Data visualisation and the bigger picture of visualising other types of data
Why would you want to do that? Well to share his thoughts on that topic let’s welcome back one of our regular contrarian voices.
Guest blogger Tony Boobier is an author, commentator & mentor, since his days advising insurance firms whilst an IBM executive. He’s shared with us before on topics as diverse as discernment, loneliness & the end of your leadership career. Now lets’s hear his view on Data Viz.
I asked Tony to share an end user’s perspective on Data Visualisation. What’s the view of those for whom analysts often produce their charts? What are they looking for from visualisation in the future? What would provide them with fresh insights? Here’s Tony’s view…
Stepping back from a focus on technical delivery
It’s tempting with a topic like data visualisation to instantly focus on topics like dashboarding and clever bi-directional data manipulation. The ability to dive into detailed data through an effective front end visualisation, with click-through capabilities, has increasingly become a minimum requirement for business intelligence and dashboard vendors.
Readers thinking about effective visualisation will invariably consider issues like:
- Understanding the audience, and aligning the visualisation accordingly
- Effective use of graphics and colour
- Benchmarking as an effective tool, which provides context
- Where visualisation is used in presentations, the effective use of storytelling leading to an effective conclusion
But aren’t these just technical aspects which can be learned by anyone and implemented with a bit of practice? Many data tools such as Excel and Tableau, to name just two, already have visualisation tools and templates or ‘wizards’ built into them. Data visualisation is no longer the complex skill that it used to be.
Visualising other types of data
The need for effective visualisation has become an increasingly important attribute especially as leaders and managers are increasingly overwhelmed with the sheer amount of data and information available.
So, in the nature of being slightly disruptive, I wanted to take a huge step backwards and perhaps hopefully make readers think a little more about visualisation generally.
Data is more than financial or business-orientated information. It’s a broad term which reflects a mathematical way of capturing information and ultimately communicating it. How do we effectively visualise non-financial and non-business information?
Three areas I would like to focus on by way of example are those of ‘location visualisation’, ‘experiential visualisation’, and finally ‘emotional visualisation’.
(1) Location Visualisation
Dealing firstly with location visualisation, we should think about the topic in terms of ‘location intelligence’. This is a technological repositioning of the concept of creating and using maps. Mapping is important as a topic as it portrays the visualisation of what was originally just the spoken word.
The first maps of the world are thought to be from 4th or 5th Century BCE (Before the Common Era, as an alternative to the Dionysian expressions BC and AD). They changed the way we communicated and absorbed data about distance and places. Imagine circumnavigating the world if journeys had been based on the spoken word alone?
Location intelligence is a later evolution of the mapping story, recognising that everything and everyone is somewhere. The ability to apply localisation to sets of data to help us to understand critical information – customer base, footfall, flood risk – has become increasingly critical.
Data visualisation companies increasingly add a location component. Mapping companies are improving the way that different sets of data are visualised by adding a location component. In effect, there is an increasing convergence of two inter-related technologies.
(2) Emotional Visualisation
For the purposes of this particular post, I also wanted to stretch your imagination by suggesting that emotions and experiences can not only be digitalized but also be visually imaged or visualised. Doing so can add to our understanding. I suppose it’s a logical extension of visualisation of sentiment analytics.
In terms of visualising ‘emotions,’ one example to consider is the very visual concept of a ‘rollercoaster of emotions’, that is, how emotions can change relative to a set of circumstances, and how processes can be changed to manage (or manipulate) that rollercoaster.
Imagine the ongoing situation of the recent UK flooding. When a homeowner’s home is underwater, they feel like they are in an emotional ‘trough’, a bit like the trough at the bottom of the rollercoaster ride. When they realise they are insured, they feel better and their emotional state improves, a little like the rollercoaster climbing up the slope. Then they find out that the process will take weeks to resolve, and their emotional stage quickly falls, like the rollercoaster car rushing down the other side. And so on it goes, up and down until the problem is eventually resolved. A complaints process might follow a similar up and down journey.
I write about this concept of the emotional rollercoaster in my book on insurance. Making the point that processes need to be designed using operational analytics to best manage the customer’s rollercoaster ride:
(3) Experiential Visualisation
In terms of visualisation of ‘experiences’, this seems at face value to be much trickier. One of the most influential books I have read is called ‘The Atlas of Experience’ by Jean Klare & Louise van Swaaij. It portrays in a visual and perhaps slightly quirky way, in the form of a map, how we as individuals travel across the ‘World of Experience’ to reach our eventual destination.
By way of example, considering the world of work, our personal journey might take us from the foothills of ‘Persistence’, across the ‘Mountains of Work’, through the ‘City of Stress’ and its suburbs of ‘Tension’ and ‘Drudgery’. From there into the ‘Valley of Duty’ and eventually down to the seaside resort of ‘Prosperity’. Its only one possible route, as a wrong turn could lead us to the village of ‘Failure’.
The point is that visualisation isn’t a new idea. As a concept, it is ‘age-old’ and used by ancient civilisations to discover their world. Nowadays, we are increasingly using tech-driven visualisation to help us better understand massive amounts of financial and business data. But, in terms of the story of visualisation, it seems that this particular journey is far from being completed.
Won’t the next step be to develop the use of visualisation to more effectively understand less-structured forms of information? Data such as emotion and experience. Won’t we need to converge that with more traditional structured forms of data?
How do you see Data Visualisation developing?
Many thanks to Tony for sharing his perspective, challenge & what looks a fascinating book. Has that post prompted any new thinking from you? I hope so. It would be great to hear others perspectives on the Data Visualisation capability we need for the future.
Is the growing use of web-based interactive data visualisation the way to go? Will dashboards evolve into something that helps executives steer their businesses forwards, or are they an immature solution? Whether you’re a Data Artist or a Data Viz Consumer, please get in touch if you have a post to share on how you see Data Visualisation needs to evolve.