Data is like deep fryer refuse, not oil. People closest to the data can refine it.

Data is like deep fryer refuse, not oil. People closest to the data can refine it.

Data is Not the New Oil - More Like Deep Fryer Refuse

The Grim Reality

Let's burst that bubble: Most data is far from being the light, sweet crude we were promised. Think less "Spindletop gushes riches" and more "last night's deep fryer leftovers." That goopy, lumpy mess of data most have? It's filled with impurities and inconsistencies. Seriously, if data were oil, it would be lumps of tar in a soup foul spillage.

A Sober Reckoning

Now, let's take a hard look at where you stand. I’m betting only a handful in your organization, probably the tech-savvy folks buried in the trenches, can distinguish the gold from the garbage. Clarity often begins at the bottom of the org chart. Yet, leaders frequently miss the forest for the trees—they don’t know where to dig, how to engage, or even what questions to ask.

Our increasing awareness of our business mortality hits home. That tranquil period of Zero Interest Rate Policy (ZIRP) was a lullaby we now must wake from. It’s time to face reality.

No Mary Poppins for Data Cleanup

Tossing your data into the AI pot won't magically transform it into a treasure trove of insights. Best case, you'll get a machine that's slightly better than your average high school senior at writing grammatically correct sentences. Worst case, it's all smoke and mirrors with no lasting value.

Rolling Up Your Sleeves

Here’s the deal: the transformation begins with your own people. Engage with those individual contributors at the bottom of the org chart—the ones who are knee-deep in where the data is born. They'll help structure, clean, and contextualize your data, turning that lumpy fryer oil into high-grade crude.

And let's not sugarcoat it: it’s a refining process. Skipping this part is like trying to ace a college course without ever cracking open a book. The students who walk into the lecture prepared are the ones who truly grasp the material.

In short, there’s no snapping of fingers for pristine data sets. It’s a grind, a journey that starts from the ground up. But trust me, this groundwork sets the stage for any AI wizardry you may want to pull off down the line.

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