Test whether a market can support the people your plan requires

A role-specific workforce process

1. Translate jobs into occupationsList the actual roles, skills, seniority, schedule, credentials, and expected headcount. Industry employment alone does not reveal the occupations available.
2. Measure depth and concentrationCompare employment levels, location quotients or shares, and multi-year change. A large metro may have many workers but weak specialization.
3. Examine wage distributionsUse percentiles where available, not only means. Clarify whether figures are hourly or annual and whether they exclude benefits, bonuses, or self-employment.
4. Add labor-market contextReview unemployment, participation, industry growth, and employers competing for similar roles. A large employed pool is not the same thing as an available pool.
5. Test affordability and accessCompare compensation with housing and price context, then consider where workers live and how they reach the proposed workplace.
6. Validate with current recruiting evidencePublic data lags. Confirm with recent job postings, recruiter input, time-to-fill, applicant flow, and actual compensation experience.

Worked-example framing: a support operation

Suppose a company is comparing metros for a customer-support operation. The analysis would begin with the occupational mix it expects - frontline support, supervisors, workforce planning, quality, and technical specialists - rather than using all office workers as the talent pool.

Occupational Employment and Wage Statistics can provide employment and wage estimates by occupation for supported geographies. QCEW can show which local industries are growing and may compete for workers. LAUS provides broader labor-force and unemployment context. ACS commuting, educational attainment, language, and housing measures can add resident-based context, provided the analysis keeps workplace and residence concepts distinct.

A decision-ready comparison would show headcount depth, wage bands, competing industries, growth, housing pressure, and source dates. It would also quantify the hiring assumption: what share of the relevant occupational pool the planned headcount represents and how that ratio changes under turnover scenarios.

Representative primary sources

• Occupations and wagesBLS Occupational Employment and Wage Statistics for employment and wage estimates by occupation.
• Industry employmentBLS Quarterly Census of Employment and Wages for establishment, employment, and wage context by industry.
• Labor forceBLS Local Area Unemployment Statistics for resident labor force, employment, and unemployment.
• Resident workforceCensus ACS tables for occupation, industry, education, commuting, income, and housing estimates.
• Employment projectionsBLS Employment Projections for national occupational and industry outlook context.
• Regional costsBEA Regional Price Parities for broad differences in regional price levels.
• Education pipelineNCES IPEDS and College Scorecard for institutions, credentials, fields of study, and selected outcomes. Completions are not applicants, immediate job seekers, or proof graduates remain locally, and outcome cohorts can lag.
• Healthcare workforceHRSA Area Health Resources Files for county-level provider-supply context in healthcare workforce questions. Aggregate counts can combine source years and do not show availability for a specific employer or position.

What the numbers do not promise

Occupational categories may be broader than an employer’s role. Wage estimates can lag a fast-moving market and generally do not represent a complete compensation package. Unemployment is not a count of qualified applicants. Remote and hybrid work can alter the relevant geography, and employer reputation, schedule, benefits, immigration rules, credentials, and recruiting execution can dominate public-market averages.