Beyond Numbers: Measuring What Truly Matters

The Illusion of Metrics

You’ve probably felt it before—the frustration of being evaluated by numbers that barely scratch the surface. Lines of code, story points, deployment frequency… they sound objective, maybe even scientific, but here’s the reality: these numbers don’t measure your impact. They measure something else entirely.

Most of the metrics you’ve been asked to track—or that others may point to—were designed to evaluate systems, not individuals. Deployment frequency might indicate how efficiently features reach users. Story points might reveal velocity—but only if the entire team estimates consistently. Pin those metrics to one person, and fairness vanishes.

Even when a feature is “yours,” software is never built in isolation. Your work depends on other components, other people’s code, and the overall team process. Measuring a single individual in that environment with team-level metrics is like judging the performance of a single musician by the sound of the entire orchestra. It just doesn’t work.

84% Deploy Gen AI Use Cases in Under Six Months – Real-Time Web Access Makes the Difference

Your product is only as good as the data it’s built on. Outdated, blocked, or missing web sources force your team to fix infrastructure instead of delivering new features.

Bright Data connects your AI agents to public web data in real time with reliable APIs. That means you spend less time on maintenance and more time building. No more chasing after unexpected failures or mismatches your agents get the data they need, when they need it.

Teams using Bright Data consistently deliver stable and predictable products, accelerate feature development, and unlock new opportunities with continuous, unblocked web access.

Power Your AI

Here’s the subtle truth: metrics don’t exist in a vacuum. The wrong ones erode trust. Ask yourself: if someone is mentoring a junior teammate, designing system architecture, or coordinating a critical release, will lines of code or story points reflect that effort? Not at all. And when people sense that the system is unfair, their engagement and trust drop.

Tip: Start by identifying what truly matters. Not what is easy to measure, but what defines success for this role. Focus on outcomes, influence, and real-world impact. Let the numbers follow the story, not define it.

Avoiding the Traps of Bad Metrics

Here’s a trap that almost everyone falls into: metrics that encourage the wrong behaviors. Human nature is clever, and when incentives are attached to numbers, people optimize for the number itself—not the result.

Take Goodhart’s Law: “When a measure becomes a target, it ceases to be a good measure.” It’s as simple as it is true. Track the number of pull requests closed, and suddenly PRs might be rushed or trivial. Push code coverage metrics, and hours are spent writing tests that don’t improve quality. Track story points, and quantity may win over meaningful delivery.

Even seemingly innocent metrics can have cascading negative effects:

• Teams hit aggressive deadlines, but morale collapses and key talent leaves.

• Code coverage rises, yet the software remains fragile.

• More story points are completed, yet maintainability suffers and future delivery slows.

Tip: Before you adopt any metric, ask yourself: if someone optimizes for this, will it truly lead to the outcomes we care about? If the answer isn’t a clear “yes,” rethink it. Metrics should amplify the right behaviors, not create incentives that backfire.

A practical—and slightly humorous—example: the New York subway banned dogs unless they could fit in a bag. Clever humans found ways to exploit this rule, demonstrating creativity in gaming a system. People do the same with metrics. Expect it. Plan for it. And choose metrics that can’t be “gamed” at the expense of real outcomes.

Learn Piano Through the Music You Love

flowkey is the all-in-one piano app for players of any level. Start from scratch with step-by-step interactive courses or dive into the sheet music library. With over 1000 songs across all genres, you’ll always find something you love to play.

Start learning today

Evidence That Actually Counts

So, if lines of code, commits, or story points aren’t the answer, what is? Evidence of meaningful contribution doesn’t have to be numeric—it can, and often should, be richer, multi-dimensional, and deeply tied to outcomes.

Here’s how performance can be evaluated without relying solely on activity data:

• Project delivery: Are projects delivered on time? Evaluate by percentage of projects hitting forecasted deadlines, but also consider quality and scope.

• Collaboration: How satisfied are cross-functional partners with your contribution? Peer feedback matters.

