If your dashboards still look the same as they did two years ago, there’s a good chance they’re not telling you what you need to know.
In a time when expectations have shifted from “grow at all costs” to efficient growth, the pressure on engineering leadership has changed, too. Output still matters, but not without context. Velocity means little without alignment. And shipping fast doesn’t help if the wrong things are going out the door.
At Distillery, we work closely with engineering teams navigating this exact shift. Here are five performance metrics we see the most progressive teams rethinking in 2025.
1. Time to Value (TTV)
You’re likely tracking delivery time. But how often are you tracking how long it takes users, or customers, to experience value from what your team built?
Time to Value isn’t just a product metric. It’s a signal of alignment between engineering and business. When TTV is high, it usually points to friction: confusing onboarding, fragmented data, unclear UX, or tech that’s out of sync with user needs.
Teams that actively measure TTV are often faster at recognizing scope creep, deprioritizing low-impact work, and validating their roadmap.
See how Distillery helps tech teams shorten the path to meaningful outcomes.
2. Adoption > Activation
Signups and feature clicks may look good on a dashboard, but they’re rarely indicators of real engagement. For engineering teams, the signal isn’t whether a feature gets launched or tried, it’s whether it becomes part of someone’s workflow.
High activation but low adoption often points to a delivery pipeline that’s out of sync with actual usage patterns. This can waste bandwidth, especially in orgs where PM and engineering are measured on delivery over impact.
The teams that catch this early are the ones looking beyond the “launch moment” and into consistent, retained usage.
Amplitude offers a sharp breakdown on vanity vs actionable metrics.
3. Throughput – With Better Questions
You probably already track DORA metrics: lead time, deployment frequency, change failure rate, MTTR. Most teams do. The gap isn’t in knowing what to track, it’s in how those metrics are interpreted.
- What does an improving lead time actually mean?
- If deployment frequency is up but failure rate is too, where’s the real issue – QA, culture, expectations?
- Are we measuring team speed or system health?
The engineering orgs seeing the most value from DORA aren’t just reporting on them. They’re using them to open up strategic conversations, especially around process friction, dependencies, and rework.
Atlassian’s overview of DORA remains a good reference.
4. Customer Retention Cost (CRC)
If your engineering team is shipping features meant to improve retention, this metric matters more than it might seem.
CRC captures the full cost of keeping a customer engaged – product development, support, technical infrastructure, and everything in between. When CRC rises, it may signal that engineering is spending too much time on reactive work instead of strategic improvements.
Engineering can, and should, be part of this conversation. Especially in orgs where support load, feature requests, and product stability directly impact retention.
Here’s how CRC is evolving as a key performance indicator.
5. Team Health and Productivity
Burnout isn’t always visible. And traditional productivity metrics often miss the root causes – context switching, vague priorities, poor cross-team alignment.
Leading teams are starting to track operational friction more deliberately:
- How often are engineers pulled off sprint work for unplanned tasks?
- What percentage of work ties to strategic goals vs. backlog clean-up?
- Are experienced team members mentoring or just plugging leaks?
Productivity is still important, but so is sustainability. And teams that aren’t watching for early signs of burnout usually find out about it too late.
Five Questions Worth Asking
To pressure-test your own metrics strategy, try these in your next leadership sync:
- Which of our metrics are actively influencing decisions, and which ones are just reported?
- Are we tracking speed more than value?
- What’s the signal behind the data we’re collecting?
- Where are we over-instrumented and under-informed?
- If a key metric disappeared from our dashboards tomorrow, would it change anything we’re doing?
Closing Thought
As engineering leaders, the question isn’t whether we measure performance; it’s what story our metrics are telling us. And whether we trust it.
At Distillery, we partner with engineering and product teams to build high-performing platforms and teams – helping organizations improve delivery, increase visibility across initiatives, and align technical work with business goals.
Let’s discuss how we’ve helped product and engineering teams shorten TTV, improve adoption, and scale delivery.