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2019 was a big year for me personally. I finally published my book, Cascades, a project I had been working on for 15 years, about how to create transformational change.
The book has its roots in my experiences in Ukraine’s Orange Revolution, where I first noticed the forces behind ideas that spread.
The response has been overwhelming! Reader response has been off the charts and, even better, as we’ve begun training teams in the Cascades process for driving transformational change we’ve seen first-hand how much of an impact it can have in the real world. It’s just so gratifying when you can see your work having a real impact!
Most of all, I think that 2019 will be seen as a pivotal year. As the digital revolution winds down and new technologies such as synthetic biology, materials science and AI rise to the fore, we’re going to see unprecedented challenges and opportunities over the next decade. These were the things I wrote about over the past year. Here are my top articles for 2019.
We tend to think that ideas succeed or fail on their own merits, but the story of Ignaz Semmelweis shows why that’s not true. Semmelweis, who first showed that hand washing could dramatically decrease the incidence of infection in hospitals, found that not only did his idea fail to catch on, but he himself was branded as a quack!
The problem is that a new idea has to replace an old one and the status quo has inertia on its side. Even those who are easily convinced have to convince those around them and those, in turn, need to convince others still. It takes a long chain of influence to change of the zeitgeist. That’s why to truly make an impact, you need small groups, loosely connected, but united by a shared purpose.
Over the past four decades, change management has evolved from a nascent idea to a thriving industry. Organizations that want to drive change are encouraged to “create a sense of urgency” around change, design and implement a plan, generate quick, short term wins and then accelerate and sustain the change.
Unfortunately, these efforts are rarely successful. The problem isn’t that for any significant change, there are going to people who won’t like it and who will work to undermine it. So instead of trying to convince people who don’t want to change, your efforts are much better spent on empowering people who are already enthusiastic about it.
We tend to see the history of technology through the lens of inventions like the steam engine, electricity, internal combustion, the computer and so on. Yet when we take a closer look, we find that the impact from those inventions didn’t come until decades later. In fact, it usually takes about 30 years to go from an initial discovery to a significant impact in the real world.
The reason is that inventions require ecosystems of technicians, practitioners, distributors, engineers and secondary inventions to change the world. Consider the automobile, which was invented in the 1880s, but needed roads, gas stations, mechanics, car dealers and so on to change the way we lived. That didn’t really form until the 1920s.
Yet even bigger changes came later, when cars enabled a revolution in retail and distribution. Factories moved from the north, where they were close to customers, to the south where land and labor were cheaper. The corner store gave way to supermarkets and, eventually, shopping malls. People moved from the city to the suburbs. Almost every facet of life changed.
When IBM first debuted Watson on the game show Jeopardy! in 2011 it was unlike anything anyone had ever seen before. It seemed like sophisticated systems like Watson would be the way of the future, with artificial intelligences collaborating with humans as if they were ultra-smart colleagues.
What’s emerged is altogether different. Instead of a competition among intelligent systems, we have an ecosystem of modular components, including data assets, hardware and software components and pre-trained models that can perform highly specialized tasks, such as automating supply chains in specific industries.
Traditionally, materials science has been an obscure field, in some ways almost a cottage industry. To discover a new material was a tiresome process of mostly trial and error. Researchers would often have to test thousands of candidates before they found something useful. It was a slow and extremely expensive process.
Today, however, that is quickly changing. Through the use of high performance computing simulations as well as clever machine learning techniques, there is a materials revolution underway—in some cases improving efficiency by 200-300 times— which has the potential to drive advancement in everything from manufacturing to renewable energy.
Today, we live in an intensely digital world. In fact, it often seems as if the word “digital” has become synonymous with innovation itself. Firms, in order to be competitive, strive to implement the latest digital solutions in order to adapt to what has become an inherently disruptive business environment.
Yet amid all this disruption, the digital revolution is actually ending. The end of Moore’s law means that the advancement in the underlying technology has begun to slow and will soon come to a complete halt. That will change how we need to compete. It will no longer be enough to adapt quickly, we will need to learn to prepare for a very different era of innovation.
Humans love patterns, so it shouldn’t be surprising that we are natural trend-watchers. We expect the future to be a bigger and faster version of the past, so we plan, build strategy and execute largely based on that assumption. Most of the time, that works pretty well, but when we hit an inflection point, the results can be disastrous.
Today, we are in the midst of three such inflection points in energy, synthetic biology and computing. The impact of any one of these would be hard to predict, but the three taken together is likely to be highly disruptive. The future is going to be very different than anything we’ve ever seen before.
We tend to think about innovation as coming up with better answers and, of course, that’s part of it. However, far more important is to learn to ask better questions. While answers tend to close off possibilities, good questions open them up and can take us in completely new directions.
This article features four of my favorite questions to ask about innovation that you’ll want to put into practice right away. So take a current project or one that you’re planning, apply them and see how they take you in new directions. You’ll be amazed how effective they are.
It’s become increasingly clear that the key to competitive advantage in the 21st century is not dominating value chains, but leveraging ecosystems. The better you are able to connect to ecosystems of talent, technology and information, the better you will be able to innovate, adapt and bring products to market.
Unfortunately, too much of the talk about ecosystems is nebulous and vague. It’s all too easy to invoke networks and ecosystems, but much harder to build an explicit strategy around them. This article helps show the way.
Great transformations eventually take on an air of inevitability. We look back at transformational leaders like Gandhi, Mandela or even someone like Lou Gerstner as destined for greatness. Yet one of the most interesting things I learned while I was researching Cascades was that they succeeded only after they learned to overcome early failures.
The truth is that to create truly revolutionary change, you have to put significant efforts towards early groundwork, such as cultural change, for which there is little or no immediate benefit. However, failing to create a foundation will make sustainable change nearly impossible to achieve. That’s why you need to treat transformation as a journey and not a destination.
So those are my top posts from 2019. Thanks again for all your support this year. I’m taking the next few weeks off, but will be back on Sunday, January 4th with my future trend for 2020.
Have a safe and happy New Year!
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