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Analytics Magazine

Inside Story: Troubling Tradeoffs

September/October 2010

Making a decision is easy; the ability to consistently make the right decision when the stakes are high and the insight is low is a rare trait and helps explain why C-level execs have historically been paid the big bucks. Of course, the history books – and newspapers, business magazines, blogs and bar backrooms – are also full of stories of well-paid CEOs and other execs who made at least one terrible decision that brought down a multi-million-dollar business, but those are stories for another day. (By the way, if you have an analytical failure story and want to share it with our readers, perhaps as a cautionary tale or a lesson learned, please send it my way. You’ll go to the front of the line.)

Getting back to the issue at hand, organizational decision-making is tricky business because the decision-maker is often faced with seemingly equal options. In a tough economic environment when you can’t have it both ways, which way do you go? Or maybe you can’t have it all but you can have some of both, so how far do you go in each direction, knowing that the rope (i.e., the budget) that binds the two will only stretch so far? As our cover points out, corporate decision-making can thus be seen as an artful, high-wire balancing act over tradeoffs.

For example, Mu Zhu takes the balancing act to new heights in “Predictive analytics: Managing fundamental tradeoffs” (page 18). When using predictive analytics, Chu stresses the importance of understanding and controlling three tradeoffs: “bias” vs. “variance,” “strength” vs. “diversity” and “where” vs. “how.”

In “Total cost of ownership” (page 22), an article on enterprise risk management, Lutz Schiermeyer again mentions tradeoffs when comparing the “cost and risk of migration toward an ERM landscape on one side with the ongoing operational costs and lack of flexibility to operate the current, disparate risk management systems on the other side.”

Besides complexity and tradeoffs, these and other decision problems presented in this issue all have one other thing in common: the ability and opportunity for analytics to solve them.



Using machine learning and optimization to improve refugee integration

Andrew C. Trapp, a professor at the Foisie Business School at Worcester Polytechnic Institute (WPI), received a $320,000 National Science Foundation (NSF) grant to develop a computational tool to help humanitarian aid organizations significantly improve refugees’ chances of successfully resettling and integrating into a new country. Built upon ongoing work with an international team of computer scientists and economists, the tool integrates machine learning and optimization algorithms, along with complex computation of data, to match refugees to communities where they will find appropriate resources, including employment opportunities. Read more →

Gartner releases Healthcare Supply Chain Top 25 rankings

Gartner, Inc. has released its 10th annual Healthcare Supply Chain Top 25 ranking. The rankings recognize organizations across the healthcare value chain that demonstrate leadership in improving human life at sustainable costs. “Healthcare supply chains today face a multitude of challenges: increasing cost pressures and patient expectations, as well as the need to keep up with rapid technology advancement, to name just a few,” says Stephen Meyer, senior director at Gartner. Read more →

Meet CIMON, the first AI-powered astronaut assistant

CIMON, the world’s first artificial intelligence-enabled astronaut assistant, made its debut aboard the International Space Station. The ISS’s newest crew member, developed and built in Germany, was called into action on Nov. 15 with the command, “Wake up, CIMON!,” by German ESA astronaut Alexander Gerst, who has been living and working on the ISS since June 8. Read more →



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