Design vs. Darwinism. Data vs. Darkness.

On Data Geeks and Designers

The data geek, it’s said, wants to make every decision based only on the numbers. Test this shade of blue against that shade. Pick the winner. Test something else.

The designer is a creative artist, creating something beautiful, something people love. The antithesis of the data geek.

I’ve been thinking about this because I’m a data geek, I just started a new company, and I know that a skill UX designer could help our product immensely. Are my data-loving values in conflict with the values of those who are UX-focused?

No. As someone who spent lots of time painting in college, I assert that the artist vs. data geek model is an overly simplistic view of the world.

That dichotomy assumes that the data geek cares only about superficial numbers, and lacks the thoughtfulness and creativity to understand things that are hard (or impossible) to measure. It also assumes that the designer cares only about beauty and creativity, and not about whether they’re building actually works in the real world.

It’s easier to understand ourselves with these two questions:

1) Do you want to scientifically understand the way people are using your product, and use that understanding as part of your decision making process?

2) Is your business an automatically shifting, evolutionary machine that moves itself purely based on numbers, or is someone guiding it in a specific direction?

My answer to the first question is a very strong yes: I want my company to deeply understand how people are using its products.

The second question is a bit tougher for me. I like evolution, and I understand that natural selection can yield great outcomes. On the other hand, guidance and clear direction can be a far more efficient way to get to the best outcomes.

My first blog post, The Visionary and The Pivoter, discussed my experience building a company that wound up being more evolutionary than directed, and the challenges of that.

Here’s how I see things now:

Sites focused purely on viral content — Buzzfeed, Upworthy, et al — are in the top left: impressive (to me) for their ability to iterate based on data, but far more reactive than visionary.

My last startup, Circle of Moms, was focused on improving the lives of a specific audience (moms!), but we too were more evolutionary than visionary.

Amazon is a very data-centered company, but one with clear visions on where their product and business will move the world. Apple, on the other hand, possesses clarity of vision and an intent to push the world in a certain direction, but is seemingly less data-focused. Clearly, both of those models can yield tremendous successes.

Being reactive/evolutionary and in the dark with respect to data is the worst combination: you don’t know where you want to go, but you can’t see anything around you to help you find a good path. I’ve seen a few startups like that — they change their strategy every month based not on data but on a (bad) blog post someone writes — and it’s ugly.

Many companies move up on the scientific scale over time. There’s a real cost to collecting and analyzing data, and it’s easier to invest in doing it correctly with 100 employees than with ten.

I’d like to be in the brown box that has my picture: deeply scientific, but more directed than evolutionary.

Long term, I suspect that most great user experience people won’t be too far from me. They’ll use data to help them design things that more people like. But they’ll be thoughtful in the application of that data, so they won’t feel forced into a massive, evolutionary pinball game that throws them around randomly.