MIT Sloan Lecturer in Entrepreneurship Trish Cotter
I have recently been catching up with colleagues from companies past, and when I let them know what I am doing now, I often get the reaction, “Wow! That’s such a cool job.” And it is … I’m fortunate to be the director of delta v, MIT’s student venture accelerator. Each year, we guide a new group of startups through “entrepreneurship boot camp” and help them to launch their startup ventures into the real world. This past summer, I worked with 21 startup teams as they were striving to either gain traction or make the tough decision to regroup. It was an amazing group of students with ideas that address real world problems.
But, I also thought I had a cool job at age 12 when I cleaned up after dogs at a kennel. I had a sense of purpose, got to fulfill a passion of mine by working with animals, and met some great people as well.
The organization I worked at most recently, prior to MIT, was IBM – a company that is trying to bring data analytics insights to companies, so they can address real world problems. The complexity of what both our MIT startups and IBM are doing, albeit in different ways, struck me. Are they so different? I have deep respect for IBM’s CEO, Ginni Rometty, who is moving a company the size of a small nation. However, the leaders of the MIT three-person startups are also scaling difficult challenges and placing bets with tremendous odds of failure.
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.
A majority of companies are now using huge streams of data and sophisticated analytic tools to transform how they strategize, operate, and engage with customers. According to a new global study by MIT Sloan Management Review (MIT SMR), 58% of organizations now apply analytics to create a competitive advantage within their markets or industries, up from 37% just one year ago.
Yet there is a growing gap between the most sophisticated users of data and analytics, and those just getting onto the path towards analytics competency.
MIT SMR’s initial joint study in 2010 identified three progressive levels of analytical sophistication: Aspirational, Experienced and Transformed. When we compared this year’s results to last year’s, we found that Experienced and Transformed organizations are expanding their capabilities and raising their expectations of what analytics can do, while the Aspirational organizations are falling behind. Read More »
Andy McAfee and I have just released a short e-book, Race Against the Machine. In it, we try to reconcile two important facts. 1) Technology continues to progress rapidly. In fact, the past decade has seen the fastest productivity growth since the 1960s, but 2) median wages and employment have both stagnated, leaving millions of people worse off than before. This presents a paradox: if technology and productivity are improving so much why are millions being left behind?
In the book, we document remarkable advances in digital technologies in particular. Innovations like IBM’s Watson, Google’s self-driving car, Apple’s Siri are turning science fiction into reality. Machines are doing more and more tasks that once only humans could do.
The government should be smart and strategic about the type of spending it will do, says David Schmittlein, MIT Sloan School of Management dean, who says if the government spends on innovative enterprise in America, it can put those dollars to better use.