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Over the last few years, it’s no secret that I’ve pulled some good and poorly designed data visualizations from the BusinessWeek magazine.  Since Bloomberg took over the magazine the chart/graphs and data/info visualizations have declined significantly.

Here’s my promise to the readers of this blog – this will be the last chart that I pull from BusinessWeek because it was poorly designed.  Take a look at the bar chart below that was shown in the October 18/24 issue that I just picked up.  Folks, this isn’t even charting 101, this is a pre-requisite.  A multi series 3-D bar chart, really?  I’m disappointed and they should be embarrassed because they need to be better than what’s shown below.  I probably won’t renew my subscription that I’ve had for at least 5 years, not because of the charts, but because I find less and less interesting articles with each new issue.  Then, throw in the awful charts and my choice is an easy one.

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Tip: Four line graphs for each segment with time on the x-axis would be a much better choice than this even if this one wasn’t in 3-D.  Boring? Maybe.  Effective? Yes.

As I thumb through my latest edition of BusinessWeek, I see many illustrations where the data visualization looks like the one below.  Also, it seems that with each new week come worse charts and graphs.  Looking at the one below, the 3-D effect adds absolutely no value and makes this chart pretty much useless.

[BusinessWeek, Oct 4-10]

I am pulling for the new management to do a better job, but I’m not very hopeful.  Want to make this chart better?  Simply remove the third dimension and make it a simple, plain old line graph.  If I had to guess, I’d say this might just be a case where the functionality lets me create it in the software, so it must be good, right?  Wrong.  Maybe Stephen Few is right in that great data visualizations start with well designed software that do not let the creator choose an option like this.

What do you think?  Blame it on poorly designed software or uneducated designers?

P.S.

Here’s another gem from the most recent copy of BW.

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Below is a great example of the wrong use of color in a column chart.  Use color to differentiate between segments, but don’t use it when time is on the x-axis for the different days.

A better use of color may be for each quarter within the year.  Using the chart below, it would make more sense to have every first week of the month always in one color, like blue.  Then, at least you could easily compare the first week of each month quickly.  I’m not even going to touch the chart title not matching to what is actually being displayed in the graph – days vs. weeks.

You really can’t make the color mistake if you used a line graph, just saying.

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The most recent copy of Information Management had the image below on page 8.  What’s funny is the person figure on the left looks like it’s wearing pants.  Oh wait, those aren’t pants, the blue is part of the data visualization.  The person on the right looks to be wearing orange work boots or ski boots for that matter.  The article by Julie Langenkamp is interesting and discusses how small vendors tend to rank much higher than large vendors in product support and other areas.

[image source]

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It appears that small vendors scored better than large vendors in every single category of complaints as shown in the chart above.  In the chart below, you will see that small vendors appeared to provide more benefit to the customer/client than large or medium vendors.

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There’s a lot more to the article if you are interested in business intelligence. 

One of the benefits I truly enjoy is having USAA as my insurance company.  It only took me one phone call to their customer service center to know why they consistently rank in the top of companies for customer service.  I can think of a few big companies that could learn a lot from how USAA treats their customers/policy holders. 

In their recent magazine, I quickly noticed the chart below that is called, "The Snowball Effect" while flipping through.  The heading that was cut off states the following:

"What’s the hardest-working investment tool you can use? The power of time. Beth, Bob and Bridget all invested $2,500 at the same 6 percent rate of return.  But see how compounding made Beth’s account grow? That’s the value of starting early."

Going back to high school and college one of the first lessons one learns is the time value of money and compounding effect.  I won’t get into that, but what I did want to touch on is the chart below that left me speechless for a bit.  There are so many things wrong with it that it wasn’t even worth taking out my red pen.  

I recreated the data from the chart in Excel (shown below) and used fictitious numbers for the middle of the graph.  Each person starts with the same money and each has an end amount.  So I basically filled in the blanks.   I know my chart doesn’t have Beth with her arms raised in celebration or decimals, but it’s definitely a lot cleaner and easy to understand.  This isn’t rocket science, is it?

12-17-08: I have added some titles to go with my chart numbers, as well as, pointing out the good and bad in each chart.  Please feel free to add your own comments.

From USA Today inspired by the Tableau blog, check out these interesting charts.  Some of these charts are so over-the-top that I laughed out loud.

#1 - Waddayoulookingat?

Bad – 3-D effect puts these two images at about the same size.  One is set back farther and doesn’t start at zero.  Intended to send and will actually send are two completely different actions.

Good – Data labels.  Would a better depiction of the 2008 card be one where the person had a black eye, disheveled hat and a few other bruises simulating the economy lately?  Possibly a foreclosure sign in the background?

#2 MMMM Chips

Bad – where does the data start from (zero on x-axis).  The use of chips for data referring to fruit and fruit cup. 

Good – I’m not alone… value labels and not much else.

#3 Guitar Hero – Chart Edition

Bad – Is he wearing a dress or is there a 6th series? I would have to say the shading of the bars from light to dark.

