As the saying goes, “Predictions are difficult, especially when they concern the future” (Pierre Dac). And yet we might expect people who have succeeded in a particular field and are considered experts, benchmarks, to be relevant and far-sighted when it comes to envisioning the future, but this is not the case.
“There is no reason anyone would want a computer in their home“, said Ken Olsen, founder of Digital Equipment Corporation in 1977. Nearly 50 years later, we can only laugh, and it wouldn’t be so bad if this were the exception that proves the rule.
But examples like this are a dime a dozen.
For years now, I’ve been jotting down all the outlandish predictions I come across, and as I reread them, I realized that their number was worth looking into and discovering whether there were any common “patterns” that explain why great leaders can be so wrong, and which would be so many pitfalls to avoid in order to protect oneself from one’s own biases.
In looking for what these predictions had in common, I came across a number of recurring thinking biases, often linked to cognitive biases, limitations in understanding innovations or market dynamics, and an inability to envisage radical transformations.
Forecasting is not prediction
Before going any further, we need to be clear about the difference between forecasts and predictions.
A prediction is an intuitive or speculative statement about a future event, often based on subjective beliefs or assumptions. It has little basis in data or methodical analysis, and relies more on personal opinion or general trends. As a result, it is less structured and has a lower level of certainty.
When I read a lot of predictions on the web, I often think that their authors want them to be self-fulfilling, and use them to influence the market in the direction that interests them. Experience shows that this rarely works.
By contrast, a forecast is a methodical, rational estimate of a future event, based on the analysis of existing data and the use of statistical or probabilistic models. It offers a higher level of credibility, as it is based on proven methodologies, although it always incorporates an element of uncertainty and is not resistant to unexpected changes such as “black swans”.
In short, prediction is intuitive and qualitative, while forecasting is analytical and quantitative.
The difficulty of imagining radical change (continuity bias)
Experts often extrapolate the future from the present and existing trends , underestimating the impact of disruptions.
I think there is a world market for maybe five computersA very good example is Thomas Watson, the chairman who made IBM great, who in 1943 said “I think there’s a world market for maybe five computers.”
Why? As a turn-of-the-century man (he was appointed in 1914), he couldn’t imagine a world where computers would be accessible to the general public, because he saw their usefulness in limited industrial contexts.
How could he have envisaged the miniaturization that led to large-scale business computing and then to consumer computing, with a corresponding explosion in the power of devices?
But beware: this quote ( but there are many like it ) is probably a rephrasing of a sentence taken out of context (Urban legend: I think there is a world market for maybe five computers).
By definition, disruptions call into question established mental models, but these remain firmly anchored because we find it hard to imagine the impact of something that has never existed.
Overconfidence in expertise (authority bias)
Experts in a field often believe themselves incapable of making an error in judgment, but their self-confidence can blind them.
In 1996, the visionary Steve Jobs told us that “The desktop computer industry is dead”.
He wasn’t talking about the PC as a competitor to the Mac, but about the personal computer, including the Mac, believing that the future would be portable, without even thinking about mobile.
Jobs, in fact, was so obsessed with innovation and his vision that he underestimated the longevity and adaptability of the existing offer.
Today, while laptops are undeniably successful, not to mention mobile phones and tablets, the desktop computer is still a force to be reckoned with and is not about to disappear.
Maybe tomorrow or later, but for a product that’s been dead for 30 years, it’s not doing so badly.
Resisting change and defending existing models
Many leaders and experts understandably cling to the models that have brought them success , and resist any idea that might challenge them. When the context is favorable to us, we don’t want to imagine it changing.
“Netflix will never work, because people prefer to rent DVDs in stores.” That’s what Blockbuster, Netflix’s DVD rental competitor, thought back in 2000, when Netflix offered to send DVDs by mail, something Blockbuster thought it could do with its own resources if necessary.
But it was the fact of distributing by mail that would later help Netflix have the mindset to move into web and streaming.
This is the typical case where a leader defends his business model and doesn’t want to conceive that consumer habits may evolve. Typical of the type of prediction that only serves to reassure oneself and that one hopes will be self-fulfilling.
In the end, Blockbuster refused to buy Netflix for $50 million.
But we’ve seen it before, at Kodak for example, with digital photography. Contrary to popular belief, Kodak was way ahead of the game. They invented the digital camera, but the business chose not to invest in the technology, fearing it would cannibalize its film revenues.
Underestimating the speed of adoption
Experts often think that change will happen more slowly than it actually does.
It’s often said that we always overestimate the change that will occur in the next two years and underestimate the change that will occur in the next ten, but after all, 10 years is still a short time.
” Try typing a web key on a touchscreen on an Apple iPhone, that’s a real challenge. You cannot see what you type“. We owe this meteoric rise to Mike Lazaridis, founder of RIM (Backberry) in 2007.
Lazaridis simply didn’t believe that touchscreens could become the norm so quickly, and that technologies such as multi-touch and Gorilla Glass would make it so easy and fun to use.
In fact, the combined effect of accessibility and simplicity has radically changed consumer expectations in a very short space of time.
