Delivery time is one of our most popular and versatile metics. It looks at completed tickets over time and adds up the elapsed time in calendar days (ie. including weekends) of all statuses on those tickets. We then divide all the time by the number of completed tickets and you get Delivery Time.
By configuring this metric and filtering fields like Issue Type and Status you can create some fundamental views like Lead Time, Cycle Time and Bug Resolution Time. See below for some examples:
Furthermore, once you understand the trend of your Delivery Time over time, you are able to breakdown the average days by Status to see where your process might be slow or hitting bottlenecks.
Percentiles - Rather than just the mean average, you can also calculate an exact percentile value
Outliers - Exclude statistical outliers by refining the range of data
Deployment Data - Limit the tickets to those that have been part of a production deployment
Setting up Delivery Time to track Story Cycle Time
1) Click add a metric in the top right by the date picker. Under Delivery, select Delivery Time and add it to your dashboard.
2) Once it's on your dashboard, open the metric by clicking Explore, and then go into the metric settings (the little gear icon ⚙️ in the top right).
3) In Filters, we are going to want to select just our Story tickets. Add a filter for Issue Type and select 'Story' or whichever types you want to track.
4) Next, you want to add another filter, this time for 'Status'. Here you want to select any status that represents your process from when work starts on a ticket to when it ends. Typically this should include statuses like 'In Dev', 'Review', 'Ready for Test' etc. You might also want to include any 'Done' statuses as they might show the additional time when tickets are reopened.
5) You'll want to now change the name of this metric so you and your colleagues can understand how you have configured the settings. You can do this by simply changing the Name in the top of the Metric Setting section on the right.
6) Click Save. You will notice that the data refreshes initially displaying a single over time line chart. At this stage you might want to play around with Breakdowns, we find by Status particularly useful for Delivery Time.