»Me, myself and BI«

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No peaceful peaks

If you are a fan of graphical visualizations, this blog will probably be hard to digest. As much as we love them, charts are actually dangerous communication tools if you take a good look at them. Why? Because our stone-aged instincts usually misinterpret them.

Let’s assume that we want to climb a mountain. Before our journey, we study its profile. If the slope remains constant, we calculate that our assent will be constantly difficult and strenuous. Experience shows that our intuition is usually correct. I assume that this ability is an instinct that dates back to the Stone Ages. Hunting and gathering food, escaping danger, or spotting optimal rest areas all required that people could assess paths accurately. And indeed, we are very good at interpreting upward and downward slopes in analog and, therefore, absolute form.

Mont Vinaigre
The silhouette of Mont Vinaigre in Southern France. Time series often look similar but they are not. Is that why there are so many misunderstandings?

Charts are often based on analogies to real-world objects. Take line charts, for example. Line charts – especially when displayed as area charts – often look like a mountain summit. Let’s take a look why that misconception is so fatal.

Let’s assume that we are looking at a time series with 24 periods. In the first ten periods, each value increases by ten units apiece. It then drops once by twenty units. Afterwards, each value drops by 5 units a total of 13 times. That looks like this:


A time series or a foothill of Mont Vinaigre?

A mountain climber will clearly see that the ascent is constant. The first step is just as steep as the last. A business professional, however, is more careful. He rarely focuses on absolute changes in time series. Linear scales have a constant upward slope when relative increases decline or performance drops. A logarithmic scale quickly sheds light on that:


Logarithmic visualization of the same data.

Logarithmic scales are not common. As a result, most readers of daily newspapers or managers who analyze reports are on their own when it comes to avoiding misinterpretations. I personally believe that our brains are so molded by stone-aged instincts that they can’t read the linear chart above like the logarithmic one below it. We follow the ascent with undying optimism – and can’t see the warning signs behind the drop in growth. Linear axes don’t give early warning signals.

Let’s climb another mountain – but this time, let’s choose the one in the second chart. Now, our stone-aged instincts help us feel with each step that our ascent won’t take much longer. And sometime later, the decent will get steeper and steeper. Therefore, managers who want to understand their data landscapes have to hike them in logarithmic boots.

3 comments for “No peaceful peaks”

  1. Matt said:

    Well, yeah, if you’re going to fill in the area under the plot, and with an unnecessary gradient at that, it’s gonna look like a mountain.

    And you use of the logarithmic scale here is…interesting. I see what you mean here, but I’m not sure of the point. A constant slope on a log graph, for example, would require exponential growth of the whatever, which is almost certainly unsustainable.

    Examples with real data would be useful here.

  2. paresh shah said:

    Essentially all line charts whether the area is filled in or not gives a wrong picture. The core strength of the line chart is to show the shape over time – without the log scale – errorneous!!!!!!!!! \if it onvolvrs comparison between two shapes ……………………….

    .

  3. paresh said:

    Well the problem is evident – how do we resolve it??

    A simple statement in line graphs stating that constant slope indicates declining relative performance??

    Unlikely to work as the first impression is created by the visual chart. The only solution use log scale only

    Would there be any situation where a linear scale would work as the major feature of a line graph is to show shape over time.

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