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FOR DISCLOSURES AND OTHER IMPORTANT INFORMATION, PLEASE REFER TO THE BACK OF THIS REPORT. November 1, 2016 GLOBAL FINANCIAL STRA TEGIES www.credit -suisse.com Measuring the Moat Assessing the Magnitude and Sustainability of Value Creation Authors Michael J. Mauboussin michael.mauboussin@credit -suisse.com Dan Callahan, CFA daniel.callahan@credit -suisse.com Darius Majd darius.majd@credit -suisse.com “The most important thing to me is figuring out how big a moa t there is around the business. What I love, of course, is a big castle and a big moat with piranhas and crocodiles. ” Warren E. Buffett Linda Grant, “Striking Out at Wall Street,” U.S. News & World Report , June 12, 1994 Sustainable value creation is of prime interest to investors who seek to anticipate expectations revisions. This report develops a systematic framework to determine the size of a company’s moat. We cover industry analysis, firm -specific analysis, and firm interaction. November 1, 2016 Measuring the Moat 2 Table of Contents Executive Summary ................................ ................................ ................................ ................................ 3 Introduction ................................ ................................ ................................ ................................ ............ 4 Competitive Life Cycle ................................ ................................ ................................ ................. 4 Economic Moat s ................................ ................................ ................................ ......................... 7 What Dictates a Company’s Destiny ? ................................ ................................ ........................... 8 Industry Analysis ................................ ................................ ................................ ................................ ... 10 The Lay of the Land ................................ ................................ ................................ .................. 11 Industry Map ................................ ................................ ................................ ................. 11 Profit Pool ................................ ................................ ................................ .................... 13 Industry Stability ................................ ................................ ................................ ............ 15 Industry Classification ................................ ................................ ................................ .... 17 Industry Structure – Five Forces Analysis ................................ ................................ .................... 18 Entry and Exit ................................ ................................ ................................ ............... 19 Competitive Rivalry ................................ ................................ ................................ ........ 25 Disruption and Disintegration ................................ ................................ ................................ ..... 27 Firm -Specific Analysis ................................ ................................ ................................ ........................... 32 A Framework for Added -Value Analysis ................................ ................................ ...................... 32 Value Chain ................................ ................................ ................................ .............................. 33 Sources of Added Value ................................ ................................ ................................ ............ 34 Production Advantages ................................ ................................ ................................ .. 34 Consumer Advantages ................................ ................................ ................................ ... 38 Government ................................ ................................ ................................ .................. 41 Firm Interaction – Competition and Cooperation ................................ ................................ ...................... 42 Brands ................................ ................................ ................................ ................................ ................. 46 Management Skill and Luck ................................ ................................ ................................ ................... 48 Regression Toward the Mean ................................ ................................ ................................ ................ 50 Bringing It All Back Together ................................ ................................ ................................ ................. 51 Warren Buffett on Economic Moats ................................ ................................ ................................ ........ 52 Appendix A: Checklist for Assessing Value Creation ................................ ................................ ................ 53 Appendix B: Profit Pool Analysis for Health Care ................................ ................................ ..................... 55 Endnotes ................................ ................................ ................................ ................................ ............. 59 References ................................ ................................ ................................ ................................ .......... 65 Books ................................ ................................ ................................ ................................ ...... 65 Articles and Papers ................................ ................................ ................................ ................... 69 November 1, 2016 Measuring the Moat 3 Executive Summary Sustainable value creation has two dimensions : the magnitude of the spread between a company’s return on invested capital and the cost of capital and how long it can maintain a positive spread . Both dimensions are of prime interest to investors and corporate executives. Sustainable value creation as the result solely of managerial skill is rare. Competitive forces and endogenous variance drive returns toward the cost of capital. Investors should be careful about how much they pay for future value creation. Warren Buffett consistently emphasizes that he wants to buy businesses with prospects for sustainable value creation. He suggests that buying a business is like buying a castle surrounded by a moat and that he wants the moat to be deep and wide to fend off all competitio n. Economi c moats are almost never stable. Because of c ompetit ion, they are getting a little bit wider or narrower every day. This report develops a systematic framework to determine the size of a company’s moat. Companies and investors use competitive st rategy analysis for two very different purposes. Companies try to generate returns in excess of the cost of capital , while investors try to anticipate revisions in expectations for financial performance . If a company’s share price already captures its pros pects for sustainable value creation, inve stors should expect to earn a market rate of return , adjusted for risk . Industry effects are the most important in the sustainability of high performance and a close second in the emergence of high performance. Ho wever, industry effects are much smaller than firm -specific factors for low performers . For companies that are below average, strategies and resources explain 90 percent or more of their returns. The i ndustry is the correct place to start an analysis of sustainable value creation. We recommend understanding the lay of the land , which includes getting a grasp o f the participants and how they interact , an analysis of profit pools, and an assessment of industry stability . We follow this with an analysis of the five forces and a discussion of the disruptive innovation framework . A clear understanding of how a company creates shareholder value is core to understanding sustainable value creation. We define three broad sources of added value: production advanta ges, consumer advantages, and external advantages. How firms interact plays a vital role in shaping sustainable value creation. We consider interaction through game theory , co -opetition, and co -evolution . Brands do not confer competitive advantage in and of themselves . Customers hire them to do a specific job. Brands that do those jobs reliably and cost effectively thrive. Brands only add value if they increase customer willingness to pay or if they reduce the cost to provide the good or service. Regression toward the mean is a powerful force. Empirical results show which industries regress at the fastest rate, providing a useful quantitative complement to the qualitative assessment here. Appendix A provides a complete checklist of questions to g uide the strategic analysis. November 1, 2016 Measuring the Moat 4 Introduction Corporate managers seek to allocate resources so as to generate attractive long -term returns on inve stment. Investors search for stocks of companies that are mispriced relative to expectations for financial results embedded in the shares. In both cases, sustainable value creation is of prime interest. What exactly is sustainable value creation? We can think of it in two dimensions. First is the magnitude of returns in excess of the co st of capital that a company does , or will, generate. Magnitude considers not only the return on investment but also how much a company can invest at a rate above the cost of capital . Growth only creates value when a company generates returns on investm ent that exceed the cost of capital. The second dimension of sustainable value creation is how long a company can earn returns in excess of the cost of capital. This concept is also known as fade rate, competitive advantage period (CAP), value growth dura tion, and T. 1 Despite the unq uestionable significance of the longevity dimension, researchers and investors give it insufficient attention. How is sustainable value creation distinct from the more popular notion of sustainable competitive advantage? A company must have two characteristics to claim that it has a competitive advantage. The first is that it must generate , or have an ability to generate , returns in excess of the cost of capital. Second , the company must earn an economic return that is higher than the average of its competitors. 2 As our focus is on sustainable value creation, we want to understand a company’s economic performance relative to the cost of capital, not relative to its competitors . Naturally , these concepts are closely linked. Sustainable value creation is rare , and sustainable competitive advantage is even rare r. Competitive Life Cycle We can visualize sustainable value creation by looking at a company’s competitive life cycle. (See Exhibit 1.) Companies are generally in one of four phases : Innovation. Young companies typically realize a rapid rise in return on investment and significant investment opportunities. Substantial entry into and exit out of the industry are common at this point in the life cycle. Fading returns. High returns attract competition, generally causi ng economic returns to move toward the cost of capital. In this phase, companies still earn excess returns, but the return trajectory is down. Investment needs also moderate , and the rate of entry and exit slows. Mature. In this phase, the market in which the compan ies compete approach es competitive equilibrium. As a result, companies earn a return on investment similar to the industry average , and competition within the industry ensures that aggregate returns are no higher. Investment needs continue to moderate. Subpar. Competitive forces and technological change can drive returns below the cost of capital, requiring companies to re structure. These companies can improve returns by shedding assets, shifting their business model, reducing investment levels, or putting themselves up for sale. Alternatively, these firms can file for bankruptcy to reorganize the business or liquidate the firm’s asse ts. November 1, 2016 Measuring the Moat 5 Exhibit 1: A Firm’s Competitive Life Cycle Source: Credit Suisse HOLT ®. Regression toward the mean says that an outcome that is far from average will be followed by an outcome that has an expected value closer to the average. There are two explanations for regression toward the mean in corporate performance. The first is purely statistical. If the correlation between cash flow return on investment (CFR OI ®) in two consecutive years is not perfect, there is regression toward the mean. Think of it this way : there are aspects of running the business within management’s control, including selecting the product markets it choose s to compete in, pricing, in vestment spending, and overall execution. Call that skill. There are also aspects of the business that are beyond management’s control, such as macroeconomic developments, customer reactions, and technological change. Call that luck. Whenever luck contribu tes to outcomes, there is regression toward the mean. If year -to-year CFROIs are highly correlated, regression toward the mean happens slowly. If CFROIs are volatile , causing the correlation to be low, regression toward the mean is rapid. The second explanation for regression toward the mean is that competition drives a company’s return on investment toward the opportunity cost of capital . This is based on microeconomic theory and is intuitive. The idea is that companies that generat e a hig h economic return will attract competitors willing to take a lesser, albeit still attractive, return. Ultimately, this process drives industry returns toward the opportunity cost of capital. Researchers have documented the accuracy of this prediction. 3 Com panies must find a way to defy these powerful competitive forces in order to achieve sustainable value creation. Re cent research on the rate of regression reveals some important observations . First, the time that an average company can sustain excess returns is shrinking. This phenomenon is not relegated to high technology but is evident across a wide range of industries. 4 This reduction in the period of sustain ed value creation reflects the greater pace of innovation brought about in part by increased access to , and utilizat ion of , information technology.  CFROI ® is a registered trademark in the United States and other countries (excluding the United Kingdom) of Credit Sui sse Group AG or its affiliates. Above -Average but Fading Returns Below -Average Returns Average Returns High Innovation Fading Returns Mature Needs Restructuring Economic Return Discount Rate (Required Rate of Return) Reinvestment Rates November 1, 2016 Measuring the Moat 6 Second, the absolute level of returns and the level of i nvest ment are positively related to the rate of fade. 5 A company that generates a high return on investment while investing heavily signals an attract ive opportunity to both existing and potential competitors. Success sows the seeds of competition. Why is sustainable value creation so important for investors? To start, investors pay for value creation. Exhibit 2 looks at the S&P 500 since 1961 and provides a proxy for how much value creation investors have been willing to pay for. We establish a stea dy -state value by capitalizing the last four quarters of operating net income for the S&P 500 by an estimate of the cost of equity capital. 6 We then attribute any value above the steady -state to expected value creation. The exhibit shows that 40 percent of the value of the S&P 500 today reflects anticipated value creation, above the average of the last 55 years. Following a sharp drop in 2011 to a level near a 50 -year low, the expectations for value creation have risen to a level modestly above the long -term average. Exhibit 2: Rolling Four Quarter Anticipated Value Creation , 1961 -2017E Source: Standard & Poo r’s, Aswath Damodaran, Credit Suisse. Note: As of November 1, 2016. More significant, sustained value creation is an important source of expectations revisions. There is a crucial distinction between product markets and capital markets. Companies try to understand the industry and competitive landscape in their product markets so as to allocate resources in a way that maximizes long -term economic profit. Investors seek to understand whether today’s price properly reflects the future and whether expect ations are likely to be revised up or down. Companies and investors use competitive strategy analysis for two very different purposes. Companies try to generate returns above the cost of capital, while investors try to anticipate revisions in expectations . Investors -20 -10 0 10 20 30 40 50 60 70 1961 1963 1965 1967 1969 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015 2017 Anticipated Value Creation (%) 2 standard deviations 2 standard deviations Average Current November 1, 2016 Measuring the Moat 7 should anticipate earning a market return, adjusted for risk, i f a company’s share price already captures its prospects for sustainable value creation. But companies that can create value longer than the market expects generate excess returns w ith volatility that is lower than expected. 7 We will spend most of our time trying to understand how and why companies attain sustainable value creation in product markets. But we should never lose sight of the fact that our goal as investors is to antici pate revisions in expectations. Exhibit 3 shows the process and emphasizes the goal of finding and exploiting expectations mismatches. Exhibit 3: The Link between Market Expectations and Competitive Strategy Source: Credit Suisse. Economic Moats Warren Buffett , the chairman of Berkshire Hathaway, has emphasized over the years that he looks for businesses with sustainable competitive advantage s. He suggests that buying a business is akin to buying a castle surrounded by a moat. Buffett wants the ec onomic moat to be deep and wide to fend off all competition. He goes a step further by noting that economic moats are almost never stable . Moats either get a little bit wider or a little bit narrower every day .8 This report develop s a systematic framework to determine the size of a company’s moat. Market -Implied Expectations for Value Creation Industry Analysis Firm -Specific Analysis Potential for Expectations Revisions November 1, 2016 Measuring the Moat 8 What Dictates a Company ’s Destiny? Peter Lynch , who skillfully ran Fidelity’s Magellan mutual fund for more than a decade , quipped that investors are well advised to buy a business that’ s so good that an idiot can ru n it, because sooner or later an idiot will run it. 9 Lynch’s comment introduces an important question: What dictates a firm’s economic returns? We are not asking what determines a company’s share price performance , which is a function of expectations revisions, but rather its economic profitability. 10 Before we answer the question, we can make some empirical observations. The top panel of Exhibit 4 shows the spread between CFROI and the cost of capital for 6 8 global industries, as defined by MSCI ’s Global Industry Classification Standard (GIC S), using median returns over the past five fiscal years . The sample includes more than 10 ,000 public companies. We see that some industries have positive economic return spreads, some are neutral, and some don’t earn the cost of capital. Exhibit 4: Industry Returns Vary from Value -Creating to Value -Destroying Source: Credit Suisse HOLT. Note: Data through latest fiscal year as of 10/25/16. The bottom panel of Exhibit 4 shows the spread between CFROI and the cost of capital for the companies in three industries: one that creates value , one that is value neutral, and one that destroys value . The central observation is that even the best industries include companies that destroy value and the worst industries have companies that create value. That some companies buck the economics of their industry provides insight into the potential sources of economic p erformance . Industry is not destiny . Finding a company in a n industry with high return s or avoiding a company in a n industry with low return s is not enough. Finding a good business capable of sustaining high performance requires a thorough understanding of the conditions for the industry and the f irm. -20 -10 0 10 20 30 40 CFROI minus Discount Rate (%) -20 -10 0 10 20 30 40 CFROI minus Discount Rate (%) Beverages -20 -10 0 10 20 30 40 CFROI minus Discount Rate (%) Containers & Packaging -20 -10 0 10 20 30 40 CFROI minus Discount Rate (%) Marine Nove mber 1, 2016 Measuring the Moat 9 A final word before we proceed. Our unit of analysis will be the firm. In most cases , the proper unit of analysis is the strategic business unit. This is especially true for multidivisional companies that compete in di sparate industries. T he following framework is applicable on a divisional level . S o we recommend conducting the analysis for each strategic business unit of a multidivisional company and aggregating the results. November 1, 2016 Measuring the Moat 10 Industry Analys is We have established that industry effects and firm effects are relevant in understanding corporate performance. The question is in what proportion. 11 Anita McGahan and Michael Porter, two prominent scholars of business strategy , analyzed roughly 58,0 00 firm -year observations for U .S. businesses from 1981 -1994. 12 They asses sed the impact of four factors on the sustainability and emergence of abnormal profitability : Year. The year effect captures the economic cycle. You can think of it as the macroeconomic factors that influence all businesses in the economy. Industry. Industry effects refer to how being part of a particular industry affects firm performance. A firm may benefit from industry effects if the industry has an attractive structure, including high barriers to entry. Corporate -parent. A corporate -parent effect arises when a business within a diversified firm on average under performs or outperform s its industry . For example, the corporate -parent effect was positive for Taco Bell, which saw its profitability improve in the 1980s fol lowing its acquisition by PepsiC o. Segment -specific . This effect capture s the characteristics unique to a firm that drive its perfor mance relative to rivals within the same industry. Such characteristics may include a firm’s resources , positioning, or how effectively it s managers execute strategy. Exhibit 5 summarizes McGahan and Porter’s results . They define sustainability of profits as “the tendency of abnormally high or low profits to continue in subsequent periods.” Emergence looks backward from the current year and measures the contrib utions to abnormal profits through time. High performers are those companies that generate profit s in excess of the median of their industry , and low performers are those below the median. Exhibit 5: Importance of Various Factors on Abnormal Profitability Source: Anita M. McGahan and Michael E. Porter, “The emergence and sustainability of abnormal profits,” Strategic Organization , Vol. 1, No. 1, February 2003, 79-108. McGah an and Porter found that i ndustry effects are most important in the sustainability of high performance and a close second i n the emergence of high performance behind segment -specific effects. However, industry effects are much smaller than segment -specific effects for low performers . The strategies and resources of below -average companies explain 90 percent or more of their returns in the case of either sustainability or emergence . Business managers and analysts searching for emerging or sustained competitive advantages might also note that the economic cycle is not important to the sustainability or emergenc e of performance . High Perf ormers Low Perf ormers High Perf ormers Low Perf ormers Y ear 3% -7% 2% -5% Industry 44% 12% 37% 13% Corporate-Parent 19% -4% 18% 2% Segment-Specif ic 34% 99% 43% 90% Emergence Sustainability November 1, 2016 Measuring the Moat 11 We break the industry analysis into three parts: 1. Get the lay of the land. This includes creating an industry map to understand the competitive landscape , constructing profit poo ls to see how the distribution of economic profits has changed over time, measuring industry stability, and classifying the industry so as to improve alertness to the main issues and opportunities. 2. Assess in dustry attractiveness through an analysis of the five forces. Of the five forces, we spend the bulk of our time assessing barriers to entry and rivalry. 3. Consider the likelihood of being disrupted by innovation . We consider the role of disruptive innovation and why industries transition from vertical to horizontal integration. The Lay of the Land Industry Map Creating an industry map is a useful way to start competitive analysis. 13 A map should include all the companies and constituents that might have an impact on a company’s profitability. The goal of an industry map is to understand the current and potential interactions that ultimately shape the sustainable value creation prospects for the whole industry as well as for the individual companies within the industry. From an industry point of view , you can think of three types of interactions: su pplier (how much it will cost to get inputs), customer (how much someone is willing to pay for a good or service), and external (other factors that come into play, such as government action). Exhibit 6 shows an illustration for the U.S. airline industry. Clients can create industry maps for specific companies using Credit Suisse’s PEERs tool, which analyzes a company’s supply chain . Peers can be accessed within RAVE , Credit Suisse’s research database, which also provides access to the forecasts of Credit S uisse analysts and a variety of other tools. Here are some points to bear in mind as you develop an industry map: List firms in order of dominance, typically defined as size or market share; Consider potential new entrants as well as existing players; Understand the nature of the economic interaction between the firms (e.g., incentives, payment terms); Evaluate any other factors that might influence profitability (e.g., labor, regulations). A study by Lauren Cohen and Andrea Frazzini, professors of f inance, suggests that investors may benefit from paying close attention to industry maps. The researchers examined how shocks to one firm rippled through to other firms via supply or demand links. They tested whether the market adequately incorporated the information that one firm released into the stock prices of its partner firms. They found that investors fail to adequately incorporate such information, creating a profitable trading strategy. Cohen and Frazzini state that “the monthly strategy of buyin g firms whose customers had the most positive returns in the previous month, and selling short firms whose customers had the most negative returns, yields abnormal returns of 1.55% per month, or an annualized return of 18.6% per year.” There is also eviden ce that analysts who cover both suppliers and customers provide more accurate earnings forecasts. 