100 weeks of #MakeoverMonday.

We may be going on about it a bit… well, it is a significant milestone and one we’ve truly enjoyed reaching together with all of you, our community of contributors who create vizzes and data stories every week, no matter what data we throw at you.

This week was once again a big one. We’ve definitely noticed an increase in submissions since TC17 and it’s encouraging to see everyone embrace the opportunity to learn and try out new things. We enjoy welcoming lots of people to this project every week and growing the community.

This week’s dataset looked at what the world would be like if the entire population was reduced to 100 people.

With so many submissions and unique vizzes, I managed to collect a nice list of lessons for all of us to think about and consider when creating our next dashboards, so let’s get into it…




This week’s dataset had the scope for people to include every single category in the data or to focus on a subset.

It is always tempting to try and incorporate everything into a single viz. We see it in the business world all the time: ‘give me all the information on a single page, with 10 filters and drill-down to transaction level information, a map for geographical analysis and really rich tooltips for all the details’. Umm WHAT?

Developing a dashboard that covers all the aspects of the data can be very challenging and requires practice to ensure the layout, titles, colours and chart types form one coherent story, often moving from the high level or summary view to the detail.

What I noticed this week is that some people successfully told an overarching story, looking at all the different categories that were used to portrait our world population. Staying at the high level and summarising this information in one or two charts often worked really well.

What didn’t work so well was when people included all the categories but didn’t focus their viz and instead chose a single chart for each category, maybe even using multiple different chart types across their dashboard. If this is then combined with lots of colours, different font styles and annotations, the overall viz quickly gets confusing, cluttered and stops being engaging and informative.

You could compare this with going shopping. Imagine a clothing store where every shelf is packed to the max, items tumbling to the floor, hangers sticking out in all directions, and clothes for every season are mixed together, dresses, shorts, winter jackets, shoes. You don’t even know where to start if you’re just looking for a new outfit. There is no structure or logic to it and if you’re anything like me, you turn around and walk back out. In viz language: your audience gives up and doesn’t interact with and explore your viz.

Now take a clothing store like many of the more expensive places: lots of space to walk around, shelves along the outer walls of the shop, the centre being free to walk, maybe a couch to sit on, some plants or a couple of mannequins for display. Clothes are sorted by colour and/or style, seasonality and into male and female fashion. Accessories are displayed separately to complement an outfit and as you browse someone comes over and offers you an espresso. Now that is a place I like to hang out in! And your viz, if it is equally appealing, focused and easy to navigate, will give your audience what they’re looking for rather than scare them away.


Confusing, no space and just a bit cluttered

Lots of space, clear focus, appealing layout


It takes practice, no-one is born a master. Have a look at some of the dashboards that YOU like. Browse on Tableau Public as well as other dataviz pages for some good examples, add them to your favourites and think about the way they combine different elements to tell their data story.

Often simplification is key, as is finding a focus. After exploring the data and settling on a story, ask yourself whether it has a clear focus and a clear message. Then remove the things that distract from that. A single chart is fine, a single angle is fine. Not using ALL the data is fine, too. If you wanted to just focus on the language category this week, then just do that.

Matt’s viz is a great example for focus. He didn’t include every single category and took the angle of how we judge the situation in our world today based on our own outlook. Adding colour that support the message makes it stronger and lets it stand out.


Matt Francis



This week’s dataset had 14 categories which each had subcategories. With so many distinct dimension members, there was the potential to use A LOT of different colours on a dashboard and that was in fact one of the things Andy and I critiqued about the original viz.

Colours in data visualisation play a big role in communicating your message. They can enhance your viz significantly by drawing attention to certain aspects, to outliers or growth, loss, specific regions, etc. They can also distract when too many colours compete for the attention of your audience.

Use colour sparingly to draw your audience in and help them understand the key message. There are very few situations in which using many colours in a single viz will work well. It always depends on the question we’re addressing with our dashboards and visualisations. When we want our viewers to understand the significance of something, let’s make this ‘something’ stand out from the rest of the data.

You may want to take your audience on a journey from the complex to the simple, e.g. by using story points or a long form dashboard that goes from clutter (e.g. ‘there are so many categories to measure the unique makeup of our world’s population’) to the focus (e.g. ‘starvation is still a significant issue with almost xx million people affected’).

