The clock reads 13 seconds left in the basketball game. The team huddles around their coach to plan their last play. The players listen intently as the coach explains each person’s role in the upcoming moment.
Tools for explaining: lessons from science class
Let’s take a timeout from this thought. What are the odds that their play is executed flawlessly? From a few verbal cues, each player knows what to do. Right? I’ve been in this adrenaline-pumping position more than once, and every time, the coach grabbed a whiteboard and drew out each person’s move. A few scratches of x’s and arrows on a half-court plan brings clarity in seconds.
At ThoughtForm, visual models are a staple artifact for our clients. We often leave an hour-long work session with a whiteboard sketch of our client’s new business model, offering structure, or internal process diagram. After several iterations, our client’s team has a communication tool they can use to build consensus and understanding in multiple internal and customer-facing scenarios.
Whether it be a team playbook or business ecosystem, some use visual models to call attention to key ideas and convey information to the audience. While users might discover the model in their own way, they should always walk away with the same storyline. When users consistently interpret the messages, the model is considered most effective.
Data visualizations: A new type of visual model
With the rise of big data, a new type of visual modeling—data visualization—has emerged. You are already familiar with the simple bar graph and pie chart. I’m referring to the integration of multiple complex data sets into a structure explored by the user.
Consider the recent pull for visualizations around our country’s census data or political race. These have an abundance of information packed into one view. They invite the user to interpret the information to discover their own ideas and develop a unique story, rather than unpack a scripted story told by the maker. The distinction here is what the user brings to the model.
This has me curious about how we approach data visualizations differently than traditional visual models. I’ve made a few observations about how users perceive and translate data that might influence how we approach developing visual models for businesses in the future.
Data visualizations let users write the story
Users follow different paths through the information, and develop their own story lines. Each user takes away ideas that are relevant to his or her own curiosity and goals. Since it’s no longer a one-time use piece, the lifecycle of the information is extended. Users can go back time and time again to uncover new ideas.
Data visualizations offer a range of stories
Users can get the big picture from glancing at the structure in its entirety. With census data, for example, users might get a broad sense of the socioeconomic makeup of different neighborhoods within a region. At the same time, users could also drill down and look at a more selective set of data points to understand the variation within a single neighborhood. Even further, there are multiple variables layered in to allow users to start to understand what factors are influencing that particular neighborhood. This gives users the ability to control the scope of what they’re interpreting at any given moment.
Data visualizations allow for manipulation
With interactive dashboards, users can “play” with information to test their assumptions and validate their predictions. They control how the display of information changes, revealing opportunities to discover new ideas that weren’t available before. Data visualizations can take the form of static outputs, but the information that populates them often resides in a tool that can be modified to add new data sets and features. That means designers can expand and dynamically change visualizations over time to cater to user interests.
Data visualizations provide concrete evidence
People are skeptical. They are quick to question broad statements or claims, especially if it feels like there’s a marketing spin applied. You’ve probably seen the latest telecommunications provider commercial debating what it means to have the fastest network. If you could see hard statistics regarding each network’s speed, you’d probably give that statement a little more weight. People trust data, especially when there’s proof that it’s authentic, cleaned, and verified. Statistical and numerical figures lend an authenticity that users can’t ignore.
While the power of the traditional visual model is in its ability to make abstract ideas more concrete, data visualizations emphasize the value the user brings to the information. How can we integrate these approaches to develop an even more powerful communication tool?
Up next: As digital business transforms, interconnectedness is key