Market Data

The Data Everyone Argues About Is the Data We Can Least Predict

There is an inverse relationship in our forecast record that nobody talks about: the data that dominates the headlines, tariffs, trade flows, fuel prices, is precisely the data we can least reliably forecast. The loudest numbers are the noisiest, and planning around them as if they were solid is a trap.

Grade the forecastability of manufacturing data by category and an uncomfortable pattern falls out: the numbers that generate the most argument are the ones we can least predict. As of Jul 2026, the noisiest category we track is Fuels and spot energy, with a median forecast error of 20.1%, followed by Trade flows at 10.4%. Compare that to the calmest category, Factory activity, at just 0.5%. The volatile, headline-grabbing series are an order of magnitude harder to forecast than the boring activity series nobody puts on television.

The loud-but-noisy categories

Look at where the error concentrates. Tariff-linked series carry a median error of 8.7%, and trade-flow series 10.4%, both far above the factory-activity series near 0.5%. This is not a knock on the data; it is the nature of it. Tariffs move on policy decisions, trade flows on front-loading and rerouting, fuels on geopolitics and weather, none of which follows the smooth momentum that makes a series forecastable. The very features that make these numbers newsworthy, their sensitivity to shocks, are the features that make them unpredictable.

Why this inversion matters for planning

The danger is that attention and predictability point in opposite directions. A planning process naturally spends its energy on the numbers in the news, tariffs, trade, fuel, and treats them as inputs it can pin down. But those are exactly the inputs that resist forecasting, so a plan built on confident assumptions about them is built on sand. Meanwhile the genuinely forecastable series, factory activity, hours, wages, get less attention precisely because they are calm. The rational allocation is the reverse of the instinctive one: anchor plans on the predictable series and treat the loud ones as wide scenario ranges, not point estimates.

The numbers that make the news are the ones we can least predict. Attention flows to volatility; reliability hides in the boring series nobody covers.

Plan around what holds still

The takeaway is not to ignore tariffs or fuel, they matter enormously to cost, but to stop pretending you can forecast them and to plan accordingly: hedge them, build wide bands around them, and revisit them often, rather than baking a single confident guess into a model. Reserve the confident assumptions for the series that have earned them with a track record of low error. A plan that knows which of its inputs are solid and which are guesses is far more robust than one that treats every number as equally knowable, especially when the loudest inputs are the least knowable of all.

The noisiest series in the archive

Over the five-year record Brent crude has stayed inside a recognizable band, running $59.93 in December 16, 2025 to $138.21 in April 7, 2026 and sitting today mid-range over the five-year archive at $88.90. The absence of a trend is itself the planning input: in a series this steady, a move that would be noise elsewhere is a real signal, because the base rate of movement is so low.

The forecast pages break down predictability by category, so you can see which inputs to trust and which to hedge. See the accuracy by category

Published 2026-08-06.