There’s no shortage of articles in Forbes, Harvard Business Review, LinkedIn, and elsewhere telling HR departments that “Big Data changes everything!” The main thrust of these articles is HR needs to use “talent analytics” (as Big Data is known in HR) to better hire, manage and retain talent. I call this Big Data as a Tool because it’s where HR uses Big Data to do its job better. But the full benefits of Big Data are only available when HR recognizes and takes a leadership role in two other aspects of Big Data: Big Data as Culture, and Big Data as Outsourcer.
Big Data As Culture
Big Data as culture refers the disruptive cultural effects — both negative and positive — that Big Data can have on organizations. Specifically, Big Data will come to replace personal expertise and heirarchy (not so affectionately known as HiPPO) as the standard bearer for right and wrong. Get ready for the new kid on the team to contradict the boss … and have the new kid be right. And be able to prove it. Tension and bruised egos accompany all transitions, and HR’s adoption of Big Data is no exception.
And what’s happening in HR is happening in
Driverless cars — technically known as autonomous cars — are advancing so fast, I predict my 2 year old son will never learn to drive. He won’t have to.
As Bill Gates once said, “We always overestimate the change that will occur in the next 2 years and underestimate the change that will occur in the next 10.” In this case, we’re talking 14 years, when my son will be 16. As I explain below, I believe that, by the time he’s allowed to learn to drive, over 50% of cars sold won’t need a driver. Heck — why wait until he’s 16? I thinks it’s likely that he will have been “driving” — that is, travelling alone in an autonomous vehicle — since age 14 or 15.
Big Data On Wheels
Google is the most famous company working on autonomous cars. And rightly so. They were one of the first to identify autonomous cars for what they really are: Big Data projects, where the road is just another massive data source for computers to analyze and comprehend. It’s a complex process that, as I explain in my Big Data presentations, involves 3 of the 5 Big Data data types: geographic data, sensor data, and media data. Google is a market leader in this space not because they know how to build cars, but because they are exceptional
Once people find out that Big Data isn’t always about data that’s big (as Thomas Davenport and others have long observed), they ask me, “So why is it called Big Data?” And for a while, no one knew. But some original research by the New York Times’s Steve Lohr on the term’s origin reveals that the term may have never had much precision or accuracy.
According to the article, Big Data’s coiner (or, at least, early promoter) was John Mashey, Chief Scientist at Silicon Graphics in the 1990. Silicon Graphics was an early wrangler of massive data, mostly on behalf of two bleeding-edge graphics-intensive tech industries: Hollywood and the CIA/NSA. Mashey confronted massive data sets before almost anyone and, in 1998, was the first to use “Big Data” (at least publicly) in a presentation called “Big Data and the Next Wave of Infrastress“.
A Tale of Two Meanings
So what did Mashey mean by the term Big Data back in 1998? Well, you can review the 47-page presentation, as I did. Or, you can just ask Mashey, as Steve Lohr did (which is probably why Steve is a New York Times reporter and I’m not).
Forget The Hype — Focus on Lower Costs and Better Results
If you’ve been listening to the Big Data hype, you may have run across some of the following terms: Decision Support, Predictive Analytics and Machine learning. This is all so much clearer with an example, so let’s just start with the example, and then return to definitions at the end. Let’s do a credit card example.
To listen to the hype, you’d think “Data Driven” was better than sliced bread. And it just might be. But, becoming data driven can also reveal…
…profit-killing departmental infighting
…deep-seated employee resistance to change, from the bottom all the way up to the top.
THE REALITY: Becoming data driven is more about people than people realize. I know. I’ve spent decades introducing new technologies to companies, making them more innovative and more efficient. Real change comes with bruised egos, realigned politics and the occasional defection.
Here’s an example from my own work: