As the US Republicans deal with the apparent rebuke from the American people and the US Democrats get to work on bridging a divided country under President Barack Obama’s renewed four-year lease after the 2012 Presidential Elections, the story that caught my attention is that of a statistician, Nate Silver.

Nate Silver does not work for either party. He is a statistician who accurately predicted the election, and re-election, of President Obama, by aggregating poll data from various sources to find relationships among them, and then determining, based on his own methodology, what the likely outcome is.

Pictured left: Morris Sim

Beyond elections Silver has also analysed future performance of baseball hitters and pitchers. His blog, FiveThirtyEight.com (538 being the number of electorates in the United States Presidential Elections) currently sits at website of The New York Times.

Silver, who is 34, is a new breed of analyst needed for Big Data to realise its potential.  He’s someone who understands the essence of sound statistical methods, but is able to apply/reject practices in the imperfect world that data lives in outside of academia. The lack of ability to do so leads to the wrong conclusions, as the traditional US Republican statisticians saw in the last 24 hours.

At the same time, the human story of what Silver has had to deal with in the run-up to the elections has been nothing short of amazing. An analyst at a competing poll, ironically named UnskewedPolls, says, “Nate Silver is a man of very small stature, a thin and effeminate man with a soft-sounding voice that sounds almost exactly like the ‘Mr. New Castrati’… Silver, like most liberal and leftist celebrities and favorites, might be of average intelligence but is surely not the genius he’s made out to be. His political analyses are average at best…”

Nate Silver is a change agent – he’s changed the way polls should be looked at to increase their accuracy in predicting the outcome. Change agents are often ridiculed, discredited, and repudiated, particularly by the establishment when they feel threatened, and it’s no different in the world outside politics.

As we head into the world of Big Data the operators and the number crunchers have to work together to ensure that the analysis is correct and actionable. This is not an easy task because the two sides come from different backgrounds, and the fear of change – an emotional reaction that causes walls to go up – can stop brands from being able to take advantage of Big Data.

And in the worse cast scenario, wrong analysis guided by bravado can lead one down the path to irrelevance.