And surely Lazaridis was also defending his existing model and trying to convince the market…and investors.
Inability to perceive the added value of an innovation
It also happens that new technologies or business models are often ignored because they don’t fit in with current usage or don’t seem practical in the current state of affairs.
We can’t deny David Lynch a certain knowledge of the world of cinema, and he declared in 2008 that “Now if you’re playing the movie on a telephone, you will never in a trillion years experience the film. You’ll think you have experienced it, but you’ll be cheated. It’s such a sadness that you think you’ve seen a film on your fucking telephone. Get real.“
Steve Jobs was no better, saying in 2003 that “People have told us over and over and over again, they don’t want to rent their music,” said Jobs emphatically at an event later that same year. “Just to make that perfectly clear, music’s not like a video. Your favorite movie you might watch ten times in your life — your favorite song you’re going to listen to a thousand times in your life ”.
Both failed to grasp the extent to which mobile broadband would change consumer habits and, moreover, one how music would commoditize and the other how the quality of screens and auditory devices would enhance the experience on the phone.
In addition, Jobs was faced with the additional bias of wanting to preserve his then-leading model.
Lack of short-term profitability
Some people reject ideas because they don’t seem profitable in the short term.
In 1876, Western Union rejected an invention by Alexander Graham Bell, a certain “telephone”, claiming that “This ‘telephone’ has too many shortcomings to be seriously considered as a means of communication. The device is inherently of no value to us.“
Indeed, the telephone network had to be built, a titanic undertaking requiring an equally titanic investment, and they couldn’t see any way of ever coming back into their funds.
In the 90s, many automotive experts didn’t believe that electric cars would ever be profitable either. Batteries were expensive, and the recharging network non-existent.
Where do we stand in 2025? It’s not the goose that lays the golden egg, but some players are starting to make a profit, even if the future of the sector isn’t free of clouds either.
But then, some people don’t believe that technological innovations, economic paradigm shifts and the massive development of new uses can transform the viability of a product.
Wrong view of future needs
Predictions are often based on current needs, without considering how they might evolve.
We can of course quote Ken Olsen and Thomas Watson again, but we can’t forget Bill Gates, who said in 1993 “The internet? We are not interested in it“, and who then had to put in the effort to catch up with something that was going to be massively adopted. Special mention also to his successor Steve Ballmer , who said in 2007 that “There’s no chance that the iPhone is going to get any significant market share. No chance”.
He wasn’t wrong, insofar as Apple is more concerned with capturing market value than market share. But he underestimated the extent to which users would make such a device (of whatever brand, the iPhone being the pioneer at the time) the center of their digital lives.
In fact, many technologies create needs and uses that didn’t exist before, and sometimes that even their promoters hadn’t thought of.
The pressure of prevailing opinion
There was a time when it was said that “no one was ever fired for choosing IBM”, but generally speaking, to protect one’s own credibility, one prefers to follow prevailing opinion and a conservative vision.
At the end of the 1990s, financial experts were unanimous: “Amazon is a flash in the pan. Their business model has no viability”.
It was common at the time to criticize startups, and let’s face it, the history of the first bubble proves them partly right. But as far as Amazon was concerned, they had it all wrong.
But to go against the consensus is to take a risk, and financiers don’t like that.
Ignorance of the global context
Experts and executives often analyze an innovation in a local or restricted context, ignoring its wider implications.
In the 2000s, music industry analysts were unanimous: “Spotify will never be able to generate revenues.”
This ignores the global dynamics and network effects that spread new uses like a tidal wave.
Technocentric bias
Some people don’t believe in technology, while others believe in it too much and overestimate an innovation, ignoring social, cultural or economic barriers.
In 1990, experts promised that “robots will replace all jobs by 2020. Granted, today this is a real cause for concern (Will AI replace juniors? The false debate that’s only the tip of the iceberg), but we’re still a long way off. And in any case, talk of “all the jobs” was greatly exaggerated, despite the progress made by technology. Impressive, but not enough.
Similarly, in the wake of the iPhone’s success, we were told that the future lay in connected glasses. Google Glass, not uninteresting conceptually and technologically, failed mainly because of social concerns (privacy worries), and a lack of cultural acceptance. Their design and price played a role, but it was the social component that was not acceptable at the time.
The same is true today of the Ray Ban Meta, given that privacy concerns have only crescendoed since then (How 2 Students Used The Meta Ray-Bans To Access Personal Information).
Bottom line
Preference for the status quo, inability to imagine future uses, overestimation or underestimation of constraints… there are many reasons behind bad predictions.
But let’s keep in mind that, more often than not, their authors either have something to sell or something to protect.
But if you’re going to try your hand at this type of exercise (The difficult art of business predictions), and you want to show a minimum of relevance, it’s always useful to be self-critical and ask yourself, before publishing anything, if you haven’t fallen victim to one or more of these bais.
After all, the one who was right was the one who wrote that “the essence of a guru is to be wrong”.
Image: predictions by New Africa via Shutterstock
