Eric Siegel, Ph.D. is the founder of the Predictive Analytics World conference series—which includes events for business, government, healthcare, workforce, manufacturing, and financial services—the author of Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die—Revised and Updated Edition (Wiley, January 2016), executive editor of The Predictive Analytics Times, and a former computer science professor at Columbia University. For more information about predictive analytics, see the Predictive Analytics Guide.
Eric Siegel: Predictive analytics is technology that not only gives organizations the power to predict the future but also to influence the future. And the reason it has that difference is because predictive analytics predicts for you, me, everyone – one person at a time whether you’re gonna click, lie, buy, die; whether you’re gonna default on your credit card statements; whether you’re gonna commit an act of fraud; whether you’re gonna vote for this presidential candidate or that presidential candidate. And because the predictions are on that level – and that’s really the defining characteristic of this technology of predictive analytics - it enables organizations to improve their operations – to operate more effectively. That’s what defines a functioning society is how all these organizations are serving you, interacting with you, treating you, contacting, not contacting you, medically treating you, campaign volunteers are knocking on your door, insurance providers approve or don’t approve your application.
It’s per person. So you’re being predicted and it’s important for people to understand that, that your actions, your behavior and your medical outcome for example, those types of futures for each individual person are being predicted and in some cases the thing being predicted is sensitive. So beyond sort of all the information that they have about you at organizations, right – companies remember. They don’t have very much incentive to delete data. It’s incredibly cheap to store data. So they’re just tracking all these transactions. Anything they accrue, information about you and I and consumers and health care patients and everything are valuable. They just keep storing it and they can now use it to learn from it. So, for example, large corporations such as Hewlett Packard predict for each employee are you likely to quit your job. And they’re beginning to deliver those predictions to the manager of individual employees.
The retailer Target predicts which female customer’s pregnant in order to target marketing that’s related to having a baby. In law enforcement, crime predicting computers predict is an incarcerated felon likely to commit crime again upon release. That’s called recidivism. And those predictions are used by judges when making decisions about sentencing and by parole boards when making release decisions. So they’re literally consulting to crime predicting computers as trusted advisors that help inform and make the difference in some of the decisions that are made about how long somebody stays in prison.
So there’s no simple answer. This stuff is very powerful and as Spiderman’s wise uncle said, “With great power comes great responsibility.” So the implementation and deployment of this technology is a win-win in most cases. But there’s other cases where we need to spread the awareness about what’s being done to help inform the dialog so that we can collectively make informed decisions and debate in an informed way around these issues.
Directed / Produced by Jonathan Fowler and Elizabeth Rodd
Prediction is in the cards. Here are four major developments you will experience in 2016 courtesy of predictive analytics.