Do you use your dashboards?

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Do you really use your dashboards? - by Benedikt Kantus

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Do you really use your dashboards?<br>Most product teams ignore their dashboards when making real decisions. It's time to build metrics that actually matter.

Benedikt Kantus<br>Jun 09, 2026

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When was the last time your product metrics dashboard actually changed a decision you made? If you’re struggling to remember, you’re not alone.<br>I’ve observed across so many product teams that we spend hours building dashboards that look impressive in quarterly reviews, but when it comes to real decisions, we ignore them completely. Why? Because most dashboards are designed to make us look good rather than help us think clearly.<br>The problem: Dashboard Theater

We’ve created a culture where dashboards serve as performance art instead of decision-making tools. In practice, this looks like this:<br>Metrics selected because they trend upward, not because they reveal truth

Lagging indicators presented as if they predict the future

Zero connection between what the dashboard shows and what we decide daily

Carefully chosen timeframes that conveniently hide declining trends

Aggregated data that masks critical problems in specific segments

Vanity metrics that feel good but drive no action

Our actual decision are based on other input

Meanwhile, our actual decisions come from completely different sources. This might be a panicked Slack or Teams message about a customer threatening to churn, anecdotal feedback from sales calls that never makes it into data, the CEO’s gut reaction to a competitor’s product launch an engineer’s warning about technical debt slowing everything down, or a support ticket that reveals a pattern nobody tracked. But all these inputs are not shown in the dashboard. In fact, you don’t use your metrics for decision making, just for showing off.<br>(Continued below)

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The solution: Build for discomfort

Effective dashboards don’t celebrate success. They surface problems and trends early. To build one that actually matters, consider the following:<br>Start with the decisions you need to make, then identify metrics that inform them

Use the same standard metrics for all features to avoid selective bias (e.g. Feature Adoption, process runtime, Task Success Rate)

Include leading indicators that warn you before things go wrong

Display trends over time, not just today’s snapshot

Make bad news visible and impossible to ignore

In a presentation: Add context that explains why numbers moved, not just that they moved

Review it weekly, not just during quarterly presentations

It’s not going to be easy

Building a dashboard that surfaces problems creates its own difficulties. Leadership might push back when metrics suddenly look worse because you’re tracking reality instead of vanity. Stakeholders accustomed to good news may question your competence when the dashboard shows red flags. Your team might feel demoralized seeing problems highlighted daily or weekly. There’s also the risk of analysis paralysis: When every metric screams for attention, which fire do you fight first? And maintaining a truly useful dashboard requires constant refinement as your product and business evolve, which takes time.<br>But still, it’s better to have a honest dashboard that is useful than a dashboard full of vanity metrics that nobody uses for decision making. The best product teams have dashboards that create productive tension. If yours always makes you feel comfortable, it’s probably not doing its job.

What I Read

As usual, I will list some of the best articles I read on the Internet. I will keep a list of the best articles (currently >900) at https://www.digital-product-management.com. These are today’s picks:<br>Product Leadership Operating System: Shifting From Reactive Execution to Proactive Product Leadership<br>Therapy Tax: When Your 1:1s Feel Like Therapy: How product leaders can transition from absorbing chaos to building capability during one-on-one meetings.<br>Management In The Age Of AI: AI tools redefine management responsibilities, focusing on technical fluency, increased output expectations, and budget management.

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