Auto-managed
sprint - saving hours,
every time
DISCIPLINES
Product Design · UX Research
Product Strategy
METHODOLOGY
The Atlassian Way · System design
Job to be done
PROJECT TYPE
Enterprise · B2B · SaaS
72%
of eligible teams enabled Auto-managed Sprint within 90 days, validating demand for automation in recurring sprint workflows.
68%
reduction in sprint administration time across setup, closure, and unresolved issue handling activities.
41%
decrease in support requests related to sprint management after introducing automated sprint lifecycle controls.
CONTEXT
Automation over
repetition.
In Jira, every sprint must be started and completed manually. At the end of each sprint, Scrum Masters also need to decide what happens to unresolved issues, adding extra administrative work to an already busy schedule.
This process becomes particularly challenging in enterprise environments, where multiple teams run parallel sprints and Scrum Masters repeatedly perform the same actions across projects.
Auto-managed sprint helps teams automate sprint start and end dates, reducing manual effort and improving workflow efficiency without changing the way teams plan and run their sprints.
PROBLEM
What was broken?
When a sprint closes in Jira, all remaining tasks are automatically moved back to their original position in the backlog. For sprint owners managing multiple parallel sprints, finding and reassigning those tasks became a recurring time sink.
PERSONA
Who did we design for?
Scrum Masters and Project Managers running parallel sprints in enterprise organisations. Responsible for closing sprints, managing unresolved work, and keeping multiple teams moving without manual overhead.
HYPOTHESIS
What did we believe?
If sprint owners managing parallel sprints could close a sprint without manually locating and reassigning remaining tasks, they would spend less time on sprint administration and reduce the risk of work slipping between cycles.
UNDERSTAND THE PROBLEM
Gathering data
The Atlassian public issue tracker (JAC) tickets, along with numerous comments left by Jira users, were utilised to formulate the initial problem statement, hypothesis, and to pinpoint a specific issue for further investigation.
JAC: A public issue tracker where users report bugs and suggest improvements. It hosts thousands of entries, and users can vote and comment, providing direct feedback on specific features.
EMPATHIZE WITH USERS
Expanding Horizons
Desk research and insights from customer interviews, as well as threads and comments posted by Jira users on the Atlassian Community portal, played a crucial role in empathizing with users and gaining a deeper understanding of the root cause of the problem. This combined dataset was utilised to formulate the final problem statement and develop several hypotheses that were subsequently tested during user testing activities.
EXPLORATION
Design, Prototype, Implement - Phase One
Following the creation of the problem statement and hypothesis, I organised and facilitated a remote design studio workshop. During this workshop, participants sketched initial solutions, presented their ideas and prioritised them based on business goals, technical feasibility and user needs. We used both personas and user journeys to help participants empathise with users and focus on solving real problems for our target audience.
Personas, User Journey, How might we...? Artefact and activities used to facilitate a design studio workshop
Result of an ideation session during a design studio workshop.
PHASE ONE - DESIGN
Auto manage sprint
Following the design studio workshop, I developed high-fidelity wireframes following the standards of the Atlassian Design System (ADS) and the Atlassian Design Guidelines (specifically tailored for the Atlassian Data Centre).
During the work on Auto managed sprints, wireframes were sparred several times with the design and development team redesigned and converted into Hi-Fi UI used for prototyping and usability testing.
VALIDATION
Usability testing
The culmination of the entire design process was a usability testing session where participants interacted with the Figma prototype remotely in a semi-structured usability testing session. Data from this session was processed using the Dovetail application and affinity mapping techniques.
The P.U.R.E (Practical Usability Rating by Experts) methodology was used to evaluate the interface both before and after the implementation of design changes. This methodology revealed significant improvements in usability, as evidenced by reduced time spent on tasks and a reduction in the number of errors made by users.
EXPLORATION
Design, Prototype, Implement - Phase Two
Following the successful launch, it was decided to move on to the next phase and implement a number of enhancements based on the findings from the research and usability testing. We've also included enhancements based on suggestions and requests from Jira users via the JAC portal and community forum.
These enhancements cover a range of features, including default configurations for auto-managed sprints, onboarding for auto-managed sprints, and a revamped process for enabling parallel sprints.
Among the many improvements introduced in this phase, Sprint Management becomes the largest feature developed as part of the Auto-Managed Sprints and Parallel Sprints functionality.
Learnings & Challenges
The feature touched far more of the product than expected. Time zones, Backlog, Kanban — all needed changes. It wasn't one feature. It was a system change.
No backward compatibility between Jira Data Center design guidelines and the Cloud design system. Every decision had to work across both. That slowed everything down.
Breaking delivery into small, independent chunks. Constant stakeholder alignment. Structure was the only way through the complexity.
● LET'S WORK TOGETHER
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andpon - Andrzej Poniatowski
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