Epic Template for Jira: Structure Agile Roadmaps
A structured Jira epic template for breaking down large features into user stories. Includes epic description, acceptance criteria, dependencies, timeline, and linkage to stories.
Jira Epic Template
Use this template to define large features or initiatives in Jira. Epics break into smaller user stories that fit into sprints.
Epic Header
Epic Name: [Brief feature title, 5-10 words]
Epic Key: [Auto-generated by Jira, e.g., PROJ-123]
Status: [Backlog / Planned / In Progress / Blocked / Complete]
Product Owner: [Name]
Assign To: [Team lead or architect]
Start Date: [YYYY-MM-DD]
Target End Date: [YYYY-MM-DD]
Epic Description
Business Context
What problem does this epic solve? Why are we building it?
[2-3 sentences explaining the customer pain point or business opportunity]
Example:
"Customers are manually entering data from PDFs into our system,
which takes 10+ minutes per file. This epic automates that process
to save time and reduce errors."
Proposed Solution
What high-level approach will we use?
[1-2 sentences on the solution]
Example:
"We'll build an OCR-powered upload feature that reads PDFs,
extracts structured data, and pre-fills forms automatically."
Success Criteria
How will we know this epic is done and valuable?
[ ] Feature is launched to production
[ ] 80%+ of users adopt the feature (tracked via GA4)
[ ] Manual data entry time reduced from 10 min to under 1 min per file
[ ] Customer satisfaction score is 4/5 or higher (NPS)
[ ] Zero critical bugs in first 2 weeks
In-Scope Features
What's included in this epic:
- [ ] PDF upload UI
- [ ] OCR processing (Google Vision API)
- [ ] Data extraction & structuring
- [ ] Pre-filled form population
- [ ] User feedback on accuracy
- [ ] Basic error handling
Out-of-Scope (Future Epics)
Deliberately NOT included:
- Multi-language support (future epic)
- Bulk file processing (future epic)
- Mobile app support (separate epic)
- Custom field mapping (future enhancement)
Technical Considerations
Architecture & Tech Stack
- Backend: Node.js + Express
- OCR Service: Google Vision API (or Azure Computer Vision)
- Data Format: JSON to SQL mapping
- Database: PostgreSQL (existing)
- Frontend: React component library (existing)
Risks & Dependencies
- Dependency: Google Vision API availability & pricing
- Risk: OCR accuracy varies by PDF quality (need >85% accuracy)
- Risk: Integration delays if PDF formats are inconsistent
User Stories (Breakdown)
This epic breaks into these user stories:
| Story | Title | Status | Points | |---|---|---|---| | PROJ-124 | As a user, I can upload a PDF file from my device | Planned | 5 | | PROJ-125 | As a system, I can extract text from uploaded PDF | Planned | 8 | | PROJ-126 | As a system, I can parse extracted text into structured data | Planned | 8 | | PROJ-127 | As a user, I can review and correct pre-filled data | Planned | 5 | | PROJ-128 | As a user, I can see upload progress and errors | Planned | 3 | | PROJ-129 | As an admin, I can view OCR accuracy metrics | Planned | 5 | | PROJ-130 | As a user, I receive email confirmation after upload | Planned | 2 |
Total Story Points: 36
Estimated Timeline: 2-3 sprints (4-6 weeks at 12-16 points/sprint)
Acceptance Criteria (Epic-Level)
The epic is "done" when:
- [ ] All linked user stories are marked "Done"
- [ ] All acceptance criteria in child stories are verified
- [ ] No critical/high bugs remain unresolved
- [ ] Feature is deployed to production
- [ ] Monitoring dashboards show healthy metrics (upload success rate >95%)
- [ ] User documentation is complete
- [ ] Team has completed UAT (user acceptance testing)
Dependencies & Blockers
External Dependencies
- [ ] Google Vision API quota (need 10k calls/month)
- [ ] Data privacy compliance (GDPR/CCPA for storing PDF content)
- [ ] Design mockups from Design team (blocking PROJ-124)
Internal Dependencies
- [ ] Database schema updates (DBA task, needed before coding)
- [ ] API endpoint design review (arch review, blocking backend work)
Blockers (Current)
- [ ] Design mockups not yet approved (ETA: May 31)
- [ ] GDPR legal review pending (ETA: May 28)
Sprint Schedule
Planned Sprint Allocation:
| Sprint | Week | Stories | Points | Goal | |---|---|---|---|---| | Sprint 31 | Jun 3-14 | PROJ-124, PROJ-125, PROJ-128 | 16 | Upload & OCR integration | | Sprint 32 | Jun 17-28 | PROJ-126, PROJ-127, PROJ-129 | 18 | Data parsing & review | | Sprint 33 | Jul 1-12 | PROJ-130 + bug fixes | 5 | Email notifications & polish |
Metrics & KPIs
How we'll measure success:
| Metric | Target | Tracking | |---|---|---| | Feature adoption rate | >80% of active users | GA4 event tracking | | Time saved per upload | under 1 min (was 10 min) | User survey + analytics | | OCR accuracy | >85% correct data extraction | QA testing + user feedback | | Upload success rate | >95% (no failures) | CloudWatch monitoring | | Customer NPS score | 4/5 or higher | In-app survey |
Rollout Plan
Phase 1: Beta (Week 1)
- Deploy to 10% of users (internal team + beta customers)
- Monitor errors & OCR accuracy
- Collect feedback
Phase 2: Staged Rollout (Weeks 2-3)
- Expand to 50% of users
- Monitor adoption & issues
- Address top user feedback
Phase 3: Full Release (Week 4)
- Release to all users
- Monitor adoption & support tickets
- Create knowledge base articles
Related Epics
Other epics that tie into this:
- Mobile PDF Upload Epic — Mobile app version of this feature (future)
- Data Quality Epic — Validation & error handling across all imports
- Admin Dashboard Epic — Reporting on PDF processing metrics
Success Definition (What "Done" Looks Like)
Engineering Done:
- All user stories closed
- Code reviewed and merged to main
- Deployed to production
- Monitoring alerts configured
Product Done:
- Feature launched to users
-
80% adoption within 30 days
- No critical bugs
- User feedback is positive (4/5 NPS)
Business Done:
- Revenue impact measured (e.g., +15% retention)
- Customer support tickets reduced
- Roadmap item marked as delivered
Review & Retro
Post-Launch Review (1 month after launch)
- [ ] Schedule retro with full team
- [ ] Review KPIs against targets
- [ ] Identify what went well & what to improve
- [ ] Plan improvements for future updates
Related Resources
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