Metric Trees As A Way To Align Mental Models

Enabling the organization to self-serve data without a shared model of business inputs and outputs will only result in numerous datasets, disconnected dashboards and perpetual confusion.

Earlier in my career, I was one of a handful of leaders who had a strong mental model of how the business operated. It  was second nature for me to anchor discussions of business performance around this constantly evolving mental model of input levers and desired outcomes.

However, as the organization scaled, and teams devolved into their work streams and silos, this clarity wasn’t shared across the board.

So in practice, teams navigated folders of datasets and charts, but the connections between those datasets were not as visible, and as a result, the ability to link their work to the underlying business processes and outputs was obscured.

It’s not enough to enable self-serve data or provide access to dashboards; we need to be intentional about sharing and aligning on the mental models behind the data.

That’s where frameworks like metric trees come in—they offer a way to capture and share these business models in an accessible and structured format.

By explicitly modeling how key metrics are related to one another—through input and output dependencies—we can create a shared framework that everyone can engage with.

It’s a structure that reflects the real dynamics of the business, and more importantly, it allows anyone in the organization to trace metrics back to their roots and see how changes in their areas will impact the broader business.

In essence, metric trees provide a common language for understanding the business, ensuring everyone from the C-suite to operational teams can work from the same playbook.

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