How to Map Your Industry’s Profit Pool

Many managers chart strategy without a full understanding of the sources and distribution of profits in their industry. Sometimes, they focus their sights on revenues instead of profits, assuming that revenue growth will eventually translate into profit growth. In other cases, they simply lack the data or the analytical tools required to isolate and measure variations in profitability. Whatever the cause, an incomplete understanding of profits can create blind spots in a company’s strategic vision, leading it to overlook attractive profit-building opportunities or to become trapped in areas of weak or fading profitability. In this article, we will describe a useful framework for analyzing how profits are distributed among the various activities that form an industry’s value chain. Such an analysis can provide a company’s managers with a rich understanding of their industry’s profit structure—what we call its profit pool—enabling them to identify which activities are generating disproportionately large or small shares of profits. Even more important, a profit-pool map opens a window onto the underlying structure of the industry, helping managers see the economic and competitive forces that are determining the distribution of profits. As such, a profit-pool map provides a solid basis for strategic thinking. (See our article “Profit Pools: A Fresh Look at Strategy” in the May–June 1998 HBR.) Mapping a profit pool is, in one sense, a straightforward exercise: you define the value chain activities and then you determine their size and profitability. But while the goal is simple, achieving it can be complicated. Why? Because in most industries, financial data are not reported in nice, neat bundles corresponding to each value-chain activity. Detailed data may be available on individual companies, but those companies will often participate in many different activities. Similarly, there may be good information on product sales or customer purchases or channel volumes, but the products, customers, and channels will rarely line up cleanly with the boundaries of a particular activity. Translating the available data into accurate estimates of an activity’s size and profitability requires considerable creativity. Although no two companies will perform the analysis in precisely the same way, it is possible to describe a broadly applicable process for getting the answers—a process that lays out the tasks that need to be accomplished, the questions that need to be asked, the types of data that need to be collected, and the types of analyses that need to be done. A Four-Step Process 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. (See the chart “Mapping a Profit Pool.”) We will describe each step and then provide an example of how the entire process is applied. Finally, we will look at ways of organizing the data in chart form as a first step toward plotting a profit-pool strategy. Mapping A Profit Pool Define the pool. Before you can start analyzing your industry’s profit pool, you need to define its boundaries by identifying the value-chain activities that are relevant to your own business. Where, for purposes of developing strategy, should the value chain be said to begin and to end? At the conclusion of this step, you should have a clearly defined list of the individual value-chain activities that make up your profit pool. The key is to define the value chain broadly enough to capture all the activities that have a meaningful influence on your ability to earn profits—not just today but in the future as well. You should begin by taking a close look at your own business, breaking it down into its discrete value-chain activities. But you shouldn’t stop there. Because there are many ways to compete in any industry—and new ways are being thought up all the time—you should also look at the activities of your competitors and potential competitors. Have other companies in your industry adopted business models that involve different sets of activities? Might you have opportunities to perform new activities in your industry or in other industries? Are there activities being performed in other industries that could displace or substitute for the activities you are performing? 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. Defining the bounds of a profit pool requires, in short, not just analytical skills but also good, basic business judgment. The pool you draw must be tailored to fit the strategic questions you face. Determine the size of the pool. Once you have defined the profit pool, you need to determine its overall size. What is the total amount of profits being earned in all the value chain activities? At this point, all you need is a rough estimate of total industry profits. The idea is to establish a baseline against which you can check the reliability of the more detailed, activity-by-activity calculations you will make later. If you’re lucky, you may be able to estimate the size of the pool by reading a few industry reports from stock analysts or other researchers. Or you may be able to find a reliable estimate of overall industry revenues and then apply an assumed industry-average margin to it. Usually, though, developing this estimate will not be so straightforward. The way you define your profit pool is unlikely to coincide precisely with any traditional industry definition. Moreover, the financial data you require may not be readily available in the form you need. How you define your profit pool is unlikely to coincide precisely with any traditional industry definition. A