Circle Charts – when design meets data

• Circle charts are better to use for entertainment or information purpose. They are not the best choice for a business environment.
• Circle charts are attractive for receivers and can pull them into your story.
• Using multilayers demands providing a well-defined legend.

Humans always have had a special attitude to the sun. In prehistoric and ancient ages, in some cultures sun had the status of God. Without any scientific theories, they just knew that the sun is unique and has a crucial role for our planet and any living creature. Even in cultures where ancient humans did not worship the sun, the sun motif was commonly used to decorating buildings, everyday items, or apparel.

Nowadays, we still willingly use the image of the sun, especially in art and architecture. Something is appealing in this figure. Centric circle shape with rays around them somehow reminds me of the wheel of life with rays as special moments.

Maybe that is why the pie chart and all variations of pie charts are so popular and like among people. The father of the most known data visualizations is William Playfair. He invented a pie chart in 1801, and it is still commonly used to depict data.

My personal relationship with a pie chart is …. complicated. I do not use them often in a business environment. It is hard to present accurate data on a pie chart, especially with a good number of categories. When it comes to present information for making decisions it is better to go for more readable visualizations like bar charts (check my post: “PIES ARE FOR EATING NOT FOR DISPLAYING DATA”).

However, a different story is with data journalism, when the purpose is to entertain, or inform the audience. In such case, I would give green light to anybody, who would like to present any complicated data on any variation of a circle chart like a sunburst, radial chart, or spiral chart.

Those charts give you an opportunity to present complex hierarchical information on one chart, so even though there are maybe not idealistically readable, they are still concentrated within one visualization, which is an advantage for the audience. Do not forget that data journalism has a different purpose. The main goal is to pull readers into the story. Surprisingly, more complex visualizations with a huge number of details, colors and shapes can be a better agent than simple one to achieve that mission. It is because readers must spend more time decoding that visualization and retrieve information from it. Another aspect that increases the involvement of readers is chart interactivity. Of course, that case can be applied only on website media.

EXAMPLES

Below infographics are good examples of the complexity vs. the reader engagement. It is hard to understand them at glance. You need to hang your eyes for a longer time and go deeper to acknowledge these images.

The huge advantage is adding other layers or rings to the image. Thanks to that technique additional data are introduced into a chart and we can interpret or read information from different angles or levels. Looking on the same image with several layers of information helps us to find interesting patterns and observation. Would be much harder to achieve that effect when having separate charts.

Global statistics

Our Mother Earth is round at it has a connotation with a round object like a circle. Why not use it to strengthen the message. The chart is combined with several charts placed on circle x-axis: life expectancy and average hours of sunshine is a bar chart. Life satisfaction is a heatmap.

https://www.designboom.com/design/sunshine-and-happiness-infographic/

https://www.visualcapitalist.com/visualizing-all-of-earths-satellites/

Time

The time in western culture is perceived as linear from years perspective. When we present years the line chart or bar chart would be our first choice. However, when it comes to the elements of one year, we perceive them as a cycle. What I definitely admire in circle charts is the possibility to present any periodical phenomenon connected with time:

• Seasons: Summer, Autumn, Winter, Spring
• Months
• Weeks
• Hours
• Minutes

https://www.digitalartsonline.co.uk/features/graphic-design/award-winning-infographic-designer-nadieh-bremer-on-how-create-powerful-data-visualisations/

Hierarchical information

Presenting hierarchical data is challenging. However, sunburst charts can handle that. Sunburst charts consist of rings that represent a separate level of hierarchy. This visualization gives us an opportunity to present very complex information in one view.

Note that hierarchical information can be presented as qualitative or quantitative.

The below example presents types of cheese categorize by type of milk and their hardness. This information is qualitative. Another type of visualization that we could use would be a treemap. However, a treemap does not look such good as a circle chart.

https://stackoverflow.com/questions/17069436/hierarchical-multilevel-pie-chart

DOS & DONTS

• Use colours to catch the attention but remember to choose them in accordance with best practices for colour blindness disabilities. Studies show that around 10% of people population have some disabilities in colours distinguish.
• Always provide the legend. The legend should explain the meaning of colours, shape, sizes and even positions of objects on your visualization.
• Add short text on visualisation. If there are points that should be emphasis place additional text with an explanation nearby them. The well-balanced text provides context for a particular point.
• Plan the objects’ size with available space in mind and readability aspect.
• Do not use too small fonts.
• Do not use decorative fonts as they are not readable.
• Remember about the title and short description of the data visualization.
• Leave whitespace around the visualization to not clutter the page.

