Data believability

The BBC news website has an article about how western demand for food and goods drives water shortages in developing countries. The interactive visual below is included. The problem I have with it is that the data just doesn't seem believable - I'm not saying it isn't true at all, just that when you deliver information with surprisingly high values (10,850 liters to produce a pair of jeans), you have to delve into that data to stop people instantly dismissing it. For example, how is that volume distributed over growing cotton, manufacture, and transportation? Are you including the water usage of the workers who have some involvement in the trade - is that a fair thing to include?

Without context, information becomes devalued, especially when the data seems outlandish (but may in fact be accurate).




I encountered some skepticism after writing a report concerning excess costs in U.S. shift work operations. The $206 billion annual lost opportunity seemed very high, but the methodology and charts that supported the conclusions made believers, I hope, of the listeners on NPR's Talk of the Nation, and readers of the print publications who picked up the story.

Do you have believability problems with the data in your company - is it being delivered to the decision makers effectively through dashboards and interactive reports? I can solve your data visibility problems and make your business run more efficiently and profitably. 

Design (in)considerations

A slideshow of some bad design examples I've been collecting. My favorites are the French translation making you find a 3.17mm drill and the chair that's not a chair..

Animated visualizations: Don't change the scale!!

I have an unhealthy obsession with weather - partly because we heat with wood, and partly because if it snows enough I get to use the snowblower on the front of my lawn tractor. Consequently I often have the weather radar  up on my browser.

By default, wunderground.com (and most others) show only the most current radar image - other than a total storm size I can pretty much look out of my window to get the same information.

By animating the map, I can see direction of movement - key if you are at the edge of the storm, and very important if it's a coastal storm which tends to sit and rotate rather than moving off. Equally I get to see the speed of the storm's movement, another important variable, and how the intensity of the storm is changing, denoted by the key on the right.

And here's the cardinal sin - if you're going to animate anything with a scale, don't change the scale halfway through the animation.

The initial scale has a number of shades of grey below zero (that really could be replaced with just one color, as this just means clouds with some snow blowing around).

5dBZ on the first scale (light snow) is a dark green. As the intensity of the storm passes a threshold a switch is made to the second scale. Now anything below 10dBZ is light grey, and interestingly, as is anything above 60dBZ. The second scale now also has some descriptions of the intensity. The new scale fails color blind users to a certain degree (mouseover to see) - the 45dBZ plus now looks very much like 15dBZ.

This isn't wunderground.com's fault - I would guess they pull the images from NOAA. I would also venture to guess the change in scale is as a result of the internal workings of the radar changing. Whatever the reason, software creates the scale, so it could be fixed.

One fix: as a change in scale is needed, create two images, one with the old scale, one with the new, for the period of time that that the animation covers. When you have enough frames switch over so that the animation only uses one scale. This isn't a great fix as that scale change will still confuse when viewing over longer time periods or intermittently through the day.

Much better would be to just have one scale (right) - as a member of the public (rather than a pilot for example), I don't think the values below 0dBZ, or above 65dBZ, mean much to me, so you could probably lump all of those into a bucket or two. I've still used a green to red scale, but identified the 'catch all' buckets at the top and bottom with colors outside the gradient. I've also extended the color range through purple. The greens have a lot more blue in them to help colorblind users (mouseover). A few other improvements - specify time between frames so that I can understand velocity (I always have to try to catch what the clock movements are), and state when the most recent picture was taken (not just the time of the current frame).

Pareto lines on bar charts - an Excel fudge

I found this aberration the other day on 148apps.biz. It's a pie chart of showing the categories of the apps available on the Apple website. I won't labor on why it fails, but the multiple slices, oblique view, lack of color blind sensitivity, and 0% pie pieces add up to a awkward chart.

While not 148apps fault, the choice of categories that Apple has made available makes the chart less usable - some should clearly be subcategories - strategy for example is probably a game category. 

A bar chart is a better choice - even better are bars with a pareto line showing that the top five categories account for x% of the total apps available. You can add a pareto line to a column chart relatively easily - add a new series (the cumulative percentages that you've calculated) to the column chart, change the chart type of just this series to line chart, and place it on a secondary axis.

However, you can't do this with bar charts as the line can't be plotted on a secondary axis when it's in this orientation.

Instead you are doomed to fudging a solution - plotting an XY line with the X coordinates matching the cumulative percentage, scaled up to match the current full scale (20,000), and Y coordinates that correspond to the position of the category labels. These Y coordinates are quite easy to calculate - if I have 20 labels, the Y position of the first point will be 19.5, the next 18.5, and so on. Copy and paste the new XY data in, change the chart type of this series to XY,  and ensure that you don't have to swap the X and Y column. Excel will add the data with a new Y axis - edit this and set the maximum value to the number of categories (20) - this  lines everything up, then delete this extra axis. I had to add the 0%, 25%, 50%, etc. to the bottom as text boxes.

Download the Excel file here. And yes, those are miniature iPhones making up the bars..

Insights by IBM

Came across this in The Economist (who, by the way have consistently good charts that don't discriminate against color blind readers). The gist is that IBM can organize your financial data from disparate systems into reliable, transparent, actionable information.

Is the 'chart' they show a result of not buying their software, or what you get when you do? I know it's just marketing fluff, but when you provide people with concepts like this, no wonder they are happy with revving gauges.

Actionable indeed...

Nonsense Charts

Daily Dose of Excel shows us an excellent example they found of awful chart design. The chart concerns male and females accepted to various colleges, the class size, number admitted, and number of applications.

It's unclear what the 'take home' is supposed to be - that some colleges have lots more applicants, that the acceptance rate varies, that the male/female ratio varies?

It fails immediately because you're being asked to compare areas - when comparing data we tend to look at just one dimension - e.g. length of a bar. In this case we tend to consider the diameter more than the area, leading to underestimating the difference between colleges. Secondly, the male/female comparison fails because the scale is so small that drawing anything meaningful, even within a single college is difficult.

I would also argue that the dimension used is wrong - a more interesting dimension would be % females accepted vs. % females who applied. I'm also unsure what the class size and admitted dimensions show - admitted is presumably just males plus females. Daily Dose of Excel asks "could (should) this chart be done in Excel?"

Not one to turn down a challenge I roughly estimated the data in the chart and added some college names (obviously not the real ones). It wasn't an easy thing to chart and this isn't perfect. The raw size of the applicant pool is important to show, as is the % who actually got admitted. The ratio of males/females is interesting (though I still think it's the wrong dimension). I declined to show the class size information.

A major difficulty is the very large applicant pool of (what I call) Princeton. Maybe this would be one of those few occasions where an axis with a break in it may work. Equally, for most colleges, the admitted proportion is so much smaller than the applicant pool, that it makes comparing college to college difficult - I resorted to adding the data as text as well. Lastly, there's no way you could break the admitted bar down further to show female/male, so I pulled that data out below the main chart.

For almost any application, pie charts are not the best way to show data (that whole 2D thing again), but when you only have 2 slices, it can work - I think it works okay in this situation - you can certainly quickly scan across and see where the proportion of males/females is very different and where it's more 50/50... Anyway, suggestions on a postcard for how it could be done better.