Predictive Analytics: Reinventing industries – predictive game-changer
By Eric Siegel
Despite all the advanced technology lining your pocket, car, home, workplace and even the proverbial cloud floating virtually above your head, the world is a remarkably inefficient, wasteful place. The organizations that make the world go ‘round, the companies, agencies and hospitals that treat and serve us in every which way, constantly get it wrong. Marketing casts a wide net; junk mail is marketing money wasted and trees felled to print unread brochures. Institutions are blindsided by risky debtors and policyholders. Fraud goes undetected. And, critically, healthcare could use all the prognostication it can get. These are heavy costs that tax both you and I in various ways every day. If only there were some way to run things better, to improve the effectiveness of the frontline operations that define a functional society.
Upgrading the World
Predictive analytics serves that very purpose by driving mass-scale processes empirically, guiding them with predictions generated from data. Millions of predictions a day improve decisions as to whom to call, mail, approve, test, diagnose, warn, investigate, incarcerate, set up on a date and medicate.
In this way, predictive analytics reinvents how our world’s primary functions are executed, across sectors. It boasts an intrinsic universality: A great, wide range of organizational activities can be improved with prediction by way of predicting the behaviors and outcomes of people, including individual customers, debtors, patients, criminal suspects, employees and voters. It’s that generality that makes this technology so potent and ubiquitous.
So it comes as no surprise that predictive analytics is booming. The No. 1 skill on LinkedIn’s “25 Hottest Skills That Got People Hired in 2014” is “statistical analysis and data mining,” and No. 6 is business intelligence. While most of the other skills listed are forms of engineering/development (programming, etc.), the meat of the matter – the stuff of business – is what data itself tells us, rather than the infrastructures built to collect and store data.
Prediction makes our planet rotate a bit more smoothly. For example, click on the links following any of the following six industries to see case studies of this effect:
- Marketing: predictive remarketing
- Financial services: Paychex, Chase, insurance study
- Workforce management: Walmart, Wells Fargo, via Facebook data
- Healthcare: predictive medicine, 5 reasons predict death, New book by Miner et al.
- Manufacturing: 4 predictive apps big data improves mfg, predict mfg equip fail, car telematics for…
- Government: gov’t apps—overview, IRS fraud detection, city of Chicago, disaster response in VA
Each case is executed by way of predicting an outcome or behavior (e.g., click, buy, quit your job, default on a loan or die), and those predictions drive operational/treatment decisions (e.g., remarket to, call, give a raise to, decline credit to, or apply a medical procedure on).
Predictive analytics is a game-changer; it’s like “Moneyball” for money.
As predictive analytics’ adoption widens and deepens across sectors and across organizational functions, an inter-industry synergy emerges. Stories are shared between sectors, and the lessons learned and proof-of-concepts viewed from neighboring industries inspire and catalyze growth, creating a cycliceffect.
And that is what the “big” in big data really means – big excitement and big impact.
Eric Siegel, Ph.D., is the founder of Predictive Analytics World, author of “Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie or Die” and executive editor of the Predictive Analytics Times. For more information about predictive analytics, see the Predictive Analytics Guide.
Note: This is an edited version of a longer article, “How Predictive Analytics Reinvents These Six Industries,” that appeared in Information Management. Reprinted here for promotional considerations.