14 November 1, 2016 Measuring the Moat 12 Exhibit 6: U.S. Airline Industry Map Source: Credit Suisse. Note: LCC = low -cost carrier. Airlines American (hub) United Continental (hub) Delta (hub) Southwest (LCC) JetBlue (LCC) Alaska Air (hub) SkyWest (regional) Spirit (LCC) Hawaiian Holdings (regional) Virgin America (LCC) Allegiant Travel (LCC) Republic Airways (mix ) Frontier (LCC) Aircraft Boeing Airbus Bombardier AVIC Embraer Parts suppliers Engines General Electric Pratt & Whitney (UTX) Rolls -Royce Other UTC Aerospace (UTX) Honeywell General Dynamics Textron Precision Castparts Spirit AeroSystems Rockwell Collins Parker -Hannifin L-3 Communications Triumph Group B/E Aerospace Moog CAE TransDigm Hexcel Heico Air freight and logistics UPS FedEx C.H. Robinson UTi Worldwide Expeditors Echo Global Logistics Forward Air Global distribution systems Sabre Amadeus Travelport Airports Gates, takeoff/landing slots Financing Leasing, banks, investors Labor Cabin crew, pilots Ground staff, other services External providers Atlas Air Air Transport Services Group Unions Jet fuel Government Regulation Mandated services (e.g., security, air traffic control) Fliers Commercial Business Travel intermediaries Travel agents Corporate travel departments Website aggregators Priceline.com Expedia Orbitz TripAdvisor November 1, 2016 Measuring the Moat 13 Profit Pool The next step is to construct a profit pool. 15 A prof it pool shows the distribution of an industry’s value creation at a point in time. The horizontal axis measures size, t ypicall y invested capital or sales as a percentage of the industry, and the vertical axis measure s economic profitability ( e.g ., CFROI minus the discount rate). As a result, the area of each rectangle — the product of invested capital and economic return — is the total value added for that sector or company. For example, a company that has $200 million of invested capital and a spread o f 5 percentage points between its CFROI and discount rate generates $10 million in economic profit ($10 million = $200 million x .05). The total profit pool of the industry is the sum of the added value for all of the comp anies . To understand the overall profitability of an industry, it is useful to analyze the average profitability over a full business cycle , which is generally three to five years .16 But average profitability doesn’t reveal how value has migrated over time. Profit pools are particularly effective because they allow you to trace the increases or decreases in the components of the value -added pie. One effective approach is to construct a profit pool for today, five years ago, and ten years ago and then compare the results over time. Exhib it 7 is a profit pool for the airlines industry . (S ee Appendix B for the health care sector .) It shows the main components in the industry’s value chain including airlines, airports, and a variety of services. You can see from the horizontal axis that airl ines and airports use the majority of the capital invested in the industry. These are also the businesses with among the lowest economic returns, which the vertical axis reflects . Some businesses generate strong returns, including computer reservations systems (CRS), travel agents, freight forwarders, and various service jobs. But with so little capital in vested , they are too small to offset the value destruction from airlines and airports. As a c onsequence, the industry as a whole destroyed an average of $1 7 billion of shareholder capital per year through the 200 4-11 business cycle, according to the International Air Transport Association. 17 Exhibit 7: Airline Industry Profit Pool by Activity , 2004 -2011 Source: Based on IATA, "Profitability and the air transport value chain," IATA Economics Briefing No. 10 , June 2013, 19 -20. CRS = computer reservations systems; ANSP = air navigation service provider. -10 -5 0 5 10 15 20 25 30 35 40 ROIC - WACC (Percent) Share of Industry Gross Investment Airlines Manufacturers ANSPs Airports Freight forwarders 100% Maintenance Lessors Ground services CRS Travel agents Catering November 1, 2016 Measuring the Moat 14 We can also construct a profit pool of the leading companies within an industry . Exhibit 8 shows profit pools for the U.S. airline companies for 200 5, 20 10 , and 201 5. The horizontal axis represents 100 percent of the capital invested in the industry by public companies. These charts provide a bottom -up view of the industry’s migration from value destruction to value creation . Exhibit 8: Airline Industry Profit Pools by Company, 200 5-201 5 Source: Credit Suisse HOLT. -6 -4 -2 0 2 4 6 CFROI minus Discount Rate (Percent) Share of Industry Gross Investment 2005 American Alaska Other United South - west US Air 100% Continental JetBlue -6 -4 -2 0 2 4 6 CFROI minus Discount Rate (Percent) Share of Industry Gross Investment 2010 American Alaska Other United Continental South - west US Air 100% Delta JetBlue -6 -4 -2 0 2 4 6 CFROI minus Discount Rate (Percent) Share of Industry Gross Investment 2015 American Alaska Other United Continental South - west 100% Delta JetBlue November 1, 2016 Measuring the Moat 15 Most airlines destroyed value over the first half of the decade, consistent with the industry’s history of weak returns on capital as the result of low barriers to entry and high fixed costs. E ven the low -cost , point -to-point carriers struggled despite a history of outperforming the legacy carriers. But the performance of all the major airlines improved considerably in recent years , with the six largest companies earning above their cost of capital by 2015 . Factors that drove the improvement include a sharp decline in the price of oil, better capacity utilization, and extensive con solidation following a slew of bankruptcies. 18 The x -axis shows that the top four carriers increased their market share from roughly 70 percent in 2005 to 80 percent in 2015. Industry Stability Industry stability is a nother important metric . Generally speaking, s table industries are more conducive to sustainable value creation. Unstable industries present substantial competitive challenges and opportunities. The value migration in unstable industries is greater than that of stable industries, making sus tainable value creation that much more elusive. We can measure industry stability a couple of ways. One simple but useful proxy is the steadiness of market share. This analysis looks at the absolute change in market share for the companies within an indus try over some period. (We typically use five years.) We then add up the absolute changes and divide the sum by the number of competitors. The lower the average absolute change in market share , the more stable the industry. Exhibit 9 shows the market share stability for four industries. There is relative stability in automobile manufacturing , while personal computers and mobile phones show moderate change, and there is substantial change in the smartphone market. Our rule of thumb is that absolute average c hanges of 2.0 or less over five years constitute a stable industry. November 1, 2016 Measuring the Moat 16 Exhibit 9: Market Share Stability , 2010 -2015 Source: Company data, Gartner, Nielsen, Credit Suisse. Another way to measure industry stability is the trend in pricing. Price changes reflect a host of factors, including cost structure (fixed versus variable), entry and exit dynamics, macroeconomic variables, technological change (e.g., Moore’s Law and Wright’s Law ), and rivalry. All else being equal, more stable pricing reflect s more stable industries. Warren Buffett places special emphasis on pricing power. He said, “The single most important decision in evaluating a business is pricing power. If you’ve got the power to raise prices without losing business to a competitor, you’ve got a very good business. And if you have to have a prayer session before raising the price 10 percent, then you’ve got a terrible business.” 19 Exhibit 1 0 shows the pricing trends for a variety of industries, classified as slow -, medium -, and fast -cycle businesses. Sustaining value creation in a fast -cycle industry is a challenge. A uto M anuf acturers (U.S. M arket) 2010 2015 5-Y ear Change General M otors 19% 18% 2% Ford M otor Company 17% 15% 2% Toyota M otor Corporation 15% 14% 1% Honda M otor Company 11% 9% 2% Chrysler Group/FCA 9% 13% 3% Nissan M otor Company 8% 9% 1% Hyundai-Kia 8% 8% 0% Volkswagen Group 3% 3% 0% BM W-M ini 2% 2% 0% Subaru 2% 3% 1% M azda 2% 2% 0% Daimler 2% 2% 0% O ther 2% 2% 1% Total 100% 100% A v erage A bsolute Change 1% Personal Computers (Global by Units) 2010 2015 5-Y ear Change O thers 48% 52% 4% Hewlett-Packard 16% 13% 3% Acer Group 12% 5% 7% Dell Inc 11% 10% 1% Lenov o Group 9% 14% 6% Asus 5% 5% 1% Total 100% 100% A v erage A bsolute Change 3% M obile Phones (Global) 2010 2015 5-Y ear Change O ther 40% 49% 9% Nokia/M icrosoft 29% 7% 22% Samsung 18% 21% 3% LG Electronics 7% 4% 3% Apple 3% 11% 8% ZTE 2% 3% 1% Huawei 2% 5% 4% Total 100% 100% A v erage A bsolute Change 7% Smartphones (Global) 2010 2015 5-Y ear Change Nokia 34% 0% 34% O ther 27% 48% 21% Research in M otion 17% 0% 16% Apple 15% 16% 1% Samsung 7% 23% 16% Huawei 0% 7% 7% X iaomi 0% 5% 5% Total 100% 100% A v erage A bsolute Change 14% November 1, 2016 Measuring the Moat 17 Exhibit 1 0: Pricing Stability, 2009 -2014 Source: U .S. Department of Commerce Bureau of Economic Analysis; Based on Jeffrey R. Williams, Renewable Advantage (New York: The Free Press, 2000), 11. Industry Classification Before turn ing to an industry analysis using the five forces framework, it’s useful to classify the industry you’re analyzing. The analytical process remains the same no matter which category the industry falls into. But the classification does provide guidance as to what issues you need to emphasize as you step through the analysis. For example, the challenges in a mature industry are likely to be quite distinct from those in an emerging indu stry. Exhibit 1 1 provides some broad classifications and the types of opportunities you should associate with each. Exhibit 1 1: Industry Structure and Strategic Opportunities Source: Jay B. Barney, Gaining and Sustaining Competitive Advantage (Upper Saddle River, NJ: Prentice -Hall, Inc., 2002), 110. Industry Average Annual Price Change Slow-cycle markets Dental Laboratories 7.7% Rail and T ransportation 4.4% Brew eries 3.4% Standard-cycle markets Highw ays and Streets 3.0% Motor and Generator Manufacturing 2.8% Bread and Bakery Product Manufacturing 2.5% Fast-cycle markets Warehousing and Storage -1.3% Wireless T elecommunications Carriers (Except Satellite) -2.3% Electronics and Appliance Stores -2.5% Industry Structure Opportunities Fragmented industry Consolidation:

-Discover new economies of scale -Alter ownership structure Emerging industry First -mover advantages: -Technological leadership -Preemption of strategically valuable assets -Creation of customer switching costs Mature industry Product refinement Investment in service quality Process innovation Declining industry Leadership strategy Niche strategy Harvest strategy Divestment strategy International industry Multinational opportunities Global opportunities Transnational opportunities Network industry First -mover advantages “Winner -takes -all” strategies Hypercompetitive industry Flexibility Proactive disruption November 1, 2016 Measuring the Moat 18 Industry Structure — Five Forces Analysis Michael Porter is well known for his five -forces framework (see Exhibit 1 2), which remains one of the best ways to assess an industry’s underlying structure .20 While some analysts employ the framework to declare an industry attractive or unattractive, Porter recommends using industry analysis to understand “the underpinnings of competition and the root causes of profitability.” Porter argues that the collecti ve strength of the five forces determines an industry’s potential for value creation. But the industry does not seal the fate of its members. An individual company can achieve superior profitability compared to the industry average by defending against the competitive forces and s haping them to its advantage. 21 Exhibit 1 2: Michael Porter's Five Forces That Shape Industry Structure Source: Michael E. Porter, Competitive Strategy (New York: The Free Press, 1980), 4. While analysts commonly treat Porter’s five forces with equal emphasis, we believe that the threat of entry and rivalry are so important that they warrant de eper consideration than the others . Further, our section on firm - specific analysis will put a finer point on some of the other forces. For now, here i s a quick look at supplier power, buyer power, and substitution threat: 22 Supplier power is the degree of leverage a supplier has with its customers in areas such as price, quality, and service. An industry that cannot pass on price increases from its powerful suppliers is destined to be unattractive. Suppliers are well positioned if they are mor e concentrated than the industry they sell to, if substitute products do not burden them, or if their products have significant switching costs. They are also in a good position if the industry they serve represents a relatively small percentage of their s ales volume or if the product is critical to the buyer. Sellers of commodity goods to a concentrated number of buyers are in a much more difficult position than sellers of differentiated products to a diverse buyer base. Buyer power is the bargaining strength of the buyers of a product or service. It is a function of buyer concentration, switching costs, levels of information, substitute products, and the offering’s importance to the buyer. Informed, large buyers have much more leverage over their supp liers than do uninformed, diffused buyers. Bargaining power of suppliers Threat of new entrants Threat of substitutes Bargaining power of buyers Rivalry among existing firms November 1, 2016 Measuring the Moat 19 Substitution threat addresses the existence of substitute products or services, as well as the likelihood that a potential buyer will switch to a substitute product. A business faces a substitution threat if its p rices are not competitive and if comparable products are available from competitors. Substitute products limit the prices that companies can charge, placing a ceiling on potential returns. Th e threat of new entr ants , or barriers to entry , is arguably the most important of Porter’s five forces. Before we delve into the factors that determine impediments to entry, it is worthwhile to review the empirical research on entry and exit. Entry and Exit Exhibit 13 shows the rate of entry an d exit for U .S. establishments across all industries since 1977 , using the U.S. Census’s Business Dynamics Statistics (BDS) . Most studies on corporate demography use establishments as the unit of analysis because that is the way that the Census Bureau collects and report s the data. Establishments are the physical sites where corporations operate whereas firms are the aggregations of all the establishments a parent company owns . Most firms , and especially young ones, have only one establishment. Not e that not all exits are failures. For example, some exits are planned or are the result of the sale of a viable business. 23 A useful way to think about entry and exit is to imagine an industry with 100 firms today. Based on the annual rates since 2000 , an average of 11 new firm s will enter the industry in each year and 10 will leave . This bring s the total number of firms to 101. Because the rate of entry typically exceeds that of exit , the number of establishments in the U.S. has increased over time . Exhibit 13: Rate of Entry and Exit for Establishment s in the U.S. , 1977 -201 4 Source: U.S. Census Bureau, Center for Economic Studies, Business Dynamics Statistics ; Credit Suisse. 6% 8% 10% 12% 14% 16% 18% 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Entry Rate Exit Rate November 1, 2016 Measuring the Moat 20 It is also important to understand the history of entry and exit for the specific industry you are analyzing . These rates vary widely based on where the industry is in its life cycle and on the industry’s barriers to entry and exit. Research shows that the number of firms in new industries follows a consistent path. The market is unc ertain about the products it favors i n the early stage of industry development , which encourages small and flexible firms to enter the industry and innovate . As the industry matures , the market selects the products it wants and demand stabilizes. The older firms benefit from economies of scale and entrenched advantages, causing a high rate of exit and a move toward a stable oligopoly. 24 Exhibit 14 shows the entry and exit rates for a variety of sectors, grouped according to Standard Industrial Classificatio n (SIC) codes. Exhibit 14 : Annual Average Rate of Entry and Exit by Sector in the U.S. , 1977 -201 4 Source: U.S. Census Bureau, Center for Economic Studies, Business Dynamics Statistics; Credit Suisse. There is a strong correlation between the rate of entry and exit for each sector. For instance, m anufacturing has low rates of entry and exit , while construction has very high rates, suggesting that the manufacturing sector possess es stronger barriers to entry and exit. Perhaps the most widely cited study of entry and exit rates is that of Timothy Dunne, Mark Roberts, and Larry Samuelson (DRS) . The y examined more than 250,000 U.S. manufacturing firms over a 20 -year span ended in the early 1980s. 25 A useful way to summarize the findings of DRS is to imagine a hypothetical industry in the year 201 6 that has 100 firms w ith sales of $1 million each. Should the patterns of entry and exit in U.S. industries during the period of their study apply to the futu re, the following w ill occur :26 Entry and exit will be pervasive . After five years, between 30 and 45 new firms will have entered the industry and will have combined annual sales of $15 -20 million. Half of these entrants will be diversified firms competing in other markets, and half will be new firms. During the same ti me , 30 to 40 firms with Agricultural Services, Forestry, Fishing Mining Construction Manufacturing Transportion, Public Utilities Wholesale trade Retail trade Finance, Insurance, Real Estate Services 8% 10% 12% 14% 16% 8% 10% 12% 14% 16% Entry Rate Exit Rate November 1, 2016 Measuring the Moat 21 aggregate sales of $15 -20 million will leave the industry. So the industry will experience a 30 -45 percent turnover in firms, with the entering and exiting firms representing 15 -20 percent of the industry’s volume. Companies enter ing and exiting tend to be smaller than the established firms . A typical entrant is only about one -third the size of an incumbent, with the exception of diversifying firms that build new plants. These diversifying firms, which represent less than 10 percen t of total new entrants, tend to be roughly the same size as the incumbents. Entry and exit rates vary substantially by industry . Consistent with Exhibit 14, research by DRS shows that low barriers to entry and low barriers to exit tend to go together . Most entrants do not survive ten years, but those that do thrive . Of the 30 to 45 firms that enter between 201 6 and 20 21 , roughly 80 percent will exit by 202 6. But the survivors will more than double their relative size by 202 6. Other studies have found s imilarly low chances of survival for new firms. 27 Research by Credit Suisse HOLT ® shows that less than 50 percent of public firms survive beyond ten years. Our analysis of the BDS data also rev eals low survival rates . Exhibit 1 5 shows one -year and five -year survival rates based on the birth year of the establishment . The rate today is similar to that of 1977. The latest figures show one -year survival rates of about 80 percent and five -year survival rates of roughly 50 percent . Exhibit 15: Survival Rates for Establishments in the U.S. by B irth Year, 1977 -201 4 Source: U.S. Census Bureau, Center for Economic Studies, Business Dynamics Statistics; Credit Suisse. What influences the decision of a challenger to ent er in the first place? On a broad level, potential entrants weigh the expected reactions of the incumbent s, the anticipated payoff s, and the magnitude of exit costs. 28 Researchers also find that challengers neglect the high base rates of business failure, leading to overconfidence and a rate of entry that appears higher than what is objectively warranted . We’ll explore each of these factors. 40% 50% 60% 70% 80% 90% 100% 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 One-year rate Five-year rate November 1, 2016 Measuring the Moat 22 Let’s first look at the expectations of incumbent reaction to a potential new entry. Four specific factors predict the likely ferocity of incumbent reaction: asset specificity, the level of the minimum efficient production scale, excess capacity, and incumbent reputation. For a long time, economists thought that a firm’s commitment to a market was related to how much money the company had invested in assets. More careful analysis revealed that it’s not the quantity of assets that matters but how specific those assets are to th e market. A firm that has assets that are valuable only in a specific market will fight vigorously in order to maintain its position. A clear illustration is a railroad versus an airline route . Say a company builds a railroad trac k from New York to Chicago. It can use that asset for only one thing: to move a train back and forth betwee n those two cities. A s a result, that company will go to great lengths to protect its position. 29 Now consider an airline that flies from New York to Chicago. If that route proves uneconomic, the airline can reroute the plane to a more attractive destination . Asset specificity take s a number of forms, including site specificity, where a company locates assets next to a customer for efficiency; physical specificity, where a company tailors assets to a specific transaction ; ded icated assets, where a company acquires assets to satisfy the needs of a particular buyer ; and human specificity, where a company develops the skills, knowledge, or know -how of its employees .30 The next factor is production scale. For many industries , uni t costs decline as output rises . But this only occurs up to a point. This is especially relevant for industries with high fixed costs. A firm enjoys economies of scale when its unit costs decline with volume gains. At some point, however, unit costs stop declining with incremental output and companies get to constant returns to scale. The minimum efficient scale of production is the smallest amount of volume a company must produce in order to minimize its unit costs . (See Exhibit 16 .) The minimum eff icient scale of production tells a potential entrant how much market share it must gain in order to price its goods competitively and make a profit . It also indicates the size of an entrant’s upfront capital commitment. When the minimum efficient scale of production is high relative to the size of the total market, a potential entrant is looking at the daunting prospect of pric ing its product below average cost for some time to get to scale. The steeper the decline in the cost curve, the less likely the ent ry. The main way an entrant can try to offset its production cost disadvantage is to differentiat e its product, allowing it to charge a price premium versus the rest of the industry. Minimum efficient scale is generally associated with manufacturing businesses, including automobile and semiconductor fabrication plants. For example, the cost for Intel to produce its first Xeon microprocessor was more than $10 billion, including the fabr ication plant and associated research and development. But once the chip was designed and the fab was up and running, the cost to produce incremental units dropped sharply. The concept of minimum efficient scale also applies to knowledge businesses where a company creates content once at a very high cost and then replicates it for the market. T he same cost curve exists for software as for hardware and it is even steep er in most cases . November 1, 2016 Measuring the Moat 23 Exhibit 16 : Minimum Efficient Scale as a Barrier to Entry Source: Sharon M. Oster, Modern Competitive Analysis (Oxford: Oxford University Press, 1999), 62. A third factor in assessing incumbent reaction is excess capacity. The logic here is quite straightforward. Assuming that demand remains stable, an entrant that comes into an industry that has too much capacity increases the excess capacity of the incumbents. If the industry has eco nomies of scale in production, the cost of idle capacity rises for the existing companies . As a result, the incumbents are motivated to m aintain their market share. So the prospect of a new entrant will trigger a price drop. This prospect deters entry. Th e final factor is incumbent reputation. Firms usually compete in various markets over time. As a consequence , they gain reputations as being ready to fight at the least provocation or as being accommodating. A firm’s reputation, backed by actions as well a s words, can color an entrant’s decision. Another important shaper of barriers to entry is the magnitude of the entrant’s anticipated payoff. An entrant cannot be sure that it will earn an attractive economic profit if the incumbent has an insurmountable advantage. Incumbent advantages come in the form of precommitment contracts, licenses and patents, learning curve benefits, and network effects. The first incumbent advantage is precommitment contracts. Often, companies secure future business through long -term contracts. These contracts can be efficient in reducing search costs for both the supplier and the customer. A strong incumbent with a contract in place discourages entry . Precommitment contracts take a number of forms. One is if an incumbent has favorable access to an essential raw material. An example of this occurred shortly following World War II. Alcoa, an aluminum producer, s igned exclusive contracts with all of the producers of an essential material in aluminum production called high -grade bauxite . The inability to access bauxite on such favorable terms deterred p otential entrants . Another form of precommitment contract is a long -term deal with customers. In the mid -1980s, Monsanto (NutraSweet ) and Holland Sweetener Company were two produc ers of the sweetener aspartame. After the patent on aspartame expired in Europe in 1987 , Holland entered the market to compete against Monsanto . The competition dr ove down the price of aspartame 60 percent , and Holland lost money. Average Cost Cost per unit Q Output Minimum Efficient Scale November 1, 2016 Measuring the Moat 24 But Holland had its eye on the real prize, the U.S. market, where the patent was to expir e in 1992. In a classic precommitment move, Monsanto signed long -term contracts to supply the largest buyers of aspartame, Coca -Cola and PepsiCo , and effective ly shut Holland out of the U nite d States . This suggests a crucial lesson for companies and investors: all buyers want to have multiple suppliers, but it doesn’t mean that they will use multiple suppliers. Holland created a great deal of value for Coke and Pepsi but none for itself. 31 Precommitment also include s quasi -contracts, such as a pledge to always provide a good or service at the lowest cost. Such pledges, if credible, deter entry because n ew entrants rarely have the s cale to compete with incumbents. Licenses and patents also shape a potential entrant’s payoff for reasons that make common sense . A number of industries require a license or certification from the government to do business. Acquiring licenses or certifications is costly, hence creating a barrier for an entrant. Patents are also an important entry barrier. But the spirit of a patent is different from that of a license. The intent of a patent is to allow an innovator to earn an appropriate return on investment. Most innovations require subst antial upfront costs. So a free market system needs a means to compensate innovators to encourage their activities. Patents do not discourage innovation, but they do deter entry for a limited time into activities that are protected. Learning curves can al so serve as a barrier to entry. The learning curve refers to an ability to reduce unit costs as a function of cumulative experience. Researchers have studied the learning curve for hundreds of products.

