From the Old to the New Economy
In post #29114, I explored Moore's model of the gorilla game by examining his multiple models, indicating that he was following the recursive build-test-observe-with-a-feedback-loop that is characteristic of applied science. In post, # 29340, I examined how Moore had tied the elusive concept of "power" to "competitive advantage," and how Moore had stressed the importance of catching the technology wave in his hierarchical competitive advantage model. In the present post, I examine the leap from the old to the new economy, relying on the work of CSFB's Michael Mauboussin. Beginning with a firm grasp of finance, Mauboussin builds mental models for investing in this new millennium. The present post is foundational and educational, foundational because it introduces a model for how to invest in new economy that is grounded in models of what it is and how it works, educational because it introduces a vocabulary of concepts that are useful in analyzing investments.
Laying the Groundwork.
In "Why Strategy Matters," Mauboussin and Hiler (M&H; CFSB, 1998) explored specifically how competitive advantage, strategy, and the evaluation of capital markets were intertwined. Strategy is generic, a plan of attack; competitive advantage is specific, the execution of tactics consistent with the strategy. Strategic analysis examines an industry's structural attractiveness and a company's position in it relative to its competitors. A strategy seeks to change the rules that it discovers in its favor. Porter's Five Forces Model serves as a useful analytical tool. A successful strategy creates a unique and valuable position by organizing an integrated set of business activities aimed toward achieving a strategic goal of increasing value. Strategy, including formulation and execution, is a stepping-stone to capturing competitive advantage, allowing a company to earn returns on capital in excess of the cost of capital.
Competitive advantage is a quantitative issue: it exists when a company's sales are greater than its total costs. One measure of advantaged returns is the return on invested capital minus the weighted average cost of capital (ROIC - WACC). (The authors acknowledge that Net Present Value would be the ideal method.) Using ROIC - WACC spreads, M&H examined empirical data for these spreads across selected countries, major US industries, the US computer hardware industry, and Hewlett-Packard's business units. A striking feature of all four charts was their self-similarity across all levels, a fractal pattern. In each chart, there were value-creating and value-destroying entities in both attractive and unattractive countries, industries, segments, and units. The profound implication is that value creation is not contingent on being in an attractive country, industry, segment, or company. Thus, even in less attractive situations, a company can always improve returns if it has the best strategy.
While holding growth constant, economic theory suggested that a firm that earns above-cost-of-capital returns would be more highly valued in the stock market. Empirical data collected across multiple sectors supported the theory. For example, when excess returns were regressed against market value, using data from the1997 S&P 500, the correlation yielded a multiple R-squared of .79. The higher the excess returns, the higher the valuation. These data linked stock market performance to strategy and competitive advantage: strategy is a process that allows a company to achieve a competitive advantage; competitive advantage is the ability to generate returns on capital in excess of capital; and the stock market efficiently reflects these excess returns.
Implications were drawn for both management and investors. Managers should manage against a criterion of economic value creation rather than growth, which is a second order consideration. By giving priority to value creation over growth, managers can avoid errors in capital allocation. In valuing stocks, investors must consider both excess returns and the duration of excess returns. The CSFB framework for analyzing sustainable competitive advantage is called the competitive advantage period (CAP), which can be pinpointed by considering a company's current returns, the rate of industry change, and barriers to entry. CONSISTENTLY GENERATING EXCESS RETURNS IS MANAGEMENT'S GREATEST CHALLENGE.
Because the data show that excess returns can be generated even in the worst industry, strategy matters. It is key: WINNER SEPARATE FROM LOSER BY HOW THEY ORGNAIZE THEIR ACTIVITIES TO GAIN COMPETITIVE ADVANTAGE.
Strategies for the New Economy
Mauboussin and Hiler's (1998) paper "On the Shoulders of Giants" appeared in the CSFB series on Frontiers of Strategy. In this exceptional paper, the authors' goal was to describe mental models for the new millennium. Understanding their contrast between the old and new economies is basic to the gorilla game because technology in the new economy is the domain of our investing strategy. Thus, we want out investing strategy to match the features of the new economy. The concepts used in this analysis can give us a common language for discussion.
