Practice
Data & Decision Intelligence
A number earns its place only if it can change a decision. By that test most of what a company measures is decoration.
All capabilitiesOur approach
Our perspective.
Owner-led companies steer by nine numbers or by ninety; the nine are engineered. Ground-truth acquisition, a governed metric set where every figure resolves to a choice it can move, market intelligence that survives contact with the market. A number that cannot flip a decision does not ship to the dashboard; the few that can are the leverage.
Data carries no value until it is attached to a decision it can move, and most measurement inside owner-led companies is inert by this test. The position is falsifiable on the spot: take any figure on the dashboard, name the choice it would change, and name the threshold at which that choice flips. The numbers that cannot answer both are not insight. They are cost with good production values.
So the work starts by deleting numbers. The survivors are benchmarked against their physical floor — what the inputs actually cost, what the process could actually run at — never against last year’s version of themselves, because a historical baseline bakes in the very inefficiency the analysis was hired to find.
Common challenges
The challenges we help address.
The vanity metric
A metric tracks the literal, named function and gets mistaken for the value. Sutherland’s doorman fallacy: the dashboard counts the doorman opening doors; the value was the status, the safety, and the hailed cab, none of which became line items. Optimize the number you can measure and you amputate the thing you were actually selling.
The un-decomposed aggregate
“Conversion is down,” “churn is up,” “acquisition cost is high” are symptoms, not findings. A figure you have never peeled into stage-to-stage ratios cannot name a friction point, so every intervention aimed at the aggregate is a guess.
The green that means nothing
A board that renders missing data identically to verified-clean data inflates certainty exactly where the company is blind. The silent sensor reads as a healthy sensor; the check nobody ran reads as a check that passed.
How we work
How the engagement runs.
- Step 1
Diagnose
The metric inventory and decision test: every figure the company tracks is listed against the decision it can move and the threshold at which that decision flips. The ones that answer nothing are marked for deletion — the fastest analytics work available is usually subtraction.
- Step 2
Architect
Ground-truth acquisition: the data the surviving decisions actually need is sourced and verified adapter by adapter, with “not measured” kept structurally distinct from “measured, clean” so a null can never quietly become a zero.
- Step 3
Build
The governed metric set is built: the small number of figures that passed the decision test, each decomposed into stage-to-stage ratios so a weak result names its own friction point instead of triggering a roadmap panic. Loss figures are instrumented by why each dollar left, not how many left.
- Step 4
Operate
Market intelligence in cadence: a standing read on the market that separates structural shift from operational noise, synthesized on a schedule rather than pulled from a live firehose — because on a noisy series, scheduled synthesis lets the noise cancel before it reaches the person making the call.
Deliverables
What the work produces.
- Metric governance charter
- Decide which numbers are allowed to touch a decision, and retire the rest.
- Ground-truth acquisition build
- Replace the cleanest-looking guess on the page with verified fact.
- Decision funnel & micro-ratio model
- Find where the business actually leaks: the single weakest ratio, not the aggregate that hides it.
- Market intelligence brief
- Decide against the market’s real motion, with structural shifts held apart from operational noise.
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