The data show that , for the median firm, a doubling o f cumulative output reduces unit costs by about 20 percent .32 A company can enjoy the benefits of the learning curve without capturing economies of scale, and vice versa. But generally the two go hand in hand. Network effects are a nother important incumb ent advantage that can weigh on an entrant’s payoff. Network effects exist when the value of a good or service increases as more members use that good or service . As an example, Uber is attractive to passengers precisely because so many riders and drivers congregate on the platform . In a particular business , positive feedback often ensures that one network becomes domina nt. For example, in the U.S. Uber has not only weathered competitive onslaught , it has also strengthened its position. Size, network struc ture, and connectivity contribute to network strength. 33 Good example s today are the online social networks , including Facebook and Instagram , which become more valuable to a user as more people join. We also see network effects in the smartphone market between the dominant operating systems and app lication developers. Because the vast majority of users own devices operating on Android or iOS , app lication developers a re far more likely to build applica tions for th em than for other operating systems. This creates a powerful ecosystem that is daunting for aspiring entrants. 34 The last point, consistent with DRS’s analysis of entry and exit, is the link between barriers to entry and barriers to exit. High exit costs discourage entry. The magnitude of investment an entrant requires and the specificity of the assets determine the size of exit barriers. Low investment needs and non -specific assets are consistent with low barriers to entry. Robert Smiley , a retired economist who specialized in competitive strategy, surveyed product managers about their strategies to deter entry .35 While his analysis was limited to consumer products companies, the result s are instructive nonetheless. (See Exhibit 17 .) The first three strategies — learning curve, advertising, and R&D/patents — create high entry costs. The last three — reputation, limit pricing, and excess capacity — November 1, 2016 Measuring the Moat 25 influence judgments of post -entry payoffs. Vir tually all managers reported using one or more of these strategies to deter entry. Exhibit 17 : Reported Use of Entry -Deterring Strategy Source: Robert Smiley, "Empirical Evidence on Strategic Entry Deterrence ”, International Journal of Industrial Organization , Vol. 6, June 1988, 172. Behavioral factors also play a role in the decision to enter a business. A pair of economists, Colin Camerer and Dan Lovallo, designed an experiment to understand why subjects enter a game. 36 When the scientists informed the subjects that the payoffs were based on skill, the individuals overestimated their probability of success. As a result, they entered the game at a higher rate than those who were told that the payoffs were random. Most subjects who entered the game believed they would have positive profits despite the negative total profit among all entrants. The researchers attributed the overconfidence of the entrants to “reference group neglect .” The idea is that the e ntrants focused on what they percei ved to be their unique skills while ignoring the abilities of their competitors and the high failure rate of new entries as reflected in the reference group . Th e failure to consider a proper reference class pervades many of the forecasts we make. 37 In the business world, reference class neglect shows up as unwarranted optimism for the length of time it takes to develop a new product, the chance that a merger succeeds, and the likelihood of an investment portfolio outperforming the market. 38 Competitive Rivalry Rivalry among firms addresses how fiercely companies compete with one another along dimensions such as price, service, new product introductions, promotion, and advertising. In almost all industries, coordination in these areas improves the collec tive economic profit of the firms . For example, competitors increase their profits by coordinating their pricing. Of course, coordination must be tacit, not explicit. There is a tension between coordinating and cheating in most industries . A firm that “cheats ” by lower ing the price on its product stands to earn disproportionate profits if the other firms do not react . We can think of rivalry as understanding, for each firm, the trade -offs between coordination and cheating. Lots of coordination suggests low rivalry and attractive economic returns. Intense rivalry makes it difficult for firms to generate high returns. Coordination is difficult if there are lots of competitors. In this case, each firm perceives itself to be a minor player and is more likel y to think individual istically. Naturally, the flip side suggests that the existence of fewer firms lead s to more opportunity for coordination. Research show s that most cases of price fixing that the government prosecute s involve industries with fewer firm s than average .39 Learning Curve Advertising R&D/ Patents Reputation Limit Pricing Excess Capacity New Products Frequently Occasionally Seldom Existing Products Frequently Occasionally Seldom 26% 29 45 62% 16 22 52% 26 21 56% 15 29 31% 16 54 27% 27 47 27% 22 52 8% 19 73 21% 21 58 22% 20 58 21% 17 62 November 1, 2016 Measuring the Moat 26 A concentration ratio is a common way to measure the number and relative power of firms in an industry. The Herfindahl -Hirschman Index (HHI) is a popular method to estimate industry concentration. The HHI considers not only the number of firms but also the distribution of the sizes of firms. A dominant firm in an otherwise fragmented industry may be able to impose discipline on other s. In industries with several firms of similar size, rivalry tends to be intense . Exhibit 18 shows the HHI for 20 industries. Many economists characterize readings in excess of 1,800 as industries with reduced rivalry. The index is equal to 10,000 times the sum of the squares of the market shares of the 50 largest firms in an industry. If there a re fewer than 50 firms, the amount is summed for all firms in the industry. For instance, for an industry with four companies and market shares of 40 percent, 30 percent, 20 percent, and 10 percent, the index would be 3,000. (Take 10,000 x [(.4) 2 + (.3) 2 + (.2) 2 + (.1) 2].) Exhibit 18 : Herfindahl -Hirschman Index for Selected I ndustries Source: U.S. Census Bureau, Concentration Ratios - 2012 Economic Census. If industry concentration is a reliable indicator of the degree of rivalry, you ’d expect to see some link between concentration and profitability. Researchers have shown this to be the case. Two professors of finance, K ewei Hou and David Robinson, examined industries for the years 1 963 -2001 and found that c oncentrated industries earned above average profits and less concentrated industries earned below average profits .40 Another influence of rivalry is firm homogeneity. Rivalry tends to be less intense in industries with companies that have similar goals , incentive programs, ownership structure s, a nd corporate philosophies. But in many instances , competitors have very different objectives. For example, an industry may have companies that are public, privately held, or owned by private equity firms. These competitors may have disparate financial objectives, incentive structures, and time horizons. The strategies that companies within an industry pursue will reflect the heterogeneity of obj ectives. 41 Industry (Manuf acturing) Herf indahl-Hirschman Index Breakfast cereal 2,333 Household appliances 1,576 Tires 1,377 Automobiles 1,178 Plastic bottles 934 Flour milling 772 Explosiv es 771 Book printing 623 Poultry processing 600 Stationery products 497 Iron founderies 454 Sporting and athletic goods 373 Animal food 369 Basic chemicals 362 Fabric mills 275 M otor v ehicle bodies 207 Adhesiv es 182 M achinery 91 Computer and electronic products 72 Retail bakeries 12 November 1, 2016 Measuring the Moat 27 Asset specificity plays a role in rivalry. Specific assets encourage a company to s tay in an industry even when conditions become trying because the re is no alternative use for the assets. Assets include physical assets , such as railroad tracks , as well as intangible assets such as brands. Demand variability shapes coordination costs an d hence has an influence on rivalry. When demand variability is high, companies have a difficult time coordinating internal ly and have little opportunity to effectively coordinat e with competitors. Variable demand is a particularly important consideration in industries with high fixed costs. In these industries, companies often add too much capacity at points of peak demand. While companies use this capacity at the peak, the capacity is excessive at the trough and spurs even more intense competition at the bottom of the cycle . The condition s of variable demand and high fixed costs describe many commodity industries, which is why their rivalry is so bitter and consistent positive economic returns are so elusive . Industry growth is a final consideration. When the pie of potential excess economic profits grows, companies can create shareholder value without undermining their competitors. The game is not zero -sum. In contrast, stagnant industries are zero -sum games and the only way to in crease value is to take it from others. So a rise in rivalry often accompanies a decelerating industry growth rate. Disruption and Disintegration Most strategy frameworks focus primarily on figuring out which industries are attractive and which companies are well positioned. Clayton Christensen , a professor of management, developed a theory to explain why great companies fail and how companies succeed through innovation . Christensen wondered why it was common for c ompanies with substantial resources and s mart ma nagement teams to lose to companies with simpler, cheaper, and inferior products. His theory of disruptive innovation explains that process. 42 Christensen starts by distinguishing between sustaining and disruptive innovations. Sustaining innovations foster product improvement. They can be incremental, discontinuous, or even radical. But the main point is that a sustaining innovation operate s with in a defined value network — the “context within which a firm identifies and responds to customers’ needs, solves problems, procures input, reacts to competitors, and strives for profit.” 43 A d isruptive innovation , by contrast, approach es the same market w ith a different value network. Consider book selling as an example. The evolution from mom -and -pop bookstores to superstores was a clear innovation, but the value network was the same. Amazon.com introduced a new value network when it started selling books online. It is common for disruptors to trade lower operating profit margins for high capital turnover in their bid to earn returns on invested capital in excess of the cost of capital. Christensen distinguishes between the two types of disruptive innovation: low -end disruption and new -market disruption. A l ow -end disruptor offer s a product that already exists. For instance, when Southwest Airlines entered the airline industry , it provided limited flights with no frills at a very low cost. Southwest couldn’t, and didn’t, compete with the large legacy carriers. A new -market disruption, on the other hand, competes initially against “non -consumption.” 44 It appeals to customers who previously did not buy or use a product because of a shortage of funds or skills. A new -market disruptive product is cheap or simple enough to enable a new group to own and use it. The transistor radio, introduced in the 1950s, is an example of a new -market disruption. Manufacturers such as So ny targeted teenagers, a group who wanted to listen to music on their own but who couldn’t afford November 1, 2016 Measuring the Moat 28 tabletop radio s. Teenagers were so thrilled that they could listen to these pocket -sized radios away from their parents that they ignored the static and poor sound quality. 45 Disruptive innovations initially appeal to relatively few customers who value features such as low price, smaller size, or greater convenience. Christensen finds that these innovations generally underperform established products in the near term but are good enough for a segment of the market. Exhibit 19 presents Christensen’s model visually. The horizontal axis is time , and the vertical axis is product performance. The shaded area represents customer needs and takes the shape of a dist ribution that includes low -end, average, and high -end customers. The upward -sloping line at the top is the performance trajectory of sustaining innovations. The parallel, upward -sloping line below it is the performance trajectory for a disruptive innova tion. Exhibit 19 : Christensen's Model of Disruptive Innovation Source: Clayton M. Christensen, The Innovator's Dilemma (Boston , MA : Harvard Business School Press, 1997), xvi. One of the key insights of the model is that innovations often improve at a rate faster than the consumer demands. Established companies, through sustaining technologies, commonly provide customers with more than they need or more than they are ultimately willing to pay for. When innovation drives performance for a sustaining technology past the needs of mainstream customers, the product is “overshot.” Indications that a market is overshot include customers who are unwilling to pay for a product’s new featu res and who don’t use many of the available features. When the performance of a sustaining innovation exceeds the high end of the consumer’s threshold, the basis of competition shifts from performance to speed -to-market and delivery flexibility. For instance, as the personal computer market became overshot in the 1990s, manufacturers focused on performance , such as Compaq , lost to manufacturers with more efficient delivery models , such as Dell. Mainstream Customer Needs Sustaining Innovation Performance Disruptive Innovation Time Meet customer needs at lower price Overshoot customer performance needs November 1, 2016 Measuring the Moat 29 The trajectory of product improvement allows disruptive innovations to emerge because even if they fail to meet the demands of mainstream users today they become competitive tomorrow. Further, disruptive innovations end up squeezing the established produc ers because the disruptors have lower cost structures. Christensen likes to use the example of the mini -mills versus integrated mills in the steel industry. Mini -mills melt scrap steel, so they are a fraction of the size of the integrated mills that make steel in blast furnaces.

Because the i ntegrated mills controlled the whole process, they started with the substantial advantage of producing steel of high quality. The mini -mills launched their simpler and cheaper model in the 1970s. Their inferior quality initially limited them to making re bar, the bars that reinforce concrete. This is the least expensive and least valuable market for steel. Indeed, the operating profit margins for integrated mills improved after they left the market for rebar to the mini -mills . As Christensen says, “It felt good to get in and good to get out.” But the good feeling didn’t last long . Just as the theory predicts, t he mini -mills rapidly improved their ability to make better steel and started to compete in markets that had more value. That process continued over time until the mini -mills shoulder ed into the high end of the market and destroyed the profitability of the integrated mills. A crucial point of Christensen’s work is that p assing over disruptive innovations may appear completely rat ional for est ablished companies. The reason is that disruptive products generally offer low er margins than established ones , operate in insignificant or emerging markets, and are not in demand by the company’s most profitable customers. As a result, companies that list en to their customers and practice conventional financial discipline are apt to disregard disruptive innovations. Exhibit 20 summarizes Christensen’s three categories of innovation , sustaining, low -end, and new -market , and considers the customers they ser ve, the technology they utilize to attract customers, the business models they employ , and the expected incumbent response to each. The incumbent response warrants specific attention. If a new competitor comes along with a sustaining innovation, incumbents are highly motivated to defend their turf. Christensen suggests it is very rare to see an incumbent lose this battle to a challeng er. For low -end disruptions, the motivation of incumbents is generally to flee. This is what the integrated mills did. In the short run, fleeing helps profit margins by encouraging the incumbent to focus on the most lucrative segment of the market. In the long run, it provides resources for the disruptor to build capabilities that allow it to penetrate the mainstream market on a cost -effective basis. Incumbents are typically content to ignore new -market disruptions. The example of the transistor radio sh ows why. B ecause the portable radios did not encroach on the base of the established tabletop radio customers, the incumbent firms were motivated to disregard the new product. Nove mber 1, 2016 Measuring the Moat 30 Exhibit 20 : Innovation Categories and Characteristics Source: Based on Clayton M. Christensen and Michael E. Raynor, The Innovator’s Solution (Boston , MA : Harvard Business School Press, 2003), 51. Christensen has also done insightful work on understand ing and anticipating the circumstances under which an ind ustry is likely to shift from vertical to horizontal integration .46 This framework is relevant for assessing the virtue of outsourcing. While outsourcing has provided some companies with great benefits, including lower capital costs and faster time to mark et, it has also created difficulty for companies that tried to outsource under the wrong circumstances. Firms that are v ertically integrated dominate when industries are developing because the costs of coordination are so high. Consider the computer industry in 1980. (See Exhibit 21.) Most computer companies were vertically integrated to ensure that their products would actually work. But as an industry develops, various components become modules. The process of modularization allows an industry to flip from vertical to horizontal. This happened in the computer industry by the mid -1990s. Modularization, which is not simple from an engineering standpoint, allows for standardization and the assembly of products off the shelf. Sustaining Innovation Low -End Disruption New -Market Disruption Customers Undershot customer Overshot customer at low end of existing market Non -consumer or non -producer Technology (product/service /process) Improvement along primary basis of competition Good enough performance at lower prices Simpler, customizable; lets people "do it themselves" Business Model Extension of winning business model Attractive returns at lower prices Completely new model, different from core business Competitor Response Motivated to respond Motivated to flee Motivated to ignore November 1, 2016 Measuring the Moat 31 Exhibit 21: Disintegration of the Computer Industry Source: Andrew S. Grove, Only the Paranoid Survive (New York: Doubleday, 1999), 44. Boeing’s ordeal with the 787 Dreamliner is a cautionary tale about the perils of outsourcing too early. 47 Historically, Boeing used a process called “build -to-print,” where the company did all of the design for an aircraft in-house and sent suppliers very specific instructions. For the 787, Boeing decided to outsource the design and construction of various sec tions of the plane, with the goal of lowering costs and quickening assembly times. The program was a mess. The first plane was supposed to arrive in 1,200 parts but showed up in 30,000 pieces. Boeing had to bring substantial par ts of the design back in-house at a large cost of money and time. The company failed to realize that outsourcing doesn’t make sense for products that require complex integration of disparate subcomponents. The coordination costs are simply too high. Industry analysis provides imp ortant background for understanding a company’s current or potential performance. Now we turn to analyzing the firm. Sales and distribution Application software Operating system Computer Chips Sales and distribution Application software Operating system Computer Chips IBM DEC Sperry Univac Wang Retail Stores Superstores Dealers Mail Order Word Word Perfect Etc. DOS and Windows OS/2 Mac UNIX Compaq Dell Packard Bell Hewlett – Packard IBM Etc. Intel Architecture Motorola RISCs The Vertical Computer Industry – Circa 1980 The Horizontal Computer Industry – Circa 1995 November 1, 2016 Measuring the Moat 32 Firm -Specific Analysis Core to understanding sustainable value creation is a clear understanding of how a company creates shareholder valu e. A company’s ability to create value is a function of the strategies it pursues, its interaction with competitors, and how it deals with non -competitors. 48 Much of what companies discuss as strategy is not strategy at all. As Michael Porter emphasizes, strategy is different than aspirations, more than a particular action, and distinct from vision or values. Further, Porter differentiates between operational effectiveness and strategic positioni ng. Operational effectiveness de scribes how well a company does the same activity as others . Strategic positioning focuses on how a company’s activities differ from those of its competitors . And where there are differences, there are trade -offs. 49 We first provide a fundamental fram ework for value creation. We then consider the various ways a company can add value. Finally, we delve into firm interaction using game theory and principles of co -evolution. A Framework for Added -Value Analysis Adam Brandenburger and Harborne Stuart , professors of strategy, offer a very concrete and sound definition of how a firm adds value. 50 Their equation is simple: Value created = willingness -to-pay – opportunity cost The equation basically says that the value a company creates is the differenc e between what it gets for its product or service and what it costs to produce that product (including the opportunity cost of capital).

