The path to running a successful business starts with making the right decisions. This can be a challenge for many business owners, largely because nobody can see what the future holds. This is why Business Intelligence (BI) has become so popular; it helps us make better decisions. One form of BI is visualization – taking data and turning it into something visual we can use. While this can be useful, there is a chance that it can lead to data being misrepresented and the wrong decisions being made.
Here are four tips on how to make successful data visualizations – e.g., charts, graphs, flowcharts, etc.
1. They need to be easy to understand
When visualizing data, it can be very easy to make the outcome incredibly confusing. By having too many sets of data, trying to compare and visualize too much, or by simply laying information out in a confusing way, you could actually decrease the effectiveness of the message you are trying to convey or lose it altogether.
When creating visualizations, try to get someone who is part of your target audience to look over it and make sure they can understand what the visualization is representing and that it is easy to comprehend. If they can’t, you need to go back to the drawing board and try to come up with a way to present the data where the intended audience can understand and follow it easily.
2. They need to cater to the audience
The main reason most managers or owners visualize data is to present it to an audience. 99% of the time, this audience is a decision maker and you are trying to get them to decide on whatever the data visualization is representing.
Therefore, when setting out to visualize your data you should first define an end goal – what you want the audience to do with the data. In order to do this, and to develop a successful visualization, try considering these three questions:
- Who exactly is the audience? – Because the audience will ultimately be making the decisions, you should define who they are. Focus on how much they know and how comfortable they are with the subject, and their position within their organization or outside it. From there you can begin to tailor which data to present and how.
- What does your audience expect from the data? – This can be achieved fairly simply by actually asking key members of your audience. Try reaching out in an email and asking about their expectations. If they say they want something simple to understand, don’t use overly complex graphs or visualizations. Focus on what type of information is most important to them. For example, if you are visualizing sales data for a finance team, marketing related data may not be overly relevant.
- What is the role of the visualization? – Visualizations have many roles. Some are intended to educate, while others are aimed at prompting the audience to act or ask questions. As a general rule of thumb, educational visualizations should not create questions, while actionable ones should.
3. They need to have a clear framework or layout
When visualizing data you need to ensure that you develop a layout or framework that is clear and easy to follow. This means focusing on two main areas:
- Semantics – The meaning of the words and graphs used. Remember that simple words like ‘or’, ‘and’, etc. can drastically change the meaning of a sentence and possibly make it unclear. Because of the visual nature of this method you will need to be crystal clear with accompanying words and titles. The same goes for the visual side. If you are using icons or images, they need to look like the data they are representing and be clearly identifiable as different from other sets of data.
- Syntax – This is more how the words and visuals are used and represented. If visual and accompanying words are not laid out in a clear and logical manner, there is a high chance that the message or action you want to convey will fail to be grasped. Also, pay attention to how you present the data. If you are using a graph with lines, most people will view this as trend related, even if you intended to compare the results to different sets.
Above all – They need to tell a story
The most successful visualizations tell a story about the data. Unlike TV or movies, you aren’t telling a story for pure entertainment. The story should be related to how the audience will be affected or can be helped by the data represented in the visuals. If you are struggling to find a way to tell a story, try actually explaining the data. By knowing it inside and out, you will likely be better able to come up with an explanation that you may be able to weave into a fluid story for your audience.
If you are looking into visualizing your data, or improving how you present it, why not contact us to see how our systems can help.