The First Rule of Big Data

The First Rule of Big Data

The First Rule of Big Data
How many of you have watched the movie Fight Club?  Great movie, replete with violence, ennui, and a lament for the narcissistic failings of the baby boomers.  Anyways, there’s a scene in the beginning of the movie where Edward Norton talks about how has to assess risk associated with car accidents for an insurance company.  His job is to figure out whether a recall is the right decision for an auto manufacturer to make – from a financial perspective.  Using actuarial tables, he identifies the company’s financial exposure from accidents and compares this to the costs of a recall.  If a problem will result in $50,000 per claim against 1,000 total claims ($50,000,000), and the recall cost is $75,000,000, then they don’t authorize a recall.  Financially, it makes more sense to let people die in accidents than to correct the problem  [CLICK TO TWEET].

This is a nuanced but substantive problem associated with Big Data – a company has so much information that morality, ethics, and even the rule of law are subsumed to analytical realities.  Let’s fast forward ten years into the future.  Big Data is 10,000x more advanced.  Companies use it to measure and manage customer satisfaction in every facet of its organization.  An imaginary company, BigCorp, is reviewing customer service costs.  After correlating data from Facebook and its own returned merchandise receipts, it has found that Chinese consumers are 60% more likely to complain on the internet during a product return than everyone else.  This information is an algorithmic compendium of data captured from credit card transactions, age/sex/racial data compiled from loyalty programs, and negative feedback from Facebook posts, tweets, and employee-documented information from the return itself.  Consequently, a policy is issued for customer service departments of BigCorp located in Chinatowns of major cities to ensure that the return process is quick and painless.  Well, as someone who is not from China, I don’t think that seems fair.

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The Seven Deadly Sins Of Enterprise Data Quality

Here’s another angle: let’s say BigCorp determines that white, under-30 females in Louisiana complain on the internet about returns only 15% of the time.  Sales data suggests that most returned products are baby carriages, baby onesies, and women’s shoes.

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