Academic journal article Review of Business

The Learning Curve and Production Standards : Learning Implications

Academic journal article Review of Business

The Learning Curve and Production Standards : Learning Implications

Article excerpt

The Learning Curve and Production Standards: Learning Implications


The phenomenon of learning is a natural characteristic of human activity. For the job participant, learning is an important source of psychological growth; for the organization, learning is a source of increased efficiency and ingenuity [1]. From either perspective, learning is a goal toward which efforts should be directed. Although it is a natural characteristic of human activity, there is a substantial degree of variation possible in how quickly and to what extent learning occurs. To assume that learning will just happen is to fail to understand that learning can be improved and directed to benefit both the individual and the organization.

This article examines the components of the learning curve model from a behavioral perspective. Under this approach, differences in human abilities are considered and incorporated into the model. Conversely, a scientific management approach treats the model as a static standard which depicts learning as an inert process. The behavioral approach emphasizes the effect of learning on the model, while the scientific management approach emphasizes the effect of the model on learning.

Historical Recognition of Learning

The learning curve effect was originally addressed in the literature by T. P. Wright in 1936[17]. He observed that learning normally follows a particular pattern - as additional units are produced, the time required to produce an individual unit decreases at a uniform rate. This effect necessitates the reduction of direct labor hour and cost standards as production progresses.

Researchers during World War II experimented with the learning curve phenomenon in an attempt to predict production costs and time requirements. They found that learning follows a pattern which corresponds to an exponential curve, which is consistent with the intuitive belief that people tend to perform a task more efficiently as they gain more experience - learning enhances efficiency.

Following the war, traditional management practices were expanded based on the belief that the ability to quantify desired performance levels would lead to desired levels of performance. The natural tendency, and possible deficiency, associated with this approach is to model learning ability based on some mathematical model. While empirical data does conform to a mathematical learning curve model, the model alone provides little insight into why or how learning occurs[4]. Thus, the appeal of being able to quantify learning ability often overshadows the importance of comprehending how learning may affect performance.

For example, to calculate the average cumulative hours for the 4th batch: (1) multiply the average cumulative hours for the 2nd batch by the number of units of output in the 4th batch (3.2 * 200 = 640), (2) multiply that product by the 80% learning rate (620 * 80% = 512), (3) divide that number by the total units produced to arrive at the average cumulative hours per unit (512/200 = 2.56).

The application of the learning curve during the early post war years was consistent with other management practices developed during that same time. Job participants, whether controlled by standards, budgets, or the learning curve, were essentially viewed as "passive instruments capable of performing work and accepting directions, but not initiating action or exerting influence in any significant way" [13]. Learning was not perceived to be a natural characteristic of human activity but as an element of a sliding/mechanical norm (the learning curve).

If the learning curve is to be a practical tool, human attributes cannot be ignored. Just as the areas of standard costing and budgeting have had to incorporate behavioral concepts to increase their effectiveness, so must learning curve applications include behavioral considerations[10,16]. In short, quantification of performance expectations does not necessarily guarantee the achievement of those expectations. …

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