I am going to break it to you gently: Despite all the advanced technology lining your pocket, car, home, workplace, and even the virtual cloud floating above your head, the world is a remarkably inefficient, wasteful place. The organizations that make the world go around, 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 can use all the prognostication it can get. These are heavy costs that tax us all 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 about 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 wide range of organizational activities can be improved by predicting the behaviors and outcomes of people, the futures of 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:
- Number one on LinkedIn’s 25 Hottest Skills That Got People Hired in 2014 is statistical analysis and data mining, and number six is business intelligence. While most of the other skills on the list 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.
- Research firms MarketsandMarkets and Transparency Market Research project that the predictive analytics market will reach $5.2 to $6.5 billion by 2018/2019.
Let’s look at the impact of prediction on six fields: marketing, financial services, workforce management, healthcare, manufacturing, and government.
A great deal of movement deploying predictive analytics is taking place within each of these industries, enacted by a wide range of companies for various purposes, each case executed by way of predicting an outcome or behavior – for example, click, buy, quit your job, default on a loan – and using those predictions to drive operational/treatment decisions, for example, remarket to, call, give a raise to, or decline credit to.
For example, Wells Fargo uses analytics to predict which job applicants will perform best and fit into its corporate culture. The federal government uses analytics to identify tax fraud. The city of Chicago has incorporated analytics into its inspections to attempt to predict and prevent events such as lead poisoning in children and rodent outbreaks. The state of Virginia is using predictive analytics to improve disaster response and recovery.
And it doesn’t stop there. Check out these other examples from the ever-widening range of industrial uses for predictive analytics:
- UPS uses predictive analytics to optimize delivery routes.
- Luxottica uses predictive analytics to maximize customer value and build long-term customer relationships.
- eBay is using predictive analytics to share customer segment information with business partners, and Redbox is using predictive analytics to better understand same-store sales at its 35,000 kiosks located throughout the United States.
As I put it to a relative over the holidays, 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 – the lessons learned and proof-of-concepts viewed from neighboring industries inspire and catalyze growth. There’s a cyclic effect.
And that is what the “big” in “big data” really means – big excitement and big impact across industries.
To learn more about predictive analytics and how it is being put to use in industry, check out a Predictive Analytics World conference, coming in 2015 to San Francisco (see infographic at right for more information), Chicago, Boston, Washington, D.C., London, and Berlin.
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.
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