Interpreting the networks

Distance sheds light on the immediate much like big trends shape individual positions. The opposite is also true.

The big markets, which are more profound, or at least more substantive, than any single voice can be from one day to the next, signal things to us from time to time. Or rather, from time to time we choose to listen. Of late the listening has been of special value to some, because the recent past has shaken everything with so much change — in industry, in the global economy, in society and our daily individual activities.

As commerce has been overturned at almost every level, as information barriers got shattered and knowledge has become a communal activity, as new monetary systems emerged, many can only wonder, looking back, at the path that brought us so quickly to a place so strange and monumental. Ten years ago — a trifle — these things were hardly even dreamed about outside the fringes. Now, predictions about robots, deep learning systems, quantum computing, and all manner of autonomous activity, are mainstream.

But these subjects aren’t futuristic, truth be told, these are realities already. A big event doesn’t need to be theatrical and full of flash, it doesn’t need to come with an announcement. The biggest in history, I think, have been interpreted with hindsight.

What follows then is a hindsight interpretation of the story that markets have told, noting that the markets, past and present, are always still speaking.

Phase transition

  • It happened more or less in concert with era-defining economic disturbances. The iPhone, launched in 2007, was followed by the general collapse of 2008, and the market’s attention for at least the first few years that followed was focused on the latter of the nearly simultaneous events. At least symbolically, the former was the much more permanent and consequential. Digital technology is, almost of a sudden and for almost all business forms, no longer a mere tool but close to if not the very core. This was initially unnoticed.
  • We’re at a point now where the technology label to describe certain companies or sectors is becoming outdated. Facebook (social media), Goldman Sachs (finance), Amazon (commerce, among others) and Uber (transportation) are all built on a technology core. If such a universal quality can still be used to designate a segment, then maybe the technology vendors can still be considered distinct. But that also is a murky designation as strategies evolve.

Particles and systems

  • Vendors of product are both drivers and victims of innovation. Because product is built to be disrupted, this is happening at an accelerating pace when software technology is universally accessible and, as famously noted, is eating the world.
  • The distinctive pressure on product vendors of all sorts — apparel, consumer staples, cars, others and including those whose products are services, such as law, accounting, and other forms of consultancy — is to continuously upgrade and update their offerings. This may have been the case since the beginning of a market economy, but the difference today is one of speed and proportion. Actual or threatened commoditization are impacting virtually every area, as price pressure, consolidation, and sector transformations ensue. After years of massive and unprecedented monetary accommodation, inflation still largely is subdued, while in many geographies and segments deflation is happening. Consumer technology is the most obvious.
  • On the other side from this, and borne of the same technological diffusion, are network systems. In the commercial sense, these largely used to signify telecommunications, the electric grid, and broadcast operations, but that has changed. Assets characterized by network topology with network effects are now manifest in online marketplaces, software platforms, social connectivity, information exchanges, and other such assortments, combinations and permutations on the digital experience as community.

Scarcity and abundance

  • Unlike products, which are abundant and disruptive, networks and network effects are extremely difficult to create, reproduce, or break. The interaction and codependence between nodes, the density and growth of clusters, the ties that link clusters to others, these and related elements of the network state are complex and rare at scale. When scale is achieved, there is built-in scarcity value and upside in the asset. Of the ten largest public market-caps in the world at the time of this writing, seven are such multi-dimensional networks: Apple, Alphabet, Microsoft, Amazon, Alibaba, Tencent, and Facebook.
  • While the scarcity value of networks stems from deep community structures described, the upside is enhanced by data. This is not only a byproduct of network offerings and the targeted user experience that is enabled, but of the intelligent advancement of the network itself. Artificial Intelligence is itself a network solution, combining rich data sets and processing these through dense neural architectures. This is a competitive advantage for those who have both (i.e., data and network qualities) in combination.
  • Network scarcity and product abundance: Whereas the introduction of new products can facilitate a network’s value, as it benefits from such new offerings as it evolves, products need the networks to survive. This may be a defining characteristic of the digitized economy. (Note: In the CVS (commodity vendor) pursuit of Aetna (network), the described reality is implied under the expressed headline.)

Distribution and hierarchy

  • In a networked information economy Power Law distributions emerge. This can be seen in the category dominance of leaders, followed by a long tail of smaller competitors behind (“winner-take-most” phenomenon), and it is sometimes also seen within the networks themselves as certain nodes and clusters gain in presence. Sometimes the loudest or most popular voices in the social web control discussion, certain apps in the app store rise up in the ranks, the top search results attract the most attention… these examples are all from the distributed multi-directional network types. The edited one-directional networks, like broadcast operations, are much more obviously hierarchical.
  • The tendency of networks towards hierarchy, by design or evolution, is a quality that in important ways resembles product distinctions previously described. In the extreme case, where a network’s flow is purely one-directional, this runs the disruption risks and profit pressures of a service offering, at the expense of much more valuable community. In a highly commoditized and competitive environment, networks seek to resist such outcomes.
  • Historically, the longest lasting networks in commerce have been multi-directional and distributed, where the operator’s purpose is to optimize the quality of distribution. Looking back past the current examples of digital search and marketplaces and others, examples include telecommunications systems that survived (but for regulatory intervention) since their first emergence and financial exchanges (that may have gotten into trouble from the concentrations that occurred). On the other hand, publishers of all forms (video, audio, print) have had rougher going.
  • This distinction of distributed versus hierarchical, and various points of nuance between the extremes, is shaping value formation within the network category in its current digitized form. Netflix, despite its global growth and dominant position, must compete with Hulu and HBO on the basis of its unique content. The competition is expensive, and the value of these properties, even the best of them, is nowhere near the value of the decentralized Big 5. There is no cord cutting, not really, only new digital cords.

Fluidity and options

  • A significant advantage of the open and distributed network over the hierarchical and centralized type is the former’s optionality. Defining this to mean currently unknown and possibly unknowable possibilities in direction, a fluid system is more likely to give rise to optionality than a rigid one. Although not entirely analogous, the standard Black-Scholes formula shows option value to increase with volatility. The principle is the same.
  • Because network effects are hard (maybe impossible) to manufacture, while new products can always be invented, it is far easier for a network to introduce new offerings than for offerings to develop network effects. When the latter thing takes place, almost miraculously, it’s called a tipping point and it is a landmark occasion.
  • A multi-directional network with network effects doesn’t depend on the recurrence of such monuments. Any new product offered on it is shaped by ideal lab conditions where customer acquisition costs are low and approach nil. The experimentation opportunity, thus, approaches theoretical infinity.

Tipping points and freedom

  • As any analysis written around this time must eventually arrive at Bitcoin, one way to read all of the foregoing is as a setting of the stage, a preface to the worldwide explosion in cryptocurrency.
  • If these are to be seen as a financial asset class in the traditional sense, then the value spike of the recent past resembles a bubble. If these, however, are more correctly interpreted as distributed digital networks that happen to be linked to trading mechanisms, then what shows as a bubble to the price chart reader may actually be a network tipping point.
  • Money and markets are themselves big network systems. They’ve been here a long time and grown even with repeated changes and disturbance. They want to be inclusive and widely accessible. Like all networks, in the last analysis, the markets want to be free.

Related reading:

Networks 3.0: defined by digital dimensions

If it’s not a bubble

Networks, products and their relativity

The artificial-services economy

Ten questions for the new economist

Markets and the year(s) ahead: Digital edition

Tools for a new trade

The Age of Convergence