Some tools and concepts are must-haves in the tool kit of any performance improvement professional. The industry cost curve is one of them.
In 1981 Don C. Watters of McKinsey & Company, wrote a staff paper introducing the cost curve as a model for analyzing the strategic decisions about capacity and production that players in heavy, high ﬁxed cost industries have to make. Originally developed in McKinsey’s San Francisco office by Ted Hall and others, the model presented in Watters’s paper, “The industry cost curve as a strategic tool,” is a classic business analysis tool.
The industry cost curve is really just the standard microeconomic graph that shows how much output suppliers can produce at a given cost per unit. As a strategic tool, the cost curve applies most directly to commodity or near commodity industries, in which buyers get roughly the same value from a product regardless of who produces it. But the curve also applies when the value of products from various suppliers differs in consistent, predictable ways.
To illustrate the industry cost curve, let us look at the market for yellow writing pads—a product all too familiar to consultants. For a given year, assume that demand is 75,000 tons, regardless of price. Before drawing the cost curve, you should list all existing paper mills, their production capacities, and their per-unit costs as well as any potential new mills or expansions of existing ones. Draw the curve as shown below, starting with the lowest-cost plant at the left and progressing through successively higher-cost facilities. In a well-functioning market, the lowest-cost plant will produce as much as it can, as will the second-lowest-cost plant and so on, until demand is completely satisfied. Any higher-cost plants that are not needed to meet demand will be priced out of the market.
According to the cost curve below, there are currently four paper mills capable of producing yellow notepads: two owned by the Alpha Company, one by the Bravo Company, and one by Romeo Inc. At the moment, Romeo’s $1,000-a-ton mill is mothballed, and Bravo is thinking about building a brand-new facility, Bravo 2, which would have costs of $1,200 a ton. At Alpha’s most efficient mill, called Alpha 1, production costs are $700 a ton. At Bravo 1, they are $750 a ton. And so on. One of the key insights of this exercise is that the market price is set at the cost of the next available entrant over and above those needed to satisfy current demand. For instance, since demand for notepads is 75,000 tons, only three mills are needed to supply the entire market: Alpha 1 running at capacity, Bravo 1 running at capacity, and Alpha 2 producing 10,000 tons of a potential 25,000.
What is the market price? Well, it may bounce around for a while, but it will ultimately settle down at around $1,000. Suppose, for instance, that Alpha were to set the price of its output above $1,000. In that case, the Romeo mill, which is now idle, would enter the market and steal some of Alpha’s sales. But as long as Alpha keeps its prices under $1,000, it doesn’t have to worry about new entrants. In particular, if Alpha sets its price just barely below $1,000—say, at $999—buyers will have to pay that price. Thus, all three mills set their prices at around $1,000, plus or minus a few dollars. The operating profit of each mill is simply quantity x (price-cost), which shows up as the area of a rectangle on the cost curve. The yellow box in the chart, for example, shows the proﬁts that accrue to Bravo 1.
The tricky part is getting the costs right. Let us consider a mill, such as Bravo 2, that hasn’t yet been built. To calculate its costs, begin with the cash cost of producing a ton of notepads and then add the per-unit costs of transporting the pads to their destination (assuming that the supplier does the shipping). Last, include the opportunity cost of the mill: the return on a similarly risky investment the company could make with the money required to build the mill. Opportunity costs are critical: Bravo 2 will not be built if the Bravo Company doesn’t believe that it can at least earn an acceptable return on its capital. What about a mill, such as Bravo 1, that is already built? Most of Bravo 1’s capital costs are sunk: since the money has already been spent, Bravo cannot invest it elsewhere. So the only opportunity cost at Bravo 1 is the cost of the working capital tied up in running the mill. Per-unit costs, then, are equal to the cash costs of production plus transport costs and the opportunity cost of the mill’s working capital.
Just by looking at the cost curve, you can learn some important lessons about manufacturing. For instance, even though Bravo 1 is an efficient producer, the company may not want to expand capacity there. Doing so could drive the higher-cost Alpha 2 out of the market, thus driving the price down, a development that would hurt Bravo 1 more than the additional tonnage sold would help it. 3 Conversely, consider what would happen if a producer such as Alpha were to remove a bit of high-cost capacity from the market —say, by shutting down the Alpha 2 mill. Suddenly, Romeo’s mill would have to enter the market to soak up Alpha 2’s sales. The market price would rise to $1,200— the cost of production at the unbuilt Bravo mill—causing the Alpha 1 mill to earn far higher proﬁts. Thus, from Alpha’s point of view, shutting down Alpha 2 wouldn’t be such a bad idea.
A semi-humorous example is the marijuana-growing industry in B.C. Like the yellow writing pads there is a certain amount of capacity, input costs, and transportation cost considerations. As an export industry, the B.C. marijuana producers are exposed to the rise and fall of the Canadian dollar vis a vis the U.S. dollar. Furthermore, unlike pulp and paper or other very high capital cost industries, the capital barriers to entry are relatively low, inviting new capacity to service any growth in demand. Conversely, because sunk capital costs are low, pushing capacity out of the market is less difficult than in industries with high sunk capital costs where players seek to earn anything above their variable costs in order to earn something on their sunk fixed cost investments.
As an industry, they also face some interesting strategic risks. For example, in 2010 Proposition 19 was narrowly defeated in California, which would have legalized personal production of the plant, undercutting a vast export market. Another unintended consequence of the fall in U.S. real estate prices is the much lower cost of establishing a grow-op in a suburban house. Of course the biggest factor is the price premium enjoyed by growers due to the illegal nature of the product itself.