good idea in these situations is to try to build up estimates of the total pool based on the profitability of individual companies, products, channels, or regions. You should always try to focus first on the biggest pieces—the largest companies or the highest-volume products, for example. If there are large public companies that account for a significant proportion of industry profits, use their financial statements as a starting point. To gauge the profits of the smaller players, you adjust the leaders’ margins—to reflect the smaller players’ competitive advantages or disadvantages—and then apply the adjusted margin to the remaining industry revenues. You then add the leaders’ actual profits to your estimate of the total profits of the smaller companies to gain an overall estimate of industry profits. (See the insert “What Is ‘Profit’ Anyway?”) What Is “Profit” Anyway? Today there are almost as many ways to define profit as there are to make it. For practical purposes, though, managers tend to think about profit in one of three ways: as accounting profit, as return on investment, or as cash-flow contribution. Because each of the measures can be used as the basis for management decisions, they all can be important in profit-pool mapping. Accounting profit represents a company’s earnings as formally reported. It is the measurement method underlying net-income and earnings-per-share calculations in shareholder reports and other official filings. Its precise method of calculation can vary, depending on the accounting standards specific to a given industry or country. Return on investment represents a company’s earnings after taking into account the cost of capital invested in the business. Because ROI represents the true profit associated with investment in an industry, it is an essential measure for evaluating potential new investments. It can be measured using a number of different methodologies, which all have advantages and disadvantages. One of the most useful ROI measures is economic value-added (EVA), which equals after-tax operating profits minus the cost of all invested capital. Because EVA expresses returns as an absolute profit value rather than as a percentage, it lends itself well to profit-pool mapping. Cash-flow contribution is, in general, a company’s earnings before taking fixed-asset and capital costs into account. It is frequently expressed as earnings before income taxes, depreciation, and amortization (EBITDA). In some cases, fixed operating costs, such as overhead, are also subtracted. An incremental measure, it represents the amount of cash left from a sale after subtracting the variable costs associated with that sale. Cash-flow contribution is frequently used as the basis for management decision making in mature, high-fixed-cost, and cyclical industries, particularly during down cycles. It is also a useful profit measure for companies that are investing to gain market share and for those that are engaged in leveraged buyouts. Developing detailed profit-pool maps using all three measures would be a forbiddingly complex undertaking. In most cases, fortunately, it is sufficient to use just one basis of measurement for in-depth mapping. Other relevant measures can then be roughly estimated as needed. Most companies will use accounting profit as their basic measure because that’s the form in which profit data are generally reported. However, when a company’s profit pool extends across industries or countries, managers need to be aware of and take into account possible differences in accounting standards. The goal should always be to measure profit consistently across the entire pool. While a high degree of precision isn’t necessary at this point, you do need to have confidence in the general accuracy of the estimate. 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. The more data you have and the more analytical approaches you take, the more accurate your estimate will be. Determine the distribution of profits. 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. Determining the distribution of profits among value chain activities is the core challenge. In reality, of course, most industries include a combination of pure players and mixed players. Your analysis, therefore, will likely include both aggregation and disaggregation. At some stages, you’ll be tearing data apart. At others, you’ll be building it up. You start, once again, by looking at the economics of your own company, examining revenues, costs, and profits by activity. If you’re a pure player, this won’t take much work—all your revenues and costs will be allocated to the same activity. If you’re involved in many activities and your financial-reporting system does not clearly distinguish among them, you will need to disentangle your revenues and costs. In companies whose fixed costs are shared by a number of different activities, as is the case in many financial-services institutions, allocating costs will likely require not only careful analysis but also some in-depth thinking about the structure of the business. Now you look outside your company to examine the economics of other players in the industry. Although the sources of company data will vary by industry, there are some common places to look. You will draw on annual reports, 10-K filings, and stock-analyst reports (for public companies), as well as company profiles by research organizations such as Dun & Bradstreet, reports by industry associations, and trade magazines. For regulated industries, the government can be a good source. And in some industries, there are companies that specialize in collecting and reporting detailed financial information. If data are unavailable on a company, you may need to estimate its profitability based on the performance of a similar company for which data are available. 