Mapping a profit pool involves four steps: defining the pool’s boundaries, estimating the pool’s overall size, estimating the size of each value-chain activity in the pool, and checking and reconciling the calculations.
A company that operates call centers to handle telephone orders for catalog retailers, for example, may in the future be able to fulfill customer service functions for electric utilities or transportation carriers. And, just as important, it may one day face a competitive threat from companies in other industries, such as telephone companies, cable television operators, or even Internet service providers. The call-center operator should, therefore, define its profit pool to include not only those value chain activities traditionally associated with direct-mail retailing but also activities in other industries that could influence its future creation of profits.
Finally, you should take a step back to look at your industry through the eyes of the customer. How would the customer define the life cycle of the product or service you produce? Often, a customer will define your industry to include activities that you would consider peripheral. If a paint manufacturer, for example, asks homeowners about the experience of buying and using paint, it may find that the disposal of leftover paint is an important activity from their perspective. Disposal requirements may influence the kinds of paint they buy and thus may have a direct impact on the paint industry’s profit pool. The manufacturer would be wise to include paint disposal as part of its value chain.
In addition to deciding which activities to include, a company needs to decide the proper level of aggregation for each activity. In the automotive industry, for example, financial service activities, such as lending, leasing, and renting, make up an important part of the profit pool. Do you define those activities as a single value-chain segment or do you look at them individually? The answer depends on the business you’re in. A chain of auto parts stores would probably not need to divide the financial service segment into its component activities—after all, the company would not be likely to participate in any of those activities. A used car dealer, however, might well want to break down the financial services segment into the narrower segments of lending, leasing, and renting. Because the dealer controls an important point of customer contact, it may decide to enter one or more of these activities in the future. It may also find itself competing with a participant in one of these activities—say, a new car dealer that needs to sell used cars coming off their leases.
The pool you draw must be tailored to fit the strategic questions you face.
Therefore, it is always advisable to develop estimates based on at least two different views of an industry. Try to develop estimates based, for example, on players and products. You can then compare the estimates to ensure they’re in the same ballpark.
Determining the way profits are distributed among different value-chain activities is the core challenge of profit-pool mapping. There are two general analytical approaches to this task: aggregation and disaggregation. If you are in an industry in which all the companies focus on a single value-chain activity—in which all are, in other words, “pure players”—you will calculate activity profitability by aggregating the profits of all the pure players. If, by contrast, all the companies in your industry are vertically integrated “mixed players,” each performing many different activities, you will need to disaggregate each company’s financial data to arrive at estimates for a specific activity.
You should always look first at any pure players. Once you know their revenues, costs, and profits, you’ll have an economic yardstick for measuring the activity in which they specialize. You can then look at the mixed players. In some cases, they will report their financial information by activity, making your work easier. In other cases, however, the information they report will be aggregated—you’ll need to break it down by activity. To accomplish that, you can often use what you learned about the margins and cost structure of the pure players to make accurate assumptions about the mixed players’ economics for a given activity, taking into account their particular competitive advantages and disadvantages. For activities in which your company participates, you may also be able to use your own economics as a yardstick.
You won’t need to collect data on all the companies participating in all the value chain activities. In most industries, the 80/20 rule will apply: 20% of the companies will account for 80% of the revenues. By collecting data on the largest companies, you will likely have covered most of the industry. You can then extrapolate the economic data for the smaller companies by collecting data on a sample of them. Once you have the data on your own company, the large pure players, the large mixed players, and a sample of the smaller companies, you add up the figures, activity by activity, to arrive at overall estimates.
Sometimes, it will actually be easier to gather financial data on products, customers, or channels than on companies. This is often the case in industries characterized by a high degree of vertical integration. In such cases, you should go where the data are. If you can get detailed data on the economics of different product types, for example, you can allocate costs, revenues, and profits to different activities at the product level. Then you add up the numbers, activity by activity, to arrive at total estimates. As with company data, the process is a matter of aggregating and disaggregating.
Profit-pool maps and mosaics are only snapshots, of course. They show us the shape of the pool as it exists today, but they don’t show us how the pool has been changing. To get a more dynamic view—which is essential for strategy development—we need to plot similar charts for the profit pool at earlier points in time. To develop such comparison charts, we go through the same steps of data collection and analysis; we just use data from an earlier year. By seeing how the pool’s shape has changed—where profits have increased or diminished, who’s been gaining or losing profits—we can often infer which competitive, economic, and other forces have been shaping the industry’s profit structure.
Knowing the distribution of profits along the value chain provides you with the broadest view of profit trends in your industry. Such a view is essential for identifying structural shifts that could influence the profits available to you and your competitors in the future. It is important to note, however, that profits concentrate not just in particular value-chain activities but also in particular product types, customer segments, distribution channels, and geographic regions. To develop the fullest possible understanding of your profit pool, you will want to map the pool along some, if not all, of these dimensions as well.