Incorporating Learning-Curve Effects Into Prices and Standards

How do companies use learning curves? Consider the data in Exhibit 10-11 for the cumulative average-time learning model at Rayburn Corporation. Suppose the variable costs subject to learning effects are direct manufacturing labor, at $20 per hour, and related overhead, at $30 per direct manufacturing labor-hour, for a total of $50 per direct manufacturing labor-hour. Managers should predict the costs shown in Exhibit 10-14.

These data show that the effects of the learning curve could have a major impact on the decisions Rayburn Corporation’s managers make. For example, the managers might price the firm’s radar systems lower than the cost to produce the first few units to generate high demand. As production of the systems increases to meet the growing demand, the cost per unit drops (see column F), and Rayburn “rides the product down the learning curve” as it gains market share. Although it may have earned little operating income on its first unit sold—it may actually have lost money on that unit—Rayburn earns more operating income per unit as output increases.

Alternatively, depending on legal and other factors, Rayburn’s managers might set a low price on just the final 8 units. The total labor and related overhead costs for these 8 units are predicted to be only $12,288 (see column E) and the $\$\text{1,536}\hspace{0.17em}\text{incremental cost per unit}\hspace{0.17em}(\$\text{12,288}÷8\hspace{0.17em}\text{units})$ is much lower than the $5,000 cost of the first unit produced.

Many companies, such as Pizza Hut and Home Depot, use learning curves to evaluate performance levels. The Nissan Motor Company sets assembly-labor efficiency standards and evaluates performance for new models of cars after taking into account the learning that will occur as more units are produced. The U.S. Department of Defense incorporates learning curves into its cost estimates for military weapons programs. Concepts in Action: Learning Curves and the Falling Prices of Renewable Energy shows how learning curves have helped reduce the price of renewable energy.

The learning-curve models examined in Exhibits 10-11 to 10-14 assume that learning is driven by a single variable (production output). Other models of learning have been developed (by companies such as Analog Devices and Hewlett-Packard) that focus on how quality—rather than manufacturing labor-hours—will change over time, regardless of whether more units are produced. Studies indicate that factors other than production output, such as job rotation and organizing workers into teams, contribute to learning that improves quality.