In my experience leading engineering teams, I’ve found that the hardest part of OKRs isn’t setting them — it’s making sure they actually mean something.
Too many teams set OKRs like "refactor the admin panel" or "increase test coverage" without asking the bigger question:
What business outcome are we trying to enable?
This post introduces a simple, powerful framework I use to ensure every engineering OKR ladders up to something that matters — whether that’s profitability, product reliability, user experience, or operational efficiency.
🎯 Why This Framework Exists
Most engineering leaders know we should align our work to business goals. But how do you translate something like “reduce churn” or “increase CVR” into backend initiatives or platform improvements?
The answer: start with engineering fundamentals that map cleanly to business impact, not just project deliverables.
This framework helps me to align the tech metrics with the business metrics:
- Prioritize what to build and what to cut
- Make trade-offs explicit (not accidental)
- Hold teams accountable with metrics that matter
🔺 The “Project Management Triangle” and Why It Still Matters
You’ve probably heard the saying:
“You can have it fast, cheap, or good — pick two.”
This idea is rooted in what’s known academically as the Project Management Triangle, sometimes called the Iron Triangle or informally the Golden Triangle.
It describes the fundamental trade-offs in any technical decision:
| Constraint | Engineering Focus | Example |
|---|---|---|
| Speed | Delivery & time-to-market | Lead time, sprint velocity |
| Quality | Bug prevention, testability, stability | Defect rates, incident count |
| Cost | Infra and labor efficiency | Infra cost, developer utilization |
No matter the size of the org, these tensions always exist, and the C-Level mostly only care about this triangle. And the best engineering OKRs don’t ignore them — they make them visible and intentional.
🧠 What the Experts Say (And Why I Take It Seriously)
This framework is inspired by some of the best minds in software engineering and DevOps.
📘 The Mythical Man-Month — Frederick Brooks
“Adding manpower to a late software project makes it later.”
Brooks explains how rushing projects often leads to even more delays and coordination overhead. A powerful reminder that quality and speed are not linearly scalable.
⚙️ Continuous Delivery — Jez Humble & David Farley
“If it hurts, do it more often.”
This quote refers to things like testing, deployment, and integration. The more painful a process is, the more it needs to be automated, so quality doesn’t degrade as you scale speed.
📈 Accelerate — Nicole Forsgren, Jez Humble, Gene Kim
“High performers deploy more frequently, recover faster, and are more stable.”
This book backs everything with data. The takeaway? You don’t have to trade speed for quality — high-performing teams achieve both.
✅ ISO/IEC 25010:2011
This global standard defines what "software quality" actually means, beyond just bugs. It includes:
- Reliability
- Maintainability
- Performance efficiency
- Functional suitability
These ideas directly inspired the six dimensions below.
🧱 The 7 Dimensions of Tech Performance
Every good engineering OKR I’ve seen (or set) can be mapped to one or more of the following seven dimensions. These are the technical levers that actually move the business — across speed, reliability, cost, and growth-readiness.
| Dimension | What It Measures | Example Metrics |
|---|---|---|
| 1. Delivery | How fast and predictably we ship value | Lead time, deployment frequency, sprint velocity |
| 2. Quality | How well we avoid defects and rework | Defect rate, escaped bugs, test coverage |
| 3. Availability | Whether the system is up when users need it | Uptime %, MTTR, alerting coverage |
| 4. Reliability | Whether the system behaves as expected under normal use | API P95 latency, crash-free sessions |
| 5. Maintainability | How easily the system can evolve without breaking | PR cycle time, SonarQube score, legacy deprecation progress |
| 6. Cost Efficiency | How efficiently we use compute and human resources | Infra cost/session, cloud bill reduction, manual hour savings |
| 7. Scalability | How well the system performs as usage or data grows | Throughput under load, autoscaling behavior, resource saturation thresholds |
🧠 Pro tip: Every OKR should align to at least two of these dimensions. One is not enough.
🧭 Aligning to Business Impact (Without Internal Jargon)
Instead of exposing internal OKRs, I prefer to frame impact areas like this:
- 🔄 Improving system stability for user-facing products
- 📈 Supporting growth experiments by speeding up delivery
- 💰 Reducing cloud infrastructure and operational costs
- 🔧 Eliminating manual work through better tooling
- 🧪 Improving data quality to make analytics more trustworthy
These themes are universally valuable, whether you’re in a startup or scaling enterprise.
So, when I review OKRs, I ask:
Does this actually improve one of those outcomes?
If not, it's probably technical debt disguised as a priority.
🧠 Example OKRs Using This Framework
Here’s what this looks like in practice
🚀 Improve Admin Dashboard Quality
| Objective | Sunset legacy platform and reduce manual issues |
|---|---|
| KR 1 | Avoid security issues, migrate 100% of Legacy admin dashboard to the new code base |
| KR 2 | Improve Sentry Perf score page XXX in the admin dashboard by 90% |
📌 Dimensions: Maintainability, Reliability, Quality
💸 Infra Cost Optimization
| Objective | Reduce infrastructure cost and latency API |
|---|---|
| KR 1 | Reduce Database reads by 60% |
| KR 2 | Keep P95 check-in latency ≤ 500ms |
📌 Dimensions: Cost Efficiency, Reliability
🔁 How I Operationalize This
Use this framework not just for OKR planning, but for ongoing decision-making:
- During planning: Tag each draft OKR with the dimensions it targets
- During reviews: Check if any key business outcomes are neglected
- During sprints: Map Jira stories to the OKRs and dimensions
Tools that you can use:
- Jira, Google sheet (delivery & velocity)
- APM like Sentry or New Relic (monitoring and error tracking)
- Static code analysis, SonarQube (maintainability)
- GCP/AWS billing menu for cost reports
- Team WIKI, you can use Confluence or Notion (shared visibility)
🔚 Final Thoughts
You don’t need 20 OKRs to show impact. You need fewer, smarter, well-targeted ones.
This framework — based on engineering theory, real-world use case, and business alignment — helps me set OKRs that do more than just tick boxes.
- They guide teams.
- They inform trade-offs.
- They create leverage.
Let’s stop writing OKRs that “sound good” or are not correlated with business impacts, let's start writing ones that move the needle — for real.
📩 If this resonates with you, I’d love to hear how you design OKRs in your tech org — drop a comment or message me.
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