Read the new guide – Advancing Workforce Equity: A Guide for Stakeholders
Advancing Workforce Equity: A Guide for Stakeholders
Phase 3: Data Exploration
The overarching objective of this work is to use data to develop equitable strategies to address workforce challenges. Collecting and analyzing the data is the heart of this work. This phase may also be the most time-consuming.
In this process, you are using data to examine workforce trends and inequities that limit employment for targeted groups, primarily Black and brown people, who are seeking entry into the workforce or access to living-wage careers.
Advancing Workforce Equity Data Webinar Series
Advancing Workforce Equity: Accessing and Exploring Relevant Data from the National Equity Atlas
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Here we provide some data resources for collecting key labor market data. This list is not exhaustive, and your data partner may have access to additional resources or make other recommendations, depending on which indicators you are tracking.
Pros: Includes state, metro area, and county employment, establishments, and payroll numbers by industry. It produces quarterly data with a six- to nine-month lag for preliminary data and a one-year lag for final data.
Cons: This source only includes payroll employment. It does not include data for occupations, only industries. Much of the local data is not disclosed due to privacy restrictions. The tools are difficult to work with, especially for customized multi-industry and multi-area searches.
Pros: Includes state, metro, and non-metro region employment and wage numbers by occupation rather than by industry, although it also shows how occupations are distributed across industries and vice versa. You can also find 10-year job projections for each It generally has an 18-month lag time.
Cons: Because it is a survey, there is a possibility for error. No county-level data, which makes analysis of local and custom geographic areas difficult or impossible. The interface is difficult and inefficient to navigate.
Pros: Comprehensive data for hundreds of demographic, social, and labor force variables, including labor force status, industry/occupation, wage, and journey to work.
Cons: Census 2000 is out of date for real-time, corporate decision-making. The American Community Survey is susceptible to survey error, does not include as much data as the centennial census, and excludes smaller counties. Respondents “self-classify” their industry and occupation, which is translated to standard codes by Census workers, introducing a good deal of error.
Pros: Provides payroll employment statistics by industry for local areas, including total jobs, new jobs, separations, turnover, and other variables by worker age and sex. It represents a step forward in government data integration, detail, and approximately one-year data lag.
Cons: Eight states don’t provide data, and a few have a longer lag time. Geographic and industry aggregation, no occupation data. The user interface is somewhat clumsy.
Pros: This unique dataset uses tax returns to show establishments and earnings by industry for self-employed workers and proprietors without paid employees, who do not appear in QCEW and OES. It is available for states, metros, and counties with mid-level industry
Cons: Much detailed data is undisclosed, there is a 2-3-year time lag, and there can be errors because people misclassify their industry.
Pros: This county-level source (also available for metros and states) specializes in comprehensive, high-level totals for personal income, population, employment by industry sector, and levels of total proprietor payroll employment. Unlike QCEW, it includes all types of workers—covered and non-covered.
Cons: Only provides totals for very broad industry. Data time lag of about one year for metro areas and two years for counties.
Pros: Provides profiles of knowledge, skills, abilities, work interests, work activities, workplace tools, and other characteristics for hundreds of occupations. When connected to local labor market data, it can provide quantifiable estimates of available human capital.
Cons: Requires a good deal of analysis to make the raw data useful for constructing total labor pool estimates (jobs in all compatible occupations), especially since it uses a slightly different occupational classification system than the occupational labor market.