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267 lines
11 KiB
Markdown
267 lines
11 KiB
Markdown
---
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name: variance-analysis
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description: 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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argument-hint: "<line item> <period> vs <comparison>"
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---
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# Variance Analysis
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**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.
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Techniques for decomposing variances, materiality thresholds, narrative generation, waterfall chart methodology, and budget vs actual vs forecast comparisons.
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## Variance Decomposition Techniques
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### Price / Volume Decomposition
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The most fundamental variance decomposition. Used for revenue, cost of goods, and any metric that can be expressed as Price x Volume.
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**Formula:**
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```
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Total Variance = Actual - Budget (or Prior)
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Volume Effect = (Actual Volume - Budget Volume) x Budget Price
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Price Effect = (Actual Price - Budget Price) x Actual Volume
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Mix Effect = Residual (interaction term), or allocated proportionally
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Verification: Volume Effect + Price Effect = Total Variance
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(when mix is embedded in the price/volume terms)
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```
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**Three-way decomposition (separating mix):**
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```
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Volume Effect = (Actual Volume - Budget Volume) x Budget Price x Budget Mix
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Price Effect = (Actual Price - Budget Price) x Budget Volume x Actual Mix
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Mix Effect = Budget Price x Budget Volume x (Actual Mix - Budget Mix)
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```
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**Example — Revenue variance:**
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- Budget: 10,000 units at $50 = $500,000
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- Actual: 11,000 units at $48 = $528,000
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- Total variance: +$28,000 favorable
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- Volume effect: +1,000 units x $50 = +$50,000 (favorable — sold more units)
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- Price effect: -$2 x 11,000 units = -$22,000 (unfavorable — lower ASP)
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- Net: +$28,000
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### Rate / Mix Decomposition
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Used when analyzing blended rates across segments with different unit economics.
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**Formula:**
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```
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Rate Effect = Sum of (Actual Volume_i x (Actual Rate_i - Budget Rate_i))
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Mix Effect = Sum of (Budget Rate_i x (Actual Volume_i - Expected Volume_i at Budget Mix))
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```
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**Example — Gross margin variance:**
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- Product A: 60% margin, Product B: 40% margin
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- Budget mix: 50% A, 50% B → Blended margin 50%
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- Actual mix: 40% A, 60% B → Blended margin 48%
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- Mix effect explains 2pp of margin compression
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### Headcount / Compensation Decomposition
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Used for analyzing payroll and people-cost variances.
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```
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Total Comp Variance = Actual Compensation - Budget Compensation
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Decompose into:
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1. Headcount variance = (Actual HC - Budget HC) x Budget Avg Comp
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2. Rate variance = (Actual Avg Comp - Budget Avg Comp) x Budget HC
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3. Mix variance = Difference due to level/department mix shift
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4. Timing variance = Hiring earlier/later than planned (partial-period effect)
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5. Attrition impact = Savings from unplanned departures (partially offset by backfill costs)
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```
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### Spend Category Decomposition
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Used for operating expense analysis when price/volume is not applicable.
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```
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Total OpEx Variance = Actual OpEx - Budget OpEx
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Decompose by:
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1. Headcount-driven costs (salaries, benefits, payroll taxes, recruiting)
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2. Volume-driven costs (hosting, transaction fees, commissions, shipping)
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3. Discretionary spend (travel, events, professional services, marketing programs)
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4. Contractual/fixed costs (rent, insurance, software licenses, subscriptions)
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5. One-time / non-recurring (severance, legal settlements, write-offs, project costs)
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6. Timing / phasing (spend shifted between periods vs plan)
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```
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## Materiality Thresholds and Investigation Triggers
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### Setting Thresholds
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Materiality thresholds determine which variances require investigation and narrative explanation. Set thresholds based on:
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1. **Financial statement materiality:** Typically 1-5% of a key benchmark (revenue, total assets, net income)
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2. **Line item size:** Larger line items warrant lower percentage thresholds
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3. **Volatility:** More volatile line items may need higher thresholds to avoid noise
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4. **Management attention:** What level of variance would change a decision?
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### Recommended Threshold Framework
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| Comparison Type | Dollar Threshold | Percentage Threshold | Trigger |
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|----------------|-----------------|---------------------|---------|
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| Actual vs Budget | Organization-specific | 10% | Either exceeded |
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| Actual vs Prior Period | Organization-specific | 15% | Either exceeded |
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| Actual vs Forecast | Organization-specific | 5% | Either exceeded |
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| Sequential (MoM) | Organization-specific | 20% | Either exceeded |
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*Set dollar thresholds based on your organization's size. Common practice: 0.5%-1% of revenue for income statement items.*
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### Investigation Priority
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When multiple variances exceed thresholds, prioritize investigation by:
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1. **Largest absolute dollar variance** — biggest P&L impact
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2. **Largest percentage variance** — may indicate process issue or error
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3. **Unexpected direction** — variance opposite to trend or expectation
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4. **New variance** — item that was on track and is now off
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5. **Cumulative/trending variance** — growing each period
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## Narrative Generation for Variance Explanations
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### Structure for Each Variance Narrative
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```
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[Line Item]: [Favorable/Unfavorable] variance of $[amount] ([percentage]%)
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vs [comparison basis] for [period]
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Driver: [Primary driver description]
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[2-3 sentences explaining the business reason for the variance, with specific
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quantification of contributing factors]
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Outlook: [One-time / Expected to continue / Improving / Deteriorating]
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Action: [None required / Monitor / Investigate further / Update forecast]
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```
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### Narrative Quality Checklist
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Good variance narratives should be:
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- [ ] **Specific:** Names the actual driver, not just "higher than expected"
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- [ ] **Quantified:** Includes dollar and percentage impact of each driver
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- [ ] **Causal:** Explains WHY it happened, not just WHAT happened
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- [ ] **Forward-looking:** States whether the variance is expected to continue
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- [ ] **Actionable:** Identifies any required follow-up or decision
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- [ ] **Concise:** 2-4 sentences, not a paragraph of filler
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### Common Narrative Anti-Patterns to Avoid
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- "Revenue was higher than budget due to higher revenue" (circular — no actual explanation)
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- "Expenses were elevated this period" (vague — which expenses? why?)
