How can you make data visualization accessible to your entire organization?

1 Know your audience

Before you start designing your data visualization, you need to understand who your audience is, what they need, and how they will use your data. Different audiences may have different levels of familiarity, interest, and expectations with your data. For example, a senior executive may want a high-level overview of the key insights, while a frontline worker may need more details and context. To make your data visualization accessible, you need to tailor your message, format, and style to suit your audience's needs and preferences.

2 Choose the right tools

There are many tools and platforms available to help you create and share data visualizations, from simple charts and graphs to interactive dashboards and maps. However, not all tools are created equal when it comes to accessibility. Some tools may have limitations or drawbacks that affect the usability, readability, or compatibility of your data visualization. For example, some tools may not support screen readers, keyboard navigation, or color contrast adjustments. To make your data visualization accessible, you need to choose the tools that offer the most flexibility, functionality, and compatibility for your audience.

3 Use clear and consistent design

The design of your data visualization can have an immense impact on how your audience perceives and interprets your data. If done poorly, it can confuse, mislead, or overwhelm your audience, while a well-crafted data visualization can clarify, inform, and persuade them. To make your data visualization accessible, you should employ clear and consistent design principles. This includes selecting the right type of chart or graph for your data and message, using appropriate colors, fonts, and symbols that are easy to distinguish and comprehend, adding labels, legends, titles, and annotations that explain your data and emphasize the main points, avoiding clutter, noise, or distortion that can obscure or distort your data, and following the accessibility guidelines and standards for web content and data visualization.

4 Provide multiple formats and options

Creating accessible data visualization can be a challenge since different people may have different preferences, abilities, and devices for accessing and viewing your data. For example, some may prefer to see your data as a table while others may prefer to hear it as a narration. Additionally, people may have visual impairments, cognitive disabilities, or language barriers that affect how they process your data. To make your data visualization accessible, you need to provide multiple formats and options for your audience. This could include offering alternative text, captions, transcripts, or summaries; providing downloadable or printable versions; enabling zooming, filtering, sorting, or searching features; allowing users to customize or personalize the visualization; and testing the data on different browsers, devices, and screen sizes.

5 Solicit and incorporate feedback

The final step to make your data visualization accessible is to solicit and incorporate feedback from your audience. Feedback can help you identify and address any issues, gaps, or errors, as well as improve its quality, relevance, and impact. Additionally, it can help build trust, engagement, and collaboration with your audience. To do this, you need to ask for opinions, suggestions, and questions about your data visualization. You can use surveys, polls, ratings, or comments to collect and measure feedback. After analyzing the feedback to identify the strengths and weaknesses of your data visualization, make changes or updates based on the feedback. Lastly, communicate and acknowledge the feedback and the changes to your audience.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?