Data Visualization: A Four-Point Checklist


Data visualization is a hot new field, one that's popular with senior executives, mainly because they are tired of looking at and trying to interpret hundreds of numbers on reports to find useful data. Data visualization breaks the monotony of traditional reports, and good information visuals are a great way to get the point across and spur action.

That said, a lot of hype has surrounded data visualization in the last few years -- as you can see by the number of visualization startups, vendor product offerings, and conferences dedicated to the topic. The risk with the hype is that it may get in the way of data visualization's utility. I have heard vendors and consultants sometimes interchange analytics with data visualization in their pitches; this is not a welcome trend, as it leads to additional confusion in an already complex marketplace.

I am a firm believer that data visualization is a useful tool that, when used in the right way, can be very powerful in the hands of an analytics and business intelligence professional, especially when communicating with senior leadership or a broader audience. Edward Tufte and other statisticians and information graphics experts have produced great literature on creating effective visuals, and over the years I have tried to incorporate it into analytics presentations. With this guidance, I've developed a four-point checklist for evaluating the visuals I create to support analysis.

 

  • Does it have clarity of purpose?

 

    Good information visuals should help either tell a story or discover a hypothesis. Unless you know what you are trying to achieve with the visualization, beginning work on it isn't a very good idea.

 

  • Does it help create a shared understanding?

Efficient visuals are those that allow users to look at vast quantities of data and multiple dimensions quickly without losing the simplicity of display. A lot of visualization examples focus on fancy information art, but for an analyst, presenting the data in the simplest visual way possible is key. The visual should support and facilitate understanding, never distract or detract from it. Another tip to remember: Use consistent chart styles for the same or similar data presentation throughout a unified body of work. This helps the reader to understand the key messages quickly.

  • Is it adding to the explanation of data?

Design the visualization to highlight causality between the data variables, integrating words, numbers, images, and diagrams to tell the story and provide context for and meaning to the data.

  • Is it helping to uncover insights and suggest actions?

Emphasize the information of interest and present it at a resolution sufficient to enable action.Say, for example, the company is analyzing call center performance to help identify training requirements. In this case, a visual showing performance on a call center level would not be helpful. To be useful, the visual must show performance by agent. Thinking about the potential action defines the resolution and granularity of the analysis, as well as the visual.

 

Good data visualization can help communicate the information that drives smart decisions.

Executives responsible for developing a business intelligence and analytics strategy should keep in mind that data visualization is a piece of the overall puzzle, but by itself it does not help provide insights. Think of it while you are evaluating your reporting strategy but not as a replacement to analytics.

Amaresh Tripathy, Principal, PwC

Amaresh Tripathy is a Principal in PwC's Advisory group and founded the firm's information analytics practice, which he helps to manage. He has helped Fortune 500 companies in multiple industries (telecommunications, CPG, healthcare, insurance) to use bottoms-up data analytics in strategic decision making. His work has focused on developing growth and pricing strategies, defining market entry plans, understanding customer behavior to increase profitability, improve marketing efficiency, developing operations strategy, and streamlining distribution. Amaresh received his Bachelor of Engineering from the National Institute of Technology and has a graduate degree in Transportation Systems Engineering from the University of Texas-Austin.


Re: Getting a jump on data visualization
  • 9/14/2011 12:38:15 AM
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Pierre and Beth,

Great point here. Ability to communicate data visually, like the ability to communicate it verbally or in a written report, is a skill in itself.

Re: Getting a jump on data visualization
  • 9/12/2011 10:37:18 AM
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Pierre -- I think you raise a good point. The visualization shouldn't be either so simplistic that it provides no real value or so complicated that the viewer spends more time trying to decipher it than in assessing what the valuable information (presuming there is some of that) it's delivering. I suppose what this means for any organization presenting business analytics in data visualizations is having somebody on the analytics team who is able to think visually and intuitively understand the best way to deliver the data. Not every analyst may be capable of this.

Re: Getting a jump on data visualization
  • 9/10/2011 12:15:00 PM
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AAphil,

I don't fully agree with your point, but I may see what you are suggesting.  More times than not presenters crowd information on a slide -- I saw presentations from government agencies that crowed text and images on one slide, leaving no really solid direction or takeaway.  Now, in some defense, it is possible to set one graph where the information is not really leading to a decisive conclusion - imagine a pie graph of all the people who rely on water for survival - er 100% - and you get the idea. 

This post on visual optimization can lead into presentation discussions regarding the balance between too much text and presentiing information intuitively so that the stakeholder discussion is on the decision at hand, not just how it is presented or how the information is captured.

Re: Getting a jump on data visualization
  • 9/9/2011 4:01:37 PM
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Wow. I find that discovery a bit surprising.

Let's take a poll of most people at conferences and meetings. How many people remember the information on the 1-D graphs and charts? (No one). But if you have colorful and distinctive visual aids, that sticks out. More importantly, it appears more meaningful.

Re: Getting a jump on data visualization
  • 9/9/2011 2:53:12 PM
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aaphil -- i read somewhere recently (can't remember where) that using pie and bar charts was a horrible practice. I really don't understand why that would be the case, though (unless it was graphics snobbery or some such!). I do think many users understand through visual means, and if a pie chart, as simple as that might be, helps deliver that information in a way that's more digestible, why not use one! Some infographics can be so complicated as to be completely counterproductive.

 

Re: Getting a jump on data visualization
  • 9/9/2011 2:48:47 PM
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Amaresh -- good point. Thanks!

Re: Getting a jump on data visualization
  • 9/9/2011 12:07:03 PM
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Beth, thank you.

Absolutely - interactive visualization fits right in. Infact, I do not explicitly call it out as I see interactivity as one very powerful feature available to the analyst across all the 4 points in the checklist and as the survey notes; is very effective in getting the message across among users.

However, sometimes it is not possible given the context of the meeting (using printed slides in a face to face meeting). 

The key is to realize that interactivity is a feature instead of separate technology which is how it is sometimes presented.

Re: Getting a jump on data visualization
  • 9/9/2011 12:00:51 PM
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Beth,

The way it seems to me that the use is more productive with interactive visual tools is because we are visual beings and it is much easier to see a chart than look at rows & colums of data on a chart or spreadsheet. It helps users to want to use the system.

Getting a jump on data visualization
  • 9/9/2011 11:34:31 AM
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Hi Amaresh, welcome to AllAnalytics.com and thanks for providing this checklist guidance on creating data visualizations. Based on this blog plus data i just looked over from a Bloomberg Businessweek Research Services survey of 930 business professionals around the world, I'm wondering where interactive data visualization fits into the scheme of things. Do you find much value in making data visualizations interactive, and if so, for what purposes? (The BBW research shows that 35% of organizations that report higher use of business analytics tools use interactive data visualization vs. 16% at organizations who aren't reporting increased use of analytics. (See my blog for more details on the survey.)

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