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- "Timing" without specifying what was early/late and when it will normalize
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- "One-time" without explaining what the item was
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- "Various small items" for a material variance (must decompose further)
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- Focusing only on the largest driver and ignoring offsetting items
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## Waterfall Chart Methodology
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### Concept
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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.
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### Data Structure
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```
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Starting value: [Base/Budget/Prior period amount]
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Drivers: [List of contributing factors with signed amounts]
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Ending value: [Actual/Current period amount]
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Verification: Starting value + Sum of all drivers = Ending value
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```
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### Text-Based Waterfall Format
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When a charting tool is not available, present as a text waterfall:
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```
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WATERFALL: Revenue — Q4 Actual vs Q4 Budget
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Q4 Budget Revenue $10,000K
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|--[+] Volume growth (new customers) +$800K
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|--[+] Expansion revenue (existing customers) +$400K
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|--[-] Price reductions / discounting -$200K
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|--[-] Churn / contraction -$350K
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|--[+] FX tailwind +$50K
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|--[-] Timing (deals slipped to Q1) -$150K
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Q4 Actual Revenue $10,550K
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Net Variance: +$550K (+5.5% favorable)
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```
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### Bridge Reconciliation Table
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Complement the waterfall with a reconciliation table:
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| Driver | Amount | % of Variance | Cumulative |
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|--------|--------|---------------|------------|
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| Volume growth | +$800K | 145% | +$800K |
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| Expansion revenue | +$400K | 73% | +$1,200K |
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| Price reductions | -$200K | -36% | +$1,000K |
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| Churn / contraction | -$350K | -64% | +$650K |
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| FX tailwind | +$50K | 9% | +$700K |
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| Timing (deal slippage) | -$150K | -27% | +$550K |
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| **Total variance** | **+$550K** | **100%** | |
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*Note: Percentages can exceed 100% for individual drivers when there are offsetting items.*
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### Waterfall Best Practices
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1. Order drivers from largest positive to largest negative (or in logical business sequence)
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2. Keep to 5-8 drivers maximum — aggregate smaller items into "Other"
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3. Verify the waterfall reconciles (start + drivers = end)
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4. Color-code: green for favorable, red for unfavorable (in visual charts)
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5. Label each bar with both the amount and a brief description
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6. Include a "Total Variance" summary bar
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## Budget vs Actual vs Forecast Comparisons
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### Three-Way Comparison Framework
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| Metric | Budget | Forecast | Actual | Bud Var ($) | Bud Var (%) | Fcast Var ($) | Fcast Var (%) |
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|--------|--------|----------|--------|-------------|-------------|---------------|---------------|
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| Revenue | $X | $X | $X | $X | X% | $X | X% |
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| COGS | $X | $X | $X | $X | X% | $X | X% |
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| Gross Profit | $X | $X | $X | $X | X% | $X | X% |
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### When to Use Each Comparison
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- **Actual vs Budget:** Annual performance measurement, compensation decisions, board reporting. Budget is set at the beginning of the year and typically not changed.
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- **Actual vs Forecast:** Operational management, identifying emerging issues. Forecast is updated periodically (monthly or quarterly) to reflect current expectations.
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- **Forecast vs Budget:** Understanding how expectations have changed since planning. Useful for identifying planning accuracy issues.
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- **Actual vs Prior Period:** Trend analysis, sequential performance. Useful when budget is not meaningful (new business lines, post-acquisition).
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- **Actual vs Prior Year:** Year-over-year growth analysis, seasonality-adjusted comparison.
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### Forecast Accuracy Analysis
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Track how accurate forecasts are over time to improve planning:
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```
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Forecast Accuracy = 1 - |Actual - Forecast| / |Actual|
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MAPE (Mean Absolute Percentage Error) = Average of |Actual - Forecast| / |Actual| across periods
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```
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| Period | Forecast | Actual | Variance | Accuracy |
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|--------|----------|--------|----------|----------|
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| Jan | $X | $X | $X (X%) | XX% |
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| Feb | $X | $X | $X (X%) | XX% |
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| ... | ... | ... | ... | ... |
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| **Avg**| | | **MAPE** | **XX%** |
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### Variance Trending
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Track how variances evolve over the year to identify systematic bias:
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- **Consistently favorable:** Budget may be too conservative (sandbagging)
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- **Consistently unfavorable:** Budget may be too aggressive or execution issues
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- **Growing unfavorable:** Deteriorating performance or unrealistic targets
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- **Shrinking variance:** Forecast accuracy improving through the year (normal pattern)
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- **Volatile:** Unpredictable business or poor forecasting methodology
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