variance-analysis
Decompose financial variances into drivers with narrative explanations and waterfall analysis. Use when analyzing budget vs. actual, period-over-period changes, revenue or expense variances, or preparing variance commentary for leadership.
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mkdir -p ~/.claude/skills && cd ~/.claude/skills && curl -L -o variance-analysis.zip https://jpskill.com/download/22621.zip && unzip -o variance-analysis.zip && rm variance-analysis.zip
$d = "$env:USERPROFILE\.claude\skills"; ni -Force -ItemType Directory $d | Out-Null; iwr https://jpskill.com/download/22621.zip -OutFile "$d\variance-analysis.zip"; Expand-Archive "$d\variance-analysis.zip" -DestinationPath $d -Force; ri "$d\variance-analysis.zip"
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C:\Users\あなたの名前\.claude\skills\(Win)または~/.claude/skills/(Mac)へ移動 - 4. Claude Code を再起動
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詳しい使い方ガイドを見る →- 最終更新
- 2026-05-18
- 取得日時
- 2026-05-18
- 同梱ファイル
- 1
📖 Skill本文(日本語訳)
※ 原文(英語/中国語)を Gemini で日本語化したものです。Claude 自身は原文を読みます。誤訳がある場合は原文をご確認ください。
[スキル名] variance-analysis
分散分析
重要: このスキルは分散分析のワークフローを支援しますが、財務上のアドバイスを提供するものではありません。すべての分析は、報告書で使用する前に、資格のある財務専門家によるレビューを受ける必要があります。
分散の分解手法、重要性の閾値、ナラティブ生成、ウォーターフォールチャートの方法論、予算と実績と予測の比較について説明します。
分散分解手法
価格/数量分解
最も基本的な分散分解です。収益、売上原価、および価格×数量で表現できるあらゆる指標に使用されます。
計算式:
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)
3要因分解(ミックスを分離する場合):
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)
例 — 収益分散:
- 予算: 10,000単位 @ $50 = $500,000
- 実績: 11,000単位 @ $48 = $528,000
- 総分散: +$28,000 (好調)
- 数量効果: +1,000単位 x $50 = +$50,000 (好調 — より多くの単位を販売)
- 価格効果: -$2 x 11,000単位 = -$22,000 (不調 — ASPの低下)
- 純額: +$28,000
レート/ミックス分解
異なる単位経済を持つセグメント間のブレンドレートを分析する際に使用されます。
計算式:
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))
例 — 売上総利益分散:
- 製品A: 60%マージン、製品B: 40%マージン
- 予算ミックス: A 50%、B 50% → ブレンドマージン 50%
- 実績ミックス: A 40%、B 60% → ブレンドマージン 48%
- ミックス効果がマージン圧縮の2ppを説明
人員数/報酬分解
給与および人件費の分散を分析するために使用されます。
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)
支出カテゴリ分解
価格/数量が適用できない場合の営業費用分析に使用されます。
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)
重要性の閾値と調査トリガー
閾値の設定
重要性の閾値は、どの分散が調査と説明を必要とするかを決定します。閾値は以下に基づいて設定します。
- 財務諸表の重要性: 通常、主要なベンチマーク(収益、総資産、純利益)の1〜5%
- 項目サイズ: 項目が大きいほど、パーセンテージ閾値を低く設定
- 変動性: 変動性の高い項目は、ノイズを避けるためにより高い閾値が必要な場合あり
- 経営陣の注目度: どの程度の分散が意思決定を変えるか?
推奨される閾値フレームワーク
| 比較タイプ | ドル閾値 | パーセンテージ閾値 | トリガー |
|---|---|---|---|
| 実績 vs 予算 | 組織固有 | 10% | いずれかを超過 |
| 実績 vs 前期 | 組織固有 | 15% | いずれかを超過 |
| 実績 vs 予測 | 組織固有 | 5% | いずれかを超過 |
| 連続(前月比) | 組織固有 | 20% | いずれかを超過 |
ドル閾値は組織の規模に基づいて設定してください。一般的な慣行:損益計算書項目については収益の0.5%〜1%。
調査の優先順位
複数の分散が閾値を超えた場合、以下の基準で調査を優先します。
- 最大の絶対ドル分散 — P&Lへの影響が最大
- 最大のパーセンテージ分散 — プロセス上の問題やエラーを示唆する可能性
- 予期せぬ方向 — 傾向や期待と逆の分散
- 新しい分散 — 順調だった項目が外れた場合
- 累積/傾向分散 — 各期間で増加している場合
分散説明のためのナラティブ生成
各分散ナラティブの構造
[項目]: [好調/不調] 分散額 $[金額] ([パーセンテージ]%)
[期間]の[比較基準]と比較して
要因: [主要な要因の説明]
[分散のビジネス上の理由を説明する2〜3文。貢献要因の具体的な定量化を含む]
見通し: [一時的/継続が予想される/改善傾向/悪化傾向]
アクション: [不要/監視/さらなる調査/予測の更新]
ナラティブ品質チェックリスト
良い分散ナラティブは以下の条件を満たす必要があります。
- [ ] 具体的: 「予想より高い」だけでなく、実際の要因を特定している
- [ ] 定量的: 各要因のドルおよびパーセンテージの影響が含まれている
- [ ] 因果的: 何が起こったかだけでなく、なぜ起こったかを説明している
- [ ] 将来志向: 分散が継続すると予想されるかどうかを述べている
- [ ] 実行可能: 必要なフォローアップや意思決定を特定している
- [ ] 簡潔: 2〜4文で、余分な記述がない
避けるべき一般的なナラティブのアンチパターン
- 「収益は
(原文がここで切り詰められています)
📜 原文 SKILL.md(Claudeが読む英語/中国語)を展開
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:
- Financial statement materiality: Typically 1-5% of a key benchmark (revenue, total assets, net income)
- Line item size: Larger line items warrant lower percentage thresholds
- Volatility: More volatile line items may need higher thresholds to avoid noise
- 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:
- Largest absolute dollar variance — biggest P&L impact
- Largest percentage variance — may indicate process issue or error
- Unexpected direction — variance opposite to trend or expectation
- New variance — item that was on track and is now off
- 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 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
Waterfall Chart Methodology
Concept
A waterfall (or bridge) chart shows how you get from one value to another through a series of positive and negative contributors. Used to visualize variance decomposition.
