How to read the stacked area charts?
Apr 4, 2020
The stacked area chart type is used in the Open Tasks, Completed Tasks, and the Timing screen. It is a powerful chart as it allows grouping of data, and seeing trends over a selected date range. This how-to guide helps you to read and understand this chart to get most out of it.
The stacked area shows each of the grouped items, in this case labels, as a separate colour. The horizontal axis shows the totals per day. It’s a time series chart showing your task completion pace over a time period. Grouping can be by any available property in your task data, including custom fields.
You can see the overall trend by looking at the shape of the chart (also shown as a trend line at the overlay above the chart). Is it ascending or descending?
You can adjust the length of the history shown from the drop down menu on the top right. The overlays on top of the chart show totals from the selected time period.
Numbers are clickable so you can drill down to see the individual tasks behind the numbers. That can reveal useful information about the individual tasks completed at a specific point in time in case you want to dig a little bit deeper.
For example, clicking through from the Timing screen shows the cycle times of individual tasks:
That information can be used for analysing quick and slow tasks in the past. In addition to spotting outliers, you may find patterns that can help you plan your work in the future. Lean more about detecting bottlenecks in your workflow
What people sometimes get confused about this chart is by its use of a rolling window, in this case 30 days. It is there so that you can see the overall trend without getting distracted by too much detail.
So what does an individual data point represent?
In Completed Tasks screen, a single data point in the horizontal axis represents the number of tasks completed over the previous 30 days period. In Timing screen, each data point shows the average cycle time.
A rolling window is used for smoothening away the daily fluctuations in the number of tasks completed. In some days your team completes zero tasks, in some days multiple tasks. In some days, e.g. near the end of a sprint, the completion rate can spike. This is just noise which you are unlikely to be interested in.
What you really want to know is the overall trend, is it ascending or descending. By default, the chart uses 30 days rolling window. That means that each point in the horizontal axis shows the number of tasks completed during the previous 30 days period. That smoothens out the daily, weekly and per sprint variation in the data, and results into more readable chart that allows to see longer time trends.
When you hover your mouse on the chart, a tooltip is shown showing the start and end date of the rolling window, and the totals for that period.
You can also click through to see the individual tasks at any point of the chart. Wanna see what’s behind the numbers? Just click through to see in more detail.
Adjusting the size of the rolling window
You can change the rolling window length it in the screen settings:
You can choose between 7 days and 30 days rolling window. The default is 30 days. If you set the rolling window to 30 days, the first day of the chart shows the numbers from the 30 days period before the start date of the selected date range.
Exporting the data
If you want to get more data scientific, or mix it with your own data, you can always export your data in CSV of JSON and make your own calculations. The export feature is available in the main menu:
Before exporting, select the grouping of the data and adjust the unit in the settings if needed. You can choose to use estimates (card size, story points etc.), any of your numeric custom fields, or simply a task count as the unit.
Check out our product roadmap and follow us on twitter or Facebook. Please do not hesitate to contact us any time at hello@screenful.com if you have questions or feedback.
Let us know if you have questions or feedback by contacting hello@screenful.com. To stay on the loop, read our blog, or follow us on LinkedIn.