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How to speed up information decoding by simple data visualization tricks – the story of one chart.

How many times have you struggled to quickly understand what a chart is presenting? It is something that I often experience in media when reading articles or watch some statistics on TV. Sometimes is extremely hard for me to make sense of what I see, just because I am not the subject matter expert and those data at a glance do not seem familiar. And let face it, I am a data person. What must feel ordinary people, who do not work with data on a daily basis and are not highly data literate?

This post is inspired by data visualisations in the article that I have read recently about the employment situation in the UK. You can find the link to the paper at the bottom of the post.

We are going to focus on three easy to introduce improvements to make any chart more readable, impactful, and thoughtful:

• Additional Axis labelling
• Annotation
• Preattentive Attributes                

As an example, we will improve the below chart that presents changes over years of staff availability index.

Additional Axis Labelling

I am not familiar with the staff availability index. From the title and footer of the chart, I understand that the higher, the better. However, that information could be served on the plate. Based on my experience, I can see an easy fix for such a case that speed up the cognitive work of my brain. Most of the time, when some charts are presented, they present some changes over time or comparisons between two or more phenomena. 

In this case, adding small arrows to the Y-axis and additional words describing axis directions give much more sense to the chart and improve the audience experience. Now the chart presents not only changes over time but informs the expected direction of change.

Annotation

There is a common myth that “Data speaks for itself”. No data can speak because it does not have a tongue. The responsibility of proper understanding of the message lies on the messenger side.  Another quick win is adding more text to the chart itself. Additional description or insight help people to process information more effectively and, thanks to visual presentation, make it easier to remember. 

I have added a sentence from the article next to the point that I have wanted to emphasise. The rich text pays attention to the audience eyes, and the soft grey line directs to the specific point on the chart.

Preattentive attributes

Each object on Earth has properties like shape, colour, size, position. This is what we notice without using conscious effort, and because we do not involve too much conscious effort, we must take advantage of it to decoding information faster. Thanks to them, we can guide the audience eyes through our data visualisation and point them exactly where we want.

Introducing a small red dot is a true game-changer for presenting information on the below chart. We can get this effect by taking off the line chart colour and add to the chart another object with a different shape (circle), size (the circle is significantly thicker than the line), and by adding contrasting colour (the red one). At the final stage, let us analyse our eyes movement. First of all, our eyes start looking at the chart with the title (that is why do not forget about titles! Never!). Then they go straight to the red dot. Just next to the red dot is an insight that explains that point.  Next, they track the line chart and finally look at additional Y-axis labelling. Now, our brain, after collecting all this information, can process them and make sense of those data.

I would recommend those three easy to remember and use tricks to uplift any data visualisation that will improve your audience experience.

The link to the article:

https://www.theguardian.com/business/2021/jul/08/uk-employers-struggle-with-worst-labour-shortage-since-1997?CMP=Share_AndroidApp_Other

Storytelling structures that support presenting data.

Key points:

1. How to structure your presentation to keep the audience attention?
2. What to avoid to not overwhelm people?

Many professionals struggle with conveying their messages in an effective way. They often fail to convince others with their ideas or perspective. Most of the time the reason why it happens is poor delivery of the presentation. It is a hard job to present a topic in a logical way that does not confuse the audience. The second challenge is to create an engaging and exciting experience for the audience. Things even get more complicated when you use numbers and figures in your presentations.

Why do you need storytelling to present data?

The simple answer is because numbers are too abstract for the human’s brain. Presenting or talking about numbers is not such a piece of cake. Thousand years ago, nobody had to analyse sales trends or try to understand what influences shipments delivery.  Data analysis and data visualization is relatively a new demand, and a lot of people struggle to gain this new skill.