The role of technology in business shifted over the course of the last century. The old economy generates an image of a factory: physical inputs went in and were transformed by technology that used automated machinery and task-trained workers to add value to a finished product. Contrasting the old and new technology, the old technology was mechanistic, deterministic, metallic, stand alone, and fixed; whereas, the new is virtual, non-deterministic, software driven, massively interactive, and continuously refigured, respectively. Some present day companies are relatively more old economy; others, more new economy.
Mauboussin and Hiler described three macro features of the new economy:
(1) The economics of networks. Driven by positive feedback, the larger a network, the more valuable it becomes. In the old economy, supply-side economics had positive feedback that increased economy of scale, but that ran into physical limits; whereas, network economics are driven by demand-side economics that create operating leverage that scales with the growing market.
(2) The dramatic reduction in transaction costs. Cheaper computing and the power of networks massively accelerated the rate of decline in transaction costs.
(3) The central role of knowledge. Because physical capital and its manipulation, rather than knowledge and its manipulation, characterized the old economy, outdated mental models from economics and accounting do not fit the new economy.
The more a business displays the new economy features of networks, lower transaction costs, and knowledge, the less an old strategy can be made to fit the advancing tide of the new economy. So, what's new about the new economy?
The economist Paul Romer asked a fundamental question: given that physical resources have remained the same, why are we so much wealthier now than one hundred years ago? He also answered it: because the advancement of "software," which is a set of instructions, formulas, or processes that are followed in order to create value, permits us to rearrange these resources in more valuable ways. (Note that the quotes embracing "software" imply that this is an abstraction; it is knowledge used to order processes, formulas or instructions; although software as written code is a common concrete embodiment of knowledge, it is not the only embodiment.)
The move from "atoms" to "bits," from physical capital to knowledge capital, benefited from three characteristics of software:
1. Software and sharing. Unlike a physical good, more than one person at a time can use software.
2. Low incremental costs. Although software has high upfront developmental costs, the cost of replicating new copies approaches zero.
3. Increasing returns. The more software that is created, the more building blocks are available to meet the challenge of new opportunities. The larger the body of software, the faster is the growth in innovation.
When viewed as building blocks, the power of additional software is a function of the number of possible combinations that might generate a new solution. If you had four building blocks, then 4 x 3 x 2 x 1 = 24 possible solutions; increase the building blocks by 50% by developing 2 new software-building-blocks and the combinations increase from 24 to 720-thirty times greater. Knowledge can provide an order of magnitude gain in power.
Old and New Strategy
Two themes have dominated traditional thinking about economics and strategy. One theme is the metaphor of the world as a closed system of equilibrium; the other is that physical capital is central to wealth. When the world is considered to be a closed system that maintains its equilibrium, prices are seen as increasing with decreasing supply and increasing demand, and shocks unbalancing the system are seen as temporary. Our accounting systems were developed to handle tangible assets. This means that we have no way to account adequately for intellectual capital, making our investment decisions less reflective of what is going on in a knowledge economy.
Closed Frameworks and Linear Value Chains
Old strategic frameworks employ mechanistic cause-and-effect thinking because they assumed that linearity characterized a closed system of equilibrium. New strategic frameworks select organic metaphors from biology rather than deterministic metaphors from physics. Borrowing ideas from complexity theory, new economy businesses no longer believe that they exist in a world of stable equilibrium but instead face a dynamic, ever-changing competitive landscape, operating on the edge between order and chaos, an edge of rapid change, unpredictability, and an absence of determinism.
Mauboussin and Hiler critiqued the concept of the value chain based on Porter's model of Five-Forces (FFM) and his linear value chain of corporate activities. The FFM was used to illustrate a closed system. At its core is the rivalry among competitors that tends toward a stable equilibrium. At its periphery, the bargaining power or suppliers and buyers and the threats of new entrants or of substitutes disrupt the system until it reacts and rebalances. This model still describes many parts of the old economy.
Porter's value chain analysis was chosen to illustrate a linear framework. The strategy of analyzing the primary activities of inbound logistics, operations, outbound logistics, marketing & sales, and service follows the linear flow of an imagined physical object passing down a line with value added along the way. This model works less well with a virtual object of knowledge than a tangible unit of capital. The old models of strategy assumed market equilibrium, diminishing returns, and continuous improvement.
