| Dictionary: learning curve |
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| Hoover's Profile: Learning Curve International, Inc. |
|
1111 W. 22nd. St., Ste. 320 Oak Brook, IL 60523 IL Tel. 630-573-7200 Fax 630-573-7575 |
Type: Subsidiary
On the web:
http://www.learningcurve.com
Employees:
220
Chugga! Chugga! Whoo! Whoo! All aboard Thomas the Tank Engine as he steams along with Learning Curve International. The company, known for its wooden and battery-powered train sets, also offers other toys: a line of Caring Corners dolls and accessories and John Deere-branded farm theme toys. Its Lamaze Infant Development System and The First Years (acquired in 2004) lines amuse children from birth to three years, and the PlayTown toys target older children. The company, which focuses on nonviolent, creative play toys, does not advertise to children. Learning Curve was founded in 1993 by its president, John Lee. In 2003 RC2 purchased the company and made it a subsidiary.
Key numbers for fiscal year ending December, 2008:
Sales: $19.8M
Officers:
Chairman; EVP and Director, RC2: Richard E. (Dick) Rothkopf
President; EVP, RC2: Peter Hensler
COO: Gregory J. Kilrea
Competitors:
Action Products International
Hasbro
Mattel
| Accounting Dictionary: Learning Curve |
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 follows:

| Small Business Encyclopedia: Learning Curves |
Learning curves graphically portray the costs and benefits of experience when performing routine or repetitive tasks. Also known as experience curves, cost curves, efficiency curves, and productivity curves, they illustrate how the cost per unit of output decreases over time as the result of accumulated workforce learning and experience. That is, as cumulative output increases, learning and experience cause the cost per unit to decrease. Experience and learning curves are used by businesses in production planning, cost forecasting, and setting delivery schedules, among other applications.
Learning curves are geometric curves that can be graphed on the basis of a formula. Typically the X (horizontal) axis measures cumulative output, and the Y (vertical) axis measures the cost per unit. The curve starts with a high cost per unit at the beginning of output, decreases quickly at first, then levels out as cumulative output increases. The slope of the learning curve is an indication of the rate at which learning becomes transformed into cost savings.
An 80 percent learning curve is standard for many activities and is sometimes used as an average in cost forecasting and production planning. An 80 percent learning curve means that, for every doubling of output, the cost of new output is 80 percent of prior output. As output doubles from one unit to two units to four units, etc., the learning curve descends quite sharply as costs decrease dramatically. As output increases, it takes longer to double previous output, and the learning curve flattens out. Thus, costs decrease at a slower pace when cumulative output is higher.
One can explain the shape of learning curves another way. When a new task or production operation begins, a person or system learns quickly, and the learning curve is steep. With each additional repetition, less learning occurs and the curve flattens out. At the beginning of production or learning, individuals or systems are said to be "high" on the learning curve. That means that costs per unit are high, and cumulative output is low. Individuals and systems "move down" the experience or learning curve by learning to complete repetitive tasks more efficiently, eliminating hesitation and mistakes, automating certain tasks, and making adjustments to procedures or systems.
Some theorists believe that learning curves are not actually curves, but more like jagged lines that follow a curving pattern. They assert that learning occurs in brief spurts of progress, followed by small fallbacks to previous levels, rather than in a smooth progressive curve. Such a model of learning, however, does not affect the usefulness of learning curves in business and production applications.
Further Reading:
Chambers, Stuart, and Robert Johnston. "Experience Curves in Services: Macro and Micro Level Approaches." International Journal of Operations and Production Management. July 2000.
Henry, Jane, ed. Creative Management. Sage Publications, 1992.
Lapre, Michael A., Amit Shankar Mukherjee, and Luk N. Van Wassenhove. "Behind the Learning Curve: Linking Learning Activities to Waste Reduction." Management Science. May 2000.
Waterworth, Christopher J. "Relearning the Learning Curve: A Review of the Derivation and Applications of Learning-Curve Theory." Project Management Journal. March 2000.
