In management, models of the learning curve effect and the closely related experience curve effect express the relationship between equation[clarification needed] and efficiency or between efficiency gains and investment in the effort.
"Learning curves" were first described qualitatively in 1885 by the German psychologist Hermann Ebbinghaus, who was investigating the difficulty of memorizing varying numbers of verbal stimuli. Subsequent findings about the complex processes of learning are discussed in the Learning curve article.
Experience shows that the more times a task has been performed, the less time is required on each subsequent iteration. This relationship was probably first quantified in 1936 at Wright-Patterson Air Force Base in the United States, where it was determined that every time total aircraft production doubled, the required labour time decreased by 10 to 15 percent. Subsequent empirical studies from other industries have yielded different values ranging from only a couple of percentages up to 30%, but in most cases it is a constant percentage: It did not vary at different scales of operation. The Learning Curve model posits that for each doubling of the total quantity of items produced, costs decrease by a fixed proportion.
Empirical research has validated the following mathematical form for the unit cost, Px, producing unit number x starting with P1 for a wide variety of different products and services:
where (1-b) is the proportion reduction in the unit cost with each doubling in the cumulative production. To see this, note the following:
Of course, this is only a statistical average and will rarely if ever exactly predict the unit cost of producing any future product. However, it has been found to be useful in many contexts with b ranging from 0.75 to 0.9 in different industries (so 1-b ranges from 0.1 to 0.25, as noted elsewhere in this article).
Generally, the production of any good or service shows the experience curve effect. Each time cumulative volume doubles, value added costs (including administration, marketing, distribution, and manufacturing) fall by a constant percentage.
The Experience Curve was developed by Bruce D. Henderson and the Boston Consulting Group (BCG) while analyzing overall cost behavior in the 1960s. In 1968, Henderson and BCG began to emphasize the implications of the experience curve for strategy. Research by BCG in the 1960s and 70s observed experience curve effects for various industries that ranged from 10 to 25 percent.
These effects are often expressed graphically. The curve is plotted with the cumulative units produced on the horizontal axis and unit cost on the vertical axis. A curve showing a 15% cost reduction for every doubling of output is called an “85% experience curve”, indicating that unit costs drop to 85% of their original level.
NASA quotes the following experience curves:
The primary reason for why experience and learning curve effects apply, of course, is the complex processes of learning involved. As discussed in the main article, learning generally begins with making successively larger finds and then successively smaller ones. The equations for these effects come from the usefulness of mathematical models for certain somewhat predictable aspects of those generally non-deterministic processes. They include:
The experience curve effect can on occasion come to an abrupt stop. Graphically, the curve is truncated. Existing processes become obsolete and the firm must upgrade to remain competitive. The upgrade will mean the old experience curve will be replaced by a new one. This occurs when:
The BCG strategists examined the consequences of the experience effect for businesses. They concluded that because relatively low cost of operations is a very powerful strategic advantage, firms should capitalize on these learning and experience effects.  The reasoning is increased activity leads to increased learning, which leads to lower costs, which can lead to lower prices, which can lead to increased market share, which can lead to increased profitability and market dominance. According to BCG, the most effective business strategy was one of striving for market dominance in this way. This was particularly true when a firm had an early leadership in market share. It was claimed that if you cannot get enough market share to be competitive, you should get out of that business and concentrate your resources where you can take advantage of experience effects and gain dominant market share. The BCG strategists developed product portfolio techniques like the BCG Matrix (in part) to manage this strategy.
Today we recognize that there are other strategies that are just as effective as cost leadership so we need not limit ourselves to this one path. See for example Porter generic strategies which talks about product differentiation and focused market segmentation as two alternatives to cost leadership. Sterman et al. show that expanding rapidly to realize experience curve benefits is a high risk strategy in dynamic markets with common features like bounded rationality and durable products.
One consequence of the experience curve effect is that cost savings should be passed on as price decreases rather than kept as profit margin increases. The BCG strategists felt that maintaining a relatively high price, although very profitable in the short run, spelled disaster for the strategy in the long run. They felt that it encouraged competitors to enter the market, triggering a steep price decline and a competitive shakeout. If prices were reduced as unit costs fell (due to experience curve effects), then competitive entry would be discouraged and one's market share maintained. Using this strategy, you could always stay one step ahead of new or existing rivals.
Starting in 1966, according to Henderson:
Some authors[who?] claim that in most organizations it is impossible to quantify the effects. They claim that experience effects are so closely intertwined with economies of scale that it is impossible to separate the two. In theory we can say that economies of scale are those efficiencies that arise from an increased scale of production, and that experience effects are those efficiencies that arise from the learning and experience gained from repeated activities, but in practice the two mirror each other: growth of experience coincides with increased production. Economies of scale should be considered one of the reasons why experience effects exist. Likewise, experience effects are one of the reasons why economies of scale exist. This makes assigning a numerical value to either of them difficult.
The well travelled road effect may lead people to overestimate the effect of the experience curve.
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