The New: Open Networks and Economic Webs
In contrast, the bionomic model is based on assumptions of inherent market instability, multiple (non-deterministic) potential outcomes, a predominance of inferior products, and winner-take-most of the profits. This new world of strategy was described by looking at its four elements: mechanisms, results, characteristics, and resulting strategies.
Seven main mechanisms in new economy companies were identified:
1. High upfront costs. In comparison to physical products, the cost of developing knowledge is greater but incremental units are inexpensive. The key to scalability is to increase sales more rapidly than expenses. With high upfront costs and the need to scale rapidly, size matters. Thus, companies that can afford to spend the most on R&D and marketing gain the advantage.
2. First-mover advantage. First-movers can gain an edge when they capture "mind-share," set de facto standards, establish brands, increase switching costs, and build valuable networks. However, success is not guaranteed.
3. Path dependence. Path dependence occurs when positive feedback loops create virtuous cycles that contribute to continuing success. However, these patterns are influenced by random or chance events that set initial conditions, and the process is also subject to other unexpected events that can alter it, and thus outcomes, making the prediction of success indeterminate.
4. Tipping points. A tipping point is the level of market share at which future market share gains become cheaper-and-cheaper to acquire. That is, positive feedback from first-mover competitive advantages creates market momentum that enhances the probability of success, but the company remains vulnerable to exogenous events until it passes a threshold, known as a tipping point, that serves as a point-of-no-return. Once the tipping point is reached gains in market share become free, that is, based on word of mouth by early adopters that influence the pragmatists, who assure mass market dominance. As Kevin Kelley points out, the significance threshold for tipping points is lower in the new economy, which means that investors must gather and interpret data about innovations, growth rates, and market share earlier than in the past because of the very rapid and accelerating rates of growth among the stocks that we seek.
5. Network effect. The value of the network is higher when the network is larger. Metcalf's law describes the value as increasing exponentially as the number of new members or nodes increases arithmetically.
6. Positive feedback. The strong get stronger and the weak get weaker because of positive and negative feedback loops.
7. Lock-in. Lock-in occurs when a customer becomes reluctant to switch to a competing product because of the complexity of using high technology, becoming more open to highly profitable upgrades than to competing products. Lock-in is obtained by brand-specific training, providing informational databases, and loyalty programs that generate switching costs.
Results. These seven mechanisms create desirable outcomes in the new knowledge economy that were not here-to-fore believed possible, given the assumptions of the old material economy-that competitive forces drive returns of capital down to opportunity cost, that monopolies are bad, and that the best product always wins. Standing the old wisdom on its head, the results generated by knowledge in the new economy include:
1. Increasing returns. The economist Brian Arthur describes increasing returns as "the tendency for that which is ahead to get further ahead, for that which loses advantage to lose further advantage." In the new economy this process can be idealized and described as a sequential process of steps involving positive feedback loops: (a) After incurring high upfront costs, a knowledge based product is created; (b) The product exhibits path dependence, gaining market share; (c) The market share accelerates after reaching the tipping point; (d) Now incremental revenues outpace declining costs; and (e) Expanding revenues with low marginal costs increase the excess return on capital.
2. Monopoly rents. Given the high upfront costs of creating "software" that incorporates knowledge, there must be a probability of generating monopoly returns for a period of time. Such monopoly returns are more important for knowledge-based products than for physical goods because of the former's higher upfront costs.
3. Dominance of an "inferior" product. In the new economy, the "best" technology does not always win. There are two reasons for such apparently anomalous outcomes. First, an inferior product can get locked-in. Second, the value of the web supporting a product may be more important in the purchase decision than the quality of the product considered in isolation. Quality becomes only one of many relevant criteria in making a decision.
Biological Characteristics. Because the role of technology has changed from mechanistic enabler to a flexible, organic facilitator in the new economy, strategy development requires thinking more like a biologist than a physicist.
