High-Low Method Calculator - Fixed and Variable Cost

The high-low method separates a mixed cost into estimated fixed and variable components using two observations: the highest and lowest activity levels in a data set. It is a fast managerial-accounting technique for building a linear cost equation when a detailed regression is unavailable. The estimated equation is total cost equals fixed cost plus variable cost per activity unit multiplied by activity. First calculate the variable rate by subtracting low-point cost from high-point cost and dividing by the difference in activity. If cost is $5,000 at 1,000 units and $2,000 at 200 units, the rate is $3,000 divided by 800, or $3.75 per unit. Then substitute either observation into the cost equation. At the high point, fixed cost equals $5,000 minus $3.75 times 1,000, which is $1,250. The method selects points by activity, not by cost. The highest-cost month is not necessarily the highest-activity month, and using it simply because cost is large can distort the estimate. Both observations should fall inside the same relevant range, where capacity, staffing, pricing, and operating process are reasonably stable. A step cost or plant expansion between the points violates that assumption. High-low is useful for preliminary budgets, contribution analysis, make-or-buy discussions, and quick reasonableness checks. Its main weakness is that it discards every middle observation. Either endpoint may contain abnormal overtime, shutdowns, maintenance, weather effects, discounts, or data errors. A scatterplot and least-squares regression usually provide a stronger estimate when enough reliable observations are available. A negative fixed-cost estimate or negative variable rate is mathematically possible but often signals unsuitable points, inconsistent cost classification, or nonlinearity. Investigate rather than automatically treating it as an economic fact. Match the activity driver to the cost: machine hours may explain power better than units, while delivery miles may explain fuel better than orders. Use the result only within the observed relevant range and update it when prices, productivity, capacity, or operating conditions change.