You have a big idea. Here’s how to turn it into impact

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Peter Drucker was the quintessential management visionary. Often decades ahead of his time, he developed concepts like the knowledge worker and management by objectives long before they were on anybody else’s radar. It was for good reason that the corporate elite hung on his every word as if they were supplicants granted an audience with an ancient oracle. Yet when Drucker first met Thomas J. Watson , he was taken aback. “He began talking about something called data processing,” Drucker recalled, “and it made absolutely no sense to me. I took it back and told my editor, and he said that Watson was a nut, and threw the interview away.” Yet Watson built that idea into IBM, one of the great industrial powerhouses of the twentieth century. We tend to think that if an idea is good enough, others will immediately recognize it. But that’s almost never true. Ideas that change the world always arrive out of context, for the simple reason that the world hasn’t changed yet. It’s what you do after you have one that matters. Allow yourself to be confused As a boy, Albert Einstein liked to imagine what it would be like to ride alongside a beam of light. He learned from an elementary physics text that the speed of light was supposed to be constant, which he found confusing. If he were traveling at the speed of light and shined a lantern forward, shouldn’t that light be moving twice as fast? He continued to dwell in this confusion for a decade, but eventually arrived at the idea that the speed of light is constant, but time and space are relative, which became known as his special theory of relativity . Later, he became confused by another question: What would it be like to be in a falling elevator in space? It took another 10 years of immersion for him to come up with his general theory of relativity , based on that idea. Richard Feynman , perhaps the second most notable physicist of the twentieth century, talked openly about his reverence for confusion. I felt this same kind of confusion during the Orange Revolution in Ukraine. Over time, I had built up some assumptions about how power worked, which suddenly seemed null and void. Nobody with any conventional form of power seemed to have any ability to shape events at all, which was terribly confusing. It took me 15 years to really understand it and those ideas eventually became my book, Cascades . Every profound insight begins not with epiphany, but confusion. So it’s critically important that you don’t dismiss that feeling, but immerse yourself in it. Confusion is often a signal that you have hit upon a genuinely interesting problem. Your job is to resist the urge to resolve it too quickly and keep probing until the confusion reveals what your assumptions have been hiding. Explore and validate One of the most effective programs for helping ideas make an impact in the world is I-Corps . Established by the National Science Foundation to help recipients of Small Business Innovation Research grants identify business models for scientific discoveries, it has been such an extraordinary success that Congress has mandated its expansion across the federal government. Based on Steve Blank’s Lean LaunchPad methodology , the program aims to transform scientists with promising ideas into entrepreneurs with a real business. It begins with a presentation session, in which each team explains the nature of their idea and its commercial potential. It’s exciting stuff: pathbreaking science with real potential to truly change the world. During this initial session, each team is asked, “How many customers have you talked to?” Inevitably, their answer comes up woefully short. They are then told to “get out of the building and talk to customers.” For many, it is an embarrassing dressing down that they never forget. What follows are furiously paced weeks in which they interview dozens of customers and discover, much to their surprise, that their idea is a nonstarter. It’s a bit disappointing, but once they realize they are on the wrong track, they can keep talking to people and often find a more promising application that wouldn’t otherwise have occurred to them. Ironically, much of the success of the I-Corps program is due to these early sessions. Make no mistake, every idea is wrong. Sometimes it is off by a little. Sometimes it is off by a lot. But it is always wrong. That’s why it’s crucial to explore and validate, so you can expose the flaws in your idea while also nailing down what you have right. Build the ecosystem Einstein never expected his abstract theories to find practical applications during his lifetime. It would take other developments, like the discovery of the transistor, to channel his ideas and those of others into solutions to actual problems. From there, entire industries needed to be built up to produce and distribute those solutions at scale. Ideas need ecosystems to make an impact on the world. That’s why Drucker was so puzzled about Watson’s enthusiasm for data processing. It just wasn’t on the radar of any of the other business leaders Drucker talked to. Computers, back in the 1920s, were largely a solution looking for a problem that no one thought they had. That’s why if you have an idea that’s truly new and different, you shouldn’t follow the usual management textbook advice to find the largest addressable market. By definition, large addressable markets are reasonably well served. What you want to do instead is identify a hair-on-fire use case : someone who has a problem they need solved so badly that they are willing to help you work through the inevitable glitches and snafus. That’s exactly what Watson did. He started out by courting scientific institutions and governments. IBM’s business took off in the 1930s when Congress established the Social Security Administration and IBM’s machines were perfectly suited to process the enormous amount of data needed to make the program work. That success enabled IBM to build a strong network of suppliers, partners, and customers. As its ecosystem grew, so did the company and it was able to refine and improve its ideas, resulting in a virtuous cycle that allowed the firm to dominate the computing ecosystem for half a century. Innovation is never a single event Economists have long been baffled by productivity growth, which rises and falls without any discernible rhyme or reason. The problem is that progress never follows a linear path. As I wrote in Mapping Innovation , innovation is never a single event, but a process of discovery, engineering, and transformation, and those three things hardly ever happen in the same place or with the same people. Researchers can toil for years—or even a lifetime—working to solve a single problem. Significant discoveries can lie in obscure journals for years, or decades, before they are engineered into practical solutions. It can then take decades more for those solutions to be adopted widely. People cling to old models not only out of habit and convenience, but also because they need to work with others who employ those same models. Systemwide change doesn’t come easy. That’s why ideas take time. Even after you’ve gone through the hard work of developing an idea that can impact the world, you need to identify a problem it can solve better than existing solutions. Then your solution needs to outperform alternatives by a wide enough margin that people are willing to abandon what they already know and trust. Most of all, you need to build a viable ecosystem of partners, suppliers, and customers to support your idea. We know from network science that power in an ecosystem lies not at the top, but emanates from the center. And you move toward the center by connecting out . That’s what separates great innovators from people who merely have ideas. They understand that no idea can stand on its own. Transformation is always a journey, never a destination. Having an idea is just the starting point. It gets you out the door. You have to find your own way after that.