The Experience Curve

The more experience a firm has in producing a particular product, the lower its costs

The experience curve is an idea developed by the Boston Consulting Group (BCG) in the mid-1960s. Working with a leading manufacturer of semiconductors, the consultants noticed that the company’s unit cost of manufacturing fell by about 25% for each doubling of the volume that it produced. This relationship they called the experience curve: the more experience a firm has in producing a particular product, the lower are its costs. Bruce Henderson, the founder of BCG, put it as follows:

Costs characteristically decline by 20-30% in real terms each time accumulated experience doubles. This means that when inflation is factored out, costs should always decline. The decline is fast if growth is fast and slow if growth is slow.

There is no fundamental economic law that can predict the existence of the experience curve, even though it has been shown to apply to industries across the board. Its truth has been proven inductively, not deductively. And if it is true in service industries such as investment banking or legal advice, the lower costs are clearly not passed on to customers.

By itself, the curve is not particularly earth shattering. Even when BCG first expounded the relationship, it had been known since the second world war that it applied to direct labour costs. Less labour was needed for a given output depending on the experience of that labour. In aircraft production, for instance, labour input decreased by some 10–15% for every doubling of that labour’s experience.

The strategic implications of the experience curve came closer to shattering earth. For if costs fell (fairly predictably) with experience, and if experience was closely related to market share (as it seemed it must be), then the competitor with the biggest market share was going to have a big cost advantage over its rivals. QED: being market leader is a valuable asset that a firm relinquishes at its peril.

This was the logical underpinning of the idea of the growth share matrix (seearticle). The experience curve justified allocating financial resources to those businesses (out of a firm’s portfolio of businesses) that were (or were going to be) market leaders in their particular sectors. This, of course, implied starvation for those businesses that were not and never would be market leaders.

Over time, managers came to find the experience curve too imprecise to help them much with specific business plans. Inconveniently, different products had curves of a different slope and different sources of cost reduction. They did not, for instance, all have the same downward gradient as the semiconductor industry, where BCG had first identified the phenomenon. A study by the Rand Corporation found that “a doubling in the number of [nuclear] reactors [built by an architect–engineer] results in a 5% reduction in both construction time and capital cost”.

Part of the explanation for this discrepancy was that different products provided different opportunities to gain experience. Large products (such as nuclear reactors) are inherently bound to be produced in smaller volumes than small products (such as semiconductors). It is not easy for a firm to double the volume of production of something that it takes over five years to build, and whose total market may never be more than a few hundred units.

In theory, the experience curve should make it difficult for new entrants to challenge firms with a substantial market share. In practice, new firms enter old industries all the time, and before long many of them become major players in their markets. This is often because they have found ways of bypassing what might seem like the remorseless inevitability of the curve and its slope. For example, experience can be gained not only first-hand, by actually doing the production and finding out for yourself, but also second-hand, by reading about it and by being trained by people who have first-hand experience. Furthermore, firms can leapfrog over the experience curve by means of innovation and invention. All the experience in the world in making black and white television sets is worthless if everyone wants to buy colour ones.

Further reading

De Bono, E., “Practical Thinking”, Cape, 1971; Penguin, 1976

Ghemawat, P., “Building Strategy on the Experience Curve”, Harvard Business Review, March–April 1985

Gottfredson, M. and Schaubert, S., “The Breakthrough Imperative”, HarperCollins, 2008

Henderson, B.D., “The Logic of Business Strategy”, Ballinger Publishing, 1984

Sallenare, J.P., “The Uses and Abuses of Experience Curves”, Long Range Planning, Vol. 18, No. 1, 1985

Stern, C.W. and Stalk, G. Jr (eds), “Perspectives on Strategy: From the Boston Consulting Group”, John Wiley & Sons, 1998

Offshoring

Economists argue that offshoring is a win-win phenomenon

Offshoring—the wholesale shifting of corporate functions and jobs (particularly those of back-office workers in it and accounting-type roles) to overseas territories—is what gave outsourcing a bad name. It is important, however, to note a crucial distinction between the two:

• Outsourcing need not necessarily result in job losses in a particular territory or country. A job can simply be handed over to another organisation of the same nationality and geographical location where (the company handing it over hopes) it can be carried out more efficiently. Sometimes that other organisation may be in another country, but more often than not it is not.

• Offshoring, however, does involve shifting jobs to another country, but it may not involve transferring jobs to another organisation. For example, a company may simply decide to move its local customer services operation to one of its own subsidiaries abroad. That is offshoring, but it is not outsourcing.

