The 5 levels of communicating impact as an engineer

Perfect for performance reviews and resumes

Jul 06, 2025

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Since it’s the mid-year mark and many tech performance reviews are underway, I figured I’d switch things up from my recent AI article rhythm. To those who haven’t been interested in the AI articles, welcome back 🙂

This article provides a clear, actionable, and memorable framework for communicating your impact. The framework consists of 5 levels, and each level builds upon the previous one, showing how one bad example can be transformed into an amazing example by laddering up the communication levels.

At the end, I’ll share a Custom GPT tool that uses this framework to give you feedback on your impact statements.

the 5 levels of communicating your impact — The 5 levels summarized, read bottom to top.

Let’s jump into it!

Level 1: What you did

Level 1 is the baseline, but it’s also what you want to avoid solely using.

Here’s what this looks like:

❌ Migrated the user authentication system to use OAuth 2.0

In short, we only state the output rather than the outcome.

Output = what you did
Outcome = what the result was. The impact.

In this statement, leadership has no context for why your work matters. They’re left guessing: Was the old system broken? How did this help the team?

In performance reviews, you need to show both the technical accomplishment and the business impact. That brings us to the next level.

Level 2: Had business impact

Ok, so we know we need to communicate impact. Let’s give it a try:

⚠️ Level 2: Migrated the user authentication system to OAuth 2.0, significantly reducing login failures.

This is better since it mentions the login failure improvement, but it uses weasel words—in this case, “significantly.” The problem with them is that they’re not clear to the reader. Leadership knows there was a business impact, but it’s unclear by how much. Does significant mean 10%, 20%, 50%?

As someone who works in DevEx, which is notoriously hard to measure, I’m no stranger to this category. Sometimes you’re forced into it because you don’t have perfect metrics. So don’t feel bad if you have a few statements at this level—sometimes it’s the best you can work with.

However, if you do have specific numbers to use, that brings you to the next level.

Level 3: Specific impact

Let’s change our weasel word to a clear, specific impact:

✅ Level 3: Migrated the user authentication system to OAuth 2.0, reducing login failures by 40% (from 15% to 9%).

By switching from “significantly” to “by 40%,” the reduction becomes clearer and more specific. Now, leadership can visualize the impact, and if they’re aware of these metrics, they might already know how impressive that change is.

Another variant you can try here is specifying the impact first.

✅ Level 3: Reduced user login failures by 40% (from 15% to 9%) by migrating the authentication system to OAuth 2.0.

Choose based on what you want to highlight more. To highlight technical complexity more, start with the output. To highlight impact more, start with the outcome.

Level 3 is great because it gives clear, specific impact. But the problem is, it still doesn’t answer the “compared to what” question. We can throw around numbers that sound great in practice all day, but if your leadership doesn’t know how good the improvement is, it ultimately won’t mean much.

For example, how much better is a 2% improvement in latency compared to a 40% reduction in login failures? 🤷‍♂️ It’s not clear. That’s where level 4 comes in.

Level 4: Tied to goals

In addition to having a clear outcome like “reduced login failures by 40%,” you also explain how it’s connected to the original goal.

✅ Level 4: Reduced user login failures by 40% (from 15% to 9%) by migrating the authentication system to OAuth 2.0. This exceeded our Q2 reliability target by 2x, allowing us to focus on new user onboarding features a month ahead of schedule.

To help the reader contextualize that 40% improvement, you can include things like:

Did it provide better results than expected?
Did it account for a huge chunk of your team’s quarterly target?
Was it delivered ahead of schedule?

Showing how it connects to the original goals puts that metric in context.

When sharing a metric with leadership, it might be the first time they’re seeing it or the 50th metric they’ve seen that day. By comparing it to the goal, they recognize the improvement as exceptional, rather than just seeing it as a general positive.

Level 5: And dollars

The two fundamental things a business does are increase revenue and reduce cost. If you can directly tie your work to that, you’re communicating impact in the language executives speak.

This level ensures that you can associate a dollar amount or time saved with the actions you took.

Here’s our example at Level 5:

⭐ Level 5: Prevented an estimated $2.1M in annual revenue loss by reducing user login failures by 40% (from 15% to 9%) through migrating to OAuth 2.0. This exceeded our Q2 reliability target by 2x and eliminated 15 hours/week of support tickets, allowing the team to focus on new user onboarding features.

This impact statement is the highest level you can strive for. It has everything from all levels:

Level 1 - the output: Migrated to OAuth 2.0
Level 2 - the impact: Reduced user login failures
Level 3 - was specific: By 40%
Level 4 - and tied to goals: Exceeded the Q2 reliability target
Level 5 - and tied to dollars: Prevented $2.1M in annual revenue loss

The reader sees a direct link from your work to business outcomes that any executive can understand and appreciate.

Caveat: I’m using dollars, but you can use other top-line business metrics, like MAU (Monthly Active Users), and it will have a similar impact because leaders know these metrics in extreme detail.

I’ll quickly highlight this with a metric that’s too low-level:

❌ Don’t: Improved authentication token refresh rate from 2.3 seconds to 1.8 seconds, reducing cache misses by 12% in the user session management layer

Although this is specific, few business leaders will be able to make the connection to the metrics they care about.

Instead, you need to speak their language:

✅ Do: Improved MAU by 100k annually by optimizing our authentication token refresh rate from 2.3 seconds to 1.8 seconds.

Even if they don’t understand the second, more technical part, it doesn’t matter because you’ve connected it to what they care about—MAU.

🤖 Custom GPT

Now that you know all the communication levels, you can put it into practice by using this Custom GPT I made. Paste in any impact statements you have either from your self-review or resume, then see what level it’s currently at and how to get it closer to level 5. It looks like this:

If you’d like to see the underlying prompt, check it in my tech-gpt-prompts repo. Feel free to submit any contributions as well, and I’ll update the backing Custom GPT.

💡Important callout

Not every piece of work will reach Level 5, and that’s okay. The goal isn’t to artificially inflate your impact—it’s to communicate the real impact as clearly as possible.

If your work doesn’t directly tie to revenue, Level 3 or 4 might be your ceiling, and that’s perfectly fine. The key is being as specific as possible with the data you have.

Your performance review is your chance to tell the story of your impact. Don’t let great work get lost in translation. Make every point count.

📖 TL;DR

Here’s how the same piece of work looks at each level:

Level 1: Migrated the user authentication system to use OAuth 2.0
Level 2: Migrated the user authentication system to OAuth 2.0, significantly reducing login failures.
Level 3: Migrated the user authentication system to OAuth 2.0, reducing login failures by 40% (from 15% to 9%).
Level 4: Reduced user login failures by 40% (from 15% to 9%) by migrating the authentication system to OAuth 2.0. This exceeded our Q2 reliability target by 2x, allowing us to focus on new user onboarding features a month ahead of schedule.
Level 5: Prevented an estimated $2.1M in annual revenue loss by reducing user login failures by 40% (from 15% to 9%) by migrating to OAuth 2.0. This exceeded our Q2 reliability target by 2x and eliminated 15 hours/week of support tickets, allowing the team to focus on new user onboarding features.