Generally, the technology that enables disruption is developed in the companies that are the practitioners of the original technology. That's where the understanding of the technology first comes together. They usually can't commercialize the technology because they have to couple it with the business model innovation, and because they tend to try to take all of their technologies to market through their original business model, somebody else just picks up the technology and changes the world through the business model innovation.
The personal computer was a disruptive innovation relative to the mainframe because it enabled even a poor fool like me to have a computer and use it, and it was enabled by the development of the micro processor. The micro processor made it so simple to design and build a computer that IB could throw in together in a garage. And so, you have that simplifying technology as a part of every disruptive innovation. It then becomes an innovation when the technology is embedded in a different business model that can take the simplified solution to the market in a cost-effective way.
The innovations are far more important because the technology itself has now way to impact the world for good until it's embedded in the business model. Innovation it's the combination of the simplifying technology and the business model.
At the beginning of almost every industry, the available products and services are so expensive to own and complicated to use that only people with a lot of money and a lot of skill have access to them. A disruptive technology is an innovation that simplifies the product and makes it so affordable that a whole new population of people can now have one and use it at the beginning for simple applications, and then it improves to the point that it makes the old technology obsolete.
Every disruptive innovation is powered by a simplifying technology, and then the technology has to get embedded in a different kind of a business model. The first two decades of digital computing were characterized by the huge mainframe computers that filled a whole room, and they had to be operated by PhD Computer Scientists. It took the engineers at IBM about four years to design these mainframe computers because there were no rules. It was an intuitive art and just by trial and error and experimentation they would evolve to a computer that worked.
The mistake managers often make is defining their industry too narrowly. Digital's market share in the minicomputer market stayed very robust even as it fell off the cliff. Disruption seems to come out of nowhere, but if you know what to look for, you can spot important developments well before the market does.
In general, the questions that are on our mind are the same questions that have been driving our work over the past decade. How do we bring order to this messy, unpredictable world of innovation? How can we dramatically improve the chances of creating a successful new-growth business? How can we do this again and again? More specifically, it has become very clear that the fundamental paradigms of market segmentation and branding are badly broken - and we're working on developing more useful theories for these dimensions of innovation.
We are all trained to be data driven people, but no hard data exist about the future. Therefore, the only way to look into the future with any degree of accuracy is to use theory, statements of what causes what and why. If executives have the right theories in their heads, they can very quickly interpret market developments. They can identify what matters and why, and act accordingly. So we suggest decision-makers should start by gaining a deep understanding of the relevant collection of theories, and then be alert for signals that indicate certain types of developments.
The biggest mistake is an over-reliance on data. Managers will say if there are no data they can take no action. However, data only exist about the past. By the time data become conclusive, it is too late to take actions based on those conclusions.
One of the factors that make great companies so great is that they have processes that allow them to solve difficult problems again and again. These processes have developed over time as teams have successfully wrestled with a certain type of challenge. Eventually, people begin to say, "This is just how we do something around here." The problem develops when that team then has to solve a very different set of challenges. The processes that are such strengths can be crushing liabilities.
If a company truly wants to resolve the innovator's dilemma, it does need to be able to create wave after wave of disruptive innovation. And those disruptive innovations will typically grow to the point where they do cause some pain for leading companies. But most disruptive innovations create substantial new growth before they cause that pain.
People still cling to this belief that innovation is just random and unpredictable. But if you look closely, there are some real patterns. The companies that recognize and take advantage of those patterns have the real opportunity to create competitive advantage.
We have found that companies need to speak a common language, because some of the suggested ways to harness disruptive innovation are seemingly counter-intuitive. If companies don't have that common language, it is hard for them to come to consensus on a counter-intuitive course of action.
Most companies think of disruption as a threat. But disruptive innovations have tremendous growth potential. If incumbent companies can learn how to harness the forces of disruption, they too can improve their ability to create new-growth businesses.
By the time it becomes obvious that a technology will have truly disruptive impact, it is often too late to take action. This is one reason why we are such advocates of using theory to try to analyze industry change. Conclusive evidence that proves that a company needs to take action almost never exists. In fact, the data can fool management, lulling them into a false sense of security.
The reason why it is so difficult for existing firms to capitalize on disruptive innovations is that their processes and their business model that make them good at the existing business actually make them bad at competing for the disruption. Companies in fact are specifically organized to under-invest in disruptive innovations! This is one reason why we often suggest that companies set up separate teams or groups to commercialize disruptive innovations. When disruptive innovations have to fight with other innovations for resources, they tend to lose out.
History is littered with great firms that got killed by disruption. Of course, the personal computer, a technology that first took root as a toy, got Digital Equipment Corporation. Kodak missed the boat for a long time on digital imaging. Sony was slow to get MP3 technology. Microsoft doesn't know what to do with open source software. And so on.
In a large successful company where your power base as CEO isn't all that secure, it's hard for a CEO to pursue a truly disruptive strategy.
The important thing is that over time, scientific progress transforms things that used to have to be dealt with in a problem-solving mode down to the pattern-recognition space; and from pattern recognition into the rules-based mode. This is the mechanism by which less-trained people are enabled to do more sophisticated things. This is always the way disruption happens. It enables a larger population of less-experienced people to do more sophisticated things.
Another thing I've observed is how critical the role of the CEO is when a technology truly is disruptive. In looking back on companies that have successfully launched independent disruptive business units, the CEO always had a foot in both camps. Never have they succeeded when they spin something off in order to get it off the CEO's agenda. The CEOs that did this had extraordinary personal self-confidence, and almost always they were the founders of the companies.
In most instances, biotechnology, though a radically different approach, is a sustaining technology: It's a dramatically improved way of targeting problems that we hadn't been able to solve with the conventional approach of mainstream pharmaceutical companies.
There are other dimensions of biotechnology. If you think of biotechnology like the Internet, it's not a category - it's an infrastructure that can be deployed to sustain or disrupt. In health care, the most complex problems at the high end have to be dealt with in a problem-solving mode by the best, most experienced physicians you can find.
Quite often startups were first out of the gate with a sustaining technology. But somehow the leaders got the technology and stayed atop their industries. Sometimes they acquired the startup; sometimes they just developed the technology as a follower and used their muscle and mass to win. But they always won.
If the technology is disruptive, on the other hand, the odds are that at the end of the transition, the leaders will have been toppled and new companies will be on top.
A lot has been written about the Internet bust. From my point of view, it's quite clear the Internet isn't a category; the Internet is a technological infrastructure that can be deployed to facilitate a disruptive business model or a sustaining business model.
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