Covering Disruptive Technology Powering Business in The Digital Age

Elections are a time of discomfort for many as well as a time of restless ambiguity. With all sides saying they are better than the other and coaxing voters to vote for them through endless campaigns of promises and beguiling, it is no wonder stresses run high.

All this could become a thing of the past as predictive data analytics becomes more prevalent as a tool for candidates to gauge if their motives and ideas are reaching the right tone with their electorates.

This was clearly shown in the 2012 presidential election, from a statistical viewpoint, how analytics fuelled big data advancement in computing has become the corner stone of the presidential campaign process and how the winner was actually the analytics, driven by people who managed to out-predict many political experts who relied on the conventionality of gut instinct.

During the 2012 Obama elections, there were 100 data scientists on his campaign research team. The management also hired statisticians, predictive modelers, data-mining experts, mathematicians, software programmers and quantitative analysts and eventually built an entire analytics department five times as large as that of its 2008 campaign. The coming 2016 elections will see no less in analytics from all parties.

Nate Silver at FiveThirtyEight had predicted Obama’s win by exactly how much. Simon Jackman, professor of political science at Stanford University, also accurately predicted that Obama would win 332 electoral votes and that North Carolina and Indiana would be the only two states that Obama won in 2008 that would fall to Romney.

Other analysts with excellent predictive reports include Drew Linzer, assistant professor of political science at Emory University, Sam Wang a neuroscientist at Princeton University and Josh Putnam of Davidson College who correctly predicted the presidential race with great accuracy. Their track record in predicting the 2008 election results was nothing short of outstanding either.

In predicting election outcomes, data analytics has proven itself as an unprecedented tool.

Rick Hutley who is director of the analytics program at the University of the Pacific however, has his masters students focusing on election analysis but from a very different perspective.

He says that the use of data in elections has changed these past few years. “The traditional view of analytics is the Nate Silver stuff, who is going to win,” he said. “But the Obama campaign of 2012 showed us the value of data.”

The interesting thing about data in analytics in campaigns he says, are how it’s the same as what is used in businesses. While businesses use analytics to identify what customers really want, campaigns use that data to identify what the electorates are really concerned about, such as maintaining their brand image, which helps them see how the brand is received. In real time. There’s no need to wait for a post-debate survey. They just monitor the social media and audience response and immediately tweak their message while in the debate.

George Shen, information management specialist master with Deloitte Consulting, an information strategist and consultant, says there’s a lot to learn from the 2012 elections.

“First and foremost, businesses need to rely more on a data-driven approach and measured performance and less on gut instinct when data and analytics are available. It may require a cultural change and paradigm shift in some organizations. Second, understanding consumer behavior, sentiment and purchase pattern, predicting the next sales opportunity and most profitable customer, segmenting and micro-targeting the right population with tailored messages that resonate with customers are the challenges faced by almost every business.”

He adds that businesses should start building a solid, big data knowledge base and master the new social and digital intelligence across a variety of channels that will be help in identifying, targeting and winning customers similarly to how the 2012 election was won on the digital front.

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