There’s been quite the brouhaha lately about disruptive innovation. On one side is Harvard Prof. Clay Christensen (author of The Innovator’s Dilemma) and his long-prevailing theory about how disruptive innovation drives incumbents out of the market. On the other side is Jill Lepore and her attack of Christensen’s theory in The New Yorker. It’s an interesting issue: Do disruptive innovations almost always lead to the downfall of incumbent companies? Is their only hope to “disrupt” themselves?
Along with Joshua Gans of the University of Toronto and David Hsu of Wharton, I conducted a study on the speech recognition industry over the last 58 years. We found a surprising pattern among entrants that adopted disruptive technologies: Instead of always going head-to-head with incumbents, they often adopted a dynamic commercialization strategy in which they started out competing against them, but later switched to cooperating with them (e.g. by licensing their technology). To understand how this can happen, we need to review what it means for a technology to be “disruptive.”
MIT Sloan Executive Director of Executive Education Peter Hirst
I recently attended the second annual Internet of Things World Forum in Chicago, IL. In the opening keynote presentation, Wim Elfrink, Cisco’s EVP of Industry Solutions and Chief Globalization Officer, referenced Gartner’s latest version of its“Hype Cycle,” noted that IoT (the Internet of Things) has climbed over the past year to its peak. Yet, on closer inspection, the enviable place IoT is enjoying within this technology-evolution framework is actually named the “peak of inflated expectations,” a precarious high point where individual dazzling success stories of early adopters and visionary speculation are outshining wider market reticence and slow early adoption. In the model, this magical time is usually followed by a “trough of disillusionment,” then — if the market responds favorably to second and third-generation tech — the “slope of enlightenment,” and finally — if wide market adoption takes place — a “plateau of productivity.”
The conference certainly provided many vivid illustrations of success and the potential of IoT, but will this fledgling industry make it through the inevitable coming trough, and climb “high and right” on the chart with predicted tens of billions of connected devices, as was enthusiastically espoused by Elfrink in his opening remarks?
In the 1987 movie Wall Street, Gordon Gekko’s memorable pronouncement that “greed is good” epitomized the worst features of American corporations that focus only on maximizing immediate shareholder returns without regard to the impact on their employees, customers, or communities.
That corporate caricature has continued to prevail. But recently, people ranging from Harvard University Business School Professor Michael Porter to leaders of the Sloan, Ford, Aspen, Hitachi (more here) and other foundations are putting forward the case that companies can provide great returns to shareholders and great jobs for employees.
Valuing a company is always a mix of science and art, especially for startups. Historically the science has been pretty simple: Find comparable companies and do a multiple of earnings or revenue.
However, three drivers of startup valuation have emerged that are changing the game. “Acquihire,” is the act of buying out a company for the skills and expertise of its staff. It has become so well-known that it is even listed in the Oxford English Dictionary. When Facebook buys a company like Hot Potato, it’s not for the revenue stream or products — it’s for the employees.
In 2011, two business school professors put numbers to an idea that many assumed true: that a vibrant research university can drive an economy. They studied companies started by alumni of the Massachusetts Institute of Technology and found that those businesses had provided 1.7 million jobs and generated $1 trillion in revenue annually.
As more countries try to compete in the global economy, the pressure is on policy makers and university leaders to imitate the way MIT spurs innovation and economic growth. Unfortunately, many universities struggle to match the speed and success of MIT’s model.