chart line representing the efficiencies gained from experience. Basically, it is a curve describing the relationship between the consecutive number of units produced (x-axis) and the time per unit produced (y-axis). More specifically, it is based on the statistical findings that as the cumulative output doubles, the cumulative average labor input time required per unit will be reduced by some constant percentage, ranging between 10% and 40%. The curve is usually designated by its complement. For example, if the rate of reduction is 20%, the curve is referred to as an 80% learning curve.

Applications of the learning curve theory include (1) pricing decisions,based on the estimates of expected costs; (2) requirements for scheduling labor; (3) capital budgeting decisions; and (4) setting incentive wage rates.

The following data illustrate the 80% learning curve relationship:

As can be seen, as production quantities double, the average time per unit decreases by 20% of its immediate previous time. It can be graphed as seen in the illustration on the next page.

predictable improvements following the early part of the life of a production contract, when costly mistakes are made.

a graph representing mastery of a skill plotted against the time spent on learning it. If something is hard to learn to use, it is sometimes described as having a steep learning curve (although, logically, a steep curve should indicate rapid learning). The term originated in behaviorist psychology but is now used very imprecisely.

a figurative graph of mastery of a skill plotted against the time spent learning it. Software that is difficult to master is illogically said to have a steep learning curve.