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. At the end of this step, the shape of your profit pool should be clear. You will know the profits—as well as the revenues, costs, and margins—of each value-chain activity. And you will know how your own economics stack up to the averages, activity by activity. Reconcile the estimates. The fourth and final step in the analysis serves as a reality check. You add up the profit estimates for each activity, and you compare the total with the overall estimate of industry profits you developed earlier. If there are discrepancies, you need to go back and check your assumptions and calculations and, if necessary, collect additional data. Don’t be surprised if you have to spend considerable time reconciling the numbers. Because you will often have made your estimates in an indirect way, based on fragmented or incomplete data, discrepancies will be common. Applying the Process: The RegionBank Case To show how a company would actually use this process, let’s put ourselves in the shoes of the managers of RegionBank, a hypothetical retail bank based in the midwestern United States. RegionBank is in a tight spot. Fundamental changes in the financial services industry have undermined the traditional advantages of its vertically integrated, regionally focused business model. Powerful national product specialists—MBNA in credit cards, Fidelity in mutual funds, Countrywide Mortgage in mortgage lending—are stealing away many of its best customers. New distribution channels, such as telephone and on-line banking, threaten to render its expensive network of local branches obsolete. Even its back-office transactional functions, like credit card processing, are under attack from highly efficient specialists such as First Data Corporation. As RegionBank’s management team, we know we cannot simply stay the course, hoping for the best. As margins narrow, our current business model seems unsustainable. But to develop a new model—one that will allow us to carve out and hold on to a substantial piece of the banking industry’s rapidly shifting profit pool—we need to have a thorough understanding of the industry and its patterns of profit creation. Where in the banking value chain are attractive profits being generated? Why is the profitability of some banking activities rising while the profitability of others is falling? Which companies are capturing the profits? What are their business models? Only after we know where and how profits are being made—and by whom—will we be in a position to think about the forces shaping our industry and to make rational decisions about our strategic direction. Define the pool. We start by setting the bounds of our profit pool. After looking at the activities we perform, the activities performed by current and potential competitors, and the ways customers perceive our business, we see that our industry is broader than the regional banking industry as traditionally defined. It encompasses the entire U.S. consumer-financial-services industry, which can be viewed as including three core activities: acquiring customers through branches or other channels (acquisition); lending and managing money (for simplicity, we’ll call this activity funding); and delivering a variety of related back-room services, such as transactions and reporting (servicing). These activities define RegionBank’s playing field, and by focusing on them we will have the necessary breadth of vision to answer the question on which all our strategic decisions turn: Where in consumer financial services will companies be able to make money? Determine the size of the pool. To develop a rough but accurate estimate of our profit pool, we undertake two different analyses. We determine the cumulative profits generated by all the industry’s major products, and then we determine the cumulative profits earned by all the companies competing in the three industry activities. We choose products and players for a simple reason: those are the ways financial data are typically reported in the industry. First, we examine products. We know that the consumer-financial-services industry, as we have defined it, has five major product categories: credit cards, mortgages, deposits, mutual funds, and consumer loans. Sales and profitability data for each of these categories are reported regularly by the federal government as well as by private data-reporting companies, making data collection a simple exercise. Similarly, when we turn to the players, we know that companies in the industry are required to report their financial information in considerable detail. By looking at the largest players individually and extrapolating from a sample of the smaller players, we are able to quickly estimate total profits. Both methodologies yield a similar range of estimates for the size of the profit pool—between $ 60 billion and $ 70 billion—so we are confident that we have a reliable estimate. Determine the distribution of profits. Now we have an estimate of the size of RegionBank’s current industry profit pool—in total and by product and player. What we don’t have, however, is an understanding of how the pool is distributed among the three value-chain activities: acquisition, funding, and servicing. This leads to our first major analytical problem. In consumer financial services, revenue and