Many say that coding is the new literacy. Kids are encouraged to learn programming in school and take coding courses online. In that famous scene in The Graduate Dustin Hoffman’s character was encouraged by a family friend to go into plastics. If it were shot today, it would have probably been computer code.
This isn’t actually that new. I remember first being taught how to code in middle school in the early 80s in BASIC (a mostly defunct language now). Yet even today, coding is far from an essential skill. In fact, with the rise of no-code platforms, there is a strong argument to be made that code is becoming less important.
Don’t get me wrong, there’s still plenty of coding to be done on the back end and programming is certainly a perfectly reasonable thing to learn. However, there’s no reason people need to learn it to have a successful, productive career. On the other hand writing, as well as other communication skills, will only become more important in the decades to com.
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Summer is finally here! Time to break out the sunblock, beach towels and get some time to relax. If you’re anything like me, it’s also a time to get some serious reading done. There’s just something about laying out in the sun that makes the pages turn faster and helps information to sink in.
This summer, I have a feeling that change will be on a lot of people’s minds and not just political change. Revolutions in technologies, from clean energy to genomics to artificial intelligence, are reshaping the world as we know it. The disruptions over the next decade will likely dwarf those in the last.
In some ways, the forces of change today are unprecedented. We’ve likely never had so many powerful forces swirling around at the same time. You would have to go back to the turn of the 20th century to find anything remotely similar. However, we can learn a lot from those who came before us. So I offer you these 17 books that will help you chart a path forward.
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Ever since Eric Reis published his bestselling book, The Lean Startup, the idea of a minimum viable product (MVP) has captured the imagination of entrepreneurs and product developers everywhere. The idea of testing products faster and cheaper has an intuitive logic that simply can’t be denied.
Yet what is often missed is that a minimum viable product isn’t merely a stripped down version of a prototype. It is a method to test assumptions and that’s something very different. A single product often has multiple MVPs, because any product development effort is based on multiple assumptions.
Developing an MVP isn’t just about moving faster and cheaper, but also minimizing risk. In order to test assumptions, you first need to identify them and that’s a soul searching process. You have to take a hard look at what you believe, why you believe it and how those ideas can be evaluated. Essentially, MVP’s work because they force you to do the hard thinking early.
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I recently bought a book that I was really excited about. It’s one of those books that’s created a lot of buzz and it was highly recommended by someone I respect. The author’s pedigree included Harvard, Stanford, McKinsey and a career as a successful entrepreneur and CEO.
Yet about halfway in I noticed that he was choosing facts to fit his story and ignoring critical truths that would indicate otherwise, much like Malcolm Gladwell’s often does in his books. Once I noticed a few of these glaring oversights I found myself not being able to fully trust anything the author wrote and set the book aside.
Stories are important and facts matter. When we begin to believe in false stories, we begin to make decisions based on them. When these decisions go awry, we’re likely to blame other factors, such as ourselves, those around us or other elements of context and not the false story. That’s how many businesses fail. They make decisions based on the wrong stories.
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In an age of disruption, everyone has to adapt eventually. However, the typical organization is ill-suited to change direction. Managers spend years—and sometimes decades—working to optimize their operations to deliver specific outcomes and that can make an organization rigid if the face of a change in the basis of competition.
So it shouldn’t be surprising that the idea of a networked organizations have come into vogue. While hierarchies tend to be rigid, networks are highly adaptable and almost infinitely scalable. Unfortunately, popular organizational schemes such as matrixed management and Holacracy have had mixed results, at best.
The truth is that networks have little to do with an organization chart and much more to do with how informal connections form in your organization, especially among lower-level employees. In fact, coming up with a complex scheme is likely to do little more than cause a lot of needless confusion. Here are the myths you need to avoid.
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In the 1970s and 80s, business investment in computer technology were increasing by more than 20% per year. Strangely though, productivity growth had decreased during the same period. Economists found this turn of events so strange that they called it the productivity paradox to underline their confusion.
Productivity growth would take off in the late 1990s, but then mysteriously drop again during the mid-aughts. At each juncture, experts would debate whether digital technology produced real value or if it was all merely a mirage. The debate would continue even as industry after industry was disrupted.
Today, that debate is over, but a new one is likely to begin over artificial intelligence. Much like in the early 1970s, we have increasing investment in a new technology, diminished productivity growth and “experts” predicting massive worker displacement . Yet now we have history and experience to guide us and can avoid making the same mistakes.
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We live in an age in which change has become the only constant. So it’s not surprising that change management models have become popular. Executives are urged to develop a plan to communicate the need for change, create a sense of urgency and then drive the process through to completion.
Unfortunately, the vast majority of these efforts fail and it’s not hard to see why. Anybody who’s ever been married or had kids knows first-hand how difficult it can be to convince even a single person of something. Any effort to persuade hundreds, if not thousands, of people through some kind of mass effort is setting the bar pretty high.
However, as I explain in Cascades, what you can do is help them convince each other by changing the dynamic so that people enthusiastic about change can influence other (slightly less) enthusiastic people. The truth is that small groups, loosely connected, but united by a shared purpose drive transformational change. So that’s where you need to start.
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In 1928, Alexander Fleming arrived at his lab to find that a mysterious mold had contaminated his Petri dishes and was eradicating the bacteria colonies he was trying to grow. Intrigued, he decided to study the mold. That’s how Fleming came to be known as the discoverer of penicillin.
Fleming’s story is one that is told and retold because it reinforces so much about what we love about innovation. A brilliant mind meets a pivotal moment of epiphany and—Eureka!— the world is forever changed. Unfortunately, that’s not really how things work. It wasn’t true in Fleming’s case and it won’t work for you.
The truth is that innovation is never a single event, but a process of discovery, engineering and transformation, which is why penicillin didn’t become commercially available until 1945 (and the drug was actually a different strain of the mold than Fleming had discovered). We need to stop searching for Eureka moments and get busy with the real work of innovating.
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In 2012, Shaun Wilson and Michael Brett were designing aerospace simulation software. On one particular project, Lockheed Martin’s Chief Scientist, Dr. Ned Allen, mentioned that it had just acquired an early quantum computer from D-Wave Systems, which he thought would help with computational work.
They were impressed. “We found that it was an incredibly promising technology, Brett told me. “We could see the potential to one day do things that just weren’t possible with digital computers, even the high performance systems we were working with.” It was something unlike anything they had ever seen.
“With big data taking off, we saw the need for high performance predictive analytics and thought quantum computing could be a real differentiator. That was the opportunity that led us to think about starting a company,” Brett remembers. Today, the company they founded, QxBranch, is becoming a key player in the race to develop practical quantum applications.
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Peter Thiel likes to point out that we wanted flying cars, but got 140 characters instead. He’s only partly right. For decades futuristic visions showed everyday families zipping around in flying cars and it’s true that even today we’re still stuck on the ground. Yet that’s not because we’re unable to build one. In fact the first was invented in 1934.
The problem is not so much with engineering, but economics, safety and convenience. We could build a flying car if we wanted to, but to make one that can compete with regular cars is another matter entirely. Besides, in many ways, 140 characters are better than a flying car. Cars only let us travel around town, the Internet helps us span the globe.
That has created far more value than a flying car ever could. We often fail to predict the future accurately because we don’t account for our capacity to surprise ourselves, to see new possibilities and take new directions. We interact with each other, collaborate and change our priorities. The future that we predict is never as exciting as the one we eventually create.
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