I recently struck up a conversation with a hedge fund manager who told me his firm was focused heavily on mobility. I naively assumed he’d been betting on the rise of autonomous vehicles.
“No,” he said. “They’re just not ready for prime time. We’ve made a lot of money shorting them.”
His response is a good reminder for company leaders that, when it comes to emerging technologies, not every shiny new thing is going to be the next big thing.
Every decision maker now is facing a disorienting blizzard of news and opinions telling them to embrace new technology or risk falling into irrelevance. Many tell me they’ve never been this anxious and confused about which technologies to focus on.
Breathless Predictions Abound
The march of technology never stops but there are times when it seems to accelerate with an “everything everywhere all at once” intensity. In the past few years, we’ve seen the rise of concepts like the metaverse, web 3.0, blockchain, the internet of things, and virtual reality, all accompanied by breathless predictions of how they could transform our lives and the whole economy.
Lately, the emergence of vastly improved generative AI has triggered an avalanche of advice on how companies should be using machine-learning tools to change the way they do everything.
The truth is that some of these technologies will matter a lot to a business, and to others it won’t matter at all.
Recent history is littered with new developments that were heralded as transformative but subsequently fell flat. Remember a decade ago when curved-screen TVs were touted as a game-changer for home entertainment? I bet you don’t have one in your house. Crypto was supposed to transform the way we spend, bank, and invest, but so far, it’s done little beyond giving criminals a useful tool for moving money and con artists a way to fleece investors.
Overwhelmed with contradictory and often self-serving information? Here are the three most important lenses through which to evaluate the relevance of any new technology:
The Need Lens
Before asking whether a technology will change the world, ask if it will change the life of just one person. If it can’t clearly address one individual’s important need, it has no chance of succeeding on a bigger stage. Before becoming the global behemoth it is now, Facebook demonstrated its value among a few hundred students in Harvard dorm rooms.
Most of us gasped and instantly realized the benefit of multitouch screen technology when Steve Jobs zoomed in on a family photo in his demonstration of the first iPhone. The need was clear.
Contrast that to the doomed Google Glass, which failed to demonstrate any clear need that smartphones didn’t already meet – and made its wearers look pretty silly to boot. Google got ahead of itself by assuming the product would be useful for everyone before making sure that it was useful to anyone.
Companies fail the need lens when they take people for granted. Under CEO Bob Shapiro in the 1990s, Monsanto pushed GMO crops as a force for good that could transform health, the environment, and nutrition. The technology delivered but his vision foundered because he didn’t account for skeptical consumer attitudes to so-called Frankenfoods.
The Solution Lens
A new technology may meet a clear need, but still fall short if the total solution isn’t ready for prime time. For example, it’s easy to see how autonomous cars and trucks could solve gas shortages, pollution and other problems that plague individuals and society. Indeed, many smart people have predicted AVs would be swarming the roads by now. But it turns out it’s not so easy to build a 2-ton robot that goes 65 mph without making potentially fatal mistakes.
Companies also fail to view technology through the solution lens when they forget about needed enablers. In the case of self-driving cars, that means changes to roads, regulations, and insurance policies. It doesn’t mean that Tesla is wrong to invest in AVs; just that those that aren’t directly involved in the sector don’t need to rush to respond to it yet. Electric vehicles, by contrast, have long since proven their worth as a practical solution. And there’s sufficient regulatory and infrastructure support to make them a success.
Making huge investments too early in a technology can be costly. In May of 2022, Facebook changed its name to Meta to reflect Mark Zuckerberg’s all-in bet on the metaverse. And while the jury’s still out on whether the metaverse meets a compelling need, it’s clear that the benefits haven’t caught up to the idea; many people are complaining about other users’ bad behavior, uncomfortable headsets, and motion sickness, among other problems. Hence Meta’s recent quiet pivot to make AI its main focus.
The Strategy Lens
Companies should view the potential of a new technology through the strategy lens by considering the potential impact on their business model. Self-driving vehicles will eventually disrupt FedEx’s business, but not for a little while. Electric vehicles are a much more imminent threat to the country’s tens of thousands of gas stations and repair shops.
Companies run into trouble when they minimize the potential threat of a new solution. In the face of generative AI, one banking exec with whom I spoke acknowledged the cost savings of using chatbots, but then retreated into an argument for why people will always want to talk to a human being for something as important as making investment decisions. For his sake, I hope he’s right. But he sounds a lot like the execs who said people would never buy shoes over the internet. When it comes to strategy, it’s actually better for CEOs to be paranoid and consider worst-case scenarios rather than blithely dismiss the danger.
There’s a lot to think about here. The good news is that you don’t need to have all the answers. But you do need to get moving. Faced with this kind of uncertainty, savvy leaders know internal debates are of little value. It’s far more helpful to run experiments that will teach you about the validity of needs, its timeliness, and the impact on strategy. Like investing in stocks, it’s fine to start small and then lean in further if the application of a technology shows value.
The secret to navigating technological change isn’t about knowing more than other people. It’s about learning faster than other people. Technology can be a distraction and a drain on resources, but the costs of missing out on something genuinely transformative can be enormous. And that, of course, brings us to things like Artificial Intelligence. More to come on that.
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