Important: This graphic is part of the Actionable Agile module that is not available in the new product version.
Cycle Time Scatterplot
The cycle time Scatterplot chart is a representation of how long it takes to get things done for individual items on your Kanban board.
- How long does it take for user stories to be done?
- How long does it take for bug/defect to be done?
The chart's goal is to visualize the cycle time of assignments within a predefined time frame. It aims to provide you with information about when a task can be expected to be completed and the certainty of this as a measurement in percentiles.
Across the "x" axis is a representation of time- you can see the months and dates across the button. On the "y" axis is the cycle time.
How does this chart work?
Every time an item is completed, the system plots a dot next to the cumulated cycle time for that item (just draw a horizontal line from the dot to the "y" axis). For example: on May 22nd, an item was completed and it took 7 days to get done.
A lot of the dots have small numbers inside - it means that the same number of items have been finished on that day. On hover, you can see the cards IDs.
To predict how long it takes for a single item to be completed, you need to activate the probabilistic view of the chart via the percentiles -> Select All.
Let's start with the 50% percentile. If you draw a horizontal line all across the chart, it will cut the dots in half - 50% of the dots will be below the line and 50% of them will be above the line.
What's that telling us?
The answer is that 50 % of those items took 7 days or less to complete. An alternative assumption may be - when an item enters our process, it has a 50% chance to be completed in 7 days or less.
You can calculate the 85% and 95 % percentile in the same way.
These percentiles are important because they show us how much risk we are willing to take. If we are fine being wrong 50% of the time -> we will say that 7 days are needed to complete the tasks.
If we need to be more accurate in our forecast, then we will interpret the process using the 85% or 95% percentile, which gives a higher level of certainty.
Please, read the full dedicated article about the Scatterplot chart here:: https://kanbanize.com/blog/premium-cycle-time-scatterplot/