Data Structure
Starting value: [Base/Budget/Prior period amount]
Drivers: [List of contributing factors with signed amounts]
Ending value: [Actual/Current period amount]
Verification: Starting value + Sum of all drivers = Ending value
Text-Based Waterfall Format
When a charting tool is not available, present as a text waterfall:
WATERFALL: Revenue — Q4 Actual vs Q4 Budget
Q4 Budget Revenue $10,000K
|
|--[+] Volume growth (new customers) +$800K
|--[+] Expansion revenue (existing customers) +$400K
|--[-] Price reductions / discounting -$200K
|--[-] Churn / contraction -$350K
|--[+] FX tailwind +$50K
|--[-] Timing (deals slipped to Q1) -$150K
|
Q4 Actual Revenue $10,550K
Net Variance: +$550K (+5.5% favorable)
Bridge Reconciliation Table
Complement the waterfall with a reconciliation table:
| Driver | Amount | % of Variance | Cumulative |
|---|---|---|---|
| Volume growth | +$800K | 145% | +$800K |
| Expansion revenue | +$400K | 73% | +$1,200K |
| Price reductions | -$200K | -36% | +$1,000K |
| Churn / contraction | -$350K | -64% | +$650K |
| FX tailwind | +$50K | 9% | +$700K |
| Timing (deal slippage) | -$150K | -27% | +$550K |
| Total variance | +$550K | 100% |
Note: Percentages can exceed 100% for individual drivers when there are offsetting items.
Waterfall Best Practices
- Order drivers from largest positive to largest negative (or in logical business sequence)
- Keep to 5-8 drivers maximum — aggregate smaller items into "Other"
- Verify the waterfall reconciles (start + drivers = end)
- Color-code: green for favorable, red for unfavorable (in visual charts)
- Label each bar with both the amount and a brief description
- Include a "Total Variance" summary bar
Budget vs Actual vs Forecast Comparisons
Three-Way Comparison Framework
| Metric | Budget | Forecast | Actual | Bud Var ($) | Bud Var (%) | Fcast Var ($) | Fcast Var (%) |
|---|---|---|---|---|---|---|---|
| Revenue | $X | $X | $X | $X | X% | $X | X% |
| COGS | $X | $X | $X | $X | X% | $X | X% |
| Gross Profit | $X | $X | $X | $X | X% | $X | X% |
When to Use Each Comparison
- Actual vs Budget: Annual performance measurement, compensation decisions, board reporting. Budget is set at the beginning of the year and typically not changed.
- Actual vs Forecast: Operational management, identifying emerging issues. Forecast is updated periodically (monthly or quarterly) to reflect current expectations.
- Forecast vs Budget: Understanding how expectations have changed since planning. Useful for identifying planning accuracy issues.
- Actual vs Prior Period: Trend analysis, sequential performance. Useful when budget is not meaningful (new business lines, post-acquisition).
- Actual vs Prior Year: Year-over-year growth analysis, seasonality-adjusted comparison.
Forecast Accuracy Analysis
Track how accurate forecasts are over time to improve planning:
Forecast Accuracy = 1 - |Actual - Forecast| / |Actual|
MAPE (Mean Absolute Percentage Error) = Average of |Actual - Forecast| / |Actual| across periods
| Period | Forecast | Actual | Variance | Accuracy |
|---|---|---|---|---|
| Jan | $X | $X | $X (X%) | XX% |
| Feb | $X | $X | $X (X%) | XX% |
| ... | ... | ... | ... | ... |
| Avg | MAPE | XX% |
Variance Trending
Track how variances evolve over the year to identify systematic bias:
- Consistently favorable: Budget may be too conservative (sandbagging)
- Consistently unfavorable: Budget may be too aggressive or execution issues
- Growing unfavorable: Deteriorating performance or unrealistic targets
- Shrinking variance: Forecast accuracy improving through the year (normal pattern)
- Volatile: Unpredictable business or poor forecasting methodology