Mike, Judith, Aerokat, lend me your minds!
If I have succeeded in being generous with my ideas, I hope that you will return the favor.
Does the concept of "network effects" add value to our analyses of gorilla games by identifying the dynamic driver of an inflection point in product adoption in the TALC (Technology Adoption Life Cycle)? In post # 38497,
Message 15254640
I claimed that it does. Although the Curmudgeon thread summarized my project network report as, "Mosher likes WIND," which is indeed an irreverent, humorous, and on-target poke at my long-WINDEDNESS. I claim, nonetheless, that the argument, possibly obscured by my wordiness, deserves discussion by Gorilla Gamers. I bare the argument's bones, omitting all references to Wind River, because this argument is intended to be general in its application to the TALC. You can agree, disagree, amend, or refute the argument as unsound through counter-argument so long as you don't ignore it. I may well be wrong; I would enjoy learning from my errors so I can correct them.
Context: The Bigger the Better.
Metcalfe's law tries to quantify the nonlinear value of network effects. It approximates the magnitude of that increase in value by specifying: as the number of elements or nodes increases arithmetically, the value of the network expands exponentially. Given the Internet, rather than his telephone example, however, not only one-to-one communication, but also one-to-many, many-to-one, and many-to-many communication(s) occur among many sets of people and, even, devices. Necessarily, moving from one-to-one communication to many-to-many communications increases the number of potential interactions and their explosive effects. Thus, it must expand the exponent beyond the square. What we know for certain about network effects is the bigger the better: the more elements, the greater the value. Therefore, "exponential" growth is properly used only in the vernacular sense of "compounding explosive growth."
This idea of "compounding non-linear growth" is at the heart of what is meant by the expanding value created by network effects. Network effects exist when the value of a good increases because the number of people using that good increases. Michael Mauboussin argued that successful networks generate huge shareholder value once they reach critical mass and that a locked-in network effect produced a sustainable competitive advantage. He noted that the strongest network effects are driven by (a) interactivity, where there is a lot of contact among the members or nodes, although (b) compatibility, among transactions, communities, or devices also can produce strong effects.
Using a common biological analogy of the spread of flue for the spread of innovation, Mauboussin indicated that the flue spreads as combined function of the degree of interaction and the degree of contagiousness (susceptibility or adoption threshold). The breakout of an epidemic-runaway explosive growth requires reaching a critical mass of infected individuals, creating an inflection point where interaction explosively combines with contagious susceptibility.
The concept of critical mass, the point in cumulative adoption where network effects suddenly accelerate at an increasing rate, can be described as (a) an inflection point, or elbow, in an S-curve, (b) crossing the chasm, a transition from visionary early adopters to the pragmatic, early majority, or (c) a tipping point, where incremental market share comes at incrementally lower costs. Based on many studies of innovation diffusion, the empirical results suggest that the inflection point in an S-curve of cumulative adoption occurs when a cumulative level of 10 to 20% adoption is reached. Also, quoting the Gorilla Game, Mauboussin offers this rule of thumb describing hypergrowth as a proxy for defining the threshold for critical mass: "when year-to-year growth exceeds 100%, and when quarter-to-quarter growth is also rapidly accelerating." Growing popularity is cumulative, but also it inflects sharply upward when it achieves critical mass.
The rate of diffusion of interactive innovations is more rapid than the rate of non-interactive innovations, creating a steeper S-curve for the former. Nonetheless, a non-interactive innovation is judged valuable whenever a critical mass of people has adopted it because it is now perceived to be the standard solution, expected to become the "next big thing." Consumers know that high technology changes, creating discontinuous innovations. A new solution makes what was once valuable less valuable, even worthless when it achieves great popularity. What happened to vinyl records and electric typewriters? Also, expectations are powerful. If people anticipate that the standard is becoming "VHS," not "Beta Max," then they buy a VCR based on the VHS standard. A tipping point occurs, creating critical mass, and value expands explosively as more buyers jump on the bandwagon. A cycle of increasing returns insures that more VHS videotape of movies and the like are created for this growing audience at the expense of the less popular competitor, creating its diminishing returns. The sharp, sudden inflection in popularity (or even an expected inflection in popularity) settles the dispute over which proposed standard is the real standard. Compatibility between the standard and its applications, when combined with inflecting popularity, solves the chicken-and-egg problem. Moreover, the network effect of inflecting popularity creates market power that is soon revealed by achieving a dominant share of the market.
However, when a strong network effect derives from interaction, not only do early adopters influence later adopters but also later adopters influence earlier adopters because they continue to interact. The potential interactions are from each-to-every, not just from older-to-newer users. Thus, given interactivity, the benefit deriving from each adopter increases the value for all adopters. For instance, consider the Napster site for coordinating the downloading of MP3 music as an example of how both early and later adopters can make more musical selections available to all. Such demand-driven cumulative adoption among youth is truly mega-explosive. Combine youth's known sensitivity to price with their desire to wannabe with what's cool, and a critical mass of adopters ensured an epidemic of escalating popularity for the Napster solution.
Because of this significant difference in their rate of growth, interactive network effects are called direct, and non-interactive network effects are called indirect. Runaways, whether in epidemics or innovation diffusion, require interactions in which Influence meets Susceptibility.
Influence can meet susceptibility in many venues. But, sometimes it is useful to distinguish between physical networks and virtual networksas venues, because all innovation diffusion requires social communication but all social communication does not require physical networks.
