The Election Day hero of November 6, 2012 was predictive analytics.
First, several prominent bloggers, such as Sam Wang of the Princeton Election Consortium, Simon Jackman of Huffington Pollster, and the New York Times’ Nate Silver went up against punditry, polls and “conventional wisdom,” using analytics to accurately predict the outcome of the 2012 presidential election with stunning precision. Applying sophisticated analytics to state-level polling data (and in the case of Silver, factoring in historical and economic data), these analytic experts realized long before election night that the outcome wasn't in doubt and it would be virtually impossible for Mitt Romney to even come close to victory. The power of analytics was on display in front of the entire world as these bloggers not only predicted the overall outcome of the election, but the state-by-state results with jaw-dropping accuracy.
Perhaps more importantly for the future of analytics and politics, predictive modeling played an even more important role elsewhere in the election. A Wednesday Time Magazine article, "How Obama's data crunchers helped him win," highlighted how Big Data analytics were used in the Obama campaign. Campaign aides collected, stored and analyzed data in the two-year drive for re-election. The analytics didn’t just tell them which celebrity West Coast women aged 40 to 49 would most like to dine with (George Clooney), but also which individual voters were most persuadable, who was most likely to donate, which messages would resonate most effectively with which voters, and where the campaign would achieve the highest ROI on its expenditures. Few organizations in or out of politics have ever harnessed the power of Big Data as effectively, repeatedly and aggressively as the President's re-election campaign.
At FICO Labs, we are seeing predictive analytics and Big Data changing many industries … manufacturing, retail, banking, insurance. This week it changed politics, next week…who knows.
