Browsing articles tagged with " bar chart"

Worst Bar Chart* of 2014–We May Already Have a Winner

Jan 29, 2014   //   by Karen Lopez   //   Blog, Data, Data Visualization, Fun, Snark, WTF  //  6 Comments

 

Update: It appears that this chart and other data visualizations have been removed from the website and report.  I’m hoping that means that the authors will be refactoring them with improved graphics.  Meanwhile, I’m going to leave my post below as is.  There are good lessons and tips to be shared. 

I know.  I hear you. It’s still January and we might just have a winner, one that will be impossible to beat during the next 12 months. Incredible. As you may recall, in late 2011 I awarded Stupidest Bar Chart to a doozy from Klout.  That bar chart was confusing, but not in the way this one is.  First, put down your beverage of choice.  Then take a look at this:

 

image

 

Yeah.  That…chart.  It’s kind of like a horizontal stacked bar chart.  I don’t understand anything about it, though.   This chart comes from an infographic at Deloitte.com  on Analysis Trends for 2014.

Maybe zooming in might help?

 

image

 

Nope, doesn’t make it any clearer. In fact, it’s just as crazy, but bigger.  Call it Big Crazy DataTM.

Here are the issues and questions I have about it:

  1. What do the colours mean? If this were a stacked bar chart, the grey and blue areas would indicate different data.  It appears that only some sections have data. But I’m not sure.
  2. What is the scale?  Normally a bar chart would have an axis that indicates some measure and all the bars would be graphed against that axis.  This has no axis.
  3. Why do some bars have signed numbers and one have a range?  Why are some numbers unsigned? Even some delta numbers are unsigned.
  4. What do the relative sizes of the sections mean?  In one bar we see a blue section labeled 285, but it’s larger than a section labeled 425-475
  5. Where numbers appear, do they describe the section they are on or the section next to the number? I’m not sure
  6. What does the relative position of the blue section mean? I’m not sure.
  7. Why are some of the labels in light grey and some in dark grey? I’m not sure
  8. What are the units of measurement for these numbers? Are some percentages? Units of 1000s? 100,000s? Are they of people? Positions? Something else? I’m not sure.
  9. Do the endnotes there explain the numbers? No, they are just citations for reference materials used to create the report.

Maybe the chart has an explanation inside the full document, Analytics Trends 2014: (And why some may not materialize)… No, same chart, no text that directly explains any of the numbers. To add some irony to this, the report itself is about Analytics and even covers trends in visualizations.

A Picture is Worth A Thousand Words, Unfortunately.

image

The report has something to say about data visualizations used in data analytics:

There’s no question that visualization has become a critical capability for organizations of virtually every shape and size. Easy-to-use software makes complex data accessible and understandable for almost any business user. From discovery and visual exploration to pattern and relationship identification, today’s visualization tools easily affirm the adage that a picture is worth a thousand words. Or, in this case, numbers.

This is especially true with big data, where visualization may even be a necessary capability for driving insights. That’s why visually oriented tools are rising in prominence for many big data applications. Users get to understand, explore, share, and apply data efficiently and collaboratively—often without the need for analytics professionals. And that’s where the risk comes in. In their eagerness to dive into data, users may choose polished graphics over thorough data preparation and normalization and rigorous analysis—glossing over important insights and analysis opportunities and potentially producing erroneous results. [emphasis mine]

Keep reading the report from that section.  The irony burns.

What’s Going on with this Bar Chart?

I’d bet that the Analytics professionals at Deloitte know much better than this.  The webpage and report for Analytics trends is beautiful to look at.  I’m guessing that a graphics designer has taken these numbers and created a beautiful, yet meaningless graphic with numbers. And just as the report predicts, people who don’t understand how to best use visualizations can gloss over important insights and analysis opportunities and potentially produce erroneous results.  This report has some great points. And it’s pretty.  Very, very pretty.  But the distraction of bad visualizations makes difficult for me to actually see the points the authors are trying to make.

