Hertz is a nearly 100 year-old business valued at about $2 billion. Uber is an 8 year-old business valued at $50 billion. Marriott is a 90 year-old business, with hotels all over the world, and is valued at $39 billion, while AirBnB achieved a similar value in just 11 years and doesn’t own any rooms at all.
As Barry Libert, Megan Beck, and Jerry Wind point out in an article in Harvard Business Review, many businesses today are finding that they can achieve massive valuations by leveraging platforms based on “digital, intellectual, and relationship assets” rather than physical assets to “harness the power of networks.”
They’re not the only ones. A number of recent books, including The Network Imperative, by the aforementioned authors, Matchmakers and The Platform Revolution, tout the benefits on low-asset platform businesses over traditional “pipeline” businesses. Yet platforms are not a panacea and businesses based on them have a number of flaws that aren’t always obvious.
When engineers from Xerox PARC showed off their revolutionary new personal computer, the Alto, at the company’s global conference in 1977, senior executives weren’t particularly impressed. It just didn’t seem to be relevant to their jobs or their business. Their wives, however, were transfixed.
The reason for the disparity was that the executives saw a tool to automate secretarial work, which they considered to be a low value activity. The wives — many of whom had been secretaries — saw an entirely new world of possibility and, when Steve Jobs built the Macintosh based on the Alto, everyone else saw it too.
It’s easy to shake our heads and laugh at those shortsighted executives of the past, but we’d do ourselves a much greater service by realizing that we are not that different. The truth is that the next big thing always starts out looking like nothing at all, so it’s hard to grasp its implications early on. That’s essentially where we are today with the shift from bits to atoms.
Nobody sets out to be biased, but it’s harder to avoid than you would think. Wikipedia lists over 100 documented biases from authority bias and confirmation bias to the Semmelweis effect, we have an enormous tendency to let things other than the facts to affect our judgments. We all, as much as we hate to admit it, are vulnerable.
Machines, even virtual ones, have biases too. They are designed, necessarily, to favor some kinds of data over others. Unfortunately, we rarely question the judgments of mathematical models and, in many cases, their biases can pervade and distort operational reality, creating unintended consequences that are hard to undo.
What makes data bias so damaging is that we are mostly unaware of it. We assume that data and analytics are objective, but that’s almost never the case. Our machines are, for better or worse, extensions of ourselves and inherit our subjective judgments. As data and analytics become a core component of our decision making, we need to be far more careful.
“The biggest change you are going to see over the next year is that we want to bring our toy stores to life,” newly minted Toys R Us CEO Dave Brandon told a reporter a little over a year ago. “I want kids to be dragging their parents to our stores because they want to see what’s going on at Toys R Us this weekend.”
The sentiment seems eerily similar to former Blockbuster CEO Jim Keyes’ “Rock the Block” strategy and his assertion that “As long as we change the product assortment to meet the changing needs of the customer, our stores will remain relevant.” Much like Blockbuster, Toys R Us recently filed for bankruptcy.
When a business gets into trouble, the first impulse is often to improve operations. That can be a good idea, because improving business fundamentals can improve performance. Yet it also fails to take into account that there is a essential trade-off between optimization and innovation. To beat disruption, you need to explore and experiment to find something new.
In the late 1960s and early 70s, the first computer-aided design (CAD) software packages began to appear. Initially, they were mostly used for high-end engineering tasks, but as they got cheaper and simpler to use, they became a basic tool to automate the work of engineers and architects.
According to a certain logic, with so much of the heavy work being shifted to machines, a lot of engineers and architects must have been put out of work, but in fact just the opposite happened. There are far more of them today than 20 years ago and employment in the sector is supposed to grow another 7% by 2024.
Still, while the dystopian visions of robots taking our jobs are almost certainly overblown, Josh Sutton, Global Head, Data & Artificial Intelligence at Publicis.Sapient, sees significant disruption ahead. Unlike the fairly narrow effect of CAD software, AI will transform every industry and not every organization will be able to make the shift. The time to prepare is now.
