Thursday, September 4, 2014

show the full picture!

There is still space available in my upcoming San Francisco public workshop; details and registration can be found here. Click here to suggest a location for a 2015 workshop.

I've posted a number of times about Pew Research articles. Well, not the articles exactly, but rather the visuals they contain. To be honest, it's rare that I read the actual article. I scan the headlines as they hit my inbox and if something piques my interest, I follow the link and scroll through the article, not reading, but taking a discerning look at the graphs.

This is what I was doing when the following visual caught my eye within an article titled, "Perceptions about women bosses improves, but gap remains." The full article can be found here.

They are nice looking graphs, as is the norm. But upon examination, for me both of these visuals leave out an important part of the picture. Let's examine them one at a time.

I'll start with the top chart titled "Boss Gender Preference." The first thing I want to do with a graph like this is add the percentages to understand what proportion of the overall population we're talking about. Everybody? No. In this case, a little math tells us that a lot is missing, especially in the more recent years. My "data-spidey sense" (as a former boss of mine used to call it) gives me suspicious pause. I go back and read the title, etc. to try to put what is missing (the piece or pieces that would enable the lines to add to 100%) into context. In this case, the lines represent the percent of those responding to the survey who said they prefer male bosses and the percent who prefer female bosses. So, I would assume that the remainder are those who have no stated preference (and only now as I write this do I see the footnote below the second graph confirming this; for sake of this discussion and my forthcoming makeover, I'll assume "no opinion" is the same as "no preference"). In recent years, this accounts for nearly half of the total. That seems important. And yet isn't shown explicitly.

Let's look at a different view of this data:

In this remake, I replaced the line graphs with stacked bars so that we can see the full 100%. Those preferring male bosses are along the bottom in blue, female along the top in orange so that we have a consistent baseline at both bottom and top to be able to compare what has happened over time for those groups. I only graphed the points that were labeled in the original graph, omitting the 2000 data point altogether so that I'd have a (roughly) consistent gap between the dates along the horizontal x-axis. That data point was strange to me in the original graph, anyway, since preference for both male and female bosses increased (while % indifferent went down), but then bounced back to the previous trend. It looks like something strange may have been going on there (was the question worded differently? had something recently happened in current events that influenced this? I'd want to better understand this, however since it doesn't seem critical to the overall story I'll simply omit).

With this view, you can visually lump together the grey and orange bars, or even focus on just the grey to see progress on a different level than was shown in the original graph - from an overwhelming preference for male bosses to lessened sensitivity when it comes to the gender of one's boss overall.

After plotting the data this way, I considered that perhaps a line graph would work better, but with an additional line for the indifferent portion. I drew it, but after seeing it, it reinforced for me that the stacked bars work better for being able to add different data points together, which I think is important here. In case you're curious, here's what the line version looks like:

Next, let's turn our attention to the second visual: Female CEOs. The graph as drawn by Pew Research looks like great success: up and to the right. In this case, frame of reference is critical. Yes, 4.8% is huge relative to zero. But it's really small compared to the potential (100%). Here's how I'd graph this one:

With this view, there has been progress - yes - but there is potential for much more.

As a side note, it also bothered me that the dates were totally different between the two graphs (it seems like you should be able to compare the data points across them, but if you follow 1975 in the original top graph down, this lines up with something like 2002 in the bottom graph). I attempted to address this through the titling of the graphs ("the past 60 years," "the past 20 years") but this isn't a perfect solution. Part of me wants to have a bunch of empty space on the left of the second graph and make it so the 20 years of data we have there lines up to the top graph along the same date scale, but I think this would squeeze the data we do have too much to be legible. So I settled with attempting to address through the titles.

Here is the side-by-side of the two visuals:

Note how in both cases above, the remake causes us to see a different story and perhaps even draw different conclusions than we might have with the original visuals. For me, the makeovers present a fuller picture.

It is possible that this fuller picture is all explained in the article. I really can't say, as I still haven't read it. I am probably not the only one who "reads" this way. Which is another lesson: design your visuals so they still work when your audience doesn't read the accompanying text!

In case you're interested, my other recent posts on Pew Research visuals can be found here and here. The Excel file with the makeovers from this post can be downloaded here.

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.