Cross-posted from Oliver’s Substack blog, EconPatterns

In the first four posts, I tried to map out an economy structured around the need to find out. This didn’t happen by accident, but is the result of spending a couple of decades in a realm where academic economic knowledge is held in little regard in no small part because its gatekeepers like to give off an air of having it already figured out, even if from the circumstances it’s clear that is rarely ever the case.

It doesn’t match my own opinion, but I perfectly understand when, say, the founders of a three-person startup bid adieu to their knowledge of academic economics when they learn that there is no such thing as a demand curve unless they put in the effort to assemble it piece by piece, transaction by transaction, price change by price change.

Most of them stop at this point and direct their attention to other, more pressing concerns, and I can’t blame them for it. The “need to find out” gets short shrift in most economics classes since economic instruction at universities generally starts from a vantage point where the groundwork has already been laid by wizards behind the curtain, and all that’s needed for mere mortals is to fine-tune the preconceived machinery.

That’s also a major reason why economists find employment in government, big banks, and, increasingly publicly listed tech firms, within large machineries, but are rarely ever in demand as one of the three founders of a recently minted startup with more enthusiasm than cash — or data.

This series tries to remedy that situation, and I could have subtitled it either “economics for startuppers” or “startup thinking for economists”, except the intended scope — and my intended audience — is a bit wider than that.

Use of decentralized knowledge in society

The underlying idea of “finding out” pursued in EconPatterns is ultimately derived from Adam Smith’s gains from specialization that drives specialization of labor, and that ultimately influenced another key contribution to economic lore, Friedrich Hayek’s Use of Knowledge in Society.

Hayek’s point was that there’s no point trying to steer the whole economy from a central vantage point because there is always someone somewhere closer to the ground, steeped in operational detail, who knows better, and can put that knowledge to better use than the central planner.

This idea that there is always local knowledge that is more detailed than the aggregated knowledge on the macro level, that there is knowledge that is nested, and that all participants have a mental map of the economy that is most detailed in their own vicinity and that degrades in detail, certainty, or precision, that resorts to using coarse-grained models, aggregates, or even stereotypes, the further one moves away from one’s own location, is deeply embedded in EconPatterns.

And this isn’t only true for the physical dimensions, it’s also true for the temporal dimension. Both the past and the future get hazy very quickly, and we resort to increasingly coarse-grained knowledge the further we go in each direction: Hayek’s “knowledge of the particular circumstances of time and place”.

There is an inevitable urge to remedy this shortcoming with the magic potion of “more transparency”. Every time we hear news about another supply chain pile-up, there is the inevitable stratum of pundits opining that this (the negative surprise, that is) could have been avoided if we just magically gave every participant a detailed map of the whole economy, or at least the whole chain of events — network really — leading to the participant’s problems stemming from the unexpected supply chain outage.

This is illusory of course to anyone attuned to the operational details of supply chain, not only because these pundits habitually underestimate by several orders of magnitude just how much operational raw data is out there, most of which is of no use to anyone but the data owner, but also because the countervailing demands of privacy and transparency (usually leading to the conundrum of each side demanding transparency from the other party but insisting on privacy for oneself) will inevitably lead to privacy winning out, except in those cases where the more powerful actor can compel less powerful actors to disclose their secrets.

Container ship

Supply chain and value chain integrity

Designing a mechanism that orchestrates the conflicting information needs of the participants in a value chain or its mapping into the physical realm, the supply chain, is still a holy grail in operations and in economic trade, but in no small part because the reasons why such a governance mechanism is hard to come by are still poorly understood.

Finding this holy grail, and mapping out the path to its discovery, is of course the goal of this series. A starting point is to arrive at a better understanding how knowledge disseminates thru an economy, where, when, and why it forms clusters (especially in the form of belief clusters), and how to interfere in that flow in a structured, goal-oriented way.

Just to offer a simple example, novices in the field of supply chain are often surprised to learn that the bill of lading, one of the crucial documents ensuring integrity of a product thruout its transit along ports, flights, shipments, loading and unloading, handovers and often rough handling, is still legally required to be in paper form, sent by courier from station to station.

A simple impulse is to blame an overbearing bureaucracy or an industry staunchly resistant to organizational change and technological progress, but an alternative and more plausible explanation is that paper solves a few integrity requirements that electronic communication still has a hard time to solve.

When handovers and handshakes are still the literal thing involving actual hands, if signatures are still done by hand in the presence of the counterparty, we are solving a few problems about identity that turn out to be quite tricky once we try to shift them online, into the digital domain where ascertaining that an individual is who they claim to be can be exceedingly tricky.

Turns out this simple example is repeated all over the place, in all kinds of domains and scenarios, with a number of idiosyncratic details added, but the underlying pattern still the same.

This is why I will come back to that example again and again. Because that is what EconPatterns is about.