Naming companies is hard.

When Martha and I set out to name our business, we wanted something that conveyed our desire to help people sort through their greatest challenges, make sense of our complex world, build better relationships, and work better, collaborate better, feel better, and live better as a result.

At some point the word “untangle” precipitated from our storming brains. Untangle plus an online Latin dictionary led us to retexo, which can mean just that—”to untangle”—but also “to un-weave,” or “to un-weave and weave anew” (think “textile,” from texo, “to weave”).

Perhaps Latin or Greek words as company names are cliche, but try naming a business or a product and you will quickly find that all the interesting English words are long since taken.

Plus, we liked the sound, we liked the meaning and the weaving metaphor, and most importantly, retexo.com was available.

Retexo, LLC it was.

Untangling Data

English mathematician Karl Pearson, often referred to as the father of statistics, wasn’t naming a company when he coined the term “histogram.”

Instead, he was naming the graphical technique he used to visualize and make sense of the underlying structure of data, but he also turned to the ancients.

Pearson combined the common Greek root, gramma, for “figure” or “drawing” with histos, which means “to stand upright,” like the mast on a ship, which is referred to by the same word.

Standing Up

To make a histogram, you take a bunch of measurements or observations, and divide them into discrete “buckets.” For example, if you were measuring the height of American women, you might choose one inch buckets from four feet to seven feet.

You would then count the number of height measurements in each bucket, and “stand up” the result with a vertical bar. Line up the bars for all the buckets along the x-axis of a graph, and you have a histogram. It is a picture of the frequency at which each height occurs.

In our height measurement experiment, the tallest bars would be around the five-foot-four bucket, the average height of women in the United States.

Ring the Bell

Many of the histograms for things we find in the real world—height, weight, SAT scores, and blood pressure, to name a few, form a shape you know well: the bell curve.

So many things in our world adhere to this structure that we consider it normal. That’s why we call it the “normal” distribution.

But why is the normal distribution so…normal?

What Is “Normal?”

I know I'm pushing the geek-out limit here, but trust me, this is worth understanding.

When many small, independent, random factors add together to produce an outcome, that outcome tends to form a bell curve.

Height is genetic, but it results not from one gene, but hundreds or even thousands of genes, plus environmental factors all exerting a tiny influence toward taller or shorter stature. As a result, height is normally distributed.

So is weight; so is depression; so is IQ. You get the idea.

We see this pattern so frequently in the things we really care about, including people and groups, because they work the same way. Their behavior is the result of not one big thing, but the sum of many small things.

• Your business’s financial performance results not from one action, but from thousands of individual actions adding up.
• Your employees’ job performance results not from one trait, skill, or piece of knowledge, but hundreds.
• Your team's effectiveness stems not from one or two star players, but from the quality (or lack thereof) of countless daily interactions and complementary capabilities.

Because it is so prevalent, understanding the bell-curve-shaped histogram of the normal distribution is essential to making sense of the world we live in, and helping people make sense of things is what Retexo is all about.

The fact that the histogram’s root, histos, also refers to the vertical looms used by ancient Greek weavers is pure coincidence.

Sometimes it’s better to be lucky than good!

Spectrums, Not Polarities

Most things that matter to us are not black and white. We are obviously not either tall or short. Our stature is distributed between extremes, with most people falling somewhere in the middle.

Likewise, introversion and extraversion are not binary. Those traits follow a normal distribution, too.

Importantly, these distributions often overlap. If someone selected a man and a woman at random and offered you $100 if you correctly guessed who was taller without seeing the first, the only rational choice is to bet on the man, but you would still lose at least one in ten times.

This sounds obvious, but the fact men are taller on average than women does not mean that all men are taller than all women.

The Same But Different

It is tempting to call someone who tests just right of center an extravert while the person just left of center is an introvert.

But in reality, just as a man and woman could be closer in height than two men or two women, an introvert and extravert who fall close to the middle of the distribution could have more in common with each other than with their fellow introverts and extraverts.

Emotional intelligence, personality traits, how frequently people speak up in meetings, stress levels, ad campaign performance, product defect rates, wages for a given job role in your market, and on and on, all exist not on separate poles, but distributed across a bell-shaped spectrum.

Buckets Aren't Real

Putting people in buckets can be useful, just as it is useful to put experimental observations in buckets to make a histogram. After all, that’s exactly what we’re doing when we assign a personality style of D, i, S, or C.

Those categories help us make sense of ourselves and others, but at the same time, we must always remember that we created those buckets, and they are only approximations of the unique individuals inside.

This holds true everywhere. Categories are convenient, but reality is messy. Averages can differ, but the underlying distributions often overlap.

We are predictable and also unpredictable. We are different, but also the same.

Understanding the underlying distributions allows all these things to be true. It lets us resolve the apparent paradoxes. It helps us untangle difficult knots and make sense of the world.

And if you get stuck, we're here to help.

Until next time,
Greg