The U.S. is unflinching in its optimism and ability to move forward after a crisis, such as the 2008 recession. And yet the drawback to this reflex is the ability to quickly forget what landed us in the situation to begin with. As our economy recovers, we potentially risk a growing complacency and inadequate financial oversight.
Just months ago, the country of Cyprus made global headlines as their banks’ ballooning assets grew far beyond what the country could support. Losing over 4.5 billion euros, the Cyprian banks tried to repair the damage by confiscating secure deposits, affecting the assets and the trust of investors throughout Europe and Russia and causing a ripple effect of investment withdrawals. The contagious effects of this crisis are a warning of how interconnected we are, and how one failed system could halt economic recovery elsewhere.
Most of today’s leadership literature focuses on the two most popular forms of leadership: the visionary leader—the charismatic transformational leader who inspires, or the relationship leader—the mentor who has the compassion and empathy needed to form strong relationships to support their organization.
But the global business world is changing rapidly, from the top down and the bottom up. Organizations are flatter. Boundaries are more blurred. Information moves faster across all levels within an organization. This means that leaders who can innovate and move quickly—leaders who have dynamic capabilities—are more likely to succeed.
Much of the blame around the Healthcare.gov website—a web-based insurance marketplace established by the 2010 Affordable Healthcare Act—has focused on the fact that the site couldn’t handle the amount of traffic it received. Essentially, it wasn’t scalable. But look beyond the headlines and it becomes clear that there are bigger issues around the website: not only is it not scalable and therefore not accessible to the thousands of Americans hoping to use it, but it also has some user design flaws.
Both of these issues—accessibility and user design—can be attributed to a reported lack of testing. According to The Washington Post in “Full Testing of Healthcare.gov Began Too Late, say Contractors,” testing on the site began a mere two weeks before its hard and firm go-live date of October 1, 2013.
A combination of 47 contractors and multiple agencies were involved in designing and building the website. Between the level of complexity involved in the site, the number of technologists designing and building the site, and the large numbers of “managers” involved in the process, the overall place to put blame is on the management of the project. Someone—or, more likely, many people—along the way did not do or manage the proper level of accessibility and usability testing. And in a recent management shakeup, the official who supervised the launch of the health care site left for the private sector.
While seemingly new, analytics have been used in sports for decades. After all, what was then-called Rotisserie League baseball (now Fantasy League) was all about picking baseball players based on their statistics.
The most famous use of data and analytics in sports is arguably the popular book and movie, Moneyball: The Art of Winning an Unfair Game, the true story of how Billy Beane, the general manager of the Oakland Athletics, used analytics to build a successful baseball team.
Today, Big Data is the latest extension of how (and why) sports organizations are using information to make better business decisions. As Dave Feinlab of Forbes writes in “Big Sports: Powered by Big Data,” “Big Sports is Big Business, and Big Business nowadays means Big Data…”
Smart machines are everywhere we go. They’re on the plant floor manufacturing our cars, and they are in our grocery stores scanning our purchases. In the case of the iPhone and Siri, they are even in our pockets.
And that means that smart machines and robots will be taking more and more jobs. As Erik Brynjolfsson, Professor of Information Technology at MIT Sloan School of Management said on CBS’ 60 Minutes, “There are lots of examples of routine, middle-skilled jobs that are being eliminated the fastest. Those kinds of jobs are easier for our friends in the artificial intelligence community to design robots to handle them.”
But some of the developments we’ve seen in recent years indicate robots—or smart machines—will be taking not just manual jobs, but also intellectual jobs. Just take a look at Watson, IBM’s computer that played on—and won—Jeopardy! Over the course of the tournament, Watson not only came up with correct answers, but also learned why his incorrect answers are wrong. It improved at a rate faster than any human could.