Building Products Data Provider · Head-to-head
Construction Industry Statistics (Output, New Orders, Materials) vs USGS Mineral Commodity Summaries (cement, crushed stone, sand & gravel, gypsum, clays)
Which building products data provider data fits your job: Construction Industry Statistics, or USGS Mineral Commodity Summaries. API, files, or your warehouse. Daily, weekly, or hourly.
Construction Industry Statistics (Output, New Orders, Materials)
USGS Mineral Commodity Summaries (cement, crushed stone, sand & gravel, gypsum, clays)
Where the fields line up
No shared field names. These two answer different questions.
| Field | Construction Industry Statistics | USGS Mineral Commodity Summaries |
|---|---|---|
time_period | Year or month label keying the observation row. | not in this set |
public_new_housing_output | Output index/value for public-sector new housing work (ONS identifier MV36). | not in this set |
private_new_housing_output | Output index/value for private-sector new housing work (MV37). | not in this set |
infrastructure_new_work | Output index/value for infrastructure work (MV38). | not in this set |
private_industrial_commercial_new_work | Output indices for private industrial (MV3A) and private commercial (MV3B) new work. | not in this set |
all_new_work | Combined new-work output aggregate (MV3C). | not in this set |
repair_and_maintenance_output | R&M output family: public housing MV3D, private housing MV3E, total housing MV3F, non-housing MV3G, all R&M MV3H. | not in this set |
all_work_total | Total construction output index, seasonally adjusted, 2023=100 (MV3I). | not in this set |
implied_price_deflator | Deflator converting current-price values into volume measures. | not in this set |
MCS chapter | not in this set | documented |
Section | not in this set | documented |
Commodity | not in this set | documented |
Coverage, side by side
| Construction Industry Statistics | USGS Mineral Commodity Summaries | |
|---|---|---|
| Geographic | Great Britain — England, Wales and Scotland — with a public-versus-private split; no sub-national detail in the core workbook | United States salient statistics plus world mine production and reserves tables spanning roughly 100 countries per commodity, and US production broken out by state or producer |
| Temporal | Monthly series back to 1997 in the current workbook; annual Construction Statistics articles extend further; about 140 archived vintages retained per dataset so any past reading can be reproduced exactly | Five most recent years per statistic in each edition (2021–2025 in the 2026 edition); prior editions extend the series back to 1995 |
| Granularity | Monthly, split across ten work-type categories from public new housing (MV36) through all repair-and-maintenance to total all work (MV3I), seasonally adjusted and unadjusted | One row per commodity x statistic x country x year, rounded to two significant digits |
What each contains
They tie on 1 attribute. Pick by fit, not by loyalty.
| Construction Industry Statistics | USGS Mineral Commodity Summaries | |
|---|---|---|
| Publisher | UK Office for National Statistics | U.S. Geological Survey, National Minerals Information Center |
| Subject lens | The construction industry counted from inside: output volume indices and current-price values by work type, new orders, output price indices, implied deflator, revisions triangles and index weights | The raw materials those buildings are made of counted at the mine and plant: production or shipments, imports, exports, apparent consumption, year-end stocks, unit values, employment and net import reliance per commodity |
| Geography | Great Britain — England, Wales and Scotland — with a public-versus-private split; no sub-national detail in the core workbook | United States salient statistics plus world mine production and reserves tables spanning roughly 100 countries per commodity, and US production broken out by state or producer |
| Temporal reach | Monthly series back to 1997 in the current workbook; annual Construction Statistics articles extend further; about 140 archived vintages retained per dataset so any past reading can be reproduced exactly | Five most recent years per statistic in each edition (2021–2025 in the 2026 edition); prior editions extend the series back to 1995 |
| Granularity | Monthly, split across ten work-type categories from public new housing (MV36) through all repair-and-maintenance to total all work (MV3I), seasonally adjusted and unadjusted | One row per commodity x statistic x country x year, rounded to two significant digits |
| Cadence | Monthly releases; the latest verified release carried June 2026 data published 13 August 2026 | Annual editions, published each February with data finalised through the preceding calendar year |
| Scale | One ~540 KB workbook of 22 tables per release, plus companion datasets for the all-work summary, one-month and three-month revision triangles and index weights | ~8,900 rows across 89 commodity chapters in the 2026 release; the five building-materials chapters account for roughly 575 rows |
| Documented fields | 9 documented fields, verified | 12 documented fields, verified |
| Rubric rating | 9 out of 10 | 9 out of 10 |
| Best for | Timing and turning points — when British construction slowed, which work type led, what prices did | Physical scale and input economics — how many tonnes moved, at what unit value, from which countries |
Or take both in one feed
They stack as demand signal plus input ledger. Read the demand signal off the ONS record — which work types are expanding in Great Britain, at what volume, deflated how — then check whether the material base can carry it using the USGS chapters: tonnes produced, stocks on hand, import reliance, unit-value direction.
Join discipline matters more than luck here. There is no shared key — align on time, mapping ONS months to the calendar years the USGS reports, and accept that the geographies never intersect: Great Britain on one side, the United States and world tables on the other. Treat the pair as two panels in one argument, not one merged table. Mind the cadence gap — monthly against annual — and interpolate nothing silently.
Worked example: the ONS workbook shows infrastructure new work (MV38) running ahead of the all-work index; the USGS cement chapter shows domestic production flat with net import reliance rising. Demand accelerating while the binding material depends on trade — that is a conclusion neither dataset supports alone. Or take both in one feed — delivered together, on the cadence you set.
API, files, or your warehouse. Daily, weekly, or hourly.
Fair questions
Is the Construction Industry Statistics (Output, New Orders, Materials) better than the USGS Mineral Commodity Summaries (cement, crushed stone, sand & gravel, gypsum, clays)?
Neither is better; they measure different things and tie at 9 out of 10 on Datadory's rubric with verified field definitions. Choose by whether your question is about activity or materials.
Which dataset covers more geography?
It depends which axis you count. The ONS statistics cover Great Britain — England, Wales and Scotland — deeply, monthly, with a public-versus-private split but no sub-national breakdown in the core workbook. The USGS chapters anchor on United States salient statistics yet add world mine production and reserves tables spanning roughly 100 countries per commodity, plus US production by state or producer.
Which goes further back in time?
The ONS record: monthly series run back to 1997 in the current workbook, annual Construction Statistics articles extend earlier, and roughly 140 archived vintages per dataset let you reproduce any past reading exactly, revisions triangles included. The USGS 2026 edition carries the five most recent years per statistic, 2021 through 2025, though prior editions stretch the underlying series back to 1995.
Do the two datasets report the same kind of numbers?
No, and mixing them distorts models. The ONS publishes index numbers on a 2023=100 base plus values in pounds and percentage changes — relative measures designed for trend analysis. The USGS publishes physical tonnage, dollars per metric ton and shares such as net import reliance as a percentage of apparent consumption — absolute measures rounded to two significant digits. An index cannot be converted into tonnes without an external anchor.
Can I combine ONS construction statistics with USGS commodity data in one model?
Yes, as complementary panels rather than a merged table. Align on time — ONS months against USGS calendar years — and keep the geographies honest, since Great Britain and the United States never intersect in these records. A typical stack reads British construction demand off the ONS work-type splits, then tests material availability, stocks and import reliance off the USGS chapters. Sample both, pick by fit — or take both in one feed.