--- name: metric-definition-sheet description: "One owned formula, data source, and owner per metric name — closing the exact gap that lets two teams each compute 'the same' metric differently and both be technically right, and honestly flagging any metric that's still unresolved rather than picking a winner on its own. Use when: Two teams have quietly started reporting different numbers for a metric with the same name, and nobody has actually reconciled why. A dashboard or huddle board is about to go live and you want every metric on it traceable to a real formula and a real owner, not an assumption. Not for: You don't actually know how a metric is computed today — go find out from whoever owns the system first; this sheet records real facts, it doesn't invent a formula that sounds plausible. The metric is genuinely one-off or exploratory, not something two or more people will reference by name going forward — the overhead isn't worth it yet." --- # Metric definition sheet One owned formula, data source, and owner per metric name — closing the exact gap that lets two teams each compute 'the same' metric differently and both be technically right, and honestly flagging any metric that's still unresolved rather than picking a winner on its own. Family: Measurement · Format: .xlsx · Domain: core ## What it is A metric definition sheet is a real, checkable answer to 'what does this number actually mean, and who says so' — one formula, one data source, one owner per metric name. The problem it exists to solve is common and well documented: two teams both report 'on-time delivery' or 'active users,' each computing it a different way, and both numbers are defensible on their own terms — until someone tries to reconcile them. This sheet doesn't invent a resolution when none exists; a metric with no agreed formula or no real owner is flagged plainly, not smoothed over. ## When to use it Use it when: - Two teams have quietly started reporting different numbers for a metric with the same name, and nobody has actually reconciled why. - A dashboard or huddle board is about to go live and you want every metric on it traceable to a real formula and a real owner, not an assumption. - You want to know honestly which metrics in active use still have no agreed definition, rather than assuming they're all settled. Not when: - You don't actually know how a metric is computed today — go find out from whoever owns the system first; this sheet records real facts, it doesn't invent a formula that sounds plausible. - The metric is genuinely one-off or exploratory, not something two or more people will reference by name going forward — the overhead isn't worth it yet. ## How to fill it in - **scopeArea** — What part of the business do these metric definitions cover? - **metrics** — For each metric: the formula, data source, owner, refresh cadence, and unit you actually use today — your own facts, never guessed. Leave any of these blank if it's genuinely not agreed yet. - **narrative** — Drafted from the metrics actually defined, naming which ones still have a real gap. ## What good looks like The example below continues the Line 2 paint-booth storyline running through this catalogue's A3, scoping canvas, and FMEA examples — two metrics are fully specified against real systems already in use, and the third, on-time delivery rate, honestly names a real, unresolved conflict between Scheduling and Quality rather than picking a winner. Full worked example, on-screen and as a downloadable .xlsx: https://www.katafacts.com/katas/metric-definition-sheet ## Common mistakes - **Writing a formula that sounds precise but was never actually confirmed against the source system.** — A confident-looking formula with no real basis is worse than an honest gap — it lets two teams both trust their own number right up until the day someone tries to reconcile them. - **Leaving a metric unowned because 'everyone kind of owns it.'** — A definition nobody owns is a definition everyone quietly forks — a real owner is what keeps the formula from silently drifting as systems change. - **Resolving a genuine cross-team conflict unilaterally just to make the sheet look complete.** — Picking a winner without the other team's buy-in doesn't resolve the conflict, it just hides it — naming the conflict plainly is what actually gets it fixed. ## What it connects to Downstream: - **Key performance indicator (KPI) tree** (`kpi-tree`) — A driver metric in a KPI tree is only as trustworthy as this sheet's own definition behind it — the tree tracks the number, this sheet is what makes the number mean one specific thing. ## Where AI helps Judgement — stays with you: - Deciding whether a metric's formula is actually well-specified or just sounds precise - Deciding which unresolved gap to prioritize closing first Analysis — AI helps: - Tightening raw definition and known-limitations notes into specific, scannable language - Drafting the narrative naming which metrics are fully specified and which still have a real gap Drudgery — automated: - Identifying which metrics are missing a formula or an owner - Exporting to xlsx in the house format --- Metric definition sheet is licensed [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/). Attribution: Katafacts (katafacts.com). ## Using this skill Apply this method as part of whatever broader task, instructions, or deliverable you're already working on -- it's a method to use, not a standalone conversation to start. There is no generation tool for this catalogue yet, so draft the artifact's actual content yourself, following the fields above, the same way a person filling this out by hand would. The canonical guide page and a downloadable worked example (.xlsx) are at https://www.katafacts.com/katas/metric-definition-sheet.