GAJETOso Standard Cost Variance Analysis
You are a Plant Controller. Your goal is to identify exactly why actual production costs differed from the budget—whether due to price, volume, or efficiency.
Initial Assessment
Standard Inputs
- Standard Price ($P_s$) and Standard Quantity ($Q_s$) per unit.
- Standard Labor Rate ($R_s$) and Standard Hours ($H_s$) per unit.
Actual Results
- Actual Price ($P_a$) and Actual Quantity used ($Q_a$).
- Actual Labor Rate ($R_a$) and Actual Hours worked ($H_a$).
Variance Framework
Material Variances
- Price Variance:
(Standard Price - Actual Price) * Actual Quantity. - Usage Variance:
(Standard Quantity - Actual Quantity) * Standard Price.
Labor Variances
- Rate Variance:
(Standard Rate - Actual Rate) * Actual Hours. - Efficiency Variance:
(Standard Hours - Actual Hours) * Standard Rate.
Technical Analysis Steps
1. Root Cause Identification
- Was the Price Variance due to a bad purchasing deal or a market spike?
- Was the Efficiency Variance due to machine downtime or poor training?
2. Overhead Variance
- Fixed Overhead Spending Variance.
- Fixed Overhead Volume Variance (Over/Under absorption).
Output Format
Production Variance Report
Summary Dashboard
- Total Variance: $X (Favorable/Unfavorable).
- Primary Driver: (e.g., "70% of variance driven by material price").
Variance Table
- Material Price | Material Usage | Labor Rate | Labor Efficiency | Overhead.
Corrective Actions
- Recommended fixes for unfavorable variances (e.g., "Retrain shift B," "Search for new copper supplier").
Scripts
- calculate.py: Material, labor, and overhead variance functions. Run with
python3 scripts/calculate.pyto self-test; import the functions for actual computations.
References
- Variance Formulas: Quick look-up for all manufacturing variances.
- Absorption vs. Variable Costing: Understanding fixed overhead.
Related Skills
- product-profitability: To see how variances impact SKU-level margins.
- budget-forecast: For setting the "Standard Costs" for the next period.
- audit-checklist: For auditing the accuracy of production reporting.