Comparing survey responses over two time points. Same data, displayed 6 different ways

February 18, 2021

I’ve been working with a few local councils over the last year. One thing that regularly pops up is the need to display and compare data over two time points. I scoured the web to find a good example and came across one local council’s website showing a comparison of their performance from 2019 to 2020. This repeated cross sectional data looks at seven main measures and are displayed using percentages in a standard table. I’ve changed the results slightly for anonymity purposes, but it looks a little something like this.

Summary of council’s performance. Displayed as a table

How many different ways could we effectively display this data? I’ve come up with six variations, all with positives and negatives. Let’s have a look through.

Display 1 – Clustered bar chart

This is by far the most frequent display that comes across my desk. It normally looks a little something like the one below.

While a clustered bar chart can be a valid option to use, we need to steer away from the standard Excel template and make some big improvements.

Let’s make some changes!

Some of the category names are quite long and therefore Excel has angled the writing on the X axis. Swap it to a horizontal bar so none of the writing will be squished or angled and it’s much easier for your audience to read through.
What is the focus? In this chart 2020 is our main focus with 2019 there for comparison. Therefore, use an action or focus colour for 2020 (in my case blue) and grey for the comparison (2019).
Add data labels directly to the chart, that way your audience doesn’t have to dart back and forth to work out the values.
Remove all the clutter like the gridlines and border.

With the improvements your chart should look something like this. As I’ve said before, people know how to read bar charts so you don’t run the risk of your audience not understanding it. However, it is very busy and may require a bit more visual processing time, so we risk the audience skipping over it all together.

Display 2 – Back-to-back bar chart

This back to back bar chart is a little easier to navigate through. We have a horizontal bar for 2019 and a mirrored horizontal bar for 2020. They share the same spine.

Again, we are focused on the 2020 results, so I have coloured them in our action colour blue and ordered them biggest to smallest. We can easily assess each category individually and then by its equivalent year.

This chart works for all necessary purposes. Without the data labels directly embedded it could be a lot harder to decode by comparing lengths.

Display 3 - Dumbbell dot plot

Here we have our categories on the Y axis, percentage values across the X axis and data series displaying 2019 (grey) and 2020 (blue). The points are connected by a thin grey line.

The benefit of this chart over the clustered bar and back to back bar is that we can focus a lot more on the change between the two time points. Why is that? Because unlike a bar chart which needs to start at 0 to accurately decode the chart, a dot plot can start at the lowest value (or thereabouts). In my case the X axis starts at 40%.

There is a lot more white space on this chart which makes it easier to take in and we are drawn to the length of the grey line in between the two circles. In the case of “Lobbying”, the values have stayed the same over the two years. I’ve represented this with a grey circle and a blue border. If your values are too close together, this chart may not be the most suitable.

Display 4– Table with sparklines

Sometimes the best solution for displaying your data may be keeping it in a table. It could be that you have a large number of categories or that you were required to add a table of results in the appendix of your report. Whatever the reason, add an extra column in your table and insert sparklines so your audience can easily see the trend or pattern in the data. Excel has a sparkline feature which is simple and intuitive to use. Go one step further and colour code your high and low points. In the case above, I have used orange for the low point and blue for the high point.

It should be noted that the Y axis of the sparkline is measured by the highest and lowest point of the data in that particular row. Therefore, it may not be accurate to compare between sparklines. If you want a consistent axis throughout, you can change this under the sparklines tab by clicking Axis > Vertical > and select Same for all sparklines under Minimum value and Maximum value.

Display 5 – Small multiple bar charts

Now we are getting down to the business end. If you have a busy chart with a lot happening, consider small multiples. They are an efficient way to break down a cluttered chart that allows your audience to walk through one category at a time and make comparisons.

In this case, we have seven smaller bar charts each representing one measure. They are all designed to the same scale so we can compare not only within each chart, but across the categories as well. I have colour coded 2019 in grey as it’s there for comparison, and 2020 in either blue, if it did better than the previous year, or orange if it did not.

