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 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.
In the early days of computers, companies used a fee-for-shared-service model for technology. It was common to pay a company like IBM rent for use of its mainframe machines. As computers became smaller and less expensive, businesses began to purchase their own equipment and the computer rental model went the way of the dinosaur. Interestingly, we’re now seeing a return to that old model, but instead of computers, businesses are renting web and cloud infrastructure services for apps and storage.
This is great news for small- and medium-size companies, as building the data centers to run those services is exorbitantly expensive. By only purchasing the infrastructure cloud services that they need from large companies like Microsoft, Google and Amazon, they eliminate the risk of that huge financial investment.
Even better, we’ve seen recent price wars among those service providers. Some of them slashed their prices by as much as 85 percent this spring in an effort to attract and retain customers.
I sit on the board of several companies that are dependent on web services and have seen this decision to rent play out several times. A good example is Carbonite, which is launching its computer backup services across Europe and recently joined the ranks of Amazon customers for web services. The decision for Carbonite was simple: If it were to build its own data center, not only would it cost excessive funds, it would have to maintain it and then (all too soon) upgrade it. It would be akin to building its own telephone or cable company instead of simply renting what it needs from a provider like Verizon or Comcast.
Knowledge and innovation generated at universities can lead to the creation of high-impact spin-off businesses. Whether it is through the licensing of intellectual property, partnerships or other informal arrangements, the tech transfer process can play a critical role in shaping new industries and regional economic development.
Research by Eesley and Miller and Eesley and Roberts has demonstrated the role Stanford University has played in shaping the development of Silicon Valley and MIT’s contribution to building a world-class innovation hub in the Kendall Square district of Cambridge, Massachusetts.