Stop Building Dashboards for Managers (and Start Solving Real Problems)

I spent three weeks building a comprehensive team metrics dashboard last year. Thirty days of work. Beautiful visualizations, real-time updates, every metric I thought leadership could possibly want. My manager opened it once. Never asked about it again.

That was the moment I realized I'd been solving the wrong problem entirely. I was so focused on displaying information that I never stopped to ask what decisions anyone actually needed to make with it. The dashboard looked impressive in retrospectives. It changed nothing about how we worked.

When I read that piece about engineering insights versus dashboards, it hit different because I've lived it from both sides—as a developer building monitoring tools and as someone frustrated by the metrics theater that happens when you conflate "data visibility" with "actual understanding."

The Dashboard Trap I Keep Falling Into

Here's the thing about dashboards: they're seductive. They feel productive. You get to choose colors, organize data hierarchies, build charts. There's measurable progress—you literally shipped something visual. But then you realize the person who asked for it isn't actually looking at it regularly.

Why? Because a dashboard is passive. It's a museum you walk through. An insight is active—it interrupts you and says "this matters right now." When my deployment frequency dropped 35% week-over-week, I don't need a red line on a graph. I need someone flagging that as a problem worth investigating immediately.

The cognitive load is the real issue. An engineering manager already has hundreds of tabs open, dozens of Slack channels, and pull requests waiting. A new dashboard just becomes another thing that might be important, competing for attention with everything else.

What Actually Changed My Thinking

I started noticing patterns in production incidents at work. We'd debug something catastrophic, and I'd think "this should have been caught." But it wasn't caught by our dashboards—it was caught by someone manually digging through logs who happened to notice something weird.

That's backwards. The system should work the opposite way: anomalies should find you, not the other way around. Pull requests sitting in review for three days without comment? Flag it. Repository accumulating critical security issues nobody's addressing? Alert. Deployment velocity trending down? Investigate.

The distinction is so simple once you see it, but it changes everything about how you design monitoring and metrics infrastructure.

The Question That Matters

Instead of asking "what metrics should we display?", ask "what decisions does this person need to make?" A completely different set of problems emerges.

For an engineering manager, those decisions usually look like:

• Where are we bottlenecked right now?
• Which team or project needs help?
• Are we moving faster or slower?
• What's creating friction in our development process?

Notice how these aren't "vanity metrics" about who wrote the most code. They're about system health and team momentum. Your dashboard should surface exactly what's needed to answer those questions, nothing more.

My Implementation Take

In practice, this means I've stopped building generic metrics surfaces and started thinking about automated decision support. When I helped rebuild our deployment monitoring, we ditched the graph of "deployments per week" and instead built a system that:

• Flags when deployment frequency drops outside normal variance (with context)
• Identifies which services have increased failure rates
• Surfaces which teams are blocked on infrastructure issues
• Highlights when code review cycle time gets longer than it should be

Each of these is actionable. A manager can read the summary in 90 seconds and know exactly where to focus their energy.

What I'd Push Back On

That said, I don't think dashboards are entirely wrong. Sometimes you need to explore data ad-hoc, to ask questions you didn't anticipate. But that's different from a manager's daily view. That's different from what's presented as "the state of engineering."

My concern is that teams often build a robust alert system and then pile dashboards on top, doubling down on passive visibility. If your alerts are working, your dashboard becomes noise.

The Question I'm Still Sitting With

How do you surface insights without becoming another system to check? That's the hard part that I haven't fully solved. Slack notifications? Email? Embedded in the PR interface? Different for different orgs, probably.

What's your experience? Have you seen insights-driven approaches actually change how engineering teams work, or does this feel like another layer of complexity?

Source: This post was inspired by "Engineering Managers Don't Need More Dashboards. They Need Better Insights." by Dev.to. Read the original article