Innovation & Value projects
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.
TEAM
Andrzej Poniatowski
Valeria Shymko
Jacek Krawczyk
Roman Kolosovskiy
RESPONSIBILITY
UX/UI design
Design lead
Researcher
METHODOLOGY
Good, Better, Best framework The Atlassian Way
Design Sprint
System design
PROJECT TYPE
Enterprise / Scale
B2B, B2C
Project details
The aim of this Innovation & Value projects is to address design debt, enhance Jira's capabilities and innovate based on user input gathered through the JAC portal, ideas brought by developers and design aim to improve the usability, look and feel of Jira.
All features and enhancements are designed, prototyped and tested using the Design Sprint methodology. These designs are then segmented into small, manageable components to enable independent development and ensure a steady flow of value to end users while maintaining a consistent user experience.
Each design component is logged as a task in the improvement backlog in Jira, open for any developer to work on during their allocated 20% time. They also serve as potential innovation ideas for the ShipIT project or can be assigned to new team members as part of their onboarding process. This approach encourages collaboration, innovation and skill development within the team.
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.
Learning
The redesign of the filters in Jira DC was the first project undertaken during the initiative, and based on the learnings from this project, all other sprints were modified to better suit the specific requirements of the Atlassian landscape.
After the first sprint, we decided to extend the length of the sprint from the recommended one week to four weeks, with the first two weeks dedicated to discovery, design, prototyping and research.
A further two weeks are dedicated to documenting research findings, refining designs and applying findings from usability testing sessions and collaboration with development teams. During the sparring sessions, all designs are reviewed with the development team and project manager, and then broken down into small chunks that can be delivered independently, delivering value to the end user in rapid iterations without the need to release the entire feature at once.
The overall redesign of the Jira filters was a huge success in both design and implementation. Ultimately, the sprint initiative proved to be a great way to add value to the Jira Data Centre.
● LET'S WORK TOGETHER
Got a project?
Let's talk.
andpon - Andrzej Poniatowski
© 2026