Tradition embraces stability. Time honored principles get that way because they have strong track records of success. The tried and true, extrapolated into the future, often looks like a sure thing, while deviating from historical norms can look downright foolish.
Yet the funny thing about the future is that there’s no guarantee that it will look like the past. Contexts change and when they do, old rules no longer apply. Following them blindly does not honor the past, but diminishes it by confusing fealty with wisdom.
Since 1960, the average lifespan of a company on the S&P 500 has fallen from more than 60 years to less than 20. The power of technology will increase as much in the next 18 months as it has in the last 30 years. Clearly, technology cycles have begun to outpace planning cycles. We need to learn to manage not for stability, but for disruption.
Nate Silver doesn’t look very threatening. With his spindly frame and eyeglasses, he looks more like the prototypical 98 pound weakling than an emergent media juggernaut, but he’s got a lot of people running scared nonetheless.
Whereas other pundits earn their living through a special blend of insights and access to inside sources, Silver has neither. In fact, he bases his analysis on data that, in most cases, everyone else has access to yet he’s somehow able to prove experts wrong.
And that’s exactly what makes Silver so scary, not for what he does, but what he represents—the primacy of data and analysis over personal experience. If Silver, a relative neophyte with no substantial experience on the political beat or in the halls of power can outperform respected pundits, then what does that say about the rest of us?
The future isn’t what we thought it would be. We don’t walk around in silver suits, travel to colonies on Mars or drive in flying cars. Instead, we dress casual, take selfies and communicate in 140 characters.
Yet in many ways, we’re much better off than we imagined. Rather than a Mad Max dystopia of war, famine and disease we are safer, richer and healthier than we’ve ever been. As I’ve argued before, in a very real sense 140 characters are better than a flying car.
That’s the funny thing about the future. It’s never as fantastic as we hope nor as horrible as we fear. The one thing that’s for sure is that times will change and we will have to adapt. While there is no way of knowing exactly how that change will play out, we can identify trends, make common sense judgments about where they lead and prepare for them.
The Obama administration had been preparing for years to launch its signature policy, the Affordable Care Act, otherwise known as Obamacare. With everything riding in the balance, the whole effort very nearly failed—because of a website.
Well, not a website exactly, but a dizzying array of servers, protocols and regulations. The technology behind the website needed to manage all of it in order to provide service to the public. On launch day, it fell flat.
That was embarrassing, but the problem goes far beyond health care. Virtually everything the government does these days, from drivers’ licenses to voter registration to retirement benefits, requires a robust technological platform that must overcome challenges specific to the public sector. Now, a team of technologists thinks they may have a solution.
Around the turn 20th century, Frederick Winslow Taylor introduced the practice of scientific management. He studied various tasks with a stopwatch, devised more efficient ways of getting them done and developed standards to improve productivity.
In Taylor’s world, there was truly a “right way” and a “wrong way” of doing things and managers were there to supervise. They ensured that rules were being followed, standards for work were being met and discipline was being enforced.
The rise of the knowledge economy brought a different kind of management. Instead of supervising, managers had to excel at choosing the right kind of work to be done and motivating employees. Now, as the information economy takes hold and creates pervasive change, managers will have to evolve once again. Those who don’t adapt, will not survive.
In the late 1960’s, minimills like Nucor started using a new process that could produce low grades of steel more efficiently than the big integrated steel makers. These, however, were the lowest margin products in the industry and didn’t seem much of a threat to the big guys.
In The Innovator’s Dilemma, Clayton Christensen describes what happened next. As minimill technology improved, it began producing higher grades of steel. The integrated mills migrated upward until, by the late 1980’s, they had forfeited much of their market.
We’ve seen the same dynamic play out time and time again across a variety of industries. Digital cameras, cloud based software, rental cars, education and a host of others. Yet now we’re starting to see it take hold in the high-brow market for professional services. It’s still in its early stages, but history—as well as economics—doesn’t favor the incumbents.
As the crisis in Ukraine continues to play out in Crimea—and possibly spread to Eastern Ukraine as well—it is not only conventional measures of power we should be paying attention to, but linkages.
It is, of course, Russia’s connections to a large segment of the Crimean population that Putin used as a pretext for his invasion. It was also fear of connections (ethnic Ukrainians to the mainland, Crimean Tatars to Turkey), which led him to shut down television stations and other channels of communication.
And it is through deepening and severing connections that the West intends to combat Putin’s aggression—by uniting with Western and Eastern European allies to apply sanctions that will deny Russia the economic and cultural ties it now relies on. Strategy is no longer a game of chess, because power no longer depends on nodes, but on networks.
Ever since 1962, when the first industrial robot was installed on an assembly line at a General Motors plant in New Jersey, machines have been replacing human workers. In the decades that came after, just about every industry became automated to a greater or lesser extent.
For the most part, we humans have adapted nicely. Robots could do only simple tasks, so by upgrading our skills through training and education, our living standards continued to rise. Yet more recently, that’s begun to change.
As Andrew McAfee and Erik Brynjolfsson point out in their new book, The Second Machine Age, machines are beginning to take over cognitive tasks and now algorithms are even doing the work of highly skilled professionals like doctors, lawyers and creative people. If you want to avoid being replaced by a robot these days, you better learn the right kind of skills.
In the 1950’s, Haloid Corporation thought it had a winning product. Through some clever engineering, it had created new technology that was leaps and bound better than anything that had come before it. The only problem was that nobody wanted to buy it.
Then the company’s president had an epiphany. If no one wanted to buy their copy machines, maybe some would be willing to lease? That, it turns out, was a multi-billion dollar idea and the company, now known as Xerox, became one of the world’s leading companies.
Isolated innovations are unlikely to make a significant impact on performance unless there is a commensurate change in how the enterprise operates. A new product, target market or revenue stream may move the needle slightly, but rarely more. To create meaningful change, we need to transform the business model. Here’s what you need to know:
A recent survey reported that the consulting industry raked in $39.3 billion in 2012 renting out their advice to the world’s most powerful firms. Yet still, a study by Innosight found that the average life on the S&P 500 has declined from 61 years in 1958 to only 18 today.
It makes you wonder what all those high-priced consultants are getting paid for. With all of their fancy charts and two-by-two matrices, are they really anything more than modern day witch doctors dispensing a high tech version of folk wisdom?
We’re about to find out now that Sandy Pentland is on the case. As one of the world’s top data scientists, he has developed a technique called reality mining that tracks human behavior through the use of a sociometer device he invented. He’s recently published a book called Social Physics that explains his research into what really works in business.
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, Clayton Christensen describes what happened next. As minimill technology improved, it began producing higher grades of steel. The integrated mills migrated upward until, by the late 1980’s, they had forfeited much of their market.
, machines are beginning to take over cognitive tasks and now algorithms are even doing the work of highly skilled professionals like 
that explains his research into what really works in business.
