One Definition, One Owner
Last reviewed · content updated
AdvancedWhat you'll learn
~20 min- Write a metric definition precise enough that two people produce the same number from it
- Assign a single named owner per metric and explain what that owner actually decides
- Separate certified metrics from ad-hoc analysis without banning ad-hoc analysis
What it is: naming one owner for each number your organization argues about, and writing the definition down where the query can reach it.
What it buys: the same question stops producing three different answers in three meetings. Disputes get settled once by a named person instead of re-litigated by whoever is in the room, and the cost of maintaining three parallel versions of one metric goes away.
What to fund: an hour per contested metric, plus the political cover for the owner to make a call that some department will dislike.
The three-answer problem
Meridian’s rate team, outage team, and executive dashboard all report “circuits at risk.” In a single quarter the three reported 14, 31, and 9.
None of them is wrong. They are answering different questions with the same words:
| Team | What they counted | Why |
|---|---|---|
| Rate | Circuits with any degradation signal in 12 months | Rate cases look back a full year |
| Outage | Circuits above threshold right now | They dispatch crews this week |
| Executive | Circuits above threshold for 3 consecutive months | Someone wanted to filter out noise |
The damage is not the discrepancy. It is the meeting where the three numbers collide, everybody loses confidence in all three, and the organization concludes the data is unreliable — when in fact the data was fine and the language was broken.
Ask an AI CLI for “circuits at risk” and you will get a query. It will be syntactically correct, it will run, and it will return a number. The agent has no way to know which of the three definitions you meant, so it will pick one — usually the most obvious reading — and it will not tell you it chose.
This is the central hazard of AI-assisted data work: the ambiguity that used to surface as “I don’t know how to write this query” now resolves silently into a plausible number. Speed removes the friction that used to force the conversation.
Prompt first: surface the buried assumption
Here is a metric request: "circuits at risk."
Do not write SQL. Produce a definition skeleton with these fields:grain, population (inclusions AND explicit exclusions), time basis(window, as-of, time zone), calculation in plain words, null andedge handling, proposed owner role.
For each field, give me the 2-3 plausible interpretations someonecould reasonably intend, and flag which one you would have silentlyassumed if I had just asked you for the query.That last clause is the whole point. It makes the agent surface the assumption it would otherwise have buried in a WHERE clause, and it turns a tool that hides ambiguity into one that exposes it.
Meridian defines circuit_degradation_score with 'a circuit with no telemetry is not scored.' A colleague proposes treating no-telemetry as a score of zero, arguing it keeps the list complete. What is the strongest objection?
What a definition has to contain
A metric definition is precise enough when two people who have never spoken can compute it and get the same answer. In practice that requires five things:
- Grain — one row per what? Per circuit, per circuit-month, per circuit-and-crew-assignment. Get this wrong and every downstream aggregate is quietly double-counted.
- Population — which rows are in scope, and explicitly which are excluded. Decommissioned circuits? Circuits energized mid-period? Customer-owned equipment?
- Time basis — as-of when, over what window, in whose time zone. “Last 30 days” from a job that runs at 2am local means something different in March than in January if you cross a daylight-saving boundary.
- The calculation — stated in words before it is stated in SQL, because the words are what a non-engineer can dispute.
- Null and edge handling — what a missing value means here. A circuit with no readings is not the same as a circuit with readings of zero, and the difference changes the count.
Here is Meridian’s, written out:
METRIC circuit_degradation_scoreGRAIN one row per circuit, per calendar monthPOPULATION energized distribution circuits only; excludes transmission, excludes circuits decommissioned before the period start, includes circuits energized mid-period (partial month flagged)TIME BASIS calendar month, America/Chicago, closed at month endCALCULATION weighted count of fault events and comms failures per customer served, normalized to circuit lengthNULLS a circuit with no telemetry in the period is NOT scored; it appears with status "no data" and is never counted as zeroOWNER Distribution Planning SupervisorSTATUS certifiedThe NULLS line is the one that would have prevented Meridian’s worst version of this. Treating “no telemetry” as a score of zero produced a list where the healthiest-looking circuits were the ones whose monitoring had failed.
One owner, and what they actually decide
The owner is not the person who maintains the pipeline. The owner is the person who decides, when Finance says the population should exclude municipal accounts and Operations says it should not, which one it is.
That requires a single name — not a committee, and not “the data team.” The data team cannot own it, because the question is not technical. Somebody with domain authority has to be able to say “municipal accounts are in, here is why, this is now the definition” and have that stick.
What the owner decides:
- Changes to any of the five elements above
- Whether a proposed variant becomes a second certified metric or gets rejected as a duplicate
- When the definition changes, whether history is restated or the break is documented and left in place
That last one is the decision people forget to make, and it is the one that causes the most pain later. Restating history makes trends comparable and makes every previously published number wrong. Leaving the break makes old numbers defensible and makes your trend chart lie at the seam. Either is fine. Silently doing one of them is not.
Certified and ad-hoc can coexist
The reflex after a three-answer incident is to lock everything down. Do not. Most analysis should stay ad-hoc — someone asking a one-off question should not need a governance process.
The workable split is two tiers with a visible label:
- Certified — has all five definition elements, a named owner, checks that run, and a service level. Appears in anything anyone outside the team sees.
- Ad-hoc — anything else. Perfectly legitimate. Labeled as such wherever it appears, and explicitly not the number of record.
The rule that makes this hold: an ad-hoc number that gets used twice by someone outside the team is a certified metric that has not been certified yet. That is your trigger to either promote it properly or stop it from spreading.
Key takeaway
Three teams reporting three numbers is a language failure, not a data failure — and an AI CLI accelerates it, because the ambiguity that once surfaced as “I can’t write this query” now resolves silently into a confident number. A definition needs grain, population, time basis, calculation in words, and null handling, with one named person who settles disputes and decides whether a change restates history. Certified and ad-hoc coexist as long as the label is visible and a twice-used ad-hoc number triggers promotion.
LEADERSHIP DECISION name one owner per contested metric, and back that owner when their call disappoints a departmentPRACTITIONER ACTION write grain, population, time basis, calculation, and null handling before any query; make the agent state the assumption it would have buriedSUCCESS MEASURE the same question asked in two meetings returns the same number; zero certified metrics without a named owner