On quick glance we are able to see there are three blue bars and three orange. We are easily able to navigate through each category or measure and see how it’s performed against the previous year. The advantage of small multiples is that you can split them up and use the individual charts throughout a report or PowerPoint presentation as well.

Display 6 – Small multiple slope charts

In sticking with the small multiple theme, a slope chart is an excellent way to display and compare data over two time points. We are decoding the slope chart by not only looking at the position of the dots but also the angle of the line that joins to the dots. By colour coding blue for positive performance and orange for negative, I’m further aiding readability and digestibility.

Like the previous small multiple bar chart, we can split this chart up and use it in different sections of our report or PowerPoint too.

In summary, I have presented you with six different options for displaying your data over two time points. There is no right or wrong answer, rather options for you to consider and get inspiration from.

Remember:

Consider who your audience is and the best way to reach them.
Draw focus where it is needed. Push everything else to the back for comparison.
Aid in digestibility by adding that storytelling element to your chart.

A lot to consider, but some options above to help your thinking. Happy designing!

Thank you to my friend and colleague Dr Elena Swift for her advice and assistance in writing this blog.

Designing your charts for PowerPoint Presentations

December 21, 2020

Take a look at this chart below. Let’s picture it in two different scenarios.

Scenario one

It’s Monday morning. You grab your cup of coffee, sit down at your computer and start going through your emails. Your colleague has sent you an interim report on findings from their current research project. You scroll through, read the report and take time to understand and interpret the chart. “Excellent work”, you say. You go about your business.

Scenario two

Your same colleague has been invited to present the findings from the interim report. Being 2020, let’s say this is on Zoom. They have 15 minutes to get through about 20 slides, which leaves about 45 seconds per slide. One of the slides is the same chart. The chart appears. They keep talking, and you start trying to read, interpret and make comparisons between the categories. However, your concentration is broken because the presenter is still talking and what they are talking about is not where you are on the chart. Next minute, the slide changes. “I’m confused”, you say.

My point is when designing charts for your PowerPoint presentations, there are different considerations to designing for reports or infographics. With reports and infographics, you have a lot more time to read and digest the information. For presentations, we need to reduce the cognitive load and simplify the chart as best we can to illustrate the point.

So, what can we do?

The chart above was one that came from one of my awesome clients. The horizontal grouped bar is great and does everything a bar chart needs to. She has added data labels and removed all the background noise like the gridlines. But it still takes a bit of work to go back and forth from the key down the bottom and match up with the categories and how they perform against each other. Time is not usually a luxury we have in PowerPoint presentations.

AFTER: Small multiple horizontal bar chart

This is my redesign as small multiple horizontal bars.

What have I done?

I’ve made two horizontal bars sitting next to each other with the exact same dimensions (scale, height and width). The bars are bit thicker too. I’ve kept with my client’s chosen colours for male and female (and not conformed to the old pink and blue stereotypes) and added an icon next to the heading to aid in comprehension. The first category (female), I have listed from biggest to smallest. It makes the chart easier to read. I’ve then matched the categories for the male column for easier comparisons. Like the original, I have the data labels in there but have made them that little bit bigger. There is a big difference in the number of female and male participants, so I have kept those numbers in but subtly at the top.

A few easy changes and the chart is a whole lot easier to digest.

Let’s look at another slide before and after.

I can hear you asking, “Why have you been boring and done it in the exact same way”? Good question!

Remember: time is not our friend in a PowerPoint presentation. Even if the slide was up on screen for a while, we still want our audience to process the information as quickly as possible and then focus their attention back to us as the presenter. So, keeping the same type of chart and the same layout allows our audience a quicker processing time as they are already familiar with the chart and how to read it.

Other key things to remember when designing charts for PowerPoint presentations:

Remove unnecessary clutter from your charts, like gridlines, background colour, and borders.
Always label data directly to reduce any ambiguity. It’s harder for our eyes to scroll from the end of the bar to the X or Y axis to see the exact value.
Use the graphic design principle of hierarchy to order your chart. In Western culture we read from top left to bottom right, so lead your audience through with a large title on the top left.
Add icons where you can to aid in readability. Remember PowerPoint now has its own icons.
Use the real estate on your slide! Use the space you have been given. Don’t cram it into one corner.
Use data storytelling to focus your audience’s attention on a certain part of your chart and tell the story behind it.

