Defend every number you publish.

Quarterly industry and occupation data for every US county, past, present and projected, with each value marked by where it came from. So you can stand behind the numbers you share.

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    Full depth, quarterly. Lands you in the explorer with data working.

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    Any one county, free for 7 days

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Which of these did the government publish?

You cannot tell from the numbers, and neither can anyone you hand them to. QCEW withholds a value whenever publishing it could identify an employer, and DTG estimates each value QCEW withholds. DTG then marks which values were estimated, and scores how much stock to put in each. Watch the same table answer the question.

How estimated values are built →
Manufacturing subsector2024 employmentSource · score
Chemical manufacturing1,234Published
Food manufacturing1,012Estimated · 0.92
Fabricated metal products876Published
Paper manufacturing654Estimated · 0.61
Wood products432Published
Machinery321Estimated · 0.34
Transportation equipment298Published
Plastics and rubber187Estimated · 0.78

PublishedPublished by the federal sourceEstimated · 0.60Estimated by DTG, filled to its score

Illustrative figures for an example county, not data. Manufacturing subsectors at the 3-digit level, marked the way every data page and the app mark them.

The question behind the number.

You put an employment figure in front of a board, a council, a grant reviewer, or a site selector. Someone asks where it came from. You should be able to answer that without calling your vendor.

Read the methodology →

Four observations a year, not one.

An annual average is four quarters folded into a single number, and folding is where a Q1 closure disappears.

Annual average

20212022202320242025

An illustrative series: a soft decline over four years.

Quarterly
−940

20212022202320242025

The same illustrative series, quarterly. One quarter, 940 jobs, and a date attached to it.

Know which numbers to lead with.

Published totals, state figures and parent industry sums box in every withheld value. Sometimes that box is tight enough that the figure can be almost nothing else. Sometimes it is not. The score tells you which you are holding. Every estimate in this field has this property, whether or not anyone reports it.

How the score is calculated →
Food manufacturing1,0120.92Almost no room to be anything else.
Paper manufacturing6540.61Boxed in, with some room left.
Machinery3210.34A wide range. Use it accordingly.

Illustrative figures. The score measures variation already present in the published record. It does not add any.

See the data before you decide anything.

Two ways inspect the data, and neither one asks for a card. Trial a county for 7 days anytime from inside the app.

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