For instance, banks worry about their customers divorcing because divorcing causes to change their credit worthiness. Marissa Mayer (former VP of Google, current CEO of Yahoo) metioned credit card companies predict that you are going to get divorced before two years. Surprisingly, they have 98% prediction accuracy.
In short term, divorcing tendency might be detected if the husband buys new perfume and flowers or he starts to go oftenly outside for dinner. However, he even would not know that he is going to be divorced in two years.
Similarly, parents of a teenage girl have case with Target, american supermarket company. Parents are angry with Target because their teenage girl got a pregnancy related gifts / coupons. They believe that Target encourages teenage girls getting pregnant.
Target actually detects some shopping patterns for pregnant customers. Target noticed that pregnant women tend to buy unscented products such as soap and lotion. Also, they load up on supplements like calcium and magnesium. Target analyzes shopping baskets of customers based on these examples and predicts a pregnancy score. Thus, coupons are given as a gift for most probably pregnant customers.
Although the company initially apologized parents for the coupon delivery, it is finally figured out that teenage girl was really pregnant.
In addition, there are people who compared data and oil. Peter Sondergaard (SVP, Gartner) mentioned that information is the oil of the 21st century, and data science / analytics is the combustion engine. Comparing data and oil might be utopian but last researchs reveal how important data is for enterprises. Today, an enterprise earns 13 dollars for every dolar spent. Moreover, a survey on 2K executives (in 9 industry and 15 countries) shows data science / analytics is the most critical digital technology for their organizations (after then, cloud and mobile are ranked repectively).
On the bright side, studies on this discipline are implemented under equals terms and fairly. Peter Norvig (Research Director, Google) declared they don’t have better algorithms, they just have more data.
For instance, a belgian woman plans to drive 50 miles away from her home but she drives almost 850 miles more because her GPS instruct her to do. During the driving, she passed through 3 countries; Germany, Austria, Slovenia and finally arrived Zagreb, Croatia. The driving lasts 2 days and she had to get oil twice. Moreover, she naped a few hours on the side of the road. Furthermore, she also have minor traffic accident. Finally, she figured out something going wrong when she could not read the traffic signboards.
So, are you convinced that we’ve superpowers?