Growing up, my siblings and I were absolutely nothing alike, nor did we become more similar to one another as adults. I was the nerdy kid who eventually went into computers and aerospace. My brother was the outdoorsy one, and my late sister was the one with all of the fancy degrees, and who eventually went on to become a mental health professional. Believe me when I say that I always assumed there was absolutely no chance that our career paths would ever cross. After all, my sister didn’t exactly have a deep understanding of the way that computers work, nor am I even remotely qualified to be prescribing Thorazine to someone who is experiencing psychotic episodes. Even so, I can’t help but wonder if we are about to see a strange career path convergence: Is psychologist the next hot IT job?
So, are future IT pros going to be required to hold a psychology degree? I have to admit that the question sounds like a bad joke. Even as I typed the question in the previous sentence, my mind instantly flashed back to the days of working helpdesk support early in my IT career, and to all of the seemingly emotionally disturbed callers who clearly “needed help.” As tempting as it may be to delve into stories of some of the stranger interactions that I have had with end users over the years, I’m not going to go there. In fact, my question over whether mental health professionals are about to be in demand in the world of IT is absolutely serious. In fact, it is already happening.
For me to be able to adequately explain why some IT shops are suddenly hiring psychologists, I have to talk a little bit about the current state of the tech industry. As you are no doubt aware, one of the biggest tech trends from four or five years ago was the so-called Big Data revolution. At the time, Big Data was really nothing more than a somewhat meaningless buzzword referring to the accumulation of large volumes of data. Over time however, the phrase “Big Data” slowly began to morph into “Big Data analytics.” Suddenly, it wasn’t so much the volume of data that really mattered, as what you could do with that data.
I have often said that the IT department’s job is to use technology to solve business problems. Big Data analytics might just be the perfect illustration of this philosophy. A company’s data is a tangible asset, and the entire science of data analytics is devoted to deriving useful, and often hidden, meanings from the data to help the business to flourish.
OK, that’s all good and well, but right about now I’m sure that you are probably wondering what any of this has to do with mental health professionals being recruited into IT positions.
Data does not lie — or does it?
Back in college, I remember one of my Computer Science professors saying that data does not lie. I think that this statement was probably true at one time, but today things are different than they once were. Data might not outright lie, but it can be very misleading. This is especially true for an organization that is mining vast quantities of data in an effort to derive hidden business value.
The problem with looking for hidden meaning within a large data set is that often times it leads to the discovery of trends that are circumstantial and are not firmly based in reality. Let me give you an example.
Imagine for a moment that a particular company manufactures widgets, and that the company decides to analyze its data to try to figure out the circumstances under which customers are purchasing the widgets. After careful analysis of the data, a trend emerges that shows that on the second Tuesday of each month, customers in Kentucky and North Dakota tend to purchase blue widgets, when the color selection is more evenly distributed at all other times.
Unless the Kentucky Wildcats (whose team colors are blue and white) happen to play their games on the second Tuesday of the month, this is probably a junk statistic. The statistic might be accurate with regard to what the data is saying, but it does not reflect the nature of human behavior. I mean let’s face it: Nobody wakes up in the morning and says, “Hey, it’s the second Tuesday of the month, so I better go buy a blue widget.” The trend might exist, but it is probably a coincidence. If additional data is allowed to accumulate over a longer period of time, then the data would probably show that widget color selection on a particular day of the month is actually random.
Being too focused
Even though this particular example is made up, it is loosely based on a real-world situation that I recently heard about. In the real story, the data scientists who were working for a particular company kept finding trends within the data that didn’t really coincide with the way that things work in the real world. This isn’t to say that the data scientists were stupid. I’m sure that they were all intelligent people. It’s just that when you are studying data, it is possible to become so focused on the data itself, it is easy to forget that the data corresponds to events taking place outside of the datacenter.
The problem with this, of course, is that no company performs Big Data analytics just for the fun of it. The ultimate goal is to be able to use the data, and the trends that have been derived from that data to make better business decisions. So with that in mind, imagine what would happen if the company from my previous example decided to manufacture a bunch of extra blue widgets and ship them off to Kentucky and North Dakota. That would probably prove to be a bad business decision. The trend that was spotted within the data was based on a coincidence, and does not reflect a repeatable pattern of behavior. As such, a company that tries to capitalize on this trend would most likely be stuck with an oversupply of blue widgets that nobody is buying.
Recently, I have actually heard of a couple of companies hiring psychologists as a part of their data analytics teams. Although the psychologists might not have a background in data analytics, they do have a background in human behavior, and may therefore be able to help the data scientists to better distinguish between an actual business trend and a junk statistic. In some cases, psychologists may even be able to help the data scientists figure out what sorts of data patterns they should be looking for.
New way of doing things
In my opinion, the most interesting thing about IT shops beginning to hire psychologists is that it reflects a new way of doing things. Although saying this might be taken as heresy, I think that the successful use of psychologists on data analytics teams clearly demonstrates that there is a place for nontechnical people in IT. Don’t get me wrong, I would never condone bringing some random person in off the street and letting them run the entire datacenter. However, I wholeheartedly believe that IT can benefit from bringing in people with specialized skill sets that don’t necessarily mesh with traditional IT shops. It will be really interesting to see the direction that IT goes from here.
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