If you do not weave your facts and charts into a story framework, you overwhelm your audience and lose their attention, and in the end, you fail with your ideas.

Since the beginning of humanity, people are storytellers. For ages, they have been passing on the information by narration about incredible actions of heroes, distanced journeys, and the most important, gained wisdom and knowledge through those stories. For humans, the narration is the most appealing and easy way to consume and remember information. The message “Do not eat berries” sounds flat compared to “Do not eat berries because half of the neighbourhood tribe died after ate them.”  And what are the most important, stories ignite emotions which drive people to take decisions and actions more often than logical facts and data (if you doubt this, check the latest studies of behavioral economists)

The Basics

I bet that 100% of corporate presentations have the purpose of influencing people to take action or decisions. Most of the time we:

1. solve some problems, and we need allies and sponsors to support our ideas,
2. break a status quo and introduce a change in the organisation’s business model to be ready for future challenges, and we must convince and inspire others,
3. pass information needed to make strategic decisions

So, first, you must decide the purpose of the presentation. However, sometimes I have an impression that some speakers present data analysis for themselves. They just want to boost what they found, but they lack the audience perspective.  There is the truth worth remembering: people are interested only in themselves.

“You can make more friends in two months by becoming interested in other people than you can in two years by trying to get other people interested in you.”

Dale Carnegie

When you prepare your presentation, focus on benefits for the audience. The simply Five Ws + How technique can support you in this task.

1. Who – think about people to whom you are going to present.
2. Why – think what kind of questions they can have or ask them directly, and try to give them answers or feed them with insights that help to find them, on the other hand, do not forget about what you want to achieve.
3. What – now when you know their perspective, you can start analysing data, and create a storyline.
4. How – this is a time to start thinking about the structure of the presentation and the result which you want to achieve.
5. When – at which time you will deliver a presentation is important as well, check out a corporate schedule, if the important event is coming shortly, it would be better to hurry up.
6. Where – make sure that place is convenient for your audience, there is enough room for everyone, and the place has required equipment.

Let us move further to HOW to design a presentation as a true storyteller.

Storytelling structures

Every good story has three points to cover. Every book, drama or movie follow that simple structure. Nevertheless, how and when you cover will change a narration.

• Conflict – it is a background for the story: a current situation or state, past actions and discomfort it makes.
• Climax – it is an essence of the story, critical point, the whole story is told to convey this one message.
• Resolution – a new desired state or actions need to be taken.

Let us check how we can juggle these points to get different narrations.

Storytelling techniques good for presenting data.

When you present something to the audience, you want to make them listen to you. Several techniques help you achieve this experience.

The Narrative ARC

One of the most common structures is the arc. It is a very logical structure with straightforward, easy to follow stages for the presenter and the audience. It is the extension of the conflict, climax and resolution. It follows:

1. Exposition – this is a background, a current state, a time snapshot, circumstances. All of these establish the context of your story. It is an excellent place to reveal all possible questions which your audience can have.
2. Rising action – in this point, a conflict is presented. It can be an unsatisfied situation or result. At this stage, to add some tensions, describe some risks and threats to the audience if the status quo remains, and future possibilities which you will cover further.
3. Climax – the critical or turning point, the undoubted evidence that some decision must be made. It can be your main findings.
4. Falling action – at this stage, different conflict solutions can be presented with pros and cons.
5. Resolution – final recommendation, needed decisions, actions or solutions.

In media res

This structure immediately moves the audience to the essence of your message. This strategy has on purpose to catch the audience attention and engagement. The structure follows:

1. Climax – the critical or turning point, the undoubted evidence that some decision must be made. It can be your main findings. At this stage, to add some tensions, describe some risks and threats to the audience if the status quo remains, and future possibilities which you will cover further.
2. Conflict – this is a background, a current state, a time snapshot, circumstances. All of these establish the context of your story. Reveal at this stage all possible questions which your audience can have.
3. Resolution – final recommendation, needed decisions, actions or solutions.

This structure can be highly effective when presenting to senior managers or executives who are always in a hurry and like to go straight to the point, and you need some decisions or actions from their side.