Happy designing!

Let’s talk small multiples

September 29, 2020

Check out this line chart below. As the title suggests it’s looking at AFL club membership from 2016 to 2020. It’s extremely busy with 18 different lines and colours that are awfully similar. It’s hard to gain any insight from the chart (besides that fact that it’s quite busy), let alone focus on any single data series. What if I asked you to tell me how club membership was affected by COVID-19 from 2019 to 2020? Which clubs did well? Which ones lost members? What was the overall trend? It’s virtually impossible which makes the chart pretty useless.

Luckily, we can redo this chart using small multiples instead.

What are small multiples?

The term was popularised by Edward Tufte and as he describes “resemble the frames of a movie: a series of graphics, showing the same combination of variables, indexed by changes in another variable.” They are also referred to as trellis, lattice, grid or panel charts. They are an efficient way to break down a busy chart that allows your audience to walk through one category at a time and make comparisons.

So let’s redo this chart using small multiple line charts.

What have I done?

I’ve created an individual chart for each team showing membership numbers over the last five years. Each chart is to the same scale, which is incredibly important so we don’t mislead our audience. I have decided to colour code the chart with orange used for membership decline over the previous season and blue to indicate membership growth. I have then finished this off with a descriptive title and subtitle at the top which turns my chart from an exploratory chart to an explanatory one (i.e. I’m telling you what my take away message is). Lastly, I have listed my source down the bottom. Has this redesign made it easier for you to understand and interpret the data?

Let’s try another design using small multiples area charts. This time I will incorporate data storytelling.

I’ve pushed everything to the background using grey. I’ve then decided I’ll focus on membership decline once again and highlight that using a bold red colour (a little alarmist, but intentional given the circumstances). I’ve used a complete sentence to highlight my story and colour code it to the chart. Lastly, of course, my source at the bottom.

Depending on where I am using the chart (a report or PowerPoint presentation), I may want to give context that Melbourne was hardest hit by a second wave of coronavirus and teams were moved to hubs predominately in Queensland. Additionally, no Melburnians were able to attend live games within Victoria in 2020.

How have I done these small multiples?

Great news, it’s all in Excel! Highlight and create your first chart with only the one category.

Once you have formatted it the way you want it, right click and save as template. Then copy and paste your chart however many times you need to. In my case, it was 17 more times. Lastly right click on each chart and choose “select data” to populate the new data.

Small multiples can be used for just about any type of chart. My blog on displaying Likert scale data uses a few more examples.

If you need some further inspiration that’s not football related… (I had to, it’s September!), check out these links.

Financial Times: Coronavirus tracker

McKinsey & Company: Tracking US unemployment through the COVID-19 crisis

Happy designing!

Transforming your charts using data storytelling

August 30, 2020

Our team has been working in partnership with the Doherty Institute on a longitudinal, nation-wide survey. The aim is to gain an understanding how Australians are thinking, feeling and behaving in relation to the COVID-19 pandemic and the distancing measures in place. A series of rapid reports are being produced to help decision makers in real time and you can read the full reports here. I was lucky enough to work on the design and layout of the second report.

There were a number of charts produced through the analysis by the very talented data analysts on the team. One such chart is below. Can we take a moment to recognise the great colours used! The rapid turnaround of this report limited the time available for design, but now that I have had some breathing space I thought I would show you some alternative ways the information in this chart could be displayed.

There is a lot happening in the chart and a lot to take in. We can see from the outset that the large chunks of green indicate that a lot of people have changed their behaviour in relation to the pandemic. The green and the purple have a common baseline which makes it easier for us to compare lengths, but the blue category caught in the middle is a little more difficult.

When I was formatting the report, I thought this would be an excellent example of how we can transform the chart to incorporate data storytelling.

What is data storytelling?

Data storytelling isn’t about counting how many breaths the big bad wolf took to blow down the three little pigs house and charting that. Or using statistical analysis to find where exactly the green sheep is, and where it might go next.

