Experience curve effects

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The learning curve effect and the closely related experience curve effect express the relationship between experience and efficiency. As individuals and/or organizations get more experienced at a task, they usually become more efficient at them. Both concepts originate in the old adage, "practice makes perfect".

The learning curve effect

The learning curve effect states that the more often a task is performed, the less time will be required on each iteration. This relationship was first quantified in 1925 at Wright-Patterson Air Force Base in the United States, where it was determined that every time 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.

The experience curve effect

The experience curve effect is broader in scope than the learning curve effect encompassing far more than just labour 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. This broader effect was first noticed in the late 1960s by Bruce Henderson at the Boston Consulting Group (BCG). 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.

Two Experience Curves

Mathematically these curves are described by power laws (although another possible mathematical formulation of the effect would involve exponential decay: see discussion).

Reasons for the effect


NASA has calculated the following experience curves:

There are a number of reasons why the experience curve and learning curve apply in most situations. 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.
  • 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 consumers have more experience with the product, they can suggest 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 GM products; the ones that didn't stand the test of user "beatings" were discontinued, saving the car company money. As GM produced more cars, they learned how to best produce products that work for the least money.
  • Value chain effects - Experience curve effects are not limited to the company. Suppliers and distributors will also ride down the learning curve, making the whole value chain more efficient.
  • Network-building and use-cost reductions - 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 the cost to everyone of using it.
  • Shared experience effects - Experience curve effects are reinforced when two or more products share a common activity or resource. Any efficiencies learned from one product can be applied to the other products.

Experience curve discontinuities

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:

  • Competitors introduce new products or processes that you must respond to
  • Technological change requires that you or your suppliers change processes
  • The experience curve strategies must be re-evaluated because

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. 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.

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.

In his book Economia, Geoff Davies describes the implications of the learning curve as fundamental. He argues along similar lines to BCG that, through positive feedback, the advantages conferred by the curve and other economies of scale allow one or a few firms to increase market share until they dominate their market. Maintaining that because of the learning curve effect, economies of scale pervade modern economies, Davies infers that since the resulting monopolies distort the market away from equilibrium and optimality, the modern economy is not in equilibrium. "Large, modern free-market economies are characterised not by equilibrium but by exponential growth and instability" (p46, Davies' italics). He concludes that the behaviour of real economic systems is radically different from the predictions of the general equilibrium theory of neoclassical economics, and that therefore this theory fails as a useful description of a modern economy.


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. 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.

Others claim that it is a mistake to see either learning curve effects or experience curve effects as a given. They stress that they are not a universal law or even a strong tendency in nature. In fact, they claim that costs, if not managed will tend to rise. Any experience effects that have been achieved results from a concerted effort by all those involved. They see the effect as an opportunity that management can create, rather than a general characteristic of organizations.

See also

See also

Books and articles

(in chronological order)

  • T. P. Wright, (1936) Learning Curve, Journal of the Aeronautical Sciences, Feb 1936
  • W. Hirschmann, (1964) Profit from the Learning Curve, Harvard Business Review, Jan-Feb 1964
  • Boston Consulting Group, (1972) Perspectives on Experience, Boston, Mass.
  • W. Abernathy and K. Wayne, (1974) Limits to the Learning Curve, Harvard Business Review, Sept-Oct 1974
  • W. Kiechel III, (1981) The Decline of the Experience Curve, Fortune, October 5 1981
  • G. Day and D. Montgomery, (1983) Diagnosing the Experience Curve, Journal of Marketing, vol 47, spring 1983
  • P. Ghemawat, (1985) Building Strategy on the Experience Curve, Harvard Business Review, vol 42, March-April 1985.
  • P. F. Ostwald, (1992) Engineering Cost Estimating, 3/E, Prentice Hall, ISBN 0-13-276627-2
  • G. Davies, (2004) Economia: New Economic Systems to Empower People and Support the Living World, ABC Books, ISBN 0-7333-1298-5.

External links

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