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[Case 04]

Jira Companion - AI Integration in the Jira Workflow

Jira Companion - AI Integration in the Jira Workflow

Atlassian X SUEDE Designathon 2023

[Project Overview]

"Jira Companion" is a concept designed for the SUEDE X Atlassian Designathon 2023, a competition held by Atlassian in collaboration with Sydney University Experience Design Society (SUEDE). We were tasked to make Jira - a project management tool, more accessible to new users and reduce the learning curve by utilizing Artificial Intelligence. The competition lasted for a total of 3 days.

[My Role]

UX/UI Designer, UX Researcher

[Timeline]

October 2023 (3 Days)

[Tools]

Figma, Miro, Jira, Canva

Plenti - Your affordable pantry tracking companion

Interactive Product Design Studio (DECO3200) - The University of Sydney

[Project Overview]

In this unit, we were tasked with iteratively conceptualizing, designing, and prototyping a solution that aligns with one or several of the 17 Sustainable Development Goals identified by the United Nations. We were required to consider both the social and technical aspects of our concepts, while also being aware of potential sociocultural resistances to novel ideas. The project encouraged us to take a creative, provocative, or utilitarian design approach, challenging social norms when appropriate. Additionally, our final concepts needed to be interactive, ensuring they effectively engage users while contributing to a sustainable future.

[The Brief]

Jira has a steep learning curve

"Today, when people want to start managing work in Jira, they have to learn new concepts and technical terms to get the most out of it. This is unacceptable because everyone should easily be able to get access from Jira. We envision AI simplifying complex tasks, saving people time and empowering teams to drive their mission forward."

[Our approach]

Designing the agile way

A fully working prototype was meant to be ready and submitted at the end of the designathon, which meant we had a total of 3 days to flesh out the concept; all the way from research and ideation, to testing, iteration, and the final prototype. Hence, an agile methodology was defined to develop our concept quickly at such a short notice. Each step of the process was very quick and at its best pace contributing to the development of the final concept. The agile methodology process is as shown below

[Research plan]

[01] Competitor Analysis

Conducted secondary research into existing project management tools and how they integrated AI into their workflows.

[01] Competitor Analysis

Conducted secondary research into existing project management tools and how they integrated AI into their workflows.

[01] Competitor Analysis

Conducted secondary research into existing project management tools and how they integrated AI into their workflows.

[02] Surveys

Primary research included online surveys to understand initial onboarding challenges faced by new Jira users.

[02] Surveys

Primary research included online surveys to understand initial onboarding challenges faced by new Jira users.

[02] Surveys

Primary research included online surveys to understand initial onboarding challenges faced by new Jira users.

Our research phase started off by conducting a competitive analysis. This allowed us to compare the features offered by competitor project management tools and also evaluate how competitors integrated AI technologies into their platforms to enhance user experience.

This was followed by conducting surveys on our target users (newly inducted Jira users) to get quantitative data on their pain points. Surveys were the preferred method of data collection in this case as it was the quickest way to gather a large volume of data given our extremely short timeframe.

[Competitor Analysis]

[ClickUp]

Offers basic automation and NLP features but lacks advanced AI capabilities.

[ClickUp]

Offers basic automation and NLP features but lacks advanced AI capabilities.

[ClickUp]

Offers basic automation and NLP features but lacks advanced AI capabilities.

[Ayanza]

Focuses on visual brainstorming and collaboration tools but doesn't have AI-driven features.

[Ayanza]

Focuses on visual brainstorming and collaboration tools but doesn't have AI-driven features.

[Ayanza]

Focuses on visual brainstorming and collaboration tools but doesn't have AI-driven features.

[Teamwork]

Offers AI integration for project management but lacks in NLP driven user interactions.

[Teamwork]

Offers AI integration for project management but lacks in NLP driven user interactions.

[Teamwork]

Offers AI integration for project management but lacks in NLP driven user interactions.

Addressing these gaps would require the integration of AI driven features such as natural language processing and predictive automated workflow creation into Jira.

[Surveys findings]

[Key identified issues]

Upon synthesizing our questionnaire data, we found new Jira users faced 3 main issues, as shown below.

[Refining our problem space]

After synthesizing our findings, we revised our initial problem statement to better align with the problem area. This problem reframing allowed us to pinpoint the frustrations faced by our users, and develop a design concept that addressed these specific pain points.

[Personas]

Our research findings were condensed into 2 different personas to detail the motivations and frustrations of a typical user that was new to Jira. This helped us identify the needs and preferences of the target users in a more human-centric way.

[Redesign goals & vision]

Make it simple, humanize the interface

The overarching goal of this redesign was to make Jira more intuitive and accessible for new Jira users. And so, before delving into the design phase, I established a set of pivotal conditions to shape an efficient user flow.

[Solution]

For our solution, we chose to implement three new features that directly address the pain points faced by new Jira users

[Solution]

[01] Automated Issue Creation

Users are able to simplify issue creation by asking Jira Companion

[01] Automated Issue Creation

Users are able to simplify issue creation by asking Jira Companion

[01] Automated Issue Creation

Users are able to simplify issue creation by asking Jira Companion

AI Chatbot utilizes NLP to enquire details about the issue, and then generates a template of the described issue.

Users are able to further edit this auto-filled template of their issue and finalize issue creation.

Confirmation displayed after issue creation. This keeps users informed about the status of their action.

[02] Feature Discovery

Once users click on feature discovery option, they are provided with a prompt that allows them to click on a feature and know more about it.

[02] Feature Discovery

Once users click on feature discovery option, they are provided with a prompt that allows them to click on a feature and know more about it.

[02] Feature Discovery

Once users click on feature discovery option, they are provided with a prompt that allows them to click on a feature and know more about it.

Brief description of selected feature displayed in the form of a pop-out menu.

New users can also use the walkthrough feature to familiarize themselves with the selected feature’s interface

[Final Prototype]

[Key Learnings]

Embracing challenges

I was initially intimidated by Jira due to my lack of experience, and the design brief seemed complex. However, after research and hands-on exploration, I gained insight into its pain points and challenges. This taught me the importance of overcoming apprehensions and adapting quickly to solve complex problems.

Embracing challenges

Focus on the learnings and not the end result

Despite our team not being selected as one of the finalists, I learned a lot in the intensive 3 day period of the designathon. It taught me to rapidly prototype, collaborate effectively; even with people I had just met, and it also taught me to manage my time efficiently as we only had a short window of time to complete each stage of the design process.

Focus on the learnings

Focus on the learnings and not the end result

Accomplishing time-boxed goals

Setting goals in such a short timeframe and adhering to them was one of the most difficult aspects of this challenge. There were times during the process where it felt like we were falling behind, but we managed to persevere and ultimately delivered a concept that successfully addressed the problem space.