From Commits to Outcomes: A Healthier Way to Talk About Engineering Performance

Nearshore Software Development, Software Development

Written by: Monserrat Raya 

Engineering leader reviewing performance metrics and outcomes while working on a laptop

The Temptation of Simple Numbers

At some point, almost every engineering leader hears the same question. “How do you measure performance?” The moment is usually loaded. Year-end reviews are approaching. Promotions need justification. Leadership above wants clarity. Ideally, something simple. Something defensible. The easiest answer arrives quickly. Commits. Tickets closed. Velocity. Story points delivered. Hours logged. Everyone in the room knows these numbers are incomplete. Most people also know they are flawed. Still, they feel safe. They are visible. They fit neatly into spreadsheets. They create the impression of objectivity. And under pressure, impression often wins over accuracy. What starts as a convenience slowly hardens into a framework. Engineers begin to feel reduced to counters. Leaders find themselves defending metrics they do not fully believe in. Performance conversations shift from curiosity to self-protection. This is not because leaders are careless. It is because measuring performance is genuinely hard, and simplicity is tempting when stakes are high. The problem is not that activity metrics exist. The problem is when they become the conversation, instead of a small input into it.
Engineering leader reviewing performance metrics while working on a laptop
Engineering performance is often reduced to simple metrics, even when those numbers fail to reflect real impact.

Why Activity Metrics Feel Safe (But Aren’t)

Activity metrics persist for a reason. They offer relief in uncomfortable moments.

The Appeal of Activity Metrics

They feel safe because they are:

  • Visible. Everyone can see commits, tickets, and throughput.
  • Comparable. Numbers line up nicely across teams and individuals.
  • Low-friction. They reduce the need for nuanced judgment.
  • Defensible upward. Leaders can point to charts instead of narratives.

In organizations under pressure to “simplify” performance measurement, these traits are attractive. They create the sense that performance is being managed, not debated.

The Hidden Cost

The downside is subtle but significant.

Activity metrics measure motion, not contribution.

They tell you something happened, not whether it mattered. They capture effort, not impact. Over time, they reward visibility over value and busyness over effectiveness.

This is not a new insight. Even Harvard Business Review has repeatedly warned that performance metrics, when misapplied, distort behavior rather than clarify it, especially in knowledge work where output quality varies widely. When leaders rely too heavily on activity metrics, they gain short-term clarity and long-term confusion. The numbers go up, but understanding goes down.

The Behaviors These Metrics Actually Create

Metrics do more than measure performance. They shape it. Once activity metrics become meaningful for evaluation, engineers adapt. Not maliciously. Rationally.
What Optimizing for Activity Looks Like
Over time, teams begin to exhibit familiar patterns:
  • More commits, smaller commits, noisier repositories
  • Work sliced unnaturally thin to increase visible throughput
  • Preference for tasks that show progress quickly
  • Reluctance to take on deep, ambiguous, or preventative work
Refactoring, mentoring, documentation, and incident prevention suffer first. These activities are critical to long-term outcomes, but they rarely show up cleanly in dashboards. Engineers notice. Quietly. They learn which work is valued and which work is invisible. The system teaches them what “good performance” looks like, regardless of what leaders say out loud. This is where trust begins to erode. When engineers feel evaluated on metrics that misrepresent their contribution, performance conversations become defensive. Leaders lose credibility, not because they lack intent, but because the measurement system feels disconnected from reality. Metrics do not just observe behavior. They incentivize it.
Software engineer reviewing activity metrics such as commits, tickets, and velocity on a laptop
Activity metrics create a sense of control and clarity, but they often measure motion instead of meaningful contribution.

What “Outcomes” Actually Mean in Engineering

At this point, many leaders nod and say, “We should focus on outcomes instead.” That phrase sounds right, but it often remains vague. Outcomes are not abstract aspirations. They are concrete, observable effects over time.
Outcomes, Grounded in Reality
In engineering, outcomes often show up as:
  • Improved reliability, fewer incidents, faster recovery when things break
  • Predictable delivery, with fewer last-minute surprises
  • Systems that are easier to change six months later, not harder
  • Teams that unblock others, not just ship their own backlog
  • Reduced cognitive load, making good decisions easier under pressure
None of these map cleanly to a single number. That is precisely the point. Outcomes require interpretation. They demand context. They force leaders to engage with the work, not just the artifacts of it. This does not make performance measurement weaker. It makes it more honest.

