by Juan C. Dürsteler
[message nº 73]
|To make a good information graphic is not an easy thing. It is fundamental to know what purpose it serves and to whom it is addressed, but it’s also convenient to follow a coherent process in order to correctly make it. In this issue we describe this process.
Recently I had the opportunity to prepare and give a course on information graphics for a financial entity. The subject of the course was to explain what you have to take into account when preparing a graphical presentation, especially when the data is quantitative.
So the idea wasn’t to explain how to make business charts with Excel or PowerPoint, even though we should use these ubiquitous tools to build them, but what techniques we should use in order to make the charts clearer and easier to understand.
Surprisingly enough there is very little literature on the topic. (At the end of this article you can consult a list of interesting books). The available books and information can be divided (in a rough approximation) into two categories.
- Catalogues of types of graphics and charts commonly used.
- Information on the theory and aesthetics of quantitative charts.
It’s difficult to distil elementary but general principles that summarise the best practice in performing business graphics or, in general, graphic presentations. And this is so for several reasons.
- The audience. You cannot unlink the charts from the audience they address. It’s quite different making a chart show the evolution of sales for a meeting of sales people than presenting a marketing campaign to the board of directors, even though the data can be the same.
- The objective the chart hopes to achieve. Information graphics can be done for several reasons. Among them we can highlight the following ones.
- To transmit or comunicate a message. Sales have improved but we are still behind budget….
- To present large amounts of information in a compact and easy to understand way. A road map is an archetypical example of this type of objective.
- To reveal the data. Discovering cause-effect relations, knowing what’s happening. It appears that in the business environment people think more about information graphics in order to show what is already known rather than discovering what is still unknown.
- To periodically monitor the evolution of certain parameters. For example the evolution of stock exchange, sales, budget…
The process of making an information graphic
It appears that the pressure of everyday work and the little time that we have means that when we are about to perform an information graphic we adopt the tactics of immediacy. We start Excel, throw in some data and select a chart type, accepting the terrible colours that Excel gives us by default.
In order to facilitate the process of creating a chart I’ve elaborated the diagram that you can see in the attached diagram.
The process is divided into three parts:
- What is it for?. The reason why we make the graphic representation . This determines the type of data to gather and about which we have to ask what type it has to be (quantitative, sequential categorical…) and more importantly: are they relevant for what we want?
- How?. In what way we will represent the data. A fundamental aspect of this section is that information graphics are interesting because they reveal differences. For this reason refining them and representing the data derived from their statistical treatment often reveals aspects that otherwise would result confusing.
Once data is refined we have to choose the most effective visual metaphor. Sometimes, for a little data, a table or even a sentence can be clearer that a chart. In certain occasions changing the colour palette or the type of chart can clarify the situation enormously.
- Does it work? We can obtain a nice and elegant chart but, if it doesn’t fit the goal that we have defined in the first step, we will have failed.
The key resides in revising and experimenting with what we have done until we find an improvement.
Varying the colours, reducing the saturation of what is less important and increasing it for the most relevant data, modifying the typography, the size of fonts, eliminating everything that doesn’t contribute to showing and clarifying the data (irrelevant grids, redundant data, unnecessary labels) without losing relevant information sometimes provides surprisingly improved results.
In the end, making a good information graphic consist of facilitating the understanding of complexity, instead of complicating what is simple. And this cannot be achieved without the clear understanding of what goal we pursue, who our audience is and a good deal of work and reflection.
Edward Tufte’s books: The Visual Display of Quantitative Information, Visual Explanations and Envisioning Information.
Digital Diagrams by Trevor Bounford
Visualising your business by Keith R. Herrmann
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