Politics in Analytics

Observers of American Electoral politics ,including the current Presidential Campaign would be struck by the sophisticated degree of analytics being involved. This includes the following –

1) Segmentation of likely percentage Response Rates (vote yes(1) , vote opponent (0)

based on

history of voting

response to stimuli (experience vs change)

ethnicity (black, white ,latino)

income groups (<40,000 USD ,>100000 USD)

education (college educated)

gender (male,female)

geography (rural ,urban,college town)

union affliation

and even coffee (latte drinkers etc 🙂 )

What is striking is that most of these variables like race, gender cannot be used for marketing anything else like credit cards, or financial services on charges of discrimination.

What could be really interesting is if they add credit bureau variables and create logistic models (and not just segmentation). Maybe by 2016, there will be a different category of analytics called Quantitative Political analytics.

Another note – What is similar between Ralph Nader , Chaos Theory and Butterfly effect.

Chaos theory states that future results can vary a lot based on slight changes in initial differences.

Butterfly Effect uses this to say a small event like butterfly fluttering in china can cause a big event like typhoon in the US.

Ralph Nader entering the race in 2000 got 90000 votes in Florida, mostly to be siphoned away from Al Gore , who lost Florida and the elections by less than 1000 votes.

Al Gore was against Iraq war since the beginning and had he been President maybe the world would have been greener and no war in Iraq. maybe. No offense meant to anyone.

Howard Dean screaming or Bill Clinton calling Obama as similar to Jesse Jackson’s wins (which is analytically and quantitatively true) or Hillary crying in Iowa , can be similar butterfly effects.No offense meant to anyone.

Author: Ajay Ohri


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