Good – It’s a decent bar chart with good label use and starts at zero. This is one of the better ones.  Where would laziness fall?

#4 Who’s Smarter (it’s a joke people)

Bad – The grid lines on the paper.  They should have gone with blank white construction paper. 

Good – I actually like this one.  I think the reader can quickly see the difference and understand the point.

#5 Definitely Cheese Head

Bad – Tilted bar chart.  The shading of the streaking ball which was obviously overthrown. The color use is not good.  Definition of “Hot” may need to be a footnote.

Good – Data/value labels both inside and outside the bar aren’t too bad.

#6 ….Ummm….Pass….Next.

Bad – Just about everything from the font color to the cylinder bars.  Could they be more specific or at least have sub categories?

Good – Easy to understand title. The value labels.

#7 Darn Kids These Days…

Bad – Do you even need to ask?  Seriously, just about everything. 

Good – The value labels.

#8 Guns Shooting Sparklines

Bad – There appears to be fluctuations from zero to the value.  Should there be time across the bottom?  Sun background images behind the values labels.  Can they define Smartphone?

Good – The chart title is easy to understand.

#9 Poll Done by Unbiased Gravy Producer

Bad – Does the area count towards the value?  Shadow of the “bars”.  Jumbled labels that are hard to read.  Poor title choice.

Good – Good contrast with the title font. The value labels are easy to read.

#10 Obviously These Parents Haven’t Seen The Game – Vice City

Bad – Beside being a pie chart (I think), the title is poor.  The value labels are hard to read.  It took me a long time to figure out the image is of a video game controller (again, I think).

Good – At least the values add up to 100%.

#11 Whole New Meaning to Split Ends

Bad – Just about everything including, but not limited to the title, attempt at bars, highlighting at the end and starting point.

Good – Somebody thinks outside the box at USA Today. 

Which one is your most/least favorite? My picks are #4 / #6 (really all of them)

Do you think any of these are actually good and would be effective?  I would go with #4, if I had to pick one.  Also, I am definitely guilty (and in the majority) on #2.

I received an email from the service ShareThis with the image below embedded.  The pie chart shows the top sites by category on ShareThis.  On a positive note, at least the labels are clear and pretty easy to read.

Anyone else see similar colors in the slices?  Poor choice or just the popular and most common choice?

Below is a chart that I would not recommend trying to copy for a few reasons.  First, using the little person icon instead of a bar chart distorts the data and adds to the confusion of the chart. 

Next, the sort also adds to the confusion.  The chart is sorted by change in the number of jobs from the previous year and in ascending order.  I would probably have created the chart so the sort was the percentage of people in each sector and in descending order.  Visually, this would have made the chart more organized.  Optimally, in an interactive version, there would be a sort button to toggle between the change in number and percent of jobs.

Finally, I would have dropped the ,000 and just noted that the changes are in thousands.  Better yet, I may have stuck with percentages all around by going with the percentage change in jobs from the previous year.

Source: BusinessWeek, September 8th Issue

Instead of calling them pie charts, we’ll just call them donut (doughnut) charts and make them magically delicious.  Wrong.  These two charts, which appeared in the July 14th issue of BusinessWeek, are some of the worst charts I’ve seen in a while.  Note: in the print version, the legend doesn’t cover up the actual chart.  I’m not sure why this wasn’t fixed in the online graphic. 

There have been many articles and blog posts written on the ineffectiveness of pie charts, so I won’t belabor the point more.  For more information about why pie charts (donut charts with the center filled in) are not a good data visualization option, see the links below.  There’s no point in saying the same thing in a different way.  The timing of this post is good being that Seth Godin recently created a lot of stir about bar charts, which led to more pie chart discussions.

Related books:

Creating More Effective Graphs by Naomi B. Robbins

Show Me the Numbers: Designing Tables and Graphs to Enlighten by Stephen Few

Related links on discussion of Bar and Pie charts:

DSA Insights

Jon Peltier

Peltier Technical Services

Jorge Camoes – Charts

Juice Analytics Original

Juice Analytics

Stephen Few

Edward Tufte

Junk Charts

Note: the first pie chart is credited to William Playfair roughly 200 years ago.

I just can’t seem to help myself when it comes to sharing beauties like the pie chart below with my readers.  The pie chart was found here.  Yes, it’s colorful.  Yes, it’s an example of pimping your chart.  And finally, yes, it’s extremely ineffective.  Just recreating this chart accurately was nearly impossible because of the small slices that are not even visible.

It takes entirely too long to go from legend to chart, legend to chart, legend to chart, (you get the point) to cross reference the two.  A simple bar/column chart would have been a much better choice.

Here is my version that took me longer to figure out which values referenced which slice percentages than creating the actual chart.

Suggested Reading:

The Visual Display of Quantitative Information, 2nd edition

Visualizing Data

Show Me the Numbers: Designing Tables and Graphs to Enlighten

Creating More Effective Graphs