Data storytelling is finding a story behind your data and chart, and explaining that to your audience. It’s about turning your chart from an exploratory one, where you let the audience find their own meaning, to an explanatory one where, you tell them what’s important and what you would like them to take away from the chart. Ann K Emery and Cole Nussbaumer Knaflic are the real leaders in this space.

I redesigned this chart twice , then transformed each from a traditional chart into a data storytelling chart. The good news, it was 100% done in Excel!

Chart 1 – 100% stacked bar chart.

Sticking with the original concept, I used a 100% stacked bar to show behaviour change. I made one small modification which totally transforms the chart, that is ordering the first category (yes) from largest to smallest.

100% stacked bar showing behaviour change

I’ve included percentages for the yes category to give some reference. The chart appears a little more ordered now. But it’s still an exploratory chart. I leave the audience to look through and find what’s important.

Let’s take it one step further now and make it into a storytelling chart.

Using data storytelling to show our audience what is important

What did I do?

I greyed everything out.
I decided on the story I’m going to tell. In this case, my story was the majority of people did change their behaviours to some degree and thus helped protect themselves and others from the virus.
I drew attention to this by using my action colour teal to highlight the ‘yes’ category.
I wrote a full sentence heading that describes that point.
I added an extra element by placing annotations next to three bars in the chart that I thought were interesting.

The storytelling part of your chart also depends on the audience you are presenting it to. Using knowledge translation, we can identify our target audience and what aspects of the chart may be of most interest or useful to them. For instance, say I was applying for a research grant to explore whether the rate of serious illness diagnoses have decreased because fewer people have presenting to hospital for check-ups during the pandemic. I could use the above chart to show that and redesign it like this:

Storytelling chart highlighting a different point.

Again, I’ve pushed everything to the back and highlighted my story using colour, a completed descriptive heading and an annotation.

Chart 2 – Small multiple bar chart.

The second redesign uses small multiple bar charts. To help the reader, I have categorised the behaviours into four different groups; travel, safety, work and study, and social. Each group has their own colour. This breaks up the chart into smaller, more digestible chunks and makes it easier for our audience to walk their way through.

As I’ve mentioned before, people have a much easier time comparing lengths when reading charts, especially when they have a common baseline, hence my decision to go with small multiple bars.

Here is our traditional chart:

The chart is great but again, I have left it to the audience to find meaning. So, let’s tell them exactly what’s important:

Small multiple bar chart incorporating data storytelling

What did I do?

I greyed everything out.
I decided on the story I’m going to tell. Again, I wanted to focus on the behaviour change (‘yes’ category), especially the two highest categories; ‘applying social distancing rules’ and ‘avoiding crowded areas’.
I drew attention to this by leaving the yes category in colour but reducing the opacity to 50%. I left ‘applying social distancing rules’ and ‘avoiding crowded areas’ at 100% opacity, making them a bit brighter to the reader’s eye.
I wrote a full sentence heading that describes that point and used colour to link it to the chart.
This time I decided against an annotation as the chart was already quite busy.

Easy done! Your audience can’t miss the meaning now.

Using these 4-5 steps, you can transform your traditional chart into a storytelling chart making it super easy for your audience to read and interpret.

Happy designing!

Don't put your audience to sleep with your PowerPoint presentations

February 16, 2020

Many moons ago, when I first started working at the University, a fellow colleague was giving a presentation on her research. We were in a medium sized seminar room with the lights slightly dim. The room was half full of academics from all different disciplines, eager to hear about her study. She was engaging and well prepared. Then out of nowhere, we heard this noise. The room stopped and turned. The presenter, professional as ever, kept going, but was visibly distracted. What had happened? Another colleague had fallen asleep and started snoring! Yes, a lunch time session, with the lights slightly dim, had put this poor man to sleep.

We’ve all been to those seminars where the presenter starts talking and the slides are full of dot points. Do you read the dot points, or listen to the presentation? You decide to read, tuning out the speaker and then they change the slide! The next slide appears and besides it’s six multi-level dot points and two different fonts, your attention is competing with the unnecessary clip art, the four different organisational logos and a heading that’s two sentences long with a distorted photo in the background. What is going on?! Time to check emails or even see what’s happening on your social’s news feed.