Economists argue that offshoring is a win-win phenomenon: the country that sends the work abroad gains from lower costs, and the country that gains the work gets extra jobs. But countries sometimes panic about the scale of offshoring. When production jobs moved en masse to China and other cheap labour destinations, rich-world governments did not worry unduly because they thought that their workers could glide painlessly from manufacturing jobs to service jobs. Who, they thought, would begrudge giving up a lifetime on the factory floor for a lifetime in a clean, antiseptic office?

The real problem arose when the service jobs also started to go abroad, when every other service company’s call centre suddenly seemed to be based in Bangalore, in the middle of India, not Indiana. What were western workers going to move on to this time, once they had been priced out of the services sector?

At one stage, Americans became almost hysterical about the issue. A 2004 report by Forrester Research, a highly reputable firm, estimated that 3.3m American jobs would have gone offshore by 2015. This was immediately taken as a known fact. But the author of the report subsequently told the Wall Street Journal that his estimates were no more than “educated guesses”. As one commentator said: “The public’s intense desire to understand the scope of the problem has bred a reliance on statistics that even [Forrester] admits are based heavily on guesswork.”

In practice, the hysteria died down, even as the benefits of offshoring were being questioned more and more. Managers found it increasingly difficult to manage far-flung service operations in cultures they did not understand, and firms began to bring some functions back to their home base—especially call centres, where customers often found it difficult to explain localised problems to someone working in a totally different climate in a totally different time zone. Indeed, in 2006 an Indian call-centre operator opened a new centre in Northern Ireland.

Closely allied to offshoring is the concept of nearshoring, a phenomenon whereby companies shift operations, often IT-related ones, to foreign countries that are close to their own, but where they can still gain a labour-cost advantage—from the United States, for example, where Spanish is the second language, to Mexico; or from Japan to the Chinese city of Dalian, which was occupied by the Japanese for many years and where there are Japanese-speakers. Nearby countries are more likely to speak the same language as the country of the corporation doing the offshoring; they are more easily accessible at short notice; and they are unlikely to leave the short-stay visitor with jet lag.

Further reading

Kobayashi-Hillary, M. (ed.), “Building a Future with BRICs: The Next Decade for Offshoring”, Springer, 2008

“Offshoring: Is It a Win-Win Game?”, McKinsey Global Institute, August 2003

OPERATIONS RESEARCH

The use of computer modelling and the simulation of business processes as a means of coming up with improvements in the way that things are done within an organisation

At the heart of operations research (OR) is the use of computer modelling and the simulation of business processes as a means of coming up with improvements in the way that things are done within an organisation. The tasks that OR examines are complex and involve many variables. They include things like designing an optimal telecommunications network in a situation where future demand is uncertain, or automating a paper-based bank clearing system.

According to the Operational Research Society:

Operational Research (OR), also known as Operations Research or Management Science (OR/MS), looks at an organisation’s operations and uses mathematical or computer models, or other analytical approaches, to find better ways of doing them.

The term “operational research” is generally used in the UK; the United States favours “operations research” or “management science”. Information technology is central to the skill of an operational researcher. But OR also draws on mathematics, engineering, physics and economics.

The heyday of OR was the 1950s and 1960s when, as Russell Ackoff, an OR academic, once put it, “use of quantitative methods became an ‘idea in good currency’”. By the 1990s, though, Ackoff found that OR had been pushed into “the bowels of the organisation not the head. When it could no longer be pushed down, it was pushed out”. This, he believed, was because OR had been “equated by managers to mathematical masturbation and to the absence of any substantive knowledge or understanding of organisations, institutions or their management”. Ackoff also claimed that there was a more fundamental flaw to OR. It is, he said, designed to “prepare perfectly for an imperfectly predicted future”, and it “helps us little and may harm us much”.

Igor Ansoff, author of the classic “Corporate Strategy”, was heavily influenced by the time he spent working on sophisticated operational research for the Rand Foundation in the early 1950s. Among other things, he analysed the extent of the exposure of NATO air forces to enemy attack.

OR was given a big boost by the second world war when researchers applied the principles of physics and engineering to military operations. After the war, military personnel took these practices with them to civvy street, and to the companies that they then went to work for. OR was often the entry point for engineers, like Ansoff, to come into general management. Many management gurus, including Frederick Taylor, W. Edwards Deming (the founder of the quality movement), Henry Mintzberg and Bruce Henderson (the man behind the experience curve), were trained first as engineers.

Further reading

Ackoff, R.L., “Redesigning the Future: A Systems Approach to Societal Problems”, John Wiley & Sons, 1974

Kirby, M., “Operational Research in War and Peace: The British Experience from the 1930s to 1970”, Imperial College Press, 2003

Taha, H.A., “Operations Research: an Introduction”, 8th edn, Prentice Hall, 2007

Journal of the Operational Research Society