My guess is also that this data, as a set, had no business being put together in one chart.  I’m not sure, but they don’t seem to have the same measures or even be the same type of data.  So putting them in one chart won’t help.  This was a page in a report needing a graphic, so someone made one.

*Updates:

Jamie Calder ( @jamiecalder) helped me “see” the story this chart is trying to tell: think of it as a math equation.  That might get you there.  But it’s still not an appropriate use of a bar chart.  And Josh Fennessy ( @joshuafennessy)  has pointed out that this isn’t supposed to be a bar chart at all. It’s supposed to be a waterfall chart.  But it’s dressed up as a bar chart, so I’m going to still leave as a contender for Worst Bar Chart of 2014.  Let’s just call it a self-nominated chart.  Martin Ribunal has found what is most likely the original chart from which this chart was most likely copied inspired by and has listed that in comments below.

What Have We Learned About Data Visualizations?

  1. The best data analysis can be invalidated with bad data visualizations.
  2. If you develop content, insist that you say in the final published work.  I know this is difficult in large corporate entities, but it’s important to ensuring that your goals are met.
  3. The more accessible we make self-serve BI and data visualization tools available, the more responsibility we have to educate, train, and mentor those using these tools.
  4. Show your visualizations to other people.  Ask them what they see. Ask them if they are confused, what conclusions they might have and what questions they still have.
  5. Choose the right chart type to fit your data.  Then use that chart correctly.
  6. If you needs a graphic image, don’t mimic a recognized chart type. 
  7. If you add a chart to a document, you should actual reference it in the text in the way that helps the reader understand it.
  8. If your chart has numbers, you have to say what those are number of, including some sort of unit of measure.  And your graphics should correctly portray their relative size.
  9. If a chart leaves viewers saying “I’m not sure” more than once, it’s not working.
  10. Loving your data means loving how it is presented, too.

What Would You Ask?

What other questions do you have about this…graphic.? How would you improve it?

I can’t bring myself to call it a bar chart any more.  But it’s still dressed as a bar chart, so it fits the nomination category.  If you find a bar chart or any other data visualization to nominate, let me know.  I wouldn’t want something worse than this one to go unrecognized.

Stupidest Bar Chart of 2011 – Congrats, Klout!

Dec 22, 2011   //   by Karen Lopez   //   Blog, Data, Snark  //  10 Comments

I’m no expert in graphic design or data visualizations.  I do know that pie charts are evil, as are most gauges and uses of 3D in dashboards.   However, when I saw this bar chart from the fine folks at Klout, I knew it was a winner.  Even the name of this category is wrong: Top Influential companies?  No, from their description, this is a list of companies that were most talked about the most often.  That doesn’t make a person or an organization influential.  Otherwise, I’d be dressing like Kim Kardashian and collecting Justin Bieber dolls with weird "try me" portals

At best, these companies influenced people to say things about them by doing something well…or in the case of Netflix, doing a lot of things poorly.  But they didn’t do the influencing.  People on the social networks did.

 

KLOUT bar chart - click to see full chart

 

This data visualization is a list of companies who were most talked about…so they’ve used a bar chart.  Bar charts are supposed to be used to show quantities, usually over time or some other measure.  But this ranking  is not a quantity.  In fact, the bar chart is emphasizing the wrong thing, too.  Notice how 11th place Facebook has more bar?  But it’s in the worst place in the list.  Or is it?  We don’t know because the bar chart is showing us conflicting information.  It could be that the top 11 companies are being ranked 11-1 in descending order based on their influence mentions.  From the list, I’d think think that the influence was descending, but I don’t know.  If someone doesn’t know and the visualization adds no more insight than just a list of the companies, don’t add a chart.

Jen Stirrup, BI expert and Microsoft MVP, has some more to say about bad bar charts. 

Don’t use bar charts to show rankings.  Put down your data viz tool and take a walk.  Notice the real world around you, then come back and think about using visualizations to help a reader understand the data better. That’s how to love your data.

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