Planning & Reporting

Investment Distribution

Where does your engineering time actually go? iftrue auto-categorizes every ticket and PR into features, bugs, tech debt, KTLO, and maintenance, so you can see the real investment mix across teams and quarters.

Investment distribution · Engineering org · Q1 2026
weighted by points
New features 38%
Bug fixes 22%
Tech debt 14%
Maintenance 11%
KTLO / Support 9%
Meetings & planning 6%

Bugs up 7 points vs Q4

Bug share rose from 15% to 22% while features dropped from 45% to 38%. Frontend is driving the shift. Worth a quality review this quarter.

Auto-categorization from labels, titles, and commit patterns

Feature vs bugs vs tech debt vs KTLO breakdown

Per-team and per-engineer splits

Quarterly trend so drift is visible early

Auto-categorization

Every ticket, automatically classified

No more asking engineers to tag their tickets "correctly". iftrue reads ticket titles, labels, commit messages, PR titles, and the file paths they touched to classify work into the right bucket. Overrides are one click when the model gets it wrong.

Signal-based
Jira labels, issue types, commit patterns, and changed file paths feed the classifier.
Transparent
Every classification shows why. "PROJ-512 is bug because label=bug and commit touched only payments/refund.ts."
Overridable
One-click reclassification. The override improves the model for your team over time.

PROJ-512

Fix refund edge case for promo codes

Bug fix

label=bug + commit touched refund.ts

PROJ-518

Add dark mode toggle to settings

New feature

label=feature + new files added

PROJ-524

Migrate auth middleware to new SDK

Tech debt

migration keyword + no user-facing changes

PROJ-530

Oncall: investigate p95 latency spike

KTLO

label=incident + investigation commit

By team

Every team has a different story

Org averages hide the teams that are drowning. The breakdown per team surfaces who's shipping features, who's stuck in bugs, and who's paying down debt everyone's been ignoring.

Backend

Features 42%
Bugs 18%
Debt 20%
Other 20%

Frontend

Bug-heavy
Features 28%
Bugs 34%
Debt 12%
Other 26%

Platform

Debt sprint in progress
Features 15%
Bugs 10%
Debt 58%
Other 17%

Mobile

Features 48%
Bugs 22%
Debt 10%
Other 20%

Investment mix · last 4 quarters

Bugs trending up
Q2 25 48% features · 14% bugs
Q3 25 46% features · 16% bugs
Q4 25 45% features · 15% bugs
Q1 26 38% features · 22% bugs

Trend insight

Feature share dropped 10 points over 3 quarters. Bug share doubled. If the trend continues, Q2 will look more like maintenance than product development.

Trend analysis

Drift is invisible. Until you chart it.

A single quarter might look fine. Three quarters in a row showing bug share creeping up is a signal you can't ignore. iftrue charts the mix quarter over quarter and flags changes above your threshold.

Use the trend to make the case for a debt sprint, a test coverage push, or a hiring plan. The numbers make the argument for you.

Outcomes

What this actually changes

Defend roadmap commitments

Show leadership that 60% of engineering is already on features, and more roadmap items need more headcount or fewer commitments.

Earn tech debt sprints

Point to the bug share creeping up and the debt work being squeezed out. The case writes itself.

Spot teams drowning

When one team's bug share is 2x the average, it's a capacity or quality problem, not laziness. Intervene before attrition.

Who it's for

Built for engineering leaders

Engineering Managers

Know if your team is actually shipping new value or stuck in bug-fix mode. Use real splits to argue for a tech debt sprint.

VPs of Engineering

Report to leadership where engineering effort is going. Spot teams drowning in maintenance before it turns into attrition.

Product Leaders

See how much of engineering time is going to product roadmap vs keeping the system alive. Calibrate roadmap expectations honestly.

Ready to transform your engineering organization?

Start your journey to data-driven engineering management. Book a demo to see how iftrue can help your team.