# Variance Analysis Structure For Each Variance Narrative

> Sub-skill of variance-analysis: Structure for Each Variance Narrative (+2).

- Skill: `vamseeachanta/variance-analysis-structure-for-each-variance-narrative` (Agent Skill)
- Install (CLI): `npx skillmds@latest add vamseeachanta/variance-analysis-structure-for-each-variance-narrative`
- Raw SKILL.md: https://api.skillmd.com/api/skills/vamseeachanta/variance-analysis-structure-for-each-variance-narrative/raw
- Safety review: PASS (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: vamseeachanta (https://skillmd.com/u/vamseeachanta)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/vamseeachanta/variance-analysis-structure-for-each-variance-narrative

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# Structure for Each Variance Narrative (+2)

## Structure for Each Variance Narrative


```
[Line Item]: [Favorable/Unfavorable] variance of $[amount] ([percentage]%)
vs [comparison basis] for [period]

Driver: [Primary driver description]
[2-3 sentences explaining the business reason for the variance, with specific
quantification of contributing factors]

Outlook: [One-time / Expected to continue / Improving / Deteriorating]
Action: [None required / Monitor / Investigate further / Update forecast]
```


## Narrative Quality Checklist


Good variance narratives should be:

- [ ] **Specific:** Names the actual driver, not just "higher than expected"
- [ ] **Quantified:** Includes dollar and percentage impact of each driver
- [ ] **Causal:** Explains WHY it happened, not just WHAT happened
- [ ] **Forward-looking:** States whether the variance is expected to continue
- [ ] **Actionable:** Identifies any required follow-up or decision
- [ ] **Concise:** 2-4 sentences, not a paragraph of filler


## Common Narrative Anti-Patterns to Avoid


- "Revenue was higher than budget due to higher revenue" (circular — no actual explanation)
- "Expenses were elevated this period" (vague — which expenses? why?)
- "Timing" without specifying what was early/late and when it will normalize
- "One-time" without explaining what the item was
- "Various small items" for a material variance (must decompose further)
- Focusing only on the largest driver and ignoring offsetting items