Understanding what each of the terms mean s is fundamental to appreciating the equation . Let’s start with willingness to pay. Imagine someone hand s you a brand new tennis racket. Clearly, that is good. Now imagine that the same person start s withdrawing money from your bank account in small increments. The amount of money at which you are indifferent to having the racket or the cash is the definition of willingness to pay. If you can buy a product or service for less than your willingness to pay, you enjoy a consumer surplus. The flip side describes opportunity cost. A firm takes some resource from its supplier. Opportuni ty cost is the cash amount that makes the supplier perceive the new situation (cash) as equivalent to the old situation (resource). Brandenburger and Stuart then go on to define four strategies to create more value: increase the willingness to pay of you r customers; reduce the willingness to pay of the customers of your competitors; reduce the opportunity cost of your suppliers; and increase the opportunity cost of suppliers to your competitors. This framework also fits well with Porter’s generic strategi es to achieve competitive advantage — cost leadership (production advantage) and differentiation (consumer advantage). Brandenburger teamed up with his colleague Barry Nalebuff to create what they call a “value net.” 51 We present the value net slightly diff erently than the authors do, but the components and configuration are identical. (See Exhibit 2 2.) On the left are the firm’s suppliers. On the right are the firm’s customers. Between the suppliers and customers are the company, its competitors, and its co mplementors — a term we will define in more detail . For now, the point is that companies beyond a firm’s suppliers, customers, and competitors can affect the amount of added value that it can capture. November 1, 2016 Measuring the Moat 33 Exhibit 2 2: Added -Value Analysis – The Value Net Source: Adapted from Adam M. Brandenburger and Barry J. Nalebuff, Co-opetition (New York: Doubleday, 1996), 17. The value net fits comfortably into Michael Porter’s traditional analys es but adds an important element: strategy is not only about ri sk and downside but also about opportunity and upside. Research in industrial organization emphasize s non -cooperative game theory, a reasonable approach for well -established industries near product price equilibrium. But c ooperative game theory recognizes that many industries are dynamic and offer opportunities to cooperate as well as to compete. The Value Chain Michael Porter also developed value chain analysis, a powerful tool for identifying a company’s sources of competitive advantage. The value chain is “the sequence of activities your company performs to design, produce, sell, deliver, and support its products.” 52 (Exhibit 23 depicts a generic value chain .) Porter recommends focusing on discrete activities rather than broad functions such as marketin g or logistics, which he considers too abstract. The objective is to assess each activity’s specific contribution to the company’s ability to capture and sustain competitive advantage, be it through higher prices or lower costs. Exhibit 23 : The Value Chain Source: Joan Magretta, Understanding Michael Porter: The Essential Guide to Competition and Strategy (Boston, MA : Harvard Business Review Press, 2012). Creat ing an effective value chain analysis involves the following steps: Create a m ap of the i ndustry’s value chai n. Show the sequence of activities that most of the companies in the industry perform, paying careful attention to the activities specific to the industry that create value . Compare your company to the industry . Examine your company’s configuration of activities and see how it compares to others in the industry. Look for points of difference that may reflect a competitive advantage or disadvantage. If a company’s value chain closely resembles th at of its peers, then the companies are l ikely engaged in what Porter calls a “competition to be the best.” This is when rivals Complementors Company Competitors Customers Suppliers R&D Supply chain management Operations Marketing & sales Post -sales service November 1, 2016 Measuring the Moat 34 pursue similar strategies across the same activities, and it often leads to price wars and destructive, zero -sum competition. 53 Identify the drivers of price or source s of differentiation . To create superior value, a company should l ook for existing or potential ways to perform activities differently or to perform different activities. This c an come anywhere along the value chain, starting with product design and ending with post -sales service. Identify the drivers of cost . Estimate as closely as possible the full costs associated with each activity. Look for existing or potential differences between the cost structure of the company and that of competitors. Pinpointing the specific drivers of a cost advantage or disadvantage can yield crucial insights. This allows a ma nager to rethink how, or why, a company performs a particular activity. Sources of Added Value There are three broad sources of added value: production advantages, cons umer advantages, and external (e.g ., government) factors . Note that there is substantial overlap between this analysis and the industry analysis, but here we focus on the firm. Production Advantages Firms with production advantages create value by delivering products that have a larger spread between perceived consumer benefit and cost than their competitors, primarily by outperforming them on the cost side.

We distill production advantages into two parts: process and scale economies. Her e are some issues to consider when determin ing whether a firm has a process advantage: Indivisibility . Economies of scale are particularly relevant for business es with high fixed costs . One important determinant of fixed costs is indivisibility in the pro duction process. Indivisi bility means that a company canno t scale its production costs be low a minimum level even if output is low. The b ak ing business is an example. If a bakery wants to service a region, it must have a bakery, trucks, and drivers. These parts are indivisible, and a firm must bear their cost no matter what bread demand looks like. At the same time, if the trucks go from half empty to completely full, fixed costs don’t change much. Complexity . Simple processes are easy to imitate and are unlikely to be a source of advantage. More complex processes, in contrast, require more know -how or coordination capabilities and can be a source of advantage. For instance , Procter & Gamble (P&G) reportedly spent eight years and hundreds of millions of dollars to develop Tide Pods, a unit -dose capsule form of laundry detergent. Much of the spending went toward a dedicated staff of technical professionals, testing on thousands of consumers, and hundreds of pac kaging and product sketches. The government granted P&G numerous patents on detergent chemistry, the pod’s casing , and the manufacturing process. Bob McDonald, P&G ’s CEO at the time, demonstrated his confidence in the intellectual property when he said, “I don't imagine that this is going to be able to be copied in any way that it will become a threat.” 54 Rate of change in process cost . For some industries, production costs decline over time as a result of technological advances. For example, the process -related cost of building an e -commerce company today is l ess than in the past because you can purchase most of the necessary components off the shelf. B ut the cost in the future is likely to be lower than the cost today for the same reason. For industries with declining process costs, the incumbent has learning curve advantages , while the challenger has the November 1, 2016 Measuring the Moat 35 advantage of potentially lower future cost s. So the analysis must focus on the trade -off between learning advantages and future cost advantages. Protec tion . Look for patents, copyrights, trademarks, and operating rights that protect a firm’s process. Research suggests that products with patent protection generate higher economic returns as a group than any single industry. 55 Resource uniqueness . Alcoa’s bauxite contract is a good illustration of access to a unique resource. Economies of scale are the second category of potential production advantage. Exhibit 24 illustrates the distinction between supply - and demand -side scale economies. A firm creates value if it has a positive spread between its sales and costs , including opportunity cost s.56 A firm can create more value by either reducing its costs or increasing the price it receives. Evidence suggests that differences in customer willingness to pay account for more of the profit variability among competitors than disparities in cost levels. 57 The well -known cost curve depicted in Exhibit 24 shows that , as a manufacturing company increases its output, its marginal and average unit costs decline up to a point. This is classic increasing returns to scale , as the company benefits from positive feedback on the supply side. It i s all about lowering costs. How ever, positive feedback tends to dissipate for manufacturing companies because of bureaucracy, complexity, or input scarcity. This generally happens at a level well before dominance: market shares in the industrial world rarely top 50 percent . Positive fee dback on the demand side comes primarily from network effects, a point we will develop further in our discussion of consumer advantages. Exhibit 24: Supply - versus Demand -Side Driven Scale Economies Source: Credit Suisse . Output Price Users Output Opportunity cost Cost Supplier’s share Firm’s share Buyer’s share Total Value Created Willingness to Pay Users Supply -Side Demand -Side Willingness to pay Average Cost per Unit November 1, 2016 Measuring the Moat 36 Some areas to consider when determining whether or not a company has supply -side scale advantages include: Distribution . Start by determining whether the firm ha s local, regional, or national distribution scale . We would note that very few firms have national distribution scale. One good example is retail ing . Wal -Mart built its business in the 1970s and 1980s through regional distribution advantages. Most retailers have only regional advantages and often fail to generate meaningful economic profit s outside their core markets. One useful way to assess distribution strength is to look at the firm’s operations and revenues on a map.

Firms likely have some advantages where assets and revenue are clustered. 58 Purcha sing . Some firms can purchase raw materials at lower prices as the result of scale. For instance, Home Depot was able to add over 200 basis points to its gross margin in the late 1990s by lower ing its cost of merchandising through product line reviews and increased procurement of imported products. Home Depot used its size to get the best possible price from its suppliers. Increasingly, large firms are lowering their supplier’s opportunity cost by providing the supplier with better information about demand. Research and development . Economies of scope, related to economies of scale, exist when a company lowers its unit costs as it pursues a variety of activities. A significant example is research and development spillovers, where the ideas from one research proj ect transfer to other projects. For example, Pfizer sought a drug to treat hypertension, then thought it might treat angina, and then found an unusual side effect which led to the blockbuster drug, Viagra. 59 Companies with divers e research portfolios can often find applications for their ideas more effectively than companies with smaller research portfolios . Advertising . The advertising cost per consumer for a product is a function of the cost per consumer of sending the message and the reach. If the fixed costs in advertising , including ad vertisement preparation and negotiating with the broadcaster , are roughly the same for small and large companies, the n large companies have a n advantage in cost per potential consumer because th ey can spread their costs over a much larger base. For example, s ay both McDonald’s and Wendy’s have equally effective national advertising campaigns in the U nited States . That McDonald’s has almost three times as many stores as Wendy’s does means that McDonald’s advertisin g cost per store is lower . Companies that enjoy economies of scale in their local geographic or product markets should also be aware of the impact of globalization on their industries. Analysis by McKinsey , a consulting firm, suggests that about one -third of all industries are global, one -third national, and one -third regional. (See Exhibit 2 5.) Their research also shows that industries are becoming increasingly global over time. November 1, 2016 Measuring the Moat 37 Exhibit 2 5: Various Industries and Their Stage s of Globalization Source: Lowell Bryan, Jane Fraser, Jeremy Oppenheim , and Wilhelm Rall, Race for the World (Boston, MA: Harvard Business School Press, 1999), 45. Globalization ties to economies of scale in two important ways. First, companies enjoying economies of scale in their local markets often find it extremely challenging to replicate those advantages in new product or geographic markets. Even Wal -Mart has struggled overseas, whe re competitors dominant in those regions enjoy cost advantages in areas such as advertising and distribution. Any institutional advantages Wal -Mart ha s in terms of efficiency or use of technology are offset by the local economies of scale its competitors have earned . Second, increasing globalization may undercut the advantages of economies of scale in some industries. This is tied to the idea that an industry leader can more easily maintain dominance in a market of restricted size. In a restricted market, an upstart need s to capture a significant amount of market share to reach economies of scale, a challeng e given it must wrest le share from the leader itself. But as an industry undergoes globalization, economies of scale are actually easier to obtain for new competitors, as they no longer need to capture a significant share of a local market. 60 If you believe a firm has a production advantage, think carefully about why its costs are lower than those of its competitors. Firms with production advantages often have lower gross margins than companies with consumer advantages. Industry Physical commodities Scale -driven business goods and services Manufactured commodities Labor skill/productivity -driven consumer goods Brandable, largely regulated consumer goods Professional business services Historically highly regulated (nationally) industries High interaction cost consumer goods and services Locally regulated or high trans - portation cost goods and services Government services Petroleum, mineral ores, timber Aircraft engines, construction equipment, semiconductors, airframes, shipping, refineries, machine tools, telecom equipment Refined petroleum products, aluminum, specialty steel, bulk pharmaceuticals, pulp, specialty chemicals Consumer electronics, personal computers, cameras, automobiles, televisions Beer, shoes, luxury goods, pharmaceuticals, movie production Investment banking, legal services, accounting services, consulting services Personal financial services, telecommunications service providers, electric power service providers Food, television production, retail distribution, funeral homes, small business services Construction materials, real property, education, household services, medical care Civil servants, national defense Examples 1 2 3 4 5 6 7 8 9 10 GLOBAL LOCAL ~33% Globally defined ~33% Nationally defined ~33% Locally defined November 1, 2016 Measuring the Moat 38 Consumer Advantages Consumer advantage is the second broad source of added value. Firms with consumer advantages create value by d elivering products with a spread between perceived consumer benefit and cost tha t is larger than that of i ts competitors . They do so primarily by outperforming competitors on the benefit side. Here are some common features of companies with consumer advantages: Habit and high horizontal differentiation . A product is “horizontally differentiated ” when some consumers prefer it to competing products. This source of advantage is particularly significant if consumers use the product habitually. A product need not be unambiguously better than competing products; it just has to have features that some consumers find attractive. Soft drinks are an example. Competing with Coca -Cola is hard because many consumers habitually drink Coke and are fiercely attached to the product. 61 Experience goods . An experience good is a product that consumers can assess only when they’ve tried it. Search goods, in contrast, are products that a consumer can easily assess at the time of purchase (e.g., hockey pucks or office furni ture). With experience goods, a company can enjoy differentiation based on image, reputation, or credibility. Experience goods are often technologically complex. Switching costs and customer lock -in. Customers must bear costs when they switch from one product to another. The magnitude of switching costs determines the degree to which a customer is locked in. Sometimes switching costs are large and obvious (e.g., $100 million for a company to replace its network) , and sometimes they’re small but signific ant (e.g., $100 per customer for 1 million customers to switch insurance providers). An example of a product with high switching costs is an enterprise resource planning (ERP) system. In addition to the high initial cost for the license, a company implem enting a new ERP system must also expend a significant amount of internal resources for things such as user training and IT support . Moreover, because a company must customize an ERP system to its business processes, it makes it even more costly to switch providers. Exhibit 26 provides a breakdown of various forms of lock -in and their associated switching costs. November 1, 2016 Measuring the Moat 39 Exhibit 26 : Types of Lock -In and Associated Switching Costs Source: Carl Shapiro and Hal R. Varian, Information Rules (Boston, MA: Harvard Business School Press, 1999), 117. Network effects . Network effects can be an important source of consumer advantage, especially in businesses based on information . You can think of two types of networks . (See Exhibit 27 .) The first is a hub -and -spoke network, where a hub feeds the nodes. Examples include most airlines and retailers. In these net works, network effects exist but are modest . Exhibit 27 : Network Effects Are Stronger for Int eractive Networks t han for Radial Networks Source: Credit Suisse. The second type is an interactive network, where the nodes are either physically (telephone wires) or virtually (the same software) connected to one another. Network effects tend to be significant for interactive networks because the good or service becomes more valuable as more people use it . For example, Visa and MasterCard have formidable advantages in the market for payment systems as a result of their strong network effects. Positive feedback is critical in interactive networks. If more than one interactive network is competing for customers, the network that pulls ahead will benefit from positive feedback, leading to a winner -take -most Switching Costs Information and databases Specialized suppliers as the durable ages Learning a new system, both direct costs and Converting data to new format; tends to rise over time as collection grows Funding of new supplier; may rise over time if capabilities are hard to find/maintain includes learning about quality of alternatives Any lost benefits from incumbent supplier, plus possible need to rebuild cumulative use Type of Lock -In Contractual commitments Durable purchases Brand -specific training Search costs Loyalty programs Compensatory or liquidated damages Replacement of equipment; tends to decline lost productivity; tends to rise over time Combined buyer and seller search costs; Radial Interactive November 1, 2016 Measuring the Moat 40 outcome. The dominant network benefits from having the most users and sca le, and the switching costs for its custom ers rise as the network grows . The c lassic e xample of this de facto stan dard setting is Microsoft’s personal computer operating system business. The pattern of cumulative users of an interactive network follows an S-curve, similar to the diffusion of other innovations. However, the S -curve tends to be steeper for interactive networks. 62 Everett Rogers , a prominent sociologist, found that the plot of new adopters to a technology or network follows a normal distribut ion. Judging the source and longevity of a company’s added value is central to understanding the likelihood of sustainable value creation. A number of companies , including AOL, MySpace, and Friendster, appeared to have built valuable network s only to see t heir value fizzle. If you believe a firm has a consumer advantage, consider why the consumer’s willingness to pay is high and likely to stay high. Consumer advantages generally appear in the form of high gross margins. Exhibit 28 allows us to see which companies have production or consumer advantage s by disaggregating the sources of economic return on investment. (CFROI = CFROI Margin x Asset Turnover.) The vertical axis is asset turnover. Companies with a production advantage gene rally have high asset turnover. The horizontal axis is profit margin. High margins are consistent with a consumer advantage. The isocurve shows all the points that equal a six percent CFROI. Using data from Credit Suisse HOLT, the exhibit plots the profit margins and asset turnover for the largest 100 non -financial companies in the world , by market capitalization, for the latest fiscal year . All companies that fall above or to the right of the isocurve earn CFROIs in excess of six percent . The panel at the bottom of Exhibit 2 8 shows how companies can take different paths to the same economic return. For instance, Nike and Alphabet have CFROIs of 17 percent. But Nike has a relatively low margin and high asset turnover, whereas Alphabet has a high margin a nd low turnover. November 1, 2016 Measuring the Moat 41 Exhibit 28: Sources of Economic Return for the Largest 1 00 Firms in the World Source: Credit Suisse HOLT . Note: Data for latest fiscal year as of 10/25/16. Government The final source of added value is external, or government related. Issues here include subsidies, tariffs, quotas, and both competitive and environmental regulation. Changes in government policies can have a meaningful impact on added value. Consider the impact of deregulation on the ai rline and trucking industries, Basel III on financial services , the Affordable Care Act on health care, and tariffs on the solar energy industry. 63 0 1 2 3 4 5 6 -5 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 Asset Turnover (x) CFROI Margin (Percent) Production Advantage Consumer Advantage Home Depot Wal -Mart Amgen McDonald's Alphabet Nike Qualcomm GE CFROI (%) Company Margin (%) Turns (x) Company Margin (%) Turns (x) 17 Nike 14 1.2 Alphabet 43 0.4 16 Home Depot 12 1.4 Qualcomm 36 0.4 13 General Electric 15 0.8 Amgen 56 0.2 11 Walgreen Boots Alliance 8 1.5 Roche Holding 38 0.3 10 Wal-Mart 5 1.9 McDonald's 31 0.3 9 Daimler 9 1.0 Pfiz er 36 0.3 7 Samsung 14 0.5 Union Pacific 35 0.2 Production Advantage Consumer Advantage November 1, 2016 Measuring the Moat 42 Firm Interaction — Competition and Cooperation How firm s interact with one an other plays an important role in shaping sustainable value creation. 64 Here we not only consider how companies interact with their competitors but also how companies co -evolve. Game theory is one of the best tools to understand interaction. Game theory forces managers to put themselves in the shoes of other companies rather than viewing competition solely from their own p oint of view . The prisoner’s dilemma is the classic exampl e of two -person interaction in game theory. 