I'm going to break it to you gently. 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–specifically, by way of predicting the behaviors and outcomes of people, the future of individual customers, debtors, patients, criminal suspects, employees, and voters. It's that generality that makes this technology so potent and ubiquitous.

Market Growth

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 listed there 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.

Reinventing Industries

Prediction makes our planet rotate a bit more smoothly. Let's look at examples of this effect within six industries: Marketing, financial services, workforce management, healthcare, manufacturing, and government.

As the table below reveals, a great deal of movement deploying predictive analytics is taking place within each of these industries, as enacted by various companies for various purposes—each case executed by way of predicting an outcome or behavior (e.g., click, buy, quit your job, default on a loan, or die), and using those predictions to drive operational/treatment decisions (e.g., remarket to, call, give a raise to, decline credit to, or apply a medical procedure on). Follow the links within this table to check out in detail the areas that interest you most.   

Late-breaking examples of predictive analytics' deployment across six industries:

INDUSTRY:

ARTICLES:

VIDEOS ON DEMAND:

Marketing

predictive remarketing

PAW Business Oct 2014

Financial svcs

   Credit risk

   Insurance

 

Paychex, Chase

insurance study

PAW Business Oct 2014

risk modeling for insurance

Workforce mgmt

 

Walmart

Wells Fargo

via Facebook data

talk: Talent Analytics CEO

case: call center

Healthcare

 

predictive medicine

5 reasons predict death

New book, Miner et al

PAW Healthcare Oct 2014

Manufacturing

 

4 predictive apps

big data improves mfg

predict mfg equip fail
car telematics for…

benefits of analytics in mfg

Government

 

gov’t apps—overview

IRS fraud detection

city of Chicago

disaster response in VA

keynote (at an IBM event)

Related industry events. Mirroring this market growth, the Predictive Analytics World conference series (vendor-neutral – see www.pawcon.com) holds specialized events that focus specifically on the industries listed above: PAW Business (covers marketing, financial services, insurance, and beyond), PAW Workforce, PAW Healthcare, PAW Manufacturing, and PAW Government.

Conclusions–The Predictive Game-Changer

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.