BLOGPOST: Data Visualisation: When the numbers speak for themselves
KPI. ROI. Visits. Impressions. CTRs. Email open rates. Production metrics. Customer journeys and insights. Interactions. Big data, small data and more data. As the world becomes more digitalised and networked, companies have access to ever greater amounts of data, ever deeper insights and ever more details, and yet all this data has to be understood and “translated”.
While charts and tables are still indispensable in areas such as project management and controlling, the charm of statistical processing remains somewhat limited. For this reason, a number of creative visualisations have come together under the umbrella term “data visualisation”, where figures can be made comprehensible and appealing to both internal and external stakeholders. The availability of data along with interactive tools to process it are enabling even small and medium-sized enterprises to experiment with data visualisation. Like with all graphic communication channels, there are established rules for translating numbers into visuals... but with creative leeway, too!
Think, Shape, Think, Shape
Data visualisation is more than simply presenting data in a “cuter” way. Adding more and more numbers to existing visualisations, something quite the fashion a few years ago, does not necessarily make them more informative. Talking in stark terms, as a table will never be more appealing just because the dividing lines are coloured, an infographic is not going to become better with the incorporation of more numbers. When visualising data, form and function – thinking and shaping – go hand in hand.
Therefore, the first question companies should be asking themselves is “what added value does data visualisation bring?” Even if the question initially sounds provocative, it is essential to ask it. Successfully visualising data means telling a story that sends a specific message – as it provides easy access to complex insights. But unless the data can tell the story, the effort to develop a concept and design for visualising it might be better spent elsewhere.
Data visualisation also provides the opportunity to focus on numbers and data that are either difficult to comprehend or only described in detail. The target group can be visualised in the same way as corporate growth, sales projections and the diverse composition of the company’s own teams.
The more complex the numbers, the easier the presentation
Although it sounds contradictory, this is a basic rule of visualisation. The more complex the content, the simpler the presentation should be. The “speed” of the human brain also plays a role in how to shape the presentation. Every day, your brain processes millions of pieces of information each second, such as distinguishing traffic sounds, calculating the speed of the vehicles whizzing around you, interpreting red lights to mean stop and recognising the person across the street as a former third-year primary school classmate. Not only does all this happen in the blink of an eye, but for the most part subconsciously, too. And it is precisely these processes that graphics must confront, which (to put it mildly) have to be able to keep up with the rapid conclusions our brains make.
Colours, shapes and positions therefore need to adapt to expectations and experience. How what contents are arranged where and in which colour and size influences how significantly we perceive them. In terms of colour psychology, red is also interpreted as a “signal”. As mentioned earlier in the example of traffic, complex relationships should be ideally grasped quickly and easily when the data is visualised. But the consequence of an error in this process is not an accident. Rather, the displayed content would be misinterpreted, which in the end calls into question how useful the graphic happened to be.
Interactively bringing connections and developments to life
Just as digitalisation is making access to different data and information easier and more transparent, a number of more or less expensive tools are assisting us in visualising this amount of data. It is especially relevant when data visualisations are not just going to be integrated as images in print and online media, but will also be made interactive.
Three questions to help you find the right tool:
1. Where is the data coming from?
Even though it sounds banal, the “origin” of the data plays as much a decisive role as the format of it. Does the data have to be entered manually or is there a tool that can read existing .csv files, for example? Selecting the right provider can make things easier, particularly when different data volumes need to be visualised.
2. Where should data visualisation be used and who is the target audience?
Prior knowledge of the target group and what they are looking to see are critical when you are preparing the data. Nonetheless, it also makes a big difference whether the data is going to be visualised for the home page of a website or a company brochure, especially when an online tool, program or app is used to prepare it. If you are seeking, for example, to provide some insight at customer meetings into current production, it can be envisaged, on the one hand, that everybody involved will be able to classify the data in terms of content, and on the other, that it may need to be adjusted on the spot. Then it is worthwhile to “take the data with you” and have an app ready to make it available on different end devices.
3. How do data visualisations fit into your design guidelines?
For a holistic appearance, both internally and externally, new visualisations and interactive tools should also fit into the existing corporate design. When choosing the appropriate tool, it makes sense to pay attention to the arrangements and patterns of the backgrounds, colours and fonts.
This article was originally posted in our blog: https://www.newsaktuell.com/blog/data-visualization/