65 We can consider the prisoner’s dilemma in a business context by looking at a simple case of capacity addition. Say two competitors, A and B, are deciding whether to add capacity. If competitor A adds capacity a nd B doesn’t, A gets an outsized payoff . (See the bottom left corner of Exhibit 29 .) Likewise, if B adds capacity and A doesn’t, B gets the large payoff (top right corner) . If neither expands, the total payoff for A and B is the highest ( top left corner). But i f both ad d capacity , the total payoff is the lowest (bottom right corner). If a company plays this game once, the optimal strategy is to add capacity. Consider the problem from the point of view of company A. The expected payoff from adding capacity is higher than the expected value of not expanding. The same logic applies from B’s standpo int. So adding capacity gets the competitors to the Nash equilibrium, the point where no competitor can gain by changing its strategy unilaterally. Exhib it 29 : Capacity Addition and the Prisoner's Dilemma Source: Credit Suisse. You might assume that companies always evaluate the potential reactions of their competitors . But that is frequently not the case. During a roundtable discussion in the mid -1990s, for instance, the chief financial officer of International Paper revealed that his company considered basic economic conditions when weighing the decision to build a new paper facility. But he conceded the absence of a game theoretic approach: “ What we never seem to factor in, however, is the response of our competitors. Who else is going to build a plant or machine at the same time? ”66 Pankaj Ghemawat , a professor of strategy , provides a more sophisticated example based on t he actual pricing study of a major pharmaceutical company. 67 The situation is that a challenger is readying to launch a A B A B A B A B 35 35 25 40 40 25 30 30 Competitor B Competitor A Don’t Expand Add Capacity Don’t Expand Add Capacity November 1, 2016 Measuring the Moat 43 substitute for one of the incumbent’s most profitable products. The incumbent’s task is to determine the pricing strategy that maximizes the value of its established product. Exhibit 30 shows the payoffs for the incumbent (I) and challenger (C) given various assumptions. For example, with no price change for the incumbent and very low pricing by the challenger, the model suggests a payoff of 350 for the i ncumbent and 190 for the challenger (upper left corner) . This analysis allowed the incumbent’s management to view the situation from the challenger’s point of view versus considering only what it hoped the challenger would do. Exhibit 30: The Payoff Matrix in the Face of a Challenger Product Launch Source: Adapted from Pankaj Ghemawat, Strategy and the Business Landscape -3rd Ed. (Upper Saddle River, NJ: Prentice -Hall, Inc., 200 9), 7 1. In our simple cases of capacity additions and product launch es , we treated competitor interaction as if it were a one -time event. In reality, companies interact with one another all the time. So the next level of analysis consider s repeated games. Robert Axelrod , a political scientist, ran a tournament to see which st rategy was most successful in an iterated prisoner’s dilemma. Instead of playing just once, the competitors played 200 rounds of the game with payoffs similar to that in Exhibit 29. 68 The winning strategy was tit for tat. Tit for tat starts by cooperating but then mimics its competitor’s last move. So if a competitor cuts price, a company employing tit for tat would cut price as well. If the competitor then raises prices, tit for tat immediately follows. In practice, tit for tat is effective only if compani es can judge clearly the intentions of their competitors. Game theory is particularly useful in considering pricing strategies and capacity additions. 69 A thorough review of a firm’s pricing actions and capacity additions and reductions can provide important insight into riva lry and rationality. You can do similar analysis at the industry level. Institutional memory, especially for cyclical businesses, appears too short to distinguish between a one -time and an iterated prisoner’s dilemma game. Companies and analysts can go beyond a payoff matrix that considers only one -time interaction and build a tree based on sequential actions. The approach here is similar to strategy in chess: look forward and reason back ward .70 Exhibit 31 is an ex ample of a game tree that Pankaj Ghemawat developed to reflect the payoffs from various decisions in the early days of the satellite radio industry when two companies, Sirius Satellite Radio and XM C I 190 350 C I 163 418 C I 155 454 C I 50 428 C I 168 507 C I 168 507 C I 138 511 C I 124 504 C I 129 585 C I 126 636 C I 129 585 C I 116 624 C I 128 669 No price change C has large price advantage C has small price advantage I neutralizes C’s advantage Incumbent (I) Price Challenger (C) Price Very Low Low Moderate High November 1, 2016 Measuring the Moat 44 Satellite Radio, went head -to-head .71 Sirius ’s choice was between escalating its investment by acquiring its own content and following the traditional radio model of licensing content . In either case , XM could have respond ed by choosing to escalate its own content investment . The payoffs at the end of the tree sh ow the economic consequences of the various scenarios. In reality, such analysis is difficult because the range of alternatives is large. But game trees provide insight into competitive interaction and hence the prospects for sustainable value creation. Exhibit 31: Mapping Sequential Moves in Content Acquisition for Satellite Radio Companies Source: Pankaj Ghemawat, Strategy and the Business Landscape -3rd Ed. (Upper Saddle River, NJ: Prentice -Hall, Inc., 2009), 74 -77. Another good example of game theory is the month -long turmoil in the interbank loan market during the fall of 2008 . John Stinespring and Brian Kench, professors of economics , describe the decisions that banks faced when the bankruptcy of Lehman Brothers sent a jolt of fear through the financial system . One result was that banks became reluctant to lend overnight to one another . This institutional lending and borrowing is essential to the liquidity of the financial system .72 Stinespring and Kench frame the decision in the throes of the crisis as a game of Loan or No Loan for two banks, A and B . (See Exhibit 32.) The payoffs in the table are the expected profits for each bank . (A’s profits are shown on the left , and B ’s are on the right .) If both banks choose “L oan, ” liquidity is preserved in the system , and both banks secure an expected profit of $10. If both banks choose “No Loan, ” interbank lending decreases, liquidity dries up, and both banks incur an expected loss of $10. Exhibit 3 2: Prisoner’s Dil emma in Interbank Loan Market Source: John Robert Stinespring and Brian T. Kench, “Explaining the Interbank Loan Crisis of 2008: A Teaching Note, ” February 1, 2009. See: http://ssrn.com/abstract=1305392 . Sirius XM Not escalate content XM Escalate content Not escalate content Escalate content Not escalate content Escalate content Sirius: $1.4B XM: $2.1B Sirius: $1.4B XM: $1.7B Sirius: $1.7B XM: $1.4B Sirius: $1.4B XM: $0.8B Loan Bank A Bank B No Loan 15, -15 No Loan -10, -10 10, 10 Loan -15, 15 November 1, 2016 Measuring the Moat 45 The best result for t he system is for both banks to L oan. Nevertheless, when we follow the logic of the payoff matrix, we see that A is unlikely to choose Loan when it considers what B might do . (The same logic appl ies for B .) If A thinks B will choose No Loan, A will select No Loan (-10 versus -15). If A thinks that B will choose Loan , A’s best response is still No Loan (+15 versus +10). It’s a classic prisoner’s dilemma , where the optimal strategy in a single interaction is the least attractive in repeate d interactions . Our discussion so far has focused on competition. But thoughtful strategic analysis also recognizes the role of co -evolution, or cooperation, in business. Not all business relationships are based on conflict. Sometimes companies outside the purview of a firm’s competitive set can heavily influence its value creation prospects. Consider the example electric car manufacturers and the makers of charging stations. A consumer is more likely to purchase a n electric vehicle when the number and quality of opt ions for charging increases. And charging stations are more valuable if there are more electric vehicles on the road . Complementors make the added value pie bigger. Competitors fight over a fixed pie. November 1, 2016 Measuring the Moat 46 Brands When queried about sustainable competitive advantage, many executives and investors cite the importance of brands. The question is whether brands, in and of themselves, are a source of advantage. Interbrand, a brand consultant, publishes annually its list of the most valuable brands in the world. 73 If brands are clearly linked to value creation, you should see a one -to-one relationship between brand strength and economic returns. This is not the case empirically. Of the companies that own the top t en most valuable brands, two barely earn ed their cost of capital in the latest fiscal year , and there is a weak correlation between brand ranking and economic return . (See Exhibit 33.) So a brand is clearly not sufficient to ensure that a company earns economic profits, much less sustainable economic profits. Exhibit 33: Brand Popularity Does Not Translate into Value Creation Source: Interbrand, Credit Suisse HOLT; Note: Returns data for financial companies represented by cash flow return on equity mi nus cost of equity. Note: Data for latest fiscal year as of 10/25/16. One way to think about brands is to consider what job a consumer is “hiring” a product or service to do. 74 Companies tend to structure their target markets by product category or by customer characteristics. But consumers do no t buy something just because the average consumer in their demographic is supposed to like it. Instead, they find they need something to get done and they hire a product to do the job . A company can differentiate itself and build a more enduring brand if it truly understands the job customers want done and develops its products or services accordingly. A brand, then, represents a product or service that is effective at getting a job done. -2 0 2 4 6 8 10 12 14 16 18 20 22 24 26 Apple Google (Alphabet) Coca-Cola Microsoft Toyota IBM Samsung Amazon.com Mercedes-Benz (Daimler) General Electric BMW McDonald's Disney Intel Facebook Cisco Oracle Nike Louis Vuitton (LVMH) Hennes & Mauritz Honda SAP Pepsi Gillette (Procter & Gamble) American Express 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 CFROI minus Discount Rate (%) Rank Best Global Brands, 2016 November 1, 2016 Measuring the Moat 47 From an economic standpoint, the best way to approach brands is to consider the amount of value added. A brand that represents a business benefiting from network effects or that confers horizontal differentiation may increase a customer’s willingness to pay . Google , for instance, benefits from the company’s network effects and adds value to the constituents in its ecosystem. The willingness to pay for a brand is high if you are in the habit of using it, have an em otional connection to it, trust it, or believe that it confers social status. It is less common for brands to add value by reducing supplier opportunity cost. A fledgling supplier may try to land a prestigious company, even at a discounted price, as part of its effort to est ablish credibility. To the degree that a brand plays a role in the perception of prestige or credibility, it can reduce supplier opportunity cost and hence increase add ed value for the branded company. November 1, 2016 Measuring the Moat 48 Management Skill and Luck Managerial skill entails creating a strategy and executi ng it effectively . But while better strategies will lead to more successes over time, a good pro cess provides no guarantee of a good outcome. In the highly complex environment in which companies compete, randomness , or l uck, also greatly influence s outcomes. 75 Customers, competitors, and technological change all contribute to uncertainty in decisions. This suggests that outsiders should evaluate management teams and the strategies they devise based on the processes they employ rather than the outcomes they achieve .76 There are numerous books that purport to guide management toward success. Most of the research in these books follows a common method: find successful businesses, identify the common practices of those businesses, and recommend that the manager imitate them. Perhaps the best known book of this genre is Good to Great by Jim Collins. He analyzed thousands of companies and s elected 11 that experienced an improvement from good to great results . He then identified the common attributes h e believed caused those companies to improve and recommended that other companies embrace those attributes .77 Among the traits were leadership, people, focus, and discipline. While Collins certainly has good intentions, the trouble is that causality is not clear in these examples. Because performance always depends on both skill and luck, a given strategy will su cceed only part of the time. Jerker Denrell, a professor of behavioral science , discusses two crucial ideas for anyone who is serious about assessing strategy. T he first is the undersampling of failure . By sampling only past winners, studies of business success fail to answer a critical question: How many of the companies that adopted a particula r strategy actually succeeded? 78 Let’s say two compan ies, A and B , pursue the same strategy and that A succeeds while B fails. A’s financial performance will look great , while B will die, dropping out of the sample. If we only draw our observations from the outcome rather than the strategy, we will only see company A. And because we generally associate success with skill, we will assume that company A’s favorable outcome was the result of skillful strategy. Naturally, by considering company B’s results as well , we have a better sense of the virtue of the strategy. To counter this effect, Denrell recommends evaluating all of the companies that purs ue a particular strategy so as to see both successes and failures. Denrell’s second idea is that it may be difficult to learn from superior performance. 79 The notion is that superior corporate performance is frequ ently the result of a cumulative process that benefitted from luck. Said differently, if you were to rewind the tape of time and play it again, the same companies would not succeed every time. Since some high -performing companies succeed by dint of luck, t here is very little to learn from them. Indeed, companies with good financial performance that compete in industries where cumulative processes are less pronounced may provide better lessons into the sources of success. Frustrated by a dearth of rigorous studies on business success, Michael Raynor and Mumtaz Ahmed , consultants at Deloitte , teamed up with Andrew Henderson, a professor of management, to do a statistical study to determine which companies achieve d levels of superior performance for a sufficie nt time to confidently rule out luck. The researchers studied more than 25,000 U .S. publicly traded companies from 1966 to 2010 and used quantile regression to rank them according to their relative performance on return on assets (ROA). (Bryant Matthews, w ho manages HOLT Model Development, r eplicated the ir process and found very similar results.) November 1, 2016 Measuring the Moat 49 This analysis, which controlled for extraneous factors such as survivor bias, company size, and financial leverage, allowed them to understand the empirical parameters of past corporate performance. They then weed ed out the instances of high performance th at were due to randomness in order to find truly great companies . The bad news is that a large percentage of above average corporate performance is attributable to luck. The good news is that some companies truly are exceptional performers. The ir analysis yielded a sample of 344 such companies. 80 Raynor and Ahmed used their model to see whether the firms hailed as exemplary performers in popular books on business success were likely simply the beneficiaries of luck. The authors examined 699 companies featured in 19 popular books on high performance and tested them to see how many were truly great. Of the companies that they were able to cat egorize, just 12 percent met their criteria. 81 In an earlier paper they wrote, “Our results show that it is easy to be fooled by randomness, and we suspect that a number of the firms that are identified as sus tained superior performers based on 5 -year or 10 -year windows may be random walkers rather than the possessors of exceptional reso urces.” 82 Once the researchers identified their sample of truly skillful companies, they did what other authors of the “success study” genre do: they studied the strategies of those superior companies for common patterns that might prove useful to busine ss executives trying to replicate such sustained success. They divided the skil lful companies into two groups according to the performance threshold they crossed often enough to rule out luck: Miracle Workers (top 10 percent of ROA), which consisted of 174 companies, and Long Runners (top 20 -40 percent of ROA), which consisted of 170 companies. They labeled the final group Average Joes. By identifying a sample of truly superior companies, the authors were able to study the b ehaviors that appeared to be behind their performance advantages. They couldn’t find any commonalities when they looked at specific actions but made a breakthrough when they examined the general manner in which these companies thought. The manner was highl y consistent and fit with a generic differentiation strategy. Raynor and Ahmed argue that , when considering business decisions, the ski llful companies acted as if they follow ed two essential rules: 1. Better before cheaper : compete on differentiators other than price. 2. Revenue before cost : prioritize increasing revenue over reducing costs. Based on this analysis, they suggest two steps for managers. The first is to gain a clear sense of a company’s competitive position and profit formula. Following this step , a company should understand clearly the composition of its returns (return on assets = return on sales x total asset turnover) and its relative competitive position. Companies often compare their current financial perfo rmance to the past rather than to that of competitors. Business is a game of relative, not absolute, performance. The second step is to make resource allocation decisions consistent with the rules. S o when faced with a choice between offering a product or service with a low price and minimal standards versus a higher price and superior benefits, such as a strong brand or greater convenience, executives should opt for the latter. Or a company should prefer a merger that realizes the opportunity to expand versus one that simply achieves economies of scale. November 1, 2016 Measuring the Moat 50 Regression T oward the Mean There is regression toward the mean any time the correlation between two assessments of the same measure over time is less than 1.0. The rate of regression is a function of the correlation coefficient. A correlation coefficient of 1.0 indicates that the ne xt result is exactly predictable from the last, and a correlation of zero shows that the outcome is random. Activities with high correlations are based more on skill, and those with low correlations are based more on luck. The second column of Exhibit 34 shows the year -to-year correlations for CFROI for 25 industries. The data are intuitive. Industries selling consumer packaged goods are less subject to rapid regression than industries with exposure to commodities , financial s, or technology. What’s valuable is that the exhibit provides a quantitative means to think about the rate of regression. The third column of the exhibit shows the average CFROI for each industry. This is essentially the CFROI to which an individual com pany’s results regress. The combination of a qualitative framework in the report and the quantitative results below provides an investor or executive with a robust framework to assess sustainable value creation. Exhibit 34: Rate of Regression and Towa rd What Mean CFROIs Regress for 25 Industries Source: Bryant Matthews and David A. Holland, “HOLT Industry Profitability Handbook,” Credit Suisse HOLT Market Commentary , October 4, 2016. How Much Regression? Toward What Mean? Sector One-Year Correlation Coefficient Long-Term Average CFROI (%) Food, Beverage, & Tobacco 0.95 8.6 Household & P ersonal P roducts 0.95 12.3 Food & Staples Retailing 0.93 8.2 Consumer Services 0.92 8.0 Commercial & P rofessional Services 0.91 11.1 Capital Goods 0.89 6.7 Health Care E quipment & Services 0.89 11.7 P harmaceuticals, Biotechnology, & Life Sciences 0.89 8.1 Media 0.88 9.9 Transportation 0.87 5.2 Consumer Durables & Apparel 0.87 8.5 Retailing 0.87 8.7 Regulated Utilities 0.86 3.2 Software & Services 0.85 12.3 Automobiles & Components 0.83 5.2 Telecommunication Services 0.83 6.1 Technology Hardware & E quipment 0.82 6.8 Utilities 0.82 4.1 I nsurance 0.81 8.5 E nergy 0.78 5.7 Materials 0.78 4.9 Semiconductors & Semiconductor E quipment 0.77 6.6 Real E state 0.77 4.6 Banks 0.76 9.3 Diversified Financials 0.73 9.0 November 1, 2016 Measuring the Moat 51 Bringing It All Back Together Stock prices reflect expectations for future financial performance. Accordingly, an investor’s task is to anticipate revisions in those expectations. A firm grasp o f the prospects for value creation is a critical facet of this analysis. But value creation by itself does not lead to superio r stock price performance if the market fully anticipates that value creation. The expectations investing process has three parts: 83 1. Estimate price -implied expectations . We first read the expectations embedded in a stock with a long - term discounted cash flow model (DCF) . We use a DCF model because it mirrors the way the market prices stocks. 2. Identify expectations opportunities . Once we understand expectations, we apply the appropriate strategic and financial tools to determine where and when revisions ar e likely to occur. A proper expectations analysis reveals whether a stock price is most sensitive to revisions in a company’s sales, operating costs, or investment need s so that investors can focus on the revisions that matter most. The strategic analysis in this report is the heart of security analysis and provides the surest means to anticipate expectations revisions. 3. Buy, sell, or hold . Using expected -value analysis, we are now in a position to make informed buy, sell, or hold decisions. A thorough ana lysis of a company’s prospects for sustainable value creation is essential. This analysis can then intelli gently inform a financial model to determine whether or not a particular stock offers prospects for superior returns. November 1, 2016 Measuring the Moat 52 Warren Buffett on Economic Moat s What we refer to as a “moat” is what other people might call competitive advantage . . . It’s something that differentiates the company from its nearest competitors – either in service or low cost or taste or some other perceived virtue that the product possesses in the mind of the consumer versus the next best alternative . . . There are various kinds of moats. All economic moats are either widening or narrowing – even though you can’t see it. Outstanding Investor Digest , June 30, 1993 Look for the durability of the franchise. The most important thing to me is figuring out how big a moat there is around the business. What I love, of course, is a big castle and a big moat with piranhas and crocodiles. Linda Grant, “Striking Out at Wall Street,” U.S. News & World Report , June 12, 1994 The key to investing is not assessing how much an industry is going to affect society, or how much it will grow, but rather determining the competitive advantage of any gi ven company and, above all, the durability of that advantage. The products or services that have wide, sustainable moats around them are the ones that deliver rewards to investors. Warren Buffett and Carol Loomis, “Mr. Buffett on the Stock Market,” Fortun e, November 22, 1999 We think of every business as an economic castle. And castles are subject to marauders. And in capitalism, with any castle . . . you have to expect . . . that millions of people out there . . . are thinking about ways to take your cas tle away. Then the question is, “ What kind of moat do you have aroun d that castle that protects it? ” Outstanding Investor Digest , December 18, 2000 When our long -term competitive position improves . . . we describe the phenomenon as “widening the moat.” And doing that is essential if we are to have the kind of business we want a decade or two from now. We always, of course, hope to earn more money in the short -term. But when short -term and long - term conflict, widening the moat must take precedence. Berk shire Hathaway Letter to Shareholders , 2005 A truly great business must have an enduring “moat” that protects excellent returns on invested capital.