1. Economic webs. Rather than considering a value chain as a set of activities within a company that produces value, an economic web develops from cooperative alliances of companies who offer complementary products or services built around a standard. Although a gorilla may dominate profits, the value of any node in the web is intimately linked to the value of the web overall. Thus, bigger is better.
2. Co-evolution. Just as species have learned to co-evolve, so have members of an economic web. If a company's product makes your product more valuable, that company can be called your "complementor." Consider Wintel as an example; the complementary roles of Intel and Microsoft are synergistic.
3. Punctuated evolution. Gould and Eldredge introduced "punk eek" into evolutionary theory. In punk eek, the idea is that all evolution is not gradual; rather, in certain periods, sudden change rapidly occurs. In the old economy change was gradual, but in the new, stark, sudden changes are introduced into by discontinuous innovations. The flat structure of knowledge-companies facilitates seeking opportunities-the next big thing--rather than solving problems in old strategies.
Signposts for evaluating strategies. Signposts identify what managers should do in the new economy and what investors should look for.
1. Heavily discount-or give away-new product. In spite of heavy upfront costs, securing a base of customers rapidly is a top priority because it generates first-mover advantage, lock-in, and network effects.
2. Link and leverage. After developing a base of users, leverage value by adding new features.
3. Understand the power of the economic web. The strongest webs are built around open architectures. The value of the web takes precedence over the merits of any single product or service. Any company's potential value is a function of the total value it adds to the web times its share of the web.
4. Think adaptation, not optimization. The sudden, rapid change of punk eek requires adaptation to what is occurring now, not optimization to what you and your customers believe you do best. Adaptation requires alertness to the possibility of displacement by discontinuous innovation and a willingness to let go of success to embrace the next technology wave.
5. Psychological warfare. FUD and vaporware become business tactics to freeze customers while a company tries to get back into the race. Thus, all management pronouncements cannot be taken at face value by investors.
Impact on Value Drivers.
Shifting from theory to practice, M&H considered how these new economic factors translated into stock price by examining the three drivers that determine value: cash flow, risk, and CAP.
1. Cash flow. Cash flow is defined as the difference between cash-in and cash-out in a company, specifically expressed as the difference between earnings and investment in the future growth of the company. When a company experiences increasing returns it benefits on multiple fronts: sales growth becomes exponential when a company reaches the elbow of the curve (crosses the chasm) in technology adoption, or when a network reaches critical mass; marginal unit costs are low and decline over time; the need for incremental investment become modest. Important for the investor is the principle that non-linear growth is often systematically undervalued in the market place, producing superior investment opportunities. INDENTIFY THE MARKET SEGMENT GORILLA AS EARLY AS POSSIBLE, AND SELL ALL OTHER COMPETITORS.
2. Risk. A locked-in base of customers reduces volatility. LOWER RISK TRANSLATES INTO HIGHER MULIPLES.
3. Sustainable competitive advantage. M&H defined the competitive advantage period (CAP) as the period of time a company can generate excess returns on investments. On the one hand, Schumpeter's gales of creative destruction may shorten CAPs through an increasing frequency of discontinuous innovations. On the other hand, businesses that generate increasing returns become stronger and stronger, generally at the expense of competitors but relatively in step with complementors. IDENTIFY THE DOMINANT COMPANY AS SOON AS POSSIBLE.
Implications for the Gorilla Game.
In both the CSFB Frontiers of Strategy and Frontiers of Finance series, a significant strength in Mauboussin's approach is his consistent linking of strategic models to financial models. It was their CAP model that was introduced into the GG. Grounding strategic models in financial models clarifies the bottom line of investing, specifying how management's choices in how to add value affect stock prices.
As I try to distill their argument to its essence, I will consider some implications of these mental models for the GG. Mauboussin and Hiler's argument that investment strategy must match a model of the new economy is sound. Their fundamental assumption was that a crucial historical change occurred when the role of technology changed from the manipulation of physical capital to the manipulation of knowledge capital. The Internet leveraged this change to a knowledge economy because it engendered a dramatic reduction in transaction costs and demonstrated the increasing economic value of large networks. Thus, these three macro-features-central role of knowledge, lowered transaction costs, and network effects-define the new economy. Focusing on what is new specifically, M&H identified Romer's catalyst for the creation of increased wealth: an inclusive definition of knowledge as "software," defined as a set of instructions, formulas, and processes that are followed to create value. Knowledge as "software" can be shared by multiple users, once created has low incremental costs, and can generate increasing returns because the larger the body of knowledge as "software," then the faster the growth in the building blocks of innovation.
