So you’re trying to figure out if GitHub Copilot is worth it? Join the club. I’ve been down this rabbit hole for the past few months, and honestly, it’s messier than the vendor slides suggest.

Here’s the thing - everyone wants that magic number. “Copilot will make your developers X% more productive!” But after digging through actual data from teams using it (and yeah, running our own experiments), the reality is… complicated.

What We Actually Track

Let’s start with what people think they should measure. Active users, acceptance rates, blah blah. Sure, track those. But here’s what nobody tells you - acceptance rate varies WILDLY. One day it’s 35%, next week it’s 15%. Why? Who knows. Maybe developers are working on legacy code that week. Maybe they’re just cranky.

We found these metrics somewhat useful:

  • How many devs actually use it regularly (spoiler: it’s never 100%)
  • What percentage of suggestions they accept
  • Developer surveys - but take these with a grain of salt

The surveys are interesting though. Developers feel more productive. They say stuff like “I can focus on the interesting problems now” or “it handles the boring boilerplate.” But feelings aren’t data, right?

The Productivity Question

OK so here’s where it gets tricky. How do you measure productivity anyway? Lines of code? Please. Story points? Those are already made up numbers.

We tried looking at:

  • How long tasks take (but tasks are never apples-to-apples)
  • PR velocity (somewhat useful)
  • Number of tickets closed (meh)

The GitHub studies claim 55% faster task completion. Microsoft/MIT found 26% productivity gains. Our experience? Somewhere between “it depends” and “¯_(ツ)_/¯”

Junior developers seem to love it. Senior developers… mixed bag. One senior dev told me: “It’s great for the tedious stuff, but half the time I spend more time fixing its suggestions than I would’ve spent writing it myself.”

Real World Headaches

Nobody talks about the downsides enough. Here’s what we’ve seen:

  1. Code quality concerns - more code churn, more copy-paste patterns showing up
  2. Security reviews take longer because you’re not sure what the AI pulled from where
  3. Some devs lean on it too much and their problem-solving skills get rusty

And measuring this stuff? Good luck. We tried tracking “escaped defects” and build failure rates, but there’s so much noise in that data.

What Actually Matters

After all this analysis paralysis, here’s my take: stop trying to measure everything. Focus on a few things:

First, are your developers happier? Seriously. Run a survey. If they’re less frustrated and enjoying their work more, that’s worth something.

Second, look at your overall delivery metrics - but give it TIME. Like 3-6 months. You can’t judge this in a sprint or two.

Third, consider the cost. At $19-39/month per developer (depending on your plan), you need to see some improvement to justify it. Do the napkin math - if a dev saves even 2 hours a month, you’re probably breaking even.

My Approach (YMMV)

We ended up with this rough framework:

Phase 1: Just Try It

  • Get licenses for volunteers
  • Track basic usage
  • Collect feedback (formal and water cooler chat)

Phase 2: Expand Carefully

  • Roll out to teams that showed interest
  • Start tracking team-level metrics
  • Watch for any red flags in code quality

Phase 3: Make a Decision

  • Compare metrics, but don’t obsess over them
  • Survey everyone - anonymously
  • Make the call based on the full picture

Tools and Dashboards

People always ask about tooling. We use the GitHub Copilot dashboard (it’s… fine) and pump some data into Power BI. But honestly? The most valuable insights come from 1-on-1s with developers.

If you must build dashboards:

  • Copilot usage trends
  • Team-level adoption
  • Maybe PR metrics if you trust them

But remember - dashboards don’t capture “Jim spent 30 minutes debugging Copilot’s weird suggestion” or “Sarah used Copilot to learn a new framework faster.”

Bottom Line

Is Copilot worth it? For us… probably? Most devs want to keep using it. Productivity gains are real but hard to quantify precisely. The ROI calculation is fuzzy at best.

My advice: Run a pilot. Keep it simple. Listen to your developers more than your metrics. And don’t expect miracles - it’s a tool, not magic.

Oh, and one more thing - if someone promises you exact productivity percentages or ROI calculations, they’re probably selling something. Real world is messier than that.