and scientists. (I recall one scientist calling us some version of “the village idiots.”)

  Until this time, GE had been using 4.5-pound brackets to hold 727 jet engines in place. We had been trying for years to design a lighter bracket to make planes that used our engines more fuel efficient, saving millions in fuel every year. Our engineers and suppliers had gone as far as physics would allow—or so they thought.

  So we turned to GrabCAD, an online community of over a million engineers and designers, and laid down another challenge: whoever designed the bracket that cut the most weight while still safely supporting the engine would get a cash prize of $7,000.

  It was small money, but the entries poured in, some seven hundred in all. The winner? Arie Kurniawan, a twenty-year-old Indonesian engineering student who cut the weight by 84 percent, to just under twelve ounces, by using what they call a genetic algorithm. It creates a virtual block of material and then (again, virtually) scrapes out a little bit, and then tests it, and then scrapes out another random bit, and tests it again. It does that a couple of million times, and each time creates a finished bracket based on random scrapes that is tested against the specs for high strength and low weight. It repeats the process over and over again until you end up with a perfect part.

  That’s the genius of digital manufacturing: we could iterate the most complex products for virtually no cost. As Luana Iorio, who oversaw our research on 3-D printing, told New York Times columnist Thomas Friedman, “Complexity is [now] free.”

  Getting Quirky

  Call it intuition, call it pattern recognition, call it a hunch, but I knew that whatever new form of management needed to arise inside GE would at least, in part, be based on cultivating the experiences, skills, and knowledge of entrepreneurship. I didn’t know what to call it then. I just went in pursuit of it, starting first in Silicon Valley, then the epicenter of start-up culture.

  What I learned about Silicon Valley is that its success does not arise from the genius of a few individuals but from a connected collective that integrates technologies, funding, and ideas from across the spectrum. That requires resisting the pull of rigid, hierarchical order and capitalizing on the collective, chaotic, self-governing intelligence of groups and networks.

  That’s what we needed to discover as we sought to digitize GE. First I needed to connect, and build GE’s and my personal network in Silicon Valley, so I enlisted my old friend Alex Constantinople. After our days working together at NBC and GE, Alex had moved to San Francisco and was now running a communications agency called OutCast. Alex helped me create a map of the key influencers in the Valley. We printed the “map” on poster-sized paper and sat around an OutCast conference table talking about the influencers and the interconnections and the conflicts among them. I can’t say enough about the value of such a process to understand an ecosystem. I kept the map on a wall near my desk for a year afterward, and it was instrumental in helping me understand dynamics and helped me set up meetings with the people I’d need to know.

  To do this, we grouped key players in areas ranging from venture capital to enterprise software, consumer start-ups, and big tech companies (like Google). We listed media, thought leaders, and upcoming founders of interest, as well as key events as a timeline going forward. We mapped them geographically, by influence (not scientific, more directional) and also to show how they overlapped. For example, who funded whom and where founders previously worked.

  I was in search of the innovation magic that happens when you leave your castle and engage with the broader system. It makes way for more collisions of ideas and capabilities, even serendipity. But was there a name for the kind of structure or set of rules that enables such adaptability? And could we engineer our own ecosystem to create more innovation magic and serendipity at scale?

  I found answers not in management guides but in the biology books of my college years. Unfortunately, the answer isn’t simple. In fact, it is so large that it has become difficult to see. Yet I believe it has urgent implications for everything we do. As our planet-wide digital nervous system grows, it is causing a mass reorganization of people, money, information, and things. That digital information flow has become the main driver of change. And we need new frameworks to understand and anticipate what comes next.

  One of those frameworks is known as emergence, a term that until recently has been used primarily to explain natural systems—what biologists call complex adaptive systems, systems that can adapt and evolve within a changing environment. Colonies of insects such as ants and bees, for example, use simple rules and networks to produce adaptive behavior.

  Emergence

  Emergence describes how, when individual cells, or birds, or elements interact en masse according to a set of simple rules, highly complex structures and behaviors emerge. The billions of neurons that join together in a brain to create the wonders of consciousness; a flock of ten thousand starlings flying at 40 mph making hairpin turns in an instant; the clusters of tiny circuits on chipboards from which staggering computational power arises—all are examples of simple agents working in concert to become more than the sum of their parts.

  In nature, the classic example is ants, which have the most complex social structures after humans. Even though an ant queen doesn’t actually give orders and individual ants aren’t that intelligent, these creatures manage to build massive structures, dispose of trash, bury their dead, and conduct coordinated maneuvers against their enemies. How? Each individual ant is programmed to respond to changes in its environment by releasing a few simple chemical signals that other ants can sense and to which they can respond.

  In both markets and anthills, these patterns of organization are examples of what economist Thomas Schelling called “macrobehavior originating from micromotives.” But here’s the key point: As more and more human activities flow through digital systems, those activities also take on the properties of adaptive emergent systems. We are collectively and spontaneously reorganizing around the flow of our digital information.

  The collective micromotives of connected humans are growing new macrostructures. The notion of emergence helped me to understand the extraordinary growth of the tech titans in Silicon Valley like Google and Facebook, and the growing power of networks and communities.

  From the micromotives of tens of thousands of entrepreneurs and VCs, a small region in Northern California has emerged as a world-changing innovation hub. In the world of organizations, Google, for example, was designed to harness emergence. Its products were released unfinished and exposed to its vast community of users whose continual feedback allowed those products to evolve and grow, and the company to quickly learn and adapt. There were open-source coding projects, without any centralized governing body, cocreating the world’s largest knowledge repository, Wikipedia.

  Suddenly I could see emergence at work everywhere. Technology and the digital flow were allowing unimaginably large numbers of interactions around common goals and shared purposes, where serendipity flourished and human energy (without top-down human control) drove all kinds of activities, making the kind of innovative and imaginative leaps that were once the sole province of well-financed corporate and government laboratories.

  Emergence to me is a way to make sense of the new dynamics of change in a digital world.

  How could GE tap into this emergent knowledge and these diverse skills? How could we experience the power of emergence? Ben Kaufman and his ant army of inventors seemed like emergence incarnate, and exactly what GE needed.

  I had first met Ben through Aaron Dignan. I brought Aaron on one of
our committees at the Cooper Hewitt, Smithsonian Design Museum on whose board I served. During one meeting at which we couldn’t hear people on the speakerphone, I turned to Aaron and said, “We need a base for the speakerphone, something to stop the vibration.” And Aaron replied, “I have a friend who’s got this crowdsourced invention company he just started. I’m going to get him to prototype it.”

  A few weeks later at our next meeting, Aaron showed up with the phone pillow from Ben Kaufman’s company. And it worked really well. I hadn’t even met Ben, and I was smitten. Here was this guy who was inventing, designing, and producing products with fearlessness and speed. I had to get to know him.

  So Linda Boff and the marketing team held a contest with Ben’s company, Quirky, for products that could be improved by adding software. The product Quirky came up with—Milkmaid, a connected milk jug that told you when your milk was going bad or running out—was fun and grabbed a lot of attention (TechCrunch called it “gorgeous”). This guy had figured out how to innovate faster using crowdsourcing! He had so much to teach GE, I was convinced.

  That’s how I found myself in Quirky’s Chelsea warehouse offices in New York City in late 2012. Ben had taken over an old storage space on Twenty-Eighth Street and Eleventh Avenue. He and I hit it off right away as we walked the floor and saw his team. And Ben had been a fan of GE since he was a kid.

  “I love Thomas Edison, Beth. If he were around today, he’d have founded Quirky,” Ben said.