profit information simply isn’t available for individual value-chain activities. Rather, as we saw before, financial information is organized by company and by product type. We will not, therefore, be able to measure value chain activities directly. Instead, we will have to construct five different profit pools—one for each major product category—and divide each pool into the three activities. We will then be able to add up the activity data for each product to gain an industrywide measure of activity profitability. For the sake of illustration, let’s take one product—credit cards—and walk through the way we determine the distribution of its profit pool. We start by gathering profit and revenue data for all the key players in the credit card business: card issuers, subscriber and merchant acquirers, and customer and account servicers. Because RegionBank is itself an issuer of credit cards, we can use our internal financial data as a benchmark for credit card profitability. Since there are literally thousands of credit card issuers, it would not be practicable to collect financial information on all of them. We therefore pursue an 80/20 approach, collecting data on all the major industry players but analyzing only a sample of the smaller players. To ensure that we don’t overlook any important competitors, we take the time to talk to people representing different aspects of the industry, including leading banks in overseas markets and companies in related industries such as home equity lending. We need to remember, as we pull together the information, that competition in our industry is shifting rapidly, with many kinds of new players entering the fray. As the strategic landscape evolves, new competitors and new services could present threats or opportunities to RegionBank. Failing to consider them now could be costly. Once we have profit data for all the relevant players in the credit card industry, we need to disaggregate the data by value chain segment. (See the chart “Untangling the Credit-Card Value Chain.”) We use a different calculation method for each segment: Untangling The Credit-Card Value Chain The credit-card value chain encompasses three business activities. As a result of variations in the type of data available, the profits generated in each activity need to be calculated in very different ways. Servicing. Because there are several large, public companies that specialize in credit card servicing—pure players—servicing is the easiest of the three segments for which to estimate profits. So it’s a good place to start. We know, from our own experience as a card issuer, that a typical issuer pays approximately $ 60 per subscriber per year to third-party processors to handle transaction processing, statement generation, and all the other back-office tasks associated with that subscriber. By studying the financial statements of the pure players, we find that their average pretax margin for servicing is 17 % , indicating that about $ 10 per year in servicing profits are generated per subscriber ( $ 60 × .17). Given the roughly 260 million credit-card subscribers in the United States, this works out to $ 2.6 billion in annual servicing profits. Acquisition. There are no pure players in credit card acquisition, so we need to be a little more creative here. By examining recent purchases of credit-card-subscriber portfolios, we find that the price paid, per subscriber, is approximately $ 80. We also know, from our own experience and from general industry studies, that the average cost of gaining a new card subscriber is in the neighborhood of $ 64, which indicates that the acquisition profit per card is $ 16. Amortizing this figure over the average life of a subscriber account (five years) yields $ 3.20 in annual acquisition profits per subscriber, or $ 800 million for the entire credit-card business. Funding. Finally, to estimate funding profits, we detail all the revenues and costs associated with funding a credit card—in other words, we create a profit and loss statement for a card. The data required for this exercise are reported in the secondary markets where card portfolios are bought and sold. First, we add up all the annual revenues accruing to a typical card from interest, annual fees and other charges, and merchant payments ( $ 279), and then we subtract all the costs associated with that card ( $ 235), many of which, such as acquiring and servicing, we have already detailed. We arrive at an annual funding profit of $ 44 per subscriber, or $ 11.4 billion in total. We now have categorized the credit card profit pool by value chain activity: $ 800 million for acquisition, $ 11.4 billion for funding, and $ 2.6 billion for servicing. We make similar calculations for each of the other four product categories—mortgages, deposits, mutual funds, and consumer loans—and we add up the totals to establish estimates for the size of each activity in the consumer-financial-services industry: $ 10.0 billion in acquisition, $ 42.4 billion in funding, and $ 10.4 billion in servicing. We now know the current shape of our profit pool. Reconcile the estimates. As a reality check, we add up the activity totals ( $ 63 billion) and compare the sum with our initial estimate of the industry profit pool (between $ 60 billion and $ 70 billion). The numbers jibe, so we are confident that our estimates are reasonable. Visualizing the Profit Pool As the end product of profit-pool mapping—and the starting point of strategy development—you will want to portray the data you’ve collected in a series of charts. Visualizing the profit pool