Originally published in Information Management
Predictive analytics is a game-changer — it’s like “Moneyball” for… money. This article summarizes and links resources with late-breaking coverage of how predictive analytics reinvents six industries.
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.
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.
- Research firms project the predictive analytics market to reach $5.2 to $6.5 billion by 2018/2019 (MarketsandMarkets and Transparency Market Research).
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 of resources 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.
Articles, videos, and events with late-breaking coverage of predictive analytics’ deployment across six industries:
|INDUSTRY:||ARTICLES:||VIDEOS ON DEMAND:||EVENTS IN 2015:|
|Marketing||predictive remarketing||PAW Business Oct 14||*PAW Business (5 events)|
|PAW Business Oct 14
one on insurance
|PAW Business (5 events)
(5 sessions on insurance)
via Facebook data
|talk: Talent Analytics CEO
case: call center
|PAW Workforce (March)|
why predict death
New book, Miner et al
|PAW Healthcare 2014||PAW Healthcare (Sept)
PAW SF – March:
Chicago Dept Pub Health
intro training workshop
|Manufacturing||4 predictive apps
big data improves mfg
predict mfg equip fail
car telematics for….
|analytics in mfg||PAW Manufacturing(June)|
IRS fraud detection
city of Chicago
|Siegel keynote (IBM)||PAW Government (Oct)|
*PAW stands for Predictive Analytics World (vendor-neutral conference series). In response to market growth, PAW has expanded to 9 annual events and has launched specialized events that focus on the specific industries listed above.
There’s More: Innovative Predictive Applications
It does not stop there. Check out these other examples from the ever-widening range of industrial uses.
Recent articles covering innovative predictive applications:
- Shipping and routing optimization at UPS
- Predictive resource allocation at Cisco–matching individual support cases to in-house engineers
- Proactively averting bad things:
- Detecting insider threats
- Maritime safety (what factors predict whether a boat will sink?)
- Detecting homes with high risk of child lead poisoning
- Predicting risk at the Veterans Health Administration
- Cheating detection in online games–Activision’s “Call of Duty”
- Cheating detection in salesforce operations–see the example within this interview of a leading consultancy
… and as things warm up for the 2016 presidential election, speculation on the use of predictive analytics will emerge, given the way in which Obama for America 2012 used predictive analytics to target campaign activities.
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.
Some Extra Bits
Resources with which to explore advanced and emerging methods:
- Article: Uplift modeling–How to Drive Influence by Crunching Numbers
- Video: Overview of John Elder’s training workshop
- Conference: Text Analytics World
Getting-started resources for newcomers:
• The Predictive Analytics Times Executive Breakfast
• The Predictive Analytics Guide
• Infographic: Predictive Analytics World by the numbers