One of the most common questions I get asked by senior managers is “How can we find more innovative people?” I know the type they have in mind. Someone energetic and dynamic, full of ideas and able to present them powerfully. It seems like everybody these days is looking for an early version of Steve Jobs.
Yet in researching my book, Mapping Innovation, I found that most great innovators were nothing like the mercurial stereotype. In fact, almost all of them were kind, generous and interested in what I was doing. Many were soft spoken and modest. You would notice very few of them in a crowded room.
So the simplest answer is that you need to start by empowering the people already in your organization. But to do that, you need to take responsibility for creating an environment in which your people can thrive. That’s no simple task and most managers have difficulty with it. Nevertheless, by following a few simple principles you can make a huge difference.
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Ten years ago hardly anyone had a smartphone. Social media was in its infancy. Artificial intelligence was still science fiction. Yet today all of those things are mature technologies that have become an integral part of everyday life. Anywhere you go you see people using all of them as a matter of habit.
It’s become conventional wisdom to look at these developments and say that technology is accelerating. It certainly seems that way. Nevertheless, look a little closer and it becomes clear that’s not really true. Buy a computer or smartphone today and it has nearly identical technical specifications to one that came out five years ago.
The truth is that every major technology has a similar life cycle called an S-curve. It emerges weak, buggy and flawed. Adoption is slow. In time, it hits its stride and enters a period of rapid growth until it hits maturity and an inevitable slowdown. That’s what’s happening now with digital technology and we can expect many areas to slow down in the years to come.
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In the early 1990s, established businesses were blindsided by the disruptive force of the Internet. Even those who invested heavily in IT infrastructure soon found that they had difficulty competing with nimble new upstarts who could deploy web based applications at blinding speed.
It was with this in mind that IBM launched its e-business initiative in 1996. Although considered by many at the time to be an aging dinosaur itself — the firm was close to bankruptcy three years earlier — it was able to leverage its expertise in legacy systems to transform business processes and prepare its customers for the Internet age.
Today a similar tidal wave of disruption is sweeping through the corporate world — artificial intelligence — and, once again, IBM sees a big opportunity. Much like in the early days of the Internet, there is huge value to be unlocked, but legacy systems are not set up to leverage it. It’s not enough to simply apply algorithms, you need to prepare your business for a new age.
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In Eric Ries’s bestselling book, The Startup Way, the Silicon Valley entrepreneur explains how he helped lead General Electric’s transformation from a stodgy industrial era dinosaur into a lean, entrepreneurial enterprise. Yet strangely, as Steve Blank points out in Harvard Business Review, the effort ended up with the ousting of GE’s CEO for underperformance.
Why did such a seemingly promising initiative turn out to be such a tragic failure? To be honest, I have no idea. Maybe the cultural strain of “lean startup” thinking caused the company to take its eye off the ball. Or maybe it was simply a matter of short-term thinking by activist investors. Or maybe something else entirely.
On a deeper level, running a significant enterprise is incredibly complex and, to be successful, a lot of things need to go right. There are no silver bullets. Unfortunately, that doesn’t stop pundits and consultants from offering them. As Blank also points out in his article, Ries’s ideas weren’t the problem at GE, but neither did they address obvious issues.
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By the early 20th century, the world’s great mathematicians knew they had a big problem. The very foundations of logic, held sacred since the time of Aristotle, were under siege after the discovery of troubling paradoxes by Cantor, Frege and Russell. It was unclear whether things could ever be set aright.
It was against this backdrop that David Hilbert, the most prominent mathematician of the age, created a program to get things back on track. Unfortunately, just the opposite happened. First came Kurt Gödel’s famous incompleteness theorems and then the work of Alan Turing. Logic, as everyone knew it, was dead.
Nevertheless, out of the ashes of Aristotle’s logic arose the foundations of modern computing. As it turns out, solving a fundamental problem, even if the solution isn’t what you thought you wanted, can unlock enormous value. What’s more, in every field and industry, there are countless problems just waiting to be solved. Here’s how to go about working them out.
