Thursday, March 27, 2014

more on slopegraphs

Note: only a couple spots remain in my upcoming San Francisco storytelling with data workshop. Details and registration can be found here.

I am a fan of slopegraphs. I first used one after reading about them in Alberto Cairo's The Functional Art back in 2012 (my related blog post is here; scroll to the second half for the section on slopegraphs). More recently, I created a slopegraph template that is available for download here. I find myself frequently using slopegraphs to illustrate a novel and often easier-to-show-interesting-insights-than-alternative-visualization-methods approach.

Typically, I find myself using slopegraphs to compare two points in time. I love that, in addition to the absolute values (the points), the lines that connect them give you the visual increase or decrease in rate of change (via the slope) without ever having to explain that's what they are doing, or what exactly a "rate of change" is - rather, it's intuitive.

Slopegraphs can also be useful to show comparisons between groups. For example, when reporting employee survey results, a slopegraph can be used to show a given team's feedback across survey categories compared to the overall company, as illustrated below.

I originally had mixed feelings about using a slopegraph in this way. After all, a slopegraph is a line graph, right? And I've always taught that line graphs should only be used when plotting continuous data, which isn't the case here. But I think the main reason for making sure lines are plotting continuous data is to ensure that the lines that connect the points make sense. And in this case, they do. The lines visually display the relative difference between the two groups.

In fact, a slopegraph allows us to visualize data in a way that makes easy quite a number of observations and comparisons. While doing a bit of research on the topic, I came across Charlie Park's website, where he has a couple of posts devoted to slopegraphs (that include a number of great examples from the media and elsewhere). In his first post on the topic, he recounts Tufte's list of what slopegraphs are useful for showing. Below, I've listed these, applied to the above example:
  • The hierarchy of survey categories, both for the company and Team X (relative order of points on left and right, respectively),
  • The specific numbers associated with both groups (the data values),
  • The difference for each survey item between the company and Team X (the slope of category's line),
  • How each category's difference relative to the company compares to the other categories' (the slopes of lines compared with one another), and
  • Any noteable deviations in the general trend (aberrant slopes).
Rephrasing this final point in simple English, slopegraphs can sometimes make things that would otherwise be difficult easier to see. Let's look at an example to illustrate this point.

I am an oft-recommender of the horizontal bar chart, but recently encountered a situation where a slopegraph trumped one. I was looking at alternate ways to visualize some data for a custom workshop I was conducting. Again, we are looking at survey data, this time feedback from customers across a number of survey items in 2011 vs. 2010.

I started out with the following bar chart (note: this is a genericized version of the original):


As you scroll down, taking in the data from top to bottom, we can see for each survey item, how 2011 compares to 2010. There's something possibly interesting near the bottom: Survey item I is the only place where we see a marked decrease from 2010 to 2011. This gets a bit buried in the above visualization. 

If there's a story there we want to focus on, we could highlight the relevant data points to draw attention there:


In the above, now it's a quicker process to get to Survey item I because of the preattentive attribute (color) that we've leveraged to make those data points stand out from the rest. But perhaps we can do better.

Next, let's take a look at what the same data looks like, visualized with a slopegraph:


In the above, a couple things jump out at me quickly (more quickly than they did in the horizontal bar graph): the increase over time in Survey items A and B, and the decrease in Survey item I. Per Tufte's list discussed previously, we can also easily see the rank ordering across the various survey items in 2010 and 2011, the specific data values, and the change over time, both for an individual survey item, and for the survey items compared to each other. In this example, I find that nearly all of these aspects are easier to see when visualized as a slopegraph than they were in the original horizontal bar chart.

Again, with this setup, we can use color to draw attention even more quickly to Survey item I if desired:


To complete the above visual, we'd likely want to add some text explaining why the points we're highlighting are interesting, relevant context, and perhaps a call to action. I've genericized the example a bit too much to actually do this here, but you can imagine what that could look like.

In conclusion, when you find yourself comparing two groups across the same dimensions, or plotting two points in time: think about whether a slopegraph might allow you to visualize your data in a way that would be intuitive for your audience and make what you want to highlight easy to see.

For even more on slopegraphs, check out the following:

Monday, March 24, 2014

color considerations with a dark background

I was working on some data visualization makeovers a few weeks ago and found myself facing a challenge I hadn't previously encountered: the need to leverage a dark background.

