Five Data Chart Mistakes to Avoid in Presentation

Creating effective data charts in presentations is crucial for conveying information clearly and persuasively.

For those who incorporate data graphs into their slides, it's crucial to avoid the typical data visualization mistakes that often occur when transitioning from Excel to PowerPoint.

Here are five common data chart mistakes to avoid in your presentations.

1. Inappropriate data chart

PowerPoint provides a wide selection of data chart options, with recent additions like the visually appealing Sunburst, Funnel, and Waterfall charts included in Office365. However, for the majority of presentation needs, it is advisable to rely on a selection of fundamental chart types or their variations, namely the Bar (or column) chart, the Pie chart (including the doughnut or donut variant), and the Line chart (or area chart). Each of these chart types serves a distinct purpose.

?? Line Charts and Area Charts

Line charts and area charts are particularly effective for visualizing changes in data over time. They are well-suited for displaying trends, such as sales patterns, website traffic fluctuations over a specific timeframe, or long-term variations in global warming temperatures.

Common mistakes that should be avoided when using line charts include the use of categorical Y axes (e.g., representing specific products) and the inclusion of an excessive number of variables on a single chart.

?? Pie and Doughnut Charts

These visually appealing circular charts are designed to depict data that constitutes a complete entity, often used for visualizing metrics like market share or percentage-based data, such as the distribution of survey responses.

A logical error in a pie chart occurs when the percentage values fail to add up to 100%.

A common visual error is the excessive use of categories in pie charts. To maintain clarity, it's advisable to limit pie charts to a maximum of six categories, arranged in descending order of value. If there are more than six categories, consider grouping the least significant ones (typically seven or more) into a single category labeled "others." If necessary, present this "others" category on a separate chart for improved comprehension.

?? Column and Bar Charts

These charts illustrate data values using the size of vertical or horizontal bars, making them ideal for comparing multiple categories, such as the sales of various products. Unlike line or pie charts, bar charts can effectively display more variables while maintaining chart readability.

It is advisable to implement color coding with a clear business rationale. A diverse range of colors can be used to accentuate variations between variables, while a single color may be preferred when the primary emphasis is on values rather than the diversity of categories.

How to choose chart to your data?

When selecting a chart for your data, it's essential to consider your presentation's primary objective. If the goal is to present outcomes in a clear and easily understandable manner, it is advisable to opt for classical data charts. Avoid using elaborate new chart types that may be less comprehensible to your audience, especially if your aim is not exploratory data analysis.

When deciding on one of the fundamental data graph types, it's important to consider the specific message you wish to convey:

- If you need to represent a portion of a whole, consider using a Pie or Doughnut chart.

- If you want to illustrate a trend over a period, the Line chart is the most suitable option.

- When you need to compare multiple items or categories, the Bar chart is the preferred choice.

2. Unclear reading flow of a data slide

When creating a slide for data presentation, it's essential to provide clear guidance on how the reader should approach it. Specify where they should begin and what to focus on.

Should the chart title be the reader's starting point? Is there a particular trend line, a specific data point, or an outlier that you want to emphasize? Avoid leaving the reader to guess; clearly indicate the most critical elements and the preferred sequence of interpretation.

How to tackle reading flow mistake?

Utilize design elements such as color contrast, font size, or visual markers like arrows or ovals to guide the reader's focus. Keep in mind that the typical reading pattern in Western cultures follows a left-to-right and top-to-bottom flow. People naturally tend to read slides in this manner unless indicated otherwise. Use these design elements to direct the reader's attention and enhance the intended flow of information across the slide.

Ensure that the chart objects on your slide are arranged in a logical sequence to facilitate a coherent reading flow. This organization will contribute to the slide's readability and make it easier for your audience to comprehend.

3. Too many data presented on a slide

It's common to want to present all the intricacies of your data analysis, including the process of obtaining results. However, it's vital to assess the relevance of this information for your audience. A successful presentation should prioritize the final analysis outcome and deliver a clear and effective explanation to your audience.

Consider the limited attention span of your audience, as people can maintain high focus for only a brief duration. Reflect on how you intend to utilize these valuable minutes of their time.

How to tackle data overload issue?

Carefully consider whether it's necessary to present all the intricate details that contributed to your final data analysis results. Ask yourself if the audience truly requires this extensive information. Some portions may be more suitable for inclusion in supplementary appendix materials.

4. Chart slide too detailed and decorated

Enhancing a graph with colors, icons, or other elements is beneficial, but each addition should serve a purpose. These elements should contribute value and not merely serve as decoration.

Another common pitfall in data visualization is the inclusion of excessive additional elements in a graph. It's also prevalent to use complex or elaborate graphs that may not be intuitive to comprehend, such as the overuse of 3D bar charts or radial charts when a simpler bar chart might be more comprehensible, especially if your audience is not familiar with such visuals.

Reading data should not be a quest for a reader.

Solution :? Prioritize simplicity over complexity. If your chart becomes excessively intricate, consider dividing it into multiple charts and displaying one variable at a time. Utilize color coding to highlight only the most critical elements, and evaluate whether certain data labels are necessary for a clear understanding of the data, considering their potential omission.

5. Unclear presentation goal

Even if you have exceptionally well-designed data charts that are easy to comprehend, the presentation may prove unproductive if your audience concludes with the question, "Nice, but what is it good for?" Therefore, it is crucial to contemplate this aspect before initiating any data visualization efforts.

In the process of presentation creation, it's vital to know your goals and what you intend to achieve. Consider the story and the underlying message within the data to effectively convey your message.

Establish the purpose of your presentation before crafting its content. Document this goal on paper or a whiteboard in your workspace to keep it in constant view while developing the slides. Also, ensure to articulate this objective at the outset of your presentation, allowing your audience to understand what they can anticipate.

Data visualization benefits from the application of fundamental principles of graphical design, such as contrast, alignment, and consistency. By utilizing colors and PowerPoint shapes effectively, one can generate visually appealing data plots. Furthermore, the inclusion of supplementary elements can enhance the reader's ability to interpret data categories more swiftly.

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