Strategic Metrics and Levers
Be explicit about your strategic metrics and levers. Build metric trees that make cause-and-effect relationships visible, distinguish input from output metrics, state a hypothesis for each relationship, and refine the model as evidence arrives.
Most companies have plenty of metrics and no model. Numbers are tracked, dashboards proliferate, but nobody has drawn how they connect, which input drives which output, which lever actually moves the result you care about. Strategic metrics and levers is the discipline of drawing that map: making the causal structure of the business explicit so that choosing a Key Result becomes a reasoned act rather than a guess about what happens to be countable.
Build the metric tree
A metric tree arranges measures by cause and effect: a north-star outcome at the top, the drivers that feed it below, and the inputs that feed those, down to numbers a team can actually move this week. Drawing it does two things. It reveals leverage, showing which inputs have the biggest effect on the outcome, so you focus effort where it counts. And it exposes assumptions, because every branch is a claim, "we believe improving this input moves that output", which can now be stated, tested and corrected.
Input versus output metrics
The distinction that matters most is input versus output metrics. An output metric measures the result you want (revenue, retention, activation); an input metric measures something you can directly influence that you believe drives it (demos booked, onboarding steps completed). Teams that set Key Results on outputs alone often cannot move them inside a quarter; teams that set them on inputs alone risk optimising a number that turns out not to drive the outcome. The tree keeps both in view and honest about the link between them.
State the hypothesis
Every relationship in the tree is a hypothesis, and saying so out loud is the point. "We believe faster onboarding increases activation" is a testable claim, not a fact, and treating it as a claim means you can be wrong and learn. This is where metric trees connect to critical thinking and leading and lagging indicators: the model tells you which numbers should move first if your theory is right, so a check-in becomes a test of the theory, not just a status update. The goal is a model that is useful, not perfect; a rough map that everyone shares beats a precise one nobody uses.
Levers worth modelling
In Roger Martin’s terms, these models are enabling management systems, part of the nervous system that translates strategic choices into daily behaviour, and like all such systems they are subject to the barnacle problem if never pruned. The levers worth modelling are the ones that move the How to Win: a metric tree disconnected from the theory of advantage is measurement for its own sake, elaborate, busy, and pointed at nothing that decides whether you win.
A team wants to grow revenue (output, slow). The tree traces revenue to expansion, expansion to activation, activation to first-session value (input, fast, controllable). The Key Result lands on first-session value, the lever they can actually pull, with the tree stating the belief that pulling it moves revenue upstream.
What is a metric tree? +
A map of measures arranged by cause and effect: a north-star outcome, the drivers that feed it, and the inputs beneath those. It reveals which levers matter and turns each connection into a testable hypothesis.
What is the difference between an input and an output metric? +
An output measures the result you want (often slow, not directly controllable); an input measures something you can move now that you believe drives it. Good Key Results usually target inputs, with the tree stating the link to the output.
From the ZOKRI OKR Handbook, the methodology we install and maintain. Written by Matt Roberts.
A UK-based strategy and OKR consultant and two-time SaaS founder with a venture-backed exit, Matt turns strategy into execution for teams scaling from tens to thousands. He co-founded ZOKRI in 2018, having previously co-founded Linkdex, a venture-backed enterprise SaaS platform he led to a trade sale. He writes the methodology behind these notes.
A shared model of your metrics changes every goal conversation that follows. We build the metric tree with your team, connect it to your theory of advantage, and install it in your AI Business OS.