You’re putting together a Jira report to present at a meeting. You could just hand over raw data in spreadsheets for your audience to sift through, but chances are, they won’t find that useful, interesting, or memorable. If you want to convey the information in a way that’ll go in, and stay in, you’ll need to get to grips with Jira visualization.
What is Jira visualization?
Put simply, it’s the graphical representation of your Jira data. It’s a way of letting your audience see data on issues, projects, sprints, and epics using creative visual elements such as charts, graphs, and maps. It’s difficult if not impossible to tell an interesting, coherent, or accessible story by listing dozens of rows of numbers in a spreadsheet (sorry, spreadsheet lovers). But if you visualize those numbers in a nice, easily digestible bar chart, line graph, or heat map, that’s when stories start coming together.
With Jira visualization, an audience has the chance to see in an instant something that could otherwise take much longer to identify. It’s possible to spot trends or anomalies that would go unnoticed were you to look purely at the raw data. Of course, there may be times when you have to crunch the numbers as they are, but when you’re looking to communicate information quickly and effectively, Jira visualization is the way to go.
It’s important that your visualizations are accurate and not overly complicated. Likewise, choosing the right kind of chart or graph for what you’re trying to get across is crucial. A poorly constructed or chosen chart, rather than making data more accessible, can have the opposite effect, causing confusion and potential misinterpretation of data.
But how do you choose the right charts?
Have a look at the pie chart below. Can you identify the third largest portion of the pie?
Not easy, is it? It helps that there are only three segments, and you can toggle on the key, but still. If you want a Jira visualization that’s more ‘at a glance’, let’s try the same data in a different type of chart.
Much easier this time, right? That’s because pie charts are best suited to showing the relationship between all the parts that make up a whole, but elsewhere they tend to fall down. In the words of statistician Edward Tufte, “the only design worse than a pie chart is several of them”. A bit harsh, perhaps, but it’s certainly true that pie charts are frequently used in situations they’re just not suited to.
It’s an easy trap to fall into: pie charts are visually appealing and comfortingly familiar. When you want to show small differences between data points, though, they’re practically useless, unless you include annotations that state the values of each portion – in which case you might as well just present the raw data.
If you want to make better charts with clearer visualization of your Jira data, you have to do more than just avoid pie charts. First of all, you have to be sure that what you’re aiming to present is actually worth creating a chart for at all. Sure, you could build a bar chart for two or three units of data, but it’s probably easier and more informative to simply present that data in a table.
Once you’ve decided that a chart would genuinely be useful, consider the pros and cons of different types of charts and choose whatever’s a true fit for your needs. For example, bar charts, as demonstrated above, are much better than pie charts when it comes to displaying small differences in values. However, they’re not without their own shortcomings: they don’t work well for small sample sizes or for representing continuous data, such as temperature or time. Meanwhile other chart types, such as scatter plots and histograms, are much better ways to show things like sample size and distribution of data.
Why are some Jira visualizations better than others?
Human beings’ visual cortex didn’t evolve to be able to read charts in PowerPoint. It evolved to spot predators, identify things that are safe to eat, and help us survive nature’s elements. It seems plausible that our strengths and weaknesses when it comes to interpreting data in charts stem from such adaptations. So, understanding those strengths and weaknesses is key to making better data visualizations.
Research has shown that humans are much more effective at understanding certain types of visual encoding than others. The work of statisticians William Cleveland and Robert McGill has been particularly influential in how we understand this phenomenon. They ranked the different forms of data visualization and found that people are generally better at judging the length of lines or bars, but struggle more with differences in angle, area, color, volume, direction, and shading. This is why bars typically make better charts than pies. It’s also why adding 3D elements can, as the Financial Times puts it, “obfuscate the information you want to communicate.”
How to make better charts in Jira
Statisticians and scientists spend a lot of time thinking and writing about the effectiveness of charts because data visualization plays a key role in their jobs. The right charts can help scientists better understand the work of their peers, thereby informing their own research and aiding progress. They may also be instrumental in convincing funding bodies that a project is worth paying a grant for.
It’s the same in the business world. Get the right chart in front of the right person, and it could be exactly the thing you need to push a deal over the line. Stick reams and reams of spreadsheets under people’s noses, and they might simply walk away – into the arms of a company that knows how to present data more clearly.