I have a love-hate relationship with PowerPoint. On the one hand, it’s a great tool to use for your presentations, but the majority of people are using it incorrectly.

What’s my issue with PowerPoint? The minute you open the program, it guides us into bad habits. The first slide prompts you to “click to add title”, and then “click to add subtitle”. The next slide “click to add title”, “click to add text”. But what format are you adding the text in? The evil dot points (or bullets)!

Please don’t get me started on the horrible templates they supply either.

The majority of people put the information in and never go back to reformat it, so pages and pages of dot points remain (probably copied and pasted from another document).

Here is my first take away point:

Your presentation is not a 50/50 split between you as the presenter and your PowerPoint presentation. You are the presentation and PowerPoint is your visual aid. Your slides shouldn’t make a lot of sense without you there talking to them. If they do, you probably have too much information on them.

For the majority of us, presentations are challenging. You have a set amount of time to not only condense your topic but also present it in a way that’s engaging and easy to understand. So naturally we start going through and planning what we are going to talk about on each slide, succumbing to the evil dot point format.

That’s fine and a good way to start planning, but it’s only half the job. Don’t stop there.

Second take away point:

Once you have planned what you are going to speak about on each slide, move ALL this information into the notes section below. Now you can start to design your slides.

When you start designing, make sure you start with a blank slide. This way you won’t succumb to PowerPoint’s nasty dot point trap.

Add an image, a few words or icons that illustrate the point you are talking about. Don’t be scared to stretch what you originally had on one slide over three or four. Each slide should cover one main message.

Use images. People connect to images, especially images of other people’s faces.

Why is this so important?

In his brilliant book Brain Rules, John Medina tells us that if you show someone a chunk of text, they are likely to recall 10% of that information three days later. If you combine that text with a relevant image, they are likely to recall 65% of that information three days later.

Third take away point:

Move away from dot points.

My challenge to you: create a presentation that has no dot points in it at all. It is possible! My one-day short course has over 500 slides with only one slide with dot points – and that’s an example of a ‘before’ slide. Dot points are the biggest mistake people make.

My last take away point:

Make a great first impression on your first slide.

At a conference or presentation, your first slide is likely to be on display for a while. It will be on screen while people walk into the room and wait for you to start. Make them excited about your presentation the minute they see that slide. Don’t clutter it with unnecessary information or clip art.

There are the ONLY five elements I believe should be on your first slide.

Title – a short, sharp title is better than 2 whole sentences.
Image/photo – use a high quality stock image. There are many sites like pixabay where you can get these royalty free.
Name of the presenter ONLY. You can name all your collaborators on the next slide. People want to know who is presenting in this instance.
Your institution
Your institution’s logo. This should be on your first and last slide only. If you are engaging enough, people will remember where you are from. You don’t need to remind them on every slide.

Here are some examples.

I could write a book on designing PowerPoint presentations. There is so much more you can do than jotting some dot points on a page.

Design something that’s exciting. Design something that’s engaging. Design something that wouldn’t make much sense without you there to talk to it. Don’t be scared of white space. As the famous saying goes, “less is more”.

Take your time designing. People often don’t realise how time consuming putting together a well-designed PowerPoint actually is.

And remember not to use dot points!

Scrap the bar chart to show changes over time

November 20, 2019

I often see bar charts used to display changes over time, or “before and after” comparisons. While this is a perfectly fine chart to use, there are much more effective and creative ways to display changes between two time points. One of my favourite ways is to use small multiple slope charts.

The following vertical bar came across my desk a while back. It looks at pre and post course evaluations. It was clearly done in Excel as we can see from the lovely (hideous) colour palette it spat out. On first glance, we can see the overall differences between the red and blue categories (pre and post) but actual values are a little more difficult to determine, as there are no guiding grid lines. Our eyes also dart back and forth from the bars to the key to match the categories.

Excel bar chart showing before, after and difference bars.

