Section A: Learning Curves

The term "learning curve" refers to the idea that efficiency increases the more experience a person has with a given task. As a result, the time required for performing the task decreases as increases occur in the number of times the task has been performed.

The cumulative average-time learning model is based on the assumption that the cumulative average time required per unit declines at a constant rate each time the cumulative quantity of units produced doubles. The cumulative average-time learning model can be used to estimate the average time per unit required to produce all of a given number of units produced.

The incremental unit-time learning model is based on the assumption that the incremental amount of time required to produce the last unit declines at a constant rate each time the cumulative quantity of units produced doubles. The incremental unit-time learning model can be used to estimate the time needed to produce the last unit in a quantity of units.

1 The estimated average time per unit for the entire quantity produced, from the very first unit to the very last unit produced. This is the "cumulative average." 2 The estimated total time required for the entire quantity produced, from the very first unit to the very last unit produced. 3 The estimated total production time required for a certain block of units can be calculated by finding the total time required for all the units produced through the end of that block and subtracting from that the total time required for the units up to that block. This calculation is possible only if the block of units represents the units that are produced in a doubling of production.

The incremental unit-time learning model can be used to calculate the estimated time required to produce one specific unit after the first unit, given the time required to produce the first unit.

Development of production plans and labor requirements: Learning curves should be used in the development of production and labor budgets when changes such as new products are planned. Management control: Recognizing that higher costs will occur in the early phase of the product life cycle allows more effective evaluation of managers. Development of standard costs: Labor costs should be adjusted regularly in recognition of the fact that learning causes standard costs to decrease over time.

Life-cycle costing: For calculating the cost of a contract, learning curve analysis can ensure that the cost estimates are accurate over the life of the contract, leading to better bidding. Cost-volume-profit analysis: If learning is not considered in determining a breakeven point, the result may be an overstatement of the number of units required to break even. Capital budgeting: Costs can be projected more accurately over the life of the capital investment when expected improvements in labor productivity due to learning are included. Make or buy decisions: The analysis of the cost to make the product will be affected by the learning curve in effect.

* Learning curve analysis is appropriate only for labor-intensive operations involving repetitive tasks where repeated trials improve performance. * The learning rate is assumed to be constant.

In real life, the decline in labor time might not be constant. * The reliability of a learning curve calculation can be jeopardized because an observed change in productivity might actually be associated with factors other than learning, such as a change in the labor mix, the product mix, or other factors.