Make an Impact: Three Words to Irrelevancy

COL01x - feature image for algminI get it. Creating data value is challenging under the best circumstances—and frankly, most of us aren’t in perfect situations. We have ambiguity, poor data quality, old systems, and never enough resources. It’s up to us, the data leaders, to find a way through it all and make data value happen!

While working in data I meet a wide range of folks who care about the data value mission, and are completely willing to do whatever it takes to achieve their data goals. These people are often leading their company’s data management or governance efforts, or they may be consultants like me. The data community is a welcoming world that is full of high-performing professionals that are incredibly good at what they do.

I love to talk shop, and hearing other peoples’ data stories can be riveting (really!). Sometimes, however, I run into someone who says the 3 words that make my skin crawl like no other:

“I’m not technical.”

You may think that’s not a horrible thing to say—the fact is that some people aren’t very technical: either their roles are more business-oriented, or they are engaging with data at a level of abstraction that allows them to use technology without diving in too deeply.

There is nothing wrong about not needing to be technical in our work! Plenty of influential data management and governance experts have no need to ever dive into the code. Then why does it bother me so much?

The mentality of considering oneself “not technical” effectively shuts down curiosity, or that person’s ability to fully understand the circumstances in which they find themselves.

When we label ourselves, we give the world (and ourselves) a simplified contextual understanding—signaling the evaluation is complete and that there is nothing more to look at. Why would we ever want to do that when presented with a clear opportunity to learn? After all, the only time someone says “I’m not technical” is when they are confronted with something they do not understand.

Here’s a secret: all technical people were once not-technical.

We all saw, at some point in our lives, something we didn’t yet understand and determined that we would somehow figure it out. It often involved picking up large books with small print, or more recently, searching Google for answers. It’s not magic, and we certainly weren’t born that way. And nobody knows it all, despite how we sometimes talk.

Being technical isn’t something we are, it is something we do. It is about solving problems using any tools available to us. With data, we have to recognize that every productive thing we might accomplish has some technology component to it. To make the most data-driven impact possible, we must learn to use technology to our every advantage. Sometimes that means rolling up our sleeves and getting into the details.

When doing technical work, I spend most of my time frustrated and feeling like I have no idea how to do what I’m trying to do. Then I eventually figure it out, and I am both proud and frustrated that I didn’t figure it out faster, and now I need to go figure out some other crazy thing I have no idea how to do. And repeat.

I cannot imagine it being much different for any technical person. But the funny thing is that, though that cycle seems a little depressing, at some point you realize that you can somehow solve any problem you choose to confront. This confidence is earned, and when you know you can rely on it as part of your tool belt, it feels pretty incredible.

This gets back to why I get upset hearing non-technical folks talk about being non-technical. To me, they are quitting before they even try.

When confronted with problems of any kind, we have simple fundamental reactions to choose from: freeze, flight, or fight. When it comes to data, if you are reading this, you may be the person who ultimately needs to get the problems solved. I’ll completely agree that the business challenges are paramount—but capable technology is also essential in solving most of our data problems.

Data leadership is about creating the most data value possible, and we as data leaders must use every means available to achieve it. We solve problems, and not just the convenient ones in the tidy boxes. Our companies need us to succeed, or they simply won’t be around for much longer. When the conversation turns technical, do not avoid the topic, say “I’m curious” instead—and find a way to solve the problem.

And until next time, go make an impact.

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Anthony Algmin

Anthony Algmin

Anthony J. Algmin is the Founder and CEO of Algmin Data Leadership, a company helping business and technology leaders transform their future with data. His book, “Data Leadership: Stop Talking About Data and Start Making an Impact!” is available now at

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