Nov/Dec 2016

Russia has a plan to take over Central and Eastern Europe, only this time by buying it rather than overrunning it.

• Doug Samuelson

Why should analytics professionals care about project management? After all, we are trained problem-solvers and when we “do stuff,” good things happen, right? On the contrary, projects are the primary vehicles through which we deliver value, and consistently delivering value with analytics requires effective project management. When it comes to delivering analytics, what matters is not only what you do, but also how you do it.

• Erick Wikum

You’ve heard from colleagues, from industry news, maybe even from personal experience of the success of crowdsourcing. With nearly half the world’s population online, it makes sense to tap into this tremendous resource to collect large quantities of data by breaking the collection down into micro-tasks that the enormous crowd of Internet users will complete for you at pennies per task. But you’ve probably also heard of cases of crowdsourcing gone wrong, cases like the British government agency that put the task of naming its new research vessel out to the crowd and ended up with Boaty McBoatface [1]. So you have a human annotation task – a data refinement or evaluation task that requires human input – and you’re trying to decide whether to take your chances with crowdsourcing. Where do you start? The first thing you need to know is that you have options; it’s not Boaty McBoatface or nothing.

• Ben Christensen

Fifty years have elapsed since the founding of the field of decision analysis by Howard Raiffa [1] and Ron Howard [2]. 2016 is not only a milestone year due to the anniversary but also because it marks the passing of one of the founders, Howard Raiffa. Such significant events make this year a time for reflection. Seasoned decision analysts can celebrate their contributions to the advancement of the field, while young operations research (O.R.) and analytics professionals should take this time to imagine how their current and future contributions will shape the next 50 years of the field.

• Samantha Oleson

In today’s complex business world, many organizations have noticed that the data they own and how they use it can make them different than others to innovate, to compete better and to stay in business [1].

• Prashant Tyagi
• Haluk Demirkan

Monte Carlo simulation has been used to model uncertainties since the Manhattan atomic bomb project by blasting randomly generated inputs through mathematical models. Monte Carlo spreadsheet add-ins for personal computers have been available since the mid-1980s, however, it has not been a killer app because it takes specialized training to generate the required random inputs. Actually, a great invention of the 19th century, the light bulb, was never widely adopted because it took specialized training to generate the required electricity (just kidding). Thomas Edison subsequently proposed that experts with generators provide electricity for non-experts with light bulbs, and the result was the power-distribution network.

• C. Keith Harrison
• Scott Bukstein