How IBM uses data visualization for impactful storytelling

As a global leader in IT, IBM uses data visualization to empower business leaders across different industries. As a powerful means to showcase, discover, and understand information, data visualization is a powerful tool for revealing the insights within the numbers. With a deeper understanding of information technology and a commitment to clarity, IBM has a variety of tricks up its sleeve to transform complex data sets into engaging, actionable insights.

Criteria for an IBM data visualization

When creating memorable and impactful visualizations, IBM prioritizes clarity, intention, and context. The aim isn’t only for informative graphics but also for understandable visuals that are emphasized through clean, intuitive design that ensures that data is easy to grasp. IBM relies on criteria built on specific pillars:

Understandable

As the best data visualizations do, an IBM visual should be able to communicate the main idea with a single glance. Any extra elements that make the information seem more complicated should be avoided. Here, you can rely on established design and typography principles that enhance readability and form for easy viewing. Any extra embellishments that distract from the main information should be removed to avoid any misunderstandings.

Essential

Data visualization and design rely on a lot of strategic decision-making. Since it serves a practical purpose, the design should aim to answer a question or solve a problem. Structure, hierarchy, contrast, and other design elements are used in service of the information at hand. So the choices made related to the visual model or design elements are made with consideration for the data and what conveys it most effectively.

Impactful

IBM is invested in breaking down how things work; in practice, this looks like conveying complex concepts and making detailed data displays. The goal here is always to enable the user to explore a topic in detail by utilizing a system of filters and patterns that make the concepts simpler and more accessible. Rather than shying away from details, they embrace and organize them efficiently.

Consistent

Just as a brand would have core values, there should also be a consistent set of design practices that serve as the foundation for any data visualization. Accuracy in both visual style and data is crucial since they both contribute to a grounded understanding of the information. Beyond that, consistency in style and structure guarantees engaging storytelling that maintains the integrity of the data.

What makes IBM’s data visualization distinct?

There are many features and elements to consider for an IBM data visualization to be distinctive, mainly because they all play a role in creating a functional representation of data. Here are some of the best practices they use that help highlight the design aspects and how to use them.

Chart anatomy

Understanding the anatomy of a chart helps enhance data visualization. Starting with the title, it should address the main insight derived from the data and give background. Meanwhile, labels and legends provide deeper context to the chart and clarify the meanings behind colors and shapes with data points. When possible, add labels directly to the chart to facilitate comprehension and avoid dense legends.

Additionally, axes, ticks, and gridlines help illustrate the proportions and scale, making it easier for readers to understand the data accurately. However, it’s important to know how to strike a balance and avoid crowding a chart with too many elements so that you don’t hinder comprehension.

Color

Color always plays a role in design, whether in branding or charts. At IBM, color unifies its digital products and interfaces for consistency, and aside from recognition, it also facilitates more informed decision-making from users interacting with the content. It’s important to consider the context of the data and leverage accessibility, and color in particular is a sensory cue that guides the user toward the intended narrative.

The way color is used impacts how the data is received; for example, using color to create contrast highlights key insights and contributes meaning. Moreover, grayscales can ensure visibility without taking away from the main data points, while categorical and sequential color palettes reveal hierarchies within the data. Color is not just about making an aesthetic choice; rather, it is a strategic tool that enhances the narrative’s readability.

Interaction

The most engaging data visualizations are the ones that encourage interactivity with the viewer. The ability to search, filter, or highlight specific data points makes the viewing experience more meaningful, expanding its potential for data exploration. With IBM charts, interaction makes understanding data much more seamless when users can zoom in and access detailed information on demand. By prioritizing clarity, they don’t hide crucial information in their data visualizations; it empowers users to take initiative, explore insights and relationships, and make connections within the data itself.

Motion

Data visualization isn’t just for static charts, it’s about bringing the data closer to the viewer by breathing life into it. Motion here plays a role in how user experiences are created, and with IBM, animation effectively communicates the connections between data. When the information evolves, the visuals transition to make it easy for the viewer to follow.

Motion helps highlight data through subtle animations for the entering and exiting of elements or the movement of axes and data points. You can create engaging, clear, and informative charts by using motion more thoughtfully.

Data is a language, and IBM’s data visualization knows how to translate it into clear, impactful stories. Designing charts for clarity and purpose, their visuals use interactivity, motion, and color to reveal patterns and encourage users to dive deeper into the information. By relying on solid guiding principles, these visualizations ensure that every element is intentional and immersive, transforming numbers into knowledge.