The dynamics of capitalism guarantee that competitors will repeatedly assault any business “castle” that is earning high returns . . . Our criterion of “enduring” causes us to rule out companies in industries prone to rapid and continuous change. Though capitalism’s “creative destruction” is highly beneficial for society, it precludes investment certainty. A m oat that must be continuously rebuilt will eventually be no moat at all . . . Additionally, this criterion eliminates the business whose success depends on having a great manager. Berkshire Hathaway Letter to Shareholders , 2007 November 1, 2016 Measuring the Moat 53 Appendix A: Checklist for Assessing Value Creation Overview In w hat stage of the competitive life cycle is the company? Is the company currently earning a return above its cost of capital? Are return s on invested capital increasing, decreasing, or stable? Why? What is the trend in the company’ s investment spending , including mergers and acquisitions ? Lay of the Land What percentage of the industry does each player represent? What is each player’ s level of profitability? What have the historical tren ds in market share been? How stable is the industry? How stable is market share? What do pricing trends look like? What class does the industry fall into — fragmented, emerging, mature, declining, international, network, or hypercompetitive? The First Three of the Five Forces How much leverage do suppliers have? Can companies pass price increases from their suppliers on to their customers? Are there substitute products available? Are there switching costs? How much leverage do buyers have? How informed are the buyers? Barriers to Entry What are the rates of entry and exit in the industry? How will the incumbents react to the threat of new entrants? What is the reputation of incumbents? How specific are the asset s? What is the minimum efficient production scale? Does the industry have excess capacity? Is there a way to differentiate the product? What is the anticipated payoff for a new entrant? Do incumbents have preco mmitment contracts? Do incumbents have costly licenses or patents? Are there benefits from the learning curve? Rivalry Is there pricing coordination? What is the industry concentration? What is the size distribution of firms? How si milar are the firms in incentives, corporate philosophy, and ownership structure ? Is there demand variability? Are there high fixed costs? Is the industry growing? November 1, 2016 Measuring the Moat 54 Disruption and Disintegration Is the industry vulnerable to disruptive innovation? Do new innovations foster product improvements? Is the innovation pro gressing faster than the market’ s needs? Have established players passed the performance threshold? Is the industry organized vertically, or has there been a shift to horizontal markets? Firm Specific Does the firm have production advantages? Is there instability in the business structure? Is there complexity requiring know -how or coordination capabilities? How quickly are the process costs changing? Does the firm have any patents, copyrights, trademarks, etc.? Are there economies of scale? What does the firm’ s distribution scal e look like? Are assets and revenue clustered geographically? Are there purchasing advantages with size? Are there economies of scope? Are there diverse research profiles? Are there consumer advantages? Is there habit or horizontal differentiation? Do people prefer the product to competing products? Are there lots of product attributes that customers weigh? Can customers only assess the product through trial? Is there customer lock -in? Are there high switching costs? Is the network radial or interactive? What is the source and longevity of added value? Are there external s ources of added value (subsid ies, tariffs, quotas, and competitive or environmental regulations)? Firm Interaction — Competition and Coordination Does the industry include complementors? Is the value of the pie growing because of companies that are not competitors ? Or, are new companies tak ing share from a pie with fixed value ? Brands Do customers want to “hire” the brand fo r the job to be done? Does the brand increase willingness to pay? Do customers have an emotional connection to the brand? Do customers trust the product because of the name? Does the brand imply social status? Can you reduce supplier operating cost with your name? November 1, 2016 Measuring the Moat 55 Appendix B: Profit Pool Analysis for Health Care Our profit pool example in the body of this report showed one of the most value -destructive industries ( airlines ). Here , we conduct a similar exercise for the U .S. health care sector , which has consistently created value , as well as pharmaceuticals, the sector’s largest constituent industry. We begin by using Credit Suisse HOLT data to examine the returns across various activities in the h ealth care value chain . (See Exhibit 35.) Exhibit 35: U.S. Health Care Sector Profit Pools b y Activity, 200 5-201 5 Source: Credit Suisse HOLT. 0 3 6 9 12 15 CFROI minus Discount Rate (Percent) Share of Industry Gross Investment 2010 Pharmaceuticals HC tech HC providers & services 100% HC equipment & supplies Biotech Life sciences 0 3 6 9 12 15 CFROI minus Discount Rate (Percent) Share of Industry Gross Investment 2015 Pharmaceuticals HC tech HC providers & services 100% HC equipment & supplies Biotech Life sciences 0 3 6 9 12 15 CFROI minus Discount Rate (Percent) Share of Industry Gross Investment 2005 Pharmaceuticals HC tech HC providers & services 100% HC equipment & supplies Biotech Life sciences November 1, 2016 Measuring the Moat 56 We see from the horizontal axis that e ach activity’s share of the industry’s total investment has shifted slightly over the past decade , with pharmaceuticals shrinking and health care equipment & supplies and biotech growing . The vertical axis tells a similar story, with economic returns falling for pharmaceuticals and rising for biotech, indicating that biotech is capturing a much greater share of the value pie within the overall sector . We can demonstrate this with some simple calculations. By summing the area of each of the blocks, we find that the total value pie for the sector was roughly $100 billion in 2005 , $1 20 billion in 20 10 , and $190 billion in 201 5. The pharmaceutical industry saw its share of that pie fa ll from roughly one -half in 200 5 to about one -third in 2015 , while the biotechnology industry rose from about one -tenth to one -quarter . We can zoom in on the U .S. pharmaceuticals industry . (See Exhibit 36). Creating a narrative to explain the rise and fall of the various competitors can provide important clues about what it takes to generate sustainable value creation. At a group level, it is clear that the pharmaceuticals industry has consistently earned a bove its cost of capital. However, those returns have fallen over the last decade due in part to a dearth of blockbuster drugs and increased generic competition following some key patent expirations. 84 November 1, 2016 Measuring the Moat 57 Exhibit 36: U.S. Pharmaceuticals Industry Profit Pools by Company, 200 5-201 5 Source: Credit Suisse HOLT. Note: J&J = Johnson & Johnson. 0 5 10 15 20 25 30 35 CFROI minus Discount Rate (Percent) Share of Industry Gross Investment 2005 Pfizer Bristol - Myers Other J&J Eli Lilly 100% Merck Wyeth Schering - Plough Allergan, Inc Actavis Valeant 0 5 10 15 20 25 30 35 CFROI minus Discount Rate (Percent) Share of Industry Gross Investment 2010 Pfizer Bristol - Myers Other J&J Eli Lilly 100% Merck Allergan, Inc Actavis Valeant 0 5 10 15 20 25 30 35 CFROI minus Discount Rate (Percent) Share of Industry Gross Investment 2015 Pfizer Bristol - Myers Other J&J Eli Lilly 100% Merck Allergan PLC Valeant November 1, 2016 Meas uring the Moat 58 Another thing that stands out is the consolidation and declining returns at the top of the industry. The largest three firms increased their overall share of the industry substantially, due largely to merger activity . B ut over that time , their economic returns fe ll more sharply than did the returns of the smaller firms in the industry. We can also determine the total size of the profit pool by measuring and summi ng the value of each block. The total economic profit of the industry rose from roughly $50 billion in 2005 to $53 billion in 20 10, and rose to $6 0 billion in 201 5. The top three firms represented 61 percent of the industr y’s total economic value in 2015 , down from 72 percent in 2005 . November 1, 2016 Measuring the Moat 59 Endnotes 1 Bartley J. Madden, CFROI Valuation: A Total System Approach to Valuing the Firm (New York: Butterworth - Heinemann, 1999); Michael Mauboussin and Paul Johnson, “Competitive Advantage Period (CAP): The Neglected Value Driver,” Financial Management , Vol. 26, No. 2, Summer 1997 , 67 -74 ; Alfred Rappaport, Creating Shareholder Value : A Guide for Managers and Investors – Revised and Updated (New York: Free Press, 1998) ; William E. Fruhan, Jr., Financial Strategy : Studies in the Creation, Transfer, and Destruction of Shareholder Value (Homewood, Il. : Richard D. Irwin, Inc., 1979); Merton H. Miller and Franco Modigliani, “Dividend Policy, Growth, and the Valuation of Shares,” The Journal of Business , Vol. 34, October 1961, 411 -433. For empiri cal research , see Brett C. Olsen, “Firms and the Competitive Advantage Period,” Journal of In vesting , Vol. 22, No. 4, Winter 2013, 41 -50 and Michael J. Mauboussin, Dan Callahan, and Darius Majd, “The Base Rate Book: Integrating the Past to Better Anticipate the Future,” Credit Suisse Global Financial Strategies , September 26, 2016. 2 David Besanko, David Dranove, Mark Shanley, and Scott Schaefer, Economics of Strategy -6th Ed. (Hoboken, NJ: John Wiley & Sons, 201 3), 294 -295. 3 Horace Secrist, The Triumph of Mediocrity in Business (Evanston, IL: Bureau of Business Research, Northwestern University, 1933); Pankaj Ghemawat, Commitment: The Dynamic of Strategy (New York: Free Press, 1991), 82; and Bartley J. Madden, “The CFROI Life Cycle,” Journal of Investing, Vol. 5, No. 2, Summer 1996, 10 -20. 4 Robert R. Wiggins and Timothy W. Ruefli, “Schumpeter’s Ghost: Is Hypercompetition Making the Best of Times Shorter?, ” Strategic Management Journal , Vol. 26, No. 10, October 2005, 887 -911; Robert R. Wiggins and Timothy W. Ruefli, “Sustained Competitive Adv antage: Temporal Dynamics and the Incidence and Persistence of Superior Economic Performance,” Organizational Science, Vol. 13, No. 1, January - February 2002, 82 -105; Richard A. D’ Aveni, Beat the Commodity Trap: How to Maximize Your Competitive Position and Increase Your Pricing Power (Boston, MA: Harvard Business Press, 2010); Rita Gunther McGrath, The End of Competitive Advantage: How to Keep Your Strategy Moving as Fast as Your Business (Boston, MA: Harvard Business Review Press, 2013). Wiggins and Ruefli find evidence of sustained competitive advantage not as the result of one main advantage but rather of smaller, concatenating advantages. Consistent with this is Kuo -Feng Huang, Romano Dyerson, Lei -Yu Wu, and G. Harindranath, “From Temporary Competitive Ad vantage to Sustainable Competitive Advantage,” British Journal of Management , Vol. 26, No. 4, October 2015, 617 -636. See also Tammy L. Madsen and Michael J. Leiblein, “What Factors Affect the Persistence of an Innovation Advantage? Journal of Management St udies, Vol. 52, No. 8, December 2015, 1097 -1127. 5 Bryant Matthews and Raymond Stokes, “Fade and the Persistence of Corporate Returns ,” Credit Suisse HOLT Notes , Credit Suisse, November 2012; Bartley J. Madden, “The CFROI Life Cycle,” Journal of Investing, Vol. 5, No. 2, Summer 1996 , 10 -20 . 6 Estimates for the cost of equity capital come from Aswath Damodaran, a professor of finance. See http://page s.stern.nyu.edu/~adamodar/New_Home_Page/datafile/implpr.html . 7 For expectations, see Alfred Rappaport and Michael J. Mauboussin, Expectations Investing: Reading Stock Prices for Better Returns (Boston , MA : Harvard Business School Press, 2001), 51 -52. For sustained value creation and excess returns, see Adelina Gschwandtner and Michael Hauser, “Profit Persistence and Stock Returns,” Applied Economics , Vol. 48, No. 37, February 2016. 8 Outstanding Investor Digest , December 18, 2000; Outstanding Investor Digest , June 30, 1993; Also, economic moats are a key investment theme for Morningstar, which offers research aimed at uncovering companies with wide and stable or improving economic moats. See: Matthew Coffina, “The Morningstar Guide to Wide -Moat Stock In vesting,” Morningstar Stock Investor , April 2013; Paul Larson, “Moats: Sources and Outcomes – Not all moats are created equal, and we delve into the differences,” Morningstar Equity Research , June 2012; and Heather Brilliant and Elizabeth Collins, Why Moat s Matter: The Morningstar Approach to Stock Investing (Hoboken, NJ: John Wiley & Sons, 2014). November 1, 2016 Measuring the Moat 60 9 Peter Lynch , with John Rothchild, One Up On Wall Street: How To Use What You Already Know To Make Money in the Market (New York: Penguin Books USA, 1989) , 121 . 10 For a study based on total shareholder returns , see Richard Foster and Sarah Kaplan, Creative Destruction: Why Companies That Are Built to Last Underperform the Market – and How to Successfully Transform Them (New York: Doubleday, 2001). This work addre sses a different question than the one we pose here. 11 Thomas Fritz, The Competitive Advantage Period and the Industry Advantage Period: Assessing the Sustainability and Determinants of Superior Economic Performance (Wiesbaden , Germany : Gabler, 2008); Anita M . McGahan and Michael E. Porter, “The emergence and sustainability of abnormal profits,” Strategic Organization , Vol. 1, No. 1, February 2003, 79 -108; Anita M. McGahan and Michael E. Porter, “How Much Does Industry Matter, Really?” Strategic Managem ent Journal , Vol . 18, Summer Special Issue 1997, 15 -30; Thomas C. Powell, “How Much Does Industry Matter? An Alternative Empirical Test,” Strategic Management Journal , Vol. 17, No. 4, April 1996, 323 -334; Richard P. Rumelt, “How Much Does Industry Matter?” Strategic Management Journal , Vol. 12, No. 3, March 1991, 167 -185 ; Richard Schmalensee, “Do Markets Differ Much?” American Economic Review , Vol. 75, No. 3, June 1983, 341 -351. 12 Anita M. McGahan and Michael E. Porter, “The emergence and sustainability of abnormal profits,” Strategic Organization , Vol. 1, No. 1, February 2003, 79 -108. In Ekaterina V. Karniouchina, Stephen J. Carson, Jeremy C. Short, and David J. Ketchen Jr., “Extending the Firm Vs. Industry Debate: Does Industry Life Cycle Stage Matter?” Strategic Management Journal , Vol. 34, No. 8, August 2013, 1010 -1018, the researchers find that the influence of the industry on the variance in firm performance is progressively stronger as the industry moves from growth to maturity to decline. In Da vid S chröder and Andrew Yim, “Industry Effects in Firm and Segment Profitability Forecasting: Corporate Diversification, Industry Classification, and Estimate Reliability,” Working Paper , March 2016, the authors find considerable industry effects, but only for focused firms. 13 Bruce Greenwald and Judd Kahn, Competition Demystified: A Radically Simplified Approach to Business Strategy (New York: Portfolio, 2005), 52 -54. 14 Lauren Cohen and Andrea Frazzini, “Economic Links and Predictable Returns,” Journal of F inance , Vol. 63, No. 4, August 2008, 1977 -2011. Also, Yuyan Guan, M. H. Franco Wong, and Yue Zhang, “Analyst Following Along the Supply Chain,” Review of Accounting Studies , Vol. 20, No. 1, March 2015, 210 -241. 15 Orit Gadiesh and James L. Gilbert, “Profit Pools: A Fresh Look at Strategy,” Harvard Business Review , May -June 1998 , 139 -147 ; Orit Gadiesh and James L. Gilbert, “How To Map Your Industry’s Profit Pool,” Harvard Business Review , May -June 1998 , 149 -162 ; Also Bryant Matthews, David A. Holland, Michael J. Mauboussin, and Dan Callahan, “Global Industry Profit Pools,” C redit Suisse HOLT Market Commentary , July 2016. 16 Michael E. Porter, “The Five Competitive Forces that Shape Strategy,” Harvard Business Review , January 200 8, 78 -93. 17 International Air Transport Association, "Profitability and the air transport value chain," IATA Economics Briefing No. 10 , June 2013, 19 -20; Pankaj Ghemawat, Strategy and the Business Landscape -3rd Ed. (Upper Saddle River, NJ: Pren tice -Hall, Inc., 2009). 18 International Air Transport Association, “ Industry Profitability Improves ,” Press Release No. 27 , June 2, 201 6. 19 Andrew Frye and Dakin Campbell, “Buffett Says Pricing Power More Important than Good Management,” Bloomberg , February 18, 2011. For more on pricing strategy, see Andreas Hinterhuber and Stephan Liozu, “Is It Time to Rethink Your Pricing Strategy?” MIT Sloan Management Review , Summer 2012. 20 Michael E . Porter, Competitive Strategy: Techniques for Analyzing Industries and Competitors (New York: The Free Press, 1980). 21 Joan Magretta, Understanding Michael Porter: The Essential Guide to Competition and Strategy (Boston , MA : Harvard Business Review Press, 2012); Michael E . Porter, “The Five Competitive Forces That Shape Strategy,” Harvard Business Review , January 2008 , 78 -93 . 22 This section relies heavily on Rappaport and Mauboussin, 54 -57. November 1, 2016 Measuring the Moat 61 23 Brian Headd, Alfred Nucci, and Richard Boden, “What Matters More: Bus iness Exit Rates or Business Survival Rates ?” BDS Statistical Brief , U.S. Census Bureau, 2010; Glenn R. Carroll and Michael T. Hannan, The Demography of Corporations and Industries (Princeton, NJ: Princeton University Press, 2000), 51 -52; Deborah Gage, “The Venture Capital Secret: 3 Out of 4 Start -Ups Fail,” Wall Street Journal , September 20, 2012. For a distinction between closure and failure, see Brian Headd, “Redefining Business Success: Distinguishing Be tween Closure and Failure,” Small Business Economics , Vol. 21, No. 1, August 20 03, 51 - 61. 24 Steven Klepper, Experimental Capitalism: The Nanoeconomics of American High -Tech Industries (Princeton, NJ: Princeton University Press, 2016); Steven Klepper, “Ent ry, Exit, Growth, and Innovation over the Product Life Cycle,” American Economic Review , Vol. 86, No. 3, June 1996, 562 -583; Steven Klepper, “Industry Life Cycles,” Industrial and Corporate Change , Vol. 6, No. 1, January 1997, 145 -181; Steven Klepper and Elizabeth Graddy, “The evolution of new industries and the determinants of market structure,” RAND Journal of Economics , Vol. 21, No. 1, Spring 1990, 27 -44; Rajshree Agarwal and Serguey Braguinsky, “Industry Evolution and Entrepreneurship: Steven Klepper’s Contributions to Industrial Organization, Strategy, Technological Change, and Entrepreneurship,” Strategic Entrepreneurship Journal , Vol. 9, No. 4, December 2015, 380 -397; Robin Gustafsson, Mikko Jääskelainen, Markku Maula, and Juha Uotila, “Emergence of Industries: A Review and Future Directions,” International Journal of Management Reviews , Vol. 18, No. 1, January 2016, 28 -50 ; and Mariana Mazzucato, Firm Si ze, Innovation and Market Structure: The Evolution of Industry Concentration and Instability (Northampton, MA: Edward Elgar Publishing, 2000), 34. 25 Timothy Dunne, Mark J. Roberts, and Larry Samuelson, “Patterns of firm entry and exit in U.S.

