Innovation beyond
the roadmap.
DISCIPLINES
Product Design · UX Research Service Design
METHODOLOGY
Good, Better, Best · Design sprint The Atlassian Way
PROJECT TYPE
Enterprise · Scale · B2B
37
JAC issues and backlog items grouped into
sprint-ready improvement opportunities.
86%
task completion rate across 4 validated filter management tasks.
4.8/7
average SEQ score confirming the redesigned workflow felt easier to use.
CONTEXT
Innovation through
continuous improvement.
Innovation & Value projects focused on improving Jira Data Center through new features, usability enhancements, and addressing design debt. Ideas originated from customer feedback gathered through the JAC portal, suggestions from developers, and opportunities identified by the design team.
Every initiative followed the Design Sprint approach, giving the team a structured way to explore opportunities, prototype solutions, and validate ideas before investing development effort. This helped reduce uncertainty, align stakeholders around a shared direction, and focus on improvements that delivered real value to users.
Once validated, solutions were divided into smaller implementation tasks and added to the improvement backlog. This helped create a continuous flow of improvements while maintaining a consistent user experience across Jira Data Center.
PROBLEM
What was broken?
Accumulated design debt and unresolved JAC requests were degrading the experience of Jira Data Centre users. Without a structured improvement process, issues compounded faster than they could be addressed.
PERSONA
Who did we design for?
Jira Data Centre users — project managers, developers, and administrators — working in enterprise environments. Users who submitted improvement requests through JAC and expected them to be heard.
HYPOTHESIS
What did we believe?
If improvement work was structured into repeatable design sprints addressing related JAC requests together, individual changes could be shipped independently — creating a continuous stream of value without waiting for a major release.
The Atlassian way to bring continuous improvement to the Jira Data Center
Initiatives focused on continuously improving the Jira Data Centre by developing new features, creating innovation and overcoming design debt through the use of a design sprint approach.
Process
Filters redesign: Sprint 1
Implementation of the Design Sprint process, based on a redesign of the Jira filters
Overview of the design sprint process implementation based on the redesign of the filter management experience in Jira Data Centre. A first project planned and executed as a Design Sprint during the Innovation and Value project initiative.
Sprint planning based on design capacity, number and type of similar issues that could be fixed together in a process of Jira filter redesign.
Knowing the size and capacity of the team as well as the size and number of issues we face, I decided to change the design sprint formula and modify it to better suit Atlassian specific and our workload. I decided to extend the sprint to a two-week period, with the first week dedicated to exploration, design prototyping, and recruiting participants for usability testing. The second week of the sprint was exclusively dedicated to executing usability research, documenting the findings and implementing the findings into a new design.
Throughout the design sprint process, the Miro board played a central role in fostering collaboration between all project stakeholders. From the outset, it served as the primary medium for documenting our work and facilitating remote workshops.
During the sprint, the board was instrumental in brainstorming ideas, planning activities, creating interview scripts and defining tasks for a usability testing session. It was also used for affinity mapping to analyse research findings. As the project progressed, the board was used to generate ideas within the 'good, better, best' framework
Context
In Jira, filters are customisable search criteria that allow users to define and save specific sets of issues based on various attributes such as issue type, status, assignee, priority and more. These filters allow users to quickly access and view the issues that meet their specific requirements, without having to perform a new search each time.
Filters play a critical role in managing and organising issues within Jira, helping users streamline their workflow, track progress, and gain insight into project status and performance. They are particularly useful for teams working collaboratively on projects, providing a way to focus on relevant information and streamline communication.
Explore
During the discovery phase, we used several research activities to identify opportunities and issues related to filters in Jira. After initial analysis focused on UX audit and analysis of issues and requests raised by users through the JAC system, we moved on to customer interviews and P.U.R.E evaluation to gain a deeper understanding of the issue.
Job stories were used to help the team understand the situation in which people encounter a problem and why it needs to be solved.
Using "how might we..." questions helped the team to come up with creative solutions, while keeping the team focused on the right problems to solve. The "How could we..." exercise was carried out during the solutions workshop and applied to all the problems we identified.
Make
To conclude the Explore phase and transition to the Make phase, a Solution Workshop was organised. During this workshop, participants engaged in the Crazy 8 exercise followed by Solution Sketching.
The results of the workshop were used as the basis for the development of wireframes, high-fidelity interfaces and a Figma prototype. These designs used components from the Atlassian design system, supplemented by custom components tailored to support the specific needs of Jira Data Center and enterprise customers.
Filter usage metrics & detailed view
Filter Overview - Provides a quick overview of the filters
used and helps reduce the number of fields.
Make
To conclude the Explore phase and transition to the Make phase, a Solution Workshop was organised. During this workshop, participants engaged in the Crazy 8 exercise followed by Solution Sketching.
The results of the workshop were used as the basis for the development of wireframes, high-fidelity interfaces and a Figma prototype. These designs used components from the Atlassian design system, supplemented by custom components tailored to support the specific needs of Jira Data Center and enterprise customers.
Dive into statistics: Introducing filter usage, a metric for assessing relevance
Automated cleanup
Automatic purge of unused filters ensures efficient management, while user control allows reversible actions and archived filters remain easily accessible for retrieval and restoration
Filter Management
To improve filter management, the concept of sections within the Saved Filters interface was introduced, allowing users to categorise their filters based on specific criteria such as project, team, status or priority. This provides a more organised and intuitive way for users to find and manage their saved filters.
Flexibility and efficiency of use has been improved with the introduction of a contextual menu that provides quick access to commonly used actions for filters, such as subscribing, sharing, removing from starred and editing.
The drag-and-drop interface was implemented to increase user control and freedom by allowing users to seamlessly move filters between sections, allowing them to effortlessly reorganise their filters to suit their needs without navigating through complex menu options.
To increase consistency and align with industry standards, a bulk action feature has been introduced. This allows users to perform actions on multiple filters simultaneously and includes options to Subscribe, Share or Remove multiple filters at once, saving users valuable time and effort when managing large sets of filters.
Validate
All designs created for Jira filters were tested and validated during the usability testing exercise. During this exercise we validated our hypothesis and gained insight into users' mental models for sharing, subscribing and using filters.
To conduct the exercise, 12 participants were recruited using usertesting.com. Participants were divided into two equal groups based on the software they used, Jira Data Centre and Jira Cloud.
During the usability testing session, the participants participated in a guided interview and a semi-structured usability testing session using the Figma prototype. During the usability testing session, all participants were asked to complete 4 different tasks using the Figma prototype, after each task participants were asked to answer a Single Easy Question (SEQ) to enrich the qualitative data with quantitative data.
Learnings & Challenges
The timeline. A standard Design Sprint promises answers in five days. With Jira's complexity, stakeholder structure, and enterprise sign-off requirements, one sprint cycle took closer to three weeks. The structure worked — the schedule needed to be honest.
Moving validated ideas into the development queue. Enterprise cycles are slow by design. The only way through was building evidence so clear it removed the debate — a 4.8/7 SEQ score and 86% task completion rate did that job.
Treating the backlog as a product strategy, not a list of tasks. Grouping 37 JAC issues into sprint-ready themes forced a prioritisation conversation the team hadn't had before.
● LET'S WORK TOGETHER
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andpon - Andrzej Poniatowski
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