The interesting part about this chart too, is that there has been a third category added which is looking at the difference between pre and post (the first two bars). The inclusion of this third bar is adding unnecessary ‘noise’ to the chart which then takes longer for the reader to process the information. It’s also a green bar, placed next to a red bar, which would make both categories look brown to someone with colour blindness.

So how can we redo this chart? I would suggest small multiple slope charts. Here is what I came up with.

So what’s a slope chart (or slope graph)? It’s a chart that shows development over two time points. We encode the data by looking at the position of the two points and the angle of the line that joins them.

Slope graphs can have multiple categories on the one chart, like the AFL and rugby ladder examples I constantly bombard you with (see below). This example is looking at ranking over two time points.

I know what you are thinking… why have I done 5 individual charts for this course evaluation when I could just add them all on the one? Well there are a few reasons.

Firstly, to make the charts easier to read, understand and digest, I would suggest adding the values directly next to each point. In some instances, you may be able to embed the category into the chart too, next to the value (Check out this NPR example on How Each State Generates Electric Power).

In our case, each of the categories/ questions are quite long. This would make them hard to squish at the side of the post data point. Also, there are four post categories that have a value of 100%. It would make it nearly impossible adding four long questions next to the one data point, not to mention, very messy.

Having them as five small multiples, makes it easier for your audience to walk through and understand each question individually.

What else have I done to make this chart simple and elegant? I’ve used the one colour for each of the five charts to maintain a level of consistency and matched it with a grey grid. As mentioned above, I’ve added the values next to each data point, and no other numbers have been included. It’s to scale, so I don’t mislead my audience and I have a descriptive heading that introduces the data below.

Below is another example I produced for a client recently, comparing two different categories (liberal fluid strategy vs restricted fluid strategy) at two times points (pre and post surgery).

I have created both of these in InDesign, however I can confidently say you could produce a slope chart in nearly any program. In PowerPoint, draw two 10cm lines and scale your data that way (e.g 65% would be 6.5cm up the 10cm line). Here is an excel tutorial from Peltier Tech Blog.

Slope charts are an easy, simple and elegant way of displaying changes over two time points. Scrap the old-fashioned bar chart and move to something much more contemporary and effective.

Are word clouds dead? The answer is yes, but no.

August 18, 2019

Word clouds were big 9 or 10 years ago, thanks in big part to the online application Wordle.

It only takes a quick google search of ‘word cloud’ to see how popular they were and how we absolutely used them to death. I too, am guilty of it. I’m pretty sure I created one for our annual report back in 2010 (we won’t speak of this again). Now when I see a word cloud used as a visualisation, a cold shiver goes down my spine.

However, there are some exceptions. I will get to this in a moment.

What is a word cloud?

In case you don’t know (or have been cast away on a desert island for the last 10 years… welcome back), word clouds are an image composed of source text that you input into a program or online application (like Wordle). It then creates an image of the text, scaling the words by how frequently they are used. You can then change the font, colour palette and layout.

They were cool, but very overused. People would dump paragraphs of text into these programs without a second thought. They can be hard to pull any meaning from and we only really pay attention to the few big words. Phrases would lose all meaning unless you grouped the words together.

I do however think there is some value left with word clouds. Hear me out…

What are they good for?

They are a good tool for qualitative analysis when you are making comparisons. Before and after, 2018 vs 2019 etc.

We used it to do a qualitative analysis of the Survive and Thrive program, which was an environmental education program delivered by the local CFA to school children in Anglesea. The paper can be found here - https://files.eric.ed.gov/fulltext/EJ1173481.pdf

We used a visual mapping exercise where children were asked a series of questions about what they would do in a bushfire and who would they give information to. This was done over two time points, before and after the CFA training.

We then used word clouds to draw comparisons between the two time points. See image below.

Example of a word cloud to make comparisons with qualitative data.

Why was it a success? Well, we can easily pull meaning from the before and after images. I have kept the same font and colour palette and we are not flooded with words.

This paper was published in 2014, and I would probably do things differently again now if I had the chance. Some of the word clouds used in the published article had words written both horizontally and vertically. The minute we change the angle of the text, the longer it takes to read and process. So I would keep all the words written horizontally.

