Data: It’s the people, stupid!

superfreakonomicsThey overplayed it a bit, but I love the Freakonomics brand. I’ve read most of the series, but somehow missed SuperFreaknomics, which I am reading now.

The authors consistently mention the “economic way of thinking,” something so relevant to today’s data-driven business environment.

The top five political economy firms don’t hire like the top five accounting firms

My undergraduate economics was heavy on political economy and the history of economic thought. You know, the kind of stuff employers crave. (Not.)

I wondered why I didn’t major in something a little more applied, like accounting or finance. It took some transitioning to the world of databases and financial models. Fortunately, I’m cataloging this journey in an online course, out soon!

But now that I am coming out of the wilderness, after years of taming data, I am beginning to value my political economy foundation much more. 

There’s no accounting for taste modelling for behavior

I’m grateful for this liberal education because it reminds me of the central tenet of business and economics: human behavior matters, and it can be really hard to model. 

We’re in a time where we have much more data than we can process. Analysts famously spend the majority of their time blending data from various sources and preparing it for analysis. This will soon seem as antiquated as a rotary phone.

What won’t go “out of style” is the lesson from the above quote. All this data is great. And it’s great to know how to store and prepare it effectively.

But it’s important to remember the end goal of business is to satisfy a customer’s demand. To do this we must understand the causes and effects of human behavior, seen and unseen. Framing the problems and asking the questions are difficult. There’s more to human behavior than bits and pixels.

Here’s where my Hillsdale education is key: after cutting through the weeds of complex data, my economics grounding turns it into something more than a heap of numbers. It helps me frame the problem and not pick up false confidence in my model.

To be fair, one half of SuperFreakonomics is a PhD economist, so he does a good portion of quantitative modelling. But the pair understands the importance of observing and questioning and thinking about human behavior, not just moving numbers around for the sake of it.

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