At a recent NFL meeting about the anthem protests, Houston Texans owner Robert McNair warned his fellow owners that the league should avoid having “inmates running the prison.” Besides mangling the common phrase about “inmates running the asylum,” the racial undertones of the comment caused an uproar.
McNair quickly apologized and explained that he wasn’t referring to players, but league staff who he felt were making decisions without adequately consulting owners. Still, leaving political and moral issues aside, McNair’s comment raises important issues about governance in an increasingly complex world.
As Moisés Naím pointed out in The End of Power, today “power is easier to get but harder to use or keep.” So leaders are faced with a significant challenge. How to guide and shape an organization in an age of diminished power? The answer, unfortunately for McNair, is to acknowledge that the inmates really do run the asylum and leverage new sources of power.
The Gartner Hype Cycle shows a remarkably consistent pattern. A new technology is first ignored, then begins to show promise and expectations get inflated beyond any realistic assessment of value. That leads to disillusionment and the technology is almost forgotten until, some years later, it begins to make a true competitive impact.
What makes the Hype Cycle so pervasive is that it is, essentially, a pattern based on our obsession with patterns and stories, which is so universal that there is a whole branch of mathematics devoted to it. Our love of patterns is so great, in fact, that once we notice one we are often unable to disregard it.
The concept isn’t limited to the technologies Gartner follows. At any given time there are a variety of trends and business ideas getting hyped. That’s a problem because an enormous amount of time and energy is wasted when a trend is at maximum hype. Right now there are three major trends you need to watch out for if you don’t want to get caught in the cycle.
Every leader tries to keep things simple and predictable. You hire good people, treat them well, give them clear objectives and do your best to stay out of their way. If you do your homework, plan things well and your people execute efficiently, everything should go off without a hitch. Or so the thinking goes.
Yet reality often intrudes on even the best laid plans. Technology evolves, customer tastes change and competitors release new offerings. Before you know it, your simple model becomes dizzyingly complex and your organization is struggling to coordinate a response to a rapidly changing marketplace.
The truth is that we need to manage for complexity, not simplicity and many organizations are poorly fit to adapt. The answer does not lie in better planning or execution, but greater empowerment. We need to shift our organizations from hierarchies to networks and learn how to facilitate horizontal connections across the enterprise at an operational cadence.
A recent McKinsey report found that while 84% of corporate executives think that innovation is key to achieving growth objectives, only 6% are satisfied with the innovation performance of their firm. That’s quite a mismatch and it’s hard to imagine that a success rate that low would be tolerated in any other business function.
One reason for the paltry performance is that while other business areas, like marketing or finance, are considered to be core functions, innovation is often considered to be something that’s “nice to have” rather than essential. Yet another more pervasive reason is that senior executives are trained as operators, not innovators.
There’s a fundamental conflict between innovation and optimizing an existing operation. While the execution of a conventional strategy lends itself to linear progress and clear benchmarks, innovation often proceeds by s-curves, moving at a slow crawl until it explodes at an exponential rate. To close the gap, we need to treat innovation differently than we do normal operations. Here are four things that leaders need to do to close the gap.
On a recent episode of Last Week Tonight, John Oliver pointed out the dangers of corporate consolidation. In a variety of industries today, ranging from airlines to healthcare to even buying a coffin for a funeral, a handful of major players dominate, which allows them to raise prices and restrict consumer choice.
Anybody who has flown on an airplane in recent years knows what he’s talking about. The once reeling industry now charges more and delivers less, but is reaping record profits, despite its horrific service. As Oliver pointed out, United posted strong results even after its notorious passenger dragging scandal.
Clearly, we have a problem with antitrust regulation and consumer protection, but corporate consolidation is more than an example of corporate greed, it is also an indication of industry weakness. Growing industries generally don’t consolidate and, by restricting competition, firms in oligopoly markets often hasten their own disruption and demise.
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