trust the process

One common feature of the iterative process is that things often get messier before they get better. There’s a word for that illusion that everything always improves in a linear way: monotonic. But real progress often has a lot more ups and downs than a straight line.

Let me show you what I mean.

We’ll start with a table (borrowed from the virtual mini-workshop I’m planning for 6/26). It shows evaluation results across four suppliers. It’s rich with data: we can see how each supplier performed across the five dimensions (initial setup, overall operation, functionality, ease of use, patient satisfaction) and on average. But as a visual, it doesn’t help us quickly grasp the key takeaway.

So let’s graph it. This is categorical data, so I’ll opt for a bar chart. The test metrics are a little wordy, so I’ll use the horizontal variety, where the text also is oriented horizontally, making those descriptors easy to read. Below is my initial graph. It’s a direct translation of the table into visual form.

It’s an honest first try—but dense, colorful, and hard to compare. Let’s continue to iterate.

Next, I’ll regroup the data by supplier.

At this point, I am reminded of Bob Ross. Perhaps you know the moment I’m thinking of from The Joy of Painting: he’s calmly painting a serene landscape, it’s starting to look good, and then—seemingly out of nowhere—he swipes a bold, dark line down the canvas. Gasp! Why did he ruin it?! 

But he hasn’t. 

With a bit of time, that unexpected line becomes the happy little tree in the foreground that brings the whole painting to life.

This bar graph is my dark streak. It doesn’t look better yet—there’s too much color, too many bars. It’s challenging to compare much of anything. It might even feel like a step backwards.

But that’s part of the process. Because with a few thoughtful tweaks, clarity can emerge.

I’ll eliminate clutter, streamline colors, add words in thoughtfully placed places to make the graph—and what I want people to take away from it—perfectly clear. 

Depending on the situation, I might be able to distill the detail even further and simply plot the averages, rather than the individual dimension detail.

In either case, the data has been transformed into something more.

This example is one of several that I’ll walk through during my upcoming free live virtual mini-workshop on June 26th. Join me to learn practical strategies for turning data into compelling visual stories and get your questions answered. Simply register to join.

In the meantime, if you’d like to consider how you might transform this or related visuals—or see how others are approaching it—check out the June SWD challenge.

This example is from our new book, which features twenty client-inspired makeovers designed to help you rethink how you communicate with data. Preorder it today!