Open planning is a way of running an economy in which goals and limits are set publicly and accountably, allocation inside those limits is left to the market, and delivery is confirmed by measurement rather than by the contractor’s own report. The model does not choose between plan and market: it separates them into different loops and asks each to answer for what it is good at.
1. The problem this grew out of
Why neither a pure plan nor a pure market settles the question
The “plan versus market” argument rests on the assumption that one has to be chosen. The twentieth century says otherwise: both regimes fail, but in different places, and their failures are not symmetrical — which means replacing one wholesale with the other is pointless.
Where administrative allocation fails
The centre receives no signal of scarcity. Without a price that reflects shortage, errors across the product range accumulate and surface after the fact — as a queue in a shop or a warehouse of unsellable goods. The mechanics of that failure are set out in the section on the Soviet Gosplan.
What the market does not do on its own
The market counts what carries a price and ignores what does not: a network whose last kilometre is not worth laying; prevention that pays back in twenty years; the connectivity of small settlements. These items are not “undervalued” — they sit outside the loop it calculates in.
Hence the working hypothesis: planning belongs where a decision is long, capital-heavy and networked; the market belongs where decisions are many, small and reversible. The question is not which regime is right, but where the line runs and who has the standing to draw it.
2. Three loops, and the rule that keeps them apart
Goal-setting, delivery and verification must not meet in the same hands
The model is assembled not from technologies but from three separate loops. Technology enters only where one of them has to be made faster or cheaper — and nowhere else.
The goal loop
What counts as a result, which limits are untouchable, what the priorities are for the period — decided publicly, one person one vote, not by weight of capital or tokens. There is no automation here: voting by asset weight turns the goal loop into a shareholders’ meeting.
The delivery loop
Inside the limits that have been set, market mechanisms do the work: auctions for quotas, tenders for contracts, payment against the result achieved. The centre neither appoints the contractor nor works out its costs for it — it publishes the frame and accepts the outcome.
The verification loop
Fact is confirmed by measurement — telemetry, registries, independent audit. Verifiability here is not “transparency in general” but a specific property: an outsider can redo the calculation and arrive at the same answer.
The rule that holds the structure together: whoever sets the goals does not deliver, and whoever delivers does not verify. As soon as two loops meet in the same hands the model degenerates — goals plus delivery give administrative allocation, delivery plus verification give self-reporting.
3. Where the model applies, and where it deliberately does not
A measure can be gamed, so the ground it covers has to be limited in advance
Any measure that becomes a target stops being a good measure. “Gross output at any cost” does not disappear when the paperwork goes digital — it mutates into “KPIs at any cost”. The only defence that works is to keep metrics out of the places where value cannot be measured.
Where quantitative mechanisms belong
Standardised subjects with a natural unit of result: energy and capacity, logistics and warehousing, routine procurement, road works, telecoms. Here, substituting the indicator for the goal shows up under inspection.
Where they are not used
Care, education, medicine, culture, science. Value here is created in the interaction and does not reduce to a unit of account: a “treated case” or a “graduate” is not the result but a stand-in for it. Optimising the stand-in does not improve the result; it hollows out the work.
This boundary is not a technical limit that the next generation of models will lift. It is a design decision, and it will have to be defended continuously: pressure to widen the reach of metrics arises on its own, because measurable things are easier to manage.
4. What already works, and what is still a hypothesis
The split is compulsory: without it the model becomes a promise
The parts of this structure exist at very different stages of readiness. Mixing what runs with what is being designed is the commonest mistake in writing about digital governance, and the most expensive one for its credibility.
Running in production
Open procurement data. The Open Contracting standard and the national systems built on it have shown that publishing contracts in machine-readable form is a solvable engineering task rather than a declaration.
Participatory budgeting. The practice has run since 1989 in Porto Alegre and has since been reproduced by hundreds of cities: part of the budget is allocated by a direct vote of residents.
Electronic transferable records. The UNCITRAL Model Law on Electronic Transferable Records entered Singapore law in 2021; in 2026 four TradeTrust-compatible platforms were approved by the IG P&I mutual insurance clubs — an electronic bill of lading now carries the same legal standing as paper in insured maritime trade.
Still a hypothesis
End-to-end on-chain accounting at national scale. Throughput and the cost of confirmation are an unsolved problem, not a matter of time and money.
The DAO as a goal-setting mechanism. Token-weighted voting reproduces a shareholders’ meeting rather than a civic loop, and no durable answer to that has been put forward.
We do not claim the model is ready for national deployment. We claim it is testable in parts — and that each part is more honestly tried on its own, where a mistake does not cost too much.
The weaknesses and risks in full5. Where this frame is applied in the study
The other sections are not separate topics but tests of the model against particular subjects
SELO 2.0 — what to do with rural infrastructure whose buildings and grid connection survive but whose function does not.
Connectivity 2.0 — transport, logistics and passenger flows: a subject where plan and market have to work together.
Blockchain marketplaces — the mechanics of the delivery loop: quotas, work orders, payment against the result achieved.
Biophilic cities — an example of a goal the market will not formulate on its own, because it carries no price.
In conclusion
Open planning promises no abundance and does not treat technology as a source of justice. It proposes one thing: separate goal-setting, delivery and verification into different loops, limit the reach of metrics, and make the result something an outsider can recompute. Everything else in the model follows from that choice.
Take away the blockchain, the AI and the telemetry, and the structure remains: slower and dearer, but unchanged in its logic. Take away the democratic goal loop and what remains is technocracy, which no technology will fix.