What analysts can learn from Storytelling with Data
One of the most practical Data Visualisation books for my clients is “Storytelling with Data“. So, this is a longer than usual book review of this modern classic.
I say that because it is not just accessible for those with no background in Data Viz but also focusses on the kind of charts most analysts produce. You won’t find admonitions to keep update with the latest packages for R or Python. You won’t be overwhelmed by award-winning Data Viz art.
But, before I rush in with too much enthusiasm, let me tell you a little about the author. Cole Nussbaumer Knaflic started her data viz career at Google. There she honed her craft & transformed their People Operations with incisive charts. She has since gone on to found Storytelling with Data, her own training & consulting business.
Practical data viz, not aiming to impress
What makes Cole such a refreshing voice in the data viz community is her focus on more effective basic charts. The type of charts most analysts will be asked to produce for their business day in day out. Her style & guidance really suit businesses, with a focus on the key message, not the data artist.
So, what is so helpful about this book? Why do I recommend it so readily. The first is the clear structure. Having attended one of Cole’s training courses, I can confirm that she also trains analysts using this same framework.
A structured approach to Storytelling with Data
In the introduction to this book, after highlighting the problem (too much #BadDataViz), Cole lays out her approach in 6 steps:
- Understand the context
- Choose an appropriate Visual Display
- Eliminate clutter
- Focus attention where you want it
- Think like a designer
- Tell a story
That workflow also provides the structure for the majority of the rest of this book. There are a few helpful additions that I will mention at the end, but the main learning from this book is how to apply those 6 steps.
The importance of context
In the first formal chapter of this book, Cole directs the analyst to better understand their audience. To be able to answer the who, what & how of their communication challenge.
There are useful points about the different approaches to use for exploratory verse explanatory analysis (with the latter being the focus). She also emphasises the importance of Socratic questioning to get at the real need.
She closes this capture by sharing 3 very practical tools:
- 3-minute story: Can you summarise your message down to a paragraph that you could speak in 3 minutes?
- Big idea: Can you boil that message down to just one sentence? The most important thing for them to remember afterwards.
- Storyboarding: The idea of using mini square Post-it notes as a way of structuring your presentation (more on this later, but the low tech nature of this approach matters).
Choosing an effective visualisation
In this chapter, Cole presents the 12 different approaches she most commonly uses. It is a really helpful chapter in terms of encouraging analysts to understand when it is appropriate to use different basic charts. Well worth reading, even if you think you already understand them.
Her common options are:
- Simple text (e.g. if you really have just 1 or 2 numbers)
- Line chart
- Vertical bar (column) chart
- Horizontal bar chart
- Stacked column chart
- Stacked bar chart
- Waterfall (bridge) chart
- Square area
As well as including some interesting Data Viz history for a number of these charts, she makes some important points. She substantiates these with positive & negative examples to show how they can be misused.
There are also lots of great small details (as Andy Kirk is fond of sharing). Like for instance how to judge the appropriate width for column charts. Cole also touches on ethics & Edward Tufte’s principles. Plus, of course, a much-needed critique of why pie & doughnut charts do not work well.
Clutter is your enemy
Once you have seen any of Cole’s finished charts, you will be struck by the clean efficient minimalism of her style. In this chapter, she explains the reason for her intentional use of white space & de-cluttering what is too often left on charts just because it’s a default in the software used.
By considering the cognitive load for the reader and the Gestalt principles of visual perception, we are led through how to make it easier. That is easier for our reader/viewer to see what is most important & not get distracted. She helps Data Viz designers consider where eyes go when first seeing a chart.
The biggest benefit is something that Cole is great at giving in this book, a worked example. She takes a fairly standard looking line chart produced by Excel and shows step by step how she can improve it by de-cluttering.
Focus you audience’s attention
Up until this point, a number of the examples have looked a bit dull. You will have noticed that Cole has a preference for pale grey as a default chart colour. but that is just to start with a clearer ‘canvas‘. In this chapter, she explains how colour & other changes can help you control focus.
She explains how you see with your brain. The different roles of your eyes, iconic, short-term & long-term memory. These help explain why some features of a visualisation can be preattentive. She goes on to explain that these preattentive attributes are tools for you to use to draw attention to what matters.
In addition to the judicious use of an accent colour hue (to stand out against white & grey), other preattentive attributes to consider in text & charts are:
- Line length
- Line width
- Added marks
- Intensity (e.g. bold text)
- Spatial position
Cole usefully shows how these features can be used in not just the visual elements of your chart, but also your text.
Think like a designer
For anyone else who has been on Cole’s training course, this chapter is a bonus. It includes content that there is not sufficient time to include in that course. Here she helps the reader think like a designer, for instance about how “form follows function“.
This includes considering affordances (how can you use your means of drawing focus to make it obvious how too use your chart?) How can you create a clear visual hierarchy? She also prompts us to consider accessibility (not only for the visually impaired or colour blind), including how to simplify & provide annotations when & where needed.
She also touches of aesthetics & returns to how Gestalt principles help explain why one chart may look pleasing on the eye when another jars.
This is all supported by the next chapter, entitled ‘dissecting model visuals‘. This helps you understand, via 5 positive case studies, the design decisions involved in producing the final chart.
Lessons in storytelling (not just visuals)
Another strength in Cole’s approach is she is not just teaching data visualisation. She also understands the importance of these charts sitting within a clear & persuasive story.
In this chapter, she explores the ‘magic of story‘ & how to construct the compelling elements you need. She follows Aristotle framework in identifying the need for:
- A beginning (setting the stage)
- The middle (the dramatic tension)
- The end (the solution/call to action)
She includes a number of helpful narrative tricks for analysts to use when storyboarding a compelling story. These include effective use of repetition & decoding which order works best (e.g. horizontal or vertical logic or reverse storyboarding). Once again those post-it notes (one per slide with only the headline written on them) help you play around with options.
Further support to pull it all together
Beyond the above walkthrough of Cole’s 6 steps, there are two more useful chapters to close this book.
In chaper 8, Cole provides a detailed walk through of each of the 6 steps. This time using a different context & a grouped column chart in need of improvement. This really brings the steps to life, so the reader can judge if they would make the same decisions at each point.
The final chapter includes even more case studies. Each one addresses a potential issue that analysts may face when trying to apply the theory in this book. For example there are worked examples for using a dark background, using animation & avoiding spaghetti graphs.
How are you developing your Data Visualisation skills?
So, in summary, I highly recommend this book to any analyst seeking to develop better charts. It offers a ton of good sense & worked examples to apply in practice.
Beyond that, also actively runs the Storytelling with Data (SWD) community. This includes exercises like monthly challenges and spaces where people can share their answers or makeovers to each month’s challenge.
If you aren’t able to attend an in-person training course but are looking to devote some time to work through exercises, her next book may help. To help those who want more practical exercises to learn by doing, Cole has now published “Let’s Practice“. It is like an expanded version of this book, with even more exercises for you to, well, practice. Take a look here:
However, if you would value Data Visualisation training & can’t wait until Cole is running a workshop outside the USA, please get in touch. My data visualisation training courses also get rave reviews & frankly I enjoy them too. You can find out more about those here. But do keep reading too.