Common Myths in Information Visualization

A myth is a figment of the imagination, an allegory according to Antidote. In practice, they are often shortcuts that we think will save us time. In reality, they tend to hinder understanding, undermine users’ trust in data, and impair decision-making.

We looked at the myths that we find in information visualization, which make us cringe every time we encounter them in our mandate.

Here they are:

To think that a graph alone is enough to convey the essential point.

We often hear the phrase “I want a single graph to present everything and show the interrelationships.” Well, let us tell you, putting everything in a single graph often leads to information overload, hence the famous expression ” too much is as bad as too little .”

A good chart helps answer a business question, solve a problem, or achieve a strategic objective. Ask yourself, “Does this chart help me answer question XYZ?”

Believing that adding more data, more measurements, or more visuals improves understanding.

This brings us back to our point: adding more data doesn’t necessarily lead to a better understanding of the situation. We need to choose our indicators, those that will allow us to make the right decisions within a given timeframe.

To imagine that a visualization is objective by nature, when in fact every choice (color, order, scale) influences the reading.

Some languages ​​are read from right to left, while French and English are read from left to right. People’s brains adapt to these small details, which influence how graphs and data are interpreted. Similarly, if you start a graph on a specific date, the scale will be cut off, and the data will be different; your decisions may not be the same.

Believing that the same visual can meet the needs of all audiences, from strategists to operational staff.

Some visuals are designed to encourage more time spent reading, analyzing what’s presented, and exploring different scenarios. Others are designed to facilitate the quickest possible decision. Think of a boss given a table with detailed data. Often, they won’t take the time to read it, and you’ll end up having done all that work for nothing.

That is why each visual must be chosen with in mind the time its audience has to interpret and understand it, as well as the level of data literacy* of its target audience.

To think that everyone interprets colours in the same way, when in fact they carry cultural and emotional codes.

Red can be perceived as danger… or as a sign of prosperity, depending on the cultural context. And for a colorblind person, a traffic light color code (red-yellow-green) can simply be illegible.

Confusing aesthetics with understanding. A visual can be magnificent… and totally useless.

A beautiful visual, a beautiful informational product, the addition of shading or the integration of the 3rd dimension does not mean a better understanding of the information. Clarity is measured rather by the speed of the user in answering the question “What do I need to understand and decide?”.

To believe that users will immediately understand a complex visual without context or explanation.

You’ve learned how to read graphs, but not everyone has. An explanation of the selected data, how to read the graph, and how to interpret the data in relation to other information presented in the information product—you must ensure that everything is understandable to all readers, otherwise your dashboard risks being useless in the end.

Thinking that a dashboard must show everything to be complete, when in fact overload kills understanding.

There’s a reason your car’s dashboard doesn’t always show that everything is fine. It only displays a few pieces of information and alerts when something requires your attention, so you can focus on what’s most important: driving.

To imagine that showing the data as it is is enough, whereas the value comes from the interpretation and contextualization.

If I tell you your apples will cost $4.99 a bag, is that a good deal or not? The bag weighs 4 pounds, is that better? The regular price for this type of bag is $5.99, do you still want to buy it? Usually during the second week of July, so in 3 weeks, the bag drops to $3.99, do you still want to buy this bag of apples? You will only need apples in August, what is your final decision?

The starting value was not sufficient to make a decision; it is the comparison, the context, and the perspective of the data that helps you make a better decision.

Believing that a visual that is effective in one context will automatically be effective in another.

Objectives, culture, maturity, literacy, business challenges—all of these vary from one dashboard to another. Visualization must be carefully considered to align with all these elements in order to provide the best indicators, at the right time, to the right people.

Overcoming these myths strengthens trust in data, accelerates dialogue with stakeholders, and ultimately increases the organization’s analytical maturity.

At ADNIA, our role is precisely to translate complexity into executable simplicity, by mobilizing teams around a sustainable data culture that is useful and integrated into the strategy.

Because a good visual is not meant to impress, it is meant to help decide.

Data literacy : the ability to read, understand, analyze, interpret, and communicate data in order to derive meaning and support informed decision-making. It also implies a critical mindset to question data quality, context, and potential biases. [fr.wikipedia.org] , [huwise.com]