5 Reasons to Not Care About Predictive Analytics

predictive analytics 5 Reasons to Not Care About Predictive AnalyticsTechnology: complex and alienating, or promising and fascinating?

I’ve seen plenty of people roll their eyes and give all sorts of reasons they don’t pay much attention to predictive analytics, the increasingly common technology that makes predictions about what each of us will do—from buying, thriving, and donating, to stealing and crashing your car. Here are 5 reasons to go ahead and ignore this prognostic power… or not—you may choose to pay close attention after all.

1. Predictive computers don’t affect me. Not true. You are predicted every day by companies, government, law-enforcement, hospitals, and universities. Their computers say, “I knew you were going to do that!” These institutions seize upon newfound power, predicting whether you’re going to click, buy, lie, or even die. Their technology foresees who will drop out of school, cancel a subscription or get divorced, in some cases before they are even aware of it themselves. Although largely unseen, predictive proaction is omnipresent, determining whom to call, mail, investigate, incarcerate, set up on a date, or medicate.

2. Corporations invade privacy with data and prediction. This is sometimes true. Predicting human behavior is a new “super power” that combats financial risk, fortifies healthcare, conquers spam, toughens crime-fighting, boosts sales, and wins votes. Organizations gain this power by predicting potent yet—in some cases—sensitive insights about individuals. Companies ascertain untold, private truths—Target figures out that some customers are pregnant and Hewlett-Packard deduces who’s about to quit his or her job. We must each make our own judgment about judges and parole boards who rely every day on crime-predicting computers to decide who stays in prison and who goes free.

3. Prediction is impossible. Not so fast. Nobody knows the future, but putting odds on it to lift the fog just a bit off our hazy view of tomorrow—that’s paydirt. Organizations win big by predicting better than guessing, and they are continually cranking up the precision of predictive technology. Per-person prediction is the key to driving improved decisions, guiding millions of per-person actions. For healthcare, this saves lives. For law enforcement, it fights crime. For business, it decreases risk, lowers cost, improves customer service, and decreases junkmail and spam. It was a contributing factor to the reelection of the U.S. president. Predictive analytics is one of this century’s most important emerging applied sciences.

4. Science is boring—I drive a car but I don’t care how it works. Think again. Cars are simple: little explosions push them. But a computer that learns to predict? That’s a conceptual revolution. There’s an inevitable parallel to be drawn between how a computer learns and how a person learns that only gets more interesting as you examine the details of the machine learning process. It gets even more exciting when you see the heights this technology can reach, such as that achieved by IBM’s Watson computer, which defeated the all-time human champions on the TV quiz show Jeopardy! by “predicting” the answer to each question.

5. I hate math. That’s OK. You don’t need formulas to see how this fascinating science works. Predictive analytics learns by example. The process is not so mysterious: If people who go to the dentist most often pay their bills on time, this factoid is noted and built upon to help predict bill payments. At its core, this technology is intuitive, powerful and awe-inspiring—learn all about it!

Eric Siegel, Ph.D., is the founder of Predictive Analytics World (www.pawcon.com)—coming in 2013 and 2014 to Toronto, San Francisco, Chicago, Washington D.C., Boston, Berlin, and London—and the author of Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die (February 2013, published by Wiley). For more information about predictive analytics, see the Predictive Analytics Guide (www.pawcon.com/guide).




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Comments

  1. Ana August 14, 2013 at 11:17 am

    a very good article¡

  2. rusho August 14, 2013 at 10:47 am

    I also read your book about predictive analytics which is fascinating as well as inspiring.