Within the technology adoption life cycle, a network effect describes a dynamic of suddenly noticeable and rapid inflection in cumulative adoption when the diffusion reaches critical mass, generating explosive growth. Thus, network effects are the dynamic of hypergrowth. Other descriptions of the inflection point in this accelerating growth dynamic have included phrases like "when a total solution is created," "when a compelling price point is reached," "when the value chain organizes to support a single standard," "when the buzz declares X is the next big thing," "when the last barrier to product adoption is overcome." These can be summarized as, "when the accumulation of competitive advantages tips decidedly in favor of a solution that either is in the process of becoming or is expected to become the popular or standard choice." Network effects drive or power the inflection skyward. Influence, as competitive advantages plus marketing, has met Susceptibility at the adoption threshold of the pragmatic early majority, generating explosive growth, the nonlinear growth-surge of hypergrowth called "tornado."
Identifying Network Effects
Here is a generic method for identifying network effects. First, simplify the task by remembering that Everett Rogers, the Father of Innovation Research, defined "diffusion as the process by which an innovation is communicated through certain channels over time among members of a social system." Second, to examine potential network effects, focus on the two drivers of strong network effects, interactivity and compatibility. Find both the social networks that permit the process of interaction among susceptible individuals to occur and value chains where compatibility among linked elements create a total solution. Third, after identifying promising interactions in networks and compatibilities in value chains of products, imagine how influence specifically diffuses specific innovations that become more valuable as they become more popular until they reach critical mass or become a standard solution. Fourth, decide if network effects have achieved critical mass or when cumulative adoption is expected to achieve critical mass, inflecting rapidly and locking-in a strong, sustainable, and measurable competitive advantage.
Identifying network effects only requires rudimentary social psychology or folk psychology, just using common sense approaches that are used in business everyday. We only need to answer questions like: How do people influence each other to try something new? Who is particularly influential? What sorts of influence-interactions are useful? How and when does a bandwagon form? How do we target susceptible adopters? What are the barriers to adoption? How are they overcome? This is the social psychology of influence.
Core: The Added Value of the Concept of Network Effects.
Conceptual distinctions clarify what was obscured before the distinction was named. I argue that the term "network effects" names the "dynamics that power the process of adoption" within the Technology Adoption Life Cycle. The diffusion of innovations involves a social psychological process in which influence meets susceptibility, influence that is communicated through network-like social channels.
Being able to identify the inflection point in the S-Curve appeals to investors. Recognizing that some forms of "lock-in" create a sustainable competitive advantage, the key to a long CAP, is among the most significant insights that a long-term investor can achieve. However, the GG elevates the conceptual distinctions summarized as "Open Proprietary Architecture" as its penultimate criteria of a lock-in, with, perhaps, "proprietary control over the architecture has already created a demonstrated control over the value chain during a tornado" as its ultimate criteria of desirable lock-in. In the GG, a long CAP depends on HSC and BTE; whereas, a DI that adds significant value through differentiation ensures a tall GAP.
The key point is this: network effects amplify the value of competitive advantages. That is, instead of thinking of competitive advantages (CA) as being additive, think of network effects as exponentially multiplying their arithmetic number. The amplification of competitive advantages by network effects expands their value explosively. This sharp inflection upward compounds until the upper elbow of the S-Curve is reached.
Moreover, network effects are the dynamic drivers of the TALC. This implies that network effects, because they are the dynamic amplifiers of competitive advantage, directly drive four gorilla game effects that are embodied as the six criteria of a Gorilla: Strong Value Chain, The Tornado of Hypergrowth, High Switching Costs, and Barriers to Entry. Each arithmetic addition of competitive advantage in these four realms produces the exponential increases in value that reveal the presence and power of network effects.
Although network effects have a discontinuous affect when they reach critical mass, they are, of course, not a Discontinuous Innovation. Nor are network effects implicit in Proprietary Architecture. However, the concept of "Openness" is all about the sort of compatibility that creates indirect network effects.
As I understand it, the principal analytical question is whether network effects that reach critical mass or become locked-in, indeed do produce a strong and sustainable competitive advantage. If so, is that network-effect-driven competitive advantage sufficient, without a proprietary architecture being necessary; or, going further, are locked-in network effects as strong and enduring an advantage as the one created by a proprietary architecture? Given that no one currently can supply adequate empirical answers, investors must form their own individual judgments.
Of course, I believe it is this dynamic of network effects reaching critical mass that inflects product adoption in the now susceptible early majority of pragmatists that underlies the tornadic growth within all gorilla games. I contend that this dynamic inflection combines the indirect network effects of a value chain forming around a compatible total solution and the direct network effect of mass adoption by consumers.
Revenues may lag other indicators of hypergrowth, including design wins or product adoption (recall Mike's pointing to QCOM's CDMA subscriber numbers before the Ericcson deal). The stock market may respond to proxies for hypergrowth or to a convincing story before the criteria for sequential and year over year growth in revenues that define a Tornado have been reached. Making such a predictive inference is undoubtedly far less certain than clear evidence that the Tornado has begun; it is an early warning sign, a tornado watch, not a tornado warning announcing, "invest now because the Tornado is imminently upon us."
There is no need to change the gorilla game; we all value its contributions. I am just trying on an idea about "network effects" for size to see if it fits. All we need on the G&K thread is the freedom to think and speak about alternatives using the framework that the GG provides as a starting point. A free market place of ideas lets the best ideas surface on their own merits. Together, we can create more value in our approach to investing through accepting the norms of science and polite discourse rather than just relying on the authority of the field manual. If this idea is not worthwhile, another may be.
Long term investing requires independent thinking, patience, the discipline to control our own fear and greed. This post is an exercise in independent thinking about the value added by network effects to the Gorilla Game; you must supply your own independent thinking about the value of my argument, and, of course, only you can supply your own patience, your own discipline, and your own due diligence when investing.
I hope this helps.
Don |
