The high-low method is a common tool employed to determine what portion of a cost is fixed and what portion of a cost is variable. Small-business owners can use this information to create budgets and to help understand how changes in volume affect the company's costs in total and on a per-unit basis. However, the high-low method comes with both advantages and disadvantages. Knowing the pros and cons can help you use this tool to your advantage.
Ease of Use
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A major advantage of the high-low method of cost estimation is its ease of use. By only requiring cost information from the highest and lowest activity level and some simple algebra, managers can get information about cost behavior in just a few minutes. In addition to being easy to use, because the method doesn't require any kind of tools or programs, it is also inexpensive to implement.
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Accuracy Under Stable Costs
If costs are relatively stable over time, and the high and low activity level are representative of the company's cost behavior over time, the high-low method can be extremely accurate. However, an interesting conundrum occurs if the endpoints are not representative. Even if costs are very stable throughout the rest of the range of activity, if the lowest of highest level of activity are systematically different, then managers will have inaccurate information. To guard against this, managers may want to plot activity levels vs. costs for a subset of the data that the company has. This way, managers may be able to see if the points they have selected for the high-low method really are representative of normal costs.
Inaccuracy with Variation
A problem with the high-low method is that if costs are relatively unstable, this method could produce inaccurate results. Because the high-low method uses only two points to calculate a cost estimate, monthly variation in costs is not captured in the estimate, even if the points are representative of normal cost behavior. If managers plot the activity level vs. cost and see high variability, they have a decision to make. If timeliness is more important than accuracy, then the high-low method is probably good enough. However, if accuracy is tantamount, then another method should be consulted.
Least-Squares Regression
Perhaps the biggest drawback of the high-low method is not inherent within the method itself. With the prevalence of spreadsheet software, least-squares regression, a method that takes into consideration all of the data, can be easily and quickly employed to obtain estimates that may be magnitudes more accurate than high-low estimates. Least-squares regression uses statistics to mathematically optimize the cost estimate. Further, because this method uses all of the data available, small idiosyncrasies in cost behavior have less effect on the estimate as the amount of data increases.