Or you only provide the end result and tell your story that way. There are plenty of options for you to explore, just keep in mind what you want your audience to get out of your viz at the end. Do you want them to feel empathy, be informed, take action, be curious to explore further, acknowledge your opinion, challenge your opinion? Ensure that the way you use colour in your viz helps your audience to get to that end result.

Another couple of pictures to underline this…

Lots of colour: what’s the message here? How would this help your audience understand your story?

Clear focus. It’s all about the car.

Another thing to consider when using multiple colours is to ensure the colour combinations work well together.

The colour palettes in Tableau (or your tool of choice) are usually perfectly appropriate, sometimes they may not suffice if you have more dimension members than there are unique colours in a palette though. In those cases you should naturally reconsider your colour choices.

If you use a 20-colour palette for 30 different things, some items have the same colour without having the same meaning. Not a good idea, because it is confusing and can misrepresent the data. Maybe 30 different things in 30 different colours isn’t a good idea either though: how can you show the data differently?

If you are determined to use multiple colours and want them to work in harmony, there are a few tools to check out. I’ve listed them on my website, so check them out next time you want to play with colours.

Carl’s viz uses colours that work really well together, they’re easy on the eye, not ‘screaming’ at the audience. Not every colour needs to be bright as we can see here quite clearly.


Carl Allchin





I know it’s fun to experiment with icons and pictures to create a unique design around your data story. And by all means, try things out!

This comes back to focus again: does the inclusion of icons and images enhance your viz and the focus of your story or does it distract your audience from the essentials?

I won’t stop anyone from including icons to reflect different categories. What I would suggest is to ensure the following:

  • Design the icon yourself or use icons that are labelled for reuse and credit the source. Don’t steal someone’s images.
  • Use icons sparingly so they can be impactful. 14 icons for 14 different categories? This can quickly look ‘noisy’ and weaken your story.
  • Use icons that look consistent. For example, have all icons in black and white or colour, all of them as squares or circles or with rounded corners, etc. Consistency like that will make your icons so much more appealing and will make it easier for you to incorporate them into the overall design.

When using images I’d also suggest that less is more. The ‘ownership’ question still arises and the same rules apply. Unless it is your own image, ensure the image is allowed to be reused and credit the source.

With images in dataviz, I’m no expert as I don’t have a graphic design background and this kind of artistry is beyond my skills. Having seen thousands of vizzes over the last 48 weeks and a number of them including images, I can assure you that the most important aspect for it to ‘look good’ is that the image blends into the story and data. It needs to truly become part of the overall design and not just be a ‘gimmicky add-on’. Then it will look good and draw the attention of your audience.

I’d suggest not to use an image just for the sake of it, because it will be obvious and look ‘stuck on’. Kind of like when I try and decorate a cake… :-).

Kizley’s animated viz this week is a great example of a data story that is brought to live through the icons. Sure, he could have used circles instead, but the icons add a human element and allow the audience to see themselves in his story…





One of our favourite topics is simplicity and quite frankly, I think simplicity applied to all aspects of life, far beyond dataviz, is a good thing. For dashboards and data stories it plays an important role in helping your audience to focus (see lesson 1) and better understand what you’re telling and showing them.

Something I noticed a few times this week was double encoding. What do I mean by that?

Let’s take the example of a bar chart. The length of the bars is determined by a measure, e.g. the number of people who live on certain continents. We’re encoding the ‘size’ in the data through these bars. What bar charts also allow us to do is to then compare two values to each other based on the length.

This should be sufficient to communicate your message.

What also happens though in dataviz is that we add another ‘level’ of information, for example by using colour on those bars. Where double encoding comes in is when the same measure that we used for size is then applied to colour those bars, resulting in two different pieces of information (length and colour) meaning the same thing.

In general, it is easier to keep things simple and attach meaning clearly to the elements in your viz. If length means one thing, don’t add colour for the same meaning, it’s not necessary and you can use colour instead to indicate something like change or to highlight a single dimension member across your dashboard.


Simplicity also applies to formatting.

Sticking to a single font for your dashboard will give you a clean finish and consistent design. Using size and boldness, italics, colour or capitalisation of words to add impact for titles, subtitles and text boxes, annotations and tooltips can effectively structure your message.

Coloured words in your subtitle are an easy way to replace a colour legend of a chart.

Annotations allow you to add extra information and drawing attention.