Using Metrics as Inputs, Not Verdicts

This is the heart of healthier performance conversations.
Metrics are not the enemy. Treating them as verdicts is.

Where Metrics Actually Help

Used well, metrics act as signals. They prompt questions rather than answer them.

A drop in commits might indicate:

  • Work moved into deeper problem-solving
  • Increased review or mentoring responsibility
  • Hidden bottlenecks or external dependencies

A spike in throughput might signal:

  • Healthy momentum
  • Superficial work being prioritized
  • Short-term optimization at long-term cost

Strong leaders do not outsource judgment to dashboards. They use data to guide inquiry, not to end discussion.

This approach aligns with how Scio frames trust and collaboration in distributed environments. In Building Trust Across Screens: Human Capital Insights from Nearshore Software Culture, performance is treated as something understood through patterns and relationships, not isolated metrics.
Removing judgment from performance reviews does not make them fairer. It makes them emptier.

Where Activity Metrics Fall Short (and What Outcomes Reveal)

Activity vs Outcome Signals in Practice
What’s Measured
What It Tells You
What It Misses
Number of commits Level of visible activity Quality, complexity, or downstream impact
Tickets closed Throughput over time Whether the right problems were solved
Velocity / story points Short-term delivery pace Sustainability and hidden trade-offs
Hours logged Time spent Effectiveness of decisions
Fewer incidents Surface stability Preventative work that avoided incidents
Easier future changes System health Individual heroics that masked fragility
This table is not an argument to discard metrics. It is a reminder that activity and outcomes answer different questions. Confusing them leads to confident conclusions built on partial truth.

How Experienced Leaders Run Performance Conversations

Leaders who have run reviews for years tend to converge on similar practices, not because they follow a framework, but because experience teaches them what breaks.
What Changes with Experience
Seasoned engineering leaders tend to:
  • Look at patterns over time, not snapshots
  • Ask “what changed?” instead of “how much did you produce?”
  • Consider constraints and trade-offs, not just results
  • Value work that prevented problems, even when nothing “happened”
These conversations take longer. They require trust. They cannot be fully automated. They also produce better outcomes. Engineers leave these discussions feeling seen, even when feedback is hard. Leaders leave with a clearer understanding of impact, not just activity. This perspective often emerges after leaders see how much performance is shaped by communication quality, not just individual output. In How I Learned the Importance of Communication and Collaboration in Software Projects, Scio explores how delivery outcomes improve when expectations, feedback, and ownership are clearly shared across teams. That same clarity is what makes performance conversations more accurate and less adversarial.
Software engineers collaborating while reviewing code and discussing engineering outcomes
Engineering outcomes focus on reliability, predictability, and long-term system health rather than short-term output.

Why This Matters More Than Fairness

Most debates about performance metrics eventually land on fairness. Fairness matters. But it is not the highest stake.
The Real Cost of Shallow Measurement
When performance systems feel disconnected from reality:
  • Trust erodes quietly
  • Engineers disengage without drama
  • High performers stop investing emotionally
  • The best people leave without making noise
This is not a tooling problem. It is a leadership problem. Healthy measurement systems are retention systems. They signal what the organization values, even more than compensation does. Scio partners with engineering leaders who care about outcomes over optics. By embedding high-performing nearshore teams that integrate into existing ownership models and decision-making processes, Scio helps leaders focus on real impact instead of superficial productivity signals. This is not about control. It is about clarity.

Measure to Learn, Not to Control

The goal of performance measurement is not to rank engineers. It is to understand impact. Activity is easy to count. Outcomes require judgment. Judgment requires leadership. When organizations choose outcomes-first thinking, performance conversations become less defensive and more constructive. Alignment improves. Trust deepens. Teams optimize for results that matter, not numbers that impress. Measuring well takes more effort. It also builds stronger teams.

FAQ: Engineering Performance Measurement

  • Because they are easy to collect, easy to compare, and easy to defend from an administrative standpoint. However, they often fail to reflect real impact because they prioritize volume over value.

  • No. Metrics are valuable inputs, but they should serve as conversation starters that prompt questions rather than as final judgments. Context is always required to understand what the numbers actually represent.

  • The primary risk is eroding trust. When engineers feel that their contributions are misunderstood or oversimplified by flawed metrics, engagement drops, morale fades, and talent retention suffers significantly.

  • They align evaluation with real impact, encourage healthier collaboration behavior, and support the long-term health of both the system and the team by rewarding quality and architectural integrity.