High-Low Method

High-Low Method: Separating Fixed and Variable Costs

Key takeaways

• The high-low method separates total costs into fixed and variable components using only two data points: the highest and lowest activity levels.
• It provides a quick, simple estimate but can be inaccurate because it relies on extreme values and ignores intermediate data.
• Use it when detailed cost records are unavailable; verify results with more comprehensive methods (e.g., regression) when possible.

What the high-low method is

The high-low method is a cost-accounting technique for estimating the variable cost per unit and total fixed cost of an item or activity that has mixed costs. It assumes total fixed costs are constant across the observed activity range and attributes the change in total cost between the highest and lowest activity levels to variable costs.

How it works (formulas and steps)

1. Identify the period with the highest activity and the period with the lowest activity. Record total costs and activity units for those periods.
2. Calculate variable cost per unit:
   Variable cost per unit = (Total cost at high activity − Total cost at low activity) / (High activity units − Low activity units)
3. Calculate total fixed cost using either the high or low point:
   Total fixed cost = Total cost at chosen activity level − (Variable cost per unit × Activity units at that level)
4. Form the total-cost equation:
   Total cost = Total fixed cost + (Variable cost per unit × Units)

This yields a simple linear cost model you can use to estimate costs for other activity levels.

Example: Bakery

A bakery’s monthly data shows:
* Highest month: 125 cakes, total cost $5,550
* Lowest month: 70 cakes, total cost $3,750

1. Variable cost per cake:
   (5,550 − 3,750) / (125 − 70) = 1,800 / 55 = $32.73 per cake
2. Total fixed cost (using the high month):
   5,550 − (32.73 × 125) = 5,550 − 4,090.91 = $1,459.09
3. Total-cost equation:
   Total cost = $1,459.09 + ($32.73 × Units)

Use this equation to estimate monthly costs for any number of cakes within the observed range.

High-low method vs. regression analysis

• High-low method
• Pros: Fast, simple; requires only two points; can be done with a calculator.
• Cons: Uses only extreme values; sensitive to outliers; provides a rough estimate.
• Regression analysis
• Pros: Uses all available data to produce a best-fit line; more robust to variability and provides diagnostic statistics.
• Cons: Requires more data and typically a spreadsheet or statistical software; results depend on data quality.

Regression is generally preferred when sufficient data is available; high-low is useful as a preliminary or fallback method.

Limitations and cautions

• Reliance on only the highest and lowest activity points makes the method vulnerable to atypical months or outliers.
• Assumes a linear cost relationship (constant variable cost per unit and constant total fixed cost) that may not hold in the presence of step costs, tiered pricing, or changing cost behavior.
• Does not adjust for external factors (e.g., inflation, seasonality) or multiple cost drivers.
• Should be used only when detailed cost data aren’t available or as a quick estimate; validate with additional data or methods when possible.

When to use it

Use the high-low method for quick, rough estimates of cost behavior when:
* Detailed or complete cost records are unavailable.
* A fast approximation is needed for short-term decisions.
* You plan to follow up with more rigorous analysis if results are material.

Conclusion

The high-low method is a straightforward tool for decomposing mixed costs into fixed and variable components using the two extreme activity points. It’s expedient and easy to apply, but its simplicity comes at the cost of accuracy and robustness. Treat results as preliminary and confirm with fuller data or regression analysis when possible.