Onboarding Analysis
Private betaNew engineers take months to become productive. How much is that costing you?
Every new engineer is a significant investment. You start paying from day one, but it can take months before they are working at full speed. During that time, your existing engineers also spend time helping them get up to speed. That means more engineering cost and less time spent on your actual product. Gitrevio helps you see how quickly new engineers become productive, where they are losing time, and what is slowing them down.
Get new people productive faster. Reduce the cost of onboarding. Get more work shipped with the team you already have.
Ramp-Up Curve
The ramp-up curve, measured
# Onboarding progress — Alex Rivera (hired Feb 3)
Week Productivity Benchmark Status
1 ▓░░░░ 12% 10% ahead
2 ▓▓░░░ 22% 18% ahead
4 ▓▓▓░░ 41% 35% ahead
8 ▓▓▓▓░ 63% 60% on track
12 ▓▓▓▓▓ 78% 75% on track
Time to first real feature: 18 days (org avg: 24)
Time to first solo PR: 8 days (org avg: 12)
Current mentor: Sarah Chen (4.2h/week invested)
! Blocker: CI pipeline confusion (3 failed builds, day 5-7)
Productivity is not just about how much code someone writes. Gitrevio looks at the actual work to understand how quickly a new engineer becomes productive and independent. It looks at completed work, code reviews, waiting time, and how much support the new engineer still needs from the rest of the team.
Every new hire is compared with your own team's history. You see how their ramp-up compares with previous hires in your company, rather than relying on a generic industry benchmark.
Problems show up early. If a new engineer is waiting too long for reviews, getting blocked by the same process, or needs more support than expected, Gitrevio helps you see it before weeks are lost. The earlier you see the problem, the sooner you can fix it.
What It Measures
What it measures
Every milestone that matters for a new engineer, tracked automatically. No surveys. No manager checklists. Just signal from the work itself.
First milestones
Time to first commit, first PR, first approved PR, first solo feature — the trajectory that predicts long-term ramp-up speed
Code quality trajectory
Review comment density decreasing over time. Fewer nits, fewer revision rounds, more first-attempt approvals as the new hire learns your standards
Independence curve
Decreasing mentor review ratio. Week 1, every PR gets mentor review. Week 8, they're self-sufficient. Track the slope.
Integration velocity
Cross-team PR submissions, multi-repo contributions, API boundary work — signs the new hire is moving beyond their starter project
Blocker identification
CI failures, documentation gaps, tooling confusion, long PR wait times — the friction that slows ramp-up and is invisible to managers
Knowledge acquisition
Files and repos touched over time. Expanding scope means growing confidence. Staying in one directory means they might be stuck.
Review participation
When new hires start reviewing others' code — and when those reviews start adding value. A key signal of true integration.
Collaboration patterns
Who they work with, how often, and whether they're building relationships across the team or staying isolated with their buddy.
Confidence indicators
Commit message quality, PR description thoroughness, decreasing questions in review comments — subtle signals of growing ownership.
Compare cohorts, find what works
Some teams get new engineers productive much faster than others. Why?
Maybe they have better documentation. Maybe new hires start with smaller tasks. Maybe they have a better support process. Gitrevio helps you find out what is actually making the difference. Compare onboarding across teams, seniority levels, and different time periods.
Did your new onboarding process help people become productive faster?
Did a change in your process reduce the time your existing engineers spend helping new hires?
Which teams consistently get new people up to speed faster?
Now you can see what works, learn from it, and use it across the company.
Better onboarding is not just an HR improvement. It means getting more value from every engineering hire, sooner.
# Cohort comparison — 2025 hires by team
Backend (5 hires)
Avg time to solo PR: 9 days
Avg time to full speed: 11 weeks
Top blocker: local env setup
Frontend (3 hires)
Avg time to solo PR: 14 days
Avg time to full speed: 16 weeks
Top blocker: component library gaps
Mobile (2 hires)
Avg time to solo PR: 21 days
Avg time to full speed: 19 weeks
Top blocker: build system complexity
! Mobile ramp-up is 1.7x slower than backend
The ROI
The math is simple
A senior engineer costs $150K a year. That's roughly $3K per week. If it takes 16 weeks for a new engineer to become fully productive, that's a significant amount of your investment tied up during the ramp-up period.
Cut that time to 12 weeks and you recover roughly $12K of productivity per hire.
Hire 10 engineers a year and that's around $120K of recovered productivity.
And that's only the direct cost. When new engineers become productive faster, your existing team spends less time helping them. Projects move faster. More work gets shipped. And your company can start getting value from the new hire sooner.
The longer someone takes to become productive, the longer you wait to get the return on your hiring investment.
Gitrevio helps you see where that time is being lost and where you can improve the process.
Hire better. Ramp up faster. Get more value from your engineering investment.
Onboarding ROI calculator
Avg engineer cost: $150,000/yr
Weekly cost at partial prod: $3,000
Current avg ramp-up: 16 weeks
Target avg ramp-up: 12 weeks
Savings per hire: $12,000
Annual hires: 10
Gitrevio cost (25 seats): $12,000/yr
Annual savings
$120,000
ROI
10x
The tools behind onboarding analysis
Ramp evidence is produced by named functions that handle the joiners who have not reached autonomy yet, rather than dropping them from the average.