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Category: Visualisation

Articles about visualisation, critique of bad ones, celebration of good ones and visualisation heroes.

Seeing Brains

I love the comments I get from people who see a Causal Decision Canvas for the first time.

Once they get to grips with the cause-effect concept they start exploring the Canvas. They’re drawn into the story of the whole system, the dynamic structure, the feedback loops.

They ask questions: What does it mean when that circle or arrow is bigger, fatter, brighter? The Causal Decision Canvas Anatomy helps to answer these questions.

Then people see brains. The shapes formed on the causal canvas literally look like human brains (well, apart from the one which looked like a mouse’s head).

This is the perfect visual metaphor because the pictures emerge from our mental models which are usually trapped, unseen, inside our heads.

Seeing a picture makes something more concrete. Our strategies have taken shape before our eyes; we can see their form with renewed clarity.

Usually though, the early versions of a Causal Canvas are a mess. We have to acknowledge and embrace this complexity because it naturally reflects the myriad ways people think about the world. But we can then start to tame that complexity with visual analytics.

We can get rid of the ‘noise’ and just retain the most influential paths and loops. We can emphasise parts of the model to draw out themes. We can see where we’ll get the most ‘bang for our buck’.

We can point to the most important decisions and outcomes to show where we need to reduce uncertainty or design new performance measures. We can re-cast these parts of the model for more formal problem analysis, or a business case.

The model requires us to express claims, opinions, beliefs, variables and probabilities rather than commit to certainties. The dialogue revolves about the ‘structure’ of the causal model rather than a reflection or judgement of individual positions.

This gives us a new, visual vocabulary. We can articulate purpose, vision, mission, goals, objectives, strategies, decisions all in one place. We can show how investments, initiatives, programmes, projects, interventions could change something for the better.

With this big picture in front of us we can think more clearly and communicate more clearly. In a world of noise, both inside and outside our brains, that’s something worth seeing.

A Bellyfull of Pie

This chart has been served up on LinkedIn recently and will no doubt have data visualisation purists choking.

I tracked down the original to this publication by Wolfgang Digital. The story the visualisation is trying to tell is that:

“More revenue is carried by internet sessions on desktops than on other devices.”

However because of the chart type and other design choices we have to work a lot harder to get to this message then we need to.

Pie charts are notoriously poor for making comparisons because humans can’t easily compare rotational angles or areas. In this case the designer also wants us to compare categories across two pie charts, sessions vs. revenue. We are then forced to look up the categories using both the cute device icons and coloured keys.

Trying to link these variables in our heads imposes a hefty cognitive load. Crucially, under its weight, the central message is obscured.

Here’s our alternative rendered in both Excel AND Tableau (can you tell which?).



This type of visual design might not look as sexy but it doesn’t get in the way of the story that “Desktop sessions carry more revenue”. We can subtract the pie charts, colour, legends and yet amplify the key message.

This shifts the role of the visualisation away from marketing eye-candy towards management decision-making. We consume the chart with more natural visual perception and rapid insight.

The biggest un-answered questions are how these proportions are changing over time and the distribution of sessions and revenue by purchase type. We also might want to know more about the source of the sampled data.

Minimal panels like these can pack a lot of decision signals onto a single screen or page and dispense with noisy ‘chart junk’. Most data visualisation and dashboard tools can be applied to this task to overcome the lazy defaults. We just have to make a conscious effort to stop software tools dictating the style of our visualisations, especially when they impose poor design choices and visual bloat.

At Measureology we often prototype in Excel and then use Tableau for production dashboards with virtually no change in how these are displayed or interpreted. But we’re not precious about Business Intelligence, dashboard and reporting tools as long as they can cut the visual mustard without a bellyfull of pies.

Visual Signals

Put better visual signals in front of your decision makers by starting with an easy experiment: Translate your existing management reports into a visual prototype.

A Visual Management Pack is a quick, practical exercise – one of our Visible Sprints – and only takes a couple of weeks. You could even have something ready for your next leadership meeting.

If you want to set up a discovery call to explore the idea of a Visual Management Pack then get in touch.

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