manufacturin g industries,” RAND Journal of Economics , Vol. 19, No. 4, Winter 1988, 495 -515 and Timothy Dunne, Shawn D. Klimek, Mark J. Roberts, and Daniel Yi Xu, “Entry, Exit, and the Determinants of Market Structure,” The RAND Journal of Economics , Vol. 44, No. 3, Fa ll 2013, 462 -487. 26 Here we follow closely the presentation format of Besanko, Dranove, Shanley, and Schaefer, 197 -198 . 27 Bryant Matthews and Raymond Stokes, “Fade and the Persistence of Corporate Returns,” Credit Suisse HOLT Notes , Credit Suisse, November 2012; Richard Disney, Jonathan Haskel, and Ylva Heden, "Entry, Exit and Establishment Survival in UK Manufacturing," Journal of Industrial Economics , Vol. 51, No. 1, March 2003, 91 -112. 28 We base this discussion on Sharon M. Oste r, Modern Competitive Analysis (Oxford: Oxford University Press, 1999), 57 -82. 29 A similar example is the competition between CSX and Norfolk Southern to deliver coal to Gainesville, Florida. See Adam M. Brandenburger and Barry J. Nalebuff, Co -opetition : 1. A Revolutionary Mindset That Combines Competition and Cooperation. 2. The Game Theory Strategy That’s Changing the Game of Business (New York: Doubleday, 1996), 76 -80. For a survey of the research on co -opetition, see Ricarda B. Bouncken, Johanna Gast, Sascha Kraus, and Marcel Bogers, “Coopetition: a Systematic Review, Synthesis, and Future Research Directions,” Review of Managerial Science , Vo l. 9, No. 3, July 2015, 577 -601 and Stefanie Dorn, Bastian Schweiger, and Sascha Albers, “Levels, Phases and The mes of Coopetition: A Systematic Literature Review and Research Agenda,” European Management Journal , Vol. 34, No. 5, October 2016, 484 -500 . 30 Besanko, Dranove, Shanley, and Schaefer, 119 -120 . 31 Brandenburger and Nalebuff, 72 -76. 32 Besanko, Dranove, Shanley, and Schaefer , 77 -78 . 33 Carl Shapiro and Hal R. Varian, Information Rules: A Strategic Guide to the Network Economy (Boston , MA : Harvard Business School Press, 1999), 173 -225. Also, Michael J. Mauboussin, “Exploring Network Economics,” Mauboussin on Strategy , October 11, 2004. 34 Frank Linde, Maurice Kock, and Alexandra Gorges, “Network Effects of Digital Information Goods: A Proposal for the Operationalization of Direct and Indirect Network Effects,” International Journal of Business Research , Vol. 12, No. 3, July 2012 ; Allan Afuah, “Are Network Effects Really All About Size? The Role of Structure and Conduct,” Strategic Management Journal , Vol. 34, No. 3, March 2013, 257 -273. November 1, 2016 Measuring the Moat 62 35 Robert Smiley, “Empirical Evidence on Strategic Entry Deterrence,” International Journal of Industrial Organization , Vol. 6, No. 2, June 1988, 167 -180; J. Anthony Cookson, “Anticipated Entry and Entry Deterrence: Evidence from the American Casino Industry,” Working Paper , December 2015; and Austan Goolsbee and Chad Syverson, “How Do Incumbents Respond to the Threat of Entry? Evidence from the Major Airlines,” Quarterly Journal of Economics , Vol. 123, No. 4, November 2008, 1611 -1633. 36 Colin Camerer and Dan Lovallo, “Overconfidence and Excess Entry: An Experimental Approach,” American Economic Review , Vol. 89, No. 1, March 1999, 306 -318. Other relevant papers on entry and exit include Daniel W. Elfenbein, Anne Marie Knott, and Rachel Croson, “Equity Stakes and Exit: An Experimental Approach to Decomposing Exit Delay,” Strategic Management Journal , Forthcoming and Daylian M. Cain, Don A. Moore, and Uriel Haran, “Making Sense of Overconfidence in Market Entry,” Strategic Management Journal , Vol. 36, No. 1, January 2015, 1 -18. 37 Daniel Kahneman and Amos Tversky, “On the Psychology of Prediction,” Psychological Review, Vol. 80, No. 4, July 1973, 237 -251. Also Michael J. Mauboussin, Dan Callahan, and Darius Majd, “The Base Rate Book: Integrating the Past to Better Anticipate the Future,” Credit Suisse Global Financial Strategies , September 26, 2016. 38 Michael J. Mauboussin, Think Twice: Harnessing the Power of Counterintuition (Boston , MA : Harvard Business Press, 2009), 1 -16. 39 Oster, 33 -34. 40 Kewei Hou and David T. Robinson, “Industry Concent ration and Average Stock Returns,” Journal of Finance , Vol. 61, No. 4, August 2006, 1927 -1956. 41 John Asker, Joan Farre -Mensa, and Alexander Ljungqvist, “Corporate Investment and Stock Market Listing: A Puzzle?” European Corporate Governance Institute (EC GI) - Finance Research Paper Series , April 22, 2013. 42 Clayton M. Christensen, The Innovator’s Dilemma: When New Technologies Cause Great Companies to Fail (Boston , MA : Harvard Business School Press, 1997). For additional discussion (including criticism) of the model, see Clayton M. Christensen, Michael E. Raynor, and Rory McDonald, “What Is Disruptive Innovation?” Harvard Business Review , December 20 15; Andrew A. King and Baljir Baatartogtokh, “How Useful I s the Theory of Disruptive Innovation,” MIT Sloan Management Review , Vol. 57, No. 1, Fall 2015; Juan Pablo Vázquez Sampere, Martin J. Bienenstock, and Ezra W. Zuckerman, “Debating Disruptive Innovation,” MIT Sloan Management Review , Spring 2016. A game cal led Colonel Blotto has some interesting parallels with the disruptive innovation model. See Michael J. Mauboussin , The Success Equation: Untangling Skill and Luck in Business, Sports, and Investing (Boston , MA : Harvard Business Review Press, 2012), 179 -185 . 43 Christensen , 32. 44 Clayton M . Christensen and Michael E. Raynor, The Innovator’s Solution: Creating and Sustaining Successful Growth (Boston , MA : Harvard Business School Publishing, 2003), 43 -46. 45 Clayton M. Christensen, Michael E. Raynor, and Scott D. Anthony, “Six Keys to Building New Markets by Unleashing Disruptive Innovation,” Harvard Management Update , January 2003. 46 Clayton M. Christensen, Matt Verlinden, and George Westerman, “Disruption, Disintegration and the Dissipation of Differentiability,” Industrial and Corporate Change , Vol. 11, No. 5, November 2002, 955 -993; Carliss Y. Baldwin and Kim B. Clark, Design Rules: The Power of Modularity (Cambridge, MA: The MIT Press, 2000). 47 Michael J. Mauboussin, Think Twice: Harnessing the Power of Counterintuition (Boston , MA : Harvard Business Press, 2009), 89 -91. 48 Joseph L. Bower and Clark G. Gilbert, From Resource Allocation to Strategy (Oxford: Oxford University Press, 2005); Robert A. Burgelm an, Strategy I s Destiny: How Strategy -Making Shapes a Company’s Future (New York: Free Press, 2002); William P. Barrett, The Red Queen among Organizations: How Competition Evolves (Princeton, NJ: Princeton University Press, 2008). 49 Michael E. Porter, “W hat is Strategy?” Harvard Business Review , November -December 1996, 61 -78; Richard P. Rumelt, Good Strategy Bad Strategy: The Difference and Why It Matters (New York: Crown November 1, 2016 Measuring the Moat 63 Business, 2011). On trade -offs, see Frances Frei and Anne Morriss, Uncommon Service: How to Win by Putting Customers at the Core of Your Business (Boston, MA: Harvard Business Review Press, 2012). 50 Adam M. Brandenburger and Harborne W. Stuart, Jr., “Value -Based Business Strategy,” Journal of Economics & Management Strategy , Vol. 5, No. 1, Spring 1996, 5 -24. 51 Adam M. Brandenburger and Barry J. Nalebuff, Co -opetition : 1. A Revolutionary Mindset That Combines Competition and Cooperation. 2. The Game Theory Strategy That’s Changing the Game of Business (New York: Doubleday, 1996), 16 -19. 52 Magretta, 73 -84. 53 Ibid., 21 -28. 54 Mae Anderson, “From idea to store shelf: a new product is born,” Associated Press , March 4, 2012; Procter & Gamble Q3 2011 earnings call, April 28, 2011. 55 Jeff rey Williams, “How Sustainable Is Your Competitive Advantage?” California Management Review , Vol. 34, No. 3, 1992, 29 -51 . 56 Adam M. Brandenburger and Harborne W. Stuart, Jr., “Value -Based Business Strategy,” Journal of Economics & Management Strategy , Vol. 5, 1, Spring 1996, 5 -24. 57 Richard E. Caves and P ankaj Ghemawat, “Identifying Mobility Barriers,” Strategic Management Journal , Vol. 13, No. 1, 1992, 1 -12. 58 For example, see http://flowingdata.com/2013/06/2 6/grocery -store -geography/ . 59 Jim Kling, “From Hypertension to Angina to Viagra,” Modern Drug Discovery , Vol. 1, No. 2, November - December 1998. 60 Bruce Greenwald and Judd Kahn, “All Strategy Is Local,” Harvard Business Review , September 2005 , 94 - 104 . 61 Bruce C. N. Greenwald, Judd Kahn, Paul D. Sonkin and Michael van Biema, Value Investing: From Graham to Buffett and Beyond (New York: John Wiley & Sons, 2001), 77 -78. For interesting, if controversial, research on brand preference, see: Samuel M. McClure, Jian Li, Damon Tomlin, Kim S. Cypert, Latané M. Montague, and P. Read Montague, “Neural Correlates of Behavioral Preference for Culturally Familiar Drinks,” Neuron , Vol. 44, No. 2, October 14, 2004, 379 -387. 62 Everett M. Rogers, The Diffusion of Innovation s (New York: Free Press, 1995). Also, Michael J. Mauboussin and Dan Callahan, “Total Addressable Market: Methods to Estimate a Company’s Sales,” Credit Suisse Global Financial Strategies , September 1, 2015. 63 For a more complete discussion, see Oster, 326 -346. 64 A survey by McKinsey shows that companies don’t react to competitive threats as management theory suggests they should. See “How Companies Respond to Competitors: A McKinsey Global Survey,” McKinsey Quarterly , April 2008. 65 For an exce llent resource see http://plato.stanford.edu/entries/prisoner -dilemma/ . 66 “Stern Stewart EVA Roundtable,” Journal of Applied Corporate Finance , Vol. 7, No. 2, Summer 1994, 46 - 70. 67 Pankaj Ghemawat, Strategy and the Business Landscape -3rd Ed. (Upper Saddl e River, NJ: Prentice -Hall , 2009), 69 -72. 68 Robert Axelrod, The Evolution of Cooperation (New York: Basic Books, 1985). 69 Rappaport and Mauboussin, 57. 70 Avinash K. Dixit and Barry J. Nalebuff, The Art of Strategy: A Game Theorist’s Guide to Success in Business and Life (New York: W. W. Norton & Co., 2008 ); Joshua S. Gans and Michael D. Ryall, “Value Capture Theory: A Strategic Management Review,” Rotman Sc hool of Management Working Paper , February 2016. 71 Pankaj Ghemawat, Strategy and the Business Landscape -3rd Ed. (Upper Saddl e River, NJ: Prentice -Hall , 2009), 74 -77. 72 John Robert Stinespring and Brian T. Kench, “Explaining the Interbank Loan Crisis of 2 008: A Teaching Note,” February 1, 2009. See: http://ssrn.com/abstract=1305392 . For a fascinating connection between November 1, 2016 Measuring the Moat 64 the Prisoner’s Dilemma and the financial crisis of 2007 -2008, see: John Cassidy, “Rational Irrationality,” The New Yorker , October 5, 2009. 73 Interbrand, “Best Global Brands 2012: The definitive guide to the 100 Best G lobal Brands.” 74 Clayton M. Christensen, Taddy Hall, Karen Dillon, and David S. Duncan, Competing Against Luck: The Story of Innovation and Customer Choice (New York: HarperBusiness, 2016); C layton M. Christensen, Taddy Hall, Karen Dillon, and David S. D uncan, “Know Your Customers’ ‘Jobs to Be Done’,” Harvard Business Review , September 2016; and Clayton M. Christensen, Scott D. Anthony, Gerald Berstell, and Denise Nitterhouse, “Finding the Right Job For Your Product,” MIT Sloan Management Review , Spring 2007, 2 -11. 75 Jerker Denrell , Christina Fang , Chengwei Liu , "Perspective — Chance Explanations in the Management Sciences," Organizational Science , Vol. 26, No. 3, May -June 2015, 923 -940. 76 Michael E. Raynor, The Strategy Paradox: Why Commitment to Success Leads to Failure (and What to Do About It) (New York: Currency Doubleday, 2007). 77 Jim Collins, Good to Great: Why Some Companies Make the Leap . . . and Others Don’t (New York: Harper Business, 2001). 78 Jerker Denrell, “Vicarious Learning, Undersampling of Failure, and the Myths of Management,” Organization Science , Vol. 14, N o. 3 , May –June 2003 , 227 –243. 79 Jerker Denrell, Christina Fang, and Zhanyun Zhao, “Inferring Superior Capabilities from Sustained Superior Performance: A Bayesian Analysis,” Strategic Management Journal , Vol. 34, No. 2, February 2013, 182 - 196. 80 Michael E. Raynor and Mumtaz Ahmed, The Three Rules: How Exceptional Companies Think (New York: Penguin Books, 2013), 42 -45. 81 Michael E. Raynor and Mumtaz Ahmed, “Three Rules for Making a Company Truly Great,” Harvard Business Review , April 2013, 108 -117. In categorizing the companies , the probability the results were due to luck had to be lower than 10 percent . T he qualifying length of time depend ed on the company’s life span. F or example, to be a Miracle Worker, a company with 10 years of data was required to be in the top 10 percent for every year, but a company with 45 years of data was required to be in the top 10 percent for only 16 years . 82 Michael E. Raynor, Mumtaz Ahmed, and Andrew D. Henderson, “A Ran dom Search for Excellence: Why ‘Great Company’ Research Delivers Fables and Not Facts ,” Deloitte Research , December 2009; and Andrew D. Henderson, Michael E. Raynor, and Mumtaz Ahmed, “How Long Must a Firm Be Great to Rule Out Luck?

