Learning curves are important in a variety of business applications, especially manufacturing. The learning curve theory is a relationship between unit production time and the cumulative number of units produced. As individuals or organizations collectively repeat a particular process, they gain skill or efficiency from their experience and production time improvements result.
The learning curve theory is based on three assumptions: (1) the amount of time required to complete a given task or unit of a product will be less each time the task is undertaken, (2) the unit time will decrease at a decreasing rate, and (3) the reduction in time will follow a predictable pattern. This is often referred to as "practice makes perfect."
If production has been in progress for some time, the learning percentage can be obtained from production records. The longer the production history, the more accurate the estimate will be. For new production projects, it is more a function of guesswork and expert opinion to estimate a learning curve percentage.
A firm's learning rate may differ from that of the industry due to differences in operating characteristics or even procedural differences. Often the rates will vary whether the industry rate is based on a single product or an entire product line. The manner in which the data were aggregated will cause rates to vary. Learning curves and organizational knowledge can depreciate if key individuals leave the organization or if technologies become inaccessible or difficult to use. Learning curves provide an excellent means to examine performance and can be used in a variety of settings as the closing example of heart transplant successes indicates.