What Is the High-Low Method?
In cost accounting, the high-low method is a technique used to estimate variable and fixed costs using a limited data set. By analyzing the highest and lowest activity levels and their associated total costs, this method provides insights into cost behavior patterns. It is an essential tool aimed at simplifying cost analysis, especially when detailed data are scarce.
However, it is important to exercise caution as the accuracy of this method can be influenced by the distribution of values between the highest and lowest data points.
Steps to Applying the High-Low Method
1. Calculate the Variable Cost Component
First, determine the variable cost per unit:
\text{Variable Cost} = \frac { \text{Highest Activity Cost} - \text{Lowest Activity Cost} }{ \text{Highest Activity Units} - \text{Lowest Activity Units} }
For calculations:
HAC = \text{Highest activity cost}
HAU = \text{Highest activity units}
2. Determine the Fixed Cost Component
Next, calculate the fixed cost using:
\text{Fixed Cost} = HAC - ( \text{Variable Cost} \times HAU )
3. Calculate the Total Cost
Finally, combine your results in the cost model formula:
\text{Total Cost} = \text{Fixed Cost} + ( \text{Variable Cost} \times \text{Unit Activity} )
The Insights from the High-Low Method
This cost estimation method aids in understanding the various cost components related to a product, equipment, or entire business units like geographic sales regions or subsidiaries. Significant insights can be derived regarding cost control and optimization.
Key Takeaways
- Simpler than other methods: Offers a straightforward approach to cost estimation.
- Assumption-based: Assumes constancy in variable and fixed costs, allowing for quick estimation, though potentially less precise.
- Easily extendable: While less precise, it’s simpler compared to methods like regression analysis, requiring more intricate computations.
Real-World Example of the High-Low Method
Imagine a cake bakery’s monthly performance data over a year as follows:
| Month | Cakes Baked (units) | Total Cost ($) |
|---|---|---|
| January | 115 | $5,000 |
| February | 80 | $4,250 |
| March | 90 | $4,650 |
| April | 95 | $4,600 |
| May | 75 | $3,675 |
| June | 100 | $5,000 |
| July | 85 | $4,400 |
| August | 70 | $3,750 |
| September | 115 | $5,100 |
| October | 125 | $5,550 |
| November | 110 | $5,100 |
| December | 120 | $5,700 |
In August, the bakery saw the least activity and lowest costs, while October saw the highest activity.
Calculate variable cost using high and low activities:
\text{Variable Cost} = \frac{ \$5,550 - \$3,750 }{ 125 - 70 } = \frac{ \$1,800 }{ 55 } = \$32.72 \text{ per Cake}
Calculate fixed cost:
\text{Fixed Cost} = $5,550 - ( $32.72 \times 125 ) = $5,550 - $4,090 = $1,460
Therefore, the cost model becomes:
\text{Total Cost} = $1,460 + ( $32.72 \times Units Produced )
Comparing the High-Low Method and Regression Analysis
Simplicity vs Complexity
- High-Low Method: Quick and straightforward using high and low activity levels.
- Regression Analysis: More accurate but complex, considering outliers and more data points for precise forecasts.
However, regression requires statistical tools like spreadsheets and deeper analysis of the relations and varying influences between factors.
Limitations of the High-Low Method
Despite its simplicity, the high-low method has inherent limitations:
- Inaccuracy Risk: Limited to two extreme data points, outliers can skew results.
- Use Case: Best used when minimal data are available; better methods should be employed when detailed data can be sourced.
By understanding and effectively using the high-low method, businesses can gain valuable insights while maintaining a streamlined approach to cost analysis, enabling better planning and decision-making.
Related Terms: regression analysis, cost estimation, fixed costs, variable costs.
References
- Harvard Business School. “What Is Regression Analysis in Business Analytics?”