Using a consistent font across all of these elements makes your viz look more polished and professional. Especially if you’re like me and don’t have a design background. Stick to the simple approach, it often works best.




Tools like Tableau make it easy for everyone to create a dashboard. The enhanced formatting options and containers make it even easier to achieve a clean layout for our data stories.

Creating an impactful viz still requires planning. Sure, we can drag and drop sheets on a dashboard, add a title and call it a day. What’s much more effective, though, is to plan the flow of information:

  • How do we want our audience to ‘read’ through this viz?
  • What should they look at first?
  • What is most important?
  • What message do we want to convey and do we tell it right at the beginning or build up to it?
  • What elements do we want to include?
  • Where do we need text and explanations, which charts are standalone and don’t need text?
  • What interactivity do we provide? Do we guide our audience through our analysis or should they explore it on their own, drill down into detail and create their own understanding of the data?

These are just some of the questions we can ask ourselves when designing a dashboard.

Makeover Monday is a playground. If you want to create a viz, add a title and publish it, that is perfectly fine. This lesson and all the others we provide every week are optional and are intended for those who want to learn and go further and apply what they learn in a business context. So please don’t feel like you HAVE TO do this.

If you are keen, however, then give it a go and plan your next viz. Maybe even sketch it out and see how it flows. Sketch the different elements on post-it notes and move them around until you have a natural flow that could be chronological or hierarchical or emotional. It’s really up to you.

What will help your audience is when they ‘get it’. When they feel like you’ve considered their starting point (which for Makeover Monday is often no background on the topic whatsoever) and are taking them on a journey through the data.

Viewers like when authors consider usability and user-friendly design. This includes adding filters where necessary or structuring your viz through filter and highlight actions in such a way that interactivity leads to exploring and understanding. The viewer doesn’t have to guess. They follow instructions or their intuition because you’ve made it possible for them.

Next time you viz, try some of these out. You can start with a summary and create a long-form dashboard that goes further and further into the detail. Or you stick to the landscape desktop sized layout and move from top left to bottom right in a z pattern. Add filters or actions in places where they’re most logical and intuitive and ask someone to give you feedback. Encourage them to explore and don’t be afraid to change things up if they don’t work as you intended.




It’s been a few weeks since I last wrote about bubble charts and when they pop up in the wild and I’m surrounded by dataviz friends, I kid you not, there is this audible sharp inhale by people as they brace themselves for my reaction.

Yes, I feel pretty strongly about bubble charts and about them not being the most effective way to communicate information in the majority of situations.

Circles and ‘bubbles’ are very difficult for us to judge in terms of their size and relative size when compared to each other. A bar chart wins over a bubble chart any day.

Use them with caution and if you use them, don’t make them the main part of your viz. That’s what I would suggest :-).

Unless you do it like Paula who created a great bubble chart this week. The colours and design come together so well in my view, I really enjoyed this one:





Maps are a great way to capture the attention of your audience and can be really helpful in adding context and ‘orientation’ as I like to call it.

I have no issue with people including maps this week to show the continents where people live. What I’d like to encourage people to do, though, is to spend a little extra time to ensure the map is nicely designed, blends well into the rest of the dashboard and doesn’t take up too much space if it’s not the focus of your story.

Maps can be really powerful and they can equally look a bit out of place.

Use them to enhance your design and not just as an add on. Ask yourself whether the map adds value. If not, don’t be afraid to remove it. Just because geographical data is contained in the dataset doesn’t mean you have to use a map.

In the favourites below you can see two examples of when a map is used well to set the context without having to be a huge part of the dataviz itself.




After simplicity, this is probably my second most favourite topic. Or maybe it is my favourite topic. That probably depends on my mood.

Attention to detail sets you apart. Focusing on the little things makes such a difference and shows very clearly whether an author has considered ALL aspects of their data story and design.

We all sometimes forget stuff. Tooltip formatting? Oops. Happens to the best of us.

I want to give you a list of items that, when done well, can make a huge difference in making your viz really come together and honing your skills. It would be a shame to do excellent analysis and then not have this reflected in your end result because of what we call in German ‘Fluechtigkeitsfehler’ (the dictionary tells me it’s a ‘slip of the pen’ or ‘oversight’), essentially a mistake or omission that was made because we’re in a rush or didn’t give enough thought to it.



