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It's probably a lot less often that you think. In fact, there are just three specific—and quite rare—situations in which I'd show data as a table only (as opposed to a graph or a graph plus a table).
What are those three situations? Find out in my latest video (10 mins)!
Read moreI recently had a great exchange with dataviz luminary Salma Sultana about where best to locate slice labels in a pie chart. The consensus that we came to was that it depends on the lengths of the category names and whether or not there are any very small slices.
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When looking at a line chart for an important metric, people often panic when the line goes down and celebrate when it goes up, even though those fluctuations can—and often should—be ignored, because they're just random "noise" that doesn't need to be acted on.
There are, of course, also times when a metric genuinely does require attention because it's behaving in way that indicates that something meaningful has occurred and that action may be warranted.
Is there a way to tell the difference between random fluctuations that can be ignored and meaningful patterns that require action? This video covers just that topic!
Read more“% change vs. previous period” numbers are ubiquitous on dashboards and they look useful, but they don't actually tell users anything!
Don't believe me? Check out my latest video (8 min.), which I recorded during a recent workshop for the lovely folks at Funnel, makers of great marketing dashboard software.
Read moreWe often need to show deviation values over time, e.g., deviation of our monthly expenses from the budget for each month but, unfortunately, these values are often shown as line charts, which can be very confusing or misleading for audiences.
To see a better solution, check out my latest video (5 mins.).
Read moreNot to flex or anything, but I’m somewhat of a connoisseur of hotel shower faucets. I travel frequently to deliver workshops, so I’ve seen many different models. A lot of them look almost like modern art sculptures. Clean lines. Pleasing symmetry. Modern aesthetics.
But how do I, y’know, have a %#*$ing shower?
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In this post, I list the specific chart types that, in my experience, stump audiences most often (including, sometimes, senior executives).
Read moreWhen I’m chatting with other chart creators, it sometimes feels like there are two different groups that live in two completely different worlds:
The first world is populated by those who create charts for relatively data-savvy audiences. In this world, chart types like scatterplots and histograms are “basic” chart types that everyone knows how to read.
The second world is populated by those who regularly create charts for “non-data” audiences who often struggle with anything other than simple bar, line, or pie charts.
Read moreYou might have seen this brilliant piece of viral marketing from cybersecurity firm Hive Systems, that seems to pop up every year in my social media feeds. While it's a great piece of content marketing, the color choices leave a few things to be desired, IMHO, which I discuss in this blog post.
Read moreI’ve seen the following scenario play out many times in the organizations with which I work:
A chart creator decides to “get creative” by using a histogram, connected scatterplot, ribbon chart or some other chart type that they know to be unfamiliar to the audience. They could have used a simpler, more familiar chart type to say the same things about the data, but they wanted to “challenge the audience,” or “teach them new chart-reading skills.”
The chart then goes over like a lead balloon, however. The audience misreads the chart, skips reading it altogether, or gets annoyed with the chart creator, who then feels bitter, believing their audience to be intellectually lazy or just dumb.
Read moreI first heard this objection from a client a number of years ago and it took me so off-guard that I just stared at them and then mumbled something about getting back to them on that. It just seemed like such a bizarre thing to say…
Since that time, I’ve heard this objection at least half a dozen times and have had a chance to formulate a couple of responses that usually convince dashboard users to rethink their “no red” policy.
Read moreYou may or may not be familiar with Marimekko charts, but they're popular in some fields, such as management consulting.
To see why I avoid using this chart type and what I use instead, check out my latest video (8 mins.).
Read moreI regularly hear complaints from dashboard creators that go something like this:
"My users consider dozens of metrics (or more) to be ‘KPIs’ and they want me to put them all on the dashboard."
"My users don’t understand that, among all the metrics that we could show on the dashboard, only three to five of them are truly important. The rest are just noise that distract from the truly important numbers, and so don’t belong on the dashboard."
Think about that for a second, though. Does it seem plausible that someone could run an entire team, department, or organization based on just five numbers?
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As these simple before and after examples show, direct labeling is a simple fix that can significantly improve the readability of your charts.
Read moreI recently saw people praising a chart from The European Correspondent on social media comparing the years of compulsory schooling for different European countries.
While it's certainly creative, when I tried to actually read the chart and spot the insights that were in the callouts, I had to work pretty hard, and some insights were difficult—or even impossible—to spot. In this blog post I critique the original design and propose a redesign that I think performs better.
Read moreOne of my pet peeves is dates in charts that are ambiguous, but the problem can easily by avoided by choosing good date formats.
Read moreProbably the most common way to show values on a map is the "colored-region" or "choropleth" method. I'm not the first to notice, however, that this method presents some potentially serious perceptual risks.
Read moreI was recently invited to deliver a webinar as part of JMP's great Statistically Speaking series. The webinar consisted of a 35-minute talk entitled "How to choose a chart type (it's trickier than you think)," followed by about 25 minutes of Q&A from a very engaged (and large) audience. The recording is now available to view online.
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I recently logged into the dashboard for my email list management app and noticed that the chart of my subscriber count over time suffered from several common design problems that made it unnecessarily hard to read and potentially misleading. In particular, the quantitative and time scales were less than ideal.
Check out this short (8-minute) video of me fixing these problems step-by-step:
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I recently recorded a video of me turning an “OK” chart into a great chart, step-by-step, to make it easier to interpret and to make key takeaways much more obvious.
Let me know if you agree or disagree with any of my changes!