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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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I came across this chart and found it very interesting because of the stated benefits that some foods can have on your health (probably not verified by the FDA).  For instance, did you know that eating bananas can help quiet a cough or that apples improve lung capacity?  I came across this because for the last 8 months or so I’ve been on a diet kick to lose a few pounds and body fat while trying to maintain a healthier lifestyle. 

This grid shows how unorganized data can really cause a problem for the reader or viewer of the data.  This list is great if you want to check out the health benefits of eating a certain food item.  However, if you know that there is a history of heart disease in the family and you want to eat as much food that will protect your heart as possible, you need to scan each item to figure it out (as shown below to illustrate). 

[Publisher of chart]

The creator of the chart didn’t even put similar benefits in the same column as shown in my illustration above.  An interactive version would have been best so that the reader could sort or filter as needed to get what they want.  The next best route may have been to publish a few lists with the most prevalent benefits listed in descending order.  Another option would have been to list all of the health benefits in their own column and put check marks where that benefit is found in each food. 

Organizing or optimizing data that makes sense will go a long way with the readers.

The image below appeared in the redesigned issue of BusinessWeek after Bloomberg acquired the magazine.  I will honestly say that I studied it for a few minutes and read the text a few times before I really understood what the data was showing. 

I think the psychedelic layout of the bubbles adds a confusing element to the visualization that is unnecessary.  There are a bunch of different ways to show this data that would be more straight forward and easier for the readers to understand.

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Do you think the visualization layout/design adds or takes away from the data?

Below you will see a stacked column (vertical bars) chart that has nine different segments covering eight months.  I have absolutely nothing against HubSpot and actually think they have some great services, tools and products.  I am simply using their chart to illustrate the problems with stacked bar charts and some alternatives.

I can think of a few reasons off the top of my head as to why people would use stacked bar charts. 

1. To show how each segment changes over time
2. To illustrate parts of the whole at any given time
3. A combination of 1 and 2 above

The problem is that a stacked column chart is not good for either of these requirements.  My feelings on these charts is not really anything new, as I’ve stated before on this post and also this post.  In my opinion, after you get beyond two series with like scales, a stacked column chart is pretty and pretty useless. 

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The two charts below show the S&P 500 Net Income by Sector for both 2008 and 2009 and recently appeared in BusinessWeek.  What really caught my attention is that these column charts are a little bit like a waterfall with the only difference being that these start from zero.  Prior to using the Waterfall chart utility, I created these by hand.  The workaround to get a hidden or shaded set of bars is more difficult than it really needs to be.

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Below you will see my versions of the charts using the same data and Excel.  I didn’t include the gray shaded series because I do not think that it adds any value.  Also, I do not have the text box calling out the title and final value because there is a column at the end that shows what the value is upon finish.

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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.

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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.

[image source]

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?

Below you will see a column chart that appeared in the weekend’s print edition of the Baltimore Sun.  It’s no secret that they used a gradient fill on the columns to give it the fading appearance.  I’m not a big fan of the gradient fill on the 2009 columns, but this could work for the previous year’s numbers (2008) if the intent was to minimize the prior year.  I doubt that was the case as I’m sure they were trying to make the chart "pretty" or different than the default setup.

Below you will see a replica that I made using Excel and the fill effects formatting option.  It looks alright, but something still isn’t right.  What is the problem with this chart?

The problem is the y-axis and the scale that was used.  I don’t think this is a straight out misrepresentation in order to mislead, but it could be.  That’s the risk you face when manipulating the axis.  Yes, the columns take up a lot of space when the axis starts at zero, but that’s the correct method here.  To help illustrate my point, check out the exact same chart (below) with the y-axis starting at zero.

This version using the correct axis setting accurately shows that October, year-over-year, is not three times as much, but only about 1.5 times greater.  Also, look at the trend of the first replica chart.  The upward trend definitely has a greater slope compared to the replica with the correct axis.  To help prove this visually, check out the side-by-side comparison below using a trendline in the chart.  The slope of the chart on the left is much greater than the one on the right.  If you were presenting this data in something like PowerPoint or SlideShare, and quickly went to the next slide, the audience might not catch the axis starting at 5 and the steep trendline would be the point taken from the data.

Furthermore, forget the gradient fill and go with something like the chart below if you want to highlight the current year.