metric-change-attributionlisted

# Period-over-Period Metric-Change Attribution A metric moved between two periods. This skill attributes *why*: it ranks the dimension members that drove the change (解释度/ep), optionally splits a ratio into multiplicative factors (structure × quality), drills the top contributor level by level to the root, and classifies old/new turnover at the leaf — while guarding against the dual-source denominator trap. Metric-agnostic and config-driven: the same engine works for **ratio** metrics (numerator/denominator) and **additive** totals (a single measure). You declare the metric, dimensions, and sources in a small YAML config; you do **not** edit code. ## When to use - Two comparable periods of the same metric, sliceable by ≥1 categorical dimension. - You want "which segment/factor/item is responsible", ranked and drilled. - NOT for: forecasting, single-series anomaly-point detection, or causal inference beyond decomposition of an observed change. ## The 6-step method 1. **Declare a config** — period (prev/curr), metric (ratio or additive), the dimension hierarchy, sources + column maps. Copy `templates/analysis.config.yaml`. 2. **Validate + dual-source check** — long-format sanity; confirm the deduplicated source is the denominator truth and any leaf "pool" source is direction-only. 3. **Score the top dimension** — ratio: ep / 解释度 (sums to 100%); additive: Δ-share. 4. **(ratio, optional) factor split** — log-decompose the rate into structure × quality. 5. **Rank, noise