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ClaudeWave
Skill693 estrellas del repoactualizado 12d ago

variance-analysis

This skill decomposes financial variances into component drivers using price/volume, rate/mix, and headcount techniques, then generates waterfall visualizations and narrative explanations. Use it when analyzing budget versus actual results, period-over-period changes, revenue or expense variances, or preparing variance commentary for financial reporting and leadership review.

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git clone --depth 1 https://github.com/openyak/openyak /tmp/variance-analysis && cp -r /tmp/variance-analysis/backend/app/data/plugins/finance/skills/variance-analysis ~/.claude/skills/variance-analysis
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SKILL.md

# Variance Analysis

**Important**: This skill assists with variance analysis workflows but does not provide financial advice. All analyses should be reviewed by qualified financial professionals before use in reporting.

Techniques for decomposing variances, materiality thresholds, narrative generation, waterfall chart methodology, and budget vs actual vs forecast comparisons.

## Variance Decomposition Techniques

### Price / Volume Decomposition

The most fundamental variance decomposition. Used for revenue, cost of goods, and any metric that can be expressed as Price x Volume.

**Formula:**
```
Total Variance = Actual - Budget (or Prior)

Volume Effect  = (Actual Volume - Budget Volume) x Budget Price
Price Effect   = (Actual Price - Budget Price) x Actual Volume
Mix Effect     = Residual (interaction term), or allocated proportionally

Verification:  Volume Effect + Price Effect = Total Variance
               (when mix is embedded in the price/volume terms)
```

**Three-way decomposition (separating mix):**
```
Volume Effect = (Actual Volume - Budget Volume) x Budget Price x Budget Mix
Price Effect  = (Actual Price - Budget Price) x Budget Volume x Actual Mix
Mix Effect    = Budget Price x Budget Volume x (Actual Mix - Budget Mix)
```

**Example — Revenue variance:**
- Budget: 10,000 units at $50 = $500,000
- Actual: 11,000 units at $48 = $528,000
- Total variance: +$28,000 favorable
  - Volume effect: +1,000 units x $50 = +$50,000 (favorable — sold more units)
  - Price effect: -$2 x 11,000 units = -$22,000 (unfavorable — lower ASP)
  - Net: +$28,000

### Rate / Mix Decomposition

Used when analyzing blended rates across segments with different unit economics.

**Formula:**
```
Rate Effect = Sum of (Actual Volume_i x (Actual Rate_i - Budget Rate_i))
Mix Effect  = Sum of (Budget Rate_i x (Actual Volume_i - Expected Volume_i at Budget Mix))
```

**Example — Gross margin variance:**
- Product A: 60% margin, Product B: 40% margin
- Budget mix: 50% A, 50% B → Blended margin 50%
- Actual mix: 40% A, 60% B → Blended margin 48%
- Mix effect explains 2pp of margin compression

### Headcount / Compensation Decomposition

Used for analyzing payroll and people-cost variances.

```
Total Comp Variance = Actual Compensation - Budget Compensation

Decompose into:
1. Headcount variance    = (Actual HC - Budget HC) x Budget Avg Comp
2. Rate variance         = (Actual Avg Comp - Budget Avg Comp) x Budget HC
3. Mix variance          = Difference due to level/department mix shift
4. Timing variance       = Hiring earlier/later than planned (partial-period effect)
5. Attrition impact      = Savings from unplanned departures (partially offset by backfill costs)
```

### Spend Category Decomposition

Used for operating expense analysis when price/volume is not applicable.

```
Total OpEx Variance = Actual OpEx - Budget OpEx

Decompose by:
1. Headcount-driven costs    (salaries, benefits, payroll taxes, recruiting)
2. Volume-driven costs       (hosting, transaction fees, commissions, shipping)
3. Discretionary spend       (travel, events, professional services, marketing programs)
4. Contractual/fixed costs   (rent, insurance, software licenses, subscriptions)
5. One-time / non-recurring  (severance, legal settlements, write-offs, project costs)
6. Timing / phasing          (spend shifted between periods vs plan)
```

## Materiality Thresholds and Investigation Triggers

### Setting Thresholds

Materiality thresholds determine which variances require investigation and narrative explanation. Set thresholds based on:

1. **Financial statement materiality:** Typically 1-5% of a key benchmark (revenue, total assets, net income)
2. **Line item size:** Larger line items warrant lower percentage thresholds
3. **Volatility:** More volatile line items may need higher thresholds to avoid noise
4. **Management attention:** What level of variance would change a decision?

### Recommended Threshold Framework

| Comparison Type | Dollar Threshold | Percentage Threshold | Trigger |
|----------------|-----------------|---------------------|---------|
| Actual vs Budget | Organization-specific | 10% | Either exceeded |
| Actual vs Prior Period | Organization-specific | 15% | Either exceeded |
| Actual vs Forecast | Organization-specific | 5% | Either exceeded |
| Sequential (MoM) | Organization-specific | 20% | Either exceeded |

*Set dollar thresholds based on your organization's size. Common practice: 0.5%-1% of revenue for income statement items.*

### Investigation Priority

When multiple variances exceed thresholds, prioritize investigation by:

1. **Largest absolute dollar variance** — biggest P&L impact
2. **Largest percentage variance** — may indicate process issue or error
3. **Unexpected direction** — variance opposite to trend or expectation
4. **New variance** — item that was on track and is now off
5. **Cumulative/trending variance** — growing each period

## Narrative Generation for Variance Explanations

### 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
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