There is one other occasion where I used a word cloud and that’s during my Design and Data Visualisation Short Course. In the PowerPoint session, I demonstrate some cool interactive tools that make your presentations more engaging. One of those is Poll Everywhere. We use it to ask questions and vote on important things (like - do you like coriander…) but I use word cloud to ask participants to use one word to describe how they are feeling about today’s course. All the answers are anonymous and they begin to appear on the screen in front of them.

Below is a screen shot from my August course. I’m just relieved no one said bored!

Word cloud used for August short course.

If I haven’t convinced you there is worth left in the old word cloud, some other ways to represent qualitative data include the following:

· Spectrum display

· Heat map

· Quotes

· Images

· Bold text with an action colour

· Gauge chart

· Sunburst

· Mind map

Keep your word clouds simple with consistent font and colour palettes and only use them for comparative purposes.

And how’s this for irony, the journal that the Survive and Thrive paper is published in has the following logo…

Source: http://iajiss.org/index.php/iajiss/article/view/316/277

Before: https://viz.wtf/, After: designed by Alana Pirrone

Back-to-back bar charts

July 15, 2019

In a recent presentation I gave on creating research impact using infographics and data visualisations, I displayed this terrible bar chart (found at https://viz.wtf/ – very funny site) as an example of what not to do.

As you can see it’s far too cluttered and busy and your eyes don’t know where to look. It’s hard to draw meaning from something this messy and your audience will probably give up before your message is properly communicated. We would be in serious trouble if this was to be printed in black and white. So, I suggested to the group that as we are comparing two groups, each with their own sub categories, we might think about turning this into a back-to-back bar chart. I left it at that.

After the presentation I thought I should put my money where my mouth is and actually create a back-to-back bar chart from this data to show how it should be done.

This is what I came up with...

Let me walk you through what I have done.

Before I begin, let me add that I created this in InDesign. I have included a tutorial below on how to create a back-to-back bar chart in Excel from Stephanie Evergreen.

Step 1

So first off, I organised the ‘hospital inpatient’ group from largest to smallest. This was no mean feat trying to match the eccentrically coloured columns with the tiny coloured legend at the bottom. You can see I have scrubbed out the Y axis on the left as we already have the values in the rows, we don’t need them twice. Bar graphs always look better and are easier to comprehend when the data are ordered. It’s less work for our brains to do.

I had to use a condensed font to squeeze in the 11 categories and even used some abbreviations. I then filled the data in the first bar graph. I used one colour only and put the exact values at the end of the column so there is no ambiguity.

Step 2

Step 2 was to make the next bar graph (‘residential’) on the right, making sure I had matched up the categories correctly. It was unlikely that the data would be largest to smallest in this category, but that was only necessary in the ‘hospital inpatient’ group to guide our initial design.

Again, I put the exact values into the rows so we wouldn’t need an axis or grid lines. You can now clearly see the patterns in the data and it’s a lot easier to follow and draw comparisons between the two groups.

Step 3

One thing in particular that I learnt in Stephanie Evergreen’s course was to display a heading that draws clear conclusions from your data. Tell your audience what you want them to see in the data. As I don’t know by whom or why this visualisation was created or what message they wanted to tell, I’m going to pretend and pull my own message from the data.

I have colour coded the two groups ‘hospital inpatients’ and ‘residential’ to relate to their respective bar charts so there is no need to put a key in.

If I only wanted to focus your attention, just say, on the lack of beds assigned for mental health treatment in general hospitals, I can grey out all the other data and draw attention to the ‘general hospitals’ row. This is especially effective if you are using it in a presentation. All your other data is there for comparison, but you are telling your audience exactly where you want them to focus.

So there you have it. A few easy steps to follow and we have turned something horribly busy into an easy to comprehend visualisation.

To learn how to make a back-to-back bar chart in excel, here is a tutorial from Stephanie Evergreen: https://stephanieevergreen.com/making-back-to-back-graphs-in-excel/

If you are interested to learn more about data visualisation, please take a look at my one day short course Design and Data Visualisation for Knowledge Translation. This course is designed to teach individuals ways to translate and present their work into creative and compelling visualisations. No design experience necessary.