Lecture Notes: Variance Analysis and Standard Costing

Key Topics Covered

Calculated based on a company's materials usage relative to standard quantities.
Example given for material P:
- Standard quantity for actual production: 5 kg.
- Comparison of actual quantity used (500 kg) with planned (400 kg).
- Result: Bad variance as more material was used than planned, leading to increased costs.
Exercise for material Q to be completed.

Mix Variance Formula: AQAM (Actual Quantity Actual Mix) vs AQSM (Actual Quantity Standard Mix) multiplied by Standard Price.
Example setup:
- Table for actual (P: 500 kg, Q: 730 kg) and standard (P: 5, Q: 10).
- Calculation involves fractions of materials used against total and comparison with planned mixes.
- Calculation of variance for both materials separately.
Yield Variance Formula:
- Compare actual yield with standard yield, factor in standard cost.
- Example provided with actual production of 80 units vs standard yield calculation resulting in variance being analyzed as adverse due to lower production than expected.

Differentiates between uncontrollable (planning) and controllable (operational) variances.
Importance of planning variance:
- Helps adjust standards when original data becomes outdated.
- Planning variance is uncontrollable while operational variance can be managed and adjusted.
Benefits:
- More accurate reflection of current operating efficiency.
- Helps identify planning deficiencies.
Limitations:
- Subjective and recalculations required frequently.
- Not all cost items may warrant recalculation due to resources involved.

Covers both labour rate and efficiency variances.
Example for planning and operating variance given with focus on wage increase and hour adjustments.

Focus on material and labour variances due to changes in standards and actual data.
Material price and usage planning and operating variances calculated with examples provided.

New machine purchase affecting labour hours and skills.
Requires calculation of material and labour mix and yield variances using provided data.

Emphasizes the importance of updating standard costing practices through planning and operational variance analysis.
Encourages investigation of significant variances that impact production costs and efficiency.
Highlighted the role of variance analysis in adjusting planning strategies and improving performance evaluation.