If there’s one thing that all Business Intelligence vendors should hang their heads in shame about, it’s the inclusion of gauges in their products.

The use of gauges probably derives from the association with the word “dashboard”: car dashboards have gauges, so Management Information (MI) dashboards should probably have them too. But MI dashboards are so named because they share one particular characteristic with car dashboards – a very small amount of the most important information is served up in a place that requires one glance.

Gauges are very useful in cars – when you drive, you spend hours at the wheel, a good proportion of which you spend glancing down at the speedo and rev-counter (or fuel gauge, if you’re a grown-up). Because of the amount of time you spend looking at the speedo, the position of the needle will give you a good indication of the speed you’re doing. But, until very recently, the dashboard in a car has been a mechanical solution to the problem of displaying data.

This isn’t so true of MI dashboards – as much as it will disappoint budding dashboard authors, users will not spend a good proportion of their time looking at an MI dashboard. They’ll probably have a quick look to see the position in the morning, but that will be it. Additionally, you aren’t limited by the constraints of building a mechanical device (unless your business user is a committed steampunk). So, is a gauge any use?

The key with a dashboard is to convey as much data as possible, using as little processing power of your reader’s brain as possible. This means maximising the amount of data vs non-data ink/pixels used. Or, reducing the amount of non-data ink as much as you can. Let’s analyse the standard QlikView gauge, and see if that complies.


This gauge looks like a speedo and shows that we’re doing ok against our target. So how much of this gauge is actually data? Of the 41,000 non-white pixels, only 13,500 are being used to convey data. So only 33% of the brain’s processing is being used on something useful. The other 66% of the gauge is wasted ink. How can we improve this?

QlikView allows us to strip away a lot of the non-data pixels from the gauge, leaving us with this:


Which gives us with a good concentration of data vs non-data pixels. But, is there a simpler way? Is this the quickest way of getting the data into your reader’s consciousness? Remember we aren’t limited by having to build an actual physical version of this, so all the restrictions that applied to the designers of the speedometer don’t exist when designing an MI dashboard. If you think about what we’re trying to convey with the gauge, in very simplistic terms, it’s just one number. And, there is an incredibly efficient way of conveying a single number that will be processed nearly instantly by the human brain. This method is called “the number”:


Every single pixel is telling you the exact value that is being shown to you, and there are a lot less pixels for the brain to process. Which brings us to another point about the gauge – it doesn’t show you what the value is, unless you write the value on the gauge. And then the gauge becomes entirely non-data.

Being less simplistic, and more fair to the gauge, it’s actually showing you two numbers – the current value, and how far along the scale the current value is. But again, a simple percentage will get that information into your reader’s brain quicker with less processing required:


And that is why a gauge is almost data dis-visualisation – although graphical, it actually makes things less clear than a simple number.

Have you ever seen a gauge used where it made the visualisation better?

If you would like to discuss these issues, or the impact of emerging technology or data and analytics on your industry, then contact our Data & Analytics team.

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