Weiss, Howard J., and Mark E. Gershon. Production and Operations Management. Allyn and Bacon, 1989.
| Sports Science and Medicine: learning curve |
A curve on a graph which shows performance changes against practice time or number of practice sessions. The term implies that changes in performance mirror changes in learning. Many scientists believe that this idea is an oversimplification (see latent learning). Learning curves (or, more correctly, performance curves) are used to depict the acquisition of skill. For many sports they are negatively accelerating, that is, show the fastest rate of improvement in the early stages of practice and the slowest rate as individuals approach the limits of their ability. However, accurate learning curves are difficult to obtain and are very variable since fluctuations are imposed by many factors, such as motivation, health, and concentration.
| Wikipedia: Experience curve effects |
Models of the learning curve effect and the closely related experience curve effect express the relationship between equations for experience and efficiency or between efficiency gains and investment in the effort.
Contents |
The experience of "learning curves" was first observed by the 19th Century German psychologist Hermann Ebbinghaus according to the difficulty of memorizing varying numbers of verbal stimuli. Subsequent learning about the complex processes of learning are discussed in the Learning curve article.
The experienced learning rates for exploratory discovery and development processes, for individuals and organizations, is more the focus of the main Learning curve article.
As individuals and/or organizations get more experienced at a task, they usually become more efficient at it, following a progression of the learning first getting easier and then harder as one approaches a limit. A "steep" learning curve, in colloquial usage, usually means experiencing a large and increasing amount of effort for a constant amount of learning, i.e. approaching a natural limit. Much the reverse is the meaning of a steep slope in a learning progress curve. A learning progress curve is steep when very little effort is required, as further discussed in the main article.
The rule used for representing the learning curve effect states that the more times a task has been performed, the less time will be required on each subsequent iteration. This relationship was probably first quantified in 1936 at Wright-Patterson Air Force Base in the United States[1], 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 percent up to 30 percent, but in most cases it is a constant percentage: It did not vary at different scales of operation. Learning curve theory states that as the quantity of items produced doubles, costs decrease at a predictable rate. This predictable rate is described by Equations 1 and 2. The equations have the same equation form. The two equations differ only in the definition of the Y term, but this difference can make a significant difference in the outcome of an estimate.
1. This equation describes the basis for what is called the unit curve. In this equation, Y represents the cost of a specified unit in a production run. For example, If a production run has generated 200 units, the total cost can be derived by taking the equation below and applying it 200 times (for units 1 to 200) and then summing the 200 values. This is cumbersome and requires the use of a computer or published tables of predetermined values.
where
is the number of direct labour hours to produce the first unit
is the number of direct labour hours to produce the xth unit
is the unit number
is the learning percentage2. This equation describes the basis for the cumulative average or cum average curve. In this equation, Y represents the average cost of different quantities (X) of units. The significance of the "cum" in cum average is that the average costs are computed for X cumulative units. Therefore, the total cost for X units is the product of X times the cum average cost. For example, to compute the total costs of units 1 to 200, an analyst could compute the cumulative average cost of unit 200 and multiply this value by 200. This is a much easier calculation than in the case of the unit curve.

where
is the number of direct labour hours to produce the first unit
is the average number of direct labour hours to produce First xth units
is the unit number
is the learning percentageThe experience curve effect is broader in scope than the learning curve effect encompassing far more than just labor time. It states that the more often a task is performed, the lower will be the cost of doing it. The task can be the production of any good or service. Each time cumulative volume doubles, value added costs (including administration, marketing, distribution, and manufacturing) fall by a constant and predictable percentage.
In the late 1960s Bruce Henderson of the Boston Consulting Group (BCG) began to emphasize the implications of the experience curve for strategy. [3] Research by BCG in the 1970s 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 cumulative units produced on the horizontal axis and unit cost on the vertical axis. A curve that depicts 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.
Mathematically the experience curve is described by a power law function sometimes referred to as Henderson's Law:
where
is the cost of the first unit of production
is the cost of the nth unit of production
is the cumulative volume of production
is the elasticity of cost with regard to outputExamples
NASA quotes the following experience curves:[5]
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.[citation needed] 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. [6] 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.[citation needed] See for example Porter generic strategies which talks about product differentiation and focused market segmentation as two alternatives to cost leadership.
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.[citation needed] 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.
Some authors 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.[citation needed] 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.
This entry is from Wikipedia, the leading user-contributed encyclopedia. It may not have been reviewed by professional editors (see full disclaimer)
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