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Every discussion about artificial intelligence seems to alternate between utopia and dystopia. Some believe that the productivity unleashed through automation will lift up all of society, creating a world of superabundance and more meaningful work, while others see robots taking our jobs and an acceleration of trends favoring capital over labor.
In fact, in an article in Harvard Business Review, Accenture’s Mark Knickrehm describes five distinct schools of thought, ranging from both extremes to various shades of gray in between. He suggests that leaders need to reinvent operating models, redefine jobs and include employees in the process of transformation.
Yet that’s easier said than done. Smart leaders know that even small, subtle changes can sometimes result in a backlash. Preparing your organization to leverage artificial intelligence has can be especially problematic because the most profound problems are intensely human. Gandhi, although he was no tech enthusiast, can be a good guide on where to start.
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Elon Musk is often hailed as a visionary, and rightly so. Tesla, not to mention his other ventures, has the mark of a business that can truly change the world. When he co-founded the company in 2003, electric cars seemed like a pipe dream. Today, however, just about every major carmaker is investing in the technology.
The Tesla narrative has become so well accepted that we rarely stop to think how easily it could have all gone wrong. In 2007, Shai Agassi founded Better Place with an even more expansive vision for electric cars. Yet as Brian Blum explains in his new book, Totaled, that vision led to a series of missteps that resulted in a billion dollar bankruptcy.
There are, of course, a number of reasons for a failure so colossal, including Agassi’s mercurial personality, but most of Better Place’s problems stemmed from a single mistake. To truly change the world, you need to build for the few, not the many. Find a customer that wants or needs your product so badly they almost literally have their hair on fire.
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When Steve Jobs first came up with the idea for the iPod, it wasn’t actually a machine he had in mind, but “a thousand songs in my pocket.” It was, at the time, an impossible idea, because hard drives of that capacity and size just didn’t exist. In fairly short order though, the technology caught up to the vision.
That kind of singular focus and drive helps explain Jobs’ incredible success, but what about his failures? The Lisa, a precursor to the Macintosh, flopped. So did his first venture after Apple, NeXT Computer. Even at the height of Apple’s dominance, there were missteps such as iAds. Apple TV still hasn’t really gained traction.
“It’s not what you don’t know that kills you,” Mark Twain famously said, “it’s what you know for sure that ain’t true” and that’s the real innovator’s dilemma. Innovation, necessarily, is about the future, but all we can really know is about the past and some of the present. It’s always a balancing act of staying true to your vision and re-examining your assumptions.
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Today’s problems can sometimes seem almost insurmountable. Although we’ve made strong progress over the last decade in many areas such as violence, extreme poverty and global health, issues like climate change, income inequality and a rise in populist authoritarianism still loom large.
Education could be a possible bulwark against many of these problems, providing a greater supply of skilled people to solve them, but here again we have issues. The US routinely scores poorly in international PISA tests and the OECD recently found that the US is falling behind other countries in college graduates.
100Kin10 is a non-profit trying to help turn things around. It realized that it’s not enough to simply deal with surface problems, you need to get at root causes, but those can be devilishly hard to identify. Nevertheless, they found that a productivity hack called the 5 Whys from the famed Toyota Production System was able to help point the way forward.
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It often seems easy to know when the next big thing is upon us. Someone like Steve Jobs or Elon Musk stands on stage and tells us what is being launched next. The business press gets excited, pundits swoon and a thousand imitators are created. Before long an ecosystem develops and the world is forever changed.
In reality though, things are much murkier than that. Innovation is a process of discovery, engineering and transformation and it is only the last part that is visible to most of us. The seeds of a revolution start long before, in obscure labs and at conferences with high priests presenting papers written in arcane vernacular.
Since the 1950s, the engine that’s driven new knowledge to, as Vannevar Bush put it, “turn the wheels of private and public enterprise,” has been the US government. Unfortunately, moving new discoveries out of federal labs has often been a slow and cumbersome process, but a new model holds promise for greatly accelerating breakthrough innovation.
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