In the preceding sections about the new economy, there appears to be nothing that Moore would not accept. In Fault Line, Moore's first chapter on the Age of the Internet overlaps with M&H's conception of the new economy. Moore appears to have developed his models in conjunction with his consulting business. He used his observations of business processes in action and case studies of Microsoft, Intel, Oracle, and Cisco to build and test his models. (Of course, there were also empirical data that documented the TALC.) Moore's (p. 100) list of 12 discontinuous innovations in Fault Line, were all drawn from the computer and software industry. Moore has not yet systematically introduced the Internet as a lever for lowering transaction costs or producing network effects as legitimate drivers of increasing value into his writings. Of course, one reason for this may be that these competitive advantages are first-mover advantages, not the gorilla game advantage of a proprietary open architecture.
So far, Moore's modeling has been at home in the domain of the microcosm of computers, software, and their extensions as derivatives of computers into LANs, WANs, and the Internet. That is, I believe that he has not yet systematically written about the telecosm or new Internet businesses as specific value drivers, but he accepts many of these ideas and argues for the absolute need to embrace the Internet as a significant business strategy. Certainly, Moore's turn toward P/V ratios revealed his growing experience with venture capitalism in the new economy; he appears to be using that framework as a source of ideas. Because Moore regards Mauboussin as a valuable intellectual resource, what has been written to date may reflect only Moore's present priorities.
M&H's model of the new economy stemmed from a reconsideration of two basic assumptions of classical economic theory: that physical capital is central to creating wealth and that the economy is an equilibrium system. They concluded that closed systems and linear value chains must give way to open networks and economic webs.
In Fault Line, Moore also criticized Porter's model as company-centric and weak in dealing with discontinuous innovation, and he acknowledged that the concept of economic webs is important without introducing more complexity into his model of the value chain. Moore's describes the value chain in his mental model an open, self-organizing system, which is a central feature of Mauboussin's complex adaptive systems.
M&H specified seven mechanisms that have increased significance in the new economy: high upfront costs, first-mover advantage, path dependence, tipping points, network effects, positive feedback, and lock-in. These concepts are also "buzz" words when the "new economy" is viewed as "the next big thing." Of course, Moore is attuned to these concepts. In fact, he uses first-mover advantage and recognizes high upfront costs, but has yet to adopt systematically the biological metaphors of complexity theory.
So far, Moore's tornado and fault line metaphors remain within the domain of physics. While Mauboussin's turn toward biological metaphors has become increasingly more systematic, meaning that he finds the biological metaphors to be heuristically fruitful. Mauboussin's introduction of biological and bionomic metaphors, such as, economic/ecological webs and its niches, evolutionary adaptation, co-evolution, and punctuated equilibrium, adds strength to his conceptual models. I believe that understanding the new economy and the stock market as complex adaptive systems is a useful conceptual strategy in building models that impact investment strategy. Most important to investors, inefficiency in the stock market occurs because investors who expect trends to be linear systematically undervalue nonlinear growth. WHEN YOU IDENTIFY GAPS IN MARKET PERCEPTION, OPPORTUNITY BECKONS.
Also, relying on Mauboussin, my next post in this series will examine the exponential power of network effects, arguing that a strong network effect offers a compelling competitive advantage that ranks along side a gorilla's proprietary open architecture in its power. The post that follows that one will attempt to resolve any tensions produced in the committed gorilla gamer by this preposterous claim (VBG) by reconciling both forms of compelling competitive advantage as progeny born in the nest of models derived from the technology adoption life cycle (TALC). Assuming that I have not worn out my readers and my welcome, I will then apply this expanded model to stocks like GMST and QCOM who, despite not being dot.coms, benefit from both forms of compelling competitive advantage.
I hope this helps.
Don Mosher |
