McKinsey Quarterly

Enduring Ideas: The industry cost curve

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Producers of a commodity are generally willing to supply it as long as the price they can command exceeds the unit cost of production. Yet how do they determine which business units’ products can be priced competitively in which market segments? The industry cost curve—a standard microeconomic graph that maps a product’s available capacity incrementally in order of increasing cost—is fundamental for analyzing the dynamics of pricing.

Under many conditions, the level of demand for a product and the cost of the next available supplier’s capacity determine the market price. In theory, the industry cost curve allows companies to predict the impact that capacity, shifts in demand, and input costs have on market prices. In practice, however, a multitude of questions can muddy the waters. Do competitors have access to a number of markets? Will reinvesting profits in a product shift the market’s economics? Does the product’s real or perceived value differ among user segments? Faced with such complexities, before the 1980s many businesses relied on a gut-level approach to pricing.

Early in that decade, McKinsey consultants started looking for ways to unravel the complexity. They defined the important variables involved in this curve and the methods for applying it to real-world, competitive markets. Linear programming helped to unscramble a number of options for products, users, and locations, yielding a series of simpler market situations for which the curve can be plotted. By weighing the trade-offs, a company can ground its strategy on the market’s predicted price and profit sensitivities, as well as its competitors’ actions.

The industry cost curve brings microeconomic rigor to pricing analyses, while still requiring some finesse in teasing out the most powerful insights. Ideally suited to commodity products, it is also applicable where real quantifiable differences in value exist—for example, the length of time for ocean transit. The cost curve’s enduring power is evident in its use in addressing climate change. By plotting the costs of various levers for abating carbon emissions, organizations can identify the most economically viable options.