What is data visualization for business?

Data visualization is a straightforward concept: it’s the idea that if we translate quantitative data into visual stimuli following a specific process, we can use the data much more effectively. This is the gist of it. Business visualization adds “insights” and “decision-support” to the mix and is more explicit about determining the ROI of data.

Don’t mix them up

Think of data visualization as a language. It is broadly used to analyze and communicate quantitative data, but each “speaker” has his/her own goals and tools, with a vast array of background experience and skills. You need to make sure each approach fits the situation: you can’t turn each chart into data art, but an obvious Excel chart in your corporate brochure is probably unwise.

3D exploded pie chart
Trying to grab attention without adequate design skills has catastrophic consequences.

One of the worst and most common business visualization mistakes is making charts more visually attractive using canned effects. Without necessary design skills, you end up with 3D flying pie charts that distract, call attention to themselves, not to the data, and adds no value. Design training is not strictly necessary in business visualization, but you’ll want to focus on the message, not the package. If you emphasize the message and do it right, it’s almost sure that the package (aesthetics) will be pleasing, too.

Don’t forget the data

I’m writing this in 2021, one year after the beginning of the Covid-19 pandemic. It’s hard not to be swamped by charts about cases and deaths. People consume charts avidly to get some sense of what is happening: is it getting worse? Is it getting better? How is my country doing compared to its neighbors? Unfortunately, the pandemic teaches us all a hard lesson on visualizing data for insights and action. But it is also telling us that, long before making a chart, we should ask ourselves:

  1. Can we trust the data?
  2. Is it exhaustive?
  3. Are we measuring the things we think we are measuring?
  4. Are concepts comparable?
  5. How are people in power using data to further their agenda?

Don’t forget the goal

You can explore the data without a concrete goal or a specific question to answer, but the more you move from exploration to communication, the more concrete and specific these questions must be. You can analyze pandemic data to make sense of:

  • Historic performance;
  • Country-level forecast;
  • Current personal risk assessment;
  • Implementation of vaccines.

These goals are different, and the visual display should take that into account. How you design a measure will also change: today, using relative dates (starting the first cases in each country, instead of calendar dates) is probably less relevant than it was in the early months. Many other questions arise: should we compare change or rate of change? Absolute values or divided by population? How can we visualize the data to grab attention and try to improve behaviors?

Effective insights for decision making

Business visualization has essentially the same perspective and goals: useful data, visualized effectively to maximize fast insights.

Traditionally, managers would analyze data tables and illustrate a few numbers with colorful charts. This was taken to the extreme in organizations where Excel is the primary business intelligence tool. This is not feasible anymore. Excel is still a valuable tool, but users often lack core skills to manage an ever-increasing volume of data: manipulate and structure the data and visualize it using better charts than the ones available by default. To work effectively with Excel today, users need to become familiar with tools like PowerQuery, which makes connecting to multiple sources and preparing the data much simpler than ever before. And PowerBI is also an excellent tool for data management and reporting, although its data visualization capabilities are far inferior to Excel at the moment of writing.

So, business visualization is mostly about fast results (insights, monitoring). This must be driven by improved data and visual literacy. In Excel-centered organizations, this often means a complete revamp of the way people use Excel.

Or simply outgrow Excel and choose a better tool.