Measurement

What is not measured is not managed, and quite often not even believed.

Ed. 1

HealthProblem 0005

Resistance is as much a data problem as a drug problem. Surveillance depends on cultures, and much of the world's prescribing happens where there is no microbiology laboratory within reach, so the clinician makes a reasonable guess, and what happens next is rarely recorded anywhere that would improve the next one. The map of what still works is drawn from the minority of cases that reach a lab.

Who lives with itPrescribers in primary and rural care · national AMR programmes · hospital pharmacy and stewardship teams

Why nowThe WHO's 2025 global surveillance report draws on more than 23 million confirmed cases reported by 104 countries across 93 combinations of infection type, pathogen and antibiotic: the most complete picture yet assembled, and still one built from where testing exists rather than where prescribing happens.

Why it matters · the JudgeThe feedback loop that would slow resistance is broken at its cheapest point: capture. Anything that makes empirical prescribing legible without requiring a laboratory improves the map for everyone, and most of what is sold here is tests rather than information.

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Ed. 1

EducationProblem 0011

Most institutions are writing or planning a policy about AI; few have changed what they actually measure. The essay, the problem set and the report were proxies for thinking that worked only while producing them was expensive. That assumption is gone. Detection tools are unreliable enough to risk accusing the wrong students, and much of what is graded no longer shows reliably what a student understands.

Who lives with itTeachers and lecturers redesigning assessment alone · students wrongly suspected · institutions whose credentials depend on the answer

Why nowA UNESCO survey found 19% of higher education institutions had formal AI guidance with a further 42% developing it, while more than half reported uncertainty about how to apply AI pedagogically and one in four had already encountered ethical problems including authorship disputes.

Why it matters · the JudgeThe question has moved from catching misuse to evidencing learning, and nothing is built for the new question. Making a student's reasoning visible, cheaply and without treating them as a suspect, solves what detection never could.

Inspired by reporting from UNESCO

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Ed. 1

FinanceProblem 0018

Insurers are withdrawing from places where people still live and still owe money. The mortgage requires cover; the cover depends on a risk model that has stopped holding. Homeowners find out at renewal, with weeks to replace a policy that may not exist at any price, and often no accepted way to show an insurer the work they have done to make the building safer, because that evidence is rarely collected in a form an underwriter will accept.

Who lives with itHomeowners in high-risk areas · mortgage lenders and brokers · local authorities watching values move

Why nowIn January 2025 the US Treasury's Federal Insurance Office, drawing on over 330 insurers and 246 million policies, found non-renewal rates in the highest climate-risk ZIP codes running about 80% above the lowest, with premiums averaging 82% higher.

Why it matters · the JudgeNobody owns the gap between the loan and the policy, and the one thing that would narrow it (verified, property-level evidence of risk reduction) is what neither side routinely collects.

Inspired by reporting from U.S. Department of the Treasury

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Ed. 1

FoodProblem 0015

Loss happens at the handovers: field to packer, packer to distributor, distributor to shelf. Every party measures only its own side of each one. So each set of numbers looks defensible while the total is enormous, and the interventions that would work are precisely the ones nobody can see, because they sit between two businesses rather than inside one.

Who lives with itGrowers and packers · distributors and independent retailers · redistribution charities working the same corridors

Why nowFAO estimates that 13.3% of the world's food was lost in 2023 after harvest and before retail, on farms and in transport, storage, wholesale and processing, up slightly from 13.0% in 2015 when global monitoring began.

Why it matters · the JudgeMeasurement at the handover is the wedge, and it is cheap: the produce is already photographed, weighed and scanned on both sides of every transfer. Nobody is joining those records, because each side owns only its own.

Inspired by reporting from Food and Agriculture Organization of the United Nations

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Ed. 1

EnergyProblem 0003

Training runs, batch inference and analytics are scheduled around deadlines and cluster availability, almost never around what electricity costs or emits at that hour. Much of this work is genuinely movable, a few hours either way or a different region entirely, but the information needed to move it lives in a different system from the scheduler, and in most organisations nothing joins them. So flexible load behaves like inflexible load.

