Reflecting on one year of consistent writing

I’ve been able to maintain a consistent writing schedule for over a year now, despite all of the turmoil that 2020 has brought.

For 52 weeks, I’ve published something consistently at least once a week, sometimes twice. This is on top of work and other personal projects that I’ve been working on.

I won’t say that it’s all been amazing writing (in fact, there’s one I unlisted because it was so bad), but I’ve been able to be productive based on one rule.

Whenever I’m stuck, it’s because I don’t know enough.

That rule alone has helped me overcome creative blocks more than I can count. …

Understanding how users seek information.

What makes a good visualization? That’s a question I had to ask myself when one of my early visualizations was heavily critiqued. And it was an answer that I found when reading Alberto Cairo’s The Functional Art: An introduction to information graphics and visualization.

According to him,

“A good graphic has two basic goals: It presents information and then allows users to explore that information.”

That extra step, allowing exploring the information, is crucial in order to promote user understanding. And to understand this viewpoint, let’s revisit the Information-Knowledge gap.

DIKW and the User side gap

Previously, I talked about the DIKW information model (Data, Information, Knowledge, and Wisdom) and how structuring data efficiently can only get you so far. …

Understanding the power of pre-attentive attributes.

One of the greatest joys of learning about data visualization has been getting stakeholders to pay attention to crucial design issues, even while working remotely. The simple act of visualizing a long word document caused people to pay attention and understand a design flaw in the workflow. And it was largely based on an understanding of the DIKW Information model.

DIKW: Data, Information, Knowledge, Wisdom

There is a model of understanding that comes from Alberto Cairo’s The Functional Art: An introduction of information graphics and wisdom.

In this, he talks about Russell Ackoff’s model of how something goes from unstructured data to innate wisdom.

The first step is turning reality into data. This is what happens when you write down surveys, conduct interviews, or otherwise record observations based on what you’re doing. …

The hidden costs of free learning

I failed to learn a skill I strongly wanted and needed to by my set deadline.

Why? Because I tried to do it for free.

The consensus around online learning is that it’s almost always worth it to pay for courses given the relative value you get.

But I didn’t know how much harder it would be trying to do it for free.

So here are the extra costs you will incur if you’re trying to learn for free, and what you can do about them.

The free conundrum

Students who paid for their online courses were 11 times more likely to complete them. …

The 3 questions that can make a huge difference

Your user research may be missing a step that makes a huge difference to your stakeholders.

You have followed the proper steps. You’ve gathered enough users, set up usability tests, and done data analysis.

But have you thought about how you’re going to present your data to your stakeholders? It’s a step that many skim over, but it can be crucial in making presentations that drive stakeholder action.

To start, you need to re-examine your approach.

The approach many Junior UX’ers take

I got my first lesson in presenting to stakeholders when I was told that my presentation was too long.

“You could’ve cut out a lot of the methodology section.” My mentor said, but what she said next stuck with me to this day. …

How a missed UX opportunity cost me hours in data analysis.

Recently, I got to experience the other end of the quote of how “Fixing a project after deployment costs 100x more than fixing it in design.”

What might have been a 5-minute design decision resulted in a 500-minute data-wrangling session to address a problem.

And the whole time I was thinking about how a single change in the UX Design that could have made this process a lot easier.

So if you want to understand how to make the Data Scientists on your team much happier, understand the effect that your design decisions can have on creating structured data.

Data wrangling and structured data

So to begin with, what is structured data? …

Taking a cue from Data Science as a UX Designer.

Yesterday, I made about 3 months of project progress clearer to the entire team.

I didn’t have one-on-one interviews with stakeholders or anything drastic.

I simply organized all of the information we had collected and visualized it.

I should know about visualization as a UX Designer. Between designing prototypes, creating design artifacts, and explaining research findings, I thought I knew most of the ways to visualize things.

But it was a technique from Data Science that got me to visualize our Agile backlog.

It made my life a lot easier. And it can make yours easier as well. Here’s how.

Data-aware design

As I mentioned in a previous post, I’ve been getting into Data Visualization and understanding the way that Design and Data Science can interact. …

How a blog post transformed my writing

A blog post fundamentally changed the way that I think about writing.

I came across Scott Adams’ blog post adapted from his book, How to Fail at Almost Everything and Still Win Big.

I had read the book before, but the post caused me to re-evaluate my approach towards writing.

Why? Because it asked a simple question: How did you learn to write for work?

You (probably) haven’t been taught business writing

Unless you’ve done an MBA, you’ve probably never learned how to do business writing.

If you’ve ever taken a writing course, they tend to focus on creative writing.

Those that didn’t, such as your high school English classes, may have taught you grammar or how to write an academic paper. …