Benchmarking Sustained Superior Performance Without Being Fooled By R andomness,” Academy of Management Proceedings , August 2009, 1–6. 83 Rappaport and Mauboussin, 7 -8. 84 George Eliades, Michael Retterath, Norbert Hueltenschmidt, and Karan Singh, “Heathcare 2020,” Bain & Company Research , 2012 . November 1, 2016 Measurin g the Moat 65 References Books Axelrod, Robert, The Evolution of Cooperation (New York: Basic Books, 1985). ——— , The Complexity of Cooperation: Agent -Based Models of Competition and Collaboration (Princeton , NJ : Princeton University Press, 1997). Bain, Joe S., Barriers to New Competition (Cambridge , MA : Harvard University Press, 1956). Baldwin, Carliss Y., and Kim B. Clark, Design Rules: The Power of Modularity (Cambridge, MA: The MIT Press, 2000). Barney, Jay B., Gaining and Sustaining Competitive Advantage (Upper Saddle River, NJ: Prentice -Hall, Inc., 2002). Barrett, William P., The Red Queen among Organizations: How Competition Evolves (Princeton, NJ: Princeton University Press, 2008). Besanko, David, David Dranove, Mark Shanley, and Scott Schaefer, Economics of Strategy -6th Ed. (Hoboken, NJ: John Wiley & So ns, 201 3). Bower, Joseph L. , and Clark G. Gilbert, From Resource Allocation to Strategy (Oxford: Oxford University Press, 2005). Brandenburger, Adam M., and Barry J. Nalebuff, Co -opetition : 1. A Revolutionary Mindset That Combines Competition and Cooperation. 2. The Game Theory Strategy That’s Changing the Game of Business (New York: Doubleday, 1996). Brilliant, Heather, and Elizabeth Collins, Why Moats Matter: The Morningstar Approach to Stock Investing (Hoboken, NJ: John Wiley & Sons, 2014). Bryan, Lowell, Jane Fraser, Jeremy Oppenheim, and Wilhelm Rall, Race for the World (Boston , MA : Harvard Business School Press, 1999). Burgelman, Robert A., Strategy I s Destiny: How Strategy -Making Shapes a Company’s Future (New York: Free Press, 2002) . Carroll , Glenn R., and Michael T. Hannan, The Demography of Corporations and Industries (Princeton, NJ: Princeton University Press, 2000). Christensen, Clayton M., Innovator’s Dilemma: When New Tech nologies Cause Great Firms to Fail (Boston , MA : Harvard Business School Press, 1997). Christensen, Clayton M. , and Michael E. Raynor, The Innovator’s Solution: Creating and Sustaining Successful Growth (Boston , MA : Harvard Business School Publishing, 2003). November 1, 2016 Measuring the Moat 66 Christensen, Clayton M., Michael E. Raynor, and Rory McDonald, “What Is Disruptive Innovation?” Harvard Business Review , December 20 15. Christensen, Clayton M., Scott D. Anthony, and Erik A. Roth, Seeing What’s Next: Using the Theories of Innovati on to Predict Industry Change (Boston , MA : Harvard Business School Publishing, 2004). Collins, Jim, Good to Great (New York: HarperCollins, 2001). D’ Aveni, Richard A., Beat the Commodity Trap: How to Maximize Your Competitive Position and Increase Your Pricing Power (Boston, MA: Harvard Business Press, 2010). Dixit, Avinash K., and Barry J. Nalebuff, The Art of Strategy: A Game Theorist’s Guide to Success in Business and Life (New York: W. W. Norton & Co., 2008 ). Evans, Philip, and Thomas S. Wurster, Blown to Bits: How the New Economics of Information Transforms Strategy (Boston , MA : Harvard Business School Press, 1999). Foster, Richard, and Sarah Kaplan, Creative Destruction: Why Companies That Are Built to Last Underperform the Market – and How to Su ccessfully Transform Them (New York: Doubleday, 2001). Frei, Frances, and Anne Morriss, Uncommon Service: How to Win by Putting Customers at the Core of Your Business (Boston, MA: Harvard Business Review Press, 2012). Fritz, Thomas, The Competitive Advantage Period and the Industry Advantage Period: Assessing the Sustainability and Determinants of Superior Economic Performance (Wiesbaden , Germany : Gabler, 2008). Fruhan, William E., Jr., Financial Strategy : Studies in the Creation, Transfer, and Dest ruction of Shareholder Value (Homewood, Il. : Richard D. Irwin, Inc., 1979). Ghemawat, Pankaj, Commitment : The Dynamic of Strategy (New York: The Free Press, 1991). ——— , Games Businesses Play : Cases and Models (Cambridge , MA : Massachusetts Institute of Technology, 1997). ——— , Strategy and the Business Landscape -3rd Ed. (Upper Saddle River, NJ: Prentice -Hall, Inc., 200 9). Grant, Robert M., Contemporary Strategy Analysis -7th Ed. (Chichester, UK: John Wiley & Sons, 2010). Greenwald, Bruce C. N., Judd Kahn, Paul D. Sonkin, and Michael van Biema, Value Investing: From Graham to Buffett and Beyond (New York: John Wiley & Sons, 2001). Greenwald, Bruce, and Judd Kahn, Competition Demystified: A Radically Simplified Approach to Business Strategy (New York: Penguin Group, 2005). Grove, Andrew S., Only the Paranoid Survive (New York: Doubleday, 1999). Karier, Thomas, Beyond Competition (Armonk, NY: M.E. Sharpe, 1994). November 1, 2016 Measuring the Moat 67 Kiechel, Walter, The Lords of Strategy: The Secret Intellectu al History of the New Corporate World (Boston , MA : Harvard Business Press , 2010). King, Andrew A., and Baljir Baatartogtokh, “How Useful Is the Theory of Disruptive Innovation,” MIT Sloan Management Review , Vol. 57, No. 1, Fall 2015 . Klepper, Steven, Experimental Capitalism: The Nanoeconomics of American High -Tech Industries (Princeton, NJ: Princeton University Press, 2016). Lynch, Peter, with John Rothchild, One Up On Wall Street: How To Use What You Already Know To Make Money in the Market (New York: Penguin Books USA, 1989). Magretta, Joan, Understanding Michael Porter: The Essential Guide to Competition and Strategy (Boston, MA: Harvard Business Review Press, 2012). Mauboussin, Michael J. , Think Twice: Harnessing the Power of Counterintuition (Boston , MA : Harvard Business Press, 2009). ——— , The Success Equation: Untangling Skill and Luck in Business, Sports, and Investing (Boston , MA : Harvard Business Review Press, 2012). Mazzucato, Mariana, Firm Size, Innovation and Market S tructure: The Evolution of Industry Concentration and Instability (Northampton, MA: Edward Elgar Publishing, 2000). ——— , Strategy for Business: A Reader (London: Sage Publications, 2002) . McGrath, Rita Gunther, The End of Competitive Advantage: How to Keep Your Strategy Moving as Fast as Your Business (Boston, MA: Harvard Business Review Press, 2013). McTaggart, James, Peter Kontes, and Michael Mankins, The Value Imperative: Managing for Superior Shareholder Returns (New York: The Free Press, 1994). Mueller, Dennis C., Profits in the Long Run (Cambridge: Cambridge University Press, 1986). Oster, Sharon M., Modern Competitive Analysis (Oxford: Oxford University Press, 1999). Porter, Michael E., Competitive Advantage: Creating and Sustaining Superio r Performance (New York: Simon & Schuster, 1985). ——— , Competitive Strategy: Techniques for Analyzing Industries and Competitors (New York: The Free Press, 1980). Rappaport, Alfred, Creating Shareholder Value: A Guide for Managers and Investors – Revised and Updated (New York: Free Press, 1998). Rappaport, Alfred, and Michael J. Mauboussin, Expectations Investing: Reading Stock Prices for Better Returns (Boston , MA : Harvard Business School Press, 2001). November 1, 2016 Measuring the Moat 68 Raynor, Michael E., The Strategy Paradox: Why Commitment to Success Leads to Failure (and What to Do About It) (New York: Currency Doubleday, 2007). Raynor, Michael E., and Mumtaz Ahmed, The Three Rules: How Exceptional Companies Think (New York: Penguin Books, 2013). Rogers, Everett M., The Diffusi on of Innovation s (New York: Free Press, 1995). Rumelt, Richard P., Good Strategy Bad Strategy: The Difference and Why It Matters (New York: Crown Business, 2011). Shapiro, Carl, and Hal R. Varian, Information Rules: A Strategic Guide to the Network Economy (Boston , MA : Harvard Business School Press, 1999). Slywotzky, Adrian J., Value Migration: How to Think Several Moves Ahead of the Competition (Boston, MA: Harvard Business School Press, 1996). Slywotzky, Adrian J., David J. Morrison, and Bob Ande lman, The Profit Zone: How Strategic Business Design Will Lead You to Tomorrow’s Profits (New York: Three Rivers Press, 2002). Utterback, James M., Mastering the Dynamics of Innovation (Boston , MA : Harvard Business School Press, 1996). Williams, Jeffrey R., Renewable Advantage (New York: The Free Press, 2000). November 1, 2016 Measuring the Moat 69 Articles and Papers Afuah, Allan, “Are Network Effects Really All About Size? The Role of Structure and Conduct,” Strategic Management Journal , Vol. 34, No. 3, March 2013, 257 -273. Agarwal, Rajshree, and Serguey Braguinsky, “Industry Evolution and Entrepreneurship: Steven Klepper’s Contributions to Industrial Organization, Strategy, Technological Change, and Entrepreneurship,” Strategic Entrepreneurship Journal , Vol. 9, No. 4, Decemb er 2015, 380 -397 . Asker, John, Joan Farre -Mensa, and Alexander Ljungqvist, “Corporate Investment and Stock Market Listing: A Puzzle?” European Corporate Governance Institute (ECGI) - Finance Research Paper Series , April 22, 2013. Bouncken, Ricarda B., Jo hanna Gast, Sascha Kraus, and Marcel Bogers, “Coopetition: a Systematic Review, Synthesis, and Future Research Directions,” Review of Managerial Science , Vol. 9, No. 3, July 2015, 577 - 601. Brandenburger, Adam M., and Harborne W. Stuart, Jr., “Value -Based Business Strategy,” Journal of Economics & Management Strategy , Vol. 5, No. 1, Spring 1996, 5-24. Cain, Daylian M., Don A. Moore, and Uriel Haran, “Making Sense of Overconfidence in Market Entry,” Strategic Management Journal , Vol. 36, No. 1, January 2015, 1 -18. Camerer, Colin, and Dan Lovallo, “Overconfidence and Excess Entry: An Experimental Approach,” American Economic Review , Vol. 89, No. 1, March 1999, 306 -318. Caves, Richard E., and Pankaj Ghemawat, “Identifying Mobility Barriers,” Strategic Management Journal , Vol. 13, No. 1, 1992, 1 -12. Christensen, Clayton M., “The Ongoing Process of Building a Theory of Disruption,” Journal of Product Innovation Management , Vol. 23, No. 1, January 2006, 39 -55. Christensen, Clayton M., Matt Verlinden, and George Westerman, “Disruption, Disintegration, and the Dissipation of Differentiability,” Industrial and Corporate Change , Vol. 11, No. 5, November 2002, 955 -993. Christensen, Clayton M., Taddy Hall, Karen Dillon, and David S. Duncan, “Know Your Customers’ ‘Jobs to Be Done’,” Harvard Business Review , September 2016. Cookson, J. Anthony, “Anticipated Entry and Entry Deterrence: Evidence from the American Casino Industry,” Working Paper , December 2015. Denrell, Jerker, “Vicarious Learning, Undersampling of Failure, and the Myths of Management.” Organization Science , Vol. 14, No. 3, May -June 2003, 227 –243. ——— , “Should We Be Impressed With High Performance?” Journal of Management Inquiry , Vol. 14, No. 3, September 2005, 292 -298. Denrell, Jerker, Christina Fang, and Zhanyun Zhao, “Inferring Superior Capabilities from Sustained Superior Performance: A Bayesian Analysis,” Strategic Management Journal , Vol. 34, No. 2, February 2013, 182 -196. November 1, 2016 Measuring the Moat 70 Denrell , Jerker, Christina Fang , Chengwei Liu , "Perspect ive — Chance Explanations in the Management Sciences," Organizational Science , Vol. 26, No. 3, May -June 2015, 923 -940. Disney, Richard, Jonathan Haskel, and Ylva Heden, "Entry, Exit and Establishment Survival in UK Manufacturing," Journal of Industrial Economics , Vol. 51, No. 1, March 2003, 91 -112. Dorn , Stefanie, Bastian Schweiger, and Sascha Albers, “Levels, Phases and Themes of Coopetition: A Systematic Literature Review and Research Agenda,” European Management Journal , Vol. 34, No. 5, October 2016, 484 -500 . Dunne, Timothy, Mark J. Roberts, and Larry Samuelson, “Patterns of firm entry and exit in U.S.

manufacturing industries,” RAND Journal of Economics , Vol. 19, No. 4, Winter 1988, 495 -515. Dunne, Timothy, Shawn D. Klimek, Mark J. Roberts, and Dan iel Yi Xu, “Entry, Exit, and the Determinants of Market Structure,” The RAND Journal of Economics , Vol. 44, No. 3, Fall 2013, 462 -487. Elfenbein, Daniel W., Anne Marie Knott, and Rachel Croson, “Equity Stakes and Exit: An Experimental Approach to Decomposing Exit Delay,” Strategic Management Journal , Forthcoming. Gadiesh, Orit and James L. Gilbert, “Profit Pools: A Fresh Look at Strateg y,” Harvard Business Review , May - June, 1998 , 139 -147 . ——— , “How to Map Your Industry’s Profit Pool,” Harvard Business Review , May -June, 1998, 149 -162. Gage, Deborah, “The Venture Capital Secret: 3 Out of 4 Start -Ups Fail,” Wall Street Journal , September 20, 2012. Gans, Joshua S., and Michael D. Ryall, “Value Capture Theory: A Strategic Management Review,” Rotman School of Management Working Paper , February 2016. Goolsbee, Austan, and Chad Syverson, “How Do Incumbents Respond to the Threat of Entry? Evidence from the Major Airlines,” Quarterly Journal of Economics , Vol. 123, No. 4, November 2008, 1611 -1633. Greenwald, Bruce, and Judd Kahn, “All Strategy Is Local,” Harvard Business Review , September 2005 , 94 - 104. Guan, Yuyan, M. H. Franco Wong, and Yue Zhang, “Analyst Following Along the Supply Chain,” Review of Accounting Studies , Vol. 20, No. 1, March 2015, 210 -241. Gustafsson, Robin, Mikko Jääskelainen, Markku Maula, and Juha Uotila, “Emergence of Industries: A Review and Future Directions,” International Journal of Management Reviews , Vol. 18, No. 1, January 2016, 28 -50 . Headd, Brian, “Redefining Business Success: Distinguishing Between Closure and Failure,” Small Business Economics , Vol. 21, No. 1, August 2003, 51 -61. Henderson, Andrew D., Michael E. Raynor, and Mumtaz Ahmed, “How Long Must a Firm Be Great to Rule Out Luck? Benchmarking Sustained Superior Performa nce Without Being Fooled By Randomness,” Ac ademy of Management Proceedings, August 2009 , 1–6. November 1, 2016 Measuring the Moat 71 Hinterhuber, Andreas, and Stephan Liozu, “Is It Time to Rethink Your Pricing Strategy?” MIT Sloan Management Review , Summer 2012. Hou, Kewei, and David T. Robinson, “Industry Concentration and Average Stock Returns,” Journal of Finance , Vol. 61, No. 4, August 2006, 1927 -1956. Huang, Kuo -Feng, Romano Dyerson, Lei -Yu Wu, and G. Harindranath, “From Temporary Competitive Advantage to Sustainable Competitive Advantage,” British Journal of Management , Vol. 26, No. 4, October 2015, 617 -636. Kahneman, Daniel, and Amos Tversky, “On the Psychology of Prediction,” Psychological Review, Vol. 80, No. 4, July 1973, 237 -251. Karniouchina, Ekaterina V., Stephen J. Carson, Jeremy C. Short, and David J. Ketchen Jr., “Extending the Firm Vs. Industry Debate: Does Industry Life Cycle Stage Matter? ” Strategic Management Journal , Vol. 34, No. 8, August 2013, 1010 -1018. Klepper, Steven, “Entry, Exit, Growth, and Innovation over the Product Life Cycle,” American Economic Review , Vol. 86, No. 3, June 1996, 562 -583. ——— , “Industry Life Cycles,” Industrial and Corporate Change , Vol. 6, No. 1, January 1997, 145 -181. Klepper, Steven, and Elizabeth Graddy, “The evolution of new industries and the determinants of market structure,” RAND Journal of Economics , Vol. 21, No. 1, Spring 1990, 27 -44. Kling , Jim, “From Hypertension to Angina to Viagra,” Modern Drug Discovery , Vol. 1, No. 2, November - December 1998. Madsen, Tammy L., and Michael J. Leiblein, “What Factors Affect the Persistence of an Innovation Advantage? Journal of Management Studies, Vol. 5 2, No. 8, December 2015, 1097 -1127. Matthews, Bryant, David A. Holland, Michael J. Mauboussin, and Dan Callahan, “Global Industry Profit Pools,” Credit Suisse HOLT Market Commentary , July 2016. Matthews, Bryant, and David A. Holland, “HOLT Industry Profitability Handbook,” Credit Suisse HOLT Market Commentary , October 4, 2016. Mauboussin, Michael J., and Dan Callahan, “Total Addressable Market: Methods to Estimate a Company’s Sales,” Credit Suis se Global Financial Strategies , September 1, 2015. Mauboussin, Michael J., Dan Callahan, and Darius Majd, “The Base Rate Book: Integrating the Past to Better Anticipate the Future,” Credit Suisse Global Financial Strategies , September 26, 2016. McClure, Samuel M., Jian Li, Damon Tomlin, Kim S. Cypert, Latané M. Montague, and P. Read Montague, “Neural Correlates of Behavioral Preference for Culturally Familiar Drinks,” Neuron , Vol. 44, No. 2, October 14, 2004, 379 -387. McGahan, Anita M., and Michael E. Porter, “How Much Does Industry Matter, Really?” Strategic Management Journal , Vol. 18, Summer Special Issue 1997, 15 -30. November 1, 2016 Measuring the Moat 72 ——— , “The emergence and sustainability of abnormal profits,” Strategic Organization , Vol. 1, No. 1, February 2003, 79 -108. McGahan, Anita M., and Brian S. Silverman, “How Does Innovative Activity Change as Industries Mature?” Working Paper – Boston University and Harvard Business School , February 8, 2000. Miller, Merton H., and Franco Modigliani, “Dividend Policy, Growth, and the Valuation of Shares,” The Journal of Business , Vol. 34, October 1961, 411 -433. Olsen, Brett C., “Firms and the Competitive Advantage Period,” Journal of Investing , Vol. 22, No. 4, Winter 2013, 41 -50. Porter, Michael E., “What is Strategy?” Harvard Business Review , November -December 1996, 61 -78. ——— , “Strategy and the Internet,” Harvard Business Review , March 2001, 63 -78. ——— , “The Five Competitive Forces T hat Shape Strategy,” Harvard Business Review , January 2008 , 78 - 93 . Raynor, Michael E., Mumtaz Ahmed, and Andrew D. Henderson, “A Random Search for Excellence: Why ‘Great Company ’ Researc h Delivers Fables and Not Facts,” Deloitte Research , December 2009. Raynor, Michael E., and Mumtaz Ahmed, “Three Rules for Making a Company Truly Great ,” Harvard Business Review , April 2013, 108 -117. Rumelt, Richard P., “How Much Does Industry Matter?” Strategic Management Journal , Vol. 12, No. 3, March 1991, 167 -185. Schmalensee, Richard, “Do Markets Differ Much?” American Economic Review , Vol. 75, No. 3, June 1983, 341 -351. Schröder, Da vid, and Andrew Yim, “Industry Effects in Firm and Segment Profitability Forecasting: Corporate Diversification, Industry Classificat ion, and Estimate Reliability,” Working Paper , March 2016 . Smiley, Robert, “Empirical Evidence on Strategic Entry Deterrence,” International Journal of Industrial Organization , Vol. 6, No. 2, June 1988, 167 -180. Vázquez Sampere, Juan Pablo, Martin J. Bienenstock, and Ezra W. Zuckerman, “Debating Disruptive Innovation,” MIT Sloan Management Review , Spring 2016. Waring, Geoffrey F., “Industry Differences in the Persistence of Firm -Specific Returns,” American Economic Review , December 1996, 1253 -1265. Wiggins, Robert R. and Timothy W. Ruefli, “Schumpeter’s Ghost: Is Hypercompetition Making the Best of Times Shorter?” Strategic Management Journal , Vol. 26, No. 10, October 2005, 887 –911. ——— , “Sustained Competitive Advantage: Temporal Dynamics and the Incidence and Persistence of Superior Economic Performance,” Organization Science , Vol. 13, No. 1, January -February 2002, 82 -105. Williams, Jeffrey R., “How Sustainable Is Your Competitive Adva ntage?” California Management Review, Vol. 34, No. 3, 199 2, 29 -51 . Important information This document was produced by and the opinions expressed are those of Credit Suisse as of the date of writing and are subject to change. It has been prepared solely for information purposes and for the use of the recipient. It does not constitute an offer or an invitation by or on b ehalf of Credit Suisse to any person to buy or sell any security. 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