Presenting quantitative information is a specialized form of communication. Like all forms of communication, quantitative data presentation is most effective when we follow a few best practices, such as the following seven tenets.
- Know your data. Until you understand the stories that live in your data, you can’t begin to tell them.
- Know your audience. Unless you understand what matters to your audience, you won’t know what is of interest and use to them.
- Determine your message. Every dataset contains multiple stories. You can’t tell them all at once. Before you present quantitative information, you must determine the specific message or messages that you want to communicate. Start by writing a sentence or two or three to express the message before moving on to determine the ideal means of expression.
- Reduce the data to what’s needed to communicate the message. Pare the data down to the essence of what your audience must see to understand the message. What’s essential usually involves more than a simple set of primary values (e.g., monthly sales figures), for without context in the form of comparisons, numbers mean little. For example, monthly sales figures compared to target values or to values for the same months last year are more meaningful than sales figures alone.
- Determine the best means of expression. Some quantitative messages are best communicated with words, some with tables of numbers, some with graphs, and some with a combination. Some messages are best displayed in a bar graph, some in a line graph, some in a scatter plot, and so on. Knowing which form of expression works best for the message that you’re trying to present requires a little training into how our eyes and brains process visual information. The principles are easy to learn, but they aren’t intuitive. I wrote the book Show Me the Numbers, in part, to teach these principles.
- Design the display to communicate simply, clearly, and accurately. Include nothing that isn’t data unless it’s needed to support the data. Unnecessary color variation and visual effects, or even grid lines in a graph when they aren’t needed, will detract from the message. Non-data elements that are needed should only be visible enough to do their job and never so visible that they call attention to themselves. Non-data elements should sit politely in the background so the information stands out clearly in the foreground. If some information is more important to the message than other information, do something visual to feature it. For example, a brighter color or thicker stroke would make a particular line in a line graph stand out more than the others.
- Suggest a way to respond. Whenever possible, make it easy for your audience to respond with appropriate action by suggesting specific steps. Most quantitative messages aren’t presented merely to inform, but also to motivate a useful response.