Overview
In this episode of The Dashboard Effect, Brick Thompson and Landon Oaks make a distinction that should sit at the foundation of every dashboard project: the difference between metrics that look good and metrics that do something. Vanity metrics are easy to collect and easy to report, but they rarely change how anyone acts. The episode is a practical guide to building measurement frameworks that connect directly to business outcomes and give the people responsible for those outcomes something they can actually use.
The conversation is relevant for any team that has found itself tracking numbers without being able to draw a clear line between those numbers and better decisions. See how Blue Margin’s Managed Analytics & Insights applies this outcome-first approach to every dashboard engagement, ensuring that what gets built measures what matters rather than what is easy to measure.
What This Episode Covers
Aligning with Business Goals (0:39 – 1:05)
The right starting point for any dashboard project is not the data. It is the business problem. Brick and Landon are direct about this: tracking arbitrary numbers because they are available produces reports that no one acts on. Starting with a specific problem and working backward to the metrics that illuminate it produces tools that actually get used.
Involving Stakeholders (1:55 – 2:33)
Effective dashboards require input from two directions. Leadership understands the strategic goals. Frontline employees understand the day-to-day realities that the data needs to reflect. Dashboards built without both perspectives tend to measure what is easy to measure rather than what is meaningful to the people doing the work.
Focusing on Root Causes (2:40 – 3:57)
Results metrics tell you what happened. Root cause metrics tell you why, and more importantly, they give employees something to act on when the numbers move in the wrong direction. The hosts make the case for building dashboards that trace performance back to its drivers rather than simply reporting outcomes after the fact.
The Power of Iteration (3:58 – 4:52, 6:08 – 7:35)
Waiting for a perfect dashboard before launching anything is a reliable way to delay value indefinitely. Brick and Landon advocate for shipping a minimum viable product quickly, testing whether it changes how people think and act, and iterating from there based on real feedback. The goal is a tool that improves continuously, not one that arrives fully formed.
Who It’s For
This episode is worth your time if you are a business leader or operator who suspects your current reporting is not actually influencing decisions, a BI or data professional trying to build dashboards that get used rather than ignored, a team lead who wants a framework for distinguishing metrics that matter from metrics that just fill space, or anyone starting a dashboard project and looking for a principled way to decide what to measure before writing a single query.
Why It’s Worth a Listen
The vanity metrics problem is pervasive, and it persists largely because the alternative requires more upfront clarity about what a business is actually trying to accomplish. This episode provides that clarity in a format that is easy to apply, moving from the strategic question of what problem you are trying to solve all the way through to the practical mechanics of how to iterate toward something useful.
The emphasis on root cause metrics is the most actionable part of the conversation. There is a meaningful difference between a dashboard that tells a manager their numbers are down and one that points to the specific driver they can address to change that. Building for the second outcome requires more thinking at the design stage, and this episode makes a clear case for why that thinking is worth doing before the first chart is built.
For teams that have delivered dashboards that did not stick, this episode is a useful retrospective tool. The answer is usually somewhere in the gap between what the data team thought the business needed and what the people using the tool actually needed to do their jobs.
