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.