Tuesday, August 26, 2014

design with audience in mind

Recently, my husband shared a USA Today graphic with me that summarizes diversity stats across a number of Bay Area tech companies. Surely, this would be a good blog topic, he told me. He knows me well. Here is a screenshot of the visual:

Online version can be found here.

First, let me mention how cool I think it is that companies like Google have started sharing their diversity stats. I expect that with this transparency, we'll see movement towards more diverse workforces over time.

Next, let me discuss what an annoying user experience it is to try to look at the diversity data with USA Today's visual. It shows the breakdown for the given company (Apple, in the above screenshot) by gender on the left and ethnicity on the right. The various tech companies each have their own tab; you can toggle between companies using the numbered tabs along the left (not sure what the numbers on the tabs mean...if anything).

What is the first thing you want to do with this data?

For me, the stats for a given company, on their own, are not so interesting. It's by comparing them to the other companies that we help build context for what is good (or if not good, then at least better), what is worse, and so on. In other words, the single thing I want to do most is compare the stats across companies. The way this visual is organized makes this a lot harder than necessary. If I want to compare the proportion who are women at Apple (for example) to other companies, first I look to the Apple tab and commit 30% to memory, then I click through the other tabs one by one to try to put that 30% into context. This is annoying, but possible.

It gets more annoying and difficult if you try to do it by ethnicity. Try comparing the proportion Hispanics make up of the various workforces, for example. It's further complicated by the fact that the slices on the pie move and the order in which the companies are listed changes as you toggle between companies.

This is not an ideal user experience. My guess is that there was some desire to make the visual "interactive," which it sort of feigns via the tabs of various companies along the left. But really all this does is allow you to see the various static graphs, one at a time. Why not replace with a single static visual that makes the task your audience is going to want to do easy?

In other words, let's design the visual with our audience - and how they are going to want to interact with the data - in mind. If the goal is to compare across companies, I might do something like the following:


(Note that the title and takeaway at the top were preserved from USA Today's visual; I'm not sure I would have been quite as negative.)

The above version allows me to see things that were very difficult to get to with the original. eBay is doing the best from a gender diversity standpoint, but worse when it comes to racial diversity, where Yahoo is doing better than the others, etc.

Bottom line: design with your audience in mind!

Click here to download the Excel file with the above visual.

Monday, August 18, 2014

nice summary by UP

I have been religiously wearing my UP24 band over the past two months, after taking a hiatus from the technology while pregnant. I originally strapped it on to have record of my sleep. With a newborn, of course sleep looks much different now; there's something strangely gratifying when you can not only know that's the case, but also see it. Over time, I've seen the number of night-wakings generally go down (though last night was an exception, which I feel as I groggily type this post) and sleep consolidate into bigger chunks as my little chunk sleeps for increasingly longer segments. I can start to see a pattern emerge (bed at 11pm, wake for feeding at 2-3am and again at 5-6am, get up around 8am). Visual evidence of slow but measurable progress!

What caught me by surprise when I started wearing the band again is the motivation it inspires when it comes to my activity level. The recommended goal is 10,000 steps per day. When I don't hit it, I feel a bit of shame. When I do hit it, I feel a gratifying sense of accomplishment. That sense of accomplishment goes up as the amount by which I surpass the goal increases. This motivates me to get out and move on a daily basis to ensure I'll hit my goal.

So all of this is a long prelude to the summary from UP that hit my inbox this morning. I tend to post a lot of examples of data viz with which I take issue, so thought I'd mix it up and focus this post on one that I found to be effective. Of course there are things that I would have designed differently, but this summary gets the job done. It's keeping me motivated. Let me step you quickly through what it shows.

It starts with an overall summary of week-over-week changes:


Relative to the prior week, my average sleep per night went down a hair and my movement increased a little. I like the big, clearly articulated takeaway: you held steady.

This is followed by detail on my sleep this past week:


My average nearly hit the nightly sleep goal of 8 hours. I even beat the goal three times (versus prior weeks where I haven't hit it at all!). In fact, this summary looks perhaps deceivingly good, though the number of nights of uninterrupted sleep, at 0, starts to point to the newborn effect. It will be life-changing when that number moves, even by one!

The sleep summary is followed by a movement summary:


I hit my 10,000 step goal each day (my informal goal for myself is to hit it every day in August). You can see the days where a jog or long walk really put me over the top. My most idle time of 8-9am comes as no surprise, as that's when the little one eats breakfast, sequestering me to an armchair for the better part of an hour. The rest of his day remains less predictable.

It's a straightforward and simultaneously (for me, at least) motivating summary.

For more on UP from a numbers-person's perspective (including downloading the data it captures to analyze on your own), check out Nathan Yau's recent review here. For more on the cool insights the team at Jawbone is starting to make based on the crazy amount of data they are amassing, check out their blog (for example, this post). They've shared it with others who have started to analyze and share as well (here's a recent WSJ example, though I still lament the lack of color-key on the heatmaps - ok, turns out it is impossible for me to write a blog post without critique!).

Someday, I'll download all of my data and perhaps do something fun with it. For now, I'll continue to check out the daily and weekly summaries to track my progress and for that feeling of accomplishment when I hit my goals.

Monday, August 11, 2014

the challenge of teaching data visualization

You want to increase your skills when it comes to creating effective, captivating, and informative data visualizations. I want to teach you. But with this, comes certain challenges. It is these challenges that I hope to discuss in a SXSW 2015 panel (along with three expert colleagues: Jon Schwabish of policyviz.com, Kaiser Fung of Junk Charts, and Ben Schneiderman of University of Maryland).

But we need your help.

Over 3,000 proposals have been submitted for SXSW Interactive. Obviously, only a fraction of these will be chosen for sessions. Public voting accounts for about 30% of the decision making process. That's where you come in.

Please take 20 seconds to vote for our session by clicking the button below (which will prompt you to create an account before voting if you haven't already - it's super fast, I promise).

Vote to see my session at SXSW 2015!

Check out the following slideshare for more detail on the session topic.



Thanks and I hope to see you at SXSW 2015!