  • Background colours: When you use a background colour such as grey or black, ensure your individual sheets, text boxes and all other elements have the same background colour so the whole things looks consistent and not like you ‘stuck charts on a page’
  • Lines: Remove any unnecessary lines, e.g. gridlines, border, axis and zero lines. When you remove them and your viz becomes unclear, add the axis back in, but often you can safely remove them because labels and reference lines guide your audience
  • Alignment: Align your text elements and charts neatly. The human eye can spot when things are off, even by just a couple of pixels. Use containers for fixed elements, and use the layout options for floating charts to make sure they’re all perfectly aligned. Symmetry and consistency is so pleasing on the eye
  • Fonts: Ensure your font sizing works so that words are not cut off or left out, e.g. in tree maps or titles. When you publish your viz, look at the published version and check whether it looks like it’s supposed to. If not, tweak it and republish
  • Labels: When using labels, ensure consistency for their alignment, especially inside bar charts of different length. Best to use them at the bottom or top of a bar chart than at the centre, because the centre shifts at different length and labels can look messy. When they’re at the end, they’re either all at the same level (bottom) or all at the end of the bar (top) – consistency helps your viewer.
  • Visibility: Are elements of your charts overlapping? Is information obscured? If your audience is to understand your story, make sure they can access it. Make it easy for them to see what is most important
  • Typos and Grammar: Typos can distract from great work. Many of us, myself included, are not native English speakers. Let’s still make the effort to check our work. Most of the typos I notice are not because the person doesn’t know how to spell a word. They’re generally because letters were missed or mixed up.
    Read through your text elements to check for typos and grammar before publishing. Well crafted text can be hugely impactful.



  • Titles: This week I noticed a few confusing titles. Some were unclear, some didn’t align with the rest of the viz. Your title sets the scene for what’s to come. If you ask a question in your title, make sure you provide the/an answer through your viz or conclusions at the end.
    If you make a claim or statement, ensure it is supported by your data and/or analysis in a very clear way.
  • Tooltips: Your tooltips can be a great way to convey additional information without cluttering up your viz. Use them to your advantage and format them as well as add a message to them. You can turn them into a scorecard type tooltip or use whole sentences with dynamic fields to tell the story for each data point.
  • Annotations and Labels: Annotations let you call out information on your viz and draw attention to specific points, such as outliers or significant changes over time. Labels give your audience a reference point and allow you to remove lines as visual anchors. Use them sparingly (don’t label 100 points on a viz) and format them well for the biggest impact. Your audience will thank you for it.


Someone to learn from when it comes to ‘Attention to Detail’ is Michael Mixon who creates incredible designs and also very intentionally chooses and places each element. Explore his Tableau Public profiles for great examples to learn from. The week he published for this week’s Makeover shows you great use of titles, labels, colours and white space. They’re all very deliberate, neat, uncluttered and spot on.

Michael Mixon

This week, there should be something for everyone in these lessons. I’ve personally seen a number of great vizzes. I loved the many waffle charts and unit charts and the creative approach so many of you took to the topic.

Let’s now turn to my favourites for the week:




Athan Mavrantonis

Author: Athan Mavrantonis
Link: Tableau Public

Athan created the most impactful viz this week. When I saw it, I was blown away. Reducing the world population to 100 makes it easier for us to grasp the makeup of the planet’s people, but Athan’s viz took it back to full size and showed that ‘1 person would be starving’ translates into 74 Million people actually starving.

The black and white colour scheme, the large number, the focus on the essentials, the removal of anything that’s not necessary and the succinct wording make this an absolute standout viz.

Charlie Hutcheson

Author: Charlie Hutcheson
Link: Tableau Public

Charlie has been on a roll lately, combining short, focused data stories with simple and effective design. The minimalist approach is helpful in getting the message across and the colours are used for maximum impact.

Large titles, large numbers and plenty of white space to let the data ‘breathe’ bring this together really well.

Jamie Smyth

Author: Jamie Smyth
Link: Tableau Public

Jamie’s viz stood out for me because of the design and layout choices he made. The portrait layout with plenty of space around the viz itself makes me think of a high-end newspaper publication.

The colours work really well together and the focus makes it clean and easy to understand. Having bar charts going left and right for ‘haves’ and ‘don’t haves’ is a really effective way to structure the viz and show the different sides to each topic.