Chart-Making: Cures for Loss Aversion

Loss aversion – wrong chart example

Monney Income - wrong chart

JunkCharts writes an interesting post on how loss aversion can happen in chart-making. The general concept of loss aversion tells us that “people strongly prefer avoiding losses than acquiring gains”. Translated to chart-making, it means that there is a “tendency to avoid losing data at any cost”.

“To clarify, add detail” says Tufte. Corollary: you should make data-dense charts and maximize the data-ink ratio. Problem is, this fits too well into the loss aversion tendency. Take the above chart, for instance: does it make any sense to add those nine series to a single chart? What insight do you get from it? Only one: the designer don’t know how to handle a larger number of data series.

Remove irrelevant data series and you risk a mutiny on the Bounty, even if relevant trends are easier to detect. It is absurd, but very human.

So, how can you give the users all the data they expect while keeping the chart clean and readable? Well, to clarify, add detail to existing patterns (that’s what I just did to Tufte’s sentence…).

Tufte talks about “data layers”; Ben Schneiderman’s Visual Information-Seeking Mantra (“overview first, zoom and filter, then details-on-demand”); the focus+context technique. All they convey a simple idea: prioritize your data. Know what is relevant and what is nice to have. Don’t give the user a final product. Make an interactive chart and let her discover what’s inside.

I see this loss aversion tendency at work every day at the office. Do you too? How do you handle it?

7 thoughts on “Chart-Making: Cures for Loss Aversion

  1. Jorge,

    To fix the chart above you can assign the high , middle and low income series of the Income Level chart 3 base colors. Within the groups you assign the lines tints of the same color .

    By having a base color that labels the groups the you make the chart easy to read and it immediately tells you a story. I will blog about this later on :

    http://blog.xlcubed.com

    Andreas

  2. Andreas, I agree that grouping data using colors is a very effective way of creating “reading levels” without removing data. Another option is a panel chart, like the one in the Abortion Ratios post.

    Maybe the readers can come out with other creative alternatives…

  3. Jorge

    You have given us an interesting challenge.

    I tried a bump chart first, however, it wasn’t much better. Then I tried a dot plot to focus attention on the 1967 and 2995 values.

    Here’s my post link

  4. Jorge,

    I am not really sure whether this question belongs here but it is sort of related. I am trying th plot the sales of nine retail outlets under a brand over the last twelve months. I would like to emphasise the overall pattern of sales in the outlets – a line chart would be appropriate. But plotting all the data leaves a jumbled chart, similar to the example here. While a panel chart would work, I would like to create a single chart – I would also like to plot other charts on the same page. Suggestions??

    paresh

  5. Paresh, it depends. for example:
    – A vertical panel or sparklines could be an option if the chart is to be printed;
    – An interactive chart could be another option if the user can select a series – in this case, two or three relevant series would be color coded and the others would be grayed out. When the user selects one of them it would also be highlighted;

    If you want to have only one static chart you should group outlets by color. Read this post (and the comments) at More Information per pixel fore more details.

    Other readers may have different approaches to the problem.

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