Man. Big Data is in everthing, everywhere, every time. Yet, I am underwhelmed with the persuasion possibilities of this New New Thing, for a variety of reasons. First, seldom do you need more detail to plan, execute, or evaluate persuasion. Second, you already know more than you need to know for almost all persuasion Locals. Third, failure stems more often from your errors, typically driven by vanity or convenience, not from a lack of data. Fourth, Big Data is as squishy as an Oprah cry-fest on a sofa. Fifth, well, this is just piling on, but I’ve got to add one more.
There’s no definition of the term.
How can you possible do something effectively or even ineffectively when no one agrees on what that something is today. Consider these two stories from the WSJ, a leading Big Data cheerleader. The first explains how Big Data hires workers. The second demonstrates how Big Data pays workers. It’s Big Data replacing the Human Relations guys.
For more and more companies, the hiring boss is an algorithm. The factors they consider are different than what applicants have come to expect. Jobs that were once filled on the basis of work history and interviews are left to personality tests and data analysis, as employers aim for more than just a hunch that a person will do the job well. Under pressure to cut costs and boost productivity, employers are trying to predict specific outcomes, such as whether a prospective hire will quit too soon, file disability claims or steal. Personality tests have a long history in hiring. What’s new is the scale. Powerful computers and more sophisticated software have made it possible to evaluate more candidates, amass more data and peer more deeply into applicants’ personal lives and interests.
So, now Big Data is a task that is computerized rather than interpersonal. This story reports procedures that have been in place at least since World War I (that’s 1917, kids, nearly 100 years ago) when psychologists convinced the Army to use IQ tests to classify and assign GI’s. Back then all the testing, analysis, and assignment was done by hand. Now, do the same thing with computers and you’ve got Big Data!
Now, with Big Data as paymaster. Just read the headline and lede.
Again, Big Data is doing everything that has already been done just with new words like Analytics or Predictive Analytics or Deep Analytics. And, it requires uncommonly smart geeks with rare training in . . . multiple regression!
There is absolutely nothing new in these Big Data stories. Old, established, tried, proven, and forgotten techniques for hiring and paying people to do work are presented as a New New Thing with only a new label, Big Data, as the difference. Hey, that just General Semantics: Confuse the Thing with the Word.
Now, as a persuasion guy, I appreciate the play that employment consultants are running here. They are using smoke and mirrors to get earnest and naïve WSJ writers to extol their virtues to potential customers. It’s a great persuasion play: Get Them To Say It For You. Yet these consultants, at least according to the stories, do nothing they haven’t already done except provide the promise of Big Data to solve two of the biggest headache every work organization has: Hiring and paying workers. If the Other Guys are stupid enough to fall for Big Data rather than Mployment Metrics, then I get the persuasion and more power to you.
However, I would caution that selling smoke and mirrors when the Other Guys think they are buying persuasion may be a long term losing play. But, when your Big Data Deep Analytics delivers no difference compared to the old Hire ‘Em and Fire ‘Em, the Other Guys may see the smoke in the mirror.