The Situation

Standard Bots needed to relocate from their current location and required a precise understanding of where their target workforce — specialized manufacturing and assembly technicians — actually lived within Metro New York before committing to a new address. In a market as geographically complex as the New York metro, the difference between Kings County, Queens, Nassau, and Suffolk represents dramatically different labor pools, wage profiles, and commute dynamics.

Choosing a new location based on lease economics without understanding the labor geography risked placing the facility in a submarket where their target workers simply didn't live — a hiring problem disguised as a real estate decision.

The Approach

We identified the precise occupational classifications for Standard Bots' target labor — both precise and broader categories of electrical and electronic assemblers, engine assemblers, timing device assemblers, miscellaneous assemblers, cutting and press machine operators, inspectors and testers, and semiconductor processing technicians. We then mapped the residential concentration of that labor at the block-group (neighborhood) level across the full metro area.

The analysis produced a county-level summary of target labor resident workers, current employment, five-year projected employment change, and wage distribution (25th percentile, average, and 75th percentile hourly earnings) for Kings, Queens, Nassau, and Suffolk counties. Heat maps visualized where the highest concentrations of target workers lived, providing a clear spatial framework for evaluating specific building options within those geographies.

The question isn't "is there labor in New York?" — of course there is. The question is which specific neighborhoods have the highest concentration of the exact workers you need. Those aren't the same answer.

Results

County-level labor summary delivered across Kings, Queens, Nassau, and Suffolk counties
Block-group-level heat maps produced showing precise residential concentration of target SOC workers
Wage benchmarking by percentile delivered for all target occupational classifications
Client narrowed location search to a small number of high-confidence submarkets based on labor distribution data

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