Who lives with itPlatform and infrastructure teams · sustainability leads with compute in their inventory · grid operators courting flexible demand

Why nowThe IEA's April 2025 Energy and AI report puts data centre electricity use at around 415 TWh in 2024, about 1.5% of global consumption, and projects roughly a doubling by 2030 with accelerated servers accounting for almost half the increase: a load growing fast and, unusually for industrial demand, substantially time- and place-shiftable.

Why it matters · the JudgeA large and rapidly growing load is being treated as though it had no flexibility, when a meaningful share of it does. Making compute schedulable against grid signals is a software problem sitting between two industries that do not yet share a vocabulary.

Inspired by reporting from International Energy Agency

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Ed. 1

LogisticsProblem 0014

Recycling a device profitably depends on knowing what it contains before you open it, and that information was never attached to it. So the pile is handled as undifferentiated waste: shredded for the few metals that survive the process, or stored, or exported. The materials the world is anxious about securing are sitting in it, and a large part of the reason they are not recovered is identification rather than chemistry.

Who lives with itRecyclers and refurbishers · manufacturers facing take-back obligations · anyone sourcing critical minerals

Why nowThe ITU and UNITAR Global E-waste Monitor 2024 recorded 62 million tonnes generated in 2022 with 22.3% formally collected and recycled, around $62 billion of recoverable materials embedded in it, and a projection to 82 million tonnes by 2030 as recycling falls further behind.

Why it matters · the JudgeA known, growing, geographically concentrated pile of valuable material where the binding constraint is knowing what is in each unit. That is a data and vision problem attached to an existing physical industry, a good place for a small team to start.

Inspired by reporting from ITU & UNITAR

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Ed. 1

CitiesProblem 0016

Utilities meter at the treatment works and at the customer's tap, and only coarsely in between: a district meter can say how much went missing across a whole area, not where. So loss is known as a percentage far more often than as a place, the response is scheduled rather than targeted (mains replaced by age, not by evidence), and too many leaks are found only when the road subsides or somebody rings.

Who lives with itWater utilities and municipal engineers · households in intermittent-supply cities · regulators setting loss targets

Why nowA widely cited World Bank estimate, published in 2018, puts the water utilities produce but never bill, through physical leaks and commercial losses, at around 126 billion cubic metres a year, nearly $40 billion in lost value.

Why it matters · the JudgeThe cheapest new water available anywhere is the water already treated, already paid for, and lost before it arrives. Turning a percentage into a location is most of the job, and it is an instrumentation and inference problem rather than a civil engineering one.

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Ed. 1

LogisticsProblem 0024

A small importer commits to an order months before it lands and discovers the real cost on arrival: duties applied differently than expected, a classification disputed, fees that were never quoted. Large firms keep trade teams and brokers for exactly this. A five-person business has a spreadsheet and a guess, and prices a whole catalogue on that guess.

Who lives with itSmall e-commerce brands and independent retailers · the freight forwarders serving them · their customers, eventually

Why nowTariff regimes have become materially more changeable, and the tooling that absorbs that volatility is still mostly built and priced for larger firms.

Why it matters · the JudgeVolatility is now the normal condition rather than the exception, and the answer is still priced for companies that do not need it most. A landed-cost figure a small owner can actually trust is a product, not a feature.

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8 problems. Pick one.Bring a problem

Measurement

Blind antibiotic prescribing Doctors prescribe antibiotics without knowing what works locally

Unverifiable student work Teachers can't tell who learned and who prompted

Withdrawn home insurance Homeowners lose insurance their mortgage still requires

Unmeasured supply loss Growers and buyers can't see the food lost between them

Unshifted compute load Data centres can't shift work to cheaper, cleaner hours

Unidentified e-waste Recyclers can't tell what's inside before they shred it

Unlocated water loss Utilities can't find leaks in pipes they never metered

Unpredictable landed cost Small importers can't predict what a shipment will cost