The trick is to choose a chart type that can relay whatever message you’re trying to send. Some kinds of charts, like pie charts, don’t say a lot about their underlying data, while a scatter plot can tell you a whole lot more. But that doesn’t mean you should default to the most complex chart type all the time, because it may not be appropriate, and you could end up confusing your intended audience. In spite of what Edward Tufte says, sometimes a pie chart is exactly what you need.
Although scientists put have put a lot of thought into chart types, there’s no definitive methodology for data visualization. That said, there are some straightforward practices you can follow to help you make better charts in general:
- Graphs should present data that is otherwise too numerous or complex to describe in text form, and should take up less space. If your chart doesn’t do that, it’s not doing its job.
- Choose your colors carefully. If your chart relies on the reader being able to distinguish between different colors, they need to offer enough contrast for that to be comfortable. Also, think about the connotations that may be attached to different colors, e.g. green for good and red for bad. Otherwise, you could be sending a message that you’re unaware of. People have been shown to have very real physical and emotional reactions to certain colors.
- Don’t default to pie charts. It’s tempting to use pie charts for everything, but they’re really only useful in a handful of situations. If you’re not trying to show how a series of parts make up a whole, then choose a different chart.
- Don’t use a chart at all if you don’t need to. Sometimes it’s better to simply display the raw data in a basic table. This is especially true with simple data sets and small sample sizes.
- Use better tools. The right software can be enormously helpful when it comes to creating great charts. For instance, Custom Charts for Jira offers much more than the standard Jira visualization reporting feature set, giving the user a great deal more control over how their data is presented. By default, Jira’s native visualization options are more limited, which can lead to the very problems described in this article.
- Make sure your charts are easy to read. That means avoiding confusing background images and distracting colors. It also means not laying out text in a way that makes your audience tilt their heads to read it.
- Make better charts because you want to. If you’re including charts in your reports and presentations just for the sake of it, you’re not likely to be doing yourself or your data justice.
- Consider using more than one chart for the same data set. If you want to present a lot of information about your data, two simple charts may be better than a single complicated one.
- Never sacrifice legibility for fancy styling. When it comes down to it, charts are there to communicate information, and if they fail to do that, no one will care about how pretty they look.
Can better charts really benefit your business?
The more numerous and complex your data is, the more likely you would benefit from using charts. They make something accessible which would otherwise be overwhelming. Scott Berinato, writing for the Harvard Business Review, illustrates this succinctly with an aeronautical example:
“At Boeing the managers of the Osprey program need to improve the efficiency of the aircraft’s takeoffs and landings. But each time the Osprey gets off the ground or touches back down, its sensors create a terabyte of data. Ten takeoffs and landings produce as much data as is held in the Library of Congress. Without visualization, detecting the inefficiencies hidden in the patterns and anomalies of that data would be an impossible slog.”
Similarly, if you work for a software development company, your department might encounter hundreds or even thousands of issues a day. When it comes time to assess the performance of your team for, say, the last quarter, you’ll want to look at the response times of your staff members. You’ll want to identify who’s doing what, which tasks are taking the longest, and so on. It would be impractical and self-defeating to go through all the data points one by one, but a good chart? Well, that’s a different story. Charts enable you to see the bigger picture in a matter of moments, so you can make better decisions, faster.
It’s this kind of thinking that underpins all business intelligence solutions, which is why it naturally translates into improved business performance.
Power up your Jira visualization reporting
With everything you’ve learned from this blog post, you can begin to make better charts in Jira, but if you need more control, then you might want to try Custom Charts for Jira. It enables you to quickly change between different chart types, customize colors, filter data, and more. But it’s also highly accessible, meaning more of your people will be able to use it. That means your whole organisation can benefit.
Below is a comparison of standard Jira reporting and Custom Charts for Jira reporting to demonstrate. However, the best way of understanding what the app can do is by using it. So check out our Custom Charts for Jira in our demo playground and give it a try.
|Feature||Jira Out-of-the-Box||Custom Charts for Jira|
|Choose Segment Colors|
|Rearrange Segment Order|
|Drag and Drop|
|Advanced JQL Search|
|Chart by Story Points|
|Stacked and Grouped Charts|
Chris founded three successful startups in Thailand: one was a Scuba Diving School/ Eco-Tourism company dedicated to saving turtles. Once he’d saved enough turtles, he moved back to the UK to pursue his dreams in software.
It was while working for the Atlassian Platinum Solution Partner Clearvision that Chris met Jacek. The two decided there was a gap in the market for easier-to-use Atlassian tools for Jira and Confluence users who don’t have a clue how to code (of which there are many).
“If we’re not making mistakes, we’re not trying hard enough.”