learning curve

n.
A graph that depicts rate of learning, especially a graph of progress in the mastery of a skill against the time required for such mastery.

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Learning Curve Brands, Inc.

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Contact Information

Learning Curve Brands, 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

Chugga! Chugga! Whoo! Whoo! All aboard Thomas the Tank Engine as he steams along with Learning Curve Brands. 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.

Officers:
Chairman; EVP and Director, RC2: Richard E. (Dick) Rothkopf
President; EVP, RC2: Peter Hensler
COO: Gregory J. (Greg) Kilrea

Competitors:
Discovery Toys
Hasbro
Mattel

Barron's Accounting Dictionary:

learning curve

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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 seen in the illustration on the next page.
Learning Curve

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Gale Encyclopedia of Small Business:

Learning Curves

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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.

learning curve

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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.

Investopedia Financial Dictionary:

Learning Curve

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A concept that describes how new skills or knowledge can be quickly acquired initially, but subsequent learning becomes much slower. At first, a minimal investment of resources yields significant results, but the payback from continuing effort is smaller. The learning curve was first described by psychologist Hermann Ebbinghaus in 1885 and elaborated by psychologist Arthur Bills in 1934.

Investopedia Says:

In a visual representation of a learning curve, a steeper curve indicates faster, easier learning and a flatter curve indicates slower, more difficult learning. The concept of a learning curve is important to companies in hiring and training new employees and managers, in working to increase production efficiency, and in budgeting and forecasting costs.

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Wikipedia on Answers.com:

Experience curve effects

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"Experience curve" redirects here. For the video game concept, see Experience point.

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

1 Learning curve and learning curve effect
2 The experience curve
3 See also
4 References
5 Further reading
6 External links

Learning curve and learning curve effect

Main article: Learning curve

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.

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.

$\ Y_x = K x^{\log_2 b}$ ^[2]

where

$\ K$ is the number of direct labour hours to produce the first unit
$\ Y_x$ is the number of direct labour hours to produce the xth unit
$\ x$ is the unit number
$\ b$ is the learning percentage

2. 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.

$\overline{Y_x} = K\frac{\frac{1}{1+\log_2b}x^{1+\log_2{b}}}{x}$

where

$\ K$ is the number of direct labour hours to produce the first unit
$\ Y_x$ is the average number of direct labour hours to produce First xth units
$\ x$ is the unit number
$\ b$ is the learning percentage

The experience curve

The 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.

Experience curve

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:

$\ C_n = C_1 n^{-a}$ ^[4]

where

$\ C_1$ is the cost of the first unit of production
$\ C_n$ is the cost of the nth unit of production
$\ n$ is the cumulative volume of production
$\ a$ is the elasticity of cost with regard to output

Reasons for the effect

Examples

NASA quotes the following experience curves:^[5]

Aerospace 85%
Shipbuilding 80-85%
Complex machine tools for new models 75-85%
Repetitive electronics manufacturing 90-95%
Repetitive machining or punch-press operations 90-95%
Repetitive electrical operations 75-85%
Repetitive welding operations 90%
Raw materials 93-96%
Purchased Parts 85-88%

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:

Labour efficiency - Workers become physically more dexterous. They become mentally more confident and spend less time hesitating, learning, experimenting, or making mistakes. Over time they learn short-cuts and improvements. This applies to all employees and managers, not just those directly involved in production.
Standardization, specialization, and methods improvements - As processes, parts, and products become more standardized, efficiency tends to increase. When employees specialize in a limited set of tasks, they gain more experience with these tasks and operate at a faster rate.
Technology-Driven Learning - Automated production technology and information technology can introduce efficiencies as they are implemented and people learn how to use them efficiently and effectively.
Better use of equipment - as total production has increased, manufacturing equipment will have been more fully exploited, lowering fully accounted unit costs. In addition, purchase of more productive equipment can be justifiable.
Changes in the resource mix - As a company acquires experience, it can alter its mix of inputs and thereby become more efficient.
Product redesign - As the manufacturers and consumers have more experience with the product, they can usually find improvements. This filters through to the manufacturing process. A good example of this is Cadillac's testing of various "bells and whistles" specialty accessories. The ones that did not break became mass produced in other General Motors products; the ones that didn't stand the test of user "beatings" were discontinued, saving the car company money. As General Motors produced more cars, they learned how to best produce products that work for the least money.
Network-building and use-cost reductions (network effects) - As a product enters more widespread use, the consumer uses it more efficiently because they're familiar with it. One fax machine in the world can do nothing, but if everyone has one, they build an increasingly efficient network of communications. Another example is email accounts; the more there are, the more efficient the network is, the lower everyone's cost per utility of using it.
Shared experience effects - Experience curve effects are reinforced when two or more products share a common activity or resource. Any efficiency learned from one product can be applied to the other products. (This is related to the principle of least astonishment).

Experience curve discontinuities

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:

Competitors introduce new products or processes that you must respond to
Key suppliers have much bigger customers that determine the price of products and services, and that becomes the main cost driver for the product
Technological change requires that you or your suppliers change processes
The experience curve strategies must be re-evaluated because
- they are leading to price wars
- they are not producing a marketing mix that the market values

Strategic consequences of the effect

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.

Criticisms

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.

The well travelled road effect may lead people to over-estimate the effect of the experience curve.

References

^ Wright, T.P., Factors Affecting the Cost of Airplanes, Journal of Aeronautical Sciences, 3(4) (1936): 122-128.
^ Chase, Richard B. (2001), Operations management for competitive advantage, ninth edition, International edition: McGraw Hill/ Irwin, ISBN 0-07-118030-3
^ Hax, Arnoldo C.; Majluf, Nicolas S. (October 1982), "Competitive cost dynamics: the experience curve", Interfaces 12 (5): 50–61, doi:10.1287/inte.12.5.50.
^ Grant, Robert M. (2004), Contemporary strategy analysis, U.S., UK, Australia, Germany: Blackwell publishing, ISBN 1-4051-1999-3
^ Learning Curve Calculator
^ Henderson, Bruce (1974). "The Experience Curve Reviewed: V. Price Stability". Perspectives. The Boston Consulting Group. http://www.bcg.com/documents/file13904.pdf. Retrieved 2007-03-24.

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learning curve

learning curve

Learning Curve Brands, Inc.

learning curve

Learning Curves

learning curve

Learning Curve

Experience curve effects

Learning curve and learning curve effect

The experience curve

Reasons for the effect

Experience curve discontinuities

Strategic consequences of the effect

Criticisms

See also

References

Further reading

External links