Image for post
Image for post

Reinterpreting the networks

1.

The thread of which this post is a continuation began with an early look into what have since become the Big 5 (Apple, Amazon, Facebook, Google, Microsoft) at a time when their market capitalization leadership was still a novelty. In Networks 3.0: Defined by digital dimensions (2016), the argument was made that these aren’t technology companies as a defining measure — as was and commonly still is the accepted classification — but rather multi-dimensional network platforms with deep network effects, whose rich network qualities were the driving force behind their (at the time, new) leadership position. It was suggested that this would likely keep them at the top for a long while to come, and that the blueprint of their growth serves as a strategic model for optimal value formation in the post-digital economy.

The follow-up installment in the series, Interpreting the networks (2017), was a more general look into the different types of networks and their profiles, their similarities and differences, and some of the characteristics that drive or threaten growth differently for different types. For purposes of discussion, then and now, the term network is all-encompassing and includes a great deal more than what we have traditionally thought of in telecommunications, broadcast, or social interaction. In the new connectivity environment, the term is equally appropriate in discussions about digital marketplaces, exchanges, data collectives, product platforms, and many other types and systems characterized by a network topology. In the most current context, a sampling of last year’s newly minted and highest-profile public companies — Uber, Lyft, Pinterest, Cloudflare, Peloton, Crowdstrike, Zoom, Slack, and others — much more often than not are network manifestations, and this year so far seems a continuation of that theme (e.g., Snowflake and its cloud/SaaS contemporaries, or even Opendoor in the pipeline via SPAC).

With the present installment, the idea is to build from the referenced predecessors with a few notable events in 2020, that either highlight or raise questions about the evolution of the networks segment, which I believe is a legitimate vertical, standing with increasing relevance as an industry group — more so, I think, than many that are still traditionally accepted.

2.

What follows then are certain observations about the category. These may be worth returning to and watching for important updates as events unfold:

  • TikTok and its parallel in antitrust investigations: The split-up of network areas into subcomponents, for security, competition, or any number of reasons, is proving a more complex undertaking now, in the interconnected density of software network manifestations, than maybe was the case the last time a big network breakup happened, back when Ma Bell was transformed into its regionally separated infrastructure clusters.
  • Apple vs. Epic Games and others: The battle is between the giants, and the outcome may test the relative supremacy of each in the interdependent network layers that have formed. It is interesting that other social networks besides Fortnite have started to pile on (e.g., Facebook, Spotify) as though alliances are forming. There is a lot at stake when the natural order of network effects can only be controlled, reversed or at the very least distorted, via legislation.
  • The hardware upstarts: Though not so novel anymore, Tesla and Peloton are new acts still in the development of their network profile. We haven’t thought about hardware as a network object until Apple’s series of devices came along, and now some larger and more expensive variants — the in-home unit and the car — are on a similar path. In both cases, community and, as importantly, data gathering and analytics, build network effects and a competitive edge that will prove tough to overcome, even as competitors may add new features or reduce the price of the supporting product.
  • The emergence of DeFi: The idea of decentralized finance, which is a social network construct, might go against the tendency of social networks as they grow. These, over time, move gradually to centralization, even with the community’s or operator’s best intentions, as clusters grow and points of dominance take hold. And when money is involved— unlike, say the messaging of blurbs or sharing entertainment — there may be added impetus for filters, portals, and directors to emerge. Finance, when this occurs, is not decentralized, as it has never been in its long history (of networks). Should DeFi in its intended sense succeed, it will be an unprecedented revolution.

3.

Finally, to segue into an infinitely vaster network space than any of the isolated samples listed, a look at the financial markets network, which contains (or at least touches on) them all: This year, it seems, has given rise to large new clusters — traders and investors of the retail/amateur variety — clusters that have been dominant enough to cause strange swings to happen.

It is assumed by many that the trend will pass, that the aggressive style will fade with the next sustained correction, and that if bubbles may have formed as a result of the new trade activity, these will inevitably burst and clear the space of certain strategies without a rudder.

Perhaps.

But… what if, what if this is not a passing trend… what if, in this case, the supposed decoupling of a weak economy and explosive markets isn’t that at all, and the emergence of the independent trader with such powerful network force is, on the contrary, an outcome and a feature of the recent economic state: So much that is illiquid was devalued, permanently, on a dime…

If now a liquid market is discovered — with liquid assets and options, with fluid information, where positions can be easily diversified or hedged, where the research and the tools and analytics are all out there for the asking — such a discovery doesn’t seem as risky by comparison.

The retail investor, (a cohort that had reportedly missed out on the extended market run that kicked off with the Great Recession), was trained to think of markets and investment as a mystery beyond. Try the index, it was said, invest in ETFs or, better still, let a robot mechanism do it for you, it’s powerful AI! And yet, for all the talk of delta, gamma, vega, theta, not to mention alpha, all these things that can’t apparently be conquered in the absence of a math degree and the gatekeeper’s anointment, it turns out that the market and its fractal movements are an equalizer, where the edge of the sophisticates is mainly one of speed and volume, not necessarily of insight.

So, once again… what if, what if the emergent retail trade isn’t a financial bubble, as they say — or merely that — but something more important like a community reaction and a network tipping point? Like other tipping points in networks past, leading to big movements that aren’t necessarily ephemeral, this too would then necessitate a reinterpretation of the network whole.

Related reading:

Markets and the year(s) ahead: Post-stimulus edition (2020)

Finance notes from underground (2020)

If it’s not a bubble (2018)

The artificial services economy (2017)

The Age of Convergence (2014)

Written by

Investment, finance, strategy, execution in the networked tech economy. https://www.linkedin.com/in/danramsden

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store