One of my favorite cultural tropes has to do with one of my favorite writers, Philip K. Dick, and his work Minority Report (also adapted as a blockbuster movie, with Tom Cruise and directed by Stephen Spielberg). The storyline essentially deals with law enforcement having the ability to predict a crime before it happens (and arresting a suspect before he or she becomes a suspect!).
Predicting behavior before it happens: a trope many beyond the authorities would like to see as a reality—certainly in the corporate world where management eternally clamors to market research departments for the ultimate crystal ball.
In our tech era it seems science fiction is regularly an actuality, and predictive analytics is being considered as the (next) ultimate crystal ball.
Is it? What exactly is predictive analytics?
First, it should be mentioned that in order to be prescient, predictive analytics needs to be paired with big data (a tech buzzword that, like the word “gluten” in the food industry, many still don’t know what it is). Big data is basically information too unwieldy to be addressed by traditional databases and software. Massive data centers that look like the inside of the Death Star are required to store big data. Often the firepower of the Death Star is necessary to process big data.
I like how a tech expert simply defined big data:
It’s all about sorting variables and tracking them, piecing together things that humans can’t. Computers are very good at sifting tremendous quantities of information (with the right software, of course), and that’s the core of big data.
More or less going back to science fiction, in order to understand predictive analytics, picture all the digital numbers cascading down in The Matrix, with the business world attempting to be Neo after his resurrection. So far not many in business have become “The One” in their efforts to corral big data into consumer meaning.
Morpheus might actually represent predictive analytics, though, the carrier of the Red Pill to tap into big data. According one source, predictive analytics is:
Predictive models and analysis are typically used to forecast future probabilities. Applied to business, predictive models are used to analyze current data and historical facts in order to better understand customers, products and partners and to identify potential risks and opportunities for a company. It uses a number of techniques, including data mining, statistical modeling and machine learning to help analysts make future business forecasts.
In essence, it appears this is something close to the ultimate crystal ball. In the Huffington Post’s Can Big Data Save World? the author illustrates the potential in the marriage of big data and predictive analytics:
Online retailers not only know what you bought, they know what you considered buying (viewed); where you came from (prior URL); what path you took through their site; what you finally bought; and how you paid for it. They can even suggest products that appeal to your personal tastes and interests. In other words, they now have the information to create a unique shopping experience just for you.
Seems the Oracle instead of Morpheus might be a better illustration of predictive analytics (and if big data can’t save the world, at least we still have The Avengers). In fact, the company Oracle already provides predictive analytics software (as do Microsoft, IBM, and Microsoft), as well as other smaller companies in what is a blooming market.
Here are some other ways other major players in the tech world are using predictive analytics to augur your very future:
Google: from trying to finish what you’re typing in the address bar with autocomplete, to selling its proprietary software platform, this company spends a lot of time kissing everyone’s kismet.
Facebook: Not a surprise to see this name as well, for your News Feed is all about knowing what you want to read at before even logging in. As an article in Forbes reported, researchers have concluded that Facebook “could predict our personality more accurately than most of our close family, friends, and maybe even our therapist.”
The Video Game industry: Okay, not surprising either, considering the amount of information that gets injected into the various companies from an industry that is larger than Hollywood. As an example, one source stated that:
EA games generate a whopping 50TB of data per day. This data is in the form of gameplay data, micro-transactions, time stamps, in-game advertising, multi-player information, and much more.
The piece concluded that video game companies “see the huge opportunity to customize gameplay, find new ways of monetizing games, and even enriching the gaming experience by making it social.”
All of this may indeed sound futuristic, and perhaps bordering on Orwellian, but the reality is that predictive analytics has been going on since someone told someone not to eat a fruit because they might venture on a fig-leaf shopping spree. Market research has been in the prophecy business for generations, crunching numbers in various capacities to understand consumer conduct.
As one MIT Professor put it, predictive analytics is basically “a way to predict the future using data from the past.”
All of us continually use the past to measure the future of those around us all the time, like during Thanksgiving with our families. The difference is that predictive analytics, along with big data, takes prophesying in a scope never seen before in the far reaches of the internet clouds. Not exactly science fiction, perhaps, but it certainly is a report that is not minor in any way.