Company Context
You are an Engineering Manager in Atlassian’s Jira Cloud organization. Jira is a mature, multi-billion-dollar product used by software, IT, and business teams globally, but growth has recently slowed in the enterprise segment as customers demand both faster visible innovation and stronger reliability, extensibility, and admin controls. Your team owns a shared platform layer used by multiple Jira Cloud feature teams, including workflow automation, issue views, and ecosystem integrations.
Strategic Situation
Atlassian is planning the next 12-month investment cycle. Two competing proposals are on the table for your 40-engineer group:
- Option A: Platform investment — modernize the Jira Cloud extensibility and performance layer, reducing p95 API latency, improving Forge app reliability, and enabling faster delivery for downstream teams. This work is largely invisible to end users in the short term.
- Option B: Customer-visible features — ship a package of high-demand roadmap items for Jira Premium and Enterprise, including advanced cross-project planning, richer automation templates, and executive reporting improvements.
The GM wants a recommendation on how to balance these investments. The challenge is that platform work has indirect impact through retention, ecosystem growth, and future velocity, while feature work has clearer near-term revenue and sales value. You need to recommend an allocation of engineering capacity and defend it quantitatively.
Data Points
| Metric | Current State | Notes |
|---|
| Jira Cloud annual revenue influenced by this product area | $420M | Premium + Enterprise-heavy mix |
| Enterprise gross revenue retention | 91% | Down from 93% last year |
| % of enterprise escalations tied to performance/integration/admin pain | 28% | Top themes in support and CSM feedback |
| Avg time for feature teams to launch cross-cutting capabilities | 5.5 months | Estimated 30% due to platform constraints |
| Forge/Jira app partner attach rate in enterprise accounts | 42% | Accounts with 3+ active apps retain 4 pts better |
Additional assumptions from Finance and Product:
- Platform program would require 18 engineers for 12 months and is expected to reduce p95 latency by 25%, cut integration-related incidents by 35%, and improve downstream feature team velocity by 15% starting in month 9.
- Feature package would require 22 engineers for 12 months and is forecast to generate $14M incremental ARR bookings next year if launched on time, with a 60% confidence level.
- Missing the platform work for another year is estimated to increase enterprise churn risk by 1.5-2.0 percentage points and delay ecosystem roadmap items by at least two quarters.
- You cannot exceed the current headcount envelope of 40 engineers, and Atlassian leadership expects a recommendation that fits within one annual planning cycle.
Deliverables
- Size the strategic value of platform work versus visible features using the data provided and any clearly stated assumptions.
- Recommend a capacity split across platform and feature work for the next 12 months.
- Explain the trade-offs across revenue, retention, ecosystem strength, and execution risk.
- Assess how competitors such as Asana, Monday.com, and ServiceNow affect the urgency of each investment type.
- Propose the milestones and metrics Atlassian should use to revisit the decision mid-year.
Constraints
- Recommendation must fit within 40 engineers and a 12-month planning horizon.
- You may not assume a re-org or additional hiring in the first 6 months.
- Leadership wants a plan that supports both near-term commercial goals and long-term platform health.
- The answer should stay at the strategy/portfolio allocation level, not detailed technical design.