When it comes to slides that communicate data, I don't typically recommend anything other than a white background. Anything else makes me think of Tufte's conversation on data-ink ratio. His basic idea is that you should work to maximize this figure (more data and less ink, vs. the opposite). In The Visual Display of Quantitative Information, he says, "Every bit of ink on a graphic requires a reason. And nearly always that reason should be that the ink presents new information." If we think about a colored or dark slide background from the perspective of the data-ink ratio, that's a whole lot of ink for no data at all.

Nancy Duarte more directly discusses dark backgrounds in Slide:ology, listing the following considerations:
  • Dark background: formal, doesn't influence ambient lighting, doesn't work well for handouts, fewer opportunities for shadows (Cole's input: I don't think this is a bad thing!), for large venues, objects can glow. 
  • White background: informal, has a bright feeling, illuminates the room, works well for handouts, for smaller venues, no opportunity for dramatic lighting or spotlights on the elements (Cole's input: as in the "fewer opportunities for shadows," I think the lack of opportunity for "dramatic lighting", though phrased as a negative is actually probably a good thing).
Let's take a look at what a simple graph looks like on a white, blue, and black background:


The blue and black backgrounds just feel heavier to me. They make my eyes almost pulsate a bit (that's probably the glow that Duarte referred to). That, plus Tufte's data-ink ratio and Duarte's considerations together seem to indicate that one should generally opt for a white background. That said, sometimes there are considerations outside of the ideal scenario for communicating with data that must be taken into account, such as your company's (or client's) brand and corresponding standard template. Such was the case in my specific situation.

I didn't recognize this immediately. Rather, it was only after I had completed (I thought) my revamp of the original visual, that I realized it just didn't seem to fit with the look and feel of the work products I'd seen from the client group in general. Their template was sort of bold and in your face with a mottled, black background spiked with bright, heavily saturated colors. In comparison, my visual felt sort of...meek. Here's a genericized version of my initial makeover:


To solve for this, I remade my own makeover leveraging the same dark background I'd seen used in some of the other examples shared with me. I had to sort of flip around some of my normal thought process. With a white background, the further a color is from white, the more it will stand out (so grey stands out less, black stands out very much). With a black background, the same is true, but black becomes the baseline (so grey stands out less, and white stands out very much). I also realized some colors that are typically verboten with a white background (for example yellow) are incredibly attention grabbing against black (I didn't use yellow in this particular example, but did in some others).

The same goal of identifying and eliminating clutter (elements that aren't adding informative value) still hold. In fact, reducing clutter becomes even more important on a dark background, because you're already dealing with the high ink to data ratio that we previously touched upon. So less already looks like more than it would on a white background. But it can be done.

Here's what my "more in line with the client's brand" version of the visual looked like:


What do you think - are black or colored background out when it comes to communicating with data, or can it work? What other considerations should we make when working with non-white backgrounds? What other scenarios might lead us to want to choose a dark background? Leave a comment with your thoughts.

Wednesday, March 12, 2014

slidedocs

In my workshops, we often discuss the challenge that arises when the communication you're creating is meant to be both 1) projected or handed out in a live presentation, as well as 2) sent as a follow up for those who attended to refer back to, or to fill in those who weren't able to attend the presentation. In an ideal world, these would be two separate work products. In reality, however, this often gives rise to what Nancy Duarte calls the slideument, a single document that is meant to address both needs.

The problem, of course, is that by trying to meet too many needs at once, the slideument doesn't address any of them perfectly. If you're interested in my further pontification on the topic and some thoughts on how to address the challenges that arise with the slideument, you check out this blog post.

My interest was piqued when I saw that Nancy Duarte recently introduced a new concept for using slides, which she has termed Slidedocs. The description on her site describes slidedocs as "a visual document, developed in presentation software, that is intended to be read and referenced instead of projected." The FastCo Design article written about Duarte's slidedocs is titled "Book Written Entirely in Power Point Aims to Reinvent How Businesses Communicate" (article).



With my busy schedule this week, I haven't had a chance to give the 150 page doc more than a cursory review. But rather than wait until I have more time to consume and reflect before sharing, I figured I'd post this now and gather your inputs. What do you think? Will this revolutionize the way we communicate? Leave a comment with your thoughts. I'll add mine once I have a chance to look more closely at the detail.