• Quality and reliability: Are incidents, bugs, or customer complaints minimized? Operational stability is a signal of true performance.

• Business impact: Are the features or systems delivering meaningful value to users? Metrics like user adoption, usage frequency, and business outcomes matter far more than raw task output.

The principle here is simple: metrics are tools to measure impact, not proxies for effort. Focus on outcomes first, then use supporting data to understand why results are achieved—or why they are missed.

Tip: Break down job responsibilities into observable outcomes. Then map evidence sources for each. For example, mentoring junior teammates can be evaluated by the quality of their deliverables and feedback on their experience, not by how many code reviews you performed. Delivery speed matters, but only in the context of meaningful, high-quality output.

What 100K+ Engineers Read to Stay Ahead

Your GitHub stars won't save you if you're behind on tech trends.

That's why over 100K engineers read The Code to spot what's coming next.

• Get curated tech news, tools, and insights twice a week

• Learn about emerging trends you can leverage at work in just 10 mins

• Become the engineer who always knows what's next

Join 100k+ engineers

Aligning Metrics With Roles

Not all roles are equal, and the metrics should reflect that. Junior team members may have task-level responsibilities, so output-oriented metrics (like story completion) can be part of the picture. Senior contributors, however, should be evaluated on influence, strategy, and the quality of outcomes that ripple across the team or organization.

Take a senior engineer as an example:

• Their performance might be reflected in the quality of architectural decisions, reliability of systems, and success in mentoring others.

• Tracking individual commits or story points for this person is not just unhelpful—it can be misleading.

• Their work is about shaping systems, not logging activity.

In contrast, a junior engineer completing tasks within a well-defined system may be assessed more directly on output—but even then, the context and impact of those tasks matter.

Tip: Always tie metrics to the scope of responsibility. For more senior roles, focus on outcomes and systemic impact rather than individual outputs. Use team metrics only when the role explicitly involves improving system-level performance.

The Hard Work That Metrics Can’t Replace

Here’s the bottom line: no metric can replace the human side of performance management. Metrics are guidance, not judgment. Real evaluation comes from a combination of:

• Clear expectations

• Continuous feedback

• Active support for growth and learning

• Observation of real impact

It’s about building trust, creating clarity, and aligning efforts with meaningful outcomes. The goal isn’t to quantify every action, but to illuminate whether real value is being delivered.

Tip: Treat metrics as part of a broader evidence-based approach. Observe, gather feedback, and measure where it matters. Avoid shortcuts. Plan for unintended consequences. And always remember: outcomes, not output, tell the true story.

When approached this way, measurement becomes less about scrutiny and more about understanding, support, and impact. This is the “Audience of One” perspective in action—thinking about the person in front of you, their contribution, and their growth—not just the numbers they produce.

What’s your next spark? A new platform engineering skill? A bold pitch? A team ready to rise? Share your ideas or challenges at Tiny Big Spark. Let’s build your pyramid—together.

That’s it!

Keep innovating and stay inspired!

If you think your colleagues and friends would find this content valuable, we’d love it if you shared our newsletter with them!

PROMO CONTENT

Can email newsletters make money?

With the world becoming increasingly digital, this question will be on the minds of millions of people looking for new income streams in 2025.

The answer is—Absolutely!

That’s it for this episode!

Thank you for taking the time to read today’s email! Your support allows me to send out this newsletter for free every day. 

 What do you think for today’s episode? Please provide your feedback in the poll below.

Share the newsletter with your friends and colleagues if you find it valuable.

Disclaimer: The "Tiny Big Spark" newsletter is for informational and educational purposes only, not a substitute for professional advice, including financial, legal, medical, or technical. We strive for accuracy but make no guarantees about the completeness or reliability of the information provided. Any reliance on this information is at your own risk. The views expressed are those of the authors and do not reflect any organization's official position. This newsletter may link to external sites we don't control; we do not endorse their content. We are not liable for any losses or damages from using this information.