I recently wrote an article about Tribune Publishing’s reincarnation as Tronc and the poorly thought out video that the company put out describing its efforts. It seemed to be well received and many people, even those who work at Tronc, seemed to think I had gotten it right.
My basic point was that the notion that you can transform a failing media company — or any company in any industry for that matter — by infusing it with data and algorithms is terribly misguided. I stand by that analysis, but I also realize that rather than tell publishers what they should do, I merely spelled out what won’t work.
I also think my article gave Tronc’s management short shrift. The fact is that they are trying to revive a storied icon of American journalism and should be given some credit. As a former publishing CEO who managed a number of digital and print brands, I know how difficult that can be. So here are four things that publishers need to know to compete in the digital age.
We tend to think of innovation as a moment of epiphany followed by an onward march toward disruption. Sure, there are always some twists and turns along the way, but fearless entrepreneurs seem to have no problem adapting, iterating and pivoting their way to incredible success.
That makes for inspiring stories, but the truth is that innovation more often follows a long and twisted path. Chief among the difficulties is the wide chasm—often known as the Valley of Death—that separates the discovery of important new insights and the development of a viable product. Many promising ideas never make it through.
That’s one of the things that makes James Allison’s development of Cancer Immunotherapy so inspiring. Not only is it achieving miraculous results, curing people with terminal cancer who once would have had no hope, but has led others to pursue similar research. The story also shows how hard it is to bring a major discovery to market, even if it’s a miracle cure.
A few weeks ago, my friend and former colleague Vitaly Sych reached out and asked me to write an essay about “change in America” for the Ukrainian newsmagazine, “Novoe Vremya.” It is to be published in a supplement to the magazine published in cooperation with the American Embassy in Kyiv this week.
Ukrainians are, for a variety of reasons, intensely curious about the US. They, like most nations, are interested in knowing more about the most powerful country in the world. Our influence in their affairs has grown since the Euromaidan protests and the conflict with Russia that followed. Much of their fate rests in our hands.
So while we are currently viewed very favorably by the former Soviet Republic — by a margin of 69-22 according to Pew — and they welcome our support for their independence, there remains an element of confusion surrounding us, our values and our motives. I wrote this essay for a Ukrainian audience, but I’d also like to share it here on July 4th.
After nearly seven years writing this blog, I’ve decided to start work on a book about innovation. While there is certainly no shortage of great innovation books on the market, I feel strongly that the time has come for a different approach and I think there is much I can add to the discussion.
The problem, as I see it, is that most of the literature tends to be narrowly focused on a particular approach, leaning heavily on either a single organization’s experience or a limited set of case studies. These can be very helpful if they happen to describe a problem you’re trying to solve, but absolutely useless when they don’t
That’s why I’m writing this book, to give managers a more complete account of how to match problems with solutions. To do so, I’ve cast a wide net, talking to a diverse array of executives and researchers about their work. There have also been many books that I’ve found helpful. So for this summer’s list, I’d like to highlight 17 books that I think innovators should read.
Tribune Publishing, a storied icon of American journalism, recently renamed itself Tronc and released a video to show off a new “content optimization platform,” that its Chief Technology Officer, Malcolm CasSelle, claims will be “the key to making our content really valuable to the broadest possible audience” through the use of machine learning.
As a marketing ploy the move clearly failed. Instead of debuting a new tech-savvy firm that would, in the words of Chief Digital Officer Anne Vasquez, be like “having a tech startup culture meet a legacy corporate culture,” it came off as buzzword-laden and naive. The Internet positively erupted with derision.
Yet what I find even more disturbing than the style is the substance. The notion that you can transform a failing media company—or any company in any industry for that matter— by infusing it with data and algorithms is terribly misguided. While technology can certainly improve performance, the idea that it can replace a sound strategy is a dangerous delusion.
“Managing without soul has become an epidemic in society. Many managers these days seem to specialize in killing cultures, at the expense of human engagement.” That’s what management guru Henry Mintzberg recently wrote about the current state of corporate culture on his blog.
Too make matters even worse, he points out that many executives are actually trained to operate that way at MBA programs. While business schools teach technocratic skills, such as finance, optimization and resource management, they do very little in the way of strengthening souls.
Sadly, corporate culture discussions usually devolve into buzzwords, like “authenticity.” And while Mintzberg says that after a half century of studying organizations he can get a sense of an one’s soul “in an instant,” he offers little guidance how to develop one. The truth is that you don’t find your soul inside yourself, but by finding your place in the world.
A data scientist, it’s been said, is a statistician who works in Silicon Valley, which is another way of saying that the term has attained true buzzword status. The potential to be unlocked is undeniably, but so far, there has been no shortage of disappointment and frustration. Truth be told, the steak hasn’t always lived up to the sizzle.
The problem hasn’t been with big data itself, but with the practicalities of technology. Simply put, we design systems to perform particular tasks and only later realize that we want them to do more than we originally realized. That’s when it becomes clear that our systems are hopelessly incompatible.
In a nutshell, that’s the problem IBM is now trying to fix. By creating a universal platform, which it calls the Data Science Experience, it hopes to integrate data trapped in separate protocols and incompatible systems. This will not only enable more advanced analytics, it will help us to reimagine how we manage our organizations and compete in the marketplace.
In 1882, just three years after he had almost literally shocked the world with his revolutionary lighting system, Thomas Edison opened his Pearl Street Station, the first commercial electrical distribution plant in the United States. By 1884 it was already servicing over 500 homes.
Up till that point, electric light was mostly a curiosity. While a few of the mighty elite could afford to install generators in their homes—J.P.Morgan was one of the very first—it was out of the reach of most people. Electrical transmission changed all that and in the ensuing years much of the country wired up.
Still, as Paul David explained in his paper, The Dynamo and the Computer, electricity didn’t have a measurable impact on the economy until the early 1920’s—40 years later, when we finally knew enough about the new technology and learned how to unleash its potential. The story of how that happened shows why it takes more than a single idea to change the world.
The presidential run of Bernie Sanders has often been referred to as a movement rather than a campaign and it certainly has all the trappings—a distinctive ideology, devoted followers and large crowds. Many believe that the Sanders movement will far outlive the current cycle and shape the political future.
To state the obvious, as a candidate Sanders did not succeed—by any objective Hillary Clinton trounced him—but I can see how the idea of his movement living on would salve some open wounds among his followers. To them, Bernie Sanders was always more than a candidate, he was a living embodiment of a shared purpose.
Yet I would argue that a much more likely scenario is that we’ll soon be forgetting Bernie Sanders and not because he failed as a politician, but because of how he failed as a leader of his movement, all too often choosing to attack rather than engage. Hopefully, in the years to come, his failure will become a cautionary tale to those who seek to effect change in society.
Steve Jobs built—and then revived—Apple by fusing technology with design. IBM has remained a top player in its industry for roughly a century by investing in research that is often a decade ahead of its time. Facebook “moves fast and maintains a stable infrastructure” (but apparently doesn’t break things anymore).
Each of these companies, in its own way, is a superior innovator. But what makes Google (now officially known as Alphabet) different is that it doesn’t rely on any one strategy, but deploys a number of them to create an intricate—but powerful—innovation ecosystem that seems to roll out innovations by the dozens.
The company is, of course, a massive enterprise, with $75 billion in revenues, over 60,000 employees and a dizzying array of products, from the core search business and the android operating system to nascent businesses like autonomous cars. So to better understand how Google innovates, I took a look at close look what it’s doing in one area: Deep Learning.