The Republicans are now talking in earnest about the virtues of Big Data – because they have to.
Ever since Mitt Romney lost the November presidential election, Republicans as disparate as former GOP presidential candidate and Speaker of the House Newt Gingrich and House Majority Whip Eric Cantor are pressing the need to get behind Big Data. They know now what the GOP ignored in 2012 – Obama won in large part because his campaign used the skills of over 50 data analysts in the tech space to micro-target key segments of the electorate. They know it’s critical not just appeal to broader swaths of the American public, but to go out and win elections.
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“Data science Obama-style has no relationship to the Republican model of Internet politics,” Gingrich wrote recently in a plaintive memo designed to push the GOP off its rump ahead of CPAC – the conservative gathering next week. “The Obama system is helped in data science by its 85-to-90 percent dominance of Silicon Valley,” Gingrich said. “If you have the founders of Google and Facebook helping you design your system, you have an enormous advantage over your competitors.”
It’s why the challenge, he says, “of social networking, micro-community building and citizen mobilization may be second only to the challenge of including minority Americans in the GOP in determining whether Republicans decline into minority status for the next several decades” – or not.
But actually leveraging the data that one grabs is the crux. Gingrich acknowledged this to The Fiscal Times yesterday: The GOP needs “to confront in a pretty painful way changing exactly what [we’re] dealing with. This is a cultural problem more than a technology problem.”
This is hardly limited to political organizations, though. Eric Siegel, author of the new book Predictive Analytics and founder of Predictive Analytics World, a gathering of data experts, says that by leveraging the data they collect, “organizations attain a position of power: They learn from the data how to predict human behavior.”
A company “with hundreds of thousands of customer records,” for example, “can learn from the experience encoded in this data. It’s a kind of pattern-detection that can help them discover which combinations of factors about a customer makes the individual much more likely than average to cancel.”
These factors aren’t always obvious or intuitive, Siegel told The Fiscal Times. “They are signals that reveal odds, even if a customer has not yet begun to formulate any particular plan of action.”
But there are other examples of the “multitudes of predictive discoveries awaiting within the data” – take retirement.
“The University of Zurich discovered that, for a certain working category of males in Austria, each additional year of early retirement decreases life expectancy by 1.8 months,” Siegel says. “This could be due to unhealthy habits such as smoking and drinking following retirement, they believe.”
Predictive analytics, he argues, seeks out these “connections and then works to see how they may combine together.” Hewlett-Packard has looked at employees’ intent to resign; retailer Target has deduced whether its female customers are pregnant; and law enforcement in places such as Oregon and Pennsylvania have foretold convicts’ future repeat offenses, says Siegel.
One big caveat in all of this, though: Not only do Big Data services and expertise cost money – but Big Data “requires a new way of thinking and will challenge our institutions and even our sense of identity,” say Viktor Mayer-Schonberger and Kenneth Cukier in their new book, Big Data: A Revolution That Will Transform How We Live, Work and Think.
The question is whether the Republican Party can actually make that leap in time to save itself.
