If you’ve been to school, you’ve been socialized. If you were raised in a family, you’ve been socialized. If you’ve watched TV for any period of time, you’ve been socialized.
What does that mean? It means that you’ve come to find certain assumptions, beliefs, “facts” and perhaps values to be accepted, subconscious — true without giving it much thought or challenge.
If you’ve been to business school, or trained in any form of academic or professional discipline, you’ve really been socialized. You’ve likely accepted certain concepts to be true or fundamental, consciously or unconsciously. Thus your view of the world is transformed, and you develop a filter through which you take in and process information.
It’s OK. You’re not alone. In fact, by its nature, socialization gives you common ground to connect with many others who “assume” what you do.
But, there’s a catch. The assumptions may significantly limit your ability to learn about the world around you.
By way of example — one the most profound tenets of business thinking today (born of the early 20th century, scientific management theories popularized by Frederick Taylor) is the idea that quantitative data about people and their behavior can and should drive business decisions. If you doubt this, Google “big data.” You will see how “big” this phenomenon is, and consequently how ingrained is the notion that if some quantitative data about customer behavior are good, more are better. But is it really?
Let’s see if we can’t break this down a bit.
So, one of the central engines to using big data to understand consumer behavior is predictive analytics. Predictive analytics essentially works on the principle that if you have information say, in 29 columns for a record in a data file, you can accurately predict, based on a model, what will be in column 30. For example, the first 29 columns are numbers representing things like a homeowner’s height, weight, age, education level, and TV viewing habits and column 30 is a Y/N of whether he will default on a loan in the first five years. What’s in column 30 is essentially a recommendation of whether or not to approve the loan. Column 30 could just as well be a number estimating — again, with accuracy — whether that same homeowner will buy a car next year, or will live past 73.
The same “big data,” predictive analytics-infused processes today help businesses decide how to target their ads, recommend their products, and design their “get out the vote” campaigns. Look for yourself — the tagline for IPSOS, the world’s largest market research firm, is “Nobody’s Unpredictable.” In other words, human behavior can actually be conceived of a series of patterns that, once discerned, reveals the secrets to what mankind is likely to do next.
This stunning capability naturally gives rise to an equally provocative question: so what?
I don’t mean, “so what’s next?” I mean, “so, big deal.”
Don’t get me too wrong. I love numbers. I love quantitative analysis. I often snack on a good regression line. But consider: Quantitative data’s idea of why people do what they do is “look, here’s a statistically significant — and predictive mind you — relationship between these two variables. And we’ve subjected this observation to multiple statistical tests which validates that this relationship does not occur by chance and is not the result of some other potentially confounding relationship. Aha – that means that variable 1 (or possibly 1a, 2a, and 3a) is why variable 2 is doing what it is doing! Aha!”
Quantitative explanations are so neat, tidy, right-there-in-the-numbers that they’re hard to resist. Very hard to resist if your job depends on being “right.”
So what is the problem? (See what I did there — I embedded the “so what” into that transition question. I kill myself! But I digress.) The problem is that quantitative analysis, when applied to human behavior, tells you the “what” of the behavior. It rarely, if ever, is capable of telling you “why.” It can’t. Human beings (and here comes an assumption inherent in my socialization that you can choose to accept or reject, er, be right or wrong about) construct their world and its meaning based on social experience that is constantly dynamic and constantly in flux. The meaning of the choice a human being makes is contextual and rather personal.
Apologies to IPSOS and their creative agency — everybody’s unpredictable.
If you don’t believe me, tell me why a person defaults on a home loan. You may be able to tell me what circumstances surround or accompany most of the defaulting parties prior to and at the time of default, but I’m pretty sure you can’t use numbers to tell me why an individual will or did default. It’s not in the numbers. And neither is why people buy products, select movies, or decide to do business with you (or not if you keep blindly relying on those numbers to understand them).
So why isn’t what good enough? Why do I need to know why someone does something?
Think about anything you have valued in your lifetime. Think about anyone who may have valued you. Which question played a bigger role in your experience — What? or Why? Answer this, and you’ll know whether you are socialized into the social world in which we now find ourselves. You’ll also get a sense of which businesses may survive to see the next era.
And if you think long enough, you’ll realize why I’m alternately self-indulgent, self-righteous, and snarky when discussing this topic. Then maybe you can sell me something.