makes it easier to spot areas of disproportionately large and disproportionately small profits and to identify trends influencing the distribution of profits. The resulting insights can form the basis for the development of a strategy that will enable a company to capitalize on or even control the direction of profit-pool shifts. There are several different ways to chart a profit pool, each of which provides different insights. One of the simplest but most useful charts is what we call a profit-pool map, in which profit distribution is compared with revenue distribution. (See the chart “RegionBank’s Profit-Pool Map.”) The map takes the form of a series of building blocks—each representing a value chain activity—plotted on a graph. The horizontal axis of the graph represents the percentage of industry revenues, and the vertical axis represents operating margins. Thus the width of each block indicates the activity’s share of total industry revenues, its height indicates the activity’s profitability, and its area indicates the activity’s total profits. RegionBank’s Profit-Pool Map A profit-pool map compares a value chain activity’s revenues with its profitability. By developing a map of the current U.S. consumer-financial-services industry, RegionBank is able to see the profits being generated by acquisition, funding, and servicing activities. By comparing this map with a map from an earlier point in time, the company will be able to spot trends in profit distribution. The profit-pool map portrays the distribution of profits and revenues along a single dimension: value chain activity. It will often be useful, however, to chart the profit pool along two dimensions simultaneously. In RegionBank’s case, for example, we know that many new players—product specialists, servicing specialists, and various other nontraditional competitors—have entered the industry in recent years. It would therefore be illuminating to see how industry profits are distributed among different types of companies as well as among different value-chain activities. To visualize a profit pool in two dimensions, we can create a graph that we call a profit-pool mosaic. (See the chart “RegionBank’s Profit-Pool Mosaic.”) RegionBank’s Profit-Pool Mosaic A profit-pool mosaic reveals the distribution of an industry’s profits along two dimensions. RegionBank uses a mosaic to see the profits being earned by different types of companies within each of the three core value-chain activities in its industry. In a profit-pool mosaic, the total area of the chart equals 100 % of industry profits (in RegionBank’s case, $ 63 billion). The horizontal axis indicates the percentage of total industry profits created in each activity—roughly 67 % in funding, 17 % in servicing, and 16 % in acquisition—and the vertical axis shows the percentage of profits created by company type within an activity. (Depending on a company’s particular situation and challenges, other dimensions, such as products, channels, and geographic regions, can be plotted in a mosaic.) By looking at the mosaic, we can see not only how much money is being made, activity by activity, but also who’s making it. 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. In turn, we can project how these forces might reshape the pool in the future. It is often a useful exercise, in fact, to plot a projected profit pool. If your industry is stable, with no major uncertainties on the horizon, you will probably need to develop only a single view of the future, projecting future profit data based on current trends. If there’s a lot of uncertainty in your industry, you should develop a range of possible views of the future. For instance, RegionBank might create a series of mosaic charts representing different scenarios for how its industry might look in five years. Practically speaking, you won’t be able to chart all the possible future permutations of a profit pool. We have found, though, that plotting three to five scenarios, representing a range of possibilities, is enough to provide valuable guidance in strategy development. A Foundation for Strategy Profit-pool mapping reveals the location and size of profit concentrations within an industry and sheds light on how those concentrations might shift. We have focused on analyzing the pool in terms of value chain activity. 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. As even our simplified RegionBank case indicates, profit-pool mapping often requires a considerable investment of time. And, since every business situation is unique, tough questions about scope and methodology will need to be answered at every step of the analysis. But mapping your profit pool will provide you with important benefits. You’ll gain a new store of strategic information and, even more important, a more creative approach to strategy formulation. The sheer act of defining, categorizing, and mapping a pool can stir the thinking of your management team, leading it to challenge old assumptions and to generate valuable new business insights. When you define the shape of today’s profit pool, you refine and deepen your knowledge of the mechanics of your industry—where profits are created, how they’re created, and who’s creating them. And when you think through the forces shaping the pool, you identify and isolate the most critical drivers of future industry profitability. Ultimately, the discipline of profit-pool mapping rewards you with a richer view of your business and where you might lead it.

How to Map Your Industry’s Profit Pool

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