Stop Looking at Flat Dashboards

​Dear Reader,​

Jeff Patton explained why flat backlogs don’t work for prioritizing user stories more than 16 years ago:

I believe the same issue occurs from putting metrics on a flat dashboard:

Evaluating the month-over-month changes in metrics like registrations or bookings in isolation doesn’t help teams and stakeholders understand their contribution to business goals and how their work influences leading indicators.

Just as user story mapping provides context by linking User Stories to User Activities, linking metrics to a team’s output and business goals provides context for evaluating progress:

Three things determine the context of a metric:

• What activities or other metrics have influenced it as directly as possible?
• What other closely linked metrics does it influence?
• How has it changed in a recent cadence, and what effects has this change created?

One of my biggest frustrations is the lack of context whenever I meet teams that are asked to report metrics through flat dashboards. These organizations play the reporting game rather than focusing on steering.

Imagine a SaaS company tracking Signup Conversion Rate as a key engagement metric on a dashboard.

📈 The Signup Conversion Rate jumped from 5% to 8% this month. The dashboard shows a healthy trend, and leadership is thrilled—more users are completing signups as a percentage of those who start!

What’s Actually Happening (Leading Indicators)

🔍 Signups Started dropped from 10,000 to 5,000 (-50%).

🔍 Signups Completed dropped from 500 to 400 (-20%).

Even though the conversion rate increased, the number of completed signups decreased. The improvement is misleading because it’s based on a shrinking pool of users, not better engagement.

What Caused This? (Output)

💡 The team added a mandatory credit card field during signup to reduce spam accounts. While this filtered out low-quality signups, it also deterred real potential users from even starting the process.

Upstream Impact on North Star Metric & Business Goals

📉 North Star Metric: Active Teams Using Core Features—The number of teams actively using the product stagnates because fewer users make it through the signup and start experiencing real value.

📉 Business Goals: Expansion Revenue—With fewer teams adopting the product, there are fewer opportunities for account expansion (e.g., upgrading to higher tiers, adding more seats).

Consider using contextual metrics tools like DoubleLoop or Vistaly to shift from flat dashboard to metrics views with context.

Of course, OKRs traditionally also represent metrics only in a flat layout. But that’s why I’m arguing that metrics trees should be a vital input to OKR drafting: so that teams can choose and argue for metrics that matter in their context based on their relationship to upstream business goals and downstream user behaviors and Outputs.

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Thank you for Practicing Product,

​Tim​

Gespräche über Produktmanagement

Ich durfte mit meinem geschätzten Fast-Ex-Kollegen Jan Hoppe in seinem Produktkraft-Podcast einen unterhaltsamen Austausch über den sinnvollen Einsatz von Methoden führen (zur Abwechslung mal auf Deutsch).

Content I found Practical This Week

OKR vs KPI: What's the Difference? Read it here

Who is Tim Herbig?

As a Product Management Coach, I guide Product Teams to measure the real progress of their evidence-informed decisions.

I focus on better practices to connect the dots of Product Strategy, Product OKRs, and Product Discovery.