Five Data Chart Mistakes to Avoid in Presentation

Are you presenting data graphs a lot on your slides? Make sure you are not falling into one of the data visualization traps. Here are the most common mistakes I see people do when they present various Excel charts to PowerPoint.

How to avoid those typical data visualization mistakes? I am sharing a few quick tips on how you can handle those mistakes using only PowerPoint tools.

This is a fragment of our training workshops. For more details see our Online Training on Presentation Design.

1. Inappropriate data chart

PowerPoint offers a dozen of data charts you can choose from. A recent addition (from Office365) includes a fancy-looking Sunburst, Funnel, or Waterfall chart.

However for most of the presentation purposes, you will need to use a few basic charts or their versions: Bar (or column) chart, Pie chart (also doughnut or donut one), and Line chart (or area chart). Each of them fits a different purpose:

Line Charts and Area Charts

The line chart is best for showing data change over time, For example, showing sales trends, website traffic over the last days or global warming temperatures over decades.

Mistakes I have seen involve using line charts with categorical Y axes (e.g. a specific product). Another thing to avoid using a line chart is showing too many variables on one chart.

Pie and Doughnut Charts

Those are nice-looking charts in the shape of a circle, that are meant to represent data that compose one whole. Typically a market share or any kind of percentage data e.g. a survey answers distribution.

An important mistake to avoid in a pie chart to check for – the percentage values should always sum up to 100%.

Speaking of common visual error that I see quite often, is using a pie chart with way too many categories. To keep data readability high, I recommended showing max 6 categories in a pie chart. And order them by value from biggest to smallest. If you have more categories, group the last 7+ categories into one category “others”. And if needed, show this category on another chart.

Column and Bar Charts

Those charts represent data value by the size of a vertical or horizontal bar. They are suitable to compare multiple categories e.g. sales of various products. Unlike line or pie charts, you can show here also more variables and charts will be still readable.

One thing I would suggest is to use color coding with some business logic behind it. Use various colors if you want to underline that variables are different. Apply only 1 color if you want to focus more on values than on a variety of categories.

How to choose a chart for your data

If the focus of your presentation is to show outcomes in an understandable way, and not to do exploratory data analysis, then it’s better to use those classical data charts. Avoid fancy new charts, that may not be that easy to comprehend by your audience.

Choosing one of those basic data graphs, consider what you want to show:

• Is it a share from some whole part? Then consider Pie or Doughnut chart.
• Is it a trend over time? Then the Line chart is your obvious choice.
• Or do you compare several items? Then go for the Bar chart.

To learn more about data charts I recommend a book by Nancy Duarte: Data Story or Say it with Charts by Gene Zelazny.

2. Unclear reading flow of a data slide

When you are designing a slide with data presentation, indicate clearly how the reader should look at it, where to start and where to follow.

Is the chart title the first thing a reader should look at? Or is it a trend line? A specific data value or outlier you want to highlight? Don’t let the reader guess what’s the most important part.

How to tackle reading the reading flow mistake?

Use design elements to lead an eye of a reader – using color contrast, font size, or some highlighter shapes – arrow, oval. Remember, the natural way for reading the slide is from left to right, from top to bottom (at least in western culture).  People will tend to read the slide this way unless you show the other way.

Therefore take case your chart objects are aligned for a logical reading flow. This will ensure your slide will be easy to read.

3. Too much data presented on a slide

You may be tempted to show all details of your data analysis, how you got these results, exploring and presenting many data nuances. However ask yourself: Is this crucial information also for my audience? The presentation should focus on the final result of your analysis and explain it properly.

Imagine there is a limited attention span and people can stay highly focused for a few minutes only. How do you want to spend those precious minutes of their time?

How to tackle the data overload issue?

Think twice, whether you need to present all details that led to your final data analysis outcomes. Does the audience need to hear it all? Maybe some parts can be put into appendix materials only?

4. Chart slides are too detailed and decorated

It’s a good idea to enrich a graph with colors, icons or another additional element. However, each element should have a function. It should add value and not be a mere decoration.

This is another frequent trap in data visualization – having a graph visualization with too many additional elements. Or using fancy graphs that are not intuitive to understand – this may be the case of 3D bar charts, or radial charts overuse instead of simple bar chart, if your audience is not used to such charts.

Reading data should not be a quest for a reader.

Cure: Remember “less is often more”. Prefer simplicity over sophistication. If your chart is getting too complex, consider splitting it into more charts. Show one variable at a time. Use color coding to highlight only the most important parts. Consider not showing some data labels if they are essential for data understanding.

5. Unclear presentation goal

This may not be a strictly visual mistake, but it influences all data presentation challenges I mentioned above. You may have super-looking data charts, clear to understand, but if your audience asks at the end “Nice, but what is it good for?”, then the presentation may be wasted time for you and the audience. Therefore, think about it before you start making any data visuals.

When putting together a presentation, make sure you know what is your goal, what you want to achieve by showing your data. What’s the story and morale behind data?

Cure: Define the goal of your talk before preparing the presentation. Write it on a piece of paper, whiteboard in the office to have it in front of your eyes when working on slide content. State it at the presentation beginning, too, so your reader knows what to expect.

Consider structuring your presentation using 4MAT questions model or AIDA flow (Attention, Interest, Desire, Action) – here’s an article with using AIDA slide examples.

Summing up data presentation issues

These were a few examples where data presentation can go wrong. Realizing those risk areas you can think about how to tackle them properly. There may be more, of course. A lot depends on your context – are you presenting to experts or novice audience, are you a skilled professional speaker or are you starting the path of presenting.

You don’t need to be a data science Ph.D. expert to use data charts properly. In data visualization, a lot can be done using a few rules of graphical design (contrast, alignment, or consistency). With proper use of colors and PowerPoint, shapes can create visually attractive data plots. You can enrich them with additional elements that will help a reader in faster interpretation of data categories.

For more examples check my other article on chart PPT redesign tricks.

If you want more learn more, check my data presentation training where I share more ways you can enhance data charts and make your presentation slides attractive.

Need further help in slide redesign – reach out to me, I will be glad to talk.

Peter
Concept visualization nerd :), Slide Design Trainer & Designer