Dos and Don’ts

Last but not least. You can tell the best story, but numbers need to be shown. What is more, people are visual creatures. For most of us, to understand means to see. Designing the presentation, consider the below tips to avoid overwhelming the audience.

• Too many charts on one slide – it is better to unfold visuals to more slides instead of clutter one slide with too many elements. A thoughtfully adjusted number of slides will support your story and lead the audience step by step.
• Too much text – the same situation is with text. Good presentation is economical in text. Just a few of the most important words, insights or phrases. So do not expose your audience to the wall of the text.
• Too small fonts – this one relates to the previous. If you do not have the wall of text on your slide, there is room for readable size fonts. To adjust fonts size, consider the conference room size. The fonts for the axis should be at least 12.
• Too small visuals – similar with fonts size. When using visuals, make sure that these are big enough to be visible to the audience
• Unreadable fonts – some font types are hard to read. They look exciting, but in the end, they are slowing down the decoding information process. Stick to simply fonts like Calibri, Arial, Verdana.
• Keep a short harmonic colour palette – colours evoke emotions (but this is a topic for another post). Build a colour palette around five to seven colours and stick to it in your presentation. Decide which colour would be the main one and cover 60% of the presentation deck. The following 30% leave for secondary colour, and the rest 10% for colour, which will be used for highlighting the most critical information.
• Keep agenda visible – save a place on the slide for displaying agenda. It can be at the bottom of the slide, on the side or on the top. The audience is provided with information in which part of the presentation they are right now.
• Do not add page number – if you are going to display 50 slides, it is better to keep it secret 😊
• Use grid – the human eye does not like asymmetry. The grid can help you align all objects with themselves and keep a clean and orderly layout of slides.

Four Levels of Data Storytelling – Where Do You Perform?

In this post, you will find out the four crucial skills to become a data storytelling master and why you should improve them.

Firstly, I have good news for you. Everyone can be a data storyteller and possess the required skills on a “good enough” level. Of course, each of us starts from a different position, and the time necessary to reach a “good enough” level will differ. There is scientific proof that you need about 10 000 hrs to be professional in any picked field, but only 20 hrs to have a basic knowledge of a subject. There are four fundamental skills that made you a data storyteller.:

1. Analytical skills
2. Data visualization skills
3. Communication skills
4. Subject comprehension

Analytical skills

This skill is a basic of basics. Without understanding numbers and reading them, you cannot adequately prepare a story about them. Even when you are not a “data person” – someone who already has had the skill to transform and interpret massive data sets, you still can learn it.

Our brain is divided into two halves – left and right. The left half is responsible for analytical, logical and sequential thinking. In this part of the brain, the centre of language is located. The right half gives us the ability to perceive in a non-verbal way: see objects in space, compare similarities, have intuition, have a holistic view of something. Most people experience domination of one of the halves. However, it does not determine that you are an artist or an accountant. If all humans have both halves, all of us can analyse and interpret data. Naturally, some of us are more gifted than others, but I would be far away from the opinion that you cannot learn analytics unless you suffer from solid dyscalculia.

But where to start your journey with data analytics if you do not have previous experience?

Foremost, understanding descriptive statistics is a game-changer. Descriptive statistics are methods for organizing and summarizing information. Having those statistics in place, we can start asking the right questions that help us reveal some insights. Mostly, we do analytics to see some trends, picks and falls, a contribution of factors or distribution of one of the characteristics within the population.

Data Visualization skills

Ok. We gathered all required data, organized and summarized them using descriptive statistics. But how make them readable for others?

In lots of companies still, a primary tool for performance reporting is MS Excel. And still, in those companies, the primary manner to present numbers is an excel table. There is nothing wrong with using tables, and sometimes they are even the best way to communicate results. However, we have much more tools to select to communicate numbers effectively. There is quite an impressive range of available data visualizations in any common software like Excel, Power BI or Tableau, just to name a few. Visualizing numbers is a skill like any other. You can learn it and master it.

Nowadays, this skill is more important than ever when we are submerged in the data ocean. Data visualizations are often the only way to make sense of data, find patterns and understand the surrounding world. Data visualization utilize human perception to communicate and receive data. If we do it without proper diligence and mindfulness, we can mislead our recipients, and as consequences, they will draw wrong conclusions. The worst-case scenario would be misleading the audience on purpose. Regardless of designer intentions, it is an ignorance of using and presenting data in an unethical way. There is plenty of sources that provide rules and best practices on how to use data visualizations correctly. So do not miss this opportunity and earn credibility.

Communication skills

So, two first steps in a process have been already done. You found interesting patterns and insights in the data and prepared their visual representation to make it visible to others. However, how to convey the message?

As a species, we are designed to communicate complex ideas and theories because we have speech apparatus, unlike any other animal. And vocal communication is a basic one for us. Thanks to our ability to pass complex ideas and theories, we have built an advanced civilization. But even when we speak the same language, we often cannot efficiently articulate our thoughts, and the receiver can misinterpret our message.

From a data storytelling perspective, there are two crucial components of communication. The first one is to use language adjusted to the audience. It is easy to overwhelm the audience with technical jargon, lose their attention and, in the end, lose their interest in the subject. The second one is the ability to make simple explanations. There is good exercise, at least when you have kids. When you explain your thoughts in a way that a seven-year-old kid can understand, you are the master of communication. To achieve it, try to use as many as possible comparisons, examples and metaphors from your audience experiences.

Subject comprehension

On top of the three essential skills, there is one more. I have already emphasized several times how crucial subject knowledge is. As Steven Covey said, “firstly understand to be understood”. You will not be a convincing storyteller without knowledge of what answers your audience is looking for. There is a simple rule: people always are interested in their business and problems, not yours. So, when you want to persuade them, you must present benefits or threats for them. From my experience data analysts are overloaded with ETL jobs and do not have enough room to talk with business people about business pain points and challenges. Those conversations would significantly enhance provided information. Data without context and understanding what is behind the scenes are useless.

Apart from mastering analytical, data visualisation, and communication skills, try to become a true partner for the business that you support. Build strong relationships with your internal or external customers and listen to them actively. Most people are willing to talk if you are pleased to listen. There is no better source of knowledge than subject matter experts. With those competencies, your ability to have a real impact within the organisation and building your personal brand will grow.

From Beginner to Master of Storytelling

In each discipline, there are levels of mastery. There is no difference with data storytelling. Check out where are you right now and what your aspirations are.

Beginner

This is entry-level. You even do not know that there is something like data storytelling and you can learn it to enhance your data analysis. I often meet beginners as young people who have just started their career. Their heads are plenty of theory, but they lack practice. In the first place, Beginners should improve business knowledge to prepare better and relevant data analysis. In most organizations, there is plenty of internal training and materials that bring closer inner business processes, rules and characteristics.

Recruit

I would say that those are mostly data analysts with excellent analytical skills and data visualization skills who do beautiful data visualizations that often are totally useless. The pitfall here is that when you are experienced in one very narrow specialization, you can have the delusion that you know better than others what they need and how to present it. However, they produce products for their customers and should listen to their voice. Maybe your customer does not know how to analyse data but for sure know what questions are interesting and show you in which direction data analyses should go. Recruits are typical data people, and they put too much focus on technical aspects, and they too often use very technical language when they communicate with non-technical people. They should focus more on the business side of analysis and less on the analysis itself.

Leader

As you can see on the matrix above, I valuate communication skills and business acumen more than data visualization skills in data storytelling. People who already know what the pain points of business are and can draw the audience attention do not need to know advanced data visualisation techniques to impact. However, there is a potential risk to easily mislead the audience if someone uses data without proper knowledge about basic best practices of data visualization. As I have mentioned earlier, data visualization techniques are based on human perception, which is a very fragile cognitive apparatus. Leaders have a special mission in spreading data culture across organizations because they feel comfortable with data, know how to use and present them, and, thanks to their position, can make or influence data-driven decisions.

Master

Masters have proficiency in all four skills. What is more, thanks